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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Sharifisoraki, Ziaaddin Amini, Marzieh Rajan, Sreeraman Carleton University School of Information Technology Ottawa Canada Carleton University System and Computer Engineering Department Ottawa Canada

ISBN: (纸本)9798350324136

Millimeter-wave radar technology is gaining popularity as a perception sensor in autonomous vehicles. This is due to its ability to detect nearby objects in adverse weather conditions, such as rain, snow, or fog, as well as its cost-effectiveness. In this paper, we explore the impact of different backbones and object detector heads on the performance of radar-based object detection algorithms. More specifically, we employ the RADDet dataset and its object detection algorithm which provides the entire Range-Azimuth-Doppler spectrum and incorporates an automatic annotation approach. We examine different backbones and object detector heads to identify optimal model combinations for autonomous driving applications. Our results show that using a YOLOv4 head integrated with a modified ResNet backbone leads to the highest mean average precision, reaching 66.3% with an intersection over union (IoU) of 0.1, and 43.6% with an IoU of 0.3. This observation will help to advance radar-based object detection, thereby enhancing safety and reliability in diverse environmental conditions. © 2024 IEEE.

关键词： mmWave Radar Object Detection ResNet VGG YOLO

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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah Al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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Blockchain-Driven Secure Data Sharing Framework for Edge Computing Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 978-997页

作者： Fuad A.M.Al-Yarimi Ramzi Salah Khaled Mohamoud Department of Computer Science King Khalid UniversityMuhayel Aseer 62529Saudi Arabia Faculty of Information Science and Technology University Kebangassan MalaysiaBangi 43600Malaysia Department of Information System King Khalid UniversityMuhayel Aseer 62529Saudi Arabia

This study examines secure and effective data sharing methods for edge computing *** methods of sharing data at the edge have issues with security,speed,and *** goal is to develop a Blockchain-based Secure Data Sharing Framework(BSDSF)capable of improving data integrity,latency,and overall network efficiency for edge-cloud computing *** proposes using blockchain technology with Byzantine Fault Tolerance(BFT)and smart contract-based validation as a new method of secure data *** has a two-tiered consensus protocol to meet the needs of edge computing,which requires instantaneous *** employs Byzantine fault tolerance to deal with errors and protect against *** contracts automate validation and consensus operations,while edge computing processes data at the attack *** validation and failure detection methods monitor network quality and dependability,while system security ensures secure communication between *** is an important step toward digital freedom and trust by protecting security and improving transaction *** framework demonstrates a reduction in transaction latency by up to 30％and an increase in throughput by 25％compared to traditional edge computing models,positioning BSDSF as a pivotal solution for fostering digital freedom and trust in edge computing environments.

关键词： Byzantine Fault Tolerance(BFT) blockchain-driven edge computing networks consensus contract data validation contract node validation contract

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Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

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computer systems Science & Engineering 2023年第5期45卷 1343-1356页

作者： Fadl Dahan Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Sciences Faculty of Computing and Information Technology AlturbahTaiz UniversityTaiz9674Yemen

Web services are provided as reusable software components in the services-oriented *** complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service(QoS)*** workflow consists of tasks where many services can be considered for each *** for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial(NP)-hard *** work focuses on the Web Service Composition(WSC)problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the *** proposed algorithm determines the optimal combination of the web services to satisfy the complex user *** also addresses the Bat Algorithm(BA)shortcomings,such as the tradeoff among exploration and exploitation searching mechanisms,local optima,and convergence *** proposed enhancement includes a developed cooperative and adaptive population initialization *** elitist mechanism is utilized to address the BA convergence *** tradeoff between exploration and exploitation is handled through a neighborhood search *** benchmark datasets are selected to evaluate the proposed bat algorithm’s *** simulation results are estimated using the average fitness value,the standard deviation of the fitness value,and an average of the execution time and compared with four bat-inspired *** is observed from the simulation results that introduced enhancement obtains significant results.

关键词： Cloud computing web service composition bat algorithm serviceoriented architecture

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Cluster-preserving sampling algorithm for large-scale graphs

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Science China(information Sciences) 2023年第1期66卷 60-76页

作者： Jianpeng ZHANG Hongchang CHEN Dingjiu YU Yulong PEI Yingjun DENG National Digital Switching System E&T Research Center Information Engineering University Network Systems Department of the Strategic Support Force School of Computer Science and Technology Eindhoven University of Technology Center for Applied Mathematics Tianjin University

Graph sampling is a very effective method to deal with scalability issues when analyzing largescale graphs. Lots of sampling algorithms have been proposed, and sampling qualities have been quantified using explicit properties(e.g., degree distribution) of the sample. However, the existing sampling techniques are inadequate for the current sampling task: sampling the clustering structure, which is a crucial property of the current networks. In this paper, using different expansion strategies, two novel top-leader sampling methods(i.e., TLS-e and TLS-i) are proposed to obtain representative samples, and they are capable of effectively preserving the clustering structure. The rationale behind them is to select top-leader nodes of most clusters into the sample and then heuristically incorporate peripheral nodes into the sample using specific expansion strategies. Extensive experiments are conducted to investigate how well sampling techniques preserve the clustering structure of graphs. Our empirical results show that the proposed sampling algorithms can preserve the population's clustering structure well and provide feasible solutions to sample the clustering structure from large-scale graphs.

