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arXiv 2023年

作者： Adorjáni, B. Libál, A. Reichhardt, C. Reichhardt, C.J.O. Mathematics and Computer Science Department Babeş-Bolyai University Cluj400084 Romania Theoretical Division Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States

We introduce a system of active matter swarmalators composed of elastically interacting run- and-tumble active disks with an internal phase i. The disks experience an additional attractive or repulsive force with neighboring disks depending upon their relative difference in i. In the absence of the internal phase, the system forms a Motility-Induced Phase Separated (MIPS) state, but when the swarmalator interactions are present, a wide variety of other active phases appear depending upon whether the interaction is attractive or repulsive and whether the particles act to synchronize or anti-synchronize their internal phase values. These include a gas-free gel regime, arrested clusters, a labyrinthine state, a regular MIPS state, a frustrated MIPS state for attractive anti-synchronization, and a superlattice MIPS state for attractive synchronization. Copyright © 2023, The Authors. All rights reserved.

关键词： Phase separation

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Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations

arXiv

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arXiv 2024年

作者： Hu, Zheyuan Zhang, Zhongqiang Em Karniadakis, George Kawaguchi, Kenji Department of Computer Science National University of Singapore Singapore119077 Singapore Department of Mathematical Sciences Worcester Polytechnic Institute WorcesterMA01609 United States Division of Applied Mathematics Brown University USA ProvidenceRI02912 United States Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory RichlandWA United States

The Fokker-Planck (FP) equation is a foundational partial differential equation (PDE) in stochastic processes involving Brownian motions. However, the curse of dimensionality (CoD) poses a formidable challenge when dealing with high-dimensional FP equations. Although Monte Carlo simulation and (vanilla) Physics-Informed Neural Networks (PINNs) have shown the potential to tackle CoD, both methods exhibit significant numerical errors in high dimensions when dealing with the probability density function (PDF) associated with Brownian motion. The point-wise PDF values tend to decrease exponentially as dimensionality increases, surpassing the precision of numerical simulations and resulting in substantial errors. Moreover, due to its massive sampling, Monte Carlo fails to offer fast sampling. Modeling the logarithm likelihood (LL) via vanilla PINNs transforms the FP equation into a notoriously difficult Hamilton-Jacobi-Bellman (HJB) equation, which is impractical for PINN learning, whose error grows rapidly with dimension. To this end, we propose a novel approach utilizing a score-based solver to fit the score function in stochastic differential equations (SDEs). The score function, defined as the gradient of the LL, plays a fundamental role in inferring LL and PDF and enables fast SDE sampling, offering an effective means to overcome the CoD. Three fitting methods, Score Matching (SM), Sliced Score Matching (SSM), and Score-PINN, are introduced, each contributing unique advantages in computational complexity, accuracy, and generality. The proposed score-based SDE solver operates in two stages: first, employing score matching or Score-PINN to acquire the score function;and second, solving the LL via an ordinary differential equation (ODE) using the obtained score function. Comparative evaluations across these methods showcase varying trade-offs. The proposed methodology is evaluated across diverse SDEs, including anisotropic Ornstein-Uhlenbeck processes, geometric Browni

关键词： Fokker Planck equation

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Numerical Investigation of the Fractional Oscillation Equations under the Context of Variable Order Caputo Fractional Derivative via Fractional Order Bernstein Wavelets

arXiv

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arXiv 2023年

作者： Rayal, Ashish Joshi, Bhagawati Prasad Pandey, Mukesh Torres, Delfim F.M. Department of Mathematics School of Applied and Life Sciences Uttaranchal University Dehradun248007 India Department of Mathematics Graphic Era Hill University Bhimtal263136 India School of Computer Science University of Petroleum & Energy Studies Dehradun248007 India Department of Mathematics University of Aveiro Aveiro3810-193 Portugal

This article describes an approximation technique based on fractional order Bernstein wavelets for the numerical simulations of fractional oscillation equations under variable order, and the fractional order Bernstein wavelets are derived by means of fractional Bernstein polynomials. The oscillation equation describes electrical circuits and exhibits a wide range of nonlinear dynamical behaviors. The proposed variable order model is of current interest in a lot of application areas in engineering and applied sciences. The purpose of this study is to analyze the behavior of the fractional force-free and forced oscillation equations under the variable-order fractional operator. The basic idea behind using the approximation technique is that it converts the proposed model into non-linear algebraic equations with the help of collocation nodes for easy computation. Different cases of the proposed model are examined under the selected variable order parameters for the first time in order to show the precision and performance of the mentioned scheme. The dynamic behavior and results are presented via tables and graphs to ensure the validity of the mentioned scheme. Further, the behavior of the obtained solutions for the variable order is also depicted. From the calculated results, it is observed that the mentioned scheme is extremely simple and efficient for examining the behavior of nonlinear random (constant or variable) order fractional models occurring in engineering and *** Codes 65T60, 26A33, 34K28, 65Z05 © 2023, CC BY.

