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5th International Conference on Soft Computing and Signal Processing, ICSCSP 2022

作者： Mohammad, Mohammad Mohammed, Aleem Senior Lecturer and Discipline Leader Software Engineering Melbourne Institute of Technology Sydney Campus Sydney Australia Computer Science Engineering Melbourne Institute of Technology Sydney Australia

ISBN: (纸本)9789811986680

Over hundreds of years, Australia is well known with bushfire incidents, especially during summer, which are widely spread across the country. This has impacted badly and contributed in shaping an environment in a significant way. Eastern Australia is now considered as top most dangerous fire-zone in the world, and its predominant eucalyptus forests have evolved to thrive on the phenomenon of bushfire. Since 1851 approximately, 800 people in Australia and billions of animals have been killed because of the bushfires. The advancement of technology and the Internet revolution has made, researchers think about how to implement fire detection system using intelligent devices to protect Australian communities from bushfires. This paper aims in proposing a solution, which detects a fire using IoT technology concept by connecting with cloud-based environment and physical hardware components such as a Raspberry Pi, sensors to detect fire/temperature, and drones to detect the bushfire. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Formation control and coordination of swarm robotic systems 21

Formation control and coordination of swarm robotic systems

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7th International Conference on engineering and MIS, ICEMIS 2021

作者： Kyzyrkanov, Abzal Ermekbayuly Atanov, Sabyrzhan Kubeisinovich Aljawarneh, Shadi Abdel Rahman Computer and Software Engineering Department L.N. Gumilyov Eurasian National University Nur-Sultan Kazakhstan L.N. Gumilyov Eurasian National University Senior Lecturer of Computer and Software Engineering Department Eurasian National University Nur-Sultan Kazakhstan Software Engineering Department Jordan University of Science and Technology Al Ramtha Irbid Jordan

ISBN: (纸本)9781450390446

In many applications, a group of autonomous mobile robots must follow a given trajectory while maintaining a certain geometric structure. If the motion in formation is properly organized, many advantages over traditional systems can be obtained: system cost can be reduced, system reliability and efficiency can be increased, while ensuring the reconfigurability and flexibility of the system's structure. Movement while maintaining a certain geometric structure has a wide range of applications. For example, in military missions, autonomous vehicles must maintain a certain structure of formation to cover terrain and conduct reconnaissance;in Smart Highway systems, the capacity of the transportation network can be greatly increased if vehicles can be grouped together at the same speed while maintaining a certain distance between them. This paper provides an algorithm for movement with a certain geometric structure of a group of autonomous mobile robots. © 2021 ACM.

关键词： Military applications

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New ARMO-based MPPT Technique to Minimize Tracking Time and Fluctuation at Output of PV Systems under Rapidly Changing Shading Conditions

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IEEE Transactions on Industrial Informatics 2024年 1-1页

作者： Seyedmahmoudian, Mehdi Soon, Tey Kok Horan, Ben Ghandhari, Alireza Mekhilef, Saad Stojcevski, Alex School of Software and Electrical Engineering Faculty of Science Engineering & Technology Swinburne University of Technology Melbourne Victoria Australia 3122 Senior Lecturer KUALA LUMPUR SELANGOR Malaysia 50603 Deakin University Faculty of Science Engineering and Built Environment 206228 Geelong Victoria Australia 3217 Kuala Lumpur Malaysia 50603 Electrical university of Malaya Kuala Lumpur Malaysia 50603 Swinburne University of Technology 3783 Hawthorn Victoria Australia 3122

The presence of bypass diodes that mitigate the negative effects of partial shading (PS) conditions produces multiple peak characteristics at the output of a photovoltaic (PV) array. Conventional maximum power point tracking (MPPT) methods develop errors under certain circumstances and detect the local maximum power point (LMPP) instead of the global maximum power point (GMPP). Several artificial intelligence (AI)-based methods have been used to modify the performance of conventional controllers. However, these methods have either not completely solved the PS problem or resulted in considerably complicated and unreliable methodologies, as well as require further development to be used in high-speed applications. This study aims to design, develop, and verify a novel rapid, reliable, and cost-effective method called adaptive radial movement optimization (ARMO) to diminish the effect of the PS problem in the MPP detection for PV systems with additional dynamic applications. The main advantages of ARMO are its improved tracking speed and significant reduction in output fluctuations during the tracking period. An extensive experimental verification has been conducted to provide a fair evaluation of the proposed method compared with conventional and recently developed methods under similar conditions while being applied to a unique PV system and DC/DC converter. IEEE

