Articles tagged with Computer Processing
A new camera system called PrivacyLens can replace people in images with generic stick figures, protecting their identities and reducing unnecessary surveillance. This technology could prevent embarrassing photos from being shared online and make patients more comfortable using cameras for chronic health monitoring.
A recent study analyzing 300,000 X posts found that 48 US states have a more positive than negative tone towards nuclear energy, with a national average at 54% positive. Concerns about waste, cost, and safety dominate negative sentiment, while technology themes fuel positive sentiments highlighting innovations and job creation.
Researchers have developed a system combining bio-inspired cameras with AI to quickly detect obstacles around cars, using less computational power. The hybrid system detects objects up to one hundred times faster than current systems while reducing data transmission and processing needs.
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 neural network-based system called BONES improves video streaming quality by up to 13% while reducing download size, according to NJIT researcher Jacob Chakareski. The system uses a mathematical function to optimize data transmission and can be applied to various platforms, including popular video conferencing services.
Researchers at UMass Amherst have developed an analog computing device called a memristor that can complete complex scientific tasks while reducing energy consumption. The device uses physical laws to perform computations in a massively parallel fashion, accelerating matrix operations and overcoming the limitations of digital computing.
A team of researchers developed a time-optimal control method for autonomous ships, optimizing maneuvering performance in dynamic sea conditions. The new control system accounts for various forces affecting ship movement and can improve efficiency and safety, reducing shipping costs and carbon emissions.
The Heidelberg Laureate Forum Foundation offers limited international journalist travel grants to report on the event. Journalists can apply until April 28, 2024, and will cover travel and visa costs, as well as room and board during their stay in Heidelberg.
Researchers have invented a simple yet effective algorithm called SIEVE to optimize cache management. By labeling objects as 'zero' or 'one', the system efficiently evicts the least recently used items, reducing computational complexity and bugs.
Researchers at Stanford University have developed a new phase-change memory that could help computers process large amounts of data faster and more efficiently. The technology improves several metrics simultaneously, including speed, endurance, and stability, while operating below 1 volt.
A novel robotic system developed by USC researchers can help clinicians accurately assess a patient's rehabilitation progress. The method generates an 'arm nonuse' metric using machine learning and a socially assistive robot to track how much a patient is using their weaker arm spontaneously.
A new study using twisted magnets as computational medium has made brain-inspired computing more adaptable, reducing energy use and potential carbon emissions. The research found that by applying magnetic fields and changing temperature, physical properties of the materials can be adapted to suit different machine-learning tasks.
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 Portuguese team TWIZ from NOVA School of Science and Technology secured 1st Place in the Alexa TaskBot Challenge 2 with a multimodal conversational agent. The winning team was led by João Magalhães and included CMU Portugal Affiliated Ph.D. students Diogo Tavares and Diogo Silva, who improved their visual interface as their biggest...
Researchers develop integrated photonic-electronic hardware capable of processing three-dimensional (3D) data, doubling parallelism for AI tasks and significantly boosting energy efficiency. The new chip can process 100 electrocardiogram signals simultaneously with high accuracy, outperforming electronic processors.
Researchers aim to develop programmable formal specification-based data stream processor and hardware monitor to enhance microchip security and prevent malfunctions. They will explore novel technologies for real-time monitoring of physical and biological systems, including signal patterns within computer chips.
A new study uses machine learning to analyze data from DrugAge, a database of chemical compounds modulating lifespan in model organisms. The researchers create four types of datasets to predict whether or not a compound extends the lifespan of C. elegans, using features such as compound-protein interactions and Gene Ontology terms.
A new editorial explores the potential of machine learning to enhance early cancer detection in primary care, leveraging extensive patient data and improving risk stratification accuracy. The authors emphasize the need for responsible implementation, collaboration, and validation across diverse populations.
Lero is recruiting 16 top international post-doctoral researchers for a €2.9 million fellowship program focusing on privacy, trust, inclusion and fairness in software expertise. The program will provide discipline-specific skills training and enhance career development.
A new study from the University of Copenhagen and Roskilde University found that computers malfunction between 11 and 20 percent of the time, wasting users' productivity. The researchers identify insufficient performance and lack of user-friendliness as the two biggest categories of problems.
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.
In a new study, NC State University researchers had high school students develop their own machine-learning AI models to analyze data. The project aimed to prepare students for the future workforce and help them understand the potential and challenges of AI. Students created text classification models using StoryQ technology, which all...
Assistant Professor Reza Ahmadzadeh at UMass Lowell has been awarded a $500,000 NSF CAREER grant to develop new algorithms for robots to learn complex tasks. The project aims to improve robot performance in everyday tasks, enabling them to assist older adults with daily chores and automate difficult duties in the workplace.
Researchers at the University of Missouri are acquiring a new transmission electron microscope (TEM) with a $800,000 grant from the National Science Foundation. The TEM will allow them to conduct experiments in real-time and gain a greater understanding of material structure at an atomic level.
Researchers have developed a high-speed, 3D gigapixel microscope that stitches together dozens of cameras to capture life in unprecedented detail. The device enables the recording of differences in pitch and depth, allowing scientists to study zebrafish behavior and developmental biology without harming the animals.
