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courseonline1 · 4 years ago

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30+ FREE Data Science Short Courses from FutureLearn

FutureLearn is an online learning platform offering a wide range of courses similar to various other popular MOOC suppliers. The course curricula usually consist of reading material and video clips. The tests and assignments are made available at the end of every unit. The syllabuses are provided in a simple form and are easy to navigate, as well as the general individual experience of FutureLearn’s courses is some of the best I have actually seen. We have brought you FutureLearn Free Courses in Data Science, but first let’s see are FutureLearn courses worth it?

Are FutureLearn Programs Accredited?

Yes, FutureLearn programs are accredited, authentic, and are well-acknowledged for their credibility, as they provide certificates through universities. Also, Online courses hosted on FutureLearn are from universities and not from private teachers.

Are FutureLearn’s Courses Free?

The majority of FutureLearn’s online training courses can be considered totally free, besides paid courses, microcredential programs, and online degrees. Freemium students can have complete access to the course and course material for 14 days additionally. However, FutureLearn’s free courses don’t provide access to tests or even certificates.

How to join a FutureLearn free course?

When you click on any of the links listed below, you’ll be taken to the program description page. If a program is open to signing up then you’ll see a ‘Pink button’ near the top of the program summary page:

To enroll into FutureLearn Free courses, you will have to click on “Join course for free”. Then you will be taken to the bottom of the web page having a list of options:

Clicking on Join free takes you to a web page with the information you need to know before you start learning. To begin with the FutureLearn Free course, you can click on “Go to course” or wait till course starts as in my case over here. To know what comes next, you can take a look at this article from FutureLearn: What to expect when your course starts.

Are FutureLearn certificates recognized?

Yes, as discussed before that the Future Learn programs are accredited and are recognized by well-known organizations. Moreover, micro-credential certificates are of much more value than Short course certificates.

Various types of training courses are provided by Future learn such as:

Brief Courses

Specialist Tracks

Microcredentials

Online Degrees

Here we have brought you free short courses from Future learn from the field of Data Science. These take anything from two to 7 weeks normally, and with a dedication of a few hours per week. However, you are free to take more than one short FutureLearn course simultaneously, just you should have adequate time readily available.

List of FutureLearn Free Data Science Courses

Organized by Top Universities & Organizations

Universities:

1. Birkbeck, University of London 2. Coventry University 3. Edinburgh Napier University 4. Eindhoven University of Technology 5. Griffith University 6. Johns Hopkins University 7. National Chiao Tung University 8. National Tsing Hua University (NTHU) 9. Taipei Medical University

10. The University of Law 11. The University of Manchester 12. The University of Sheffield 13. The University of Waikato 14. University of Dundee 15. University of Leeds 16. University of Michigan 17. University of Reading 18. University of Strathclyde

Oranizations:

1. Cloud Swifty, Microsoft 2. Digital Health & Care Innovation Centre 3. Institute of Coding 4. Microsoft 5. National Centre for Computing Education 6. Raspberry Pi Foundation 7. Swiss Education Group 8. The Data Lab 9. UAL Creative Computing Institute 10. UrbanTide

Subject Categories

Artificial Intelligence

Artificial Intelligence – Big Data

Artificial Intelligence – Bioinformatics

Artificial Intelligence – Business & Management

Artificial Intelligence – Healthcare & Medicine

Artificial Intelligence – IT & Computer Science

Artificial Intelligence – Law

Big Data – Data Analytics

Business & Management

Data Analytics

Data Mining

Databases

Healthcare & Medicine

IT & Computer Science

Python Programming

Recommended Free Courses

Note: Throughout the list, every course has been provided with the information as below:

Enrollments

Duration

Organized by

> Artificial Intelligence

1. Artificial Intelligence: Distinguishing Between Fact and Fiction

6300+

2 weeks

Coventry University, Institute of Coding

How well do you understand artificial intelligence (AI)? Explore how to separate the reality from the hype on this course.2. Get ready for a Masters in Data Science and AI

4400+

2 weeks

Coventry University

Identify whether you’re ready for Master’s study, improve your data science skills, and get to grips with the basics of Python.3. Introduction to Creative AI

17800+

2 weeks

UAL Creative Computing Institute

Explore the ways AI is changing the creative industries, and how you can develop your own career in creative AI.

> Artificial Intelligence – Big Data

4. AI and Big Data in Global Health Improvement

4300+

4 weeks

Taipei Medical University

Discover how data sharing in the healthcare sector has the potential to improve medical outcomes all over the world.

> Artificial Intelligence – Bioinformatics

5. Artificial Intelligence in Bioinformatics

800+

3 weeks

Taipei Medical University

Discover the future of bioinformatics and learn how AI models of bioinformatics data help us to understand biological processes.

> Artificial Intelligence – Business & Management

6. Artificial Intelligence (AI) in Hospitality: Challenges and Business Opportunities

–

4 weeks

Swiss Education Group

Explore how AI has the potential to revolutionise the international hospitality industry and the challenges of digitalisation.

> Artificial Intelligence – Healthcare & Medicine

7. AI for Healthcare: Equipping the Workforce for Digital Transformation

8000+

5 weeks

The University of Manchester

Learn how artificial intelligence is transforming healthcare and how it can be used to support change in the healthcare workforce.8. Artificial Intelligence for Healthcare: Opportunities and Challenges

7100+

4 weeks

Taipei Medical University

The use of artificial intelligence (AI) in healthcare is increasing, explore the challenges and opportunities AI presents.

> Artificial Intelligence – IT & Computer Science

9. Applications of AI Technology

3600+

4 weeks

Taipei Medical University

Learn how AI technology is influencing four key areas: intelligent systems, medtech, deep learning, and sustainable fishing

> Artificial Intelligence – Law

10. AI for Legal Professionals (II): Tools for Lawyers

900+

4 weeks

National Chiao Tung University

Discover programming with Python, and the AI tools that lawyers, legal educators, and regulators can use to deliver services.11. The Laws of Digital Data, Content and Artificial Intelligence (AI)

3400+

3 weeks

The University of Law

Discover the key legal concepts underpinning cyberspace and build legal expertise about digital technology.

> Big Data – Data Analytics

12. Big Data Analytics: Opportunities, Challenges, and the Future

39700+

2 weeks

Griffith University

We produce more data than ever before. Find out how ‘big data analytics’ can help you make use of it.

> Business & Management

13. Business Analytics Using Forecasting

16500+

6 weeks

National Tsing Hua University (NTHU)

Discover how business can harness the power of big data to make better predictive analysis.14. Collecting and Using Data for Disease Control and Global Health Decision-Making

700+

3 weeks

Johns Hopkins University

Address the application of surveillance systems in a wide variety of epidemiological situations and make data-informed decisions.15. Data Science Ethics

1100+

4 weeks

University of Michigan

Explore the ethics of big data collection and sharing, and consider the importance of data privacy in our society today.16. Harnessing the Power Of Data: Introduction to Data-Driven Decision-Making

1400+

2 weeks

Coventry University

Have the chance to learn how to assess and critique data sources and information to help you make informed business decisions.17. Introduction to Data for Business Leaders

4600+

4 weeks

The Data Lab

A leadership course that goes beyond the hype surrounding data by focusing on the practicalities of achieving business outcomes.18. Making Sense of Data in the Media

14200+

3 weeks

The University of Sheffield

Discover how to read and understand data in the media, and how to spot fake news based on misleading statistics.19. Understanding Data in the Tourism Industry

3100+

5 weeks

Edinburgh Napier University

How can you benefit from using data in your tourism business? Learn the opportunities of tourism data with this online course.

> Data Analytics

20. Big Data and the Environment

14000+

3 weeks

University of Reading

From sources such as satellites, sensors and social media, how can environmental data analytics benefit business and research?

> Data Mining

21. Advanced Data Mining with Weka

13800+

5 weeks

The University of Waikato

Learn how to use popular packages that extend Weka’s functionality and areas of application. Use them to mine your own data!22. Data Mining with Weka

34900+

5 weeks

The University of Waikato

Discover practical data mining and learn to mine your own data using the popular Weka workbench.23. Introduction to Process Mining with ProM

18600+

4 weeks

Eindhoven University of Technology

Learn how to use the free, open source process mining framework (ProM) to analyse, visualise, and improve processes based on data.24. More Data Mining with Weka

12000+

5 weeks

The University of Waikato

Enhance your skills in practical data mining as you get to grips with using large data sets and advanced data mining techniques.

> Databases

25. Introduction to Databases and SQL

14400+

3 weeks

Raspberry Pi Foundation, National Centre for Computing Education

Discover how databases work and how to use SQL in this introductory course. Supported by Google.

> Healthcare & Medicine

26. Process Mining in Healthcare

4100+

4 weeks

Eindhoven University of Technology

Learn how process mining can be used to turn healthcare data into valuable insights to improve patient care while reducing costs.27. The Power of Data in Health and Social Care

5500+

3 weeks

University of Strathclyde, The Data Lab, UrbanTide, Digital Health & Care Innovation Centre

Discover the power of data for individuals and organisations working in health and social care.

> IT & Computer Science

28. Applied Data Science

1900+

2 weeks

Coventry University, Institute of Coding Birkbeck, University of London

Develop your data science and analytics skills and improve your understanding of using data in the workplace.29. Apply Creative Machine Learning

3100+

4 weeks

UAL Creative Computing Institute

Discover the creative side of machine learning with this free course using hands-on examples.30. Data Science in the Games Industry

5500+

4 weeks

University of Dundee

Data Science in the Games Industry31. MedTech: AI and Medical Robots

6500+

2 weeks

University of Leeds

Explore human robot interaction and enter the fascinating world of robotics and artificial intelligence in healthcare.

32. Microsoft Future Ready: Azure Cloud Fundamentals

1300+

3 weeks

Cloud Swifty, Microsoft

This course will provide foundational level knowledge of cloud services and how those services are provided with Microsoft Azure.

> Python Programming

33. Programming 102: Think Like a Computer Scientist

21500+

4 weeks

Raspberry Pi Foundation, National Centre for Computing Education

Take your Python skills further in this online course, guided by the Raspberry Pi Foundation and supported by Google.34. Programming 103: Saving and Structuring Data

13000+

3 weeks

Raspberry Pi Foundation, National Centre for Computing Education

Learn how to save and structure data in external files, and import files back into your Python programs. Supported by Google.35. Programming for Everybody: Python Data Structures

9000+

6 weeks

University of Michigan

Discover data structures and learn how they’re used in the Python programming language with experts at the University of Michigan.36. Scratch to Python: Moving from Block- to Text-based Programming

17600+

4 weeks

Raspberry Pi Foundation, National Centre for Computing Education

Support learners to use the thinking & programming skills they learnt in Scratch in text-based programming languages like Python.

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comp6841lanceyoung · 6 years ago

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Security Project Proposal

Introduction

For me, computer science isn’t by itself alluring; it’s what can be done with computers that’s truly fascinating.

So, one particular idea of technology that interests me is the concept of the digital footprint. Wikipedia defines one’s digital footprint as ‘one’s unique set of traceable digital activities, actions, contributions and communications manifested on the Internet or on digital devices’.

To take it out of the domain of technology for a second, intelligence organisations have spent many hours and resources developing techniques to gather information about a target’s movements and actions. They did this because they understood the absolute value of this information – said information can aluminate bigger ideas.

In the current age, collecting one’s digital footprint is a new said technique.

To bring it into the tangible world, commercial businesses can offer free wifi to consumers visiting a particular retail store in exchange for the permission to track their movements in and out of the store (agreeing to ‘location tracking’). This can be done because the MAC address of device is unique, and therefore can be used to identify the owner. Whenever the device enters the store, it will automatically seek to reconnect – once reconnected, the MAC address is collected, and the individual is identified and their movement is recorded.

But wait, I lied. This doesn’t just track one’s movements in and out of one retail store. Instead, it tracks their movements in and out of all retail stores that have said free wifi installed (belonging to a particular ‘digital net’). In fact, if a third-party company owns all the wifis, then this tracking isn’t just restricted to one particular company, but to all companies that contribute to the digital net, and why wouldn’t they if they get such an insight into their customer’s behaviour in return?

The following article goes into more detail and provides real-life examples if interested: link.

So, to start my journey in discovering this field of technology, I want to start investigating how you can collect one’s digital footprint using wifi or Bluetooth signals sent from personal devices.

Goal

To accumulate the digital footprint of anonymous individuals accessing the sec-lab in K17 by listening to public wifi or Bluetooth signals sent from their personal devices, and hence, build a unique profile of said anonymous individuals, providing a small insight into their day to day lives.

Skills

I am going to have to have an understanding of what public wifi or Bluetooth signals are sent from particular devices. I’d like to note that I understand that by wifi’s very nature, all wifi signals are public – I only stress to say ‘public’ wifi to infer that I’m merely collecting what is already there.

Besides from passively collecting packets, it might be worth investigating whether there are particular techniques for inciting transmissions from devices for those devices that are, for any reason, ‘shy’.

