#exploratory factorial analysis

[francescolelli]

Agency in Human-Smart Device Relationships: An Exploratory Study

This is a short preview of the article: Can User of IoT technology be more then "just user"? How do they relate to technology? User and Device Agency Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the

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If you are looking for ideas for tweet or re-blog this post you may want to consider the following hashtags:

Hashtags: #Agency, #DeviceAgency, #ExploratoryFactorialAnalysis, #HumanComputerInteraction, #SmartDevices, #Survey, #UserAgency

The Hashtags of the Categories are: #HCI, #InternetofThings, #Publication, #Research, #SoftwareEngineering

Agency in Human-Smart Device Relationships: An Exploratory Study is available at the following link: https://francescolelli.info/publication/agency-in-human-smart-device-relationships-an-exploratory-study/ You will find more information, stories, examples, data, opinions and scientific papers as part of a collection of articles about Information Management, Computer Science, Economics, Finance and More.

The title of the full article is: Agency in Human-Smart Device Relationships: An Exploratory Study

It belong to the following categories: HCI, Internet of Things, Publication, Research, Software Engineering

The most relevant keywords are: Agency, device agency, exploratory factorial analysis, Human-Computer Interaction, smart devices, survey, user agency

It has been published by Francesco Lelli at Francesco Lelli a blog about Information Management, Computer Science, Finance, Economics and nearby ideas and opinions

Can User of IoT technology be more then "just user"? How do they relate to technology? User and Device Agency Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the

Hope you will find it interesting and that it will help you in your journey

Can User of IoT technology be more then “just user”? How do they relate to technology? Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the concept of agency to capture aspects of user’s sense of mastery…

[azuresynapseanalytics]

The Best Azure Synapse Analytics Online Training | Hyderabad

Components of Azure Synapse Analytics | 2024

Introduction:

Azure Synapse Analytics is an integrated analytics service offered by Microsoft Azure, designed to bring together data integration, enterprise data warehousing, and big data analytics. It is a comprehensive platform that allows organizations to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. The main components of Azure Synapse Analytics include Synapse SQL, Synapse Spark, Synapse Data Integration, and Synapse Studio. These components work together to provide a seamless and unified experience for data professionals. Let's explore each of these components in detail.

1. Synapse SQL

Synapse SQL is the core data warehousing component of Azure Synapse Analytics. It provides both provisioned (dedicated) and on-demand (server less) resources for SQL-based analytics. The provisioned resources, known as dedicated SQL pools, offer predictable performance by allocating fixed resources for data storage and processing. This model is ideal for large-scale, consistent workloads where performance needs to be predictable and consistent. Azure Synapse Analytics Online Training

On the other hand, the server less SQL pool allows users to query data without the need to pre-provision resources. This on-demand capability is particularly useful for exploratory queries, ad-hoc data analysis, and situations where data workloads are sporadic. Server less SQL pools can query data stored in Azure Data Lake Storage and other sources, providing flexibility and cost efficiency by charging only for the data processed.

2. Synapse Spark

Synapse Spark integrates Apache Spark, a popular open-source big data processing framework, into the Synapse environment. It enables large-scale data processing and analytics, making it ideal for data engineering, machine learning, and data exploration. Synapse Spark provides a managed Spark environment, meaning it handles the underlying infrastructure, allowing users to focus on writing code and analysing data. Azure Synapse Training in Hyderabad

This component supports multiple languages, including Python, Scala, and SQL, making it accessible to a wide range of data professionals. Synapse Spark can be used for batch processing, real-time analytics, and complex data transformations. It also seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure Machine Learning, enhancing its capabilities for end-to-end data workflows.

3. Synapse Data Integration

Synapse Data Integration encompasses data movement and transformation capabilities within Azure Synapse Analytics. This is primarily achieved through Synapse Pipelines, which are similar to Azure Data Factory pipelines. Synapse Pipelines provide a visual interface for creating data workflows, allowing users to orchestrate data movement and transformation across various data sources and destinations.

Data integration within Synapse is crucial for building ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes. These pipelines can connect to a wide variety of data sources, including on-premises databases, cloud-based data services, and SaaS applications. They support both batch and real-time data integration scenarios, making them versatile for different use cases. Azure Synapse Analytics Courses Online

Additionally, Synapse Data Integration supports data flows, which are visual, code-free data transformation tools. Data flows allow users to design data transformations without writing code, making it easier for business analysts and data engineers to prepare data for analysis.

4. Synapse Studio

Synapse Studio is the unified development environment for Azure Synapse Analytics. It provides a web-based interface that brings together the functionalities of all the Synapse components. Synapse Studio offers an integrated workspace where data professionals can perform data exploration, data engineering, data integration, and data visualization tasks.

In Synapse Studio, users can create and manage SQL scripts, Spark notebooks, data pipelines, and more. It also provides built-in monitoring and management tools to track resource usage, job statuses, and data flow operations. The collaborative features of Synapse Studio allow multiple users to work together, making it easier to share insights and data assets within an organization. Azure Synapse Training

Integration and Security

One of the strengths of Azure Synapse Analytics is its ability to integrate with other Azure services and external data sources. It natively supports Azure Data Lake Storage, Azure Blob Storage, Azure SQL Database, and various other Azure services. This integration extends to popular business intelligence tools like Power BI, allowing for seamless data visualization and reporting.

