#Advanced Visualization Tools

[ss-1990]

Beyond Storage: Enhancing Patient Care with PACS: Radiology Machines Interfacing Explained

In modern healthcare, the ability to efficiently manage medical imaging data is crucial for providing high-quality patient care. Radiology Machines Interfacing and Picture Archiving and Communication Systems (PACS) play a pivotal role in streamlining radiology workflows and improving diagnostic efficiency. In this blog post, we'll explore how PACS facilitates Radiology Machines Interfacing and its impact on patient care, focusing on key aspects such as Seamless Workflow, Diagnostic Efficiency, Advanced Visualization Tools, Remote Collaboration, and Long-Term Archiving & Accessibility.

Seamless Workflow is essential for optimizing radiology operations and ensuring timely delivery of imaging results to healthcare providers. PACS enables Radiology Machines Interfacing with seamless integration into existing radiology workflows, allowing for efficient image acquisition, storage, and retrieval. By automating data transfer and streamlining image interpretation processes, PACS enhances workflow efficiency and reduces turnaround times, ultimately improving patient care.

Diagnostic Efficiency is paramount in radiology, where accurate and timely diagnoses are critical for patient management. PACS provides radiologists with access to advanced image visualization tools and intuitive user interfaces, enabling them to interpret images with precision and confidence. By facilitating rapid image retrieval and manipulation, PACS enhances diagnostic efficiency, allowing radiologists to focus on interpreting images and making informed clinical decisions.

Advanced Visualization Tools offered by PACS enable radiologists to perform detailed image analysis and visualization, enhancing diagnostic accuracy and confidence. Features such as multi-planar reconstruction, 3D rendering, and image fusion empower radiologists to extract valuable insights from medical imaging data, leading to more accurate diagnoses and improved patient outcomes.

Remote Collaboration capabilities facilitated by PACS enable radiologists to collaborate with colleagues and specialists in real-time, regardless of geographical location. With PACS, radiologists can securely share images, discuss cases, and consult with other healthcare providers, fostering collaboration and enabling multidisciplinary care approaches. This remote collaboration enhances communication among healthcare teams, facilitates knowledge sharing, and ultimately benefits patient care.

Long-Term Archiving & Accessibility of medical imaging data is essential for ensuring continuity of care and facilitating research and education. PACS provides robust archiving capabilities, allowing for the secure storage and retrieval of imaging studies over extended periods. By centralizing image storage and providing on-demand access to historical imaging data, PACS ensures long-term accessibility and availability of patient records, supporting continuity of care and enabling retrospective analysis.

In conclusion, PACS plays a vital role in enhancing patient care by facilitating Radiology Machines Interfacing and streamlining radiology workflows. By prioritizing aspects such as Seamless Workflow, Diagnostic Efficiency, Advanced Visualization Tools, Remote Collaboration, and Long-Term Archiving & Accessibility, PACS empowers radiologists to deliver high-quality diagnostic services, ultimately improving patient outcomes and advancing healthcare delivery.

[dimalink]

GVim – it looks like Windows 3.11 and it is a advanced text editor

GVim – it is very interesting program. Code editor, text. With interface of style – retro under windows 3.11. And, something like, a program for a cool programmers! For those one, who is ready to jump into a rabbit`s hole!

Fist time, I give a try to use this program in 2023. But! But, once again - here it goes different – but words! Complicated! Hard to understand! Unknown! I want it, but I cannot to do this! Interesting, but too complicated! Give a try – something to understand, to learn. And, it not works for me, I failed. And, I take a decision to left it at the level of the idea. So, it was a year 2023 experience.

And, with this background, what a surprise I have. When in 2024, I find a programming language Free Basic. And they give you a compiler. Compile by yourself. And. write with code editor – the one you want.  So. this is a serious attitude. And, I decide – I have, already, give a try with GVim. I want this try again! And, with easy way, I roll into this theme. As a hedgehog I roll. At the most easy level. Write code. Commands, some easy of them. And everything is ok, it works for me! Yes, I need to read and learn, to dig a theme. But, everything works! And it is not looks hard for me! Level of difficulty was normal, very ok level! It was a very positive step!

To write a code from something like a text and compile by your own hands - it is so cool! And it is so cool to use such programs like GVim. There is also EMacs. But, I know nothing about it, except that such program exists. It is, also, as a code editor. Also, for a programmers. Also, it is a serious theme. And even, there are something like a conversations. At the level – what to select – GVim or Emacs.

GVim – it is very advanced editor for text or code. Very advanced. For me, it is something with the ideas of frontier as a Norton Commander for MS Dos. Or Volkov Commander for MS Dos. I am serious. So, it is a most simple way to understand about, that it is a very advanced soft. For a true programmers. And this is a thing of intelligence and habit to use such tools. So. from the first time, I guess, you cannot to start to use it easy. You will fail. In the end, I am for myself, use it at the simple level. Most minimum. File open, to go some place. Copy and paste strings. To compile! Fascinating! This GVim works with command line. So, straight from the GVim you can to compile! Or go to catalog with the help of MS Dos command. Class! It is, looks like, a program with unlimited capabilities.