I’ll also need to be able to work with a raspberry pi, as this will act as the device that will be collecting said data. This data will then need to be organised into a useful manner, building profiles of devices, and thereby, collecting an individual’s digital footprint. It is important to note that I’ll have to keep in mind that people have multiple devices, so maybe identifying how many and what devices each person has would be a real life example of being able to gain insights into an individual’s consumer habits.

Ambitiously, I would love to extend the digital net to two or more locations and have this information public available on a website – individual’s can look up their past movements using their MAC addresses and potentially learn something about digital footprints.

The Process

The first step is to use a USB wifi adaptor and Wireshark to start analysing packets being sent from my personal devices – I’d be focusing mainly on wifi and potentially Bluetooth signals, though I should keep an eye for cellular signals too. With that information, I aim to build an understanding of what packets I can be looking for when I’m trying to collect one’s digital footprint.

I’ll be going into this tasking knowing a few things: devices can and do automatically connect to known wifis, the device has to be assigned an IP from the modem within the wifi network (eg. 10.xx.xx…) and finally, that ARP and DHCP are important protocols to know.

Ultimately, I’ll be reverse engineering packets to gain an understanding of what kind of packets are being sent from these devices – I’ll have to keep in mind that signals from different types of devices made from different companies may differ.

So assuming I can now collect packets with easy, I then have to see if I can use information within this packets to uniquely identify devices (probably the MAC address will do).

Once I have an understanding of what I am looking for, I then have to program a raspberry pi to be listening for all packets (does it even have the firepower to do that?) and filter for the important packets, scraping data from them.

As mentioned above, this scraping cannot be restricted to one type of device from one company – all major devices must be trackable.

If there aren’t enough important packets being collected, or I have time, I’ll have to investigate whether you can encourage devices to send said packets – what if a device is already connected to the UNSW wifi? Will that restrict my ability to track the device? (I do know you can force devices to disconnect from a wifi, would be interesting to test on my own devices, but not on others).

Organise the collected data in a useful way, providing valuable information in the comings and goings of devices.

Try and pair devices together that are owned by the same person if possible.

Store data into a database, and host a public website, advertising said information to students.

Expand to more rooms.

Marking Criteria

Credit: Complete task 1 to a satisfactory level.

Distinction: Complete task 2 and 3

High Distinction: Complete task 4 and 5

Kudos and the strengthening of the case for a software project next sem: Task 6 and 7

#awesome-software-project

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denerims-archive · 6 years ago

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ᴀʙᴏᴜᴛ ᴛʜᴇ ᴄʜᴀʀᴀᴄᴛᴇʀ + little things — Alex Delarosa

Tagged by @lonewcnderer and @thomasrushed! Thanks guys 💗 Tagging @johnconstantlne, @lavellane, @atheina, @athurmorgan, @zahra-hydris, @noonvraith, @lunastres, @saintsrow1 + anyone else who would like to do it!! 😊

↠ Your muse’s name: Alex Delarosa ↠ One favorite picture/faceclaim you have of your muse: every single picture because eiza gonzalez is GORGEOUS This one + any of her in FDTD/Baby Driver:

↠ Two headcanons you have for your muse:

one ) She can count the people who know her birth name on one hand. Alex left that girl on a street corner somewhere a long time ago. A marzipan peanut candy she loved as a kid made by the De La Rosa candy company served as inspiration for her last name. Alexandra came from the prophetess of Greek mythology. She got it legally changed at age 19, one of the few things she’s ever done legally.

two ) Alex has a great poker face and by extension is very good at cards. A woman who bluffs her way through life is not the one you want to play cards with. Most of her closer friends don’t like playing cards with her because of it. Not to mention, she cheats which might have something to do with it.

↠ Three things that your muse loves doing in their free time: one ) Boxing is Alex’s outlet for unbridled rage. It keeps her on her feet during down times and doesn’t let her get soft. Not to mention, it’s come in handy in quite a few tight spots. As an extension, she also loves going down to the shooting range with Julia and Danny.

two ) Alex likes to...snoop. She has issues with privacy, she’ll be the first to admit. She loves to prod at casino security systems, government agency databases, you name it. It’s good practice and she has an unfortunate curiosity that people have always said will get her in trouble one day.

three ) Being around her team. Though many of them, besides the Kincaids, are unsure if she genuinely cares about them or is just using them to suit her own means (in truth, it’s a bit of both) but Alex likes being around them. She’s never had a close knit group of friends, usually traveling around place to place looking for scores or working alone. She’s a woman with a lot of allies but few friends.

↠ Seven people your muse loves/likes Alex likes everyone but the people she loves is a very short list.

1) Danny Kincaid 2) Julia Kincaid 3) Gabriel Chavez 4) Bee Young 5) James Winter

↠ A phobia your muse has

Alex has quite a few phobias, all linked to early-life trauma but the one that sends her truly spiraling is her claustrophobia. Any tight spaces and she has quite a bad panic attack. Even being too tightly wrapped in blankets while she sleeps is enough to set her off. It’s something she’s always been embarrassed about and tries to keep private.

LITTLE THINGS.

#character: alex #emily got tagged #the tricksters

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juniperpublishersoceanography · 4 years ago

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Mapping the Different Planktonic Groups at One of the Egyptian Bays along Mediterranean Coast- Juniper Publishers

coastal science

Abstract

The abundance and community composition of zooplankton is spatially and temporally variable so it requires sampling over space and time. Quantitative assessment of biomass, community composition, and abundance is sensitive for sampling methodology, including the location and seasonal timing of sampling, as well as mesh size and gear type. Therefore, repeated and consistent sampling is essential to determine the changes in zooplankton distribution, abundance, community composition and seasonal timing at time scales that have impacts on higher trophic levels. In the present study, El-Mex Bay is highly diversified (204 forms) but low standing crop (annual average 8935 organisms/m3). Using GIS and the other mapping applications give an easy and clear image about the distribution of aquatic fauna especially microscopic forms which help in understanding the dynamic of biological ecosystem.

Introduction

Zooplankton species are important lower trophic level members of marine ecosystem. They are a good indicator of ecosystem status since their populations respond relatively rapid to environmental variability and they are usually not fished [1].

In aquatic environment zooplankton is considered as one of the most important biotic components, particularly in the pelagic habitat. Zooplankton play a key role in the pelagic food web by controlling phytoplankton production and shaping pelagic ecosystem. In addition it has a critical role as a food source for larval and juvenile fish and consequently the dynamics of its populations have a great influence on recruitment to fish stocks. Such intermediate role of zooplankton makes it as a regulator of the biological productivity in the pelagic habitat, since it has a detrimental effect on phytoplankton by grazing and beneficial effect to the water fertility through nutrient recycling [2]. Zooplankton community demonstrates variable structure in the different aquatic habitats, relative to differences in the ecological conditions. Shallow marine coastal areas present an interesting subject of biological studies because of their productivity and the diversity of organisms which occur there [3]. Coastal marine areas are ecologically and economically important and of social interest [4]. They are extremely variable systems, where changes in the water circulation patterns and fluctuations of land influences (e.g. rivers, sewage flow) induce high temporal variability on scales ranging from hours to seasons. This variability may be reflected the dynamics of the populations, particularly planktonic ones, thriving in coastal systems and can hide the underlying seasonal patterns of organisms' abundance and biomass [4].

A fundamental challenge in Earth System science is the response of the marine ecosystem to changes in climatic forcing. In particular how will it affect ecosystem functioning and the sustainability of bio-resources. Datasets which allow us to map the distribution of marine biota are sparse. Satellite remote sensing can provide detailed information on a large scale for several bio-physical parameters, such as temperature and chlorophyll [5]. The challenge is to combine satellite data with the sparse in-situ datasets to generate distributions of higher trophic levels. To monitor the aquatic ecosystem and integrated of water, zooplankton has been recently used as bioindicator [6-12].

Abo-Taleb [13], Abdel Aziz et al. [14], Abo-Taleb et al. [12] they were found that fluctuation in the domination of copepods rotifers, Chromista and Protozoa resulted from the unstable environmental conditions of the bays and estuaries along the Egyptian Mediterranean coast. In the Egyptian part of the Mediterranean Sea, Zooplankton has attracted more attention particularly in the neritic waters. The first study has been conducted by [15]. Steuer [16,17] as preliminary reports on plankton hauls collected off Alexandria and Rosetta Coasts. Later one more detailed and comprehensive studies were carried out on zooplankton in different parts of the Egyptian Mediterranean waters. Some of these studies concern with the total zooplankton community off Alexandria Coast and Nile Delta Region Dowidar [18] studied the distribution and ecology of both phytoplankton and zooplankton in Alexandria region. El- Maghraby & Halim [19] investigated quantitatively and qualitatively the phytoplankton and zooplankton off the Eastern Harbor. Halim et al. [20] gave brief notes on the distribution of plankton organisms off the Egyptian Mediterranean Coast during the last normal Nile flood of 1964. Guerguess [21] and Dowidar & El- Maghraby [22], studied the distribution and ecology of the neritic zooplankton of the area surrounding Alexandria with special reference to Copepoda. Hendy [23] and El Raey et al.[24] , assess quantitatively the vulnerability to sea level rise of El Mex Bay and determine areas at risk of flooding and erosion.

El-Mex Bay has attracted little attention for the biological studies, although it lies under stress of huge and different types of waters. So, it is necessary to study zooplankton community in the bay. Hence, the present study is designed to study the dynamics of zooplankton community at El- Mex Bay, Using GIS (ARCMAP 10) to produce maps illustrating plankton abundance and diversity.

Material and Methods

Study area

El- Mex Bay is located west of Alexandria City, at longitude 29° 45' and 29° 54' E and latitude 31° 07' and 31° 15' N, It extends for about 15Km from Agami headland to the west to the Western Harbor to the east. The bay has a mean depth of 10m. Its surface area is about 19.4Km2, and its volume 190.3 x 106m3[25] . The shoreline of El- Mex Bay is rocky with narrow sandy beaches. It receives a heavy load of wastewater (7*109 m3/year) both directly from industrial outfalls (El- Umoum Drain) and indirectly from Lake Mariut via El- Mex Pumping Station [26]. El- Umoum Drain is mainly agricultural water. Lake Mariut receives also wastewater from the four sources in its eastern section, consisting of domestic, industrial and agricultural wastes, this liquid wastes discharged to the harbor via El- Mex Pumping Station.

Samples were collected seasonally during 5 seasons from autumn 2011 to autumn 2012 from eight stations. The stations were selected to cover all possible environmental changes of the study area. The locations of the sampling stations are shown in (Figure 1).

Zooplankton samples

Zooplankton samples were collected at each station by standard plankton net (No. 25) of 55μm mesh size which lowered vertically till near the bottom then pushed up to the water surface. The zooplankton organisms which retained in the net were then transferred into smaU bottle and preserved in 5% neutralized formalin solution and the sample volume was then adjusted to 100ml. The samples were examined under a binocular research microscope. The identification was undertaken to species levels. For estimation of standing crop, sub samples of 5ml were transferred to a counting chamber (Bogorov chamber) using a plunger pipette this operation performed three times and the average of the three counts was taken, and the standing crop was calculated and estimated as organisms per cubic meter according to the following formula [27]

N= (n * v) / (V * 5)

V= πr2.d

Where;

N: Total number of zooplankton per cubic meter.

n: Average number of zooplankton in 5ml of the sample.

v: Volume of concentrated sample (100ml).

V: Volume of total water filtered (m3).

d: Length of the traction by the net.

Identification of the different species of zooplankton species was carried out according to Sars [28,29] (Copepoda), Rose [30] (Mediterranean copepods), Tregouboff & Rose [31] (Mediterranean plankton), Pontin [32] (Freshwater plankton), Guerguess [33], Hutchinson [34] (Plankton as a general), Marshall [35], Bick [36], Paulmier [37], Jorgensen [38] (Protozoa), Gurney [39-41] and Hardig & Smith [42] (freshwater Copepoda), Wilson & Yeatman [43], Edmondson [44], Gurney [45] (Copepoda and Cladocera), Berzins [46], Berzins & Pejler [47] (Rotifera), Sars [48] (Ostracoda), Sars [49] (Entomostraca) and using WORMS database [50].

Data analysis

The remotely sensed satellite imagery (LAND SAT 7) was found to be the most appropriate one for this study, as with its regional coverage, all necessary map features were obviously clear and interpreted. A raster depending software was used for the purpose of digitizing the map features. ARC-GIS 10 and Envi software was used for this purpose for its high digitization capabilities, also in finalizing and visualizing data. The analysis and interpretation of different zooplankton groups was done by ARC-GIS 10.

Diversity index was estimated according to Shannon & Weaver [51] as follows:

H = - Σ Pi ln Pi

Where;

Pi = n/N

Pi: is the proportion of a species number (n) to the total number of zooplankton (N).

