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A New Membrane Algorithm Based on Quasi-Affine TRansformation Evolution for Optimization Problems 1

15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Wang, Xiaopeng Snášel, Václav Mirjalili, Seyedali Chu, Shu-Chuan Shehadeh, Hisham A. Bai, Zhonghai Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava70800 Czech Republic Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Brisbane4006 Australia College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Faculty of Computer Science and Informatics Amman Arab University Amman11953 Jordan

ISBN: (数字)9789819700684

ISBN: (纸本)9789819700677

This paper develops a new meta-heuristic algorithm, called Membrane Algorithm based on Quasi-Affine TRansformation Evolution (MA-QUATRE). The proposed algorithm combines the principles of QUATRE, the one-level membrane structure, and the rules of membrane systems. The different operations of QUATRE are for each inner elementary membrane and outer skin membrane, and the transformation/communication is like rules in membrane systems. For the effectiveness of MA-QUATRE, it is first evaluated on the CEC2022 benchmark and compared with five QUATRE-related algorithms. Further, the proposed algorithm is used to solve two engineering design problems (tension/compression spring and pressure vessel design) and compared with the original QUATRE and six state-of-the-art algorithms. Finally, experimental results show that the proposed MA-QUATRE is a competitive algorithm for optimization problems. The source codes of this algorithm can be found in https://***/matlabcentral/fileexchange/134372-ma-quatre and https://***/wangxper/***. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Membranes

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CRISP - DM Process in Smart Building Management 11

CRISP - DM Process in Smart Building Management

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11th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Dursun, Mahir Sabyrzhan, Moldir Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey Graduate School of Informatics Gazi University Department of Computer Science Ankara Turkey

ISBN: (纸本)9798350362541

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM). © 2024 IEEE.

关键词： Information management

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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DO DEEP NEURAL NETWORKS UTILIZE THE WEIGHT SPACE EFFICIENTLY?

arXiv

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arXiv 2024年

作者： Koyun, Onur Can Töreyin, Behçet Ugur Department of Computer Engineering Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Department of Artificial Intelligence and Data Engineering Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey

Deep learning models like Transformers and Convolutional Neural Networks (CNNs) have revolutionized various domains, but their parameter-intensive nature hampers deployment in resource-constrained settings. In this paper, we introduce a novel concept utilizes column space and row space of weight matrices, which allows for a substantial reduction in model parameters without compromising performance. Leveraging this paradigm, we achieve parameter-efficient deep learning models.. Our approach applies to both Bottleneck and Attention layers, effectively halving the parameters while incurring only minor performance degradation. Extensive experiments conducted on the ImageNet dataset with ViT and ResNet50 demonstrate the effectiveness of our method, showcasing competitive performance when compared to traditional models. This approach not only addresses the pressing demand for parameter efficient deep learning solutions but also holds great promise for practical deployment in real-world scenarios. © 2024, CC BY-NC-ND.

关键词： Deep neural networks

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Automobile Spare Part Classification via AI Image Processing Techniques, a Comparison Study 12

Automobile Spare Part Classification via AI Image Processing...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Lee, Boon Hoe Jasser, Muhammed Basheer Issa, Bayan Ajibade, Samuel-Soma M. Chua, Hui Na Wong, Richard T.K. Majeed, Anwar Abdul P.P. University of Aleppo Faculty of Informatics Engineering Syria Sunway University Bandar Sunway School of Engineering and Technology Selangor Darul Ehsan47500 Malaysia Istanbul Ticaret University Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350391398

Artificial intelligence (AI) and image recognition technologies are developing rapidly, creating new opportunities for process improvement in industry, especially in spare parts classification. Spare parts classification using images has not been thoroughly researched and utilized in the car repair industry, especially in Malaysia. This project seeks to create a reliable and effective system that uses AI to identify and classify spare parts from user-uploaded images precisely. The main goals are to simplify inventory management and improve the precision and speed of part identification in diverse industrial environments. In the end, an accuracy of 98.70% was achieved for spare part type classification and 89.70% for both type and car brand classification with the use of transfer learning, finetuning, and object detection techniques. © 2024 IEEE.

