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IEEE International Symposium on Information Theory

作者： Daniella Bar-Lev Adir Kobovich Orian Leitersdorf Eitan Yaakobi Faculty of Computer Science Technion - Israel Institute of Technology Haifa Israel Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

This paper presents a novel approach to address the constrained coding challenge of generating almost-balanced sequences. While strictly balanced sequences have been well studied in the past, the problem of designing efficient algorithms with small redundancy, preferably constant or even a single bit, for almost balanced sequences has remained unsolved. A sequence is $\varepsilon(n)$ -almost balanced if its Hamming weight is between $0.5n\pm\varepsilon(n)$ . It is known that for any algorithm with a constant number of bits, $\varepsilon(n)$ has to be in the order of $\Theta(\sqrt{n})$ , with $\mathcal{O}(n)$ average time complexity. However, prior solutions with a single redundancy bit required $\varepsilon(n)$ to be a linear shift from $n/2$ . Employing an iterative method and arithmetic coding, our emphasis lies in constructing almost balanced codes with a single redundancy bit. Notably, our method surpasses previous approaches by achieving the optimal balanced order of $\Theta(\sqrt{n})$ . Additionally, we extend our method to the non-binary case, considering q-ary almost polarity-balanced sequences for even $q$ , and almost symbol-balanced for $q=4$ . Our work marks the first asymptotically optimal solutions for almost-balanced sequences, for both, binary and non-binary alphabet.

关键词： Codes Termination of employment Symbols Encoding Iterative methods Time complexity Hamming weight

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Movement Impacts on Eyeblink Detection Using FMCW Radar 9

Movement Impacts on Eyeblink Detection Using FMCW Radar

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9th IEEE Smart World Congress, SWC 2023

作者： Zhang, Xinze Brahim, Walid Ma, Jianhua Apduhan, Bernady O. Hosei University Graduate School of Computer and Information Sciences Tokyo184-8584 Japan Kyushu Sangyo University Faculty of Science and Engineering Department of Information Science Fukuoka813-0004 Japan

ISBN: (纸本)9798350319804

Eyeblink detection is essential for assessing physiological and psychological states in various applications. Radar technology offers a promising solution for non-intrusive and reliable eyeblink detection. This ongoing work investigates the effects of movements on eyeblink detectability using FMCW radar. The proposed methodology relies on the use of Adaptive Variational Mode Decomposition algorithm (AVMD) for blink signal extraction. Extensive experiments were performed to assess the performance under challenging conditions, analyzing the influence of body, head, and mouth movements on blink detectability. An in-depth analysis of movement impacts, identification of underlying reasons, and potential mitigation strategies is presented. This research provides a comprehensive evaluation, useful for the next step of research to provide a more reliable radar-based blink detection solution. © 2023 IEEE.

关键词： AVMD body Eyeblink FMCW radar head mouth movement impact

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Preventing Cloud Network from Spamming Attacks Using Cloudflare and KNN

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computers, Materials & Continua 2023年第2期74卷 2641-2659页

作者： Muhammad Nadeem Ali Arshad Saman Riaz SyedaWajiha Zahra Muhammad Rashid Shahab S.Band Amir Mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaSlovakia

Cloud computing is one of the most attractive and cost-saving models,which provides online services to *** computing allows the user to access data directly from any *** nowadays,cloud security is one of the biggest issues that *** types of malware are wreaking havoc on the *** on the cloud server are happening from both internal and external *** paper has developed a tool to prevent the cloud server from spamming *** an attacker attempts to use different spamming techniques on a cloud server,the attacker will be intercepted through two effective techniques:Cloudflare and K-nearest neighbors(KNN)*** will block those IP addresses that the attacker will use and prevent spamming ***,the KNN classifiers will determine which area the spammer belongs *** the end of the article,various prevention techniques for securing cloud servers will be discussed,a comparison will be made with different papers,a conclusion will be drawn based on different results.

关键词： Intrusion prevention system spamming KNN classification spam cyber security botnet

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Output Tracking Control of a Nonlinear System Based on Takagi-Sugeno Fuzzy Model: Generalized Partial Eigenstructure Assignment Approach

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IEEE Access 2024年 12卷 18520-18535页

作者： Soltanian, Farzad Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2M9 Canada Shiraz University of Technology Electrical Engineering Faculty Shiraz71557-13876 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2-performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2-performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems. © 2013 IEEE.

