Articles tagged with Software
Researchers propose a new approach to reduce the tradeoff between overhead and protecting machines against vulnerabilities. The 'Vulnerability-Adaptive Protection Paradigm' applies different protection strategies to different parts of the system, allocating resources more wisely.
A team of researchers aims to improve autonomous vehicle safety by identifying and mitigating vulnerabilities in software and hardware. They plan to use knowledge gained from a $926,737 NSF award to design protection mechanisms that can be applied selectively to ensure safety while maximizing efficiency.
A new course launched with funding from the UK Space Agency to address the growing skills gap in software, data, and AI for the UK space sector. The Securing the future of space: Space Software and Data/AI CPD programme will equip mid-career professionals with expertise in AI and data-science.
Researchers at Boston University created an AI tool that can determine the cause of dementia using commonly collected patient data, boosting doctor accuracy by 26%. The algorithm identifies 10 types of dementia, including vascular and frontotemporal dementia, to help doctors manage patients more effectively.
Researchers at USC developed an approach that matches polysomnography using a single-lead echocardiogram, allowing anyone to create their own low-cost, DIY sleep-tracking device. The software significantly outperformed other EEG-less models and assesses sleep stages at the highest level.
A large multicenter study has identified 34 new genetic diseases using genetic diagnostics, including a novel AI-powered analysis tool called GestaltMatcher. The study analyzed the genetic data of 1,577 patients and found changes in 370 different genes, with 425 children diagnosed with rare diseases.
A study found that large language models, despite accuracy in medical exams, fail to consistently request necessary examinations and often deviate from treatment guidelines. In comparison to human doctors, AI diagnoses achieved lower accuracy rates, highlighting concerns about their suitability for everyday clinical practice.
Researchers developed a new method to study rock engravings, integrating technological and visual analysis to uncover the cultural significance of engravings in Timna Park. The approach provides comprehensive insights into the production processes and cultural context of ancient engraving practices.
A recent study investigates the trust and involvement of Cameroonian software developers in open-source projects, highlighting cultural biases and infrastructural limitations as major barriers. The research aims to enhance understanding of trust mechanisms within these communities, focusing on African developers' unique challenges.
A team of researchers developed EMOKINE software to measure the objective kinematic features of movements that express emotions. The software provides movement parameters from data sets at the touch of a button, allowing scientists to analyze emotional expression and intentions.
The WVU researchers developed a non-invasive, at-home sleep apnea detection device that uses artificial intelligence technology to measure oxygen levels in the blood. Early detection can help prevent worsening of underlying comorbid conditions and reduce healthcare costs, according to Dr. Sunil Sharma.
A new study identifies six best practices for addressing non-functional requirements (NFRs) to ensure software security and performance. The research highlights the importance of NFRs in determining software quality and success, and how developers discuss and manage these requirements.
Researchers developed a symbolic model checking approach to verify quantum circuits, addressing the gap between model-checking quantum programs and quantum circuits. They used Maude programming language to formally specify and verify quantum circuits, confirming their correctness and paving the way for error-free quantum computing.
The University of Bonn has developed an AI software that can simulate the growth of field crops using drone photos. This allows farmers to estimate parameters such as leaf area or yield with high accuracy, and even predict the outcome of certain interventions. The software also focuses on polycultures, which can boost yields by reducin...
A recent study published in Anesthesia & Analgesia found that clinical decision support software can prevent up to 95% of medication errors in the operating room. The software provides evidence-based information to clinicians at the point-of-care to enhance decision-making and prevent errors.
Researchers from Mainz University and the University of Chile are developing a new technique called Gradual Abstract Interpretation to improve program analysis methods and detect security vulnerabilities in WebAssembly. They aim to identify and address security vulnerabilities while eliminating redundant protective measures.
Research from Texas McCombs finds that developers who multihome their software attract more users to the original product, improving its performance and standing out in the market. The study also shows that multihoming can lead to a 5.3% increase in average monthly usage for similar products.
Two new Parnas Fellows, Prof. Hongyu Zhang and Prof. Daniela Damian, will share their expertise with researchers at Lero, enabling collaboration and knowledge sharing. The fellowship programme has brought world-class software researchers to Ireland to share their experience and expertise.