Azure Synapse Analytics also places a strong emphasis on security and compliance. It supports data encryption at rest and in transit, as well as advanced security features like role-based access control, virtual network support, and managed private endpoints. Compliance certifications ensure that data handling meets industry standards and regulations. Azure Synapse Analytics Training

Conclusion

Azure Synapse Analytics provides a comprehensive, integrated platform for data analytics. Its main components—Synapse SQL, Synapse Spark, Synapse Data Integration, and Synapse Studio—offer a wide range of capabilities, from data warehousing and big data processing to data integration and visualization. This integration enables organizations to unlock insights from their data efficiently and securely. Whether for data engineers, data scientists, or business analysts, Azure Synapse Analytics offers the tools and features needed to drive data-driven decision-making.

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[earaercircular]

The second life of aluminium packaging

We consume products wrapped in aluminum almost every day. This waste most often ends up in the incinerator because it does not fit into the traditional recycling channels. The Liège Metallurgical Research Center (CRM)[1] has found a way to give a second life to small household and industrial aluminum.

Coffee capsules, crisps’, biscuits’, chocolate or coffee wrappers, lasagna trays, medicine packaging, aerosols, hair coloring tubes, wine bottle rims, milk product jar lids ..., the list of everyday consumer products wrapped in aluminum is long.

This waste may be light but, on average, the Belgian throws almost two kilos each year in the dust bin.

And if they are found back in nature, their natural degradation is very slow: around 200 years for a can. If this packaging does not end up in the incinerator, it can end up in export circuits with industrial aluminum waste such as offcuts and shavings left over from the manufacturing process, motors and window frames and are therefore not recovered at their fair value with us (aluminum is currently worth 1800 euros per ton). It is not easy to give them a second life: they are very thin and polluted by glues, varnishes, paints, lacquers, plastic films, oils, foams or rubber.

"We need to make better use of these products and, in a conventional recycling circuit, it is very complicated. This requires special equipment to treat organic materials and, above all, the packaging aluminum burns very easily if we do not take precautions, ”explains Christian Marique, technical director at the Liège Metallurgical Research Center. "It must therefore be conditioned beforehand, mixed with other denser products, be prepared, fragmented and then compacted to be processed more easily. This is what we have put in place."

Metallurgy in reverse

Since three years, a CRM team has been working on designing a process for recycling household and industrial aluminum. This initiative is part of the "Reverse metallurgy" project, funded by the Walloon Regional Government since 2015. "Aluminum was selected as a key product by Reverse metallurgy. A secondary aluminum sector already exists , in which we recover a series of products which are melted then reformatted. When we looked in more detail at the potential of recycling, we wanted to go much further. " The technique from the Liège metallurgy industry collective research centre, doubly patented at European level, is now perfected. It also separates the aluminum from the coffee capsules from the grounds they contain and also allows domestic and industrial waste to be mixed in a single recycling process.

Outside the CRM premises, containers are filled with this little everyday waste.

"We needed raw materials. As early as 2016, the CRM asked its staff [2] to collect this household waste of small aluminum. We gave reusable bags to fetch them as well as a magnet, in order to be able to distinguish them from steel waste (such as certain capsules or boxes), which themselves are magnetic, ” says the technical director, who is also the head of the aluminum recycling project. The recycling line is on a pilot scale but the CRM, in collaboration with the Liège-based company CMI[3], has designed an economically profitable factory project in which 20,000 tons of aluminum waste can be recycled per year. The plan foresees a doubling of the volume in a second stage. The project does not only have an ecological impact (in addition to the reprocessing aspect, the recycling of aluminum consumes only 5% of the energy necessary for the primary production sector), it also aims to create a new foundry activity in Wallonia, focused on recycling.

The miniaturized line of the CRM can process between 300 and 400 kilos of waste per day. "They are crushed, fragmented; certain organic components are released and then the waste is compacted into briquettes, with a density comparable to the same volume of pure aluminum, in order to make them easily handled. We knowingly compose them with certain types of waste placed together because we are targeting a particular chemistry ", explains, with a supporting demonstration, Adrien Nélis, engineer and head of the technical part of the aluminum project.

Almost pure recycled aluminum

Then follows the stage when they are put in the oven. The oven is heated to 800 °. After 30 to 35 minutes, the recycled and molten aluminum flows, silvery and shiny, into the mold. Half a day is necessary to be able to handle a cooled ingot. After lithification, samples are presented for chemical analysis. "We can adapt the recycling recipe according to the sectors targeted as customers. We can indeed find iron or zinc in our recycled aluminum, metals that affect the properties of materials, their applications and their quality. Packaging aluminum is quite pure because it does not need other elements to provide mechanical properties, unlike that used to make frames or within the automotive and aeronautical industry. So, in the recycled version, we get very good aluminum. "

Who are the potential customers of recycled aluminum? "We have developed a cooking recipe which makes it possible to target special markets: foundries, the steel industry, a large consumer of aluminum to make calmed steels[4], the cosmetics, pharmaceutical and agrifood industries", details Christian Marique. "And we have other ideas, which are still in an exploratory state. With additive manufacturing[5] which is developing, but what still is very expensive today are the powders of the metals it uses. We could use our aluminum as a metallic powder, after an automation effort. It would be less expensive. New outlets are there. "

There remains a problem to be solved if we want to launch an industrial recycling sector: the collection of this type of waste upstream. "The public authorities will have to organize additional sorting from individuals and collection. If manufacturers are not sure of having all the necessary material, they will not invest in this project", concludes Christian Marique.

