Personally, I find this focus on integrating data measurement and informing key stakeholders to be essential in advancing healthcare practices and ultimately improving patient care. It highlights the importance of proactive approaches in leveraging data to drive informed decision-making and optimize patient outcomes. Furthermore, it underscores the significance of providing actionable and timely data to enhance patient outcomes.
I regularly use MATLAB as a simulation tool for the class tutorials in my technical courses.
This MATLAB GUI teaching application for Ferroresonance Simulation for undergraduate engineering curricula is designed and implemented in this paper. The GUI provides a user‐friendly interface to help students understand the characteristics of ferroresonance models in a virtual interface.
This is a great tool for students to learn by changing the simulation parameters, such as power system, transmission line, load, and fault data, and observing their effects on the type of ferroresonance.
Here is an interesting debate surrounding the demise of AI prompt engineering, which sparks discussion about its evolving role and relevance. I believe prompt engineering techniques are obsolete, but others contend that they have merely been transformed. The advent of large language models (LLMs) like GPT-3 has shifted focus towards fine-tuning prompts rather than crafting them meticulously. This shift emphasizes the importance of understanding how to leverage these models effectively, harnessing their capabilities through nuanced input manipulation. However, this evolution doesn't render prompt engineering irrelevant; it necessitates adaptation and innovation. Refining prompts remains crucial in optimizing LLM performance for diverse applications.
Prompt engineering persists in a new form, reflecting the dynamic nature of AI development and utilization. https://spectrum.ieee.org/prompt-engineering-is-dead
I was surprised to reveal that OpenAI's GPT-4 generated copyrighted content in 44% of its prompts, underscoring a pressing issue. Language model training data frequently includes copyrighted material, making it simple for models to reproduce it verbatim. This poses substantial legal and reputational threats to companies employing these models. To mitigate these risks, it's imperative to detect such reproductions. The Copyright Detection API for LLMs, like Patronus.ai's offering, emerges as a crucial solution.
https://www.patronus.ai/blog/introducing-copyright-catcher
Its features likely include robust algorithms capable of identifying copyrighted content, safeguarding against legal entanglements, and preserving the integrity of AI-driven systems. Embracing such tools is essential for responsible AI development and deployment in today's landscape.
Here is how to submit a paper to the Journal of Aircraft using the ScholarOne Manuscripts system. All authors, including the corresponding author, will receive an email for contribution verification. I like that the complete submission requires confirmation from all authors. You can check the submission status by logging into AIAA ScholarOne Manuscript site and selecting the Author Center.
Access the submission link here: https://mc.manuscriptcentral.com/aiaa-ja
I concur that AI tools should not be recognized as co-authors of scientific papers. While AI can be invaluable in aiding individuals with disabilities in accessing scientific literature through enhanced language formatting, it is essential to maintain that humans author the core concepts, insights, and conclusions. This ensures the integrity and authenticity of scholarly work while leveraging AI's capabilities to improve accessibility for all individuals, regardless of their abilities. Check this webinar on AI tools in scientific publishing https://www.peeref.com/webinars/external/368
I fully agree that AI tools should not be listed as paper co-authors. While AI can undoubtedly assist in language formatting and even offer suggestions, the core ideas, knowledge, and conclusions should be the product of human intellect and research. Allowing AI to be credited as co-authors blurs the line between human and machine contributions, potentially undermining the integrity and authenticity of scholarly work. Instead, AI tools should be used as aids to enhance the quality and efficiency of scientific publishing while preserving the fundamental role of human expertise in knowledge creation and interpretation.
Looking for a PhD position! Tilburg School of Social and Behavioral Sciences offers a PhD in Sociology for a 4-year project on uncertainty around candidate quality and discriminatory hiring outcomes. You will fit well for this position if you have strong quantitative skills and an affinity for sociology.
To apply, submit a cover letter detailing your interest in a specific research project and relevant skills, along with your CV, including contact details for two references. Include transcripts for both Bachelor's and Master's degrees and provide an academic writing sample, such as a draft of your master's thesis.
Start date: September 1, 2024 (sooner or later upon mutual agreement)
You can find the vacancy here: https://career5.successfactors.eu/career?career%5fns=job%5flisting&company=S003974031P&navBarLevel=JOB%5fSEARCH&rcm%5fsite%5flocale=en%5fUS&career_job_req_id=22173&selected_lang=en_US&jobAlertController_jobAlertId=&jobAlertController_jobAlertName=&browserTimeZone=Europe/Amsterdam&_s.crb=SznzKuJKo8%2fH5hJcgKE2p5pBmyRkfJBf%2fvfQ%2bD8YXI4%3d
The webinar comprehensively analysed the complexities of water table flooding, focusing on Texas' upper coast barrier islands. Dr Dorina Murgulet's expertise elucidated groundwater flow modelling and the effects of extreme weather on water quality.
I was personally interested in the machine learning models developed. This insightful session offered invaluable insights for addressing environmental challenges, enhancing understanding, and promoting sustainable solutions.
One of the primary emphases in the computer vision field is on artificial intelligence algorithms for segmentation and classification, such as machine learning and deep learning techniques. The fundamental disadvantage of supervised segmentation techniques is that they require a big dataset of ground truth validated by medical professionals.
This work introduces a novel graphical user interface application (MedicalSeg) for managing medical imaging based on preprocessing and segmentation.
In my perspective, this app's benefits are twofold: first, it builds a test platform for comparing segmentation algorithms, and second, it generates segmented photos to create ground truths that can later be used as artificial intelligence tools.
According to Arkham, Tesla Inc. and SpaceX have a combined total of around 19,800 Bitcoins. The stash is divided across many wallets: Tesla holds around 11,500 BTC across 68 addresses, while SpaceX holds around 8,300 tokens across 28 wallets. The tokens are worth over $1.4 billion after Bitcoin reached new all-time highs and crossed above the $72,000 level. https://markets.businessinsider.com/stocks/tsla-stock?op=1
How long will this hype of Bitcoin last this time?
I'm considering a one-year post-doctorate position at Reykjavik University, which is extendable for an additional year at Magnus M. Halldorsson's laboratory. The salary is approximately 4400 EUR per month. Funded by the Icelandic Research Fund, the project focuses on randomized distributed graph coloring algorithms and encompasses general algorithms research, with a new emphasis on machine learning theory, particularly graph neural networks. Applicants must email a PDF CV with a publication list to mmh@ru.is, a statement demonstrating their suitability for the project and the contact information of at least two references. Informal inquiries are encouraged. The application deadline is 30 March 2024.
I can't find more information on this open call on the official web page https://en.ru.is/the-university/open-positions/nr/27331. Share your experience with a post-doc application with e-mail invitations only.
Revolutionizing Banking with Digital Transformation
Digital transformation has sparked dramatic changes in the banking industry, altering how financial institutions operate and deliver services.
https://www.itu.int/cities/digitaltransformationdialogues/banking/
Adopting online and mobile banking platforms is an important part of banking's digital revolution.
These user-friendly interfaces allow clients to seamlessly make transactions, manage accounts, and access financial services from their devices, promoting convenience and accessibility.
Can Artificial intelligence and Machine Learning revolutionize several elements of banking, including customer service and fraud detection?
This year, I'm participating in the European Research and Innovation Days 2024. This annual flagship event brings together policymakers, researchers, stakeholders, and the public to debate and shape the future of research and innovation in Europe and beyond. This fifth edition will take place during the Research and Innovation Week on March 20 and 21, 2024. You can sign up for online participation here https://projects.research-and-innovation.ec.europa.eu/en/events/upcoming-events/research-innovation-days
研讨会