Go to

Results

Diversity of zooplankton groups in the bay

Zooplankton community in the El-Mex Bay was represented by 204 species belonging to 12 groups. Protozoa was the most diversified group in the bay 69 species, followed by Copepoda which represented by 50 species. Rotifera ranked the third diversified group in the bay represented by 38 species, Chordata represented by 9 forms while, Cnidaria, Mollusca and other Arthropoda were represented by 6 forms for each one of them, Cypredina, Cladocera and Annelida were represented by 12 forms, four to every group. Two cirripedian forms and two Chaetognathans were recorded, two Radiolaria, one Pteropoda and Porifera residues (Figure 2).

The number of species varied temporary where the highest number of species were recorded during winter (151 species), decreased during spring to reach 123 species and still decreased during summer and autumn 2012 to reach (114 and 113 species) respectively. Number of species differed from one station to another with its maximum at station I and VI (130 and 131 species respectively) reaches 126 species at station III and ranged from 105 to 116 species at the other stations, with the most diversity at station IV (100 species) as recorded in (Table 1) .

Relative contribution (%) of different groups

As shown in Table 2, Copepoda was the most important group, contributing 55% of the total zooplankton. Protozoa occupied the 2nd order of abundance forming 15.6% of the total zooplankton. Rotifera formed 11.7% of the total zooplankton. Other groups were frequently encountered such as Larvacea, Chaetognatha, Cladocera, Cirripedia, Ostracoda, Chordata, Mollusca, Annelida, Nematoda and Cnidaria.

Dynamics of zooplankton groups in the bay (Zooplankton groups distributions)

Zooplankton communities showed wide seasonal variations at El- Mex Bay, the following data described these fluctuations (Figure 3-7).

Copepoda: Appeared as the predominant component of zooplankton in El- Mex Bay. The adult copepods formed 63% of total copepod counts with an average of 3218 individuals/m3 while, the rest 37% were represented by copepodite stages and nauplii with an average of 1866 individuals/m3. The maximum density was recorded during autumn 2011 and gradually decreased to their minimum value during spring 2012.

Protozoa: Ranked the 2nd dominant group in the bay with annual average of 1440 organisms/m3. Generally, winter and spring seasons showed maximum densities (average of 2272 and 2045 individuals/m3), while minimum average counts were recorded at the beginning of the study during autumn 2011. Their counts ranged between maximum of 5860 individuals/m3 at station VII during spring and minimum of 212 individuals/m3 at station V during autumn 2011.

Rotifera: Ranked the 3rd group and recorded annual average 1077 individuals/m3. 38 rotifer species were identified under 16 genera within 12 families, 3 orders and one class. The maximum counts were recorded at station VII (4161 individuals/m3) during autumn 2012 and minimum of 170 individuals/m3 at station V during autumn 2011. The highest rotifer average was recorded at station VII (2508 individuals/m3), while stations III and V showed minimum average counts of rotifers (596 and 558 individuals/m3)

Annelida: Ranked as the 4th dominant group at the El- Mex Bay during the study period, they constituted 3.9% of the total zooplankton groups with average total counts of 332 individuals/m3. Their minimum values were recorded during autumn 2011 (188 individuals/m3) and flourished during winter 2012 with a maximum of 556 individuals/m3. Annelids were represented by some adult polychaete species, polychaete larvae and different stages of Spionid larvae included several stages of trochophore larvae (late trochophore, early trochophore, and mid. trochophore). According to spatial distribution they recorded their maximum values (1137 individuals/m3) at station II during winter 2012 and minimum of 42 individuals/ m3 at station V during autumn 2011(Table 3).

Chordata: Constituted 2.9% of the total zooplankton groups and occupied the 5th rank in the bay after annelids with average numbers were 259 individuals/m3. During winter and spring 2012 chordates flourished and recorded their maximum average counts (424 and 329 individuals/m3) respectively while it showed lower values during summer (105 individuals/m3). They recorded the maximum density (1035 individuals/m3) at station I during winter 2012, while it was absent at station IV during autumn 2011 and at station VII during summer 2012. Chordata in the El-Mex Bay were represented by Euchordata and Urochordata. Euchordata expressed as fish eggs and larvae. While Urochordata represented by two classes; Appendicularia and Ascidiacea, the first class included five species were Folia sp., Oikopleura dioica, O. parva, O. fusiformis and O. longicauda. On the other hand the second class was represented by Tadpole larvae of tunicate (Phallusia mammillata and Ciona intestinalis), this class was recorded by small counts (Table 3).

Cirripedia: Ranked the 6th order of abundant and was represented by nauplii larvae and cypris larvae of cirripeds. They formed collectively 2.9% with total average counts 264 organisms/m3. It was recorded throughout all the year except at stations IV and V during summer 2012. They recorded their maximum counts (589 individuals/m3) during autumn 2012 and decreased to 77 individuals/m3 during summer 2012. Cirriped larvae were the dominant Cirripeda (Table 3).

Mollusca: Ranked the 7th order of abundant with total average of 196 individuals/m3 during the investigated period; they constituted about 2.1% to total zooplankton groups. Mollusca were recorded in all the study seasons, their maximum values were during summer and autumn 2012 (268 and 285 individuals/m3), while they became the lowest (133 individuals/ m3) during spring. Mollusca in the bay were represented by gastropods, pteropods and the lamellibranch veliger (Table 3).

Cnidaria: was represented by 1.2% of total zooplankton groups with total average was 94 individuals/m3. Generally, Cnidaria recorded their maximum average values (165 individuals/m3) during spring; on the other hand the minimum values were recorded during the two autumn seasons (42 individuals/m3). Cnidaria recorded their maximum values at the stations which located at the sea side (stations III with average 95 individuals/m3 and station VIII with average 125 individuals/ m3) and total average of 140 individuals/m3 at station IV due to the relatively high salinity values at this station (Table 3).

stracoda: represented 0.9% of total zooplankton with average was 59 individuals/m3. Their maximum densities were recorded during autumn 2011 and winter (74 and 77 individuals/m3), while minimum densities (21 individuals/ m3) were recorded during summer 2012. Ostracoda at El-Mex Bay dominated by Cyclocypris sp., Cypridina mediterrianea, Cytheridea punctillata and Xestoleberis depressa (Table 3).

Other arthropoda: In this study was represented by Insect species and their larvae, water mites, Mysis relicta, Gammarus marinus and Zoea of Decapoda. They formed collectively 0.9% of total groups with average numbers were 41 individuals/m3. During winter and spring seasons they flourished to be 87 and 48 individuals/m3 respectively, while their minimum values were recorded during the two autumn seasons (6 and 25 individuals/ m3 respectively). Through the whole study period these forms were absent at station V. While the maximum values (average 74 individuals/m3) were recorded at station VII and station IV (average of 54 individuals/m3).

Nematoda: Were represented by free living nematodes which formed only 0.7% of the total zooplankton groups, with total average 30 individuals/m3. They recorded their maximum density during autumn 2011 (44 individuals/m3) and minimum of 11 individuals/m3 during autumn 2012. According to spatial distribution, nematodes were completely absent from station IV all the study period. On the other hand they were dominated at stations I with total average of 58 organisms/m3 and decreased to minimum at station V (9 individuals/m3) (Table 3).

Cladocera: Was dominated by Evadne spinifera, Podon polyphemoides and P. leuckarti and Moina micrura. Cladocera represented by 0.6% of total zooplankton with total average number were 23 individuals/m3. Cladocera flourished during two seasons, winter and spring (26 and 63 individuals/m3) but their minimum value (5 individuals/m3) was recorded during summer. They were absent at station II. On the other hand they recorded their maximum average counts at stations III (35 individuals/m3) at the first section, VII and VIII (34 and 36 organisms/m3 respectively) which located at the right side of El Umoum Drain inlet (Table 3).

Chaetognatha: In the El- Mex Bay constituted 0.5% and averaged 11 individuals/m3. They disappeared from the bay during spring but recorded their maximum densities (average, 19 individuals/m3) during winter. According to spatial distribution Cheatognatha was absent from stations I, V and VI through the whole study period, while they recorded their maximum values (average, 28 individuals/m3) at stations III and VIII during winter and station IV during autumn 2012 (Table 3).

Diversity index

Shannon’s diversity index of the zooplankton assemblages fluctuated between a minimum of 2.77±0.23 during autumn 2012 to maximum of 3.39±0.18 during spring (Figure 8) Station VII showed maximum diversity index (3.63) during spring season and also the minimum diversity index (2.48) during autumn 2012. According to spatial distributions the maximum diversity index was recorded for stations II and VI where there diversity index values were 3.25±0.28 and 3.22±0.18 respectively (Figure 9).

Discussion

The observed spatial and temporal variations of the zooplankton abundance might be traced to the effect of El- Umoum Drain discharge into El- Mex Bay. With increasing phytoplankton biomass, the abundance of phytoplankton cause herbivorous zooplankton species to increase [52]. Due to pollution and eutrophication the copepod Acartia clausi was favored, while rare species became extinct [53]. Zhenbin et al. [54] reported that zooplankton community structure changed from eutrophic-indicator genera (Brachionus, Polyarthra and Keratella) to genera more characteristic of oligotrophic conditions (Tintinnopsis and Acanthocyclops). Li et al. [55] also found that the dominant species Brachionus spp. and Keratella spp. were replaced by Tintinnopsis spp. in Xihu Lake.

Hussein [56] recorded 121 zooplankton species, while El- Sherif [57] found that zooplankton community in El- Mex Bay was represented by 130 taxa. The present study revealed that zooplankton of El-Mex Bay is highly diversified (204 forms) with low standing crop (annual average 8935 organisms/m3). The species composition of zooplankton community reflects clearly the effect of the land based effluents, whereas the high salinity stations were comparatively lesser diversified than the low salinity stations. On the other hand, effect of El-Umoum Drain and El-Mex Pump Station resulted also in clear temporal variation of species richness at each station relative to variations in values of discharged water.

The high zooplankton diversity during the present study is attributed to the intrusion of the freshwater ciliates and rotifers. Day et al. [58] reported that most estuarine zooplankton organisms have evolved to broad physiological tolerance in order to ensure their survival into unstable environmental conditions and consequently results in high species composition. The temporal distribution of zooplankton composition demonstrated the highest diversified community (151 species) appeared in winter and the lowest (113 species) in autumn 2012, these variations could be attributed to temporal changes in the number of freshwater species enter into the bay through the discharged waste waters also due to the environmental variables like temperature , salinity, nutrients and phytoplankton biomass. These observations are in agreement with Morques et al. [59,60].

The temporal variations of diversity provide useful information on succession of community structure and it may be used as an index for assessing the degree of environmental stress [61]. Day et al. [58] whereas the pollution causes the loss of some sensitive species and led to the occurrence of few of the most tolerant species in great numbers.

The temporal zooplankton abundance showed peaks during winter and autumn 2012. The high water dynamics in these two seasons may play clear role in temporal variations of zooplankton abundance. This contradicts with the observation in other areas, where temperature was the essential element in the seasonal dynamics of zooplankton [62].

The copepods were the dominant component of zooplankton in El-Mex Bay. This observation is agreed with other studies on the marine ecosystem [63-68]. El- Sherif [57] found that Copepoda was represented in the study area by 22 species, only one of them (Acanthocyclops americanus) belongs to the freshwater forms. Other recorded species, Acartia clausi, A. latisetosa, Paracalanus parvus, Oithona nana and Euterpina acutifrons are eurythermal and euryhaline species. They are common at the near shore waters west of Alexandria [56,69].

In El- Mex Bay, the freshwater rotifers are more diversified and the predominant zooplankton component in the water mass is directly stressed by El- Umoum Drain. Rotifers are usually known as the major zooplankton component in the freshwater habitate [70]. The high species number of rotifers at the low salinity stations compared to those at stations (I and IV) indicates the role of discharged freshwater. The rotifers' diversity in El- Mex Bay were rich (38 species), perhaps due to the effect of the mixture of freshwater and marine species and the high trophic level of the system. This agreed with [53] and [9] whom mentioned that the bay subjected to high trophic conditions. The majority of species in this study were euryhaline forms (21 species) and the rest species were freshwater forms (17 species). Throughout the present investigation, the percentage of genus Synchaeta was 51.3% of the total rotifer abundance followed by Brachionus with 19.1% and Keratella 4.5 % [9].

[71] stated that rotifer was the leading group at the mixed land drainage water type constituted 85.75 % of the total zooplankton community in the bay. Protozoa occupied the 2nd order of abundance among zooplankton groups in El-Mex Bay contribution 15.6 % of the total zooplankton counts (averaged 1440 organisms/m3), predominated by ciliates. Protozoa are characterized by many specific structural and functional features, present an important ecological assemblage in aquatic ecosystem and play a crucial role in the function of microbial food webs in addition to their role as indicators of water quality [72]. Protozoa community in El- Mex Bay is pronounced affected by the dispersion pattern of discharged waters. Higher values were particularly observed during winter 2012 (2272 organisms/m3) while autumn 2011 displayed lower densities (519 organisms/m3). Protozoa reached the maximum density at station VII during spring 2012 (5860 organisms/m3) due to the predominance of Centropyxis aculeate, Difflugia oblonga, Favella azorica, Tintinnopsis beroidea, T. campanula, T. cylindrical, and T. lobiancoi.