Source

Isabelle Lemaire, La seconde vie des emballages en aluminium, in: La Libre Belgique, 1-3-2021 https://stories.lalibre.be/inspire/numero98/index.html

[1] CRM Group is a collective research centre having as Core Members two major worldwide steel companies (ArcelorMittal and Tata Steel) and as Associated Members numerous companies producing non-ferrous metals, providing services to the steel industry or promoting the use of metals. [2] 265 workers, Editor's note [3] Cockerill Maintenance & Ingénierie (CMI), nowadays John Cockerill [4] deoxidized, Editor's note [5] by 3D printing, to put it simply, Editor's note

[nitadesaiblog]

Y-Valves Market Trending High Globally and Its Highly Applicable for Oil & Gas, Power Industry, Steel Industry

Y-Valves are a basic bit of gear when the progression of water or different liquids are required to be conveniently redirected, as in a marine head application where a holding tank is used. They are easily mounted to a bulkhead. The valves are worked by a basic 120° development. Positive stops are given between positions.

Request a PDF copy of this report at https://www.qyreports.com/request-sample/?report-id=177558

QYReports recently published an analysis titled Y-Valves market to its increasing repository. The objective of this statistical report is to present a variegated overview of the competitive landscape across North America, Latin America, Europe, Asia-Pacific, and India. This informative report has been scrutinized by using some significant exploratory techniques such as primary and secondary research.

The report offers effective sales approaches adopted by top industries to increase the clients rapidly in the Y-Valves sector. The competitive landscape has been elaborated by focusing on major key players across the globe. The report gauges competition at the domestic and international level. Additionally, it offers different factors that are fueling or limiting the progress of the market.

Key Strategic Manufacturers:

Forespar, Jabsco Marine, Bosworth, CN CSV Steel Valve, Recon Control, Beijing Valve General Factory

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The report explores and aligns global opportunities in the industry. It focuses on effective sales strategies along with some online as well as offline activities to augment client base. Facts and figures about local consumption, import and export have been presented through infographics, charts, and tables. This research study further discusses existing and upcoming trends, and tools as well as technological advancements. The worldwide market for the Y-Valves sector has been described by focusing on market factors such as type, size, applications, and end users.

This research report will be useful to investors, business owners, industry experts, policymakers. The notable feature of this report is, it covers various dynamic and static aspects of the businesses.

Key players operating in worldwide regions like North America, Latin America, Asia-Pacific, Africa, and Europe have been examined. This research report encapsulates several attributes of businesses such as demand and overview of the products or services. This research report presents a 360-degree overview of the competitive landscape of the global Y-Valves market. For an accurate enterprise outlook, the document on the global Y-Valves market includes some significant projections that can be practiced. Every segment of the market has been studied in painstaking detail and presented in the report.

Researchers of the report throw light on economic factors that affect the progress of the market. A comparative analysis of regional players has been included in the research report. It includes some online and offline activities suggestions for branding the businesses strategized by our team of expert analysts.

It is well-informed and an in-depth report specializing in primary and secondary drivers, market share, leading segments and regional analysis. Moreover, it highlights ratio, capacity, production, revenue and consumption in terms with geographical areas. It shows absolute study about major drivers boosting this market along with restraining factors that can hamper the growth of market. It also projects opportunities that will show substantial growth rate in near future. This study demonstrates the market dynamics and trends altogether the five regions that influence the present nature and future standing of. It discusses the key regional trends conducive to growth of the Y-Valves Market. Further, it analyzes the market potential for every nation.

The scope of the report extends from market eventualities to comparative rating between major players, price and profit of the required market regions. This makes available the holistic view on competitive analysis of the market. Some of the top players involved in the market are profiled completely in a systematic manner.

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About Us We at, QYReports, a leading market research report published accommodate more than 4,000 celebrated clients worldwide putting them at advantage in today’s competitive world with our understanding of research. Our list of customers includes prestigious Chinese companies, multinational companies, SME’s and private equity firms whom we have helped grow and sustain with our fact-based research. Our business study covers a market size of over 30 industries offering unfailing insights into the analysis to reimagine your business. We specialize in forecasts needed for investing in a new project, to revolutionize your business, to become more customer centric and improve the quality of output.

[datascience12course]

Data Science Course with placement

A Detailed Overview of Data Science

Introduction

Data science is the study of extracting meaningful information from data using state-of-the-art analytics technologies and scientific principles for business decision-making, strategic planning, and other reasons. More than ever, businesses require data science insights to improve marketing and sales strategies, increase operational effectiveness, and discover new business chances. They may eventually result in competitive advantages over rival companies. 

Why is Data Science Important?

Almost all facets of corporate operations and strategies benefit from data science tools and techniques. For instance, it helps companies learn more about their customers to create better marketing plans and targeted advertising to increase product sales. It aids in the prevention of equipment breakdowns, fraud detection, and risk management of financial risks in factories and other industrial settings. It aids in thwarting online threats to IT systems' security.

Advantages of Data Science

The data science services make use of cutting-edge technology, including machine learning and artificial intelligence (AI), to examine the data structure of your business and determine the best course of action as we advance. Working with a data science organization has several established advantages, one of which is its capacity to assist your company in making decisions based on structured predictive data analysis. They can develop solutions that enable real-time data viewing, delivering outcomes, and enhancing corporate leaders' agility.

For further information, visit the trending  Data Science course.

Life Cycle of Data Science

The data science lifecycle, which comprises a range of roles, tools, and processes, can provide analysts with useful insights. The data science project often goes through the following phases:

Data Ingestion: The data collection phase of the lifecycle starts with gathering raw, unstructured, and structured data from all relevant sources using several techniques. These methods can include manual data entry, online data mining, and real-time data streaming from devices and machines. Structured data, such as consumer data, can also be gathered from unstructured data sources like log files, video, music, pictures, the Internet of Things (IoT), social media, and more.