关键词： Transient analysis

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Automatic Segmentation of Underwater Images with Shannon's Thresholding and UNet Variants

Automatic Segmentation of Underwater Images with Shannon's T...

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2023 Winter Summit on Smart Computing and Networks, WiSSCoN 2023

作者： Mohan, Ramya Abouhawwash, Mohamed Arunmozhi, Rama Rajinikanth, Venkatesan Department of Computer Science Engineering Tamil Nadu Chennai602105 India Mansoura University Faculty of Science Department of Mathematics Mansoura35516 Egypt East LansingMI48824 United States

ISBN: (纸本)9798350334050

Automatic detection of the Region of Interest (RoI) from the chosen digital image is one of the prime tasks in various domains, and this work considered the underwater images for the study. In order to extract the RoI with better accuracy, the proposed research aims to develop a scheme by integrating the image enhancement approach and the Convolutional Neural Network (CNN) segmentation. The various phases of this scheme involve;(i) Image collection and pre-processing, (ii) RoI extraction using CNN segmentation, and (iii) Comparing the segmented region with Ground-Truth (GT) and confirming the merit of the implemented technique. This work considered Shannon's Entropy and Firefly Algorithm (SE+FA) tri-level thresholding to pre-process the images. Then the necessary RoI from these images are mined using the UNet and its variants, such as UNet+, UNet++, and VGG-UNet. The experimental investigation of this scheme confirms that the VGG-UNet implemented using VGG16 as the backbone (encoder) helped achieve a better result than other schemes. This investigation considered the UFO-120 database for the assessment, and the VGG-UNet offered an RoI mining accuracy of>98%. Other UNet variants offered >96% accuracy, which confirms the merit of the proposed scheme. © 2023 IEEE.

关键词： Image enhancement

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Improving DeepFake Video Detection Performance with a Noval Deep Learning Approach 3

Improving DeepFake Video Detection Performance with a Noval ...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Fouda, Mona A. El-Shafai, Walid El-Rabaie, El-Sayed M. Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Engineering Menouf32952 Egypt Prince Sultan University Security Engineering Lab Computer Science Department Riyadh11586 Saudi Arabia

ISBN: (纸本)9798350323511

With the rise in both the quantity and sophistication of deepfake videos, the need for robust detection systems to identify potentially misleading content on social media and the internet has become paramount. However, current automated face forgery detection systems still face limitations, often demonstrating bias towards the training dataset. This research paper addresses this issue by proposing a novel approach for detecting deepfake media. We introduce a custom Visual Geometry Group (VGG16) deepfake detection method that leverages convolutional neural network architectures. To evaluate the effectiveness of our approach, we utilize the deepfake detection challenge (DFDC) dataset on Kaggle to build network models and compare the performance of our custom VGG16 method against the standard VGG16. Additionally, we investigate the impact of data augmentation techniques on the performance of Convolutional Neural Network (CNN)-based deepfake detectors, examining their effect on both VGG16 and our custom VGG16 approach using the DFDC dataset. Our results demonstrate a high level of accuracy, with precision, recall, and f1-score values of 0.983, 0.975, and 0.979, respectively, and an overall accuracy of 0.986 for deepfake detection. This study presents a promising approach to enhance the accuracy of deepfake video detection, representing a crucial step towards mitigating the potential negative impacts of deepfake technology. © 2023 IEEE.

关键词： Convolutional neural networks

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A comprehensive study on the microstructure of plasma spraying coatings after electron beam remelting 14

A comprehensive study on the microstructure of plasma sprayi...

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14th International Conference on Electron Beam Technologies, EBT 2022

作者： Wȩglowski, M.St. Śliwiński, P. Dymek, S. Kalemba-Rec, I. Kapuściński, M. Wrona, A. Kustra, K. Lukasiewicz - Institute of Welding Gliwice Poland Lukasiewicz - Institute of Non-Ferrous Metals Gliwice Poland AGH University of Science and Technology Faculty of Metals Engineering and Industrial Computer Science Krakow Poland