El- Mex Bay has the highest tintinnid densities during the study period which was dominated by Tintinnopsis beroidea, this agreed with [73] while [57] stated that Protozoa was the highly diversified group in the Western part of Alexandria. It was represented by 63 species (48.46% to the total number of the recorded species). Out of them, 40 tintinnid species, 11 Foraminifera species and 12 species of fresh water ciliates. All tintinnid species are marine forms while some of Foraminifera species are belonging to freshwater forms. Zakaria et al. [71] stated that Protozoa was the second important group after rotifers in the bay. Pteropoda appeared very rare in El-Mex Bay due to the acidification of the bay during sometimes, absence of this group is considerable evidence of the high acidity of any water body, This agree with [74]. Pteropods are the most sensitive Planktonic group because their shell is composed of aragonite, which will be subject to increased dissolution under more acidic conditions. Pteropods would not be able to adapt quickly enough to live in under saturated conditions. Pteropods, with their aragonite shells, are highly vulnerable, while, foraminifera and some crustaceans, with their calcite shells and liths, are less vulnerable. Pteropods are likely to decline and may eventually disappear in response to ocean acidification [75].

Nematods represented by 0.7 % of the total zooplankton with an average of 65 organisms/m3. Nemeth-Katona [76] considered that the presence of nematodes is an indication of the final stage of contamination with sewage, the ultimate putrefaction of water: hydrogen sulphide indicator. Cladocera are considered to be important in the economy of the area because of their relation to pelagic fisheries and are believed to play an important role in the phosphorus regenerate [77]. during the study period Cladocera represented by 0.6% of the total zooplankton with total average number were 23 organisms/ m3 dominated by Evadne spinifera, Podon polyphemoides and P leuckarti and Moina micrura flourished during winter and spring, their minimum values during summer, occurred intermittently at the sampled stations. Although salinity seems to impact the spatial distribution of Cladocera at El-Mex Bay the freshwater species Moina micrura was recorded at some sampled stations indication it is tolerance of wide salinity. Moina micrura is a common species in eutrophic water and can be indicator of eutrophication [78]. Food concentration may affect growth and reproduction of cladocerans [79].

Cirripedia contributed 2.9 % of the total zooplankton (averaged 264 organisms/m3), exhibited comparatively high abundance at high salinity, and disappeared at low salinity stations. This showed by significant correlation between cirripeds and salinity. Jeffries [80] reported that the overabundance phytoplankton as food is associated factors may have been responsible for delay reproduction of adult cirripeds. Polychaetes and larvae were found during the study period with a percentage of 3.9 % and covered the whole area at wide salinity range. These larvae are described as estuarine zooplankton component, being restricted to low salinities and an aerobic conditions or high pollution levels [81] and they play crucial role in meroplankton in the Egyptian Mediterranean coastal water [82].

The presence of freshwater species (Copepoda, Cladocera, Protozoa and so on) in marine coastal areas are considered a biomarkers on the presence of fresh water discharge into these areas, and according to types of this species can determine the source of water discharged neither rivers, lakes, drainage or sewage Froneman [83].

Conclusion

From the obtained results it concluded that El-Umoum Drain discharge, maritime activities and shipping movements in the study area were reflected on the hydrographic conditions and the dynamics of zooplankton community in the El-Mex Bay. The zooplankton showed great numbers of freshwater species which considered as bioindicator to the huge amount of freshwater entering the bay, also the great numbers of rotifers and the presence of other forms like nematodes and some ciliated protozoa serve as bioindicators of pollution and declining water quality.

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sycriptouk · 4 years ago

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ELI5: What makes Bitcoin valuable? What is Lightning Network? What is Taproot?

Alright, this is a long post. But hopefully, it is able to further your understanding of Bitcoin. At least, that's the goal!

If you were new to cryptocurrency even 5 years ago, you didn't have much choice. Today, that's not the case, especially in a bull market, which is when a lot of newcoiners typically flock to this space.

This post is intended to educate newcoiners, and perhaps some old HODLers as well, on what makes Bitcoin valuable, the Lightning Network and Taproot without overly complicating the conversation.

What's so unique about Bitcoin?

There's a common misunderstanding that Bitcoin has such great value because it was the first. This is untrue. There were several prior attempts at digital money - B-money, Bit gold and Hashcash (although not technically money) the most prominent among them. Satoshi's PoW algorithm solved a critical flaw in the use of blockchain as a public ledger known as the Byzantine Generals Problem.

The concept of blockchain predates Bitcoin by almost two decades. So the value was never in blockchain but the way Bitcoin was able to utilize blockchain as a trustless, permissionless, decentralized public ledger to democratically create, distribute and exchange value.

So centralized iterations of blockchain are indeed a waste of time. Permissioned protocols can often achieve greater efficiency using an SQL database instead.

Another misconception among newcomers is that you're late to the Bitcoin party. Just as you can never be late to the Internet, you can never be late to Bitcoin.

Bitcoin is not just a cryptocurrency. Bitcoin, in the broader sense, is a protocol capable of functioning as the network layer of a decentralized Internet. Bitcoin can therefore fix the Internet's original sin, centralization at the hands of a powerful few, and restore it to its original form - a decentralized P2P network protocol.

Bitcoin is capable of remaining decentralized by allowing any participant in the network to access their own version of the truth in a very economical manner. You can run your own Bitcoin full node on a Raspberry Pi. This allows you to be an equal rights citizen on the network and not have to delegate trust to a third party. Without being able to verify on your own, you're just going from trusting bankers to a random person on the internet. That's hardly revolutionary.

Samourai Dojo Bitcoin Full Node on Raspberry Pi (cost $40)

Bitcoin is not only time-tested but has proven to be doggedly antifragile. What makes Bitcoin antifragile is the ability of the average user to run a full node.

There's no locus of power to attack. Every node is equal and they're distributed all across the world on every continent. Every quadrennial cycle, while higher profile individuals and entities attack Bitcoin, these attacks only end up effecting even greater faith in the protocol.

Being a pure P2P network allows Bitcoin to withstand state attacks (Satoshi, 2008)

Altcoins bring a lot of necessary innovation each cycle, more so since Ethereum came along, but the problem with open, unbridled innovation is that, while it engenders infinite possibilities, it also breeds exploitation and self-seeking greed.

ICOs were all the rage 4 years ago. But thanks to exploitation, they've all but disappeared. The idea of crowdfunded development of decentralized protocols wasn't the problem. The problem was that without a native set of rules to prevent exploitation, greed defeats innovation.

Just because something is possible doesn't make it necessary. What's truly necessary is impossible to stop. Necessary innovation will become impossible to stop once we are able to self-police cryptocurrency from greedy opportunists seeking to deny innovation a chance to thrive to cynically line their own pockets.

Lightning Network

Lightning Network is a decentralized layer-2 network protocol that uses a native smart contract scripting language to enable instant, almost feeless Bitcoin payments.

On the Lightning Network, both parties to a transaction are required only to have a sufficiently funded open channel on the network. This is done through a single on-chain transaction.

If there is a direct channel open between the parties, the transaction is routed directly and incurs zero fees. Without a direct channel, the transaction is routed through routing nodes.

Whan a transaction passes through a routing node, it is referred to as a "hop". There are currently 23k nodes on the Lightning Network with 13k nodes having active channels.

Three years ago, Lightning Network was admittedly far from ideal for everyday payments.

Lightning Network Node Map (March 2018)

But the network has seen exponential growth since, particularly this year. Lightning Network is now a fully-fledged global payments network secured by the Bitcoin blockchain. Lightning wallets have also come a long way and are now very intuitive to use for the average user.

Lightning Network Node Map (July 2021)

Network capacity has doubled this year. Likewise, nodes and channels have grown exponentially, reducing the number of hops and fees incurred for hops through routing nodes, and improving channel lifespan.

The growth of the Lightning Network has inspired some exciting developments this year,

Following the success of the Bitcoin beach project, a pilot for Lightning Network's viability as MoE, El Salvador has adopted Bitcoin as legal tender. Other countries like Tonga, Colombia and other LatAm countries have expressed interest to follow suit.

Strike app has introduced a Bitcoin tab, with the ability to purchase Bitcoin for a nominal fee of a few cents through the Lightning Network.

Twitter is expected to launch a tipping system on its platform later this year using the Lightning Network.

Feeless payment of 1 satoshi sent from Spain to Tokyo

Taproot

Now with Lightning Network's maturation as an instant, almost feeless, infinitely scalable decentralized global payments network, Bitcoin is shifting focus to its next big milestone, Taproot, which is due to go live in November.

Taproot brings a set of protocols that further enhance Bitcoin's scalability through even more efficient use of block space by introducing a new type of output - Pay to Taproot (P2TR).

P2TR uses Schnorr signatures, which are more compact than the conventional Elliptic Curve Digital Signing Algorithm (ECDSA) signatures. Schnorr signatures are between 6 and 9 bytes shorter than ECDSA.

An even more exciting aspect of Schnorr signatures is that it enables the aggregation of multiple signatures into a single signature. This opens up infinite possibilities, including being able to execute multi-sigs and L2/sidechain smart contracts as a simple regular transaction on-chain.

It's a truly game-changing development, as it allows Bitcoin to have smart contract protocols without bloating the blockchain layer.

Further, Taproot also includes optimization for the Lightning Network called Point Time-Locked Contract(PTLC). PTLC replaces Hash Time-Locked Contract(HTLC). PTLC uses adaptor signatures, which enhance privacy and security on the Lightning Network, enabling escrow contracts in Lightning channels and allowing users to retry stuck payments.

Curfew cocktail bar in Copenhagen, Denmark accepting Lightning payment

submitted by /u/xcryptogurux [link] [comments]

from Cryptocurrency News & Discussion https://www.reddit.com/r/CryptoCurrency/comments/opa0p6/eli5_what_makes_bitcoin_valuable_what_is/ via IFTTT

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agilenano · 4 years ago

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Agilenano - News: The $50 Ham: WSPR-ing Around the World