Researchers developed CT-Derived Functional Imaging, a software program that calculates lung volume changes and blood mass without contrast dye. The technology has improved diagnoses for up to 30% of patients who couldn't tolerate contrast dye, and also benefits all patients with lung issues such as COPD and cancer.
Konstantinos Mamouras, assistant professor of computer science at Rice University, has been awarded a $547,555 NSF CAREER Award to decentralize IoT applications and relieve network congestion. He aims to introduce novel programming techniques that enable efficient and reliable IoT development.
A new tool called VFCFinder analyzes open-source software updates to pinpoint specific code sections being modified to address security vulnerabilities. This helps programmers determine which updates are necessary without unnecessary changes.
A study reviewed 100 US institutions with National Center of Academic Excellence in Cybersecurity designations, finding significant variation in program types, credits, and learning outcomes. The research aims to improve industry-readiness and graduate employability by highlighting areas for improvement in cybersecurity education.
Researchers created GraSSRep and rhea, tools that outperform current methods for handling repeats and structural variants in metagenomic data. These methods use self-supervised learning and graph neural networks to analyze microbiome data, offering new insights into biological processes and potential applications in antibiotic resistance.
A new AI method developed by Swedish researchers can identify toxic substances based on their chemical structure, potentially replacing animal testing. The method has been shown to be more accurate and broadly applicable than existing computational tools, offering a promising alternative for environmental research and authorities.
A study by Washington State University found ChatGPT's generative AI system provided inconsistent heart risk assessments for patients with chest pain. The AI failed to match traditional methods used by physicians and returned different results for the same patient data, highlighting its limitations in high-stakes clinical situations.
A computer vision researcher has developed privacy software for surveillance videos that obscures identifiable information such as faces and clothing in real-time. The software, funded by the National Science Foundation's Accelerating Research Translation program, aims to balance surveillance needs with privacy concerns.
Using AI software called SLEAP, scientists at Salk Institute are designing climate-saving plants with optimized root systems that can store more carbon. This approach enables researchers to analyze plant features and connect desirable traits to targetable genes, accelerating the development of carbon-capturing plants.
A Wayne State University researcher is working to transform code review tools and workflows to address participants' challenges in understanding and communicating code changes. The goal is to produce high-quality feedback using empirical methods, machine learning, and natural language techniques.
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.
The digital twin of a railway wireless network uses scenario modeling, radio wave propagation characterization and integrated operation platforms to improve safety and efficiency. The study introduces key technologies such as ray tracing and AI-based super-resolution to achieve accurate deterministic modeling of wireless channels.
A new study introduces a high-performance rail inspection system using YOLOv8 for fast and accurate defect detection. The system achieved up to 281.06 FPS on desktop systems and 200.26 FPS on edge computing platforms, increasing processing speeds while maintaining high accuracy levels.
Researchers at Kennedy Krieger Institute and Johns Hopkins Medicine developed a new method for analyzing walking and gait using free software and cellphone videos. This approach is more accessible and quicker than current state-of-the-art methods, enabling clinicians to assess patients' walking abilities more conveniently.
Researchers developed Umwelt software that allows blind and low-vision users to build customized data representations without an initial visual chart. The system incorporates three modalities: visualization, textual description, and sonification.
Researchers at University of Missouri are developing software that allows drones to fly independently, perceiving and interacting with their environment while achieving specific goals. This technology has the potential to assist in mapping and monitoring applications, such as 3D or 4D advanced imagery for disaster response.
Researchers developed a new tool to improve the accuracy of electronic devices that measure plant leaf color to assess health. The software uses polarization to account for variations in light and reduce errors caused by glare.
A four-month department-wide EHR optimization project led to improved usability and reduced administrative burdens. The study demonstrates that successful EHR workflow optimization is possible at the departmental level through ongoing collaboration between EHR users and IT colleagues.
A new measure called “outdoor days” describes the number of days per year that outdoor temperatures are neither too hot nor too cold for people to go about normal outdoor activities. This measure reveals significant global disparities, with the North gaining more outdoor days and the South losing them due to rising temperatures.
A new Dartmouth study reports on a unique case of prosopometamorphopsia (PMO), a rare condition that distorts facial features. The researchers used computer software to visualize the patient's real-time perception of face distortions, providing accurate and photorealistic visualizations for the first time.
The selected research project aims to develop a lightweight edge AI-based technology for jointly exploiting wireless communications and sensing in smart factories. It will enable high-quality wireless communications even under challenging situations.
