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IEEE Texas Power and Energy Conference (TPEC)

作者： Meisam Mahdavi Konrad Schmitt Stephen Bayne Manohar Chamana Department of Electrical Engineering University of Jaén Linares Jaén Spain Electrical and Computer Engineering Department Texas Tech University Lubbock TX USA Renewable Energy Program Texas Tech University Lubbock TX USA

Operational costs are affected by energy losses of distribution systems, in which these losses are higher than those of the transmission system. The placement of distributed generation (DG) units in power distribution networks is an efficient way of energy loss reduction. Today, DG penetration in distribution systems is increasing because of the great effect of renewable energy resources on environmental sustainability. Power demand variations have an essential role in the determination of energy losses amount and optimal generation of DGs. Besides, considering the variability of load level in the DG allocation problem raises the burden and computational time substantially. Therefore, this paper proposes an effective DG allocation strategy for energy loss minimization in the presence of variable power demand. The evaluation of numerical results indicates the desired performance of the presented framework for the optimal placement of DG units in distribution systems with time-varying loads.

关键词： Energy loss Renewable energy sources Power demand Costs Propagation losses Power systems Numerical models

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Hopf Solitons in Helical and Conical Backgrounds of Chiral Magnetic Solids

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Physical Review Letters 2020年第5期125卷 057201-057201页

作者： Robert Voinescu Jung-Shen B. Tai (戴榮身) Ivan I. Smalyukh Department of Physics University of Colorado Boulder Colorado 80309 USA Materials Science and Engineering Program Soft Materials Research Center and Department of Electrical Computer and Energy Engineering University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory and University of Colorado Boulder Colorado 80309 USA

Three-dimensional topological solitons attract a great deal of interest in fields ranging from particle physics to cosmology, but remain experimentally elusive in solid-state magnets. Here we numerically predict magnetic heliknotons, an embodiment of such nonzero-Hopf-index solitons localized in all spatial dimensions while embedded in a helical or conical background of chiral magnets. We describe conditions under which heliknotons emerge as metastable or ground-state localized nonsingular structures with fascinating knots of magnetization field in widely studied materials. We demonstrate magnetic control of three-dimensional spatial positions of such solitons, as well as show how they interact to form moleculelike clusters and possibly even crystalline phases comprising three-dimensional lattices of such solitons with both orientational and positional order. Finally, we discuss both fundamental importance and potential technological utility of magnetic heliknotons.

关键词： Dzyaloshinskii-Moriya interaction Skyrmions Chiral magnets Micromagnetic modeling Topology

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Exploring Personal Knowledge Ecologies: Dealing with Digital Platform Asymmetries

Exploring Personal Knowledge Ecologies: Dealing with Digital...

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International Conference on computer Supported Cooperative Work in Design

作者： Marcos Antonio De Almeida Jano Moreira De Souza António Correia Daniel Schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

The rise of artificial intelligence agents and information technology platforms governed by data-driven algorithms has had profound impacts on the way knowledge work is managed and carried out. Concerning the novel uses of digital work platforms, the arising tensions might suggest that the socio-technical design frameworks adopted by major tech firms are becoming less viable and in some cases ineffective. We propose a conceptual architecture to support a socio-technical framework for exploring Personal Knowledge Ecologies in the context of the digital knowledge economy. This framework aims to increase the degree of individual freedom for the interoperation of these knowledge information infrastructures.

关键词： Knowledge engineering Sociotechnical systems computer architecture Ecology Software Heterogeneous networks Complexity theory

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Performance analysis of the Raft consensus algorithm on Hyperledger Fabric and Ethereum on cloud

Performance analysis of the Raft consensus algorithm on Hype...

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： João H. F. Battisti Vitor E. Batista Guilherme P. Koslovski Maurício A. Pillon Charles C. Miers Marco A. Marques Marcos Simplício Diego Kreutz Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil Laboratory of Computer Networks and Architecture (LARC) Universidade de São Paulo (USP) Brazil Graduate Program in Software Engineering Federal University of Pampa (Unipampa) Brazil

The use of private or consortium blockchains in organizations’ applications is growing. A relevant aspect of blockchains is the choice of consensus mechanism. This decision delimits which blockchain solutions are suitable for the private scenario. Once the consensus mechanism is chosen, more than one blockchain may be enabled. However, this decision making is not trivial and requires detailed experimental indicators about algorithms and blockchains performance. In this context, we provide a comprehensive performance analysis of the Raft consensus mechanism based on its implementation in Hyperledger Fabric and Ethereum blockchain solutions. We performed our experiments on an OpenStack private cloud using each blockchain developer’s default settings for virtual machines. Our findings show how the implementation of each solution can impact the application’s performance under certain conditions.