关键词： Linear algebra

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An enzyme-free interdigitated electrode for ketamine detection

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Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A 2023年第5期46卷 441-452页

作者： Phan, Thien Luan Van Hieu, Nguyen Lin, Jing-Jenn Wu, Hsing-Ju Chu, Pei-Yi Hsiao, Chin-Sung Yao, Fiona Yan-Dong Lin, Yung-Kai Ching, Congo Tak Shing Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung Taiwan Viet Nam Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Taiwan Research Assistant Center Show Chwan Memorial Hospital Taiwan Department of Medical Research Chang Bing Show Chwan Memorial Hospital Taiwan Department of Pathology Show Chwan Memorial Hospital Taiwan School of Medicine College of Medicine Fu Jen Catholic University Taiwan Computer Science and Information Engineering Asia University Taiwan Division of Science Engineering and Health Studies College of Professional and Continuing Education The Hong Kong Polytechnic University Hong Kong Department of Food Science National Taiwan Ocean University Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan

Ketamine is an anesthetic, which when used wrongly would affect judgment and behavior, increasing risks to individual such as unwanted or risky sexual behavior. This study reports the development of an admittance- and capacitance-spectroscopy-based sensor to detect ketamine in solution, such as whiskey, a popular alcoholic drink. The result confirms the proposed method is capable of detecting the presence of ketamine in whiskey, in concentration as low as 6.25 ng/μL, by using admittance and capacitance measured at 6.75 MHz, as well as quantifying the measured admittance (sensitivity: 300 μΩ−1/Log (ng/μL);limit of detection (LOD): 0.16 ng/μL) or capacitance data (sensitivity: 2 nF/Log (ng/μL);LOD: 0.73 ng/μL) at 18 kHz and 7.69 MHz, respectively. © 2023 The Chinese Institute of Engineers.

关键词： Capacitance

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RETRACTED ARTICLE: A Systematic Survey on Implementation of Fuzzy Regression Models for Real Life Applications (Archives of Computational Methods in Engineering, (2024), 31, 1, (291-311), 10.1007/s11831-023-09978-x)

引用

Archives of Computational Methods in Engineering 2025年

作者： Khan, Mufala Kumar, Rakesh Aledaily, Arwa N. Kariri, Elham Viriyasitavat, Wattana Yadav, Kusum Dhiman, Gaurav Kaur, Amandeep Sharma, Ashutosh Vimal, S. Department of Mathematics Lovely Professional University Punjab Phagwara144411 India Department of Computer Science Government Bikram College of Commerce Punjab Patiala147001 India College of Computer Science and Engineering University of Ha’il Hail Saudi Arabia College of Computer Science and Engineering Prince Sattam Bin Abdulaziz University Al‑Kharj Saudi Arabia Business Information Technology Division Department of Statistics Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon University Centre for Research and Development Department of Computer Science and Engineering Chandigarh University Mohali Gharuan140413 India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun248002 India Division of Research and Development Lovely Professional University Phagwara India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Artificial Intelligence and Data Science Ramco Institute of Technology Tamil Nadu Rajaplayam India

The Editors-in-Chief have retracted this article. After publication, concerns were raised about the originality of the study reported. An investigation conducted by the Publisher confirmed that the article contains material that substantially overlaps with a previous study by different authors [1]. In particular, the research methodology, research questions, numerous formulations, and discussion are almost identical with those in [1]. The Editors-in-Chief therefore consider this article redundant. None of the authors have responded to correspondence from the Publisher about this retraction. © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2025.

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Seeking optimal Human/Machine collaborative practice in antisemitic terminology detection

Seeking optimal Human/Machine collaborative practice in anti...

