Articles tagged with Knowledge Based Systems
Devadas pioneered the field of hardware security, making foundational contributions to Trusted Execution Environments (TEEs), Physical Unclonable Functions (PUFs), and Side Channel Resistant Processors. His innovations have shaped both academia and industry, safeguarding data in a digital world.
Researchers create PhishLumos AI system to detect phishing campaigns by analyzing infrastructure clues, achieving 8-day faster detection than experts. The system uncovered over 190,000 new links, with 92% later flagged as malicious, outperforming content-centric approaches.
TurboLynx, developed by POSTECH researchers, analyzes complex, interconnected data up to 184 times faster than existing systems. The engine groups similar data together and processes them collectively, reducing unnecessary memory usage and enabling efficient analytical queries.
A recent EHU study reveals that overreliance on generative AI tools can undermine key learning skills. However, students with strong self-regulation abilities are less likely to fall into this trap, as they tend to use AI as a tool for speed rather than relying solely on its responses.
ACM recognizes educators Yasmin Kafai and Mitchel Resnick for their contributions to creative computing and Scratch. Ed Felten receives the ACM Policy Award for his work on technology policy, while Jodi Tims is honored with the Outstanding Contribution to ACM Award for increasing women's participation in computing
Nicki Washington, a Duke University professor, has been recognized by the Association for Computing Machinery (ACM) for her exceptional commitment to diversifying the computing community. Her mentoring programs have led to increased student success and career opportunities.
The report examines how generative AI tools are transforming software development, offering benefits such as increased productivity but also raising security vulnerabilities and technical debt. Strong software engineering practices are still required to ensure systems are secure, reliable, and maintainable.
A recent study from Lancaster University reveals that AI systems like ChatGPT can learn to mirror human impoliteness, potentially escalating into verbal violence. The research tested ChatGPT's ability to respond to real-life impolite interactions, finding it often produces more impolite behavior than humans.
Ricardo Baeza-Yates has made fundamental contributions to computer science through his pioneering work in algorithms and information retrieval. He has fostered a vibrant transnational research community across Latin America, inspiring young people with the South American Programming Contest.
Researchers developed a lightweight fault-diagnosis framework for high-speed train bogies using selective knowledge distillation-based domain adaptation. The approach improves cross-domain diagnostic accuracy by at least 2.1% while keeping the final model size to 28.5 kB.
Matei Zaharia's work on open-source systems like Apache Spark, Delta Lake, and MLflow has enabled large-scale machine learning, analytics, and AI at global scale. His innovations have made scalable computing accessible to researchers, nonprofits, and enterprises across every industry.
The conference will feature keynote dialogues, fireside chats, and panel discussions on key themes such as AI and education, law and regulation, public governance, and global cooperation. Distinguished participants include senior representatives from international organisations and public policy institutions.
Digital Science acquires Ontopic, a pioneer in Virtual Knowledge Graph technology, to democratize research data and provide enterprise-grade AI solutions. The acquisition enables users to build and access Knowledge Graphs directly from existing data sources.
Researchers at Dartmouth College developed a mathematical framework to map students' conceptual knowledge from short multiple-choice quizzes, revealing peaks of mastery and valleys of struggle. The technique could enable personalized learning, AI tutoring systems, and more efficient feedback.
A new study proposes a framework for connecting AI risk prediction systems with scheduling platforms to detect emerging risks and adjust project plans before delays occur. This approach aims to close the gap between early warning and actionable response, enabling more resilient project delivery.
Researchers at the University of East London identified a critical weakness in Industrial Internet of Things networks that can destabilize factories and safety-critical infrastructure. Attackers can exploit subtle 'delay attacks' to quietly disrupt coordination, making timing just as important as information in highly automated systems.
A global study documents the collective ecological memory of Indigenous Peoples and local communities, revealing a consistent pattern of large-bodied bird species disappearing from local environments replaced by smaller-bodied species, with average bird mass declining from 1500g to 535g over eight decades.
Researchers developed an autonomous AI network technology that enables multiple AI systems to spontaneously collaborate and share knowledge to discover new materials. This collaboration improves exploration efficiency and paves the way for the creation of numerous new materials.
Researchers develop a framework that mirrors human expert assessment to verify AI-generated answers, filtering out clear mistakes and identifying nuanced gaps. The system saves thousands of working hours and highlights the importance of contextual knowledge and internal documentation.
