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New modification of the Hestenes-Stiefel with strong Wolfe line search

AIP Conference Proceedings 2021年第1期2355卷

作者： Nur Athira Japri Srimazzura Basri Mustafa Mamat 1Faculty of Applied Sciences & Technology Universiti Tun Hussein Onn Malaysia 86400 Johor Darul Takzim Malaysia. 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus of Tembila 22200 Terengganu Darul Iman Malaysia.

The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter that fulfils the condition of sufficient descent using a strong Wolfe-Powell line search. Besides, the conjugate gradient method with the proposed conjugate gradient also guarantees low computation of iteration and CPU time by comparing with other classical conjugate gradient parameters. Numerical results have shown that the conjugate gradient method with the proposed conjugate gradient parameter performed better than the conjugate gradient method with other classical conjugate gradient parameters.

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Clustering botnet behavior using K-means with uncertain data 18

Clustering botnet behavior using K-means with uncertain data

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18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2019

作者： Ibrahim, Wan Nur Hidayah Selamat, Ali Anuar, Syahid Krejcar, Ondrej School of Computing Faculty of Engineering Universiti Teknologi Malaysia Universiti Teknologi Malaysia Johor Baharu Johor81310 Malaysia Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala Lumpur54100 Malaysia Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala Lumpur54100 Malaysia Center for Basic and Applied Research Faculty of Informatics and Management University of Hradec Kralove Rokitanskeho 62 Hradec Kralove500 03 Czech Republic

ISBN: (纸本)9781643680125

Botnets are the most deadly threat in the network due to the capability of exploiting resources within a network as an army to launch huge attacks such as Denial-Distributed-of-Service (DDOS) or spam emails. Network Intrusion Detection System (NIDS) that designed based on the behavior of botnets in network traffic is seen as the promising technique in detecting botnets that are hiding by using encryption technique or any hiding techniques. This paper proposes on K-means clustering algorithm as the first phase of botnet's behaviour detection model that extracts data from network traffic. The criterion highlighted for our behaviour detection model is that it should be able to detect botnet in encrypted packets(hiding techniques), structure-independent (centralized and peer-to-peer), requiring minimal computing resources and minimal time processing. Other than that, by representing the real-time of network traffics, the detection model also must be resistant to noise and able to identify the anomaly of botnets behavior among a huge number of normal traffic. We are using the botnet benchmark dataset and normal traffic from Malware Capture Facility Project and comparing our proposed method using K-means algorithm with Expectation Maximization algorithm that proposed by the previous researcher in clustering the similar pattern of botnet behavior. The result shows that the K-means algorithm producing much higher accuracy, 94% and lower false negative rate, 0.1413. While, average accuracy for Expectation Maximization algorithm is 88% and False Negative Rate, 0.2245 with the insertion of uncertain data from real network traffic. © 2019 The authors and IOS Press. All rights reserved.

关键词： Botnet

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Network and Systems Medicine: Position Paper of the European Collaboration on Science and technology Action on Open Multiscale Systems Medicine

Network and Systems Medicine

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Network and Systems Medicine 2020年第1期3卷 67-90页

作者： Comte, Blandine Baumbach, Jan Benis, Arriel Basílio, José Debeljak, Nataša Flobak, Åsmund Franken, Christian Harel, Nissim He, Feng Kuiper, Martin Méndez Pérez, Juan Albino Pujos-Guillot, Estelle Reen, Tadeja Rozman, Damjana Schmid, Johannes A. Scerri, Jeanesse Tieri, Paolo Van Steen, Kristel Vasudevan, Sona Watterson, Steven Schmidt, Harald H.H.W. Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Université Clermont Auvergne INRAE UNH Clermont-Ferrand France Freising-Weihenstephan Germany Holon Institute of Technology Holon Israel Institute of Vascular Biology and Thrombosis Research Center for Physiology and Pharmacology Medical University of Vienna Vienna Austria Medical Centre for Molecular Biology Institute of Biochemistry Faculty of Medicine University of Ljubljana Ljubljana Slovenia Department of Clinical and Molecular Medicine Norwegian University of Science and Technology Trondheim Norway The Cancer Clinic St. Olav's University Hospital Trondheim Norway Digital Health Systems Einsingen Germany Department of Pharmacology and Personalised Medicine Faculty of Health Medicine and Life Science Maastricht University Maastricht Netherlands Department of Infection and Immunity Luxembourg Institute of Health Esch-sur-Alzette Luxembourg Institute of Medical Microbiology University Hospital Essen University of Duisburg-Essen Essen Germany Department of Biology Faculty of Natural Sciences Norwegian University of Science and Technology Trondheim Norway Department of Computer Science and Systems Engineering Universidad de la Laguna Tenerife Spain Centre for Functional Genomics and Bio-Chips Institute of Biochemistry Faculty of Medicine University of Ljubljana Ljubljana Slovenia Department of Physiology and Biochemistry Faculty of Medicine and Surgery University of Malta Msida Malta CNR National Research Council IAC Institute for Applied Computing Rome Italy GIGA-R Medical Genomics-BIO3 University of Liège Liège Belgium Georgetown University Medical Centre WashingtonDC United States Northern Ireland Centre for Stratified Medicine Ulster University Londonderry United Kingdom Department of Pharmacology and Personalised Medicine Faculty of Health Medicine and Life Science MeHNS Maastricht University Netherlands