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Single-Shot Readout of a Solid-State Spin in a Decoherence-Free Subspace

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Physical Review Applied 2021年第3期15卷 L031002-L031002页

作者： D. Farfurnik R. M. Pettit Z. Luo E. Waks Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics and Joint Quantum Institute University of Maryland College Park Maryland 20742 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA

The efficient single-photon-emission capabilities of quantum dot molecules position them as promising platforms for quantum information processing. Furthermore, quantum dot molecules feature a “decoherence-free” subspace that enables spin qubits with long coherence times. To efficiently read out the spin state within this subspace requires the optical cycling of isolated transitions that originate from a triplet manifold within the quantum dot molecule. We propose and theoretically study a two-stage spin-readout protocol within this decoherence-free subspace that allows single-shot readout performance. The process incorporates a microwave π pulse and optical cycling of the isolated transitions, which induces fluorescence that allows us to identify the initial spin state. This protocol offers enhanced readout fidelity compared to previous schemes that rely on the excitation of transitions that strongly decay to multiple ground states or require long initialization via slow optically forbidden transitions. By simulating the performance of the protocol, we show that an optimal spin-readout fidelity of over 97% and single-shot readout performance are achievable for a photon-collection efficiency of just 0.12%. This high readout performance for such realistic photon-collection conditions within the decoherence-free subspace expands the potential of quantum dot molecules as building blocks for quantum networks.

关键词： Optoelectronics Quantum information with solid state qubits Quantum networks Single photon sources Double quantum dots Coherent control Microwave techniques Quantum master equation

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Steerable ePCA: Rotationally Invariant Exponential Family PCA

arXiv

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arXiv 2018年

作者： Zhao, Zhizhen Liu, Lydia T. Singer, Amit Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61820 United States Department of Electrical Engineering and Computer Sciences University of California at Berkeley BerkeleyCA94720 United States Department of Mathematics Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

—In photon-limited imaging, the pixel intensities are affected by photon count noise. Many applications, such as 3-D reconstruction using correlation analysis in X-ray free electron laser (XFEL) single molecule imaging, require an accurate estimation of the covariance of the underlying 2-D clean images. Accurate estimation of the covariance from low-photon count images must take into account that pixel intensities are Poisson distributed, hence the classical sample covariance estimator is sub-optimal. Moreover, in single molecule imaging, including in-plane rotated copies of all images could further improve the accuracy of covariance estimation. In this paper we introduce an efficient and accurate algorithm for covariance matrix estimation of count noise 2-D images, including their uniform planar rotations and possibly reflections. Our procedure, steerable ePCA, combines in a novel way two recently introduced innovations. The first is a methodology for principal component analysis (PCA) for Poisson distributions, and more generally, exponential family distributions, called ePCA. The second is steerable PCA, a fast and accurate procedure for including all planar rotations for PCA. The resulting principal components are invariant to the rotation and reflection of the input images. We demonstrate the efficiency and accuracy of steerable ePCA in numerical experiments involving simulated XFEL datasets and rotated Yale B face data. Copyright © 2018, The Authors. All rights reserved.

关键词： Principal component analysis

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Emotional ant based modeling of crowd dynamics

Emotional ant based modeling of crowd dynamics

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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： Soumya Banarjee C. Grosan A. Abraham Department of Computer Science Faculty of Mathematics and Computer Science Babes Bolyai University Cluj-Napoca Romania Department of Computer Applications Institute of Management Studies Dhradun India School of Computer Science and Engineering Chung-Ang University Seoul South Korea Department of Computer Science Babes-Bolyai University Cluj-Napoca Romania IITA Professorship Program Chung-Ang University Seoul Korea

It is known that one of the most disastrous forms of collective human behavior is the kind of crowd stampede induced by panic. This situation often leads to fatalities as people are crushed or trampled. This problem has been well researched from a socio-psychological point of view. In this paper we attempt to study and analyze the crowd behavior by using an ant colony optimization (ACO) based computational framework. The initial simulations refer to a panic situation generated in a few connected cities of a war affected country.

