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Towards end-to-end structure determination from x-ray diffraction data using deep learning

npj Computational Materials 2024年第1期10卷 1048-1059页

作者： Gabe Guo Judah Goldfeder Ling Lan Aniv Ray Albert Hanming Yang Boyuan Chen Simon J.L.Billinge Hod Lipson Department of Computer Science Columbia UniversityNew YorkNY10027USA Department of Applied Physics and Applied Mathematics Columbia UniversityNew YorkNY10027USA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC27708USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA

Powder crystallography is the experimental science of determining the structure of molecules provided in crystalline-powder form,by analyzing their x-ray diffraction(XRD)*** many materials are readily available as crystalline powder,powder crystallography is of growing usefulness to many ***,powder crystallography does not have an analytically known solution,and therefore the structural inference typically involves a laborious process of iterative design,structural refinement,and domain knowledge of skilled experts.A key obstacle to fully automating the inference process computationally has been formulating the problem in an end-to-end quantitative form that is suitable for machine learning,while capturing the ambiguities around molecule orientation,symmetries,and reconstruction *** we present an ML approach for structure determination from powder diffraction *** works by estimating the electron density in a unit cell using a variational coordinate-based deep neural *** demonstrate the approach on computed powder x-ray diffraction(PXRD),along with partial chemical composition information,as *** evaluated on theoretically simulated data for the cubic and trigonal crystal systems,the system achieves up to 93.4%average similarity(as measured by structural similarity index)with the ground truth on unseen materials,both with known and partially-known chemical composition information,showing great promise for successful structure solution even from degraded and incomplete input *** approach does not presuppose a crystalline structure and the approach are readily extended to other situations such as nanomaterials and textured samples,paving the way to reconstruction of yet unresolved nanostructures.

关键词： structure powder crystalline

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Geyser Inspired Algorithm:A New Geological-inspired Meta-heuristic for Real-parameter and Constrained engineering Optimization

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Journal of Bionic engineering 2024年第1期21卷 374-408页

作者： Mojtaba Ghasemi Mohsen Zare Amir Zahedi Mohammad-Amin Akbari Seyedali Mirjalili Laith Abualigah Department of Electronics and Electrical Engineering Shiraz University of TechnologyShirazIran Department of Electrical Engineering Faculty of EngineeringJahrom UniversityJahromFrasIran Department of Electrical and Computer Engineering Tarbiat Modares UniversityTehranIran Department of Electrical and Computer Engineering University ofCyprusNicosiaCyprus Centre for Artificial Intelligence Research and Optimisation Torrens University AustraliaBrisbaneQLD 4006Australia University Research and Innovation Center Obuda University1034 BudapestHungary Department of Electrical and Computer Engineering Lebanese American UniversityByblos 13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied Science Research Center Applied Science Private UniversityAmman 11931Jordan

Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world *** study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization *** efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark ***,GEA has been applied to several real-parameter engineering optimization problems to evaluate its *** addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization *** results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and *** that the source code of the GEA is publicly available at https://***/projects/gea.

关键词： Nature-inspired algorithms Real-world and engineering optimization Mathematical modeling Geyser algorithm(GEA)

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computer Python Network Security Monitoring System Based on Intelligent Algorithms 4

Computer Python Network Security Monitoring System Based on ...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Na, Ren Xiang, Rui Ordos Institute of Applied Technology Department of Mathematics and Computer Engineering Kangbashi Ordos China

ISBN: (纸本)9798350352931

In response to the increasingly complex and diverse network security threats, a network security monitoring system is introduced that combines intelligent algorithms and Python software to achieve efficient and accurate real-time security monitoring and protection. Firstly, the system collects network traffic and log data through libraries such as Scapy and Pyshark, and performs preprocessing. Then, using Python's machine learning library Scikit learn, features are extracted, including traffic patterns, protocol types, source IP (Internet Protocol) addresses, etc., to construct a classification model. Next, based on the characteristics of network attacks, the random forest algorithm in supervised learning is selected to train the annotated attack samples. The false alarm rate of the system is 3.1%, indicating that when detecting the spread of malicious software, the system occasionally misjudges normal file transfers as malicious behavior. The system has significantly improved the efficiency and accuracy of network security monitoring through the application of intelligent algorithms, and has broad application prospects. © 2024 IEEE.