引用

Digital Platforms and Societal Harms (DPSH), IEEE

作者： Wendy Melillo Jessica Emami Solene Guarinos Dhanush Kikkisetti Melanie Klein Lisa Liubovich Raza Ul Mustafa Nathalie Japkowicz Journalism Division School of Communication American University Department of Sociology College of Arts and Science American University Department of Mathematics College of Arts and Science American University Justice Law and Criminology School of Public Affairs American University Data Science for Applied Public Affairs School of Public Affairs American University Department of Computer Science College of Arts and Science American University

ISBN: (数字)9798350351309

ISBN: (纸本)9798350351316

This study is concerned with the use of antisemitic language on loosely moderated extremist alt-right social media. It compares, contrasts, and combines human- and machinebased approaches for discovering antisemitic coded or noncoded terminology in such media. Coded terminology refers to the language used in closed-knit communities to communicate beliefs and attitudes without expressing them explicitly. In noncoded discourse, the views of the writer are expressed more explicitly. The detection and analysis of antisemitic terminology in social media is an important problem that can help uncover and monitor the evolution of societal attitudes towards the Jews, and eventually, towards other minority groups once we expand our study. Given the growing prevalence of antisemitic rhetoric in online public spaces, there is a greater need for academic studies to determine its presence and identify strategies to curb its influence. Scholars have noted how intolerant expressions can threaten democratic values. Antisemitic content, like other forms of hate speech, has the potential to radicalize people who may commit violence based on their prejudicial viewpoints. The purpose of this paper is to discuss three different approaches for discovering antisemitic terminology on social media. In particular, it describes an experiment in which three groups—human, software, and mixed—"competed” on the task of retrieving antisemitic terminology over a two-month period (January-February, 2024). The results were manually evaluated for relevance and frequency of occurrence in the next month period (March 2024). The study shows that each group discovered valuable terminology and that neither the human nor the machine group could replace the other. Instead, we advocate that both groups work together using their respective knowledge to optimize the discovery of new terminology on social media.

关键词： Terminology Social networking (online) Hate speech Collaboration Media Software Rhetoric Monitoring

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Pattern formation and flocking for particles near the jamming transition on resource gradient substrates

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Physical Review E 2022年第6期106卷 064602-064602页

作者： L. Varga A. Libál C. Reichhardt C. J. O. Reichhardt Mathematics and Computer Science Department Babeş-Bolyai University Cluj-Napoca 400084 Romania Theoretical Division and Center for Nonlinear Studies Los Alamos National Laboratory Los Alamos New Mexico 87545 USA

We numerically examine a bidisperse system of active and passive particles coupled to a resource substrate. The active particles deplete the resource at a fixed rate and move toward regions with higher resources, while all of the particles interact sterically with each other. We show that at high densities, this system exhibits a rich variety of pattern-forming phases along with directed motion or flocking as a function of the relative rates of resource absorption and consumption as well as the active to passive particle ratio. These include partial phase separation into rivers of active particles flowing through passive clusters, strongly phase separated states where the active particles induce crystallization of the passive particles, mixed jammed states, and fluctuating mixed fluid phases. For higher resource recovery rates, we demonstrate that the active particles can undergo motility-induced phase separation, while at high densities, there can be a coherent flock containing only active particles or a solid mixture of active and passive particles. The directed flocking motion typically shows a transient in which the flow switches among different directions before settling into one direction, and there is a critical density below which flocking does not occur. We map out the different phases as function of system density, resource absorption and recovery rates, and the ratio of active to passive particles.

关键词： Emergence of patterns Foraging Active matter

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Ad Hoc File Systems for High-Performance Computing

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Journal of computer science & Technology 2020年第1期35卷 4-26页

作者： AndréBrinkmann Kathryn Mohror Weikuan Yu Philip Carns Toni Cortes Scott A.Klasky Alberto Miranda Franz-Josef Pfreundt Robert B.Ross Marc-AndréVef Zentrum für Datenverarbeitung Johannes Gutenberg University MainzMainz 55128Germany Center for Applied Scientific Computing Lawrence Livermore National LaboratoryLivermoreCA 94550U.S.A Department of Computer Science Florida State UniversityTallahasseeFL 32306U.S.A Mathematics and Computer Science Division Argonne National LaboratoryLemontIL 60439U.S.A Department of Computer Architecture Universitat Politecnica de CatalunyaBarcelona 08034Spain Computer Science and Mathematics Division Oak Ridge National LaboratoryOak RidgeTN 37831U.S.A Computer Science Department Barcelona Supercomputing CenterBarcelona 08034Spain Fraunhofer Institute for Industrial Mathematics ITWM Fraunhofer-Platz 1Kaiserslautern 67663Germany

