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4th IEEE International Conference on Data science and computer Application, ICDSCA 2024

作者： Sheng, Ze Wu, Fenghua Zuo, Xiangwu Li, Chao Qiao, Yuxin Lei, Hang Computer and Information Science University of Pennsylvania Philadelphia United States Integrated Circuit Science & Engineering University of Electronic Science & Technology of China Chengdu China Computer Science & Engineering Texas A&M University College Station United States Graduate School of Arts and Sciences Georgetown University WashingtonDC United States Computer Information Technology Northern Arizona University Flagstaff United States Co. Ltd Nanjing China

ISBN: (纸本)9798350368239

The security issues of large-scale software systems and frameworks have become increasingly severe with the development of technology. As complexity of software grows, vulnerabilities are becoming more challenging to detect. Although traditional machine learning methods have been applied in cybersecurity for a long time, there has been no significant breakthrough until now. With the recent rise of large language models (LLMs), a turning point seems to have arrived. The powerful code comprehension and generation capabilities of LLMs make fully automated vulnerability detection systems a possibility. This paper presents LProtector, an automated vulnerability detection system for C/C++ codebases based on GPT-4o and Retrieval-Augmented Generation (RAG). LProtector performs binary classification to identify vulnerabilities in target codebases. To evaluate its effectiveness, we conducted experiments on the Big-Vul dataset. Results show that LProtector outperforms two state-of-the-art baselines in terms of F1 score, demonstrating the potential of integrating LLMs with vulnerability detection. ©2024 IEEE.

关键词： C++ (programming language)

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Pose Control With an Input-to-state Safe Control Barrier Function for Rigid Body Motion

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2023年第1期143卷 67-75页

作者： Murao, Toshiyuki Matsumoto, Kosuke Kawai, Hiroyuki Ibuki, Tatsuya Fujita, Masayuki College of Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi Ishikawa921-8501 Japan Graduate Program in Mechanical Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi Ishikawa921-8501 Japan School of Science and Technology Meiji University 1-1-1 Higashimita Tama-ku Kawasaki Kanagawa214-8571 Japan Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

In this paper, we present a pose control method for rigid body motion via an input-to-state safe control barrier function (ISSf-CBF). The control objective is that a mobile robot converges to the desired pose with avoiding any obstacles under input disturbances. First, we derive a control error system to discuss stability via the Lyapunov method. Through the kinematic model for a rigid body, we design an ISSf-CBF for obstacle avoidance under input disturbances. Next, we present a control Lyapunov function (CLF) for the control error system. By using the ISSf-CBF and the CLF, we discuss a unified quadratic program formulation that ensures both safety and stability for pose control of rigid body motion under input disturbances. Our proposed approach, which deals with both the position and the orientation of rigid body motion, connects the safety and the stability via the ISSf-CBF and the CLF. Finally, simulation and experimental results confirm the validity of the proposed ISSf-CBF control method compared to the stabilizing one. ©c 2023 The Institute of Electrical Engineers of Japan.

关键词： Lyapunov methods

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Assessment of Competence of HR Practitioners in Exponential Organizations using Analytic Hierarchy Process (AHP) and Multilayer Perceptron (MLP) 23

Assessment of Competence of HR Practitioners in Exponential ...

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Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management

作者： Xuming Zhang Ling Peng Shilong Wang School of Management Guangdong University of Science and Technology China Graduate School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9798400716478

In the fast-changing business landscape, HR practitioners' competence in exponential organizations is crucial. Traditional assessment methods lack objectivity and comprehensiveness. To fill this gap, we combine Analytic Hierarchy Process(AHP) and Multilayer Perceptron(MLP) to evaluate HR practitioners' competence. AHP establishes a hierarchy and weightings for competence factors, while MLP utilizes subjective AHP weightings and objective data to build the evaluation model. The approach provides accurate assessments, overcoming traditional limitations. This research enhances HR management practices, improving organizational performance and competitiveness. It also has broader implications for related fields, stimulating further research in HR evaluation methodologies, and ultimately addressing the critical need for HR competence evaluation in exponential organizations.

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An efficient edge swap mechanism for enhancement of robustness in scale-free networks in healthcare systems

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International Journal of Web and Grid Services 2024年第3期20卷 360-383页

作者： Abbas, Syed Minhal Javaid, Nadeem Alrajeh, Nabil Bouk, Safdar Hussain Department of Computer Science COMSATS University Islamabad Islamabad Campus 44000 Pakistan International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Yunlin64002 Taiwan Department of Biomedical Technology College of Applied Medical Sciences King Saud University Riyadh11633 Saudi Arabia Old Dominion University 5115 Hampton Blvd. NorfolkVA23529 United States

This paper presents a sequential edge swap (SQES) mechanism to design a robust network for a healthcare system utilising energy and communication range of nodes. Two operations: sequential degree difference operation (SQDDO) and sequential angle sum operation (SQASO) are performed to enhance the robustness of network. With equivalent degrees of nodes from the network’s centre to its periphery, these operations build a robust network structure. Disaster attacks that have a substantial impact on the network are carried out using the network information. To identify a link between the malicious and disaster attacks, the Pearson coefficient is employed. SQES creates a robust network structure as a single objective optimisation solution by changing the connections of nodes based on the positive correlation of these attacks. SQES beats the current methods, according to simulation results. When compared to hill-climbing algorithm, simulated annealing, and ROSE, respectively, the robustness of SQES is improved by roughly 26%, 19% and 12%. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Disasters

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DViTPolyp: Small Polyp Detection in Colonoscopy Videos based on Deep Vision Transformer 4