Data storage and processing: Companies must consider various storage systems depending on the type of data that has to be captured because data can have a variety of formats and structures. Workflows for analytics, machine learning, and deep learning models are made easier to adopt by establishing standards for data storage and organization with the aid of data management teams. It is necessary to clean, deduplicate, transform, and merge the data at this step using ETL (extract, transform, load) jobs or other data integration technologies. Before being loaded into This data, preparation is essential for improving data quality and can be done in a data warehouse, data lake, or another repository.

Data analysis: Here, data scientists analyze the data in an exploratory manner to look for biases, trends, ranges, and distributions of values. This data analytics exploration drives the creation of a/b testing hypotheses. It also helps analysts to assess whether the data may be used for modeling in predictive analytics, machine learning, and/or deep learning. Depending on the model's accuracy, organizations may rely on these insights for internal decision-making, allowing them to scale up more effectively.

Communicate: Finally, insights are presented as reports and other data visualizations to help business analysts and decision-makers better understand the insights and how they will affect the organization. In addition to using specialized visualization tools, data scientists can create visualizations using components built into programming languages for data science, such as R or Python.

Conclusion

Data science is an interdisciplinary field that uses information from data to infer knowledge and understanding across various application domains by applying scientific methods, procedures, algorithms, and systems insights from noisy, structured, and unstructured data. In the context of mathematics, statistics, computer science, information science, and domain knowledge, it uses methods and theories from various domains. You can master this data science course with placement. and build your career with specialized domain courses.

[researchforetell]

Covid-19 Impact on Carbon Brush Market to Witness Mounting Growth in Approaching Time

Researchforetell much awaited study on Carbon Brush market was recently released. It uses exploratory techniques like qualitative and quantitative analysis to uncover and present data on the target market. Efficient sales strategies have been mentioned that would business and multiply customers in record time.

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https://www.researchforetell.com/reports/56316/carbon-brush-market---global-outlook-and-forecast-2021-2027/request

North America, Latin America, Asia-Pacific, Europe, and India have been considered for studies on the basis of productivity, types of products or services along with its features. It also identifies the competitive landscape of Carbon Brush industries to understand the competition at the domestic and international level.

By Type, 2020 (%)

  Electrographite Brush

  Graphite Brush

   Metal Graphite Brush

   Silver Graphite Brush

By Application, 2020 (%)

  Industrial Equipment

  Automotive Application

  Automotive Application

   Micro Motors

key players include:

   Mersen

   Morgan

   Schunk

   AVO

   Helwig Carbon Products

   GERKEN

   Ohio

   Fuji

   Tris

   Toyo Tanso

   Dremel

   Harbin Electric Carbon Factory

   Donon

   Sunki

   Nantong Kangda

   Morxin

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Graphical presentation techniques such as tables, chart, graphs, and pictures have been used to bring out the data more effectually. The report studies different attributes of business such as, recent developments, technological platforms, tools and techniques that help in understanding the existing market.

Major industry key players such as Carbon Brush have been documented to study successful strategies employed by leading industries. Different market factors such as type, size, applications, and end-users have been included to study businesses thoroughly. Major pillars of the businesses that affect the ups and downs of Carbon Brush companies are also included in this report. The study has been aggregated on the basis of recent scope, challenges faced by businesses, and global opportunities to enlarge the Carbon Brush sector in upcoming years.

Complete report is available at

https://www.researchforetell.com/reports/56316/carbon-brush-market---global-outlook-and-forecast-2021-2027

Market segment by Region, regional analysis covers

  North America (United States, Canada and Mexico)

   Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe)

   Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia)

   South America (Brazil, Argentina, Colombia, and Rest of South America)

   Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa)

Scope of the Report

The market characteristics section of the report defines and explains the market.

The market size section gives the market size ($b) covering both the historic growth of the market, the impact of the Covid 19 virus and forecasting its recovery.

Market segmentations break down market into sub markets.

The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the impact and recovery trajectory of Covid 19 for all regions, key developed countries and major emerging markets.

Competitive landscape gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.

The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

The heavy trucks market section of the report gives context. It compares the heavy trucks market with other segments of the heavy trucks market by size and growth, historic and forecast.

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Identify growth segments for investment.

Outperform competitors using forecast data and the drivers and trends shaping the market.

Understand customers based on the latest market research findings.

Benchmark performance against key competitors.

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[bloglumfia]

Clinical Analysis of Suspicious Pigmented Lesions

A digital trial master record (eTMF) provides a strong program to document management which allows examine staff people to get an instant insight necessary to successfully control clinical trials and speedup time to market. Electric document administration operations are now being followed at a regular pace as it becomes vital to organization productivity, reduced biopharma product development timelines, and charge cutting.

The advantage of eSource is evident and the FDA endorsed it since it is likely to be of good use in: facilitating real-time entering of electronic supply knowledge throughout subject trips, eliminates the need to copy data, permits accuracy and completeness of data by using electronic requests for sporadic and lacking data and reduces the chance for transcription NIPT東京.

The necessity to update and streamline the way information is collected are growing, as a result, a lot of the exploratory performed thus far by several pharmaceutical organizations have been mostly to build internal competency. In going forward, it is crucial that criteria and interoperability within various eSource modalities get together to help produce systems offering appropriate data in clinical research.

The ability to powerful control, record and analyze knowledge is of paramount value in clinical trials. The major difficulty is that information from clinical trials are usually joined by doctors electronically or physically across multiple stations including EDC, LIMS, CDMS and IVRS and different programs each with unique underpinning needs.

This process triggers data to result in different sources which makes it complex and time-consuming to influence and match the data. There's distress in regards to what constitute or becomes CDR as distinct from a clinical information factory (CDW). CDR could be thought of as consolidated storage and move of data for clinical trials including security, workflow, and methods for doing day-to-day job all under one umbrella.