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ-and symptom-based medical concepts toward network-and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management. © Blandine Comte et al. 2020;Published by Mary Ann Liebert, Inc. 2020.

关键词： Big data

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Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots

arXiv

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arXiv 2023年

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023, CC0.

关键词： Machine learning

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Understanding the pattern of wind direction in Peninsular Malaysia

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AIP Conference Proceedings 2023年第1期2500卷

作者： Nor Hafizah Moslim Yong Zulina Zubairi Abdul Ghapor Hussin Siti Fatimah Hassan Nurkhairany Amyra Mokhtar 1)Institute of Advanced Studies University of Malaya 50603 Kuala Lumpur Malaysia 2)Centre of Mathematical Sciences College of Computing & Applied Sciences Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Gambang Pahang Malaysia 3)Centre for Foundation Studies in Science University of Malaya 50603 Kuala Lumpur Malaysia 4)Faculty of Defence Sciences and Technology National Defence University of Malaysia Kem Sungai Besi 57000 Kuala Lumpur Malaysia 5)Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Cawangan Johor Kampus Segamat 85000 Segamat Johor Malaysia

Understanding the pattern of wind direction is important in meteorological studies. In exploratory data analysis, summary statistics provide basic information such as the measures of central tendency and the spread of the maximum wind direction. In this study, daily wind direction data recorded at maximum wind speed of northeast and southwest monsoons from three stations in Peninsular Malaysia from the year of 2014 to 2019 are used. The wind direction data is modeled using von Mises distribution where confidence interval for concentration parameter is estimated using bootstrap-t method. Based on the performance measure of expected length, the confidence interval provides an efficient measure of the concentration parameter. Findings of this study suggest that there are variations with respect to monsoons and locations as some are dense and some are sparsely distributed. This information is useful in providing a better-understanding of the pattern of wind direction in Malaysia.

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Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks

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Medical Image Analysis 2022年 78卷 102396-102396页

作者： Subramaniam, Pooja Kossen, Tabea Ritter, Kerstin Hennemuth, Anja Hildebrand, Kristian Hilbert, Adam Sobesky, Jan Livne, Michelle Galinovic, Ivana Khalil, Ahmed A. Fiebach, Jochen B. Frey, Dietmar Madai, Vince I. CLAIM - Charité Lab for AI in Medicine Charité Universitätsmedizin Berlin Germany Department of Computer Engineering and Microelectronics Computer Vision & Remote Sensing Technical University Berlin Berlin Germany Berlin Germany Bernstein Center for Computational Neuroscience Berlin Germany Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine Charité Universitätsmedizin Berlin Berlin Germany Fraunhofer MEVIS Max-von-Laue-Str. 2 Bremen Germany Department VI Computer Science and Media Beuth University of Applied Sciences Berlin Germany Johanna-Etienne-Hospital Neuss Germany Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Berlin Germany Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Mind Brain Body Institute Berlin School of Mind and Brain Humboldt University Berlin Berlin Germany Berlin Institute of Health Berlin Germany School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham United Kingdom QUEST-Center for Transforming Biomedical Research Berlin Institute of Health Charité Universitätsmedizin Berlin Charitéplatz 1 Berlin10117 Germany

Deep learning requires large labeled datasets that are difficult to gather in medical imaging due to data privacy issues and time-consuming manual labeling. Generative Adversarial Networks (GANs) can alleviate these challenges enabling synthesis of shareable data. While 2D GANs have been used to generate 2D images with their corresponding labels, they cannot capture the volumetric information of 3D medical imaging. 3D GANs are more suitable for this and have been used to generate 3D volumes but not their corresponding labels. One reason might be that synthesizing 3D volumes is challenging owing to computational limitations. In this work, we present 3D GANs for the generation of 3D medical image volumes with corresponding labels applying mixed precision to alleviate computational constraints. We generated 3D Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) patches with their corresponding brain blood vessel segmentation labels. We used four variants of 3D Wasserstein GAN (WGAN) with: 1) gradient penalty (GP), 2) GP with spectral normalization (SN), 3) SN with mixed precision (SN-MP), and 4) SN-MP with double filters per layer (c-SN-MP). The generated patches were quantitatively evaluated using the Fréchet Inception Distance (FID) and Precision and Recall of Distributions (PRD). Further, 3D U-Nets were trained with patch-label pairs from different WGAN models and their performance was compared to the performance of a benchmark U-Net trained on real data. The segmentation performance of all U-Net models was assessed using Dice Similarity Coefficient (DSC) and balanced Average Hausdorff Distance (bAVD) for a) all vessels, and b) intracranial vessels only. Our results show that patches generated with WGAN models using mixed precision (SN-MP and c-SN-MP) yielded the lowest FID scores and the best PRD curves. Among the 3D U-Nets trained with synthetic patch-label pairs, c-SN-MP pairs achieved the highest DSC (0.841) and lowest bAVD (0.508) compared to the benchmark

