Articles tagged with Numerical Analysis
A research team at Tohoku University and Islamic Azad University developed a mathematical solution to simulate heat propagation through rods when heated simultaneously. They used a matrix equation to calculate the complementary error function, enabling rapid simulation of heat transfer.
Researchers propose a new analytical approach to determine the limiting velocity of an avalanche crack, revealing that it may propagate at supersonic speeds in certain situations. The findings reconcile conflicting interpretations and provide insights into designing structures impacted by snow masses.
A new study uses machine learning to predict chemical toxicity in rare and endangered species, reducing the need for direct biological testing. The model achieved strong performance predicting acute and chronic toxicity, with life stage being a key factor.
The foundation recognizes five early-career scientists who apply computational methods to cancer research, with a focus on developing new protein designs and understanding chromatin modifications. Their work aims to improve treatment strategies and precision oncology for various cancers.
A scientist from Tokyo Metropolitan University has resolved the thirty-year mystery of dissonance in gravitational waves emitted by a black hole. The phenomenon was caused by resonance between two distinctive modes, which is not a rare incident but turns up universally in a range of modes.
The study investigates how the electrodynamic proximity effect can be used to improve defect detection in Structural Health Monitoring (SHM) applications by optimizing measurement setup arrangement. The analysis reveals that proper arrangement of the setup can enhance defect sensitivity up to 300% compared to non-optimized setups.
Researchers evaluate drones' potential for long-term daily collection of meteorological data, showing promising results and cost-effectiveness. The study demonstrates that drones can provide accurate measurements comparable to traditional methods, improving the accuracy of numerical weather predictions and disaster prevention.
Researchers at Newcastle University developed a novel approach using electromagnetic waves to solve partial differential equations, specifically the Helmholtz wave equation. The innovative structure, known as a metatronic network, effectively behaves like a grid of T-circuits and allows for control over PDE parameters.
A team of researchers at Pusan National University developed a pricing formula for perpetual American strangle options (PASOs) using a stochastic volatility model. The formula is accurate and provides a better understanding of the risks and returns associated with PASOs, especially in low-volatility environments.
A massive ancient galaxy, JWST-ER1g, has been found to have a high dark matter density, puzzling physicists. Researchers offer an explanation that suggests a mechanism compressing the dark matter halo could be responsible for the high density.
Researchers developed a carbon-based tunable metasurface absorber with an ultrawide, tunable bandwidth in the THz range. The absorber boasts high absorption efficiency and insensitivity to polarization angles, paving the way for advanced technological applications.
Researchers have successfully solved a problem in graph theory that has attracted attention from within the field. The team's research involves packing coloring, which deals with labelling parts of a graph to comply with certain rules and avoid specific conflicts.
Researchers developed a multiphase solver to predict beer foam features, including patterns, heights, stability, and volume fractions. The study found that foam generation is sensitive to temperature and pressure, with higher temperatures producing more foam.
A new digital twin of laser-directed energy deposition repair technology has been developed to improve industrial sustainability. The system automatically determines optimum forming conditions, reducing metal powder waste and increasing the effectiveness of the repair process.
Researchers at Rensselaer Polytechnic Institute developed a model to predict cryptocurrency scams using Benford's Law and found that scam addresses deviated from the law. They also advocated for robust blockchain interoperability to provide stability in decentralized systems.
Researchers used natural language processing and machine learning to analyze nearly 35,500 death records, identifying the most common substances involved in overdose deaths. The system reduced data processing time by months, allowing for more rapid public health responses and interventions.
Researchers have discovered a simple way to prevent pharmaceutical fraud using candy-coated pills with unique color patterns. The technique, called CandyCode, uses tiny multicolored candy nonpareils as a uniquely identifiable coating for pharmaceutical capsules and pills.
Researchers studied twisted trilayer graphene, discovering a phase diagram that decouples into product states of graphene and bilayer graphene. The system exhibits unique insulating and semi-metallic phases in the presence of an electric field.
A new KAUST study uses machine learning to predict disease spread with high accuracy, dynamically incorporating latest data without human bias. This approach offers a promising alternative to conventional models, providing a more accurate story of the underlying epidemic data.
A computational analysis of billions of tweets has uncovered high-resolution timelines of the major stories surrounding Trump's presidency from 2016 to 2021. The study found that turbulence in these stories varied over time, with dominant narratives emerging for longer periods during certain periods.
