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SpringerBriefs in Applied Sciences and Technology 2025年 Part F127卷 v页

作者： Sambhav, Saurabh Singh, Deepak Kumar Pandey, Ashok Kumar Ismail, Azman Zulkipli, Fatin Nur Öchsner, Andreas Amity University Patna Bihar Patna India Madhya Pradesh Bhopal India Maritime Engineering Technology and Centre for Women Advancement and Leadership Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology Perak Lumut Malaysia Information Science Studies College of Computing Informatics and Mathematics Universiti Teknologi MARA Machang Kelantan Malaysia Faculty of Mechanical Engineering Esslingen University of Applied Sciences Baden-Württemberg Esslingen Germany

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A review of mobile chatbot apps for anxiety and depression and their self-care features

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Computer Methods and Programs in Biomedicine Update 2021年 1卷

作者： Ahmed, Arfan Ali, Nashva Aziz, Sarah Abd-alrazaq, Alaa A Hassan, Asmaa Khalifa, Mohamed Elhusein, Bushra Ahmed, Maram Ahmed, Mohamed Ali Siddig Househ, Mowafa Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Centre for Health Informatics Australian Institute of Health Innovation Faculty of Medicine Health and Human Sciences Macquarie University Sydney Australia Mental Health Services Hamad Medical Corporation Qatar

Background: Anxiety and depression rates are at an all-time high. Smartphone-based mental health chatbots can aid psychiatrists replacing some of the costly human based interaction providing a unique opportunity to expand the availability and quality of mental health intervention whilst providing an alternative approach to fill the much-needed self-care gap. Objective: Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. Methods: A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbot apps for anxiety and depression. Eligibility was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and post-installation by two reviewers. Information on quality was assessed by following the mHONcode principles. Results: Only a handful (n=11) of chatbots were included from an initial search of 1000 that provide a substitute for human-human based interaction and clearly had a therapeutic human substitute goal in mind. The majority of reviewed apps had a high number of downloads indicating their popularity. The apps were also of a general high quality based on our assessment according to the mHONcode principles. Conclusion: The general popularity of apps reviewed, and results of our quality assessment indicate chatbots have a promising future within the realm of anxiety and depression. Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed low-cost assistance to professionals. © 2021

关键词： ”Anxiety” ”Chatbots” ”COVID-19” ”Depression” ”Pandemics”

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InP/ZnS core/shell quantum dots: Synthesis, characterization and their application in fullerene derivative based flexible solar cells

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Results in Physics 2025年 69卷

作者： Zhichu, Chen Tahir, Muhammad Muhammad, Fida Aziz, Fakhra Ayub, Ambreen Badshah, Fazal Refat, Moamen S. Cakmak, Sadiye M. Rehan, Shanza Adam, Abdel Majid A. Alsuhaibani, Amnah Mohammed Ayob, Afida Sarker, Mahidur R Khan, Adam School of Electrical and Information Engineering Hubei University of Automotive Technology Shiyan 442002 China Semiconductor Physics & Devices Laboratory Department of Physics Faculty of Physical and Numerical Sciences Abdul Wali Khan University Mardan 23200 Pakistan Department of Electronics University of Peshawar KP Pakistan Department of Physics Women University Mardan KP 23200 Pakistan Department of Chemistry College of Science Taif University P.O. Box 11099 Taif 21944 Saudi Arabia Program of Medical Monitoring Techniques Osmangazi University Eskisehir Eskisehir 26040 Turkey Faculty of Materials and Chemical Engineering GIK Institute of Engineering Sciences and Technology Topi 23640 Pakistan Department of Physical Sport Sciences College of Sport Sciences & Physical Activity Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Centre for Integrated Systems Engineering and Advanced Technologies (INTEGRA) Department of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia Bangi 43600 Malaysia Institute of Visual Informatics Universiti Kebangsaan Selangor Malaysia Bangi 43600 Malaysia Universidad de Diseno Innovacion y Tecnología UDIT Av. Alfonso XIII 97 Madrid 28016 Spain Department of Electronics Engineering University of Engineering & Technology Peshawar (Abbottabad Campus) Abbottabad Pakistan

