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Experimental validation of a novel hybrid Equilibrium Slime Mould Optimization for solar photovoltaic system

Heliyon 2024年第20期10卷 e38943页

作者： Zabia, Djallal Eddine Afghoul, Hamza Kraa, Okba Himeur, Yassine Ramadan, Haitham S. Genc, Istemihan Idriss, Abdoulkader I. Miniaoui, Sami Atalla, Shadi Mansoor, Wathiq Laboratory of Identification Command Control and Communication (LI3CUB) University of Biskra Algeria LAS Laboratory Faculty of Technology Ferhat Abbas Setif-1 University Algeria Laboratory of Energy System Modeling Electrical Engineering (LMSE) Algeria College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Electrical Power and Machines Department Faculty of Engineering Zagazig University Egypt ISTHY Institut International sur le Stockage de l'Hydrogene Meroux-Moval 90400 France Department of Electrical Engineering Istanbul Technical University Istanbul 34469 Turkey Electrical and Energy Department Faculty of Engineering University of Djibouti Street Djanaleh 1904 Djibouti

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems. © 2024

关键词： Complex partial shading condition Equilibrium Slime Mould optimization algorithm Maximum power point tracking Photovoltaic system Renewable energy

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Deep Learning-Based Reverse Method of Binary Protocol 1st

Deep Learning-Based Reverse Method of Binary Protocol

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1st International Conference on Security and Privacy in Digital Economy, SPDE 2020

作者： Yang, Chenglong Fu, Cai Qian, Yekui Hong, Yao Feng, Guanyun Han, Lansheng School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security Wuhan430074 China Department of Command and Control Air Defence Forces Academy of PLA Zhengzhou450052 China

ISBN: (纸本)9789811591280

With the growth of network equipment, the security of network access environment becomes particularly important. Many network security technologies, such as vulnerability mining, fuzzy testing and intrusion detection, have attracted more and more attention. However, the effectiveness of these security technologies will be greatly reduced in the face of unknown protocols. By automatically extracting the format information of unknown protocols through the protocol reverse technology, the processing capability of the above security technologies in the face of unknown protocols can be enhanced. In this paper, by analyzing the changing characteristics of protocol fields, a field sequence coding method is proposed, which is suitable for reflecting the field sequence characteristics of different protocols and can improve the generalization ability of the model. Using the above field sequence coding method, a field classification model for unknown protocols is implemented based on the LSTM-FCN network, which is widely used in time series classification tasks. Finally, a binary protocol reverse method based on deep learning is proposed. The method is based on the field classification model and realizes the division and type identification of unknown protocol fields according to the classification results. In the experiment, the field classification model has high accuracy and recall in different protocols, which shows that the model has the ability to identify the field type according to the changing characteristics of the field. The proposed protocol reverse method also accurately and quickly identifies the field and its type, proving the reverse ability of the method to unknown binary protocols. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Intrusion detection

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Survey on methods for automated measurement of the software scale

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International Journal of Performability engineering 2020年第2期16卷 255-264页

作者： Zhu, Jing Huang, Song Shi, Yaqing Chen, Mingyu Liu, Jialuo Liu, Erhu Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China Training Management Department Navy Command College Nanjing210016 China 94973 Troop Hangzhou310021 China

Software scale automated measurement plays an increasingly important role in the early stage of software development. Mainstream software scale measurement methods are mainly based on function point methods, which are dependent on manpower. Therefore, software scale measurement based on automated acquisition of function points is one of the emphases of future research. In this paper, software scale measurement is discussed, and main algorithms based on the IFPUG function point method are introduced. These algorithms are compared and analyzed in order to summarize their advantages and disadvantages. Then, four steps that should be performed to automatically obtain function points are proposed, and the technical challenges of each step are pointed out. Finally, the future research direction is given. © 2020 Totem Publisher, Inc.

关键词： Software design

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Cosmological neutrino N-body simulations of dark matter halo

arXiv

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arXiv 2023年

作者： Chen, Yu Lu, Chang-Zhi Li, Juan Liu, Siqi Zhang, Tong-Jie Zhang, Tingting Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University Beijing102206 China Department of Astronomy Beijing Normal University Beijing100875 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China College of Physics and Electronic Engineering Qilu Normal University Jinan250200 China Institute for Astronomical Science Dezhou University Dezhou253023 China College of Command and Control Engineering PLA Army Engineering University Nanjing China

The study of massive neutrinos and their interactions is a critical aspect of contemporary cosmology. Recent advances in parallel computation and high-performance computing provide new opportunities for accurately constraining Large-Scale Structures (LSS). In this paper, we introduce the TianNu cosmological N-body simulation during the co-evolution of massive neutrino and cold dark matter components via the CUBEP3M code running on the supercomputer Tianhe-2 and TianNu’s connected works. We start by analyzing 2.537 × 107 dark halos from the scientific data of TianNu simulation, and compare their angular momentum with the matched halos from neutrino-free TianZero, revealing a dependence of angular momentum modulus on neutrino injection at scales below 50 Mpc and around 10 Mpc. Copyright © 2023, The Authors. All rights reserved.