One of the most popular thermal spraying technology is atmospheric plasma spraying (APS). However, it should be noted, that numerous imperfections in the APS surface layers can be occurred. The porosity, microcracks as well as lamellar microstructure occurred. Moreover, the adhesion of the coating is limited. However, the reduction of porosity and other imperfections by remelting process can be eliminated. The laser or electron beams for remelting are the most popular technologies. Mainly, power of the beam and travelling speed influence on the thickness and the final properties of the remelted coatings. In the paper, the electron beam (EB) process for remelting of plasma spraying surface layers in relation to microstructure is presented. The Ni20%Cr + 30%Re APS coating on stainless steel substrate 316Ti grade by electron beam was remelted. The effect of remelting process on microstructure was presented. The light microscopy (LM) as well as scanning electron microscopy (SEM) and energy disperse spectroscopy (EDS) for microstructure analysis of APS coatings after EB remelting were used. The results show that the APS coatings subjected EB remelted becomes much denser. Moreover, the porosity was reduced and the chemical composition of the coatings after remelting became homogeneous. © Published under licence by IOP Publishing Ltd.

关键词： Remelting

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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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Decision Level Fusion Using Hybrid Classifier for Mental Disease Classification

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computers, Materials & Continua 2022年第9期72卷 5041-5058页

作者： Maqsood Ahmad Noorhaniza Wahid Rahayu A Hamid Saima Sadiq Arif Mehmood Gyu Sang Choi Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia86400 Parit RajaBatu PahatJohorMalaysia Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Information Technology The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan 38542Korea

Mental health signifies the emotional,social,and psychological well-being of a *** also affects the way of thinking,feeling,and situation handling of a *** mental health helps in working with full potential in all stages of life from childhood to adulthood therefore it is of significant importance to find out the onset of the mental disease in order to maintain balance in *** health problems are rising globally and constituting a burden on healthcare *** diagnosis can help the professionals in the treatment that may lead to complications if they remain *** machine learning models are highly prevalent for medical data analysis,disease diagnosis,and psychiatric *** research addresses the challenge of detecting six major psychological disorders,namely,Anxiety,Bipolar Disorder,Conversion Disorder,Depression,Mental Retardation and *** challenges are mined by applying decision level fusion of supervised machine learning algorithms.A dataset was collected from a clinical psychologist consisting of 1771 observations that we used for training and testing the ***,to reduce the impact of a conflicting decision,a voting scheme Shrewd Probing Prediction Model(SPPM)is introduced to get output from ensemble model of Random Forest and Gradient Boosting Machine(RF+GBM).This research provides an intuitive solution for mental disorder analysis among different target class labels or groups.A framework is proposed for determining the mental health problem of patients using observations of medical *** framework consists of an ensemble model based on RF and GBM with a novel SPPM *** proposed decision level fusion approach by combining RF+GBM with SPPM-MIN significantly improves the performance in terms of Accuracy,Precision,Recall,and F1-score with 71\%,73\%,71\%and 71\%*** framework seems suitable in the case of huge and more diverse multiclass ***,three

关键词： Mental health diagnosis machine learning depression shrewd probing diagnostic approach

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Intelligent Optimization-Based Clustering with Encryption Technique for Internet of Drones Environment

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computers, Materials & Continua 2022年第12期73卷 6617-6634页

作者： Dalia H.Elkamchouchi Jaber S.Alzahrani Hany Mahgoub Amal S.Mehanna Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computers and Information Computer Science DepartmentMenoufia UniversityEgypt Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo 11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The recent technological developments have revolutionized the functioning of Wireless Sensor Network(WSN)-based industries with the development of Internet of Things(IoT).Internet of Drones(IoD)is a division under IoT and is utilized for communication amongst *** drones are naturally mobile,it undergoes frequent topological *** alterations in the topology cause route election,stability,and scalability problems in *** is considered as an effective method to transmit the images in IoD *** current study introduces an Atom Search Optimization basedClusteringwith Encryption Technique for Secure Internet of Drones(ASOCE-SIoD)*** key objective of the presented ASOCE-SIoD technique is to group the drones into clusters and encrypt the images captured by *** presented ASOCE-SIoD technique follows ASO-based Cluster Head(CH)and cluster construction *** addition,signcryption technique is also applied to effectually encrypt the images captured by drones in IoD *** process enables the secure transmission of images to the ground *** order to validate the efficiency of the proposed ASOCE-SIoD technique,several experimental analyses were conducted and the outcomes were inspected under different *** comprehensive comparative analysis results established the superiority of the proposed ASOCE-SIoD model over recent approaches.

关键词： Internet of drones atom search algorithm clustering encryption signcryption

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