关键词： Generative adversarial networks

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Performance study on mounting system for displacement transducer in mechanical tests of timber samples using photogrammetry method

Research Square

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Research Square 2021年

作者： Mohamed, Ahmed Zhang, Hexin Deng, Yu Lehmann, Martin Sigrist, Christophe Uheida, Kal Zheng, Yu Bahadori-Jahromi, Ali Shahidan, Shahiron Caudoux, Remi School of Engineering and the Built Environment Edinburgh Napier University 10 Colinton Road Scotland EdinburghEH10 5DT United Kingdom Civil Engineering Department Faculty of Engineering Omar Al-Mukhtar University Libya School of Civil Engineering and Architecture Guangxi University of Science and Technology Liuzhou545006 China Institute for Materials and Wood Technology Bern University of Applied Sciences Solothurnstrasse 102 Biel2504 Switzerland School of Environment and Civil Engineering Dongguan University of Technology Dongguan523080 China Department of Civil Engineering and Built Environment School of Computing and Engineering University of West London LondonW5 5RF United Kingdom Faculty of Civil Engineering and Built Environment Universiti Tun Hussein Onn Malaysia Johor Batu Pahat86400 Malaysia Signature Murale 12 rue du Parc Royal Paris75003 France

This paper presents a unique study to reveal the effect of the mounting system of the linear variable differential transformer (LVDT) on the mechanical property tests of timber materials. This effect has been overlooked in the past but proven to be significant enough that will distort the measurements completely if the displacement is relatively small. The reason for causing this error is because the LVDT is not directly measuring targeting points on a sample, instead, the LVDT is measuring the distance between one point on the stop-end (where the tip rested on) and the holder. The wrong common sense hopes that this point on the stop-end and holder reliably following the movement of the sample points. But this study reveals that it is not always the case with the aid from the photogrammetry method. The messages of this paper are simple but alertly useful and, important: 1) the mounting system and the method of installation of the LVDTs have a significant impact on the actual displacement measurement in a mechanical properties test of timber materials. It should be carefully designed and validated before the actual test;2) the displacement distribution is not uniform across the timber sample. This should be taken into account when selecting the mounting points of the LVDTs. Testing standards should consider this effect when recommending displacement transducers to be used in a timber-related test. © 2021, CC BY.

关键词： Timber

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6LoWPAN Protocol in Fixed Environment: A Performance Assessment Analysis

6LoWPAN Protocol in Fixed Environment: A Performance Assessm...

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IEEE International Conference on Intelligent Data Acquisition and Advanced computing Systems

作者： Nin Hayati Mohd Yusoff Nurul Azma Zakaria Axel Sikora Jubin Sebastian E Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Malaysia Faculty of Information and Communication Technology Center for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Malaysia Institute of Reliable Embedded Systems and Communication Electronics Offenburg University of Applied Sciences Offenburg Germany

The Internet of Things (IoT) application has becoming progressively in-demand, most notably for the embedded devices (ED). However, each device has its own difference in computational capabilities, memory usage, and energy resources in connecting to the Internet by using Wireless Sensor Networks (WSNs). In order for this to be achievable, the WSNs that form the bulk of the IoT implementation requires a new set of technologies and protocol that would have a defined area, in which it addresses. Thus, IPv6 Low Power Area Network (6LoWPAN) was designed by the Internet Engineering Task Force (IETF) as a standard network for ED. Nevertheless, the communication between ED and 6LoWPAN requires appropriate routing protocols for it to achieve the efficient Quality of Service (QoS). Among the protocols of 6LoWPAN network, RPL is considered to be the best protocol, however its Energy Consumption (EC) and Routing Overhead (RO) is considerably high when it is implemented in a large network. Therefore, this paper would propose the HRPL to enchance the RPL protocol in reducing the EC and RO. In this study, the researchers would present the performance of RPL and HRPL in terms of EC, Control traffic Overhead (CTO) and latency based on the simulation of the 6LoWPAN network in fixed environment using COOJA simulator. The results show HRPL protocol achieves better performance in all the tested topology in terms of EC and CTO. However, the latency of HRPL only improves in chain topology compared with RPL. We found that further research is required to study the relationship between the latency and the load of packet transmission in order to optimize the EC usage.