关键词： Maximum power point trackers

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Modeling and Analysis of the Kinetics of the Pyrolysis Process of Biomass with Influence Raw Material Composition on Comsol Multiphysics

Modeling and Analysis of the Kinetics of the Pyrolysis Proce...

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Technological Advancements in Computational Sciences (ICTACS), International Conference on

作者： Mamatkulova Sayyora Gulyamovna Uzakov Gulom Norboyevich Qodirov Farrux Ergash Ug'Ii Ulasheva Shaxlo Tagayevna PhD Student of the Department Alternative Energy Sources Karshi Engineering Economic Institute Karshi City Uzbekistan Professor of the Department Alternative Energy Sources Karshi Engineering Economic Institute Karshi City Uzbekistan Head of the Department of Informatics and its Teaching Methodology Shakhrisabz State Pedagogical Institute Kashkadarya Uzbekistan Senior Lecturer of the Department of Information Technology Software Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

In this article, the modeling and analysis of the kinetics of the pyrolysis process is carried out, which allows us to determine the rate of chemical reactions occurring during the decomposition of the material, as well as to identify key factors affecting the speed and efficiency of pyrolysis. The simulation was performed using Comsol Multiphysics software based on the kinetic mechanisms of the reaction of biomass of corn cob particles at a temperature of $500^{\mathrm{o}}\mathrm{C}$ . The pyrolysis process of plant biomass was analyzed at a residence time of 0 to 10 minutes. The resulting models describe temperature changes well, especially in the center of the biomass. It was found that pyrolysis of corncob biomass occurred in the temperature range from 190 to $43 2^{0}\mathrm{C}$ , at $19 0^{0}\mathrm{C}$ mass loss began, which ended at 432 $\circ \mathrm{c}$ . The kinetic parameters were calculated using the Kissinger method, and the least squares method and correlation analysis were used to calculate the kinetic constants. The study results will be useful for optimizing the conditions of the biomass pyrolysis process in the future.

关键词： Temperature sensors Temperature distribution Analytical models Correlation Biological system modeling software Biomass Kinetic theory Surface treatment Least mean squares methods

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Effect of geometric heterogeneity using an auxiliary device on the accuracy of complete arch implant scanning: An in vitro study of different clinical simulations

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Journal of Prosthetic Dentistry 2023年

作者： Abdelrehim, Aly Sulaiman, Eshamsul Sofian, Hazrina Salleh, Nosizana Mohd Graduate student Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Associate Professor Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Senior Lecturer Department of Software Engineering Faculty of Computer Science & Information Technology Universiti Malaya (UM) Kuala Lumpur Malaysia

Statement of problem: Intraoral scanning of implants supporting complete arch prostheses is limited because of the lack of geometric heterogeneity and unique reference points, creating inherent errors in the image stitching process by the scanner software program. Purpose: The purpose of this in vitro study was to evaluate the significance of geometric heterogeneity on complete arch implant scanning by using a novel auxiliary geometric device. Three different clinical simulations were tested to assess its significance. The study also assessed whether scans produced using the auxiliary device would meet a clinically acceptable threshold. Material and methods: A total of 60 scans (n=20) were performed using an intraoral scanner in 3 different clinical simulations: 2 parallel implants, 4 parallel implants, and 4 implants with a 30-degree posterior angulation of the distal implants. Scanning alternated between using the auxiliary geometric scanning device (test groups;4IP+, 4IA+, 2IP+) and not using the device (control groups;4IP-, 4IA-, 2IP-). A reference scan for each model was prepared from a high precision laboratory scanner. The scans were analyzed for accuracy in 3-dimensional deviation, interimplant distance deviation, and angular deviation by using an inspection software program. The effect of the auxiliary device was statistically analyzed by comparing scans of the same group using the paired t test for normally distributed data and the Wilcoxon Signed Rank test when data were not normally distributed (α=.05). Results: Significant effects of the auxiliary geometric device were found in 3-dimensional, distance and angular deviations (P<.05). Scans performed using the device were significantly more accurate in most implant positions (P<.05). Linear and angular deviations were clinically acceptable for all test groups. However, the deviations were above the clinically acceptable threshold for the control groups. Conclusions: Using an auxiliary geometric device sig

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Optimization of Neural Network Parameters Based on a Genetic Algorithm for Prediction of Time Series

Optimization of Neural Network Parameters Based on a Genetic...