The ACM's Technology Policy Council has issued a report on automated speech recognition (ASR) highlighting the need for rigorous audit and governance practices. The report raises concerns about technological bias, inequity, and lack of transparency in ASR systems.
The UAE has launched an AI ecosystem to support climate-resilient farming in vulnerable communities worldwide. The CGIAR AI Hub and four other initiatives aim to drive digital transformation and innovation in agriculture, providing practical solutions for farmers, governments, and development actors.
The German Research Foundation extends TRR 318 'Constructing Explainability' for a further three and a half years, focusing on context within explanations to develop more comprehensible AI systems. The collaboration involves over 60 researchers across seven disciplines, aiming to create social forms of explainable AI.
Researchers aim to understand and overcome the limitations of current large language models, which make mistakes despite extensive training. The Emmy Noether Research Group will focus on developing new architectures with predictable capabilities.
The University of Houston is designing robotic hands with dexterity for industries such as healthcare, agriculture, and manufacturing. The team, part of the NSF Convergence Accelerator program, has received $5 million in funding to develop hybrid polymeric materials that can mechanically retract and perform motions like flexion.
Researchers at the University of Missouri have developed an AI-powered method to detect hidden hardware trojans in chip designs, offering a 97% accurate solution. The approach leverages large language models to scan for suspicious code and provides explanations for detected threats.
The Wits MIND Institute has received a $1 million boost from Google.org, enabling it to drive next-generation breakthroughs in natural and artificial intelligence. The partnership aims to advance the scientific understanding of both natural and artificial intelligence, foster breakthrough research and technological innovation.
The 34th International Joint Conference on Artificial Intelligence (IJCAI) will take place in Montreal, Canada, from August 16 to 22, 2025. The conference aims to showcase the frontiers of artificial intelligence research and applications, with a focus on AI's impact on society.
Researchers use AI to solve differential equations, such as Schrodinger's equation, for large-scale systems, improving efficiency and accuracy in fields like drug discovery and material design.
Stanford researchers introduce a cost-effective way to evaluate AI language models, accounting for question difficulty to ensure fair comparisons. The new approach reduces costs by half and enables rapid progress in the field of artificial intelligence.
The new journal aims to accelerate knowledge dissemination in AI by prioritizing theoretical breakthroughs, practical applications, and societal implications. It features short peer-reviewed contributions and opinion pieces to facilitate swift engagement with contemporary AI issues.
The College of Engineering at Texas A&M is developing a suite of university-wide resources to integrate generative AI into course material, research, and outreach. The initiative aims to make generative AI a core part of the academic toolkit accessible to faculty across disciplines.
Prof. AU Man Ho Allen has been recognized with the prestigious Hong Kong Engineering Science and Technology (HKEST) Award 2024-25 for his outstanding contributions to the Web3 ecosystem and the digital economy. His research focuses on developing practical, secure, and privacy-preserving cryptographic solutions.
Ashish Sharma's dissertation developed fundamental advances in natural language processing to positively impact mental health. His AI-supported tools have been used by over 160,000 people, with more than fifty percent of users reporting a household income of less than $40,000 per year.
A recent study found that nearly 1 in 6 adults with hypertension and 3 in 10 with diabetes were unaware of their condition by 2021-2023. Young adults and women are disproportionately affected by a lack of awareness.
University of Missouri researchers create digital sentiment map using AI to analyze public Instagram posts, linking emotional tone to real-life features. The tool aims to improve city services, identify areas of concern, and inform emergency response decisions.
This year's ACM awards recognize groundbreaking innovations in autonomous systems, cryptography, and software for parallel computers. Peter Stone receives the Allen Newell Award for contributions to AI, while William Gropp and his team receive the Software System Award for developing MPICH.
The study highlights the need to reconstruct human education due to increasing uncertainties in politics, economy, science, and technology. A proposed strategy includes rebuilding an educational contract based on understanding and cooperation, developing a dynamic lifelong education system, and exploring AI-empowered education models.
A new approach to AI developed by Texas A&M University engineers mimics the human brain's neural processes, integrating learning and memory in a single system. This 'Super-Turing AI' has the potential to revolutionize the industry by reducing energy consumption and environmental impact.