Herein, we report on the synthesis and characterization of p-type semiconductor indium phosphide/zinc sulphide (InP/ZnS) core/shell quantum dots (QDs) prepared via a simple solvothermal method and their potential application in bulk heterojunction (BHJ) flexible solar cell (SC). The BHJ SC composed of donor–acceptor (D-A) configuration at nanoscale provides larger interfacial junction area throughout the bulk volume of the photo-absorber D-A blend that facilitates excitons to efficiently dissociate within the bulk layer at D-A interface. Hence, InP/ZnS core–shell QDs and a fullerene derivative – phenyl C61 butyric acid methyl ester (PCBM) – are used as hybrid inorganic–organic D-A materials, respectively, to fabricate Ag/LiF/InP/ZnS-PCBM/P3HT/ITO/PET BHJ flexible SC. Indium tin oxide (ITO) coated on polyethylene terephthalate (PET), poly(3-hexylthiophene) (P3HT), lithium fluoride (LiF) and silver (Ag) are employed as a flexible substrate, hole transport layer (HTL), electron transport layer (ETL) and counter electrode, respectively. Photovoltaic (PV) properties of the fabricated BHJ flexible SC are studied under standard testing conditions (STC) i.e., 25 ⁰C, 1.5 AM global and 100 mW/cm² irradiation, which exhibit fill factor (FF) of 59 ± 0.02 % and power conversion efficiency (PCE) of 4.22 ± 0.05 %. Also, the heterojunction characteristics are investigated in dark condition (0 lx) to find series resistance (R_s), ideality factor (n), and reverse saturation current (I₀). X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM) and ultraviolet–visible (UV–vis) spectroscopy are performed to further investigate the properties of InP/ZnS-PCBM thin films. Transmission electron microscopy (TEM) image of InP/ZnS core/shell QDs confirmed the successful synthesis of QDs having an average size of 5 ± 1 nm. The InP/ZnS-PCBM D-A photo-absorber layer reveals its potential as one of good candidates for hi

关键词： Flexible solar cell Hybrid bulk heterojunction (BHJ) InP/ZnS core/shell QDs Power conversion efficiency (PCE) Quantum dots (QDs) synthesis

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Preface

SpringerBriefs in Applied Sciences and Technology

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SpringerBriefs in Applied Sciences and Technology 2024年 Part F2025卷 v页

作者： Ismail, Azman Zulkipli, Fatin Nur Daril, Mohd Amran Mohd Öchsner, Andreas Centre for Women Advancement and Leadership Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology Perak Lumut Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Kelantan Machang Malaysia Malaysian Institute of Industrial Technology Universiti Kuala Lumpur Johor Masai Malaysia Faculty of Mechanical Engineering Esslingen University of Applied Sciences Esslingen am Neckar Baden-Württemberg Germany

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Machine learning for modelling unstructured grid data in computational physics: a review

arXiv

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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

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PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery

arXiv

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arXiv 2024年

作者： Das, Adrito Khan, Danyal Z. Psychogyios, Dimitrios Zhang, Yitong Hanrahan, John G. Vasconcelos, Francisco Pang, You Chen, Zhen Wu, Jinlin Zou, Xiaoyang Zheng, Guoyan Qayyum, Abdul Mazher, Moona Razzak, Imran Li, Tianbin Ye, Jin He, Junjun Plotka, Szymon Kaleta, Joanna Yamlahi, Amine Jund, Antoine Godau, Patrick Kondo, Satoshi Kasai, Satoshi Hirasawa, Kousuke Rivoir, Dominik Pérez, Alejandra Rodriguez, Santiago Arbeláez, Pablo Stoyanov, Danail Marcus, Hani J. Bano, Sophia Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Department of Neurosurgery National Hospital for Neurology and Neurosurgery London United Kingdom HKISI CAS China Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China National Heart and Lung Institute Faculty of Medicine Imperial College London United Kingdom Centre for Medical Image Computing University College London London United Kingdom University of New South Wales Sydney Australia Shanghai AI Lab Shanghai China Informatics Institute University of Amsterdam Amsterdam Netherlands Department of Biomedical Engineering and Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Netherlands Sano Center for Computational Medicine Krakow Poland Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg a partnership between DKFZ University Hospital Heidelberg Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Muroran Institute of Technology Hokkaido Japan Niigata University of Health and Welfare Niigata Japan Konica Minolta Inc. Osaka Japan National Center for Tumor Diseases Dresden Germany Centre for Tactile Internet TUD Dresden Germany Universidad de los Andes Bogota Colombia DKFZ UKDD TUD Germany

The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a surgery: including which surgical steps are performed;and which surgical instruments are used. This information can later be used to assist clinicians when learning the surgery;during live surgery;and when writing operation notes. The Pituitary Vision (PitVis) 2023 Challenge tasks the community to step and instrument recognition in videos of endoscopic pituitary surgery. This is a unique task when compared to other minimally invasive surgeries due to the smaller working space, which limits and distorts vision;and higher frequency of instrument and step switching, which requires more precise model predictions. Participants were provided with 25-videos, with results presented at the MICCAI-2023 conference as part of the Endoscopic Vision 2023 Challenge in Vancouver, Canada, on 08-Oct-2023. There were 18-submissions from 9-teams across 6-countries, using a variety of deep learning models. A commonality between the top performing models was incorporating spatio-temporal and multi-task methods, with greater than 50% and 10% macro-F1-score improvement over purely spacial single-task models in step and instrument recognition respectively. The PitVis-2023 Challenge therefore demonstrates state-of-the-art computer vision models in minimally invasive surgery are transferable to a new dataset, with surgery specific techniques used to enhance performance, progressing the field further. Benchmark results are provided in the paper, and the dataset is publicly available at: https://***/10.5522/04/26531686. Copyright © 2024, The Authors. All rights reserved.

关键词： Endoscopy

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Explainable AI: Definition and attributes of a good explanation for health AI

arXiv

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arXiv 2024年

作者： Kyrimi, Evangelia McLachlan, Scott Wohlgemut, Jared M. Perkins, Zane B. Lagnado, David A. Marsh, William Gimson, Alexander Shafti, Ali Ercole, Ari Banerjee, Amitava Glocker, Ben Schafer, Burkhard Gatsonis, Constantine Grosan, Crina Sent, Danielle Berman, David S. Glass, David O'Regan, Declan P. Letsios, Dimitrios Morrissey, Dylan Pisirir, Erhan Leofante, Francesco Soyel, Hamit Williamson, Jon Grieman, Keri Dube, Kudakwashe Mardsen, Max Nagendran, Myura Tai, Nigel Kostopoulou, Olga Jones, Owain Curzon, Paul Stoner, Rebecca S. Tandle, Sankalp Joshi, Shalmali Mossadegh, Somayyeh Buijsman, Stefan Miller, Tim Madai, Vince Istvan School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom School of Nursing Midwifery and Palliative Care King's College London London United Kingdom Centre for Trauma Sciences Blizard Institute Queen Mary University of London London United Kingdom Royal London Hospital Barts Health NHS Trust London United Kingdom Department of Experiment Psychology University College London London United Kingdom Cambridge Liver Unit Addenbrooke's Hospital Cambridge University Hospitals Hills Road Box 210 Cambridge United Kingdom University of Cambridge United Kingdom Cambridge Consultants Ltd. United Kingdom Division of Anaesthesia Cambridge Centre for AI in Medicine University of Cambridge Cambridge United Kingdom Magdelene College University of Cambridge United Kingdom Institute of Health Informatics University College London London United Kingdom Department of Computing Imperial College London London United Kingdom SCRIPT Centre for IT and IP Law School of Law University of Edinburgh United Kingdom Center for Statistical Sciences School of Public Health Brown University Providence United States Research Group Artificial Intelligence HU University of Applied Sciences Utrecht Netherlands Jheronimus Academy of Data Science Tilburg University Eindhoven University of Technology s-Hertogenbosch Netherlands Centre for Theoretical Physics Queen Mary University of London London United Kingdom School of Computing Ulster University Belfast United Kingdom MRC Laboratory of Medical Sciences Imperial College London London United Kingdom Department of Informatics King's College London United Kingdom Physiotherapy Department Barts Health NHS Trust London United Kingdom Sport and Exercise Medicine Queen Mary University of London London United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Department of Computing Imperial College London United Kingdom Departmen

Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity of these models grows, transparency and users' understanding often diminish. This suggests that accurate prediction alone is insufficient for making an AI-based solution truly useful. In the development of healthcare systems, this introduces new issues related to accountability and safety. Understanding how and why an AI system makes a recommendation may require complex explanations of its inner workings and reasoning processes. Although research on explainable AI (XAI) has significantly increased in recent years and there is high demand for XAI in medicine, defining what constitutes a good explanation remains ad hoc, and providing adequate explanations continues to be challenging. To fully realize the potential of AI, it is critical to address two fundamental questions about explanations for safety-critical AI applications, such as health-AI: (1) What is an explanation in health-AI? and (2) What are the attributes of a good explanation in health-AI? In this study, we examined published literature and gathered expert opinions through a two-round Delphi study. The research outputs include (1) a definition of what constitutes an explanation in health-AI and (2) a comprehensive list of attributes that characterize a good explanation in health-AI. © 2024, CC BY.

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Neutral point clamped inverter for enhanced grid connected PV system performance based on hexagonal space vector modulation

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Scientific Reports 2025年第1期15卷 1-21页

作者： Palanisamy, R. Vijayakumar, K. Gulbarga, Mohammad Imtiyaz Al Awadh, Mohammed Hui, Liew Tze Department of Electrical and Electronics Engineering College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chennai 603203 India Faculty of Engineering and Informatics Department of Computer Science & Engineering Ala-Too International University Bishkek Kyrgyzstan Department of Industrial Engineering College of Engineering King Khalid University P.O. Box 394 Abha 61421 Saudi Arabia Center for Engineering and Technology Innovations King Khalid University Abha 61421 Saudi Arabia Centre for Intelligent Cloud Computing (CICC) COE of Advanced Cloud Faculty of Information Science & Technology Multimedia University Jalan Ayer Keroh Lama Bukit Beruang Melaka 75450 Malaysia

The increasing global demand for renewable energy has accelerated the adoption of grid-connected photovoltaic (PV) systems. However, conventional PV inverters often rely on transformers, which add to the system’s cost, size, and power losses. Transformerless inverter topologies have emerged as a promising alternative, offering improved efficiency, compact design, and lower costs. Despite these advantages, challenges such as high total harmonic distortion (THD), common mode voltage (CMV) issues, and neutral current imbalance must be addressed to ensure reliable grid integration. This research investigates a transformerless five-level neutral point clamped (NPC) inverter for grid-connected PV applications, aiming to overcome these challenges. The study focuses on analysing THD, mitigating CMV to enhance system reliability, and optimizing output voltage levels to meet grid standards. The proposed transformerless five-level NPC inverter, incorporating a coupled inductor, is controlled using Hexagonal Space Vector Modulation (HSVM) to improve performance. Additionally, the research evaluates neutral current behavior to ensure stability and compliance with grid codes. Simulation and experimental results validate the proposed system’s effectiveness under varying operating conditions, highlighting its potential as a high-efficiency, cost-effective solution for sustainable energy integration into the grid. © The Author(s) 2025.

