Articles tagged with Information Processing
Research found that sounds can influence how we perceive objects visually, making related sounds prioritize certain features. This effect was observed in three experiments, showing that audio input influences object-morph selection speed and accuracy when played during visual discrimination phase.
A new Dartmouth study uses a subjective approach to investigate how people perceive social interactions. The results show that the brain responds more strongly to information interpreted as social versus non-social, highlighting humans' tendency to see social connections.
Researchers developed a spreadsheet tool to analyze large comment samples and identify themes within patient comments. The HCP Review Comment Analysis Tool allows providers to easily analyze patient comments and identify actionable measures of patient satisfaction, providing insights into specific actions by healthcare practitioners.
Researchers developed a new machine-learning framework that enables cooperative or competitive AI agents to consider the future behaviors of all agents, not just their teammates or competitors. This framework, FURTHER, uses two modules: an inference module and a reinforcement learning module, to enable agents to adapt their behaviors a...
A novel multi-modal image retrieval system, DenseBert4Ret, has been developed by researchers from Gwangju Institute of Science and Technology (GIST) using deep learning algorithms. The system outperforms state-of-the-art models in retrieving images based on both image and text features.
Deep learning models can become less accurate in recognizing specific categories of images, sounds, or text after network pruning. Researchers demonstrate a technique to address this challenge, improving the fairness of deep learning models.
A recent study published in Engineering Construction & Architectural Management identified the main obstacles preventing digital transformation in the engineering and construction industry. The three main problems are a lack of laws and regulations, a lack of support and leadership, and a lack of resources and professionals.
Researchers discovered that dormant bacterial spores can evaluate their environment without waking up, using stored electrochemical energy to determine favorable conditions. They found that spores release their energy to perform a computation about their surroundings, similar to how neurons operate in the brain.
Researchers at Cold Spring Harbor Laboratory discovered that tufted cells in the olfactory bulb are better at recognizing smells than mitral cells. This finding sheds light on how the brain processes sensory information, including smell intensity and identity.
Rice undergrad Colter Decker creates programmable, air-driven circuits that can perform Boolean functions using compressed air. The system combines digital and analog components, simplifying the overall architecture and achieving new capabilities.
A new neurocomputational model introduces a three-level information processing framework to understand brain development and cognition. The model focuses on Hebbian learning and reinforcement learning, highlighting two fundamental mechanisms for multilevel cognitive ability development in biological neural networks.
Researchers have successfully achieved efficient spin injection and transport in antiferromagnetic hybrids, paving the way for room-temperature spintronics devices. The study, led by Igor Barsukov at UC Riverside, shows promise for ultra-fast and energy-efficient information storage and processing.
A new University of Illinois project aims to improve undergraduate students' ability to estimate their knowledge using artificial intelligence methods. The researchers will utilize machine learning to anticipate student performance and provide personalized feedback to enhance studying strategies.
A team led by Professor Song Min Kim developed a system that can support concurrent communications for tens of millions of IoT devices using backscattering millimeter-level waves. The system offers internet connectivity on a mass scale to IoT devices at a low installation cost.
A study by Max Planck Institute for Human Development found that children use spontaneous strategy changes and broader attentional focus to achieve better results, similar to adults. This broadens the understanding of learning behavior in children.
Researchers at Boston University developed an AI-powered computational model that can detect cognitive impairment from audio recordings of neuropsychological tests. The model was trained on over 1,000 individuals and accurately distinguished between healthy individuals and those with dementia.
A new study takes inspiration from the 'waggle dance' of honeybees to devise a way for robots to communicate effectively in situations with unreliable network communications. Researchers designed a visual communication system using on-board cameras, allowing robots to interpret gestures and convey complex information.
Scientists at the University of Oxford have created a new type of computing processor that uses light to process information, achieving speeds faster than traditional electronics. By leveraging multiple polarisation channels, the researchers increased computing density by several orders of magnitude, paving the way for more efficient p...
A study of HealthCare.gov Marketplace enrollment data from 2015 to 2021 found that 32% of enrollees lacked reported race or ethnicity information. Disproportionately, Black and Hispanic individuals were more likely to have missing data, suggesting the marketplace may serve a more diverse population than indicated by self-reported data.