Centralization of the storage and management of knowledge answers are the purpose of CDR and to supply a accurate and trusted infrastructure that supports clinical information analysis and administration, aid standardization and protected move of information, permit analytics and cross-trial evaluation and to influence data from trials across the pipeline.

[nadrn438]

The role of older women in contesting norms associated with female genital mutilation/cutting in Senegambia

Social norms theory is increasingly utilized in studies that aim to understand the perpetuation of FGM/C, and was used as a framework to explore how norms influence FGM/C decisions, and how these norms differ across generations. The authors used focus group interviews to generate data for exploratory investigations of social norms, values, and meanings. These focus groups also helped researchers to examine the participants’ social interactions, power structures, and dynamics of change.

Research questions included: How are social norms interrelated with FGM/C decision-making? How are norms upheld, shifted, or resisted as social circumstances progress? When and how are social norms questioned or challenged, and by who? The article found that FGM/C was often upheld by peer convention and peer pressure, seemingly because it serves as a signal to other affected women that a girl or woman respects authority and her elders, and is fit to enter a social network. Upholding tradition was strongly associated with the perpetuation of FGM/C as it is seen as a way to respect ancestors and cultural values.

I was interested in this article because it pointed out how older woman could take on the role of change leaders, where they would increase norm flexibility and thus accelerate the abandonment of FGM/C without drastically changing ethnic/cultural traditions.

Older women appeared to be more accepting of change and question the necessity of FGM/C, especially when they considered risks such as HIV infection. The study found that the openness of older women to reassess social norms may be a driving factor in negotiating change and serve as a means of eliminating FGM/C. 

“By recognizing the authority of older women as advocates for change, and drawing on variability and fluidity in norms and practices, it may be increasingly possible to shape possibilities for action and accelerate abandonment of FGM/C without undermining the value of cultural traditions.”

Source:

Shell-Duncan B, Moreau A, Wander K, Smith S. 2018. “The role of older women in contesting norms associated with female genital mutilation/cutting in Senegambia: A factorial focus group analysis.” PLoS ONE 13(7):e0199217. https://doi.org/10.1371/journal.pone.0199217

[francescolelli]

Agency in Human-Smart Device Relationships: An Exploratory Study

This is a short preview of the article: Can User of IoT technology be more then "just user"? How do they relate to technology? User and Device Agency Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the

If you like it consider checking out the full version of the post at: Agency in Human-Smart Device Relationships: An Exploratory Study

If you are looking for ideas for tweet or re-blog this post you may want to consider the following hashtags:

Hashtags: #Agency, #DeviceAgency, #ExploratoryFactorialAnalysis, #HumanComputerInteraction, #SmartDevices, #Survey, #UserAgency

The Hashtags of the Categories are: #HCI, #InternetofThings, #Publication, #Research, #SoftwareEngineering

Agency in Human-Smart Device Relationships: An Exploratory Study is available at the following link: https://francescolelli.info/publication/agency-in-human-smart-device-relationships-an-exploratory-study/ You will find more information, stories, examples, data, opinions and scientific papers as part of a collection of articles about Information Management, Computer Science, Economics, Finance and More.

The title of the full article is: Agency in Human-Smart Device Relationships: An Exploratory Study

It belong to the following categories: HCI, Internet of Things, Publication, Research, Software Engineering

The most relevant keywords are: Agency, device agency, exploratory factorial analysis, Human-Computer Interaction, smart devices, survey, user agency

It has been published by Francesco Lelli at Francesco Lelli a blog about Information Management, Computer Science, Finance, Economics and nearby ideas and opinions

Can User of IoT technology be more then "just user"? How do they relate to technology? User and Device Agency Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the

Hope you will find it interesting and that it will help you in your journey

Can User of IoT technology be more then “just user”? How do they relate to technology? Abstract: With technology in reach of everyone and the technology sector in ascendance, it is central to investigate the relationship people have with their devices. We use the concept of agency to capture aspects of user’s sense of mastery…

[rr-envr1301]

Activity 3.2.3.1 Solar Power and Solar Energy Policy

Six-Point Critical Analysis of Current Event

1. Exploratory

 If we look back at our learnings from activity3.2.1, we know that solar energy is a renewable natural resource that can be turned into electricity. Hazlehurst solar farm II is going to create enough energy for 8,5000 EMC households. This project is 3x larger than Hazelhurst solar farm I. The solar farm not only helped give Facebook more green energy but, it also provided the county with tax revenue for education,construction etc. This new solar plant in Dalton is the largest solar panel assembly plant in the western hemisphere. This plant was built for Facebook’s goal of 100% green energy usage (annually). Georgia has a vast amount of land and is naturally farming land so the switch from cattle/crop to a solar farm was integrative. 

2. Diagnostic

Hazelhurst solar farm II was created to serve as the second solar farm to serve Facebook’s need for green energy. Georgia is farming territory so turning it into a solar farm was both creative and revolutionary (for the county). The project brought tax revenue to the poverty ridden county, while also providing jobs to the locals. 

3. Cause and Effect

The solar farm provides green energy to the Facebook station, while also providing energy for ~8,500 EMC homes. This project helped the county by providing green energy, providing jobs during the building process and gave the county a large tax revenue which they could use for education or other social needs. “June Merritt, chair of the Early County Board of Commissioners, estimates that $8 million will come into the county in the form of taxes over the next 25 years.”(Andrea H, Mary Kelly)

4. Priority

The most important issue is creating green energy. Facebook wants to run 100% on green energy, but solar energy also reduces the amount of emissions/pollution that could have come from a coal or nuclear plant. “Had there been a golden opportunity to sell a piece of his land for a nuclear plant or a coal plant, Singletary says he probably would have taken that, too.”(Andrea H, Mary Kelly)

5. Application

 Green energy benefits everyone, the less pollution being put out by emissions from a factory/plant everyday,the better. I personally would like to see more solar farms in Texas and throughout the country.