关键词： Angular momentum

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A Guide to Image and Video based Small Object Detection using Deep Learning: Case Study of Maritime Surveillance

arXiv

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arXiv 2022年

作者： Rekavandi, Aref Miri Xu, Lian Boussaid, Farid Seghouane, Abd-Krim Hoefs, Stephen Bennamoun, Mohammed The Department of Computer Science and Software Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The Department of Electrical Electronics and Computer Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The School of Mathematics and Statistics The University of Melbourne Melbourne Australia submarine optronics undersea combat systems and undersea command and control maritime division Defence Science and Technology Group Australia

Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects. Typically, small objects appear in real-world due to large camera-object distance. Because small objects occupy only a small area in the input image (e.g., less than 10%), the information extracted from such a small area is not always rich enough to support decision making. Multidisciplinary strategies are being developed by researchers working at the interface of deep learning and computer vision to enhance the performance of SOD deep learning based methods. In this paper, we provide a comprehensive review of over 160 research papers published between 2017 and 2022 in order to survey this growing subject. This paper summarizes the existing literature and provide a taxonomy that illustrates the broad picture of current research. We investigate how to improve the performance of small object detection in maritime environments, where increasing performance is critical. By establishing a connection between generic and maritime SOD research, future directions have been identified. In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the datasets are provided. © 2022, CC BY-NC-SA.

关键词： Object recognition

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Three approaches to the design of a golden online course on data structure 2

Three approaches to the design of a golden online course on ...

引用

2nd International Conference on Computer Science and Educational Informatization, CSEI 2020

作者： Chen, Weiwei Li, Zhigang Tang, Yanqin Wang, Baohua Wang, Bin Zhou, Lei Liu, Ying Command and Control Engineering College Army Engineering Univ. of PLA Nanjing210007 China Office of Educational Administration Army Engineering Univ. of PLA Nanjing210007 China Assessment Center Army Engineering Univ. of PLA Nanjing210007 China Army Engineering Univ. of PLA Fundamental Education Department Nanjing210007 China

ISBN: (纸本)9781728170077

The problem of Attention Deficit Disorder is more noticeable in online teaching than in face-to-face teaching. Facing the new requests of constructing Golden Course and based on the analysis of the relationship between Golden Course and Attention Deficit Disorder, the paper takes the national-level MOOC, Data structure, as an example and explores three approaches to solve the problem of Attention Deficit Disorder from the perspective of teaching content organization and implementation. These three approaches are also the core strategies for Golden Course design. The main content is as follows. First, establish the levels of learning objectives under the guidance of BLOOM model, and optimize the design of learning objectives with Mager method, so that students can obtain specific information, find correct learning direction, and avoid lack of attention. Second, use concept map to select and divide learning content, highlighting the importance and relevance of learning content, and ensure that the content is explained within about 10 minutes. Although the time is fragmented, the content is not fragmented. Third, the BOPPPS model is used to organize the process of course implementation and introduce the learning content under the guidance of questions, so as to ensure that the internal logic of the course is compact and effective, and students' interest in learning can be enhanced. Practice shows that the curriculum design strategy which combines the three approaches mentioned above can effectively solve the problem of Attention Deficit Disorder. The course, Data Structure, constructed with three mentioned approaches, was selected as one of the national-level MOOCs in January 2019, which has been running for 4 years on the net for 7 semesters, with a course rating score of 4.8 points out of 5 points, and taken by more than 70, 000 learners. © 2020 IEEE.

关键词： Data structures

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Modeling and Analysis of Contact Detumbling by Using Flexible Brush

Modeling and Analysis of Contact Detumbling by Using Flexibl...

引用

2019 IEEE International Conference on Unmanned Systems, ICUS 2019

作者： Cheng, Wenhua Li, Zhi He, Yingzi Space Engineering University Department of Graduate Management Beijing China Space Engineering University Department of Space Command Beijing China Beijing Institute of Control Engineering Space Intelligent Control Laboratory Beijing China

ISBN: (纸本)9781728137926

The prerequisite for capturing a tumbling object is that the angular rate is within a certain span. Within this paper, the feasibility of detumbling a target with contact force by using flexible brush is studied. A generic detumbling model is established and the detumbling process is analysed. The contact force model, including the friction, is derived based on mechanics of materials. With these models, the detumbling process is simulated and the DE (Detumbling-Effect) relationships with each factor are researched. © 2019 IEEE.