Maybe, because of this kind of programs. Programmers looks like in a movies, as a super-humans. So, everything is flashing at the screen, then yes it is. So, it jumps a picture here. Programmer writes a command there. This makes a call for something else. So, everything is so bright! Lots of colorful text at the screen. Beautiful pictures. Lots of code fragments.

By sides. By center – picture. And, this kind of way – it is shown as programmer. And, this is co cool and positive! I, even, think, it is true and it is like this! When, you have a knowledge and head works well! At this level – you still need to reach it! And all of these miracles and different colors – they are in your head! World is starting to bloom! So, with this I can to agree!

One more interesting thing, there is a Vim code editor. And, I use GVim. So, this is, also, a  standalone theme. And, I start, of course, with first impression. It is, of course, a visual side. It, looks, someway, close to some retro. GVim interface makes a surprise on me. It is so black and white. White background. As, it looks for me. Some little pictures at the top. Points of menus. As Windows 3.1 or windows 3.11, it is first things, that came into my head! And I like it! Beautiful interface! This visual side, it is, also, a valuable!

And next, even, more – lots of capabilities for a syntax. Syntax support. Even, Free Basic, I can find there! Wow! But, you need to search it for yourself and select settings for yourself. Once again, before this, I write in Visual Studio – and, something, I never think about compile, about syntax, light some keywords method. Everything is works automatic there for me. And, also, a dig – it is very hard and complicated! And, I am as Alice from Wonderland. I touch the mystery. So, these example of feelings from using GVim. For this points, I like a program! I. just. still waits to meet in this program – a rabbit! Kind and funny one!

iron (hardware) and programs. From time to time i restore computers, retro computers. Try retro soft. Check some programs. And write about all of these. Dima Link is making retro videogames, apps, a little of music, write stories, and some retro more.

WEBSITE: http://www.dimalink.tv-games.ru/home_eng.html ITCHIO: https://dimalink.itch.io/

BLOGGER: https://dimalinkeng.blogspot.com/ TUMBLR: https://dimalink.tumblr.com/

[lucalicatteart]

-- Poorly Constructed Enchanted Tool --

A small tool carved from a fruit tree seed. Energy to power the enchantment has seemingly run-out long ago, and the method of recharging is unknown - but, based on the appearance, it's very likely that this was once used for detecting magic. Usually, looking through the glass center would highlight areas of higher magical energy concentration present in the viewer's environment, even if they were otherwise obscured to the naked eye. While this form of enchantment itself is highly advanced, the craftsmanship of the item is far less neat or complex than what might be typically seen in similar devices. It may have been made as part of training/practice, or as a hasty replacement for a previous tool that had broken.

[03349656115]

appleiphone

[mimok]

The Machine Dreams

text to video with firefly. Today, I gained access to Firefly’s text-to-video generative feature, and it feels like stepping into the future. The speed at which technology is advancing is breathtaking, and with each new tool, creative possibilities expand in ways we couldn’t have imagined just a few years ago. I tested it by generating videos using a reference image and others directly from text…

[munaeem]

How to use COPILOT in Microsoft Word | Tutorial

This page contains a video tutorial by Reza Dorrani on how to use Microsoft 365 Copilot in Microsoft Word. The video covers: Starting a draft with Copilot in Word. Adding content to an existing document using Copilot. Rewriting text with Copilot. Generating summaries with Copilot. Overall, using Copilot as a dynamic writing companion to enhance productivity in Word. Is there something…

[2happyherder]

[vuelitics1]

Discover how the world’s top companies are leveraging Business Intelligence (BI) to stay ahead of the competition! In this video, we break down the strategies and tools used by giants like Google, Amazon, Apple, and more to optimize operations, enhance customer experience, and drive innovation. From real-time data analysis to predictive analytics, these companies are transforming the way business is done.

Whether you’re a business owner, a data enthusiast, or just curious about how big brands like Netflix and Tesla use BI to gain a competitive edge, this video is a must-watch. Learn how Business Intelligence tools like Tableau, Microsoft Power BI, and SAP BusinessObjects are being used to make smarter decisions, predict customer behavior, and streamline operations.

Visit Our Webiste: https://vuelitics.com/

[generative-ai-in-bi]

Smart Insights: AI Interfaces Driving BI Evolution

In such an ever-changing business arena, wisdom is one of the key assets and you have to rely not only on your intuition. Using Data Analytic Tools and Advanced Artificial Intelligence Models, one would be able to deduct the necessary strategic choices. The old trend was that the usage of such instruments mostly depended on particular experts to do it which happened to confine the utilization of these tools to most of the big organizations with their reliable data science teams. Yet the emergence of Generative AI Interfaces for instance is turning the tide beyond this traditional model of analytics democratizing access to advanced analytics and making it possible for small companies to be equipped with sophisticated analytics capabilities with unprecedented speed and thus making better decisions.