Everybody has a bucket list, things to be accomplished before the day we eventually wake up on the wrong side of the grass. Many bucket-list items are far more aspirational than realistic; very few of us with “A trip to space” on our lists are going to live to see that fulfilled. And even the more realistic goals, like the trip to Antarctica that’s been on my list for ages, become less and less likely as your life circumstances change — my wife hates the cold. Luckily, instead of going to Antarctica by myself — and really, what fun would that be? — I’ve recently been getting some of the satisfaction of world travel through amateur radio. The last installment of “The $50 Ham” highlighted weak-signal digital modes using WSJT-X; in that article, I mentioned a little about the Weak Signal Propagation Reporter, or WSPR. It’s that mode that let me test what’s possible with very low-power transmissions, and allowed me to virtually visit six continents including Antarctica and Sweden-by-way-of-Alaska. Whispers in the Noise Ask a random amateur radio operator what’s on his or her mind at any given moment and chances are pretty good the answer will be, “How are the bands right now?” That’s shorthand for what the current state of the ionosphere is, which largely determines how well RF signals will bounce off the various layers of charged particles that wrap around the planet. These layers shift and move in diurnal cycles, and undergo longer-term cycles of strengthening and weakening that depend on the cycles of magnetic activity on the Sun. Assessing the state of the ionosphere and finding out which bands have a path to which points on the globe used to be something that hams had to do by spinning the dial and listening for beacon stations. Beacons are stations that transmit a generally low-power signal from a fixed, know location on a regular schedule. If you can hear the beacon, chances are good that you’ve got a propagation path between you and the general area of the beacon on that frequency. While beacons are useful, they have their limits. They depend on the kindness of strangers, who devote resources to running and maintaining the beacon station. Beacons are also subject to occasional maintenance outages, so not hearing a beacon you expect does not necessarily mean that you don’t have a path between two points. But perhaps the most limiting aspect of traditional beacons is that they operate on a pull model — you have to sit down at your radio and intentionally tune into the beacon’s frequency and decode what you hear — beacons almost always use continuous wave (CW) mode with Morse code. Add to that the fact that whatever you learn about the propagation paths available to you stays pretty much within your shack, and beacons have limited utility. WSPR signal by Louis Taber, CC BY-SA 4.0 With those limitations in mind, Joe Taylor (K1JT) began working on a digital mode in 2008 specifically for exploring propagation paths. The protocol was dubbed WSPR, which of course everyone pronounces as “whisper,” which given its capabilities is an apt name indeed. WSPR is a digital mode that employs special digital signal processing algorithms to decode signals with a signal-to-noise ratio (SNR) of -28 dBm in a bandwidth of 2,500 Hz. When transmitting, WSPR sends a compressed 50-bit message that encodes the station’s callsign, the grid location, and the transmitter power. The message is modulated using frequency-shift keying at a very low bit rate — less than 1.5 baud. This means an entire message with error correction takes almost two full minutes to send. Transmissions are synchronized by the WSPR software to begin one second into each even-numbered minute, making accurate time synchronization essential. Propagation Made Visual The shape of things to come — east coast stations are hitting Antarctica on 20 meters, which means I might too in a few hours when the Sun sets over my QTH. As cool as the WSPR protocol is, the magic of WSPR comes from the “R” part of its name: reporting. This is where WSPR closes the loop that traditional beacons leave open, since WSPR client software can be configured to log any WSPR signals received and decoded by a station to a central database. WSPRnet.org is the place where all the reports go; the site contains a searchable database of all “spots” reported as well as a map that shows current contacts by many, many stations. The map on WSPRnet is admittedly a bit janky — it’s based on Google Maps, and an error dialog pops up every time you load a new view. There are other visualizations, though, but even with the issues, WSPRnet’s map is a great way to see what propagation paths may be available to you at the current time. For example, I took a quick peek at the 20-m band just now and found that from my area, I’ve got solid paths to pretty much all of North America. More importantly, I can see that I have no paths into Europe or Asia, and very little to the south into Central and South America. But, by looking at what’s going on with paths on the east coast of the US, where the sun is currently setting and which are actively reaching several stations in and just offshore of Antarctica, I might have a path to the bottom of the planet coming up as the sun sets over me. Doing My Part As I mentioned in my first weak-signals article, I’ve currently got WSJT-X running on a Raspberry Pi 4 that I have dedicated to ham radio use. WSJT-X has a built-in WSPR mode, which makes it easy to switch back and forth between exploring possible propagation paths with WSPR and exploiting that information to make actual QSOs using FT8 or one of the other supported modes. The beauty of using WSJT-X for WSPR work is that it’s basically completely automated. Depending on how you set it up, you can either be a dedicated WSPR receiving and reporting station, or you can choose to also transmit. When I’m going to be in the shack / office, which is almost always, I set up WSJT-X to transmit on WSPR with a 20% duty cycle — that is, one out of every five two-minute blocks will be dedicated to transmitting. That way, I can do my part contributing to the WSPR map — there generally aren’t many WSPR beacons operating in my part of North Idaho, so I figure this is my way of pitching in. Plus, I get the occasional bonus of nabbing a cool contact, like the aforementioned hit on DP0GVN-1, a German research vessel parked off the coast of Antarctica that I reached on the 30-m band using just five watts. Sweden, By Way of Alaska As cool as it is to know you’ve made a solid contact over a path of about 10,000 km on less power than it takes to run an LED light bulb, there’s also a lot to be said for the unusual stations you receive when you leave your WSPR station running. Case in point: the other day I glanced up at WSJT-X and noticed a strange callsign, SA6BSS. After a while of looking at callsigns you get to know which general areas they come from, and I suspected this was a “rare DX” coming from Europe, which is really hard for me to hit with my antenna from the inland Pacific Northwest. A quick lookup on QRZ.com confirmed that SA6BSS is a ham named Mikael Dagman, based in southern Sweden — cool! I quickly spun up the WSPRnet map and was surprised to see that Mikael’s station was reporting its position as coming from Alaska rather than Sweden. I zoomed in the map a little and found that the signal was coming from a grid hundreds of kilometers south of Unalaska Island in the Aleutians. What in the world would a Swedish ham be doing in the North Pacific in February? I shot Mikael a quick email about the contact, and he confirmed that I had indeed received a correct position report from his WSPR station, currently floating around the world on a party balloon! Since he released the balloon on Feb 23, it has traveled at around 11,000 meters altitude from Sweden to the Middle East, across Asia, and over the Pacific to just off the coast of Oregon. There it took a hook and headed back out to sea; as I write this it’s heading roughly in the direction of Hawaii. Literally WSPR-ing around the world — at least halfway so far. SA6BSS launched a balloon carrying a WSPR transmitter on Feb 23 that crossed the Pacific; I copied it when it was south of the Aleutians. Mikael was kind enough to include a little information on the WSPR transmitter he included on his balloon, which is completely solar-powered and weighs in at only 2.6 grams. The spareness of his design is almost comical — it’s just a GPS module, an ATMega328, and an Si5351 for the transmitter. It’s a perfect example of what can be done on a budget, which is right in line with “The $50 Ham” concept. So naturally, building a lightweight, inexpensive WSPR beacon will be the basis of the next installment in this series. #JoeTaylor #WSJT-X #Propagation #The$50Ham #WeakSignal

Agilenano - News from Agilenano from shopsnetwork (4 sites) http://feedproxy.google.com/~r/Agilenano-News/~3/71GKKpe0ScU/the-50-ham-wspr-ing-around-the-world

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evoldir · 5 years ago

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Fwd: Postdoc: InstZool_Beijing.BeetleMetagenomics

Begin forwarded message: > From: [email protected] > Subject: Postdoc: InstZool_Beijing.BeetleMetagenomics > Date: 10 May 2020 at 06:32:54 BST > To: [email protected] > > > Beijing.IOZ Chinese Academy of Sciences.BeetleMetagenomic > > Postdoctoral position, Beetle Metagenomic, Institute of Zoology, Chinese > Academy of Sciences, Beijing, China > > One full-time PIFI postdoctoral position for two years (with a possible > > extension) is available at Prof. Bai's lab from Institute of Zoology, > > Chinese Academy of Sciences, located in Beijing, P.R. China. > > Topic > Coleoptera is the most biodiversity in organic sphere. Based on > metagenomics by high-throughput sequencing, the large-scale biodiversity > assessment of beetles from different sites from China will be explored, > which can reveal the species catalogue, species richness, distribution > status, community structure and so on. The relationship of genetic > diversity, species diversity and ecological diversity were inferred too. > > The work conditions are > 1. Two year contract with a possible extension; > 2. The appointment ideally starts this June but negotiable; > 3. An annual salary to postdoctoral researchers to cover living > expenses and health insurance in China. Each selected awardee > will receive a pre-tax stipend of ￥200,000 per year. In > addition, the fellowship provides an economy-class round-trip > international travel; > 4. Be under the age of 40. > > Qualified candidates are requested to send a CV with a brief motivation > to [email protected] with a title [Postdoc Application - fullname]. > > About the Institute > Institute of Zoology (IOZ), Chinese Academy of Sciences (CAS), is a > government-funded research institution in zoological sciences. It has a > long history of over 80 years. The predecessor of IOZ was Fan Memorial > Institute of Biology founded in 1928. Many distinguished scientists > including thirteen CAS Academicians started their research career in > IOZ. Some of them are founders of various sub-disciplines of zoology > in China, such as Professor Bing Zhi, first director of IOZ and one of > the main founders of modern biology in China. Several sub-disciplines in > zoological sciences in China were derived from IOZ, such as entomology, > animal ecology, and experimental embryology. IOZ also has a long history > of service to the country with many significant contributions, such > as successful control of China’s chronic agricultural pest-locust, > control and management of other pest insects and rodents, establishment > of nature reserves in China, conservation of giant panda, crested ibis > and other endangered wildlife, reproduction and contraception, and fish > nuclear transfer. Zoological Museum of IOZ has over 8 million animal > specimens. Several field stations and research bases also play important > role in IOZ research programs. > > About the PI > Dr. Bai has been engaged in the systematics and evolution of insects, > e.g. scarabs and ice crawlers. On the basis of inheriting the > traditional taxonomy, he has opened up a new research direction of > the new taxonomy driven by new technologies such as quantification, > Big Data and Artificial Intelligence. The main academic achievements > are as follows. (1) He systematically revised the Chinese Scarabaeoidea > and Grylloblattodea, built a database on Chinese insect type specimens, > and published a new insect order, 4 new families, and more than 200 new > genera. (2) In the three key aspects of taxonomic research (character > cognition, character comparison, character evolution), new technology > innovation-driven research has been carried out, including the development > of new instruments and new software in digital and three-dimensional > technologies, the integration of quantitative geometric morphometrics > and erection on the new research paradigm. The establishment of a new > insect order, Alienoptera, and the systematic status of some important > extinction groups were revealed. The origin of dung feeding behavior > was investigated. An Intelligent Identification System of World Beetles > (BICS, https://ift.tt/3dvZeF1) was created. > > Contact > Ming BAI Ph.D. Full Professor > Principal Investigator of the Group of Morphology and Evolution of Beetles > Address: Box 92, Institute of Zoology, Chinese Academy of Sciences > No. 1, Beichen West Road, Chaoyang District, Beijing, P.R. China > Email: [email protected] > [CN] https://ift.tt/3dxVHWY > [EN] https://ift.tt/2Wjnc0L > [BICS] Beetle Intelligent Classification System: https://ift.tt/3dvZeF1 > Reprints (PDF): https://ift.tt/3cjnGtj > > "Prof. Dr. BAI Ming" > via IFTTT

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effectsdatabase · 5 years ago

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Last week's top 20 videos (2020, week 11)

Top 20 videos last week (March 8-14)

Ground Control Audio - Amaterasu V2 and Tsukuyomi Boosts (by AndyDemos)

Boss DD-8 & Slowdive Delays with Roland JC-40 | Digital Delay Demo (by Pedal Partners)

My Face Says It All! - Beetronics Swarm | Analog Fuzz Harmonizer Synth pedal (by R.J. Ronquillo)

Iconic Marshall Pedals - The Marshall Guv'nor vs Blues Breaker vs Drive Master (by intheblues)

PANAMA DEMO SONG by PAT TOMASELLI (by Carl Martin)

TC Electronic Drip Spring Reverb Bass Demo (by Bassic Gear Review)

OFFICE HOURS with andy: let's learn about BLOOPER from chase bliss audio (by Andy Othling)

Nile Rodgers plays the Wahcko @ Abbey Road Studios! (by JAM Pedals)

Darkglass Hyper Luminal ? FIRST IMPRESSION #4 (by himynameisjayme)

EarthQuaker Devices Plumes (by rigrigrigmusic)

Shift Line Twin MkIIIS | direct recording + Soyuz 017 FET (by deniki4)

Maestra Fuzz Tone - DEMO (by Diego Leanza)

BOSS GT-1000 | DREAM THEATER | PULL ME UNDER GUITAR TONES!!! (by juca2929)

Joyo Aquarius (by KytaryCZ)

Strymon Volante - soundscaping loop with Elektron Digitakt (by Delay Dude)

Electro-Harmonix - Nano Big Muff Pi - Demo (by Ryan Lutton)

Source Audio Ventris Reverb Pedal | Review (by iguitarmag)

Audio Testing Binson Echorec Model 'T7E' Serial #6753 (by Effectrode)

Tone Freak - Severe, Abunai 2, Dragonfly (by Pedalicious)

[PEDAL TESTING] Earthquaker Devices Rainbow Machine v Arturia MicroFreak (by Pedals4synths)