关键词： Inventory control

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Risk Assessment of Linkedin Profiles 8

Risk Assessment of Linkedin Profiles

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8th International Conference on computer Science and engineering, UBMK 2023

作者： Aydin, Arzum Bahtiyar, Serif Istanbul Technical University Cyber Security and Privacy Research Lab SPFLab. Faculty of Computer and Informatics Engineering Maslak Istanbul Turkey

ISBN: (纸本)9798350340815

Fake or fraudulent accounts are a significant problem in social networking that is often addressed by the users of various social networking platforms involving Linkedin. Fraudulent accounts generally try to convince people about their identity that they are authentic. Adversaries use fake profiles or they impersonate a real identity on social networks to obtain more privileges. Therefore, it is critical to understand problems regarding fraudulent profiles. In this paper, we propose new sustainable framework to assess risks about profiles in social networking platforms. The framework is implemented as a web extension and it is analyzed with ITU alumni profiles in Linkedin. The analyses results show that there are different profiles within one community in Linkedin that may be significant threat for social network users. © 2023 IEEE.

关键词： Risk assessment

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A Framework for Automated Cardiovascular Magnetic Resonance Image Quality Scoring based on EuroCMR Registry Criteria 13

A Framework for Automated Cardiovascular Magnetic Resonance ...

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13th International Conference on computer and Knowledge engineering, ICCKE 2023

作者： Nabavi, Shahabedin Moghaddam, Mohsen Ebrahimi Abin, Ahmad Ali Frangi, Alejandro F. Shahid Beheshti University Faculty of Computer Science and Engineering Tehran Iran The University of Manchester Division of Informatics Imaging and Data Sciences Schools of Computer Science and Health Sciences Manchester United Kingdom

ISBN: (纸本)9798350330151

Cardiovascular magnetic resonance (CMR) imaging is a radiation-free modality widely used for functional and structural evaluation of the cardiovascular system. Achieving an accurate diagnosis requires having good-quality images. Subjective CMR image quality assessment is a tedious, time-consuming and costly process. This paper presents an automated scoring framework for CMR image quality assessment that uses deep learning models to evaluate left ventricular coverage and CMR imaging artefacts. The quality scoring in the proposed framework is an attempt to automate some of the subjective quality control criteria of the EuroCMR registry for the short-axis cine steady-state free precession (SSFP) CMR images. The scores given by a radiologist and a cardiologist with experience in CMR imaging for the images of 50 subjects from the UK Biobank were used to validate the proposed framework. The Pearson correlation coefficient (PCC) and the Spearman rank-order correlation coefficient (SRCC) calculated for the experts' quality scores versus ones obtained from the proposed framework are 0.908 and 0.806 on average. The results show that the quality scoring by the proposed framework is highly correlated with the experts' opinions. The proposed framework can be used for post-imaging quality assessment of short-axis cine SSFP CMR images and quality control of large population studies such as the UK Biobank. © 2023 IEEE.

关键词： Quality control

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Deploying YOLOV10 for Affordable Real-Time Handgun Detection 22

Deploying YOLOV10 for Affordable Real-Time Handgun Detection

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22nd IEEE International Symposium on Intelligent Systems and informatics, SISY 2024

作者： Zigulic, Nikola Glucina, Matko Frank, Domagoj Lorencin, Ivan Sverko, Zoran Matika, Dario University of Rijeka Faculty of Engineering Rijeka Croatia Istrian University of Applied Sciences Department of Engineering Pula Croatia University North Department of Computer Science and Informatics Koprivnica Croatia Juraj Dobrila University of Pula Faculty of Informatics Pula Croatia University North Department of Electrical engineering Varaždin Croatia