The AI Predictive Analytics has developed to a game changer in the realms of strategic decision making since it allows us to e pump up performance and business tremendously by predicting even the advanced matters of level. Leveraging AI-Based Forecasting Algorithms allows companies to react in a premitive manner to their mindsets, while foreclosed emerging opportunities and eliminating risks. By doing so, companies gain a significant competitive advantage in their industries. On the other hand, due to the complex nature of traditional analytics platforms, their adoption has been limited by the fact that to efficiently operate them one needs to be properly trained while an expert is preferable for navigation.

And these are the two areas in which Generative AI plays a major role, offering an innovative way to handle Business Intelligence (BI) problems through artificial intelligence, aimed at automating and simplifying the process. In contrast to traditional BI solutions that contains queries and examines fact-based static reports, Generative AI interfaces deploy machine intelligence which makes immediate relevant insights based on the unique needs and objectives of user. As a result, the individuals cut off from the loop manually for the model have required tasks been automated, not only has it eliminated human manipulation but also enabled users to discover the hidden patterns and correlations that were ignored by human analysts.

The use of Generative AI in BI applications proves to have various optimization options. First of all, these approaches increase scalability and accessibility of analytics solutions, thus granting organizations an opportunity to spread the advanced analytics capabilities not only across the departments but also across the functions without a need of specialised knowledge. AI-Empowered Business Analytics Software for Finance or Marketing teams will have AI-Powered Smart Interfaces which allow the users to derive actionable results with minimum learning.

Additionally, machine learning with AI, smart analytics and generative AI variation introduces a huge leap in the AI-driven wisdom capability allowing the organization to make informed decisions with certainty and lucidity. These systems transform huge data sets into valuable patterns which eventually amplify human decision-making proficiencies, thus, executives can tackle uncertain strategic issues hand in hand with analyzing capability. Whether it’s incorporating artificial supply chain management, demand forecasting or new revenue generation, AI Generative AI powered businesses in exploring new frontiers in their data resources.

The main example of the Generation AI is that, it is capable of adapting and developing new algorithms all the time as it’s instructed and the new information is provided. The ongoing cycle of continuous learning is the direct way towards improving the accuracy and reliability of AI-based forecasting. These points also give organizations the chance to stay nimble and adaptable to the dynamic business environment. Therefore, the companies will benefit from having a secured place in the future marketplace because generative AI is an effective and a revolutionary tool that enables them to stop losing to the competitors.

Besides, the democratization of Generative AI for Business Intelligence spurs innovation and entrepreneurship into a whole new dimension. It does this by lowering the door where most people can enter but in addition, it equips individuals with advanced analytics tools which they use to not only make data driven decisions but also try out new things. It isn’t sequestered to a small group of larger companies but rather is open to any business that wants to utilize it, and they are not discriminated against because of their size. Whether it is a startup looking to disrupt an industry or a small business seeking to optimise its operations, Generative AI interfaces level the playing field, enabling entities of every dimension to compete and succeed in digital economy.

In conclusion, the implementation of Generative AI inside Business Intelligence structure is a pivotal step for how to unlock the power of data with the purpose of encouraging the growth and creativity of organizations. Through the act of democratizing the advanced analytics tools and the premature artificial intelligence analytics, businesses gain wide access to advanced methods of decision making, faster. It can help unraveling hidden insights or making forecasts, or simply optimizing operations. This is how Generative AI interfaces become a new horizon of opportunities with which organization need to catch-up. Furthermore the journey of this disruptive technology is yet to discover its full extent and hence the future is highly satisfying.

[programmmingexperts]

Tableau Course: Is it Worth it to Learn Tableau for Data Science in 2024

Introduction

In today’s data-driven world, the demand for skilled data scientists is at an all-time high. Data professionals are expected to possess a multitude of skills, including proficiency in data visualization tools. One such tool that has gained considerable popularity in recent years is Tableau. As we approach the year 2024, a pertinent question arises — is it worth it to learn Tableau for data science? In this blog, we will explore the benefits of learning Tableau, its relevance in the field of data science, and provide answers to frequently asked questions on the topic.

Benefits of Learning Tableau

User-Friendly Interface and Ease of Use

One of the standout features of Tableau is its user-friendly interface. Whether you are a beginner or an experienced data scientist, Tableau’s intuitive interface makes it easy to learn and use. With its drag-and-drop functionality, data analysis and visualization become a breeze, eliminating the need for extensive coding knowledge. This ease of use allows users to focus on interpreting data and uncovering insights rather than getting bogged down by technicalities.

Robust Data Visualization Capabilities

Data visualization plays a crucial role in data science, as it helps in effectively communicating insights to stakeholders. Tableau excels in this area by offering a wide array of visually appealing and interactive charts, graphs, and dashboards. The ability to create compelling visualizations allows data scientists to present complex data in a simplified manner, making it easier for decision-makers to grasp insights quickly.

Integration with Multiple Data Sources

Tableau provides seamless integration with a variety of data sources, including spreadsheets, databases, and cloud platforms. This integration enables data scientists to work with large datasets from diverse sources, eliminating the need for manual data extraction and consolidation. By connecting directly to data sources, Tableau saves time and allows real-time analysis and visualization, a crucial aspect in the fast-paced world of data science.