关键词： Protocols Topology Energy consumption Network topology Internet of Things Routing

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Toward the end-to-end optimization of particle physics instruments with differentiable programming

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Reviews in Physics 2023年 10卷

作者： Dorigo, Tommaso Giammanco, Andrea Vischia, Pietro Aehle, Max Bawaj, Mateusz Boldyrev, Alexey de Castro Manzano, Pablo Derkach, Denis Donini, Julien Edelen, Auralee Fanzago, Federica Gauger, Nicolas R. Glaser, Christian Baydin, Atılım G. Heinrich, Lukas Keidel, Ralf Kieseler, Jan Krause, Claudius Lagrange, Maxime Lamparth, Max Layer, Lukas Maier, Gernot Nardi, Federico Pettersen, Helge E.S. Ramos, Alberto Ratnikov, Fedor Röhrich, Dieter de Austri, Roberto Ruiz del Árbol, Pablo Martínez Ruiz Savchenko, Oleg Simpson, Nathan Strong, Giles C. Taliercio, Angela Tosi, Mia Ustyuzhanin, Andrey Zaraket, Haitham MODE Collaboration Istituto Nazionale di Fisica Nucleare Sezione di Padova Italy Université catholique de Louvain Belgium Chair for Scientific Computing Technische Universität Kaiserslautern Germany Università di Perugia and INFN Sezione di Perugia Italy HSE University Russia Université Clermont Auvergne Laboratoire de Physique de Clermont CNRS/IN2P3 France SLAC National Accelerator Laboratory United States Department of Physics and Astronomy Uppsala University Sweden Department of Computer Science University of Oxford United Kingdom Physik-Department Technische Universität München Germany Center for Technology and Transfer University of Applied Sciences Worms Germany CERN Switzerland NHETC Department of Physics and Astronomy Rutgers University United States Università di Napoli "Federico II" Italy Germany Università degli Studi di Padova Italy Department of Oncology and Medical Physics Haukeland University Hospital Norway Instituto de Física Corpuscular UV-CSIC Spain Department of Physics and Technology University of Bergen Norway Instituto de Física de Cantabria UC-CSIC Spain Lund University Sweden Multi-Disciplinary Physics Laboratory Optics and Fiber Optics Group Faculty of Sciences Lebanese University Lebanon the World Constructor University Bremen gGmbH Campus Ring 1 Bremen 28759 Germany

The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, "experience-driven" layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized through a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this white paper, we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications. © 2023 The Author(s)

关键词： Astrophysics

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The atomic and thermal performance of CuO nanoparticles/paraffin as phase change materials in a circular tube: Molecular dynamics simulation approach

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Nano-Structures & Nano-Objects 2025年 42卷

作者： Sabreen Q. Al-Timimy Waqed H. Hassan Narinderjit Singh Sawaran Singh Ghazi Faisal Naser Soheil Salahshour S. Mohammad Sajadi Maboud Hekmatifar University of Misan College of Engineering Department of Materials Engineering Amarah Iraq University of Warith Al-Anbiyaa Kerbala 56001 Iraq Department of Civil Engineering College of Engineering University of Kerbala Kerbala 56001 Iraq Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia Chemical Engineering Department College of Engineering Al-Muthanna University Iraq College of Engineering Al-Ayen University Thi-Qar Iraq Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Research Center of Applied Mathematics Khazar University Baku Azerbaijan Department of Chemistry Payam e Noor University Saqqez Branch Saqqez Kurdistan Iran Fast Computing Center Shabihsazan Ati Pars Tehran Iran

Background Using molecular dynamics simulation, this study investigates the effect of CuO nanoparticle addition on the thermodynamic and atomic properties of an octadecane that was being utilized as a phase change material within a circular tube. Methods The results indicate that the density (D) was greatest in the vicinity of the tube walls. At its peak, D was 0.0300 atoms per square centimeter. This behavior is due to the increased attractive force that is between the structure's boundaries and its particles. Particle velocity (V) values reached their utmost attainable values in the intermediate regions of the tube, where movement was greatest. At its peak, V was 0.0078 Å/fs. The tube exhibits a maximum temperature (Max T) value of 754.43 K at its midpoint. Significant Findings Due to the increased particle motion in the intermediate regions, the investigated structure experienced a greater number of collisions in those areas. After 10 ns, the sample's heat flux, thermal conductivity, and thermal stability converged to values of 3.94 W/m 2 , 1.38 W/mK, and 1821 K, respectively. The structure showed charging and discharging times of 6.41 and 7.15 ns, respectively.

关键词： Atomic and thermal behavior CuO nanoparticles Molecular dynamics simulation Phase change material

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