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2020 International Multi-Conference on Industrial engineering and Modern Technologies, FarEastCon 2020

作者： Tormozov, V.S. Zolkin, A.L. Vasilenko, K.A. Pacific National University Senior Lecturer of the Software Engineering for Computers and Computer-based Systems Sub-faculty Tikhookeanskaya St. 136 Khabarovsk680054 Russia Ph.D. in Engineering Science Povolzhskiy State University of Telecommunications and Informatics Senior Lecturer of Computer and Information Sciences Department of the Povolzhskiy State University of Telecommunications and Informatics Samara443010 Russia Highest Category Lecturer Service and Design College of the Vladivostok State University of Economics and Service Service and Design College of the Vladivostok State University of Economics and Service Vladivostok690092 Russia

ISBN: (纸本)9781728169514

The article proposes a method that allows to solve the complex combinatorial problem of structural optimization of an artificial neural network with a large dimension of the space of optimization parameters using the stochastic mutation function with a constant coefficient of variation. A study on assessment of applicability of this approach to solve the problem is given. This method is proposed to be used for the forecasting of time series values. © 2020 IEEE.

关键词： Structural optimization

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Binary Particle Swarm Optimization Algorithm Based on Z-shaped Probability Transfer Function to Solve 0-1 Knapsack Problem

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2021年第2期48卷 1-9页

作者： Sun, Wei-Zhong Zhang, Min Wang, Jie-Sheng Guo, Sha-Sha Wang, Min Hao, Wen-Kuo A lecturer of School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China A postgraduate student of School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China A professor of School of International Finance and Banking University of Science and Technology Liaoning Anshan114051 China

Binary particle swarm optimization (BPSO) algorithm can map the original continuous searching space to the binary searching space by introducing a new velocity transfer function. For the 0-1 knapsack problem, a binary particle swarm optimization algorithm based on the Z-shaped probability transfer function was proposed. In order to solve the shortcomings of BPSO algorithm based on S-shaped and V-shaped probability functions that it is easy to fall into local optima and slow convergence speed, a new probability function (Z-shaped transfer function) was proposed. Then a penalty function strategy is adopted to deal with the violation of the constraint solutions. In order to verify the effectiveness of the proposed algorithm, the BPSO algorithm based on the Z-shaped transfer function with different parameters was used to solve the typical 0-1 knapsack problems, which is compared with the BPSO algorithm based on the S-shape and the V-shape transfer functions. Simulation experiment results show that the proposed Z-shaped probability transfer function improves the convergence speed and optimization accuracy of the BPSO algorithm. © 2021. All Rights Reserved.

关键词： Transfer functions

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Feature Extraction, Essential Dimension Estimation and Dimension Reduction Method of Colony Images

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2021年第2期48卷 1-13页

作者： Sun, Wei-Zhong Guo, Fu-Jun Wang, Jie-Sheng Chen, Lin Wei, Dong Du, Xin-Feng A lecturer of School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China A postgraduate student of School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China A professor of School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China An associate professor of School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan114051 China

A colony is a group of microorganisms produced by the growth and reproduction of a single microorganism species. A method of colony image feature extraction, essential dimension estimation and dimension reduction based on digital image processing technology was proposed. Firstly, based on the HSI image color moments (first, second and third order moments), nine color characteristics of the colony images were extracted. Based on gray-level co-occurrence matrix (GLCM), twenty texture features of colony images were obtained. Then, three essential dimension estimation methods, namely, the correlation dimension estimator, the maximum likelihood estimator and the packing numbers estimator, are used to estimate the dimension of the inner low-dimensional structure of the high-dimensional data of the colony images. The results of different dimension estimators were combined with six different dimension reduction techniques (PCA, LDA, MDS, ISOMAP, SNE and NCA) respectively to form 18 different data dimension reduction methods. Based on the distance criterion function, an optimal dimension reduction method for the high-dimensional feature data of the colony images corresponding to the maximum distance criterion function was obtained. © 2021. All Rights Reserved.