Advanced Analytics and Machine Learning

Tableau offers advanced analytics capabilities, allowing data scientists to perform complex calculations, statistical analysis, and predictive modeling within the tool. Furthermore, with the integration of machine learning algorithms into the Tableau platform, users can explore and discover patterns, trends, and outliers in their data. This integration of advanced analytics and machine learning makes Tableau a valuable tool for data science professionals.

Relevance of Tableau in Data Science in 2024

Data science is an ever-evolving field, and staying updated with the latest tools and technologies is critical for success. As we approach 2024, Tableau is projected to remain a dominant force in the data visualization landscape. Many organizations across industries have adopted Tableau as their preferred tool for data analysis and exploration. Its popularity can be attributed to its ease of use, robust visualization capabilities, and ability to integrate with multiple data sources.

Additionally, Tableau’s continuous innovation and commitment to staying at the forefront of data visualization technology make it a valuable asset for data scientists. The Tableau community is vast and supportive, providing resources, forums, and training opportunities for users to enhance their skills and knowledge. As the demand for data professionals with Tableau expertise continues to rise, learning Tableau in 2024 can provide a competitive edge in the job market.

Conclusion

In conclusion, learning Tableau for data science in 2024 is unquestionably worth it. With its user-friendly interface, potent data visualization capabilities, and integration with diverse data sources, Tableau stands as an invaluable tool. In a job market hungry for skilled data professionals, Tableau expertise sets you apart. Stay ahead in data science — invest in learning Tableau today. SkillUp Online offers a tailored Tableau course for your success. Enroll now and unlock the potential of meaningful insights from data!

FAQs

Q1. Is Tableau only useful for data visualization?

While Tableau is renowned for its data visualization capabilities, it is more than just a visualization tool. Tableau offers robust data analysis, integration with multiple data sources, and advanced analytics features, making it an indispensable tool for data science professionals.

Q2. Do I need to have coding knowledge to learn Tableau?

No, Tableau eliminates the need for extensive coding knowledge due to its user-friendly interface and drag-and-drop functionality. However, having a basic understanding of database concepts and SQL can be helpful for leveraging Tableau’s full potential.

Q3. Can Tableau handle large datasets?

Yes, Tableau can handle large datasets by leveraging efficient data extraction and compression techniques. Additionally, Tableau’s ability to connect to various data sources enables users to work with datasets of all sizes, even in real-time.

[munaeem]

10X Your Excel Skills with Copilot

Here’s a brief summary of the key points from the YouTube page “10X Your Excel Skills with Copilot” by Pavan Lalwani: The video, hosted by Pavan Lalwani, aims to significantly enhance Excel skills using Microsoft’s Copilot tool. The video has over 359,000 views and has received numerous positive comments. Viewers appreciate the clear and concise demonstrations provided by Pavan Lalwani,…

[generative-ai-in-bi]

Generative AI: Redefining Data Analysis in Business

In the swiftly changing environment of data analysis, companies are permanently requiring for novel approaches to be able to find manageable outputs and gain a market advantage. Step into Generative AI – an innovative technology that is about to rewrite the way organizations generate and analyze their data. Here, we explore the revolutionary power of Generative AI in changing the old data analysis methods and helping organizations to take more competent decisions that would contribute to the growth and sustainability of the business.

Introduction to Generative AI in Business Intelligence:

As businesses have to deal with the increasing volumes of data, the demand for advanced analytics tools has never been higher than now. AI-driven generative technology brings about the transformational change in the way data analysis is carried out, helping to fabricate artificial data, forecast trends, and enhance the decision-making process.

Understanding the Landscape of AI Business Analytics Tools:

AI driven business analytics tools have emerged as essential assets in the arsenals of organizations from various industries. They use their advanced algorithms and machine learning methods to received important insights from complicated datasets.

The Role of Generative AI in AI-Powered Business Intelligence:

Generative AI is the essence of AI-powered business intelligence which enables companies to extract and use meaningful insights from multiple data sources. The accurate simulations and forecasts made by the Generative AI empower businesses to predict market trends, discover and exploit opportunities, prevent problems before they occur.

Harnessing AI Predictive Analytics for Strategic Decision-Making:

AI predictive analytics, as the core of the cutting-edge business intelligence methodology, makes it possible for companies to forecast trends with incredible accuracy. Through historical data pattern analysis and real-time information inclusion, AI predictive analytics promotes data-driven decision making at each organizational level.

Unlocking the Potential of AI-Based Forecasting:

AI-based forecasting algorithms utilize sophisticated machine learning models, which enable them to predict future patterns and trends. AI-based forecasting, in its function as demand prediction, financial planning, and resource optimization, helps businesses to allocate resources effectively and to stay at the cutting edge.

Empowering Decision Support Systems with AI-Driven Insights:

DSS (Decision support systems), which are AI-driven, furnish the decision-makers with insightful recommendations and strategy for their findings. Through processing huge datasets to identify the connections, AI-based DSS provide organizations with the possibility of making real-time informed decisions.