Research at RMIT University uses Getty's top lists of editorial pictures to analyze daily investor sentiment, predicting stock market returns based on global mood. The algorithm produces a daily score from 10 popular photos, providing a quick snapshot of investment mood across developed and emerging economies.
A research team found that the GEA-1 algorithm, used in mobile phones since the 1990s, is easy to break and likely a deliberate weak encryption. The vulnerability no longer poses a significant threat to users, as most data traffic now uses more secure networks.
Scientists used drones and artificial intelligence to analyze over 10,000 images of seabirds in the Falkland Islands, achieving accurate counts with 97% accuracy for albatrosses and 87% for penguins. This technology increases ability to monitor seabird colonies worldwide and track marine ecosystem health.
A new study by Dr Andrea Baronchelli and colleagues reveals a connection between cryptocurrency coding and market behavior. The researchers found that 4% of developers contribute to the code of two or more cryptocurrencies, questioning the transparency surrounding the coding process.
A study by Technical University of Munich found that fans' mood worsens significantly after VAR decisions, with 76.24% of tweets related to the topic being negative. The researchers recommend more transparent communication of VAR decisions to improve audience experience.
Researchers found that a combination of AI and human coaches can effectively train bottom- and top-ranked sales agents, improving performance. The study suggests that tailored designs for targeted agents can overcome challenges faced by different types of sales agents.
Researchers have created an algorithm that significantly reduces the time taken to analyze HeLa cancer cells using Electron Microscopy. The new approach uses deep learning architectures and achieves results in minutes, compared to a week for human experts.
A study by Kansas State University analyzed nearly 2 million congressional speeches and found that politicians use simpler language and express more positive or negative sentiments. The analysis also showed a decrease in reading level and vocabulary over time.
Researchers used machine learning to analyze mouse facial expressions and identified specific facial expressions correlated with emotional descriptors. The study may assist in moving towards a universal definition of emotions across species.
A SUTD research team developed a novel N-shaped electrode design for measuring single cells' lateral positions and biophysical properties in a microdevice. This approach uses differential current to encode particles' trajectories, eliminating expensive imaging setups.
A new mobile heart monitor paired with an automated algorithm and physician review can accurately detect atrial fibrillation, showing 96.6% sensitivity and 94.1% specificity compared to traditional ECGs. However, the device failed to classify some results as normal or possible AF, highlighting its limitations.
A new recommendation algorithm uses cosine similarity to predict customer preferences in high-dimensional spaces, leveraging the angle between user rating lines. The approach balances signal gain with noise introduction, resulting in more accurate predictions and better performance, particularly when ratings data is sparse.
Qiang Du, a leading applied mathematician at Columbia University, has been elected an AAAS Fellow for his distinguished work in applied and computational mathematics. His research focuses on theoretical analysis, numerical simulations, and mathematical modeling of various applications.
Lim's work impacts public through real-world applications, including neural fiber mapping and Human Connectome Project. He received multiple awards for his research on tensors, hypermatrices, and computational geometry/topology.
Researchers have developed a new technique to enhance low-quality brain scans, allowing for the analysis of hundreds of thousands of images. This enables large-scale studies of stroke outcome and other disorders such as Alzheimer's disease.
Researchers at Kumamoto University have derived a new theoretical formula to predict the wetting and spreading behavior of droplets on flat surfaces. The formula allows for quantification of the maximum wetted area of droplets after collision, influencing equipment quality and efficiency.
Nathan Cahill, an RIT associate professor, has been named a Rising Researcher by SPIE for his work in defense and security research. He was recognized for his contributions to remote sensing, machine learning, and cybersecurity.
A numerical study explores the patterns made by 2-D rectangular plates falling freely within water, identifying parameters influencing their motion and force characteristics. The findings may aid in improving wing designs for unmanned aerial vehicles and controlling object motions within fluids.
Researchers at Binghamton University have developed an algorithm using Singular Spectrum Analysis (SSA) to quickly detect and locate power grid faults, providing a promising solution for authorities to remotely identify issues before they cause prolonged outages or equipment damage.
Researchers at University of Notre Dame develop a new algorithm to more accurately represent complex dependencies in data, leading to better predictions for invasive species, shipping networks and infectious diseases. The approach can also be applied to other fields such as social media, telecom companies and urban planning.