关键词： Random forests

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Lyapunov-guided representation of recurrent neural network performance

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Neural Computing and Applications 2024年第34期36卷 21211-21226页

作者： Vogt, Ryan Zheng, Yang Shlizerman, Eli Department of Applied Mathematics University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States

Recurrent neural networks (RNN) are ubiquitous computing systems for sequences and multivariate time-series data. While several robust RNN architectures are known, it is unclear how to relate RNN initialization, architecture, and other hyperparameters with accuracy for a given task. In this work, we propose treating RNN as dynamical systems and correlating hyperparameters with accuracy through Lyapunov spectral analysis, a methodology designed explicitly for nonlinear dynamical systems. To address the fact that RNN features go beyond the existing Lyapunov spectral analysis, we propose to infer relevant features from the Lyapunov spectrum with an Autoencoder and an embedding of its Latent representation (AeLLE). Our studies of various RNN architectures show that AeLLE successfully correlates RNN Lyapunov spectrum with accuracy. Furthermore, the Latent representation learned by AeLLE is generalizable to novel inputs from the same task and is formed early in the process of RNN training. The latter property allows for predicting the accuracy to which RNN would converge when training is complete. We conclude that the representation of RNN through the Lyapunov spectrum, along with AeLLE, provides a novel method for the organization and interpretation of variants of RNN architectures. © The Author(s) 2024. corrected publication 2024.

关键词： Recurrent neural networks

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Estimating Risk-aware Flexibility Areas for Electric Vehicle Charging Pools via AC Stochastic Optimal Power Flow

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1247-1256页

作者： Juan S.Giraldo Nataly Bañol Arias Pedro P.Vergara Maria Vlasiou Gerwin Hoogsteen Johann L.Hurink Energy Transition Studies Group Netherlands Organisation for Applied Scientific Research(TNO)Amsterdam1043 NTThe Netherlands Department of Electrical Engineering Mathematics and Computer ScienceUniversity of TwenteEnschede7522 NBThe Netherlands Intelligent Electrical Power Grids Group Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft2628 CDThe Netherlands

This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.

关键词： Electric vehicle flexibility management stochastic optimal power flow(SOPF) risk awareness compensation mechanism

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HoloStream: a GPU-powered high-speed user interface for holographic microscopy imaging

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Optics Express 2025年第7期33卷 15648-15660页

作者： Morales, Johan Obando-Vásquez, Sofia Doblas, Ana Trujillo, Carlos Applied Optics Group School of Applied Science and Engineering EAFIT University Medellin Colombia Optical Imaging Research Lab Electrical and Computer Engineering Department University of Massachusetts Dartmouth DartmouthMA United States

This paper presents HoloStream, a GPU-powered high-speed user interface designed for holographic microscopy imaging. The platform reconstructs quantitative phase images rapidly for off-axis digital holographic microscopy (DHM) systems operating in the telecentric regime. By optimizing critical computational procedures, the HoloStream app reconstructs phase maps of 1280 × 960 pixels up to 11 frames per second (FPS) in live visualization and 90 fps for pre-recorded holographic videos. This real-time phase compensation is performed by upgrading the semi-heuristic phase compensation (SHPC) algorithm through GPU acceleration via PyCUDA. The interface also offers a user-friendly experience with flexible control over acquisition modes, visualization formats, and 3D tracking functionalities. Experimental validation demonstrates the platform’s capability to achieve fast and accurate phase imaging for live microscopy applications. The HoloStream app advances DHM technology by combining high-speed processing with ease of use, making it suitable for a wide range of DHM imaging applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： computer graphics equipment

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Problems in Video Conferencing-Mediated Teaching: Experiences of Three User Roles of a University in Bangladesh

Problems in Video Conferencing-Mediated Teaching: Experience...

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2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Mansoor, Nafees Rozario, Anatte Kibria, Muhammad Golam Khalid, Md Saifuddin University of Liberal Arts Department of Computer Science and Engineering Bangladesh Department of Applied Mathematics and Computer Science Kongens Lyngby Denmark

ISBN: (纸本)9798350350289

Video-conferencing systems (VCS) became a defacto tool for online and hybrid teaching during COVID-19 and the gradual return to physical classrooms. As part of the EdViCon Erasmus+ project, towards defining the scenarios for improving teaching with additional portable tools by university teachers, this study reports users' problems in the context of the University of Liberal Arts Bangladesh (ULAB). Classroom observations, problem-tree analysis, interviews, and focus-group discussions with academics, e-learning and IT consultants, and students provide different perspectives on the central problems, underlying causes, and the effects of VCS use during live teaching sessions. While teachers emphasized the lack of resources and technical barriers, students' problem statement focused on the reduced quality of interactions due to the differences between VCS-mediated and physical classrooms, and the IT & e-learning professionals emphasized technological issues (audio, tone, lack of facial expression etc.), lack of collaboration, and differences in expectations among participants. The central contribution of this paper is three diagrams showing problem tree analysis from the perspectives of the three roles. Each of the causes, effects, and problem statements will be considered as point-of-view statements for generating ideas for supporting hardware and software tools and training on technology and pedagogy, © 2024 IEEE.