Communications of the ACM has been revamped as a web-first, open-access publication, enabling rapid article publication and enhanced reader experience. The new model aims to increase engagement with the broader computer science community, expand author reach, and showcase cutting-edge ideas and research.
Researchers found counterexamples to ADOPT's termination and optimality properties, potentially leading to suboptimal solutions or failure to terminate. They proposed a modified version that corrects these issues, ensuring the algorithm's termination and optimality.
A new study by Zachary Kowaleski found that RegTech investments can have operational benefits for large broker-dealers, including improvements in customer relations and employee monitoring. However, small companies were more negatively affected, with profits dropping by an average of over 10 times the apparent savings.
Scientists have created an algorithm to design synthetic DNA segments that indicate the state of cells in real-time. This tool will be used to screen for anti-cancer or viral infection drugs, as well as improve gene and cell-based immunotherapies.
A new camera system records natural animal-view videos with high accuracy, enabling scientists to study animal behavior and navigation. The system uses four color channels, including UV light, to produce accurate video of how animals perceive colors.
Researchers have designed a new, affordable system to study neural interactions and compute using living neurons. The open-source MiV system boasts over 500 electrodes, offering improved control and precision in measuring neural processes.
Incheon National University researchers developed a web 3.0 streaming architecture that reduces delay, improves user experience, and ensures transparency and fairness for real-time services. The proposed system uses Inter-Planetary file system (IPFS) to enable blockchain-based peer-to-peer data storage and caching.
Quantum Research Sciences has developed a quantum computer software that achieves 28% improved accuracy over classical computers in predicting optimal inventory levels. The software will be used by the US Air Force to manage its supply chain, reducing costs associated with excess or inadequate inventory.
A new data collection system has been developed to support diverse applications in the railway industry, including carbon emissions accounting and green cost-benefit analysis. The system enables efficient data collection and integrated management, leveraging metadata and data exchange schemas.
A new study uses reinforcement learning to develop an AI model that can hedge derivative contracts with significantly lower training data requirements. The model's adaptability and accuracy under realistic conditions outperformed benchmark systems.
The new platform, Arras Energy, simulates how all parts of an electric grid work together, making it easier to understand and apply the results. The tool can help utilities harden their distribution systems against extreme weather and integrate renewable energy sources.
Scientists at the University of Washington School of Medicine developed a novel protein design approach using AI, creating proteins that bind to challenging biomarkers with exceptionally high affinity and specificity. The breakthrough has implications for drug development, disease diagnosis, and environmental monitoring.
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.
Researchers developed a new solver algorithm for the MPAS-Ocean ocean circulation model, reducing run time by 45% and enabling semi-implicit stability. This allows for faster climate predictions and energy efficiency, as well as reduced computational power consumption.
A new algorithm, SIMSEF, significantly speeds up and simplifies the identification of chemicals in tissues, enabling researchers to confidently recognize and visualize their distribution in organs. This development has great implications for medical diagnosis and treatment outcomes.
A new software algorithm intelligently combines vocals and instrumentals from different songs, mimicking professional music composition techniques. The result is a unique blend of pleasing lyrics and exciting instrumentals that appeal to listeners, particularly hip-hop fans.
The study reveals a diverse landscape of software as a medical device (SaMD) with notable progress in artificial intelligence/machine learning-based devices, accounting for 22% of all FDA-approved SaMDs. Established companies focus on incremental innovations, while new entrants and start-ups drive disruptive innovation.
Professor Sebastian Erdweg aims to automatically incrementally compute software for significant energy savings. His new project AutoInc seeks to overcome fundamental limitations of existing approaches, promising enormous improvements in efficiency.
A new study reveals AI tools are more vulnerable than thought to targeted attacks that force AI systems to make bad decisions. Researchers developed a software called QuadAttac K to test for vulnerabilities in deep neural networks.
Researchers developed DIRFA, an AI-based program that generates realistic videos with facial animations synchronized to spoken audio, showcasing improvements over existing approaches. The tool has potential applications in healthcare, education, and entertainment, enhancing user experiences.
A team of researchers from Northwestern University and the University of Pittsburgh has received a $600K NSF Award to explore novel learning-enabled cyber-physical systems (LE-CPSs) for building flexibility into hardware. This could lead to extended device lifespan, reduced e-waste, and improved sustainability.