ISBN: (纸本)9798350385601

The development of artificial intelligence is one of the most significant technological innovations that contributes to humanity with its characteristics and facilitates, secures, and improves everyday life. However the challenge arises when the programmer-engineer learns the algorithm of artificial intelligence to perform the proposed task, that is, the challenge lies in the issue of available hardware resources. Artificial intelligence algorithms perform many human-impossible tasks, such as detection and counting, i.e. calculating the interrelationships of individual objects, segmentation of tumors and other malignant diseases, i.e. tissues, classification of specific states of classes of a scene, and many other similar technologies. This research paper examines the possibility of implementing the You Only Look Once algorithm of the tenth generation on certain devices such as an affordable Raspberry Pi, and will discuss the advantages and disadvantages of changes in detection parameters, i.e. inferences to the applied model. In addition, a mock-up of the device will be shown, which will serve to provide timely information about criminals and suspicious persons who possess firearms in different situations, such as normal weather conditions in a populated place or in shops where petty robberies are frequent. The testing will be done using recorded videos in real-time scenarios. Finally, real-time inference or detection in real-time will be tested and the actions that Raspberry will perform will be simulated. The results indicate that the optimal model achieved a precision of 0.938, recall of 9.863, mAP50 of 0.91, and mAP50-95 of 0.739. This was achieved using an image size of 640, IOU threshold of 0.7, confidence threshold of 0.6, and training for 600 iterations with the Stochastic Gradient Descent optimizer, without augmentations, and employing the ONNX inference format. © 2024 IEEE.

关键词： Stochastic systems

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Numerical Modelling of The System of Doubly Nonlinear Diffusion Equations with Convective Transfer and Damping

Numerical Modelling of The System of Doubly Nonlinear Diffus...

引用

2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Sadullaeva, Shakhlo Azimbaevna Anarova, Shahzoda Amanbayevna Khaydarov, Abdugaffor Fayzullayeva, Zarnigor Nazirova, Dilorom Mirkhodzhaeva, Nazhiba departament Intellegent systems Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Tashkent Uzbekistan Department of Convergence of Digital Technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis National University of Uzbekistan Tashkent Uzbekistan Department of Informatics Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis NUUz Tashkent Uzbekistan

ISBN: (纸本)9798400716928

Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have properties that are absent in linear theory and therefore make them quite difficult for both analytical and numerical analysis of the solution. For this reason, great attention is paid to the research of nonlinear mathematical models, the construction of efficient numerical solution schemes and algorithms, and the creation of software using the capabilities of computer technologies. In this article, the mathematical model of the diffusion process in a two-component nonlinear medium under the influence of time-dependent convective transfer and damping is studied. The calculation scheme, algorithm, and software for nonlinear problems were developed. Based on a study of the qualitative properties of a nonlinear mathematical model of a reaction-diffusion system, computer modeling of reaction-diffusion processes was carried out. The developed computational schemes, algorithms, and software packages for solving systems of parabolic equations with double nonlinearity provide high productivity in studying the theory and processes of numerical solutions of such problems. © 2024 ACM.

关键词： Nonlinear equations

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A Mixed Reality Interface for Tactical Data Management in Geographic Information Systems 7

A Mixed Reality Interface for Tactical Data Management in Ge...

引用

7th International Conference on computer Science and engineering, UBMK 2022

作者： Keskin, Fatih Ince, Gokhan Istanbul Technical University Faculty of Computer and Informatics Engineering Istanbul Turkey Aselsan A.Ş.

ISBN: (数字)9781665470100

ISBN: (纸本)9781665470100

The requirements of security systems evolve as the complexity of risks and dangers increases in modern times. Due to the nature of security operations, the operator's stress and cognitive load increase, as the operators must strictly report events that occur in certain situations. In this paper, we present an alternative interface design for a command and control software traditionally used in regional security systems. We propose a mixed reality application that uses holograms and superimposition methods to enhance the operator's experience. The proposed interface is tested on four different security operation scenarios which are operational planning, unit tracking, surveillance, and alarm detection. According to the results of applied questionnaires such as NASA TLX, PSSUQ, and SUS, it has been observed that the created interface is more informative and more usable compared to the traditional command and control software in terms of security operations. © 2022 IEEE.

关键词： Augmented reality

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