Researchers at the Sainsbury Wellcome Centre discovered that brain area communication is dynamic and changes over rapid timespans, with influences varying on a fast timescale. This finding suggests that cortical areas may control different aspects of processing in downstream regions over very short time spans.
A new training algorithm for deep spiking neural networks (SNNs) uses biologically plausible spatiotemporal adjustment to improve performance and reduce energy consumption. This approach achieves competitive classification accuracy with only 3% of the energy used by traditional artificial neural networks.
Researchers developed a methodological framework to ensure web data validity in marketing studies. The study provides recommendations for addressing challenges in collecting and using web data via web scraping and APIs.
A study conducted by Kaunas University of Technology researchers analyzed how people with Alzheimer's disease process visual information from faces. The study found that brain signals in patients are significantly noisier, making it harder for them to focus and be attentive.
Researchers found that neurons in the fly's lateral horn play a crucial role in evaluating individual odors and mediating odor-guided behavior. The study identified glutamatergic neurons as key players in this process, which enables flies to recognize good or bad odors.
A new study by Bar-Ilan University researchers reveals that synchronized brain activity is crucial for information transfer between brain regions. Increasing synchronization improves transmission and processing of information, while decreasing it impairs cognitive function. This finding may contribute to the development of treatments f...
A new distributed learning technique, GD-SEC, reduces communication requirements in wireless architecture, improving efficiency and reducing computational cost. The method employs data compression to transmit only meaningful, usable data, enhancing the impact of machine learning while minimizing its limitations.
Snap Inc has endowed a professorship at TU Graz to develop visionary software methods in camera technology and explore new approaches to visual information processing. The professorship will pursue new application ideas for mixed reality, including the fusion of photos with computer-generated content.
The study found that the fragile X protein regulates the opening and closing of the GABA-A receptor in neurons from the brain's memory center, influencing how such neurons process information. This nuanced understanding may hold the key to developing effective therapies for fragile X syndrome.
Xie aims to develop algorithms that reflect human domain knowledge and reasoning patterns, increasing trust in machine learning models. He also explores algorithmic fairness, considering multiple perspectives on what's considered fair, to address concerns about biased decision-making.
Scientists at Rochester and Erlangen develop logic gates that operate at femtosecond timescales, paving the way for ultrafast electronics and information processing. The breakthrough involves harnessing and independently controlling real and virtual charge carriers in gold-graphene-gold junctions with laser pulses.
Researchers have discovered a way to mitigate significant losses in spin current transport by integrating an atom-thin insulator between materials. This innovation has important implications for energy-efficient and ultra-fast storage technologies, as well as applications in terahertz emitters and other spintronic devices.
The study reveals that superconductors can transmit spin currents between magnets, allowing for controlled magnetic interactions and modifying the magnetic response. This breakthrough enables new approaches to information processing using magnetic materials at low temperatures.
Researchers at the University of Missouri are applying AI to analyze protein dynamics, identifying potential target sites for new drug therapies. The approach can simulate protein changes related to conditions like cancer, enhancing the chances of successful therapies.
Researchers at Salk Institute discover that brain parses information through interactions of waves of neural activity, changing how data is processed and affecting attention and focus.
Researchers developed a light-controllable time-domain digital coding metasurface that can manipulate microwave reflection spectra by time-varying light signals. The metasurface platform produces harmonics based on phase modulation, generating symmetrical harmonics and white-noiselike spectra.
A study by Tokyo University of Science researchers used WCNs with increasing n values to find features of language that cannot be analyzed using existing WCNs. They found important features in networks with more than three co-occurrences, independent of text data.
Researchers develop a new method to reconstruct the states of complex nonlinear systems based on time series data. The approach optimizes reconstruction parameters by focusing on the geometric structure of attractors, resulting in improved accuracy.
Neurobiologist Marion Silies is investigating how various visual systems adapt to specific environments and behavioral conditions. She will use fruit flies as an animal model to understand visual processing mechanisms and their adaptation to differing conditions.
A landmark study found that autistic individuals think as quickly and rationally as non-autistic people, challenging the idea that autism is a mental processing disorder. The research suggests that certain fundamental processes are more similar between autistic and non-autistic individuals than previously thought.
Researchers used a contrast pattern mining algorithm on publicly available data from 16,000 participants in the T1D Exchange Clinic Registry. The study found individuals with an immediate family history of Type 1 diabetes were more frequently diagnosed with hypertension and other co-occurring conditions.
