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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Nugraha, Toha Ardi Ardiyanto, Yudhi Damarjati, Cahya Fachrie, Muhammad Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Information Technology Yogyakarta Indonesia Universitas Teknologi Yogyakarta Faculty of Science and Technology Department of Informatics Yogyakarta Indonesia

ISBN: (纸本)9781665465410

Vehicular communication allows vehicles to communicate with each other without connecting to a centralized infrastructure (i.e., base station). Vehicular communication including Vehicle-to-vehicle and vehicle-to-infrastructure communications also allows for the exchange of information between vehicles, which supports a number of applications, such as intelligent transportation systems and safety management. However, mobility management is a key aspect that has yet to be addressed properly for vehicular communication. Therefore, this paper reviews the existing mobility management and summarizes the resource allocation scheme for vehicular communication. We present a mode selection to maintain the connectivity of vehicular communication. Then, we simulate and discuss the existing mobility management scheme for vehicular communication. © 2022 IEEE.

关键词： Vehicles

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Efficient Detection of Knee Osteoporosis Using the Swin Transformer on X-Ray Images

Efficient Detection of Knee Osteoporosis Using the Swin Tran...

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2024 International Conference on Computer and Applications, ICCA 2024

作者： Sultana, Rahat Zaman, Muhammad Ivković, Nikola Cengiz, Korhan Rafaqat, Iqra Akhunzada, Adnan The University of Lahore Faculty of Computer Science Sargodha Pakistan Comsats University Islamabad Department of Computer Science Islamabad Pakistan University of Zagreb Faculty of Organization and Informatics Varaždin Croatia Biruni University Department of E&e Engineering Istanbul Turkey University of Doha for Science and Technology Department of Data and Cybersecurity Doha24449 Qatar

ISBN: (纸本)9798350367560

Knee Osteoporosis (KOP) is a skeletal disease that is caused by low bone mineral density and the degradation of bone tissue. It increases the risk of bone fractures in the knee region and is commonly seen in older people but usually ignored due to its silent nature. Osteoporosis is mostly diagnosed via X-ray images and Dual-Energy X-ray Absorptiometry (DXA) scans that can be difficult to read due to their sheer volume the subtle variations. This study aims to develop a Deep Learning (DL) utilizing Swin Transform model that can accurately recognize osteoporosis in knee X-ray images at an early stage. The dataset used for this research comprises knee X-rays labeled as either 'normal' or 'osteoporotic,' with image preprocessing including resizing to standard dimensions, converting the images into tensors, and normalizing pixel values to improve model performance. The model is trained and validated on arranged dataset, characterized by metrics such as accuracy, precision, recall or F1-score that gives an idea how well our model performs for prediction as acknowledged for its performance in image classification tasks. The results demonstrate that the Swin Transformer model has an overall accuracy of 89.38% on the data set for identifying osteoporosis features on knee X-ray images. This approach demonstrates the potential of the Swin Transformer model to serve as an effective tool for early osteoporosis diagnosis, offering improved accuracy and reliability compared to traditional convolutional neural networks (CNNs). © 2024 IEEE.

关键词： Diseases

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A Mini Review of the Literature of Fractional-Order Chaotic Systems and Its Applications in Secure Communications Schemes During the Last Three Decades (1990–2020) 6th

A Mini Review of the Literature of Fractional-Order Chaotic ...

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6th International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2022

作者： Atoussi, Mahedi Abdelghani Nail, Bachir Saadi, Slami Bettayeb, Maamar Applied Automation and Industrial Diagnostics Laboratory LAADI Faculty of Science and Technology University of Djelfa Djelfa Algeria Mechanical Engineering Materials and Structures Laboratory Faculty of Science and Technology Tissemsilt University Tissemsilt Algeria Faculty of Exact Sciences and Informatics Ziane Achour University of Djelfa Djelfa Algeria King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9783031212154

This paper deals with an inclusive review of the literature on fractional-order chaotic systems and their applications in secure communications and synchronization schemes over the last three decades from 1990 to 2020. Chaotic systems have gained more attention in the literature, which can be detected in different fields of science and engineering, such as mechanical, chemical, biological, and physics. Furthermore, the fractional-order increases the degrees of complexity in chaotic systems’ behaviour, which leads to better degrees of security. This work can help researchers by highlighting the most critical applications of the fractional-order chaotic systems that exist in the literature, which saves the trouble of searching and time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Chaotic systems

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Influence of Milling Parameters on the Characteristics of Alumina-Titania Nanocomposite Prepared by High-Energy Ball Milling 1

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5th International Conference on Advances in Manufacturing and Materials engineering, ICAMME 2022