6. Critical

I have never realized how much land it takes to have a solar farm. The small panels you see on homes are nowhere near the size used on the farms. In my mind an acre is already a lot of land,so to realize a solar farm could take up 450+ acres put into perspective how much space is needed for green energy.

sources; 

Hsu, A., & Kelly, M. L. (2019, June 24). How solar grew in Georgia despite lack of mandates on renewable energy. National Public Radio. Retrieved from https://www.npr.org/2019/06/24/733795962/how-georgia-became-a-surprising-bright-spot-in-the-u-s-solar-industry

Silicon Ranch Hazlehurst II Project on Georgia Farm Bureau TV https://vimeo.com/217896697

[finevili241]

Willow Bough - Exploratory Analysis

Who designed it? William Morris

When was it designed? 1887

What did the designer want to express/deliver? In these designs, Morris was trying to express the look and feel of nature.

Was it the designer’s answer or resolution to a problem or issue? 

How long did it take to complete the design since its inception? 

What is the material(s) it is made of/from? William Morris designed the Willow Bough as wallpaper, and in 1895 he produced it as a fabric too.

How was it manufactured/crafted? Morris had his wallpapers printed by hand, using carved, pear woodblocks loaded with natural, mineral-based dyes, and pressed down with the aid of a foot-operated weight. Each design was made by carefully lining up and printing the woodblock motifs again and again to create a seamless repeat.

Were there any design/technical challenges? Design Challenges he would’ve faced would be the process of making the wallpaper. A lot of sleepless hours are put into creating the wallpapers.

How did the designer overcome them? Morris employed the printers Jeffrey & Co. to print his wallpapers up until his death in 1896, when the Merton factory took over production until the company’s voluntary liquidation in 1940.

How many units have been produced?

Was the material(s) and/or manufacturing/crafting process better than its predecessors or competition? If so, how and why? Compared to other wallpapers at the time, William Morris designed something colourful and unique. Other wallpapers were plain, and after the Willow Bough was designed, it changed the way people decorate their homes.

Was there any consideration of its potential impact on the environment, people or society put into practice ahead of its time? The Willow Bough had a huge impact on how people decorated their homes and to this day you still see wallpapers of this design in peoples homes.

Who was its target audience?

What kind of responses did it meet with? Can you describe its typical use or experience? In 1887, Morris designed Willow Bough as a wallpaper, and in about 1895 he produced it as a fabric too.

What are the most impressive qualities or features of the design (in your opinion)? I think at the time the Willow Bough was designed, it would’ve been very unique as other wallpapers would’ve been plain and boring. Inspired by nature, Morris designed a wallpaper that was colourful and gives aesthetic pleasure.

Did you find any less known but remarkably enticing features? 

Any other intriguing facts? 

Do you think it is technically, aesthetically or culturally important or meaningful? Aesthetically meaningful: The Willow Bough was designed in 1887, when wallpapers were plain and boring. Morris changed the way people decorated their homes with this design inspired by nature. To this day, people still use these types of designs but now for a range of things, for example: clothes, wallpaper, furniture etc.

In conclusion, why do you think it deserves to be an exemplar of good design? I think this deserves to be an exemplar of good design because it is original, unique, and aesthetic.

How would you improve it if you redesign it?

Reference:

Tagart, E. (2008, Janurary 28). Meet William Morris: The Most Celebrated Designer of the Arts & Crafts Movement. My Modern Met. https://mymodernmet.com/arts-and-crafts-movement-william-morris/

Victoria and Albert Museum. (2020). William Morris and wallpaper design. https://www.vam.ac.uk/articles/william-morris-and-wallpaper-design

[theresawelchy]

Introduction to Prinicipal Component Analysis: Dimensionality Reduction Made Easy

Introduction to Prinicipal Component Analysis: Dimensionality Reduction Made Easy

BigML’s upcoming release on Thursday, December 20, 2018, will be presenting our latest resource to the platform: Principal Component Analysis (PCA). In this post, we’ll do a quick introduction to PCA before we move on to the remainder of our series of 6 blog posts (including this one) to give you a detailed perspective of what’s behind the new capabilities. Today’s post explains the basic concepts that will be followed by an example use case. Then, there will be three more blog posts focused on how to use PCA through the BigML Dashboard, API, and WhizzML for automation. Finally, we will complete this series of posts with a technical view of how PCAs work behind the scenes.

Understanding Principal Component Analysis

Many datasets in fields as varied as bioinformatics, quantitative finance, portfolio analysis or signal processing can contain an extremely large number of variables, that may be highly correlated, resulting in sub-optimal Machine Learning performance. Principal component analysis (PCA) is one technique that can be used to transform such a dataset in order to obtain uncorrelated features or as a first step in dimensionality reduction. 

Because PCA transforms the variables in a dataset without accounting for a target variable, it can be considered an unsupervised Machine Learning method suitable for exploratory data analysis of complex datasets. However, when used towards dimensionality reduction, it also helps reduce supervised model overfitting, as there remain fewer relationships to consider between variables after the process. To do this, the principal components yielded by a PCA transformation are typically ordered by the amount of variance each explains in the original dataset. The practitioner can decide how many of the new component features can be eliminated from a dataset while preserving most of the original information contained in it.