The Heidelberg Laureate Forum Foundation offers journalist travel grants to cover the 10th HLF from September 24-29, 2023. Recipients of prestigious awards in mathematics and computer science will gather with young researchers for a week of interdisciplinary dialogue.
University of Missouri engineers are working on a collaborative human-robot order picking system to speed up the online delivery process. The proposed model aims to optimize key decisions in warehouse operations, allowing robots to navigate efficiently and collaborate with humans to increase efficiency.
Researchers from McGill University and MIT developed an AI system that can learn the rules and patterns of human languages on its own. The model automatically generates higher-level language patterns that can be applied to different languages, achieving better results.
Researchers at Stanford University have created a new chip architecture called NeuRRAM that performs AI computing directly within memory, reducing energy consumption and increasing efficiency. The chip has been tested on various AI tasks and shown high accuracy rates.
NTU Singapore has launched the Algorand Centre of Excellence at NTU (ACE@NTU), a new research and education centre focused on developing and advancing blockchain technologies. The centre aims to become the nexus for blockchain education and research in Singapore and the region.
A team of researchers at Osaka University has created a machine learning system that can virtually remove buildings from a live view, streaming in real-time on a mobile device. This technology can help accelerate the process of urban renewal based on community agreement, reducing conflicts and delays.
Researchers at University of Virginia are developing long-lived sensors for the Internet of Things (IoT) to reduce maintenance costs and upgrade challenges. The goal is to create an ecosystem that enables sensors to adapt to changing environments, reducing electronic waste.
PaSh parallelizes Unix shell scripts automatically and accurately, boosting execution speeds by hundreds of times. Researchers tested the system on hundreds of scripts and found no errors, making it accessible to data scientists, biologists, engineers, and economists.
Researchers at ETH Zurich have developed a novel memristor design that can switch between two operation modes, enabling greater efficiency in machine learning applications. This breakthrough component is made of halide perovskite nanocrystals and simulates complex neural networks with high accuracy.
Researchers at North Carolina State University have developed FAXID, a hardware-based approach for detecting ransomware that is significantly faster than software-based methods. In proof-of-concept testing, FAXID demonstrated accuracy comparable to XGBoost but with speeds up to 65.8 times faster.
Scientists from the University of Copenhagen have discovered a fundamental property of magnetism that could lead to the development of more powerful and efficient computers. The discovery highlights the potential for magnetism to replace traditional electron-based computing methods.
Developed by Prof. Qing Shi's team, SQuRo can mimic the motion of actual rats and perform various motions like crouching-to-standing, walking, crawling, and turning. It successfully passed through an irregular narrow passage and demonstrated its potential application to inspection tasks inside narrow spaces.
Researchers at Nara Institute of Science and Technology developed a new calibration method to compensate for variations in illumination while scanning stained-glass windows. This approach can help capture the colors of cultural artifacts in a lifelike way, even with long scanning times.
Researchers developed a new reading method for SOT-RAMs that can nullify the readout disturbance, reducing it by at least 10 times. The method involves creating a bi-directional read path, cancelling out the disturbances produced by spin currents.
A study by the University of Texas at Austin found that software development teams given greater autonomy are more productive and have higher customer satisfaction rates. The researchers tested 461 projects over 50 months and found a 39% increase in value added for autonomous teams compared to traditional teams.
Researchers have developed a custom finger clip device that measures blood pressure and other vital signs like heart rate, oxygen saturation, body temperature, and respiratory rate. The device uses photoplethysmography sensors and achieves an accuracy rate of about 90% for systolic blood pressure.
The University of Texas at Arlington has received a $1.5 million grant from the US Department of Education to support domestic doctoral students specializing in Internet-of-Things study and research. The project aims to increase diversity among computer science researchers, with a focus on women and minorities.
Fred Martin, a UMass Lowell computer scientist, is being recognized for developing an educational framework that introduces robotics and AI to K-12 students. His work has guided the development of primary and secondary AI education initiatives worldwide.
Researchers have demonstrated ultrafast optical circuit switching for datacenters using integrated soliton microcombs, which can handle increasing bursty datacenter applications while reducing overheads. The proposed architecture employs a central comb system to improve power efficiency and reduce complexity.
A team of researchers from Osaka University has designed a sulfonated polyaniline network for reservoir computing, achieving 70% accuracy in speech recognition tasks. The device uses an electrochemical approach and has potential applications in the development of artificial intelligence devices.
SUTD researchers develop sensor that assigns dirt score to areas based on visual and tactile analysis, allowing for more efficient exploration of complex spaces. The sensor is integrated with a smart algorithm that directs the robot to focus on areas with high dirt probability.
Researchers created a novel molecular device that can be reconfigured multiple times using varying applied voltages, similar to the human brain's plasticity. The device retains information for future retrieval and processing, offering a potential solution to the von Neumann bottleneck.
Researchers at OIST Graduate University develop robots capable of conducting complex experiments and analyzing data. The 'Nobel Turing Challenge' achieves significant advancements in scientific discovery by leveraging AI-driven robotics.
A new $2.7 million grant from the US Department of Energy will support a three-year research effort to identify and store quantum information in solids, enabling significant advancements in quantum computing. The project aims to build a database of viable qbits by analyzing defects in solids.