作者： Asari, Siti Atikah Mohammad Yusoff, Mahani Masri, Mohamad Najmi Jaafar, Hidayani Razali, Mohd Hasmizam Nik, Wan Mohd Norsani Wan Faculty of Bioengineering and Technology Universiti Malaysia Kelantan Jeli Kelantan17600 Malaysia Faculty of Science and Marine Environment Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

ISBN: (数字)9789811995095

ISBN: (纸本)9789811995088

High energy ball milling (HEBM) is a simple mechanical technique used for particle size reduction and mixing different materials from bulk to nanostructured materials. It is able to produce nano-size grains of ceramic-based composite and sometimes with sufficient energy new phase can be formed through the diffusion process. The present study focuses on the effect of HEBM on the structure, microstructure, and properties of alumina—titania (Al2O3-TiO2) nanocomposite. Elemental powders of Al2O3 and TiO2 were milled in a planetary ball mill at different milling times and milling speeds, then heated to 600 °C. The composites were characterized for phase identification, structural properties, morphology, and compaction behavior. The peak broadening was significant with increasing milling time. The unstable Al2TiO5 was formed at a lower milling time for 300 rpm but diminished after heat treatment. The lowest crystallite size was obtained after 10 h milling time and with the speed of 300 rpm which originated from grain refinement due to a large amount of defects generation during milling. Increasing milling time and milling speed influenced the green density as a result of fine composite particle size and TiO2 particles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Titanium dioxide

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Color-based image processing techniques for laser range finder: a comparative study on air and water distance detection 16

Color-based image processing techniques for laser range find...

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16th International Conference on Correlation Optics, COR 2023

作者： Multajam, Rizki Ayob, Ahmad Faisal Mohamad Sanjaya, W. S. Mada Sambas, Aceng Rusyn, Volodymyr Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus21030 Malaysia Dept. of Physics Faculty of Science and Technology Universitas Islam Negeri Sunan Gunung Djati Bandung40614 Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu22200 Malaysia Dept. of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tasikmalaya46196 Indonesia Dept. of Radio Engineering and Information Security Yuriy Fedkovych Chernivtsi National University 2 Kotsjubynskyi Str. Chernivtsi58000 Ukraine

ISBN: (纸本)9781510671829

In this paper, we studied comparative distance detection using a Laser Rangefinder equipped with color detection and image processing techniques in air and water environments. The main objective of this study is to evaluate the performance and accuracy of the distance detection methods in these two mediums. Furthermore, color detection is employed in the air environment to identify objects within the captured images, followed by image processing techniques such as edge detection and contour analysis to calculate the distances between the objects and the Laser Range Finder. In the water environment, challenges arise due to the refractive properties of water, which can distort object appearances. To overcome this, we employ an underwater Laser Range Finder system, along with color detection and image processing methods adjusted for the refractive index of water. The findings show that the distance measurement in the air has a small error value of 0.63 %. Meanwhile, measuring distances in water has a high error value of 35.18 %. These results indicate that measurements in the air perform better than measurements in water. Water's scattering and refractive properties caused significant deviations and higher error values. The light intensity fluctuations had minimal impact on measurements in water but were significant in water. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Refractive index

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WiMA:Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

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Computers, Materials & Continua 2023年第5期75卷 2347-2363页

作者： Sohaib Manzoor Hira Manzoor Saddaf Rubab Muhammad Attique Khan Majed Alhaisoni Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Electrical Engineering Mirpur University of Science and Technology(MUST)Mirpur-10250(AJK)Pakistan Faculty of Electronics Telecommunications and InformaticsGdansk University of Technology80-233 GdanskPoland Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of *** of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too *** this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi *** association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput *** implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network *** performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.

关键词： Association multi-criterion SDN Wi-Fi

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Multi-talker Verbal Interaction for Humanoid Robots

Multi-talker Verbal Interaction for Humanoid Robots

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Bartlomiej Klin Ryszard Beniak Michal Podpora Arkadiusz Gardecki Joanna Rut Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Department of Computer Science Opole University of Technology Faculty of Production Engineering and Logistics Opole University of Technology

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

Working in multi-talker mode is viable under certain conditions, such as the fusion of audio and video stimuli along with smart adaptive beamforming of received audio signals. In this article, the authors verify part of the researched novel framework, which focuses on adapting to dynamic interlocutor’s location changes in the engagement zone of humanoid robots during the multi-talker conversation. After evaluating the framework, the authors confirm the necessity of a complementary and independent method of increasing the interlocutor’s signal isolation accuracy. It is necessary when video analysis performance plummets. The authors described the leading cause as insufficient performance during dynamic conversations. The video analysis cannot derive a new configuration when the interlocutor’s speech apparatus moves beyond the expected margin and the video frame rate drops.

