Computer Systems Science and Engineering最新文献_第8页

Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests 加速寿命试验自适应多相关状态采样方案设计

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.036179

P. Charongrattanasakul, Wimonmas Bamrungsetthapong, P. Kumam

引用次数: 0

Computing of LQR Technique for Nonlinear System Using Local Approximation 非线性系统LQR技术的局部逼近计算

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.035575

A. Shahzad, A. Altalbe

引用次数: 0

Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents 基于连接智能体强化学习的多智能体动态区域覆盖

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.031116

Fatih Aydemir, Aydın Çetin

{"title":"Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents","authors":"Fatih Aydemir, Aydın Çetin","doi":"10.32604/csse.2023.031116","DOIUrl":"https://doi.org/10.32604/csse.2023.031116","url":null,"abstract":"Dynamic area coverage with small unmanned aerial vehicle (UAV) systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process. Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved. In this paper, we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems. The proposed decentralized decision-making dynamic area coverage (DDMDAC) method utilizes reinforcement learning (RL) where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment. Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents. The connectivity provides a consensus for the decision-making process, while each agent takes decisions. At each step, agents acquire all reachable agents’ states, determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area, respectively. The method was tested in a multi-agent actor-critic simulation platform. In the study, it has been considered that each UAV has a certain communication distance as in real applications. The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"17 1","pages":"215-230"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78975169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People 马鹿优化视障人士人工智能图像字幕系统

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.035529

A. Hilal, Fadwa M. Alrowais, F. Al-Wesabi, Radwa Marzouk

引用次数: 1

A Novel Soft Clustering Method for Detection of Exudates 一种新的渗出液软聚类检测方法

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.034901

K. Wisaeng

引用次数: 1

EfficientNetV2 Model for Plant Disease Classification and Pest Recognition 植物病害分类与害虫识别的高效netv2模型

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.032231

R. Devi, V. R. Vijayakumar, P. Sivakumar

引用次数: 0

3D Model Encryption Algorithm by Parallel Bidirectional Diffusion and 1D Map with Sin and Logistic Coupling 基于并行双向扩散和一维映射的正弦与Logistic耦合的三维模型加密算法

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.040729

Yongsheng Hu

{"title":"3D Model Encryption Algorithm by Parallel Bidirectional Diffusion and 1D Map with Sin and Logistic Coupling","authors":"Yongsheng Hu","doi":"10.32604/csse.2023.040729","DOIUrl":"https://doi.org/10.32604/csse.2023.040729","url":null,"abstract":": 3D models are essential in virtual reality, game development, architecture design, engineering drawing, medicine, and more. Compared to digital images, 3D models can provide more realistic visual effects. In recent years, significant progress has been made in the field of digital image encryption, and researchers have developed new algorithms that are more secure and efficient. However, there needs to be more research on 3D model encryption. This paper proposes a new 3D model encryption algorithm, called the 1D map with sin and logistic coupling (1D-MWSLC), because existing digital image encryption algorithms cannot be directly applied to 3D models. Firstly, this paper introduce 1D-MWSLC, which has a wider range of parameters compared to traditional 1D chaotic systems. When the parameter exceeds a specific range, the chaotic phenomenon does not weaken. Additionally, 1D-MWSLC has two control parameters, which increases the cryptosystem’s parameter space. Next, 1D-MWSLC generates keystreams for confusion and diffusion. In the confusion stage, this paper use random confusion, and the keystream generates an index matrix that confuses the integer and decimal parts of the 3D model simultaneously. In the diffusion stage, this paper use parallel bidirectional diffusion to simultaneously diffuse the integer parts of the three coordinates of the 3D model. Finally, this paper verify the proposed algorithm through statistical analysis, and experimental results demonstrate that the proposed 3D model encryption algorithm has robust security.","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"57 1","pages":"1819-1838"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76860242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis 基于深度学习的改进元启发式电影评论情感分析

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.034227

Abdelwahed Motwakel, Najm Alotaibi, E. Alabdulkreem, Hussain Alshahrani, M. Elfaki, Mohamed K. Nour, Radwa Marzouk, Mahmoud Othman

引用次数: 0

Implementation of Hybrid Deep Reinforcement Learning Technique for Speech Signal Classification 语音信号分类中混合深度强化学习技术的实现

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.032491

R. Gayathri, K. Rani

引用次数: 0

Intrusion Detection in 5G Cellular Network Using Machine Learning 基于机器学习的5G蜂窝网络入侵检测

IF 2.2 4区计算机科学

Computer Systems Science and Engineering Pub Date : 2023-01-01 DOI: 10.32604/csse.2023.033842

Ishtiaque Mahmood, T. Alyas, Sagheer Abbas, Tariq Shahzad, Qaiser Abbas, K. Ouahada

引用次数: 0