Overviews of the previous weeks: http://www.effectsdatabase.com/video/weekly

from Effects Database https://bit.ly/3dkj9ro

#FXDB #Effects Database

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tak4hir0 · 6 years ago

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Eight years ago, universities like MIT and Stanford first opened up free online courses to the public. Today, close to 1000 schools around the world have created thousands of free online courses, popularly known as Massive Open Online Courses or MOOCs. I’ve compiled this list of 620+ such free online courses that you can start this month. For this, I leveraged Class Central’s database of over 15,000 online courses. I’ve also included each course’s average rating. Class Central's HomepageI’ve sorted these courses into the following categories based on their difficulty level: BeginnerIntermediateAdvancedCourses that are being offered for the first time are marked as [NEW]. Many of these courses are completely self-paced. The rest will start at various times throughout the year. You can find complete lists of the technology-related courses starting later in 2020 on Class Central’s Computer Science, Data Science, and Programming subject pages. I understand this a long list and might be daunting for learners new to programming. In that case, you might find David Venturi’s recommendations for the best Data Science online courses useful — even if you’re not looking to learn Data Science. I hope to create more of these guides in the future. And finally if you have trouble figuring out how to signup for Coursera courses for free, don’t worry — I’ve written an article on how to do that, too. Beginner (175)An Introduction to Interactive Programming in Python (Part 1) from Rice University ★★★★★(3161)Elements of AI from University of Helsinki ★★★★★(202)Introduction to Computer Science and Programming Using Python from Massachusetts Institute of Technology ★★★★☆(122)Learn to Program: The Fundamentals from University of Toronto ★★★★★(105)CS50's Introduction to Computer Science from Harvard University ★★★★★(78)Ruby on Rails: An Introduction from Johns Hopkins University ★★★☆☆(56)Introduction to HTML5 from University of Michigan ★★★★☆(43)Internet History, Technology, and Security from University of Michigan ★★★★★(37)Introduction to Linux from Linux Foundation ★★★★☆(37)Intro to HTML and CSS[New] The Beauty and Joy of Computing (CS Principles), Part 1 from University of California, Berkeley[New] Introduction to Database Systems from Indian Institute of Technology Madras[New] Coding for Designers, Managers, & Entrepreneurs I from University of Virginia[New] Coding for Designers, Managers, & Entrepreneurs II from University of Virginia[New] Coding for Designers, Managers, & Entrepreneurs III from University of Virginia[New] Computational Social Science Methods from University of California, Davis[New] Creating a Great User Experience for Mobile Apps from University of Leeds[New] Computer Programming for Everyone from University of Leeds[New] Learn to Code for the Web from University of Leeds[New] Cloud Security Basics from University of MinnesotaBuild a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course) from Hebrew University of Jerusalem ★★★★★(25)[New] C for Everyone: Structured Programming from University of California, Santa Cruz[New] Introduction to Site Reliability Engineering and DevOps from Linux Foundation[New] Introduction to Web Accessibility from World Wide Web Consortium (W3C)[New] Introduction to Web Development from Raspberry Pi FoundationWeb Security Fundamentals from KU Leuven University ★★★★☆(22)Introduction to Cyber Security from The Open University ★★★★☆(20)Computer Science 101 from Stanford University ★★★★☆(17)Fundamentos TIC para profesionales de negocios: Desarrollo de Software from Universitat Politècnica de València ★★★★☆(17)Introduction to CSS3 from University of Michigan ★★★★★(14)HTML, CSS, and Javascript for Web Developers from Johns Hopkins University ★★★★★(14)Programming Basics from Indian Institute of Technology Bombay ★★☆☆☆(13)Fundamentos TIC para profesionales de negocios: Aplicaciones empresariales from Universitat Politècnica de València ★★★★★(13)Introduction to Computer Networking from Stanford University ★★★★★(12)Introduction to the Internet of Things and Embedded Systems from University of California, Irvine ★★★★☆(12)Creative Programming for Digital Media & Mobile Apps from University of London International Programmes ★★★★☆(11)Introduction to Programming for the Visual Arts with p5.js from University of California, Los Angeles ★★★★★(10)HTML5 Coding Essentials and Best Practices from World Wide Web Consortium (W3C) ★★★★☆(10)Learn to Program: Crafting Quality Code from University of Toronto ★★★★☆(9)Usable Security from University of Maryland, College Park ★★★☆☆(9)Introduction to Bootstrap - A Tutorial from Microsoft ★★★☆☆(9)Intro to Relational DatabasesLinux Command Line BasicsHow To Create a Website in a Weekend! (Project-Centered Course) from State University of New York ★★★★☆(6)Diagramas UML estructurales para la Ingeniería del Software from Universitat Politècnica de València ★★★★★(6)Introduction to jQuery from Microsoft ★★★★☆(6)Paradigms of Computer Programming – Fundamentals from Université catholique de Louvain ★★★★★(5)Paradigms of Computer Programming – Abstraction and Concurrency from Université catholique de Louvain ★★★★☆(5)HTML5 and CSS Fundamentals from World Wide Web Consortium (W3C) ★★★★☆(5)CS50's Web Programming with Python and JavaScript from Harvard University ★★★★★(4)Technical Support Fundamentals from Google ★★☆☆☆(4)Programming in Scratch from Harvey Mudd College ★★★★★(4)Introduction to Computing using Python from Georgia Institute of Technology ★★★★★(3)Web Development and Design using Wordpress from California Institute of the Arts ★★★★☆(3)Object-Oriented Programming from Indian Institute of Technology Bombay ★★★☆☆(3)Web Coding Fundamentals: HTML, CSS and Javascript from National University of Singapore ★★★★★(3)Learn to Program in Java from Microsoft ★★★★★(3)Version Control with Git from Atlassian ★★★★★(3)The Unix Workbench from Johns Hopkins University ★★★★☆(2)The Beauty and Joy of Computing - AP® CS Principles Part 1 from University of California, Berkeley ★★★★★(2)Introduction to Internet of Things from Indian Institute of Technology, Kharagpur ★★★★★(2)Introduction to the Internet of Things (IoT) (COMING 2020) from Curtin University ★★★☆☆(2)Linux Basics: The Command Line Interface from Dartmouth ★★★★★(2)C Programming: Modular Programming and Memory Management from Dartmouth ★★★★★(2)Think. Create. 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to Computer Programming from University of London International Programmes ★★★★★(1)How Computers Work from University of London International Programmes ★★★★★(1)Software Engineering: Introduction from The University of British Columbia ★★★★★(1)Python Programming Essentials from Rice University ★★★★★(1)Introduction to Web Development from University of California, Davis ★★★☆☆(1)Web Design: Strategy and Information Architecture from California Institute of the Arts ★★★★★(1)Cyber Security Economics from Delft University of Technology ★★☆☆☆(1)C Programming: Language Foundations from Institut Mines-Télécom ★★★★★(1)C Programming: Pointers and Memory Management from Dartmouth ★★★★★(1)C Programming: Using Linux Tools and Libraries from Dartmouth ★★★★★(1)Creative Coding from New York University (NYU) ★★★★☆(1)Lernen objekt-orientierter Programmierung from Technische Universität München (Technical University of Munich) ★★★★★(1)C for Everyone: Programming Fundamentals from University of California, Santa Cruz ★★★★☆(1)Computing: Art, Magic, Science from ETH Zurich ★★★★☆(1)Computing Form and Shape: Python Programming with the Rhinoscript Library from Rhode Island School of Design ★★★★★(1)MyCS: Computer Science for Beginners from Harvey Mudd College ★★★☆☆(1)How Computers Work: Demystifying Computation from Raspberry Pi Foundation ★★☆☆☆(1)Blockchain in the Energy Sector from InnoEnergy ★★☆☆☆(1)ES6 - JavaScript ImprovedCS50 for Lawyers from Harvard UniversityPrinciples of Computing from Stanford UniversityHacker Tools from Massachusetts Institute of TechnologyComputational Thinking for Problem Solving from University of PennsylvaniaThe Blockchain System from University of California, IrvineThe Blockchain from University of California, IrvineThe Beauty and Joy of Computing - AP® CS Principles Part 2 from University of California, BerkeleyThe Beauty and Joy of Computing (CS Principles), Part 3 from University of California, BerkeleyThe Beauty and Joy of Computing (CS Principles), Part 4 from University of California, BerkeleyFoundations to Computer Systems Design from Indian Institute of Technology MadrasProgramming in C++ from Indian Institute of Technology, KharagpurProblem Solving through Programming in C from Indian Institute of Technology, KharagpurAn Introduction to Programming through C++ from Indian Institute of Technology BombayProgramming Fundamentals from Duke UniversityInteracting with the System and Managing Memory from Duke UniversityComputer Science: Programming with a Purpose from Princeton UniversityIntroduction to Internationalization and Localization from University of WashingtonIntroduction to Cybersecurity from University of WashingtonProgramming, Data Structures And Algorithms Using Python from Chennai Mathematical InstituteSoftware testing from Indian Institute of Technology BangalorePrinciples of Secure Coding from University of California, DavisIdentifying Security Vulnerabilities from University of California, DavisВведение в базы данных from St. Petersburg State Polytechnic UniversityScratch: Programmeren voor kinderen (8+) from Delft University of TechnologyAP Computer Science A: Java Programming Loops and Data Structures from Purdue UniversityAP Computer Science A: Java Programming Polymorphism and Advanced Data Structures from Purdue UniversityAP Computer Science A: Java Programming Classes and Objects from Purdue UniversityProgrammazione I from University of Naples Federico IILaTeX for Students, Engineers, and Scientists from Indian Institute of Technology BombayОсновы проектирования приложений интернета вещей from Moscow Institute of Physics and TechnologyТонкости верстки from Moscow Institute of Physics and TechnologySoftware Design as an Element of the Software Development Lifecycle from University of Colorado SystemProactive Computer Security from University of Colorado SystemTCP/IP and Advanced Topics from University of Colorado SystemSoftware Design as an Abstraction from University of Colorado SystemSoftware Design Methods and Tools from University of Colorado SystemIntroduction to Cybersecurity for Business from University of Colorado SystemIntroduction to the Internet of Things from Universitat Politècnica de ValènciaБазы данных (Databases) from Saint Petersburg State UniversityCyber Security Basics: A Hands-on Approach from Universidad Carlos iii de MadridDeep Learning for Business from Yonsei UniversityIntroduction to TCP/IP from Yonsei UniversityVideo Game Design and Balance from Rochester Institute of TechnologyProblem Solving, Python Programming, and Video Games from University of AlbertaBlockchain 360: A State of the Art for Professionals from EIT DigitalGetting Started with AWS Machine Learning from Amazon Web ServicesAWS Fundamentals: Addressing Security Risk from Amazon Web ServicesIntroduzione a LaTeX from University of Modena and Reggio EmiliaC Programming: Getting Started from DartmouthC Programming: Advanced Data Types from DartmouthIntrodução à Ciência da Computação com Python Parte 1 from Universidade de São PauloIntrodução à Ciência da Computação com Python Parte 2 from Universidade de São PauloWeb Accessibility from GoogleProgramación Orientada a Objetos con Python from Universidad AustralDiseñando páginas web con Bootstrap 4 from Universidad AustralIntroducción a la programación en C: Instrucciones de control y ficheros de texto from Universidad Autónoma de MadridIntroduction to Design Thinking from MicrosoftCSS Basics from MicrosoftWriting Professional Code from MicrosoftObject Oriented Programming in Java from MicrosoftHow Entrepreneurs in Emerging Markets can master the Blockchain Technology from University of Cape TownCyber Attack Countermeasures from New York University (NYU)Introduction to Cyber Attacks from New York University (NYU)Introducción a la programación en Python I: Aprendiendo a programar con Python from Pontificia Universidad Católica de ChileBlockchain: Understanding Its Uses and Implications from Linux FoundationIntroduction to Open Source Networking Technologies from Linux FoundationInternet Connection: How to Get Online? from CiscoHome Networking Basics from CiscoComputing: Art, Magic, Science - Part II from ETH ZurichMobile Computing with App Inventor – CS Principles from The University of Warwickプログラミングしながら学ぶコンピュータサイエンス入門 : Introduction to Computer Science and Programming from Tokyo Institute of TechnologyL'intelligence artificielle pour les managers et leurs équipes from CNAMIntroduction to MongoDB from MongoDB UniversityProgramación Orientada a Objetos (POO) from MéxicoXComputer Networks from Devi Ahilya Viswavidyalaya, IndoreHTTP & Web ServersIntroduction to Virtual RealityUsing Databases with Python from University of Michigan ★★★★★(1462)Machine Learning from Stanford University ★★★★★(352)Introduction to Agent-based Modeling from Santa Fe Institute ★★★★★(78)Machine Learning for Musicians and Artists from Goldsmiths, University of London ★★★★★(78)Divide 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★★★★★(2)Software Testing Management from University System of Maryland ★★☆☆☆(2)Browser Rendering Optimization from Google ★★★★☆(2)Client-Server Communication from Google ★★★★★(2)Developing International Software, Part 1 from Microsoft ★★★★☆(2)Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course) from Hebrew University of Jerusalem ★★★★★(2)Approximation Algorithms Part I from École normale supérieure ★★★★★(2)SQL for Data AnalysisNetworking for Web DevelopersComputation Structures 2: Computer Architecture from Massachusetts Institute of Technology ★★★★☆(1)Computational Thinking for Modeling and Simulation from Massachusetts Institute of Technology ★★☆☆☆(1)Software Development Fundamentals from University of Pennsylvania ★★★☆☆(1)Advanced Algorithms and Complexity from University of California, San Diego ★★★☆☆(1)Bitcoin and Cryptocurrencies from University of California, Berkeley ★★★★★(1)Database Systems Concepts & Design from Georgia Institute of 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shirlleycoyle · 6 years ago

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Hackers Dissect ‘Mr. Robot’ Season 4 Episode 9: ‘Conflict’

Episode 9 of Mr. Robot’s final season was not only amazing plot-wise but also happily filled with hacks. We discussed [SPOILERS, obvs] IMSI catchers, Raspberry Pis, PGP, phishing telcos and stealing cryptocurrency. (The chat transcript has been edited for brevity, clarity, and chronology.)

This week’s team of experts includes:

Em Best: a former hacker and current journalist and transparency advocate with a specialty in counterintelligence and national security.

Trammell Hudson: a security researcher who likes to take things apart.

Micah Lee: a technologist with a focus on operational security, source protection, privacy and cryptography, as well as Director of Information Security at The Intercept.

Freddy Martinez: a technologist and public records expert. He serves as a Director for the Chicago-based Lucy Parsons Labs.

Yael Grauer (moderator): an investigative tech reporter covering online privacy and security, digital freedom, mass surveillance and hacking.

IMSI Catchers

Yael: I thought it was clever of Darlene and Elliot/Mr. Robot to use IMSI catchers.

Micah: I've never had a chance to play with one for real, But they're also referred to as "cell site simulators" because they simulate cell phone towers. Your phone tries to connect to the tower with the strongest signal, so in order to do a man-in-the-middle attack against cell phones, you just need to broadcast a stronger signal than the nearest cell phone tower and nearby phones will connect to your IMSI catcher instead. Then, you forward the traffic to the real cell phone tower, so the phones will still work, but you can spy on/modify all the traffic in the meantime

Yael: I’ve written about them before, but it was about law enforcement use of them for surveillance. They can’t intercept Signal messages, right? So if Deus Group just read a Freedom of the Press Foundation guide, Darlene and Elliot's plot would be foiled.