关键词： Automation Accuracy Array signal processing Humanoid robots Oral communication Human factors

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An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments

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Computers, Materials & Continua 2023年第9期76卷 3859-3876页

作者： Weizheng Wang Xiangqi Wang Xianmin Pan Xingxing Gong Jian Liang Pradip Kumar Sharma Osama Alfarraj Wael Said College of Information Science and Engineering HunanWomen’s UniversityChangsha410138China School of Mathematics and Statistics Hunan First Normal UniversityChangsha410138China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China Department of Computing Science University of AberdeenAberdeenAB243FXUK Department of Computer Science Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazig44511Egypt

Image-denoising techniques are widely used to defend against Adversarial Examples(AEs).However,denoising alone cannot completely eliminate adversarial *** remaining perturbations tend to amplify as they propagate through deeper layers of the network,leading to ***,image denoising compromises the classification accuracy of original *** address these challenges in AE defense through image denoising,this paper proposes a novel AE detection *** proposed technique combines multiple traditional image-denoising algorithms and Convolutional Neural Network(CNN)network *** used detector model integrates the classification results of different models as the input to the detector and calculates the final output of the detector based on a machine-learning voting *** analyzing the discrepancy between predictions made by the model on original examples and denoised examples,AEs are detected *** technique reduces computational overhead without modifying the model structure or parameters,effectively avoiding the error amplification caused by *** proposed approach demonstrates excellent detection performance against mainstream AE *** results show outstanding detection performance in well-known AE attacks,including Fast Gradient Sign Method(FGSM),Basic Iteration Method(BIM),DeepFool,and Carlini&Wagner(C&W),achieving a 94%success rate in FGSM detection,while only reducing the accuracy of clean examples by 4%.

关键词： Deep neural networks adversarial example image denoising adversarial example detection machine learning adversarial attack

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A secured GA-WPC framework for scheduling the independent tasks in cloud environment

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 13003-13015页

作者： Dubey, Kalka Sharma, S.C. Kumar, Mohit Kumar, Prashant Nasr, Aida A. Cloud Computing and Wireless Sensor Lab Indian Institute of Technology Roorkee Uttarakhand Roorkee247667 India Department of Computer Science and Engineering Rajiv Gandhi Institute of Petroleum Technology Jais Uttar Pradesh Amethi229304 India Department of Information Technology Dr BR Ambedkar National Institute of Technology Punjab Jalandhar144011 India Information Technology Department Faculty of Computers and Informatics Tanta University Tanta Egypt

Cloud computing proved itself a powerful and popular platform for providing computing services. It offers on-demand services to users with highly efficient resources over the internet. With the exponential increase in the number of internet users and due to the high acceptance rate to use the cloud services in everything, the demand for cloud platforms has also increased significantly. This leads to heavy workloads on the servers, which is a difficult task to manage due to the heterogeneity and uncertainty of the resources. However, several traditional, heuristic, and evolutionary-based approaches have been proposed to solve the problem of scheduling. Existing state-of-art techniques and frameworks have solved the problem up to a limited level. Still, these solutions have not given any effective and concrete solution for the overall resource scheduling problem. Therefore, this paper tries to overcome the bottleneck of existing solutions by presenting a new framework named Genetic Algorithm Water Pressure Change (GAWPC) to solve task scheduling problems efficiently. The GAWPC framework exploited the feature of the Genetic Algorithm (GA) and Water Pressure Change optimization (WPCO) techniques to form a new hybrid mechanism. In the proposed framework, GA has been deployed to find the optimal solution for a particular population. WPCO has been used to optimize fitness function for a fast convergence rate. The computer-based simulation has demonstrated promising benefits like improved computation cost, make-span time, and load balancing when compared with the most recent existing baseline techniques using CloudSim. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Genetic algorithms

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A Deep Learning Driven Feature Based Steganalysis Approach

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Intelligent Automation & Soft Computing 2023年第8期37卷 2213-2225页

作者： Yuchen Li Baohong Ling Donghui Hu Shuli Zheng Guoan Zhang College of Computer Science and Information Engineering Hefei University of TechnologyHefei230009China College of Information Engineering Anhui Broadcasting Movie and Television CollegeHefei230011China Department of Informatics Faculty of Natural&Mathematical SciencesKing’s College LondonLondonWC2R2LSUK

The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic *** traditional ste-ganalysis detector is trained on the stego images created by a certain type of ste-ganographic algorithm,whose detection performance drops rapidly when it is applied to detect another type of steganographic *** phenomenon is called as steganographic algorithm mismatch in *** resolve this pro-blem,we propose a deep learning driven feature-based *** advanced steganalysis neural network is used to extract steganographic features,different pairs of training images embedded with steganographic algorithms can obtain diverse features of each *** a multi-classiﬁer implemented as lightgbm is used to predict the matching *** results on four types of JPEG steganographic algorithms prove that the proposed method can improve the detection accuracy in the scenario of steganographic algorithm mismatch.

关键词： Image steganalysis algorithm mismatch convolutional neural network JPEG images

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