关键词： graph sampling clustering structure top-leader nodes expansion strategies large-scale graphs

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Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

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computers, Materials & Continua 2024年第6期79卷 4963-4977页

作者： Iftikhar Naseer Tehreem Masood Sheeraz Akram Zulfiqar Ali Awais Ahmad Shafiq Ur Rehman Arfan Jaffar Faculty of Computer Sciences&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Information System Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Lung cancer is a leading cause of global mortality *** detection of pulmonary tumors can significantly enhance the survival rate of ***,various computer-Aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high ***,the existing method-ologies cannot obtain a high level of specificity and *** present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet *** LCSC model comprises two distinct *** first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung ***,an improved AlexNet architecture is employed to classify lung *** the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate *** suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or *** proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

关键词： Lung cancer segmentation AlexNet U-Net classification

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R3 - Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic systems

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IEEE Access 2023年 11卷 119284-119312页

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Yee, Por Lip Ku, Chin Soon Alexan, Wassim Faculty of Media Engineering and Technology Computer Science Department Cairo11835 Egypt National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia Faculty of Information Engineering and Technology Communications Department Cairo11835 Egypt New Administrative Capital Mathematics Department Cairo13507 Egypt

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm's efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age. © 2013 IEEE.

关键词： Cryptography

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Comparative Analysis of Decision Tree Algorithms Using Gini and Entropy Criteria on the Forest Covertypes Dataset 3rd

Comparative Analysis of Decision Tree Algorithms Using Gini ...

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3rd International Conference on Innovations in Computing Research, ICR 2024

作者： Mustafa, Omar M. Ahmed, Omer M. Saeed, Vaman A. Computer Science Department University of Zakho Duhok Iraq Computer Information System Department Duhok Polytechnic University Duhok Iraq Information Technology Department Duhok Polytechnic University Duhok Iraq

ISBN: (纸本)9783031655210

By applying split conditions at each node that divide the training records into subsets with output variables of the same class, decision trees are constructed recursively. The procedure commences at the root node of the decision tree and advances through the implementation of split conditions at every non-leaf node, ultimately producing subsets that are homogeneous. Nevertheless, the attainment of completely homogeneous subsets is unattainable. Consequently, the objective at every node is to determine an attribute accompanied by a split condition that reduces the commingling of class labels, thereby producing subsets that are nearly pure. This paper investigates decision tree models with the intention of determining which one is most suitable for the classification of forest cover types. Individual classifications using the Gini index and information gain were conducted on the covertype dataset, which categorizes pixels into seven distinct forest cover types according to characteristics including elevation, aspect, slope, hill shade, soil type, and more. Both classifiers were assessed in this study with respect to their accuracy. The findings of the research demonstrate that irrespective of the imbalance or balance of the dataset, the classification models indices that entropy was slightly more effective than Gini in this context. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Entropy

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Analysis of the Earth's Ionosphere Influence on the Parameters of High-Frequency Radio Signals Using the Bicharacteristics Method

Analysis of the Earth's Ionosphere Influence on the Paramete...

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2025 systems of Signals Generating and Processing in the Field of on Board Communications, SOSG 2025

作者： Kryukovsky, Andrew S. Kutuza, Boris G. Rastyagaev, Dmitry V. Institute of Information System and Engineer-Computer Technology Russian New University Moscow Russia Kotelnikov Institute of Radioengineering and Electronics Moscow Russia

ISBN: (纸本)9798331532635

The propagation of a radio signal emitted by a spacecraft through the Earth's ionosphere is considered. The influence of the ionosphere and traveling ionospheric disturbances on the propagation of a radio signal of the decimeter and meter ranges is studied. The following are calculated: deviations of rays from rectilinear propagation, changes in delay time, phase lag, and phase deviation. The total electron concentration and Faraday rotation are calculated in the presence of ionospheric inhomogeneities. The influence of the ionosphere on the absorption of a radio signal, its amplitude, and polarization is analyzed. © 2025 IEEE.

关键词： Ionosphere

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Recent ViT based models for Breast Cancer Histopathology Image Classification 14

Recent ViT based models for Breast Cancer Histopathology Ima...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Karuppasamy, ArunaDevi Oman College of Management and Technology Department of Computer Science and Management Information System Muscat Oman

ISBN: (纸本)9798350335095

Breast cancer is one of the most common type of cancer affecting women worldwide, and a leading cause of cancer-related deaths. Histopathology image analysis plays a vital role in breast cancer diagnosis. Early diagnosis and accurate classification of breast cancer histopathology images can help for effective treatment. In recent years, deep learning-based image classification methods have shown promising results in automated breast cancer diagnosis. Earlier, Convolutional Neural Network(CNN) had a huge attention in image classification tasks, and also obtained a good performances in histopathology image classification. Recently, Vision Transformer (ViT) based on self-attention mechanism has shown promising results in computer vision tasks, including image classification. In this paper, we review recent ViT-based model for breast cancer histopathology image classification. Furthermore, we summarize the results obtained from our experiments with both CNN and ViT-based models in breast cancer histopathology image classification. © 2023 IEEE.

关键词： Image classification

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