The Evolution of AI-Enabled Business Reporting Solutions:

More and more modern business reporting products are being generated as an answer to the growing need for your real-time insights and customizable analytics. Advanced AI-powered reporting systems utilize natural language processing and data visualization technologies to tailor dynamic reports to the distinct needs of the stakeholders

Visualizing Data with AI-Powered Data Visualization:

AI-supported data visualization tools allow companies to change intricate datasets into attractive and interactive visual models. These tools empower data analysis with the aid of sophisticated algorithms and pattern recognition tools which in turn provides a platform for informed decision making.

Navigating the Future of Data Analytics with Generative AI:

As organizations become a part of the digital transformation era, Generative AI is ready to take its place as one of the core principles in shaping data analytics of the future. From improving the accuracy of forecasts to revealing the unknown information, Generative AI will provide you with the key to new chances for decision-making based on data.

Embracing Enterprise AI Adoption for Competitive Advantage:

For business entities, AI investment is no more a luxury but a necessary strategic move for organizations wishing to gain competitive edge. Organizations can be able to automate most operations, reduce inefficiencies, and improve innovation across every aspect of their business simply by incorporating Generative AI into their business intelligence frameworks.

Conclusion: Revolutionizing Data Analysis with Generative AI:

Ultimately, Generative AI can be the revolutionary technology that will transform business minds about data processing forever. A new worldwide development approach is the merger of humans with artificial intelligence, and it can be used by organisations for multiple purposes like detection of new opportunities and risks and managing of sustained growth in a very complex and competitive world.

It is hard to tell whether thanks to its data model creation ability, virtual prediction of the nearest future and preparation of the solutions for the decision-makers, Generative AI will make a revolution in the area of data analysis and thus it will change business intelligence. To get past the hindrances and exploit the upsides, digital age businesses will adopt Generative AI which is critical for the future of the data-dominant world in which they are competitive.

[connectinfosofttech]

Business Analytics Services | Connect Infosoft | Data-Driven Solutions

Discover the transformative potential of your data with Connect Infosoft's Business Analytics services. Our expert team offers comprehensive solutions to unlock actionable insights and drive informed decision-making. From analytics consulting to advanced tools and visualization services, we empower businesses to harness the full power of their data. Partner with us for predictive analytics, data visualization, and business intelligence tools that pave the way for success.

For more info: Click Here

[milkoomi]

how to make finals your bitch. ᥫ᭡

- be at your best to give it your best -

hello angels! so it’s been almost 2 months since i’ve been active on here & it’s simply just been due to me focusing a lot of my time and energy into my academics, career, & personal life! i’m nearing the end of my program with my externship just being one month away! as with a lot of us, the spring semester is slowly but surely coming to an end! and that means finals are just around the corner! i wanted my “comeback” to be some of my helpful tips, tricks, & tidbits of advice for getting through finals and making sure you pass with flying colors!

also, thank you so so much for 1.2k!! i didn’t expect to gain such an influx of followers while i was gone! it means so much to me that so many of you have supported my blog even during my inactivity/unexpected hiatus! i can’t promise i’ll be coming back completely as i have my externship coming up, so i’ll be very busy the next few months! but i hope to continue to post every now and again for you angels!

let’s begin …

୨ৎ — pre-finals prep

it’s important to start prepping for finals in advance! finals may be 4-5 weeks away, but it never hurts to get a head start in your preparations!

create a checklist! — you can always start by making yourself a list or two for everything you need to get yourself prepared for that intimidating finals week! these lists could be a list of different study materials you’ll need, a list in order of priority of the different classes you need to study for, a list of supplies you’ll need to get yourself through the week (& yes, this can include snacks or any self-care stuff!), or even a list of different topics from your classes that you feel need a bit more of your attention! checklists are an amazing tool to use to keep yourself organized and can help you visual what needs to get done or what needs to be obtained!

plan out the weeks! — designate a day in your week where you take some time to plan out your weeks prior to finals week and the week of! include time blocks where you set aside time to study and time to take breaks and rest your mind & body! add small, achievable to-do lists for each day or a bigger, more broad one for each week! weekly planning can give you a tangible idea of what your weeks leading up to finals and the week of will look like, so don’t hesitate to give it a try or incorporate that into your weekly routine!

tina’s tip: utilize your phone’s calendar app! i do almost everything digitally and i’ve been making great use of the Apple calendar to plan out my weeks! it’s a great way to color code different events, classes, appointments, assignments, etc. & if you’re also someone who wants to get into digital planning it’s a great first step into getting into it!

prioritize & maintain good health! — i’m saying this with love, but pulling all-nighter’s every single day leading up to finals is not going to guarantee the best scores for you. you need to make sure your health is where it needs to be! sleep is absolutely vital to making sure your mind and body is working at its very best. as someone who used to be an insomniac and who used to religiously pull all-nighter’s for school, i’m telling you it is not worth it. i didn’t see any improvement in my grades when i was doing that. if anything, my scores and my motivation for school got worse. you can’t just go all night racking your brain over your studies. prioritize your health! this also means making sure you fuel your brain and body with good nutrients! when i’m only running on caffeine, not only do i feel physically weak, but my mind is using so much more energy on becoming anxious than staying focused.

tina’s tip: make sure you set aside time at least once or twice a week to something that makes you happy, helps you relax, and is not related to your academics! i have a rule for myself that after 7:30pm-8pm every single night that i immediately stop working on anything related to my studies so that i can truly unwind for the night. i’ll use my time before bed to have a self-pamper night, play video games, watch a show/movie/youtube video, draw, read, or chat with a friend on facetime! it’s important to include things that bring you joy into your routine! don’t burn yourself out by only focusing on your studies!