关键词： Biological system modeling computer science Humans Psychology computer applications engineering management Mathematics Ant colony optimization Military computing Computational modeling

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Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation

arXiv

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arXiv 2024年

作者： Islam, Md. Farhadul Zabeen, Sarah Manab, Meem Arafat Mahin, Mohammad Rakibul Hasan Mondal, Joyanta Jyoti Reza, Md. Tanzim Hasan, Md Zahidul Haque, Munima Sadeque, Farig Noor, Jannatun Research Group Department of Computer Science and Engineering School of Data and Sciences BRAC University Dhaka Bangladesh Department of Computer Science and Engineering School of Data and Sciences BRAC University Dhaka Bangladesh Biotechnology Program Department of Mathematics and Natural Sciences School of Data and Sciences BRAC University Dhaka Bangladesh Department of Computer and Information Sciences University of Delaware United States School of Law and Government Dublin City University Ireland Gina Cody School of Engineering and Computer Science Concordia University Canada

The majority of medical images, especially those that resemble cells, have similar characteristics. These images, which occur in a variety of shapes, often show abnormalities in the organ or cell region. The convolution operation possesses a restricted capability to extract visual patterns across several spatial regions of an image. The involution process, which is the inverse operation of convolution, complements this inherent lack of spatial information extraction present in convolutions. In this study, we investigate how applying a single layer of involution prior to a convolutional neural network (CNN) architecture can significantly improve classification and segmentation performance, with a comparatively negligible amount of weight parameters. The study additionally shows how excessive use of involution layers might result in inaccurate predictions in a particular type of medical image. According to our findings from experiments, the strategy of adding only a single involution layer before a CNN-based model outperforms most of the previous *** Codes 68T45 © 2024, CC BY-NC-SA.

关键词： Convolutional neural networks

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Total variation superiorized conjugate gradient method for image reconstruction

arXiv

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arXiv 2017年

作者： Zibetti, Marcelo V. W. Lin, Chuan Herman, Gabor T. Graduate Program in Electrical Engineering and Computer Science Federal University of Technology - Paraná Curitiba80230-901 Brazil School of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan610031 China Department of Computer Science Graduate Center City University of New York New YorkNY10016 United States

The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise;due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Nonlinear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG);one of its input parameters is a positive number ". It is proved that, for any given " that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ". Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value " of the half-squared residual. Copyright © 2017, The Authors. All rights reserved.

关键词： Conjugate gradient method

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The Use of Large Language Models and Their Association With Enhanced Impact in Biomedical Research and Beyond

MedComm - Future Medicine

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MedComm - Future Medicine 2025年第2期4卷

作者： Cheng, Huzi Shi, Wen Sheng, Bin Lee, Aaron Y. Car, Josip Chaudhary, Varun Atanasov, Atanas G. Liu, Nan Qiu, Yue Chen, Qingyu Wong, Tien Yin Tham, Yih-Chung Zheng, Ying-Feng Department of Psychological and Brain Sciences Indiana University Bloomington IN United States Department of Ophthalmology the First Affiliated Hospital of Guangzhou Medical University Guangzhou China Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology University of Washington School of Medicine Seattle WA United States Centre for Population Health Sciences Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore Department of Primary Care and Public Health School of Public Health Imperial College London London United Kingdom Department Health Research Methods Evidence and Impact McMaster University Hamilton ON Canada Department of Surgery McMaster University Hamilton ON Canada Ludwig Boltzmann Institute Digital Health and Patient Safety Medical University of Vienna Vienna Austria Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences Jastrzebiec Poland Centre for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Tsinghua Medicine Tsinghua University Beijing China Yale School of Medicine Yale University United States Singapore Eye Research Institute Singapore National Eye Centre Singapore School of Clinical Medicine Beijing Tsinghua Changgung Hospital Beijing China Ophthalmology and Visual Sciences Academic Clinical Program Duke-NUS Medical School Singapore Centre for Innovation and Precision Eye Health and Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China

The release of ChatGPT in 2022 has catalyzed the adoption of large language models (LLMs) across diverse writing domains, including academic writing. However, this technological shift has raised critical questions regarding the prevalence of LLM usage in academic writing and its potential influence on the quality and impact of research articles. Here, we address these questions by analyzing preprint articles from arXiv, bioRxiv, and medRxiv between 2022 and 2024, employing a novel LLM usage detection tool. Our study reveals that LLMs have been widely adopted in biomedical and other types of academic writing since late 2022. Notably, we noticed that LLM usage is linked to an enhanced impact of research articles after examining their correlation, as measured by citation numbers. Furthermore, we observe that LLMs influence specific content types in academic writing, including hypothesis formulation, conclusion summarization, description of phenomena, and suggestions for future work. Collectively, our findings underscore the potential benefits of LLMs in scientific communication, suggesting that they may not only streamline the writing process but also enhance the dissemination and impact of research findings across disciplines. © 2025 The Author(s). MedComm - Future Medicine published by John Wiley & Sons Australia, Ltd on behalf of Sichuan International Medical Exchange & Promotion Association (SCIMEA).

关键词： academic writing chatGPT large language models LLM

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