Storage backends of parallel compute clusters are still based mostly on magnetic disks,while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory(NVRAM)are deployed within compute *** these new storage technologies into scientific workflows is unfortunately today a mostly manual task,and most scientists therefore do not take advantage of the faster storage *** approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes,which serve as temporary storage systems for single applications or longer-running *** paper presents results from the Dagstuhl Seminar 17202"Challenges and Opportunities of User-Level File Systems for HPC"and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage *** discussion includes open research questions,such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file *** presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device *** interfaces and semantics are presented,for example those used by the three ad hoc file systems BeeOND,GekkoFS,and *** presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

关键词： parallel architectures distributed file system high-performance computing burst buffer POSIX(portable operating system interface)

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COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

引用

computers, Materials & Continua 2021年第7期68卷 391-407页

作者： Aqib Ali Wali Khan Mashwani Samreen Naeem Muhammad Irfan Uddin Wiyada Kumam Poom Kumam Hussam Alrabaiah Farrukh Jamal Christophe Chesneau Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Program in Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiThanyaburi12110Thailand Departments of Mathematics Faculty of ScienceCenter of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research LaboratoryRoom SCL 802 Fixed Point LaboratoryScience Laboratory BuildingKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand Department of Medical Research China Medical University HospitalTaichung40402Taiwan College of Engineering Al Ain UniversityAl Ain64141United Arab Emirates Department of Mathematics Tafila Technical UniversityTafila66110Jordan Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan 11Department of MathematicsUniversitéde CaenLMNOCaen14032France

The purpose of this research is the segmentation of lungs computed tomography(CT)scan for the diagnosis of COVID-19 by using machine learning *** dataset contains data from patients who are prone to the *** contains three types of lungs CT images(Normal,Pneumonia,and COVID-19)collected from two different sources;the first one is the Radiology department of Nishtar Hospital Multan and Civil Hospital Bahawalpur,Pakistan,and the second one is a publicly free available medical imaging database known as *** the preprocessing,a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest(ROIs)and acquire 52 hybrid statistical features for each ***,12 optimized statistical features are selected via the chi-square feature reduction *** the classification,five machine learning classifiers named as deep learning J4,multilayer perceptron,support vector machine,random forest,and naive Bayes are deployed to optimize the hybrid statistical features *** is observed that the deep learning J4 has promising results(sensitivity and specificity:0.987;accuracy:98.67%)among all the deployed *** a complementary study,a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

关键词： COVID-19 machine learning fuzzy c-mean deep learning J4

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Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology

arXiv

引用

arXiv 2022年

作者： Hu, Zheyuan Jagtap, Ameya D. Karniadakis, George Em Kawaguchi, Kenji Department of Computer Science National University of Singapore Singapore119077 Singapore Division of Applied Mathematics Brown University ProvidenceRI02912 United States

In this paper, we propose the augmented physics-informed neural network (APINN), which adopts soft and trainable domain decomposition and flexible parameter sharing to further improve the extended PINN (XPINN) as well as the vanilla PINN methods. In particular, a trainable gate network is employed to mimic the hard decomposition of XPINN, which can be flexibly fine-tuned for discovering a potentially better partition. It weight-averages several sub-nets as the output of APINN. APINN does not require complex interface conditions, and its sub-nets can take advantage of all training samples rather than just part of the training data in their subdomains. Lastly, each sub-net shares part of the common parameters to capture the similar components in each decomposed function. Furthermore, following the PINN generalization theory in Hu et al. [2021], we show that APINN can improve generalization by proper gate network initialization and general domain & function decomposition. Extensive experiments on different types of PDEs demonstrate how APINN improves the PINN and XPINN methods. Specifically, we present examples where XPINN performs similarly to or worse than PINN, so that APINN can significantly improve both. We also show cases where XPINN is already better than PINN, so APINN can still slightly improve XPINN. Furthermore, we visualize the optimized gating networks and their optimization trajectories, and connect them with their performance, which helps discover the possibly optimal decomposition. Interestingly, if initialized by different decomposition, the performances of corresponding APINNs can differ drastically. This, in turn, shows the potential to design an optimal domain decomposition for the differential equation problem under consideration. © 2022, CC BY.

关键词： Domain decomposition methods

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