୨ৎ — the study wave

try to give yourself at least two weeks in advance to study for finals. consider these two weeks as the study wave! this is the perfect time to really lock into those time-blocks you’ve set aside for your study sessions. each day should be filled with review & ensuring you fully understand the material! the time-blocks could be as long as 5 hours or as short as 30 minutes. i recommend the start of the study wave to include longer study time-blocks and as you get closer to the week of finals to shorten those time-blocks!

week 1 of study wave — reteaching yourself the material: rewatch lectures, review powerpoints/videos/notes/previous homework assignments, and incorporate study methods like the feynman technique, practice tests, & active recall! use this time to form study groups, don’t hesitate to have longer study sessions (remember to take breaks!), and refresh your mind of everything you need to know for upcoming exams! let week 1 help you decide what material/topics/chapters/classes need more of your time and attention and which ones don’t!

tina’s tip: dedicate certain days out of the week to 1-2 classes! this will help to prevent any overwhelming feelings of stress, anxiety, and/or burn-out as you prepare for finals! prioritize which class(es) need the most review, maybe a couple classes need more than one designated study/review day and maybe other classes just need one day throughout the week!

week 2 of study wave — refresh & review: utilize study methods like the blurting method, flashcards, practice tests, & other forms of active recall! this is prime time to focus on active recall methods. doing so will help make sure the information stays fresh in your mind and will help you refine that mental list of which classes/topics still need a little more attention! week 2 of the study wave should included shorter study sessions whether it’s 1 or 2 hours shorter than week 1 or even as short as setting aside 20 minutes every day reviewing material. take this time to try and focus more on those more challenging topics rather than reviewing every single bit of information!

tina’s tip: if you use the blurting method, i recommend using it towards the end of your study sessions! this allows you to recall information as well as put it into your own words that will show whether or not you comprehend the material. review what you’ve written down based off of memory and identify any missing points or errors in your work! this will also help you refine what bits of information still need more focus! repeat this method 3 times!

i highly encourage you guys to also use this time to meet with professors/instructors to ask any additional questions! you’d be surprised at how much of a difference it makes to ask those pressing questions on different parts of the material!

୨ৎ — finals week

it’s extremely important that you are getting enough rest the week of finals! it all sounds cliché, but making sure you’re well-rested and you’ve filled your body with the right nutrients can make such a crucial difference in your exam performance!

if you have time in-between different exams, use that time to do quick review sessions to prepare for your next exam!

avoid cramming! — these in-between study sessions should be used wisely and in an effective manner. take some time to focus on material that has been challenging for you and don’t worry too much about reviewing parts that you’re already confident with!

keep the review short! — if you have 30 minutes or even a couple hours before your next final, do not use the entire time of your “break” to study/review! give your mind a break to rest! listen to some music, play a cozy game, or even take a quick nap if you’re able to! a lot of your mental energy should be put into your time taking the exam, so don’t expend all that energy into studying/reviewing!

final notes —

finals can be exhausting, anxiety-inducing, and just an overall challenge. since it’s that time of the semester where, i’m sure, most of us are starting to experience a drop in the level of our academic motivation, it’s really important to maintain a good and reliable study/school routine to keep yourself on the track you ideally want to be on!

i stress this a lot in my other posts, but self-care is extremely important in being able to maintain good routines in your day to day life! so be sure you’re still incorporating time to focus on your self care to keep yourself afloat!

with lots of love, faustina 🌷

[avelera]

Can we hear your thoughts on Jayce’s and Viktor’s intelligence? I can’t help but feel like Jayce is often…dumbed down. Which feels insulting to the both of them.

Rarrrr.... I should be doing other things... but this is a rage button issue for me... so....

Jayce is just as smart as Viktor.

The reason he doesn't come across as just as smart has multiple elements:

1 ) Arcane S1 in particular does a lot of sleight of hand to set up Jayce as facing down a corruption arc where he's tempted by fame and power. They achieve this in multiple ways. On an emotional level, they often zoom out for his more tender lines and zoom in when he says something dumb or unfortunate.

Intellectually, they tend to show things like his chalkboard after the fact, when he's not at it, but they show things like Viktor actively working in the lab quite a lot. Basically, we see Viktor doing a lot more active science stuff while he's doing it, but with Jayce we tend to see the effects of the science stuff he's already done, like presenting prototypes that are already made, him holding hexgems that are already created, showing equations and notes of his that are already complete instead of showing him making them.

Overall, this creates a visual impression that Jayce is the dumber of the two, because we see him doing less actively, but if you pay attention he's doing at least as much science as Viktor regularly, it's just more off-screen.