关键词： Students

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Application of computer Vision Technology in User Interface Design 3rd

Application of Computer Vision Technology in User Interface ...

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3rd World Conference on Intelligent and 3D Technologies, WCI3DT 2024

作者： Su, Jianna Department of Mathematics and Computer Engineering Ordos Institute of Applied Technology Inner Mongolia Erdos017010 China

ISBN: (纸本)9789819791231

This article explores the application of computer vision technology in user interface design, particularly through gesture recognition to enhance human–computer interaction. Gestures offer natural and versatile advantages in the process of human–computer interaction. Vision-based gesture recognition technology has broad application potential in virtual environments, sign language recognition, machine control, and other fields. In the task of gesture recognition in user interface design, the recognition results are affected by some irrelevant factors, such as dynamic backgrounds and close-fitting clothing. The attention mechanism is a good way to address the above problems, as it applies weights to key areas to extract essential features, thereby improving the model's performance. Several commonly used attention mechanisms, such as spatial attention, channel attention, and mixed attention mechanisms, can only apply attention to a single-frame image, focusing on specific regions. However, gestures consist of sequences of multiple-frame images, and the recognition results are collectively influenced by multiple-frame gesture images. The aforementioned attention mechanisms cannot meet the requirements effectively. To address this issue, a joint intra-frame and inter-frame attention module has been investigated. The model is able to prevent the impact of irrelevant elements during the gesture identification process because of this module's ability to apply attention concurrently across many consecutive frames and inside a single frame. In order to further user interface design, this study employs convolutional neural networks to include gesture recognition. These results shed light on how computer vision technology may revolutionize UI design and enhance user experiences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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A QoS-based technique for load balancing in green cloud computing using an artificial bee colony algorithm

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Journal of Experimental and Theoretical Artificial Intelligence 2025年第2期37卷 307-342页

作者： Tabagchi Milan, Sara Jafari Navimipour, Nima Lohi Bavil, Hamed Yalcin, Senay Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Department of Computer Engineering Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou Taiwan Department of Computer Engineering University of Applied Sciences & Technology Tabriz Iran Department of Computer Engineering Nisantasi University Istanbul Turkey

Nowadays, high energy amount is being wasted by computing servers and personal electronic devices, which produce a high amount of carbon dioxide. Thus, it is required to decrease energy usage and pollution. Many applications are utilised by green computing to save energy. Scheduling of tasks acts as an important process to reach the mentioned goals. It is worth stating that the vital characteristic of task scheduling in green clouds is the load balancing of tasks on virtual machines. Efficient load balancing moves tasks from overloaded to underloaded virtual machines to maintain the Quality of Service (QoS). This issue is an NP-complete problem, so this research suggests a new technique based on the behavioural structure of artificial bee behaviour. This method aims to improve QoS while lowering energy usage in green computing. In addition, the honey bees are considered the removed tasks from overloaded virtual machines and a candidate for migrating selected tasks with the lowest priority. The CloudSim testing findings demonstrate that the technique is successful in QoS, makespan, and energy usage compared to other ways. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Cloud computing

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Blockchain-based secure and transparent election and vote counting mechanism using secret sharing scheme

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14009-14027页

作者： Chouhan, Vikas Arora, Anshul Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee India Department of Applied Mathematics Delhi Technological University Delhi India

Privacy and transparency in vote counting are the most prevalent concerns these days due to the involvement of untrusted authorities in the counting process. As a result, the counting process faces significant privacy, trust, and transparency hurdles. Hence, there is a need for an efficient and trusted mechanism to resolve such problems. Blockchain technology has the potential to bring transparency and trust in several applications. Therefore, in this work, we explore blockchain technology in conjunction with a secure partitioning scheme to promote transparency, trust, and privacy between users and participating authorities in a decentralized platform. This paper presents a chaincode-based implementation of our proposed secure and verifiable vote counting mechanism that enables trust and fairness over a decentralized platform. Multiple authorities participate in the vote counting process in a trusted manner to cooperate and coordinate in a decision process over a decentralized platform. Our research exhibits that blockchain technology can eliminate the trust gaps and increase transparency and fairness in the election and vote counting procedure. We register user votes in the blockchain platform based on the secret sharing mechanism to enable fairness and openness between counting authorities. Each vote is recorded into the distributed ledger to support openness and verifiability in our mechanism. The ledger is accessible to every registered user as per the permissioned blockchain policy. We created many authorities in the blockchain network and deployed multiple smart contracts on the Hyperledger platform to analyze the feasibility of our strategy. The performance results are obtained and reported using the Hyperledger Caliper benchmark tool. The results demonstrate that the proposed chaincode-based solution achieves the highest throughput at 200–400 tps for fetching and removing contracts. We achieve the optimal latency of 18.09 s for the vote distribution contract

关键词： Smart contract

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