关键词： Feature extraction

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A novel Skin lesion prediction and classification technique: ViT-GradCAM

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Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) 2024年第9期30卷 e70040页

作者： Muhammad Shafiq Kapil Aggarwal Jagannathan Jayachandran Gayathri Srinivasan Rajasekhar Boddu Adugna Alemayehu School of Information Engineering Qujing Normal University Qujing China. Key Laboratory of Intelligent Sensor and System Design College of Information Engineering Qujing Normal University Qujing China. Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India. Department of AIML Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Hyderabad India. Lecturer in Software Engineering Wachemo University Hosaina Ethiopia.

BACKGROUND:Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinical experts in detecting and localizing skin lesions. Vision transformers (ViT) based on image segmentation classification using multiple classes provide fairly accurate detection and are gaining more popularity due to legitimate multiclass prediction capabilities. MATERIALS AND METHODS:In this research, we propose a new ViT Gradient-Weighted Class Activation Mapping (GradCAM) based architecture named ViT-GradCAM for detecting and classifying skin lesions by spreading ratio on the lesion's surface area. The proposed system is trained and validated using a HAM 10000 dataset by studying seven skin lesions. The database comprises 10 015 dermatoscopic images of varied sizes. The data preprocessing and data augmentation techniques are applied to overcome the class imbalance issues and improve the model's performance. RESULT:The proposed algorithm is based on ViT models that classify the dermatoscopic images into seven classes with an accuracy of 97.28%, precision of 98.51, recall of 95.2%, and an F1 score of 94.6, respectively. The proposed ViT-GradCAM obtains better and more accurate detection and classification than other state-of-the-art deep learning-based skin lesion detection models. The architecture of ViT-GradCAM is extensively visualized to highlight the actual pixels in essential regions associated with skin-specific pathologies. CONCLUSION:This research proposes an alternate solution to overcome the challenges of detecting and classifying skin lesions using ViTs and GradCAM, which play a significant role in detecting and classifying skin lesions accurately rather than relying solely on deep learning models.

关键词： Grad‐CAM Multi‐Headed Self attention (MSA) linear patch projection multilayer perceptron (MLP) skin lesion transformer encoder vision transformer (ViT)

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Cancellation of Spiral Wave and Spatiotemporal Chaos by Synchronization of Network

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IAENG International Journal of Applied Mathematics 2021年第4期51卷 1-8页

作者： Zou, Chengye Wang, Xingyuan Li, Haifeng Huang, Chun Lecturer of School of Mathematics and Statistics Anyang Normal University Anyang455000 China Professor of School of Information Science and Technology Dalian Maritime University Dalian116026 China Doctoral candidate of School of Software Dalian University of Technology Dalian116024 China Associate professor of College of Electrical and Electronic Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

In cardiac clinical trials, appearance of spiral waves in myocardium electrical signal is associated with the arrhythmia and tachycardia. Spatiotemporal chaos generates form breakup of spiral waves, and may lead to ventricular fibrillation. Therefore, cancellation of spiral wave and spatiotemporal chaos can avoid the emergence of arrhythmia, tachycardia and ventricular fibrillation. Kinetic behavior of cardiac myocytes is well described by Fitzhugh-Nagumo model. In this paper, Fitzhugh-Nagumo model as node for a network. Spiral waves or the spatiotemporal chaos of a nodes have been canceled by bidirectional feedback, then spiral waves or the spatiotemporal chaos of the other node is suppressed through synchronization of network. Numerical simulation results demonstrate that proposed method can eliminate spiral wave and spatiotemporal chaos of the network effectively. Compared with previous synchronization tactics such as active-passive decomposition method and Lyapunov exponent method, our proposed method has better synchronization performance within network. © 2021. All Rights Reserved.

关键词： Synchronization

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