2 ) Viktor wouldn't partner with someone who's not as smart as him.

Viktor reroutes his entire life to work with Jayce after reading his notes on Hextech. It's insulting to Viktor's intelligence to think he would "lower himself" to working with Jayce. Jayce is his equal, his partner, they compliment each other and both accomplish things the other couldn't.

For my money, Viktor is the more out-of-the-box thinker, Jayce comes from a family of tool makers and he tends to think in straight lines, most of his innovations are direct results of the spells he saw his Mage do, like weightlessness and transportation, while Viktor tends to come up with things like the Hexclaw and the Hexcore.

But both are also craftsmen and tinkerers, and it was Jayce's idea originally to do magic with technology, Viktor is working with him to innovate on that vision.

3 ) Jayce is a better public speaker and he's physically attractive and muscular, in a way that makes people underestimate his intelligence. It is very common for people who are good at speaking, people who are of above average attractiveness and, god forbid, people who keep an exercise routine to be seen as less smart even though those things have nothing to do with one another. Because Jayce is seen as the "face" of Hextech it's assumed that he's the lesser intellectual partner, when the truth is, it's just a division of labor. Viktor is terrible at public speaking and doesn't like doing it, Jayce is charismatic so he does it.

He's not a gym jock, his muscles come from the forge where he makes absolutely mind-bogglingly advanced items like Caitlyn's sniper rifle and his own hammer, the guy is basically making Hadron Colliders over an anvil. But because people tend to judge based on appearances, people tend to think he's dumb.

4 ) Jayce thinks in straight lines. He's incredibly direct. The reason he agrees to raid the Shimmer Factory with Vi is because he's sick of politics and he's sick of the corruption, and he wants to just deal with a problem directly. That's why he and Vi bring out the worst in each other, because they both think like that, and straight lines aren't always the best way to tackle a difficult problem, but Jayce is a scientist, he's used to seeing a problem and just fucking solving it.

The problem is, that doesn't work for all problems. He's incredibly smart as an engineer, literally Ambessa can't even find a scientist in Piltover as good as him and Viktor, but he's not widely read. He's not a politician or a diplomat or a social scientist. This also lends to the perception that he's dumb but you'll notice, Viktor is never put in a position to make decisions like that, Mel is never put in lab to solve a scientific equation, and in general, most characters aren't put in a position where they have to perform at the top of more than one field in the way Jayce is, so yeah, Jayce ends up looking dumb because he has to handle being the leader of a city when he spent his life working on Hextech and promoting Hextech. Of course he's not going to be perfect.

But that's also another case of sleight of hand, we see Jayce failing at more things because we see him thrown in a position to impact more things. A lot of characters maintain their image of being smarter or more skilled than him because they're not asked to work outside their range of skills nearly so often.

[dragonnarrative-writes]

Generative AI Is Bad For Your Creative Brain

In the wake of early announcing that their blog will no longer be posting fanfiction, I wanted to offer a different perspective than the ones I’ve been seeing in the argument against the use of AI in fandom spaces. Often, I’m seeing the arguments that the use of generative AI or Large Language Models (LLMs) make creative expression more accessible. Certainly, putting a prompt into a chat box and refining the output as desired is faster than writing a 5000 word fanfiction or learning to draw digitally or traditionally. But I would argue that the use of chat bots and generative AI actually limits - and ultimately reduces - one’s ability to enjoy creativity.

Creativity, defined by the Cambridge Advanced Learner’s Dictionary & Thesaurus, is the ability to produce or use original and unusual ideas. By definition, the use of generative AI discourages the brain from engaging with thoughts creatively. ChatGPT, character bots, and other generative AI products have to be trained on already existing text. In order to produce something “usable,” LLMs analyzes patterns within text to organize information into what the computer has been trained to identify as “desirable” outputs. These outputs are not always accurate due to the fact that computers don’t “think” the way that human brains do. They don’t create. They take the most common and refined data points and combine them according to predetermined templates to assemble a product. In the case of chat bots that are fed writing samples from authors, the product is not original - it’s a mishmash of the writings that were fed into the system.

Dialectical Behavioral Therapy (DBT) is a therapy modality developed by Marsha M. Linehan based on the understanding that growth comes when we accept that we are doing our best and we can work to better ourselves further. Within this modality, a few core concepts are explored, but for this argument I want to focus on Mindfulness and Emotion Regulation. Mindfulness, put simply, is awareness of the information our senses are telling us about the present moment. Emotion regulation is our ability to identify, understand, validate, and control our reaction to the emotions that result from changes in our environment. One of the skills taught within emotion regulation is Building Mastery - putting forth effort into an activity or skill in order to experience the pleasure that comes with seeing the fruits of your labor. These are by no means the only mechanisms of growth or skill development, however, I believe that mindfulness, emotion regulation, and building mastery are a large part of the core of creativity. When someone uses generative AI to imitate fanfiction, roleplay, fanart, etc., the core experience of creative expression is undermined.