关键词： contact detumbling contact dynamic flexible brush on-orbit service

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Test of Artificial Neural Networks in Likelihood-free Cosmological Constraints: A Comparison of IMNN and DAE

arXiv

引用

arXiv 2022年

作者： Chen, Jie-Feng Wang, Yu-Chen Zhang, Tingting Zhang, Tong-Jie Institute for Frontiers in Astronomy and Astrophysics Department of Astronomy Beijing Normal University Beijing102206 China Department of Astronomy Beijing Normal University Beijing100875 China Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China Department of Astronomy School of Physics Peking University Beijing100871 China Department of Physics Beijing Normal University Beijing100875 China College of Command and Control Engineering Army Engineering University Nanjing210017 China Institute for Astronomical Science Dezhou University Dezhou253023 China

In the procedure of constraining the cosmological parameters with the observational Hubble data, the combination of Masked Autoregressive Flow and Denoising Autoencoder can perform a good result. The above combination extracts the features from OHD with DAE, and estimates the posterior distribution of H0, Ωm, ΩΛ with MAF. We ask whether we can find a better tool to compress large data in order to gain better results while constraining the cosmological parameters. Information maximising neural networks, a kind of simulation-based machine learning technique, was proposed at an earlier time. In a series of numerical examples, the results show that IMNN can find optimal, non-linear summaries robustly. In this work, we mainly compare the dimensionality reduction capabilities of IMNN and DAE. We use IMNN and DAE to compress the data into different dimensions and set different learning rates for MAF to calculate the posterior. Meanwhile, the training data and mock OHD are generated with a simple Gaussian likelihood, the spatially flat ΛCDM model and the real OHD data. To avoid the complex calculation in comparing the posterior directly, we set different criteria to compare IMNN and DAE. Copyright © 2022, The Authors. All rights reserved.

关键词： Neural networks

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Strategy and control for Robotic Detumbling of Space Debris by Using Flexible Brush 3

Strategy and Control for Robotic Detumbling of Space Debris ...

引用

3rd IEEE International Conference on Robotics and Automation Sciences, ICRAS 2019

作者： Cheng, Wenhua Li, Zhi He, Yingzi Department of Graduate Management Space Engineering University Beijing China Department of Space Command Space Engineering University Beijing China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9781728108537

Active space debris removal (ASDR) is an effective and reliable mean to keep space exploration and space environment. But space debris is always with complex attitude, including spinning and nutation, due to space environmental torque, and causing trouble in ASDR. This paper focuses on the strategy and control for robotic detumbling of space debris by using flexible brush. First, the model of detumbling-robot and flexible brush, which acts as the end-effecter, are proposed. On this basis, the contact force model, including the friction, is derived based on mechanics of materials and Coulomb friction. Subsequently, the motion and dynamic equations between robot and debris are formulated. With detumbling strategy, the control law is presented. Simulation results are appended. The results show that it is difficult to ensure long-term contact between the detumbling-robot and debris because of the contact elastic force without control force. Instead, the angular rate of debris would be detumbled to desired value after several times contact, and the energy which used up during detumbling is also in reasonable span. The tumbling debris could be detumbled by flexible brush with the strategy and control law stated above. © 2019 IEEE.

关键词： Friction

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HASN:A Hierarchical Attack Surface Network for System Security Analysis

引用

China Communications 2019年第5期16卷 137-157页

作者： Kangyu Huang Lin Yang Renfang Fu Shengli Zhou Zheng Hong College of Command and Control Engineering Army Engineering UniversityNanjing 210007China China Electronic Equipment & System Engineering Corporation Beijing 100141China State Grid Jiangsu Electric Power Company Research Institute Nanjing 210019China Information Department of Zhejiang Police College Hangzhou 310053China

Attack surfaces, as one of the security models, can help people to analyse the security of systems in cyberspace, such as risk assessment by utilizing various security metrics or providing a cost-effective network hardening solution. Numerous attack surface models have been proposed in the past decade,but they are not appropriate for describing complex systems with heterogeneous components. To address this limitation, we propose to use a two-layer Hierarchical Attack Surface Network(HASN) that models the data interactions and resource distribution of the system in a component-oriented view. First, we formally define the HASN by extending the entry point and exit point framework. Second, in order to assess data input risk and output risk on the HASN, we propose two behaviour models and two simulation-based risk metrics. Last, we conduct experiments for three network systems. Our experimental results show that the proposed approach is applicable and effective.

关键词： attack surface security analysis security model risk assessment

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