DViTPolyp: Small Polyp Detection in Colonoscopy Videos based...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Ma, Ming Xia, Likun Seo, Hyunseok Katz School of Science and Health Yeshiva University Dept. of Graduate Computer Science and Engineering New York United States College of Information Engineering Capital Normal University Beijing China Biomedical Research Institute Korea Institute of Science and Technology Seoul Korea Republic of

ISBN: (纸本)9798350395914

Early detection of colorectal polyps and removal play a crucial role in the prevention of colon cancer. computer-aided detection (CAD) methods can be employed to help endoscopists reduce the polyp miss-rates. Numerous automatic polyp detection methods have been explored. However, it is still challenging to automatically detect colon polyps in small size in colonoscopy videos. This paper presents a method termed DViTPolyp for detecting small colorectal polyp in colonoscopy videos. The proposed method leverages the power of the deep vision transformer as the detection head in the network to aggregate rich global features, and uses the re-attention mechanism to regenerate attention maps to capture the features from the backbone model and DViT block. Also, we propose to use a power regularized Intersection Over Union (IoU) as the loss function to further enhance the accuracy of detection. Experiments are conducted on a mix of several public polyp datasets. Comparative results show that our proposed method has a better performance than other methods. © 2024 IEEE.

关键词： colonoscopy videos loss function polyp detection vision transformer

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Improving Resolution of Translated Infrared Images

Improving Resolution of Translated Infrared Images

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IEEE SENSORS

作者： Michiya Kibe Takeru Inoue Junya Morioka Ryusuke Miyamoto Dept. of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan Dept. of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

With the development of generative adversarial networks (GANs), it has become possible to perform style transfers from infrared images, which often lack color and contrast information, to more familiar domain images. For sensor systems, it is crucial to ensure the performance of transference to the target domain at the resolution required to recognize detailed structures. In this study, we propose the application of a novel structural loss function that excludes the luminance component from the structural similarity index measure (SSIM) to enhance style translation accuracy and resolution. To achieve this, we conducted experiments by translating mid-wave infrared (MWIR) images to shortwave infrared (SWIR) images, which are easier for humans to interpret. The experimental results show that the introduction of cycle consistency and SSIM loss is effective for improving the performance of the modulation transfer function (MTF) and that the application of the proposed structural loss function further enhances performance.

关键词： Degradation Image resolution Target recognition Image color analysis Transfer functions Modulation Generative adversarial networks Loss measurement Sensor systems Indexes

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A Software Design Method for Creation and Utilization of Experiential Knowledge

A Software Design Method for Creation and Utilization of Exp...

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2022 IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2022

作者： Hoshino, Takayuki Yoshioka, Rentaro University of Aizu BIPROGY Inc. Technology Research & Innovation The Graduate School of Computer Science and Engineering Tokyo Japan University of Aizu The Graduate School of Computer Science and Engineering Aizu-Wakamatsu Japan

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

Until now, knowledge-related efforts in engineering, including software engineering, have aimed to automate human activities. But, unfortunately, the use of knowledge for automation leads to the black-boxing of the system, making it difficult to respond flexibly to changes and shaking the reliability, safety, and trustworthiness of computer processing results. When it is necessary to respond to change and diversity and realize a sustainable society, knowledge must be used for change, diversity, and creation for sustainability, not for automating existing mechanisms. To realize such knowledge creation and utilization, it is necessary to design a software support environment and make it available as a platform for knowledge creation. This paper will show the design and effect of a knowledge creation platform for human beings to use knowledge in their activities and evolve, deepen, continue, and maintain their activities. © 2022 IEEE.

关键词： Software design

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Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

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computers, Materials & Continua 2024年第6期79卷 4825-4844页

作者： Ahmed H.Alhadethi Ikram Smaoui Ahmed Fakhfakh Saad M.Darwish Computer Science and School of Electronics and Telecommunications University of SfaxSfax3029Tunisia LETI Laboratory University of SfaxSfax3029Tunisia Digital Research Center of Sfax Technopark of SfaxSfax3029Tunisia Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandriaEgypt

The act of transmitting photos via the Internet has become a routine and significant *** the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further *** study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous *** main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image *** paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during *** employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious ***,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been *** applications involving the transmission and sharing of images across a *** suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture *** effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of *** scheme ensures a large reduction in computational and energy requirements while minimizing image quality *** approach employs multi-scale characteristics to improve the resistance of signatures against image *** proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

关键词： Image transmission image compression text hiding Bezier curve Histogram of Oriented Gradients(HOG) LSTM image enhancement Gaussian noise rotation

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Perfomance Improvement of mpdCNN as Ensemble Learning Model on Low Resolution Image-Face Recognition System

Perfomance Improvement of mpdCNN as Ensemble Learning Model ...

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International Conference on Electronics, Materials Engineering and Nano-technology (IEMENTech)

作者： Daniel Anando Wangean Derwin Suhartono Master of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

Low resolution image-face recognition system is one of the challenging aspects of face recognition models' development. From machine learning, deep learning, and into ensemble learning are implemented to develop face recognition models. Including mpdCNN that published by Mishra in a journal article. This mpdCNN already achieved 88.6% accuracy score on SCFace dataset while published. Based on literature review, ensemble learning model can be improved by modifying parallel layers. The purpose of this research is to improve mpdCNN's performance by implementing some modifications include adding parallel layers, alternating the fusion layers, expanding the layers, and adding residual connections. Some modifications were successfully improved mpdCNN's accuracy score. By adding parallel layers and residual connections into mpdCNN's architecture, the modified mpdCNN that proposed in this research achieved 92.33% accuracy score, measured by Rank-k evaluation metric.

关键词： Measurement Deep learning Accuracy Image resolution Image recognition Face recognition Instruments Robustness Ensemble learning Systematic literature review

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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