Even though they are all grouped under the same umbrella term (PCA), under the hood, BigML’s implementation incorporates multiple factor analysis techniques, rather than only the standard PCA implementation. Specifically,

Principal Component Analysis (PCA): BigML utilizes this option if the input dataset contains only numerical data.

Multiple Correspondence Analysis (MCA): this option is available if the input dataset contains only categorical data.

Factorial Analysis of Mixed Data (FAMD): in case the input dataset contains both numeric and categorical fields this option is also available.

In the case of items and text fields, data is processed using a bag-of-words approach allowing PCA to be applied. Because of this nuanced approach, BigML can handle categorical, text, and items fields in addition to numerical data in an automatic fashion that does not require manual intervention by the end user.

Want to know more about PCA?

If you would like to learn more about Principal Component Analysis and see it in action on the BigML Dashboard, please reserve your spot for our upcoming release webinar on Thursday, December 20, 2018. Attendance is FREE of charge, but space is limited so register soon!

[evoldir]

Course: UK.PopulationGenetics.Feb11-15

Reproducible data science for population genetics (RDPG02) This course is being delivered by Dr Thibaut Jombart and Dr Zhian Kamvar (authors of the Adgenet package which will focus heavily in the course) from the 11th - 15th February 2019 in Glasgow City Centre Course Overview: With the increasing availability of various types of genetic and genomic data, population genetics and molecular ecology are becoming largely data driven sciences. Understanding the evolutionary, demographic, and ecological underpinning the genetic makeup of natural populations now relies on a combination of exploratory approaches and models. This course will provide an in-depth introduction to these techniques, with a strong emphasis on reproducibility though the use of modern analytic practices and tools. After an introduction to phylogenetic reconstruction, the course will cover a number of multivariate approaches for the analysis of genetic patterns, including supervised and unsupervised factorial methods, clustering approaches, and advanced methods for describing population diversity and revealing spatial genetic patterns. The approaches introduced will be applicable to most genetic data, including markers such as microsatellites, SNPs, or AFLP, as well as nucleotide and amino-acid sequence data. Every day will start with a lecture dedicated to a type of problem and methods, followed by an introduction to a specific technique for reproducible data analysis; afternoon will be devoted to hands on praticals. The last day will be devoted to open problems, where participants will be able to analyse their own data. Intended Audience The course is aimed at PhD students, research postgraduates, and practicing academics as well as persons in industry working with genetic data in fields such as molecular ecology, evolutionary biology, and phylogenetics. Email oliverhooker@prstatistics.com Check out our sister sites, http://bit.ly/2BpXxpa (Ecology and Life Sciences) http://bit.ly/2qdTVVO (Bioinformatics and data science) http://bit.ly/2GvgDyl (Behaviour and cognition) UPCOMING COURSES! 1. July 23rd – 27th 2018 EUKARYOTIC METABARCODING (EUKB01) Glasgow, Scotland, Dr. Owen Wangensteen http://bit.ly/2qdR9jx 2. October 1st – 5th Time series models for ecologists (TSME02) Glasgow, Dr Andrew Parnell http://bit.ly/2KGKlFg 3. October 1st – 5th 2018 INTRODUCTION TO BIOINFORMATICS USING LINUX (IBUL03) Glasgow, Scotland, Dr. Martin Jones http://bit.ly/2KD9ay2 4. October 8th – 12th 2018 INTRODUCTION TO FREQUENTIST AND BAYESIAN MIXED (HIERARCHICAL) MODELS (IFBM01) Glasgow, Scotland, Dr Andrew Parnell http://bit.ly/2KICua3 5. October 15th – 19th 2018 APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (ABME) Glasgow, Scotland, Dr. Matt Denwood, Emma Howard http://bit.ly/2ps8OCu 6. October 23rd – 25th INTRODUCTIUON TO R (This is a private ‘in-house’ course) London, England, Dr William Hoppitt 7. October 29th – November 2nd 2018 INTRODCUTION TO R AND STATISTICS FOR BIOLOGISTS (IRFB02) Glasgow, Scotland, Dr. Olivier Gauthier Link to follow – see previous http://bit.ly/2KvnUDG 8. October 29th – November 2nd 2018 INTRODUCTION TO BIOINFORMATICS FOR DNA AND RNA SEQUENCE ANALYSIS (IBDR01) Glasgow, Scotland, Dr Malachi Griffith, Dr. Obi Griffith http://bit.ly/2DwqQI0 9. November 5th – 8th 2018 PHYLOGENETIC COMPARATIVE METHODS FOR STUDYING DIVERSIFICATION AND PHENOTYPIC EVOLUTION (PCME01) Glasgow, Scotland, Dr. Antigoni Kaliontzopoulou http://bit.ly/2DwZqBI 10. November 19th – 23rd 2018 STRUCTUAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (SEMR02) Glasgow, Scotland, Dr. Jonathan Lefcheck Link to follow – see previous http://bit.ly/2KD9dtI 11. November 26th – 30th 2018 FUNCTIONAL ECOLOGY FROM ORGANISM TO ECOSYSTEM: THEORY AND COMPUTATION (FEER Glasgow, Scotland, Dr. Francesco de Bello, Dr. Lars Götzenberger, Dr. Carlos Carmona http://bit.ly/2n0pu0B 12. January 21st – 25th 2019 STATISTICAL MODELLING OF TIME-TO-EVENT DATA USING SURVIVAL ANALYSIS: AN INTRODUCTION FOR ANIMAL BEHAVIOURISTS, ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (TTED01) Glasgow, Scotland, Dr. Will Hoppitt http://bit.ly/2KD30hz 13. January 21st – 25th 2019 ADVANCING IN STATISTICAL MODELLING USING R (ADVR08) Glasgow, Scotland, Dr. Luc Bussiere, Dr. Tom Houslay http://bit.ly/2KvnX2k 14. 28th January – 1st February 2019 AQUATIC ACOUSTIC TELEMETRY DATA ANALYSIS AND SURVEY DESIGN Glasgow, Scotland, VEMCO staff and affiliates http://bit.ly/2KKWTbn 15. 4th – 8th February 2019 DESIGNING RELIABLE AND EFFICIENT EXPERIMENTS FOR SOCIAL SCIENCES (DRES01) Glasgow, Scotland, Dr. Daniel Lakens http://bit.ly/2KvnXzm 16. February 11th – 15th 2019 REPRODUCIBLE DATA SCIEDNCE FOR POPULATION GENETICS Glasgow, Scotland, Dr. Thibaut Jombart, Dr. Zhain Kamvar http://bit.ly/2IQGMY2 17. 25th February – 1st March 2019 MOVEMENT ECOLOGY (MOVE02) Margam Discovery Centre, Wales, Dr. Luca Borger, Prof. Ronny Wilson, Dr Jonathan Potts http://bit.ly/2yacoYJ 18. March 4th – 8th 2019 BIOACUSTIC DATA ANALYSIS Glasgow, Scotland, Dr. Paul Howden-Leach LiNk coming soon 19. March 18th – 22nd 2019 ECOLOGICAL NICHE MODELLING USING R (ENMR03) Glasgow, Scotland, Dr. Neftali Sillero http://bit.ly/2IVv6U8 20. March 25th – 29th 2019 LANDSCAPE GENETIC/GENOMIC DATA ANALYSIS USING R (LNDG03) Glasgow, Scotland, Prof. Rodney Dyer http://bit.ly/2Kvo0ew 21. April 1st – 5th 2019 INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R (IPSY01) Glasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierre http://bit.ly/2IQGOz8 via Gmail