Eitan Tadmor, a renowned mathematician, has received the prestigious Peter Henrici Prize for his groundbreaking work on nonlinear partial differential equations. His research has had significant impacts on fields like fluid dynamics, image processing, and social dynamics.
The Karlsruhe Institute of Technology (KIT) has secured funding for two collaborative research centers (CRCs): one focused on wave phenomena in mathematics and the other on enhancing weather forecasting. The CRCs aim to analytically understand, numerically simulate, and manipulate wave propagation under realistic scenarios.
An analysis of statements from 51 recognized civilian heroes found that most describe their acts as intuitive, rather than deliberate. This suggests that high-stakes extreme altruism may be largely driven by automatic, instinctual processes.
Researchers developed an algorithm to reconstruct audio signals from minute object vibrations captured in video. They successfully extracted intelligible speech from a potato-chip bag and useful audio signals from other objects like aluminum foil and leaves.
A new AI algorithm analyzes the Beatles' albums, demonstrating a progressive change in their musical style from one album to the next. The algorithm was also applied to other bands, such as Queen and U2, with notable results.
A new algorithm analyzes void space in sphere packing to study the geometry of liquids and their flow through porous media. The method can also be applied to protein structure analysis, revealing key quantities such as buried cavity sizes and solvent accessibility.
Researchers analyzed 2.5 million articles from 498 English-language outlets, finding that tabloid newspapers are more readable than broadsheets and use more sentimental language. The study also revealed a dominance of male voices in news content, with 'Sport' and 'Financial' articles being the most male-biased.
A new noninvasive test measures DNA changes and fecal blood to detect precancerous lesions, showing high detection rates for cancers and precursors. The test achieved 98% sensitivity for all cancers and 83% for precursors with high-grade dysplasia.
Computer scientists in India have developed a two-pronged algorithm to detect and block botnets. The standalone algorithm uses heuristic approaches to spot suspicious activity, while the network algorithm analyzes network traffic to identify malicious behavior.
Researchers developed an algorithm that accurately identifies potential 'red-light violators' within seconds, reducing false alarms. The algorithm's accuracy surpasses existing safety-prediction technologies, with a 85% success rate in identifying violators.
A new algorithm developed by Tel Aviv University researchers can process massive amounts of digital data instantly, allowing for more efficient tracking and prediction of criminal movements. The algorithm creates probability maps displaying likely locations of suspects, enabling officials to focus resources on high-probability areas
Professor Bjorn Engquist received the Peter Henrici Prize for his fundamental contributions to applied and computational mathematics, with a focus on scientific computing and engineering applications. He also delivered the associated lecture, Fast Algorithms for High Frequency Wave Propagation, at ICIAM 2011.
A study by Pitt researchers reveals that organizing products tailored to customers' knowledge levels can improve consumers' learning and satisfaction. Highly knowledgeable consumers preferred novel product formats, while novice consumers benefited from familiar groupings.
The EPSRC has invested £13 million in three new mathematical sciences Centres for Doctoral Training at Lancaster University, University of Cambridge and University of Warwick. These centres will train at least 40 students over seven years and focus on statistics, analysis and applied mathematics.
Three graduate students, Awad Al-Mohy, Jie Chen, and Shun Zhang, receive the award for their outstanding research papers on matrix exponentials, tensor SVD, and interface problems. The prizes include a monetary award, framed certificate, and publication in SIAM journals.
Franco Brezzi, a prominent figure in computational mathematics, has been awarded the 2009 John von Neumann Lecturer honor by SIAM. His work on numerical stability and stabilization techniques has significantly advanced our ability to simulate complex physical phenomena.
Professor Abdulle is recognized for his outstanding contributions to applied mathematics fields, including stability analysis and mathematical software for stiff initial value problems. He will receive a monetary award and present the 2009 Wilkinson Prize Lecture on July 10.
A new algorithm developed by scientists at University of California, Davis, can extract features and patterns from huge data sets using minimal computing power. The algorithm has been successfully applied to analyze complex phenomena represented by billions of data points.
Fengyan Li, a Rensselaer Polytechnic Institute assistant professor, has been recognized as a 2008 Sloan Research Fellow. Her research focuses on developing computer algorithms for solving problems in sciences and engineering, with applications in various fields such as weather forecasting, pollution control, and image processing.
Gilbert Strang received the Peter Henrici Prize for his work in applied and numerical analysis, including finite element methods, linear algebra, and wavelets. The prize is awarded jointly by ETHZ and SIAM.