Em: It will intercept the Signal data, but messages are encrypted until they reach the recipient’s device, so it's not enough to just intercept it.

Micah: Their plot wouldn't have been foiled because Cyprus National Bank still sends two-factor authentication codes (2FA) over unencrypted SMS. I thought it was a nice touch how much Raspberry Pis were represented. In the first scene, in the hotel, the camera panned across some Raspberry Pis, and Darlene was logged in to a Raspberry Pi during the garage door hack.

Image: USA

Freddy: The Raspberry Pi 3 uses USB 3.0, which is fast enough to run a homemade IMSI Catcher.

Em: Homemade antennas are fun. =)

Yael: Oh, did they make their own?

Freddy: You can make your own. I think those are limeSDRs.

Price’s Last Stand

Yael: We had Price in yet another hostage situation.

Em: Yeah, he handled it very well. The traditional ways of getting out of a hostage situation weren't going to work there, but he did several important things for the situation he was in:

1. He kept calm. This is the most important thing. If he had panicked he'd have been killed a lot sooner.

2. He kept Whiterose off balance. His teasing and taunting was beautiful to watch, especially the "wind in his hair" bit.

3. He didn’t give up any important info to accomplish number 2.

4. He provoked Whiterose when they were both visible outside. Walking away after saying what he said almost guaranteed not only that he'd be shot there but that Whiterose would do it—in public.

Yael: My favorite taunts were, “it’s bad management when your best employees either walk off the job or blow their brains out,” and “all this over a little pipsqueak in a hoodie.” I think Price kind of didn't care if he died after Angela died.

Em: I think he didn't care if he died but he wanted to get Whiterose first. Once he handed off the drive (which he did right before going to the meeting), he had accepted his fate.

Freddy: You can't control people who have nothing to lose.

Em: Or to gain.

Micah: I like how Mr. Robot explained why he was there in the hotel room, instead of Elliot, by saying, "Life throws you an error code like that, you don't have the luxury of a fucking pop-up explanation."

The Bank Heist

Yael: Okay, so let’s talk about the hack. They said they needed to correlate phone numbers with bank account numbers to initiate the money transfers.

Em: They needed that for the script so they'd know which 2FA code to use for which request. Otherwise they'd have to brute-force it for each account, and that'd likely trigger a safety measure.

Micah: So Elliot and Darlene seem to have a SQL database from the bank, and their database includes account numbers, first name, last name, and hashed phone numbers. They needed to use the IMSI catcher (and the cell phone tower hack) to learn everyone's phone numbers, so they could hash them and then lookup the hashes in the bank database until they had phone numbers for all 100 accounts

Em: That's pretty realistic, FWIW. An equivalent of that was one of the first things we pulled from Phineas Fisher’s hack of Cayman National Bank and Trust (much to the dismay of some of the account holders).

Trammell: There was a CCC talk about nation-states doing 2FA intercept on Telegram password resets.

Micah: So, the venue changed. They got a hotel room within line of sight of the first venue, and they expected all Deus Group members to show up there, but the location moved. Mr. Robot figured out that Whiterose was at the first venue, though. So Darlene went to the second venue with the IMSI catcher, and Mr. Robot/Elliot stayed at the first venue to try to focus on just Whiterose's phone number. So all that hacking that Mr. Robot was doing, he was hacking into the telecom company that owns the closest cell phone tower.

Yael: How did Whiterose figure out that they needed a venue change and he had to get at Price?

Freddy: She said that Elliot disappeared right after Price said he was retiring, and that Price asked for a Deus Group meeting on Xmas, which was suspicious.

Micah: Elliot had a dump of Tyrell Wellick's phone, and it looks like he and Darlene imported Tyrell's Firefox passwords into Iceweasel, and then looked through his Google calendar. There was a password-protected attachment in one calendar event, and the thing I don't quite understand is how they got the password. I think Darlene sent it to him in Signal Desktop, but I don't know how they knew what it was.

Image: USA

Freddy: It almost looked like a script to execute, but I couldn't tell. Maybe it was a pop-up?

Yael: I think it directed to a password-protected webpage hosted on some kind of private server. So I guess Whiterose got sloppy and forgot to take Tyrell off the list of people getting the venue change.

Micah: Tyrell was the guest of honor; he was getting named new CEO of Evil Corp. She just didn't realize he was dead.

Yael: I'm sort of stunned Whiterose didn't know Tyrell was dead or at least missing, with their surveillance..

Em: It happened in the middle of nowhere and the FBI didn't handle the crime scene, so the search around the van etc. was limited.

Yael: Yeah, but they had eyes on Tyrell and would've noticed he was missing after.

Hacking The Cell Tower

Micah: Okay, so let's talk about the cell phone tower hack.

Yael: Elliot was phishing telecom employees to try to get access to the cell phone tower because he didn't have the cell-site simulator.

Micah: Yeah, exactly. He needed to hack the cell phone tower, because that would give him the same access as if he had his own IMSI catcher. Once he got credentials from his phishing, he was trying to re-use them to login to the telco's VPN.

Yael: So what's easier and more reliable, building your own IMSI catcher or phishing telcos?

Freddy: Probably the latter, to be quite honest.

Micah: Also, did you notice that when he was phishing the telco, he scraped PGP keyservers to get a list of their email addresses? That's not realistic, though. Nobody in real life uses PGP. Except for The Intercept, but it's painful. I'm not sure all these gallatintelco.com employees would have keys on the keyservers.

Em: It would only take one person uploading their set of public keys to get them there. Keyservers verifying permission of the owner to list the keys is relatively new, as far as I can tell.

Yael: Why does he need their public keys, though? How does this work?

Em: He didn't need the keys, he just needed the email addresses associated with them so he could phish the telco employees. He was basically IDing which email addresses were being used—rather than trying to get a list of employees and then figuring out the company’s email address format (e.g. [email protected]).

Trammell: And he was hoping that one of them used the same password on the cell site infrastructure that they used to login in response to the phishing email. The first few didn't, but eventually one of them did. Someone always does…

Micah: It looks like USA Network didn't actually generate all these PGP keys. They're not in the SKS pool.

Trammell: Elliot’s ECorp key from the 2017 season is on the key servers. Or someone like me ran a key generator to spoof the 32-bit key id and uploaded it to the server and then registered e-corp.co.uk to complete the fake. 32-bit PGP key IDs are short enough that you can find a key that matches .

Image: USA

Freddy: I don't know any company, much less a telco, that requires you to publish PGP keys online.

Micah: The Intercept.

Yael: I think also the Electronic Frontier Foundation.

Freddy: When I used to work in cybersecurity I think I was the only one with a PGP key.

Micah: I think it's much more likely that a telco wouldn't be using any email encryption. But if they did, they'd use S/MIME, which is like PGP but centrally managed and therefore popular in the corporate/government world, and simpler to use.

Yael: I feel like I got PGP for street cred to get hackers I wanted to interview to talk to me vs. actually using it.

Micah: I used PGP to help facilitate the Snowden leak. Good times.

Garage Door Hack

Yael: Let’s talk about the garage door hack.

Trammell: Based on the scripts I think Darlene was using a HackRF. In that screenshot you can see that she has logged into a Pi with the HackRF and captured the signal while the security goon was pressing "close."

Image: USA

Bank Transfer

Micah: So as far as the bank transfer goes, I think there are some pieces of the puzzle that aren't quite clear in this episode. Last episode there was a snippet of python that involved mixing cryptocurrency. So I think they must have done something like this. Once they could spy on everyone's SMS, they initiated bank transfers for everyone, to transfer their money into some other bank account. When all the Deus Group members got SMS messages, they intercepted the 2FA codes and sent them to the bank to complete the transfers.

Freddy: Yeah but even then, you can't just do a bulk transfer of billions of dollars into cryptocurrency?

Micah: On the other end, the receiving account must have automatically been hooked into a cryptocurrency exchange, immediately selling all of that money for cryptocurrency, and then, immediately mixing that cryptocurrency.

Freddy: And do what with it? Someone will notice a trillion dollars being dumped into BTC (cough cough TETHER). Also, there is a cost to buying that cryptocurrency and you couldn't get the network throughput for syncing the transfers. Syncing a blockchain is much slower compared to something like SWIFT.

Em: Cryptocurrency for this is not realistic.

Micah: Before it could get exchanged for cryptocurrency, they had to have done a SWIFT transfer to a different bank. That must have been the first step.

Freddy: I am just saying, where did the money go? The cryptocurrency stuff is like "fancy Hollywood magic."

Micah: So maybe the money is all just sitting in like, a Swiss bank account or something that they set up just for this hack, and they're slowly working on moving it into cryptocurrency

Em: It would have to be several SWIFT transfers or things would not be accepted on the other end. Moving it all into one account wouldn't help, because it would be seized and returned.

Micah: It's a separate SWIFT transfer account for each Deus Group member, but still.

Freddy: Moving that much money would have tripped all sorts of liquidity rules at the banks.

Em: Yes, and the receiving accounts would have had issues with it. Even if all translated to BTC etc., they'd have to distribute it very widely to prevent it from being returned. A well set-up bank would also have additional confirmations required for transfers that empty out accounts or are over a certain amount.

Trammell: The liquidity of any of the cryptocurrency exchanges wouldn't be able to handle any significant buy-in like that. It would be like the flash crash in reverse.

Yael: Wait, I thought BTC couldn't get returned.

Em: Anything can be seized.

Micah: Yeah, I think once they get successfully get it into BTC, the only way they could seize it is by seizing the actual wallet, e.g. the secret keys.

Em: The exchange(s) are a vulnerable point, I think. Cryptocurrency would be harder to seize than a traditional account, if no one ever did anything with it. It'd have to sit there, dead.

Micah: If Elliot and Darlene can maintain their anonymity from the financial fraud investigators, they won't have any way of knowing who to seize it from. Also, if they don't actually want the money, they can just destroy the wallet.

Trammell: If they are doing the "K Foundation" attack rather than a "Robin Hood" approach, they could also transfer the BTC to a random address (or a symbolic one) where there is no secret key.

Em: There is one thing we're overlooking in the discussion of cryptocurrency transfers:

eCoin. We don't know how eCoin worked, but it's likely that it was more integrated with Cyprus Nat'l Bank than BTC et al is with most traditional banks.

Trammell: Good point—we're hypothesizing about how eCoin might work, as compared to real cryptocurrencies. (If eCoin is even anything other than a fiat currency issues by Evil Corp).

Em: I would be amazed if the bank wasn't integrated with it. And remember, eCoin wallets aren't secure against Evil Corp. They had the ability to look in every wallet etc.

Freddy: Presumably they also stole all the money from Price/Tyrell, too. So what's to stop them from bankrupting Evil Corp?

Trammell: I'm surprised that such rich people would have only one bank account. Their funds only have FDIC insurance up to $250k.

Em: What does FDIC insurance matter when the accounts are owned by the people who own the government(s)?

Freddy: Or for off-shore bank accounts.

Trammell: A more realistic response from Whiterose would be "oh, there's more where that came from."

Em: I think that's besides the point, considering the power dynamics at play.

Trammell: Offshore, different banks, different countries, etc. Single points of failure are so very dangerous.

Em: Whiterose would have been totally humiliated, all her data and everyone else's gone, their money taken—why would they give her more? The goal wasn't to bankrupt the members of the Deus Group but to bankrupt the Deus Group. Fsociety made Whiterose and the Dark Army bleed in a way that made them no longer appear invulnerable. Who would want to work with them then? But even arguendo, Whiterose would know the funds were gone for the immediate future and that'd ruin the Congo plan.

Darlene

Micah: I like that in the video Darlene told everyone the address of the Deus Group meeting, so that protestors showed up and stalled them from leaving long enough to complete the hack

Yael: haha yeah that was a fun distraction

Trammell: F L A S H M O B

Freddy: The only thing that rich people understand is an unruly mob.

Micah: Did you also notice the billboard for the fictional NBC TV show about fsociety called SHIFT+CONTROL?

Image: USA

Yael: Good name!

Micah: And the very last scene: Whiterose is putting on makeup while it appears a SWAT team is raiding her mansion and there's firefight going on? I think Whiterose is done.

Em: It's hard to tell. Zhang is done, definitely. Whiterose might not be. Though probably, given how close we are to the end of the series.

Yael: I was surprised when Price got shot. I knew he was gonna die, but didn’t expect it like that.

Em: He did such a good job of provoking Whiterose. It was beautiful.

Yael: That was a great episode. I was glad the hack finally happened and also that Darlene had a pivotal role in it. For Dom.

Hackers Dissect ‘Mr. Robot’ Season 4 Episode 9: ‘Conflict’ syndicated from https://triviaqaweb.wordpress.com/feed/

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rafi1228 · 5 years ago

Link

Learn about Anaconda, PyCharm, Networking, Socket Programming, ChatBot App, Database and Chat App, Numpy in details.

What you’ll learn

Learn in-built standard modules in python like datetime, math, statistics etc.