[wastebaskettaxon]

Building resilience to violent extremism has featured in preventing violent extremism efforts for over a decade. Validated and standardized cross-cultural measures can help identify protective capacities and vulnerabilities toward violent extremism for young people. Because drivers for violent extremism are multi-factorial, a measure of resilience cannot be used to predict who will and will not commit acts of terror. Instead, its purpose is to track the multiple forms of capital available to youth at risk of adopting violence to resolve ideological, religious and political grievances, and to use this data to inform interventions that increase young people’s capacity to resist violent extremism’s push and pull forces. In this study, we developed such a measure, using data from 200 Australian and 275 Canadian participants aged eighteen–thirty years old. Following exploratory and confirmatory factor analysis, a fourteen-item measure emerged consisting of five factors: cultural identity and connectedness; bridging capital; linking capital; violence-related behaviors, and violence-related beliefs. The Building Resilience against Violent Extremism (BRAVE) measure was found to have good internal reliability (α = .76), correlating in expected directions with related measures. The BRAVE shows promise for helping understand young people’s resilience to violent extremism.

[crystalmarketresearch]

Wearable Fitness Trackers Market - Global Industry Analysis & Forecast to 2025

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Xiaomi

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[bookmandigital123-blog]

Test Bank for Discovering Statistics Using IBM SPSS Statistics 5th Edition by Field

This is completed downloadable of Test Bank for Discovering Statistics Using IBM SPSS Statistics 5th Edition by Andy Field

Instant download Test Bank for Discovering Statistics Using IBM SPSS Statistics 5th Edition by Andy Field after payment

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http://testbankair.com/wp-content/uploads/2018/07/Test-Bank-for-Discovering-Statistics-Using-IBM-SPSS-Statistics-5th-Edition-by-Andy-Field.pdf

Test Bank for Discovering Statistics Using IBM SPSS Statistics 5th Edition by Andy Field

With an exciting new look, new characters to meet, and its unique combination of humour and step-by-step instruction, this award-winning book is the statistics lifesaver for everyone. From initial theory through to regression, factor analysis and multilevel modelling, Andy Field animates statistics and SPSS software with his famously bizarre examples and activities. What’s brand new: A radical new design with original illustrations and even more colour A maths diagnostic tool to help students establish what areas they need to revise and improve on.  A revamped online resource that uses video, case studies, datasets, testbanks and more to help students negotiate project work, master data management techniques, and apply key writing and employability skills New sections on replication, open science and Bayesian thinking Now fully up to date with latest versions of IBM SPSS Statistics©. All the online resources above (video, case studies, datasets, testbanks) can be easily integrated into your institution’s virtual learning environment or learning management system. This allows you to customize and curate content for use in module preparation, delivery and assessment. For instructions on how to upload the resources you want, please visit the Instructors’ page  or alternatively, contact your local SAGE sales representative

Table of Content:

1 Why is my evil lecturer forcing me to learn statistics? 2 The SPINE of statistics 3 The Phoenix of Statistics 4 The IBM SPSS Statistics environment 5 Exploring data with graphs 6 The beast of bias 7 Non-parametric models 8 Correlation 9 The Linear Model (Regression) 10 Comparing two means 11 Moderation, mediation and multicategory predictors 12 GLM 1: Comparing several independent means 13 GLM 2: Comparing means adjusted for other predictors (analysis of covariance) 14 GLM 3: Factorial designs 15 GLM 4: Repeated-measures designs 16 GLM 5: Mixed designs 17 Multivariate analysis of variance (MANOVA) 18 Exploratory factor analysis 19 Categorical outcomes: chi-square and loglinear analysis 20 Categorical outcomes: logistic regression 21 Multilevel linear models

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