Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a node’s representation. Disentangled GCNs have been proposed to divide each node’s representation into several feature channels. However, current disentangling methods do not try to figure out how many inherent factors the model should assign to help extract the best representation of each node. To solve the problems, a research team led by Chuliang WENG published…
The new method optimises the technical design with regard to classic objectives such as costs, efficiency and package space requirements and also takes greenhouse gas emissions along the entire supply chain into account The development of vehicle components is a lengthy and therefore very costly process. Researchers at Graz University of Technology (TU Graz) have developed a method that can shorten the development phase of the powertrain of battery electric vehicles by several months. A team led by Martin Hofstetter…
Medieval friar William of Ockham posited a famous idea: always pick the simplest explanation. Often referred to as the parsimony principle, “Ockham’s razor” has shaped scientific decisions for centuries. But lately, incredibly complex AI models have begun outperforming their simpler counterparts. Consider AlphaFold for predicting protein structures, or ChatGPT and its competitors for generating humanlike text. A new paper in PNAS argues that by relying too much on parsimony in modeling, scientists make mistakes and miss opportunities. First author and…
Evaluation of an AI-based voice biomarker tool to detect signals consistent with moderate to severe depression Background and Goal: Depression impacts an estimated 18 million Americans each year, yet depression screening rarely occurs in the outpatient setting. This study evaluated an AI-based machine learning biomarker tool that uses speech patterns to detect moderate to severe depression, aiming to improve access to screening in primary care settings. Study Approach: The study analyzed over 14,000 voice samples from U.S. and Canadian adults….
Are humans or machines better at recognizing speech? A new study shows that in noisy conditions, current automatic speech recognition (ASR) systems achieve remarkable accuracy and sometimes even surpass human performance. However, the systems need to be trained on an incredible amount of data, while humans acquire comparable skills in less time. Automatic speech recognition (ASR) has made incredible advances in the past few years, especially for widely spoken languages such as English. Prior to 2020, it was typically assumed…
Additional data can help differentiate subtle gestures, hand positions, facial expressions The Complexity of Sign Languages Sign languages have been developed by nations around the world to fit the local communication style, and each language consists of thousands of signs. This has made sign languages difficult to learn and understand. Using artificial intelligence to automatically translate the signs into words, known as word-level sign language recognition, has now gained a boost in accuracy through the work of an Osaka Metropolitan…
Researchers from Osaka University introduced an innovative technology to lower power consumption for modern memory devices. Stepping up the Memory Game: Overcoming the Limitations of Traditional RAM Osaka, Japan – Numerous memory types for computing devices have emerged in recent years, aiming to overcome the limitations imposed by traditional random access memory (RAM). Magnetoresistive RAM (MRAM) is one such memory type which offers several advantages over conventional RAM, including its non-volatility, high speed, increased storage capacity and enhanced endurance. Although…
Cutting-Edge Framework for Enhancing System Security Researchers at the University of Electro-Communications have developed a groundbreaking framework for improving system security by analyzing business process logs. This framework focuses on ensuring that role-based access control (RBAC) rules-critical to managing who can access specific system resources-are correctly implemented. Noncompliance with these rules, whether due to error or malicious activity, can result in unauthorized access and pose significant risks to organizations. Challenges in Ensuring Compliance with RBAC Policies RBAC is a widely…
AQSolotl’s quantum controller is designed to be adaptable, scalable and cost-efficient. Quantum technology jointly developed at Nanyang Technological University, Singapore (NTU Singapore) and National University of Singapore (NUS) has now been spun off into a new deep tech startup, AQSolotl. The startup’s flagship product, CHRONOS-Q, is a quantum controller that acts as a translator between conventional computing systems and quantum computers. Developed by university researchers affiliated with Singapore’s Centre for Quantum Technologies (CQT), it enables users to control quantum computers…
Pacific Northwest National Laboratory to contribute leadership to national effort in microelectronics design and development. Microelectronics run the modern world. Staying ahead of the development curve requires an investment that doesn’t just keep pace but sets new standards for the next generation of technological advances. Today, the Department of Energy announced the creation of three Microelectronics Science Research Centers to address the nation’s specific needs for microelectronics designed to operate in extreme environments such as high radiation, extreme cold, and…
With a processing speed a billion times faster than nature, chip-based laser neuron could help advance AI tasks such as pattern recognition and sequence prediction. Researchers have developed a laser-based artificial neuron that fully emulates the functions, dynamics and information processing of a biological graded neuron. With a signal processing speed of 10 GBaud —a billion times faster than its biological counterparts — the new laser graded neuron could lead to breakthroughs in fields like artificial intelligence and other types…
New technology could remotely identify various types of plastics, offering a valuable tool for future monitoring and analysis of oceanic plastic pollution. Researchers have developed a new hyperspectral Raman imaging lidar system that can remotely detect and identify various types of plastics. This technology could help address the critical issue of plastic pollution in the ocean by providing better tools for monitoring and analysis. “Plastic pollution poses a serious threat to marine ecosystems and human livelihoods, affecting industries like fisheries,…
Artificial Intelligence (AI) has established a strong presence across industries, large and small. The “VoBaKI” research project has empowered small and medium-sized enterprises (SMEs) with an innovative tool to independently champion the challenges of using artificial intelligence (AI). Rational and accessible solutions were developed to assist SMEs on their journey towards an AI future while collaborating with the FIR at RWTH Aachen University and the Institute of Ergonomics (IAW) at RWTH Aachen University and along with the support of numerous…
APECS Pilot Line starts Operation in the Framework of the EU Chips Act. The pilot line for “Advanced Packaging and Heterogeneous Integration for Electronic Components and Systems” (APECS) marks a major leap forward in strengthening Europe’s semiconductor manufacturing capabilities and chiplet innovation as part of the EU Chips Act created under the “Chips for Europe” initiative of the European Commission. Within APECS, the institutes collaborating in the Research Fab Microelectronics Germany (FMD) will work closely with European partners, to make…
Europe is investing heavily in the future of telecommunications, with four major 6G projects involving the University of Oulu launching in January 2025. Funded through the SNS JU (Smart Networks and Services Joint Undertaking), these initiatives represent a substantial EU commitment, with a total budget of €39.6 million across the projects. Collectively, the projects aim to tackle critical challenges in sustainability, resilience, collaboration, and human-centric innovation. SNS JU’s role in shaping Europe’s 6G development is significant. The SNS JU was…
Fraunhofer HHI and Partners Launch First Open-Source 5G FR2 MIMO Demonstrator. Fraunhofer Heinrich-Hertz-Institut (HHI) and its partners, Allbesmart, National Instruments (NI), and TMYTEK, have unveiled the world’s first open-source 5G FR2 MIMO demonstrator. This cutting-edge test platform for 5G and future 6G technologies features high-bandwidth capabilities at 28 GHz, allowing users to explore advanced technologies such as joint communication and sensing. The use of multiple antennas enhances link stability and maximizes bitrates. The demonstrator was developed as part of the…
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