Researchers reexamined hundreds of experiments on neural activity and consciousness, finding that experiment parameters determine results. The study used artificial intelligence to predict which theory would be supported by each experiment with 80% success.
Studies investigating the impact of memory on perception aim to understand how our brains alter sensory information, enabling us to conserve energy on expected stimuli. This research may lead to advancements in treating PTSD by analyzing communication between brain regions affected by trauma.
A machine learning model has been developed to predict cognitive performance based on reaction time, eye movement, and difficulty level. The model achieved an accuracy of 82.8% in predicting participant success in visual attention tasks.
A new AI-based app developed by Otto-von-Guericke-Universität Magdeburg allows individuals with pedophilic tendencies to access initial consultations and remote treatment while maintaining anonymity. The technology, called AnonymPrevent, aims to increase acceptance of preventative treatment against child abuse.
A review by Nathan et al. showcases big-data revolution in movement ecology, revealing new insights into animal behavior and habitat use. Reverse-GPS systems, such as ATLAS, track animals with high accuracy, while acoustic telemetry tracks aquatic life, providing crucial data for conservation.
Neurobiologists demonstrated that humans can unconsciously distinguish between even very similar sounds, but often don't recognize these differences. The study used EEG to measure brain responses to stimuli and found that the brain reacts differently to local and global irregularities in sound sequences.
Scientists found smaller, faster waves in the visual cortex that relate to how attentive the brain is. These wave patterns may help understand sleep, anesthesia, and attention by suppressing irrelevant information. The discovery could also improve artificial brains using machine learning techniques.
A new study reveals that the superior colliculus, a lesser-studied region responsible for saccades and facial recognition, dynamically changes its clustering of neurons depending on the mouse's conscious state. This finding suggests that the brain optimizes visual information processing based on its awake or anesthetized state.
A transdisciplinary research team at Göttingen Campus has found a new perspective on the rhythmic processes in the brain. They discovered that adapting interneurons can switch between very slow rhythms and fast rhythms, challenging previous assumptions about their function.
A study by McGill University found that those who experienced more pandemic-related worry had reduced information processing speed and ability to retain information needed for tasks. Pandemic worry also predicted individuals' tendency to distort described risk levels, which may influence decisions about getting a COVID-19 vaccine.
Researchers from the University of Würzburg discovered that monarch butterflies process sun information as a compass during migration, but only when flying actively. The butterfly's brain represents the heading direction relative to the sun in a similar way to a compass.
A new study on mice finds that cognitive training designed to focus on what's important while ignoring distractions can enhance the brain's information processing. The research suggests that this type of training can lead to improved learning and memory, particularly in novel tasks. By analyzing neural activity in the hippocampus durin...
Researchers used sound processing to examine neural synchrony in comatose patients. They found that higher neural synchrony was predictive of a favorable outcome, with indistinguishable levels from healthy controls. The study also revealed surprising neural complexity, with reduced complexity in survivors compared to non-survivors.
Researchers at University of Missouri and University of Chicago develop an artificial material that can respond to its environment, make decisions, and perform actions not directed by humans. The material uses a computer chip to control information processing and convert energy into mechanical energy.
A new grant will help libraries increase information literacy around scientific information by analyzing knowledge brokers' assessment of technical and scientific info. The project aims to develop services that enable consumers to discern reliable sources and process information effectively.
Researchers at NJIT, USC, and Harvard are developing a new software called StreamWare to analyze multiple sources of live data. The team plans to test new combinations of algorithms and hardware accelerators on various data sets, aiming to demonstrate prototypes in 3-6 months.
A new algorithm has been developed to train spiking neural networks, mimicking the human brain's structure and function. This approach enables these powerful, fast, and energy-efficient systems to solve complex tasks like image classification with high precision.
Researchers discovered how neurons in a small area of the brain filter distracting signals to coordinate dexterous movements. The findings may hold lessons for building better prosthetics and robots that can fine-tune their movements based on sensory input.
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.
Researchers discovered a distinct brain signature associated with team flow, characterized by increased beta and gamma waves in the middle temporal cortex. This neural pattern is linked to enhanced information processing and synchronization between teammates during the team flow state.