关键词： Capacitor voltage unbalance (CVU) Common mode voltage (CMV) Photovoltaic (PV) systems Total harmonic distortion (THD) Transformerless five-level neutral point clamped (NPCI) inverter

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Investigation of the hyperchaos and control in the fractional order financial system with profit margin

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Partial Differential Equations in Applied Mathematics 2024年 9卷

作者： Johansyah, Muhamad Deni Sambas, Aceng Qureshi, Sania Zheng, Song Abed-Elhameed, Tarek M. Vaidyanathan, Sundarapandian Sulaiman, Ibrahim Mohammed Department of Mathematics Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu 22200 Malaysia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tamansari Gobras Tasikmalaya 46196 Indonesia Department of Computer Science and Mathematics Lebanese American University Beirut 13-5053 Lebanon Department of Mathematics Near East University Mersin 99138 Turkey Department of Basic Sciences and Related Studies Mehran University of Engineering and Technology Jamshoro 72060 Pakistan School of Data Science Zhejiang University of Finance and Economics Hangzhou 310018 China Institute of Mathematics and Interdisciplinary Sciences Zhejiang University of Finance and Economics 310018 China Department of Mathematics Faculty of Science Assiut University Assiut 71516 Egypt Centre for Control Systems Vel Tech University Avadi Tamil Nadu Chennai 600062 India Institute of Strategic Industrial Decision Modelling School of Quantitative Sciences Universiti Utara Malaysia Sintok Bukit Kayu Hitam Kedah 06010 Malaysia Faculty of Education and Arts Sohar University Sohar 311 Oman

This research study proposes a novel hyperchaotic finance system with profit margin and then utilizes the Adomian Decomposition Method (ADM) to tackle the solution of the associated Caputo-derivative based fractional-order hyperchaotic finance system with profit margin. Numerical simulations and analyses, such as the evaluation of Lyapunov exponents (LE), the creation of bifurcation diagrams (BD), the complexity analysis (CA), and the 0-1 test, are used to get a full picture of the system. The results of our study demonstrate the occurrence of periodic, chaotic, and hyperchaotic dynamics in the system. Furthermore, the overall criteria for the existence and the uniqueness of the exact solutions for Caputo fractional-order models are presented. In addition, we present a control methodology for the fractional-order hyperchaotic financial system utilizing the Laplace transform and linear feedback control. Significantly, our research showcases a noteworthy correlation between the analytical results and numerical simulations, emphasizing the soundness and effectiveness of our methodology. © 2024 The Author(s)

关键词： Chaotic system Financial system Fractional order Hyperchaos

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Investigation of chaos behavior in a new two-scroll chaotic system with four unstable equilibrium points, its synchronization via four control methods and circuit simulation

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IAENG International Journal of Applied Mathematics 2020年第1期50卷 12-21页

作者： Sambas, Aceng Vaidyanathan, Sundarapandian Sudarno Mamat, Mustafa Mohamed, Mohamad Afendee Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tasikmalaya West Java46196 Indonesia Research and Development Centre Vel Tech University Avadi Chennai Tamil Nadu600062 India Faculty of Engineering Universitas Muhammadiyah Ponorogo Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak Kuala Terengganu21300 Malaysia

This paper reports the finding of a new 2-scroll chaotic system with four quadratic nonlinear terms. We also discover interesting properties of the new chaotic system such as equilibrium points, bifurcation and Lyapunov exponents. For a comparative study, we apply four different control methods for the global synchronization of the new chaotic system with itself and present a comparative analysis of the results obtained with the four control methods, viz. (A) Adaptive Control, (B) Backstepping Control, (C) Passive Control and (D) Integral Sliding Mode Control. Our results show that integral sliding mode control gives the best results for achieving synchronization of the new chaotic system with itself. An electronic circuit simulation of the new 2-scroll chaotic system is shown using MultiSIM to check the feasibility of the model. © 2020.

关键词： Chaotic systems

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