Pub Date : 2023-01-01DOI: 10.32604/csse.2023.036179
P. Charongrattanasakul, Wimonmas Bamrungsetthapong, P. Kumam
{"title":"Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests","authors":"P. Charongrattanasakul, Wimonmas Bamrungsetthapong, P. Kumam","doi":"10.32604/csse.2023.036179","DOIUrl":"https://doi.org/10.32604/csse.2023.036179","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"46 1","pages":"1631-1651"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75952041","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.035575
A. Shahzad, A. Altalbe
{"title":"Computing of LQR Technique for Nonlinear System Using Local Approximation","authors":"A. Shahzad, A. Altalbe","doi":"10.32604/csse.2023.035575","DOIUrl":"https://doi.org/10.32604/csse.2023.035575","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"15 1","pages":"853-871"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79148364","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.031116
Fatih Aydemir, Aydın Çetin
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.
{"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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.035529
A. Hilal, Fadwa M. Alrowais, F. Al-Wesabi, Radwa Marzouk
{"title":"Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People","authors":"A. Hilal, Fadwa M. Alrowais, F. Al-Wesabi, Radwa Marzouk","doi":"10.32604/csse.2023.035529","DOIUrl":"https://doi.org/10.32604/csse.2023.035529","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"20 1","pages":"1929-1945"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75594324","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.034901
K. Wisaeng
{"title":"A Novel Soft Clustering Method for Detection of Exudates","authors":"K. Wisaeng","doi":"10.32604/csse.2023.034901","DOIUrl":"https://doi.org/10.32604/csse.2023.034901","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"362 1","pages":"1039-1058"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76510453","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.032231
R. Devi, V. R. Vijayakumar, P. Sivakumar
{"title":"EfficientNetV2 Model for Plant Disease Classification and Pest Recognition","authors":"R. Devi, V. R. Vijayakumar, P. Sivakumar","doi":"10.32604/csse.2023.032231","DOIUrl":"https://doi.org/10.32604/csse.2023.032231","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"2 1","pages":"2249-2263"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76777169","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.040729
Yongsheng Hu
: 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.
3D模型在虚拟现实、游戏开发、建筑设计、工程制图、医学等领域都是必不可少的。与数字图像相比，3D模型可以提供更真实的视觉效果。近年来，数字图像加密领域取得了重大进展，研究人员开发出了更加安全高效的新算法。然而，在三维模型加密方面还需要更多的研究。针对现有数字图像加密算法不能直接应用于三维模型的问题，本文提出了一种新的三维模型加密算法，称为一维映射与正弦和逻辑耦合(1D map with sin and logistic coupling, 1D- mwslc)。本文首先介绍了与传统一维混沌系统相比，具有更大参数范围的1D- mwslc。当参数超过一定范围时，混沌现象不减弱。此外，1D-MWSLC具有两个控制参数，增加了密码系统的参数空间。接下来，1D-MWSLC生成用于混淆和扩散的密钥流。在混淆阶段，本文采用随机混淆，密钥流生成一个索引矩阵，同时混淆三维模型的整数部分和小数部分。在扩散阶段，本文采用平行双向扩散的方法对三维模型三个坐标的整数部分同时进行扩散。最后，通过统计分析验证了所提出的算法，实验结果表明所提出的三维模型加密算法具有鲁棒性。
{"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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.034227
Abdelwahed Motwakel, Najm Alotaibi, E. Alabdulkreem, Hussain Alshahrani, M. Elfaki, Mohamed K. Nour, Radwa Marzouk, Mahmoud Othman
{"title":"Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis","authors":"Abdelwahed Motwakel, Najm Alotaibi, E. Alabdulkreem, Hussain Alshahrani, M. Elfaki, Mohamed K. Nour, Radwa Marzouk, Mahmoud Othman","doi":"10.32604/csse.2023.034227","DOIUrl":"https://doi.org/10.32604/csse.2023.034227","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"104 1","pages":"1249-1266"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76888809","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.032491
R. Gayathri, K. Rani
{"title":"Implementation of Hybrid Deep Reinforcement Learning Technique for Speech Signal Classification","authors":"R. Gayathri, K. Rani","doi":"10.32604/csse.2023.032491","DOIUrl":"https://doi.org/10.32604/csse.2023.032491","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"8 5 1","pages":"43-56"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72858089","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}
Pub Date : 2023-01-01DOI: 10.32604/csse.2023.033842
Ishtiaque Mahmood, T. Alyas, Sagheer Abbas, Tariq Shahzad, Qaiser Abbas, K. Ouahada
{"title":"Intrusion Detection in 5G Cellular Network Using Machine Learning","authors":"Ishtiaque Mahmood, T. Alyas, Sagheer Abbas, Tariq Shahzad, Qaiser Abbas, K. Ouahada","doi":"10.32604/csse.2023.033842","DOIUrl":"https://doi.org/10.32604/csse.2023.033842","url":null,"abstract":"","PeriodicalId":50634,"journal":{"name":"Computer Systems Science and Engineering","volume":"3 1","pages":"2439-2453"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80927292","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}
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