Creating engages the body. As a writer who uses pen and paper as well as word processors while drafting, I had to learn how my body best engages with my process. The ideal pen and paper, the fact that I need glasses to work on my computer, the height of the table all factor into how I create. I don’t use audio recordings or transcriptions because that’s not a skill I’ve cultivated, but other authors use those tools as a way to assist their creative process. I can’t speak with any authority to the experience of visual artists, but my understanding is that the feedback and feel of their physical tools, the programs they use, and many other factors are not just part of how they learned their craft, they are essential to their art.

Generative AI invites users to bypass mindfully engaging with the physical act of creating. Part of becoming a person who creates from the vision in one’s head is the physical act of practicing. How did I learn to write? By sitting down and making myself write, over and over, word after word. I had to learn the rhythms of my body, and to listen when pain tells me to stop. I do not consider myself a visual artist - I have not put in the hours to learn to consistently combine line and color and form to show the world the idea in my head.

But I could.

Learning a new skill is possible. But one must be able to regulate one’s unpleasant emotions to be able to get there. The emotion that gets in the way of most people starting their creative journey is anxiety. Instead of a focus on “fear,” I like to define this emotion as “unpleasant anticipation.” In Atlas of the Heart, Brene Brown identifies anxiety as both a trait (a long term characteristic) and a state (a temporary condition). That is, we can be naturally predisposed to be impacted by anxiety, and experience unpleasant anticipation in response to an event. And the action drive associated with anxiety is to avoid the unpleasant stimulus.

Starting a new project, developing a new skill, and leaning into a creative endevor can inspire and cause people to react to anxiety. There is an unpleasant anticipation of things not turning out exactly correctly, of being judged negatively, of being unnoticed or even ignored. There is a lot less anxiety to be had in submitting a prompt to a machine than to look at a blank page and possibly make what could be a mistake. Unfortunately, the more something is avoided, the more anxiety is generated when it comes up again. Using generative AI doesn’t encourage starting a new project and learning a new skill - in fact, it makes the prospect more distressing to the mind, and encourages further avoidance of developing a personal creative process.

One of the best ways to reduce anxiety about a task, according to DBT, is for a person to do that task. Opposite action is a method of reducing the intensity of an emotion by going against its action urge. The action urge of anxiety is to avoid, and so opposite action encourages someone to approach the thing they are anxious about. This doesn’t mean that everyone who has anxiety about creating should make themselves write a 50k word fanfiction as their first project. But in order to reduce anxiety about dealing with a blank page, one must face and engage with a blank page. Even a single sentence fragment, two lines intersecting, an unintentional drop of ink means the page is no longer blank. If those are still difficult to approach a prompt, tutorial, or guided exercise can be used to reinforce the understanding that a blank page can be changed, slowly but surely by your own hand.

(As an aside, I would discourage the use of AI prompt generators - these often use prompts that were already created by a real person without credit. Prompt blogs and posts exist right here on tumblr, as well as imagines and headcannons that people often label “free to a good home.” These prompts can also often be specific to fandom, style, mood, etc., if you’re looking for something specific.)

In the current social media and content consumption culture, it’s easy to feel like the first attempt should be a perfect final product. But creating isn’t just about the final product. It’s about the process. Bo Burnam’s Inside is phenomenal, but I think the outtakes are just as important. We didn’t get That Funny Feeling and How the World Works and All Eyes on Me because Bo Burnham woke up and decided to write songs in the same day. We got them because he’s been been developing and honing his craft, as well as learning about himself as a person and artist, since he was a teenager. Building mastery in any skill takes time, and it’s often slow.

Slow is an important word, when it comes to creating. The fact that skill takes time to develop and a final piece of art takes time regardless of skill is it’s own source of anxiety. Compared to @sentientcave, who writes about 2k words per day, I’m very slow. And for all the time it takes me, my writing isn’t perfect - I find typos after posting and sometimes my phrasing is awkward. But my writing is better than it was, and my confidence is much higher. I can sit and write for longer and longer periods, my projects are more diverse, I’m sharing them with people, even before the final edits are done. And I only learned how to do this because I took the time to push through the discomfort of not being as fast or as skilled as I want to be in order to learn what works for me and what doesn’t.

Building mastery - getting better at a skill over time so that you can see your own progress - isn’t just about getting better. It’s about feeling better about your abilities. Confidence, excitement, and pride are important emotions to associate with our own actions. It teaches us that we are capable of making ourselves feel better by engaging with our creativity, a confidence that can be generalized to other activities.

Generative AI doesn’t encourage its users to try new things, to make mistakes, and to see what works. It doesn’t reward new accomplishments to encourage the building of new skills by connecting to old ones. The reward centers of the brain have nothing to respond to to associate with the action of the user. There is a short term input-reward pathway, but it’s only associated with using the AI prompter. It’s designed to encourage the user to come back over and over again, not develop the skill to think and create for themselves.

I don’t know that anyone will change their minds after reading this. It’s imperfect, and I’ve summarized concepts that can take months or years to learn. But I can say that I learned something from the process of writing it. I see some of the flaws, and I can see how my essay writing has changed over the years. This might have been faster to plug into AI as a prompt, but I can see how much more confidence I have in my own voice and opinions. And that’s not something chatGPT can ever replicate.