Researchers at Mizzou have developed a proactive approach using artificial intelligence to address evolving threats against smart grids. The CIBR-Fort system can predict cyberattacks with 91.88% accuracy and defend against them in real-time, enabling scalable security for power grids of the future.
Researchers at Graz University of Technology developed a new database to improve speech recognition of Austrian German using speech data from 38 speakers. They found that traditional HMM-based systems are more robust for short sentences and dialectal language, while transformer-based models excel with longer sentences and context.
A new study by Lancaster University reveals that language in job ads can unintentionally reinforce or disrupt labour force gender/racial composition. Workforces with more women tend to use family-friendly policies in ads, while racial minority workers' ads lack impact, the research shows.
Experts from UTHealth Houston and Baylor College of Medicine developed a pragmatic approach to monitor and manage AI systems in healthcare organizations. The guidance emphasizes the need for robust governance systems, testing processes, and transparency with patients to ensure safe AI adoption.
Researchers developed a framework called SigLLM that uses large language models to detect anomalies in time-series data. The approach converts time-series data into text-based inputs and can be deployed right out of the box, offering an efficient anomaly detection solution for complex systems.
A study found that GPT-4 matched the performance of radiologists in detecting errors in radiology reports, with an accuracy rate of 82.7%. The use of GPT-4 resulted in lower mean correction cost per report than the most cost-efficient radiologist.
A new study by Carey Morewedge and colleagues found that people are more likely to recognize bias in algorithmic decisions than their own. This is because algorithms can codify and amplify human bias, but also reveal structural biases in society. The research suggests ways to increase awareness of biases and correct them.
The TRAILS AI Institute has awarded eight seed grants totaling $1.5 million to advance AI design, development and governance. The funded projects include developing AI chatbots for smoking cessation and designing animal-like robots for autism support.
A NSF-funded project, MABLE, is developing a digital app using crowdsensing, AI, and robotics to empower individuals with responsive maps and turn-by-turn instructions. The app aims to improve accessibility and navigation for persons with visual or mobility impairments, such as those with low vision and wheelchair users.
A Lancaster University academic argues that AI and algorithms contribute to polarization, radicalism, and political violence, posing a threat to national security. The paper examines how AI has been securitized throughout its history, highlighting the need for better understanding and management of its risks.
The University of Trento coordinates a European research network, Elias, aiming to establish Europe as a leader in AI research. The project focuses on developing new computational systems and models for sustainable innovation, social cohesion, and reliable AI.
Researchers found AI chatbot responses to top cancer queries are generally accurate but lack actionable information. These limitations suggest relying on chatbots for supplementary purposes rather than primary medical information.
ChatGPT consistently provided accurate, evidence-based answers in public health questions, beating rival AI assistants. Meanwhile, Amazon Alexa and Google Assistant struggled to recognize or refer users for help.
A recent study assessed an AI chatbot's ability to answer ophthalmic questions, finding it answered approximately half correctly. The results suggest that while AI has medical advances, the current chatbot is not yet ready for substantial assistance in board certification preparation.
A new neural network, CD-GAN, uses common sense knowledge to enhance text descriptions and generate images of birds at three resolution levels. The system achieved competitive scores against other image generation methods, producing vivid and natural-looking images.
A survey study of 19,000 patients found that self-managed abortion was prevalent before accessing in-clinic care, particularly among those with limited access. The findings suggest a need for increased access to telemedicine and decentralized abortion care models.
A new study found that repeated requests for personal data increase disclosure, despite unchanged concerns about privacy. Researchers suggest practical measures to reduce this effect and encourage mutually beneficial sharing.
A recent study in Los Angeles County found that more than half of adults with Omicron variant infection were unaware of their infectious status. Health care employees had higher awareness rates than non-employees, highlighting the need for increased vigilance and testing to prevent transmission.
A scoping review of knowledge graph applications in medical imaging analysis identifies increasing trend and potential future directions. The study highlights the effectiveness of prior knowledge in medical imaging tasks, but also reveals limitations, including limited annotated data and weak generalizability.
Researchers aim to create a flexible security feature that learns from past cyberattacks and requires minimal human intervention. They'll collaborate with device developers to share solutions and improve future responses to attacks.
Researchers developed WebFRIS, a web-based platform to provide socio-economic vulnerability analysis and simplify flood risk information. The tool can help formulate targeted solutions and enhance social capacity and resilience in flood-prone regions.