Learn Networking using sockets, APIs for twitter and emails.

Learn Data science modules for IoT such as numpy, scipy, pandas, matplotlib.

Finally we will learn Multi-threading and Exception handling.

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A Computer or a laptop

Description

Please note that There are four courses in this series. They are as follows:

1st Course: Python for IoT Tutorials

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3rd Course: IoT (Internet of Things) Automation with ESP8266

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We are now at “2nd Course: Advanced Python for IoT & IoT Based Data Analysis”. This part will deal more with python concepts. We will be learning in-built standard modules in python like datetime, math, statistics etc. Then we will cover Networking using sockets, APIs for twitter and emails. Then we will get in to Data science modules for IoT such as numpy, scipy, pandas, matplotlib. Finally we will learn Multi-threading and Exception handling.

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The post IoT#2: Advanced Python for IoT and Numpy appeared first on Free Course Lab.

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juniperpublishersoceanography · 5 years ago

Text

Mapping the Different Planktonic Groups at One of the Egyptian Bays along Mediterranean Coast- Juniper publishers

Abstract

Introduction

Material and Methods

Study area

Zooplankton samples

N= (n * v) / (V * 5)

V= πr2.d

Where;

N: Total number of zooplankton per cubic meter.

n: Average number of zooplankton in 5ml of the sample.

v: Volume of concentrated sample (100ml).

V: Volume of total water filtered (m3).

d: Length of the traction by the net.

Data analysis

Diversity index was estimated according to Shannon & Weaver [51] as follows:

H = - Σ Pi ln Pi

Where;

Pi = n/N

Pi: is the proportion of a species number (n) to the total number of zooplankton (N).

Results

Diversity of zooplankton groups in the bay

Relative contribution (%) of different groups

Dynamics of zooplankton groups in the bay (Zooplankton groups distributions)

Zooplankton communities showed wide seasonal variations at El- Mex Bay, the following data described these fluctuations (Figure 3-7).

Diversity index

Discussion

Nematods represented by 0.7 % of the total zooplankton with an average of 65 organisms/m3. Nemeth-Katona [76] considered that the presence of nematodes is an indication of the final stage of contamination with sewage, the ultimate putrefaction of water: hydrogen sulphide indicator. Cladocera are considered to be important in the economy of the area because of their relation to pelagic fisheries and are believed to play an important role in the phosphorus regenerate [77]. during the study period Cladocera represented by 0.6% of the total zooplankton with total average number were 23 organisms/ m3 dominated by Evadne spinifera, Podon polyphemoides and P leuckarti and Moina micruraflourished during winter and spring, their minimum values during summer, occurred intermittently at the sampled stations. Although salinity seems to impact the spatial distribution of Cladocera at El-Mex Bay the freshwater species Moina micrura was recorded at some sampled stations indication it is tolerance of wide salinity. Moina micrura is a common species in eutrophic water and can be indicator of eutrophication [78]. Food concentration may affect growth and reproduction of cladocerans [79].

Conclusion

To Know More About Journal of Oceanography Please Click on: https://juniperpublishers.com/ofoaj/index.php

#Aquaculture #Coral reef ecology #Ecotoxicology #Juniper publishers group #oceanography articles

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robertbryantblog · 6 years ago

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itsjohnleeblog · 6 years ago

Text

A smart home fingerprint identification access control system design-fingerprint module of Guangzhou Zhongyi Technology Co., Ltd

The uniqueness and stability of fingerprints make it one of the widely used biometric technologies. The design of smart home fingerprint identification access control system introduced by Xiaobian uses FPI fingerprint identification module, combined with Linux design, to achieve accurate and fast. Complete the authentication to realize the function of opening and closing the door and the alarm function of timing.

Before introducing the design, let's review the principles of fingerprint recognition.

First, the technical principle of fingerprint recognition

The technical principle of fingerprint recognition is to find out whether the fingerprint data matches the fingerprint collection from the fingerprint database, and achieve the purpose of switching the door lock by distinguishing the identity. The basic principle is shown in Figure 1. The fingerprint identification system consists of fingerprint image acquisition, fingerprint image preprocessing, fingerprint feature extraction, fingerprint feature matching, and feature database. Fingerprint image preprocessing uses Gabor filtering method to perform grayscale filtering to denoise. After filtering the image, it is binarized to filter out or correct various noises. The fingerprint feature extraction is based on the statistical analysis of the neighbors of the point 8. The feature points are obtained by calculating the CN (Croosing Number). The process of fingerprint feature matching is a process of calculating the similarity degree of two fingerprints. Before fingerprint matching, different fingerprint images must be calibrated to find the best transformation between the input feature point set and the template feature point set.

The fingerprint identification system can be roughly divided into two parts: fingerprint registration and fingerprint comparison. Fingerprint registration mainly includes fingerprint collection, fingerprint image preprocessing, feature point extraction and feature value storage. The first 3 steps of the fingerprint comparison are exactly the same as the fingerprint registration. After the feature points are extracted, the generated fingerprint feature values will be matched with the feature values stored in the fingerprint feature database, and the matching result will be output.

Second, fingerprint recognition access control hardware principle

The fingerprint identification access control system designed in this paper is mainly composed of FPI fingerprint identification module, Raspberry Pi main control module and AVR module.

The three-party communication realizes the fingerprint input and matching of the user, and the switch of the door lock, and monitors the state of the door lock by sending an email.

The powerful image processing function of the FPI fingerprint identification module is very sensitive to fingerprint recognition, and timely processes the received fingerprint information and communicates with the Raspberry Pi. The Raspberry Pi module controls the AVR to detect the switch status and switch the door lock on the one hand, and controls the FPI fingerprint entry and matching on the other hand, and establishes a database to record user information on the Raspberry Pi. The controller AVR feeds back to the switch state of the Raspberry Pi door, and controls the motor to open and close the door lock, which enhances the hardware expansion and can monitor the door in more aspects through hardware.

In addition, the wireless communication module is used to avoid the damage of the original door lock structure caused by excessive wiring, and the hardware composition of the system is convenient and fast.

Fingerprint identification module

The fingerprint module is based on TI's TMS320VC5509 advanced digital DSP processor as the main core, and the chip structure block diagram is shown in Figure 3. High-precision optical acquisition head (TFS-D0307), high-speed, stable; standard UART interface communication, standard 8-byte communication protocol, FPI finish processing the received fingerprint information, and communicate with the Raspberry Pi main control module.

Image acquisition chip

The image acquisition chip FPC1011F is integrated on the FPI chip. The FPC1011F fingerprint sensor is a capacitive semiconductor sensor device. The capacitive fingerprint sensor utilizes a reflective detection technology and belongs to a planar acquisition fingerprint sensor. Compared with the traditional capacitive sensor, it collects the dermis layer of the finger and has good applicability to wet and dry fingers. FPC1011F fingerprint acquisition principle: FPC1011F fingerprint sensor is composed of 152 × 200 sensor arrays, each array is a metal electrode, which acts as a pole of the capacitor, and the corresponding point of the finger on the sensing surface acts as another The working principle is based on a capacitive sensor with variable pole spacing. The capacitance is determined by equation (1): (where: C is the capacitance; d is the plate spacing; ε0 is the vacuum dielectric constant; εr is The relative dielectric constant of the medium between the plates; s is the effective area of the plate)

When the finger touches the sensor conductive frame, it can be known from equation (1) that the valley and the ridge have different capacitance values C due to the different distance from the sensor array, and the operational amplifier circuit forms different voltage values through the internal A/. D conversion to obtain high quality digital fingerprint images.

processor

The main processor used in this system is the 32-bit fixed-point high-speed digital DSP processor of TMS320VC5509. The hardware of the development board includes: USB2.0 FullSpeed interface for transmitting high-speed data such as images and video; 1M BytesFLASH for off-chip expansion; RTL8019AS network interface The chip realizes the Ethernet communication Ethernet circuit; the development interface: UART (RS232) realizes communication with the host computer; 2 channels of 10-bit A/D input interface.

Master module

The Raspberry Pi, the main control module used in the system, replaces the bulky computer to achieve control functions. The Raspberry Pi is an ARM-based operating system with an open source Linux system. It comes with a 700MHz processor, SD card and Ethernet support, two USB ports, and HDMI and RCA output support. On the one hand, the Raspberry Pi controls the AVR to detect the switch status of the door and switch the door lock. On the other hand, it controls the FPI fingerprint entry and matching and establishes a database to record user information on the Raspberry Pi.

With these hardware, embedded development can be carried out, and the hardware system of the fingerprint identification system can be quickly established.

Third, fingerprint identification access control system software development

The system is based on the Linux operating system, and the automatic fingerprint identification system is transplanted to the embedded Linux. The software design of the fingerprint identification system is carried out on Linux. The software design of the fingerprint identification system includes four aspects: the upper computer communicates with the AVR serial port, the upper computer and The fingerprint module serial communication, maintenance MYSQL and script send alarms.

1, the process of fingerprint identification

As shown in Figure 4, first initialize the serial port, open the serial device 0, 1, set the serial port parameters, restore the serial port unblocked state, and perform the user selection function after the serial port is successfully initialized: register the opening account or register the closing account or run the access control service [ N/C/R]. After selecting the system function N, the newly opened door user is registered, and the same fingerprint is acquired for 3 times. Compared with the traditional image acquisition, the problem that the registered fingerprint is not refined and the identification is not easy to identify is eliminated. . After the fingerprint is successfully collected, the user's personal information is input, the new ID number from the upper computer database is registered, and the user fingerprint information is stored in the database, and then whether to continue adding the user is selected. Similarly, the user selects the system function C to complete the operation of registering the closed user.

After the user selects the system function R, the access control service is run. On the one hand, the AVR queries the current door lock state, for example, assigns the door opening command to the matching state of the door. If the fingerprint matching operation FPI and the door match state are the same, the relay receives the AVR from the AVR. The door opening command drives the motor to perform the door opening action, and records the time at that time, adding a new user usage record to the local database and writing it into the log. In the same way, the closing command is executed. On the other hand, the AVR queries the current motor current level, and sends the real-time switch status of the door lock to the user by executing the switch door action and the current door lock motor current state by means of mail, realizing real-time monitoring of the door, greatly enhancing the access control system. safety.

2. Sending of alarm mail

The ARM on the Raspberry Pi receives the query information from the AVR periodically to the access control state and current state through the RS 232 serial port, and writes a shell script program, which is transmitted to the mail sending module through the serial port by using wifi, and sends the alarm content to the specified user mailbox. It is time to monitor the status of the door lock. The procedure is as follows:

This part completes the function of packaging the information and sending the alarm content to the specified mailbox. The AVR periodically detects the state of the door and the current current state. When no one performs the opening and closing operation, the content of the door.log is “0”. When someone performs the opening and closing operation or the current exceeds a certain value, the door.log content is “ 1", wherein the switch door lock includes two situations: one is that the registered user successfully realizes the switch door lock through fingerprint recognition; the other is that the unregistered user fails the fingerprint recognition but opens the door lock. The folder calls this data from the database and sends the data to the mailbox of the specified user, and then the door.log changes to "0" again, thus looping through the state of the gate.

The ARM on the Raspberry Pi receives the query information from the AVR periodically to the access control state and current state through the RS232 serial port, and writes a shell script program, which is transmitted to the mail sending module through the serial port by using wifi, and sends the alarm content to the designated user mailbox. The status of the door lock is monitored periodically.

Fourth, fingerprint identification access control system test

In order to verify the performance of the fingerprint recognition access control system, open the Linux program, register 4 different fingerprints, and then use different fingers for fingerprint recognition test. Observe the action of the actuator when the fingerprint recognition succeeds and fails, and test the contents of the mail body for 50 times.

The contents of the mail include ID, Name, Action, and Date. The first seven lines are the registered users who successfully realize the switch door lock through fingerprint recognition, so their ID number and name information will be in the mail, and the last line of user fingerprint recognition fails but the door lock is opened, so the mail will be Their ID and name are set to NULL, alerting the administrator to pay special attention to the status of the door lock at the time to achieve the administrator's timing monitoring of the door status.

V. Summary

Based on the fingerprint recognition technology, the FPI fingerprint identification module is combined with Linux to design the fingerprint recognition access control system. One of the features of the design is based on the Linux operating system, establish a concurrent execution environment, improve the CPU utilization, and use the Raspberry Pi master module and wireless. The communication module makes the whole structure simpler and has a significant improvement in system performance. Another feature is the timing detection of the door lock status and the use of wireless communication to send alarm messages to the user, greatly enhancing the security of the door lock. The practical test results show that the system runs well, can carry out reliable and safe fingerprint identification, and accurately and quickly complete the verification of personal identity to realize the function of opening and closing the door and the fast and timely mail alarm operation. In the subsequent work, the system can improve the stability of the existing program to improve the performance of the system to make the fingerprint door lock function more perfect.

Guangzhou Zhongyi Technology Co.,Ltd-fingerprint module, fingerprint sensor

http://www.zyjjhome.com/

#fingerprint module

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