Journal of Automation, Mobile Robotics and Intelligent Systems最新文献_第7页

Resource Optimisation in Cloud Computing: Comparative Study of Algorithms Applied to Recommendations in a Big Data Analysis Architecture 云计算中的资源优化:大数据分析架构中推荐算法的比较研究

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/28

Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, Akou Aboubakr, Youssef Charkaoui, Omary Fouzia

{"title":"Resource Optimisation in Cloud Computing: Comparative Study of Algorithms Applied to Recommendations in a Big Data Analysis Architecture","authors":"Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, Akou Aboubakr, Youssef Charkaoui, Omary Fouzia","doi":"10.14313/jamris/4-2021/28","DOIUrl":"https://doi.org/10.14313/jamris/4-2021/28","url":null,"abstract":"Recommender systems (RS) have emerged as a means of providing relevant content to users, whether in social networking, health, education, or elections. Furthermore, with the rapid development of cloud computing, Big Data, and the Internet of Things (IoT), the component of all this is that elections are controlled by open and accountable, neutral, and autonomous election management bodies. The use of technology in voting procedures can make them faster, more efficient, and less susceptible to security breaches. Technology can ensure the security of every vote, better and faster automatic counting and tallying, and much greater accuracy. The election data were combined by different websites and applications. In addition, it was interpreted using many recommendation algorithms such as Machine Learning Algorithms, Vector Representation Algorithms, Latent Factor Model Algorithms, and Neighbourhood Methods and shared with the election management bodies to provide appropriate recommendations. In this paper, we conduct a comparative study of the algorithms applied in the recommendations of Big data architectures. The results show us that the K-NN model works best with an accuracy of 96%. In addition, we provided the best recommendation system is the hybrid recommendation combined by content-based filtering and collaborative filtering uses similarities between users and items.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"112 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80673489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An AI & ML Based Detection & Identification in Remote Imagery: State-of-the-Art 基于AI和ML的远程图像检测与识别:最新进展

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/22

Hina Hashmi, R. Dwivedi, Ashok Kumar

{"title":"An AI & ML Based Detection & Identification in Remote Imagery: State-of-the-Art","authors":"Hina Hashmi, R. Dwivedi, Ashok Kumar","doi":"10.14313/jamris/4-2021/22","DOIUrl":"https://doi.org/10.14313/jamris/4-2021/22","url":null,"abstract":"Remote Imagery and the allied processing have been a matter of curiosity among researchers for a long, and have achieved various fruitful milestones in various facets. From the near past, due to the entrance and buzz of AI & ML based computing, remotely sensed imagery & allied processing technology are growing rapidly and continuously expanding towards multiple important services- like land surveying, traffic surveillance, and various earth science disciplines. As Artificial intelligence has become the charm of researchers, machine learning and deep learning have been proven as the most commonly used and highly effective techniques for object detection. AI & ML based object segmentation &detection makes this area hot and fond to the researchers again with the opportunities of enhanced accuracy in the same. A vast literature is available from a long past till now related to the development of various techniques proposed in this area. In this paper, we have explored the major techniques of image processing for object detection and identification from remote imagery, including the current research directions and future directives. This literature survey is basically focused on analyzing and summarizing the past and recent work done in this field through a chronological sequence of research done for object detection and identification in remotely sensed imagery.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89433397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Smart Sorting Machine Using Artificial Intelligence for Chili Fertigation Industries 基于人工智能的辣椒工业智能分选机的研制

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/26

M. F. Abdul Aziz, W. B. Daud, M. N. Sukhaimie, T. A. Izzuddin, M. A. Norasikin, A. Rasid, N. Bazilah

{"title":"Development of Smart Sorting Machine Using Artificial Intelligence for Chili Fertigation Industries","authors":"M. F. Abdul Aziz, W. B. Daud, M. N. Sukhaimie, T. A. Izzuddin, M. A. Norasikin, A. Rasid, N. Bazilah","doi":"10.14313/jamris/4-2021/26","DOIUrl":"https://doi.org/10.14313/jamris/4-2021/26","url":null,"abstract":"This paper presents an automation process is a need in the agricultural industry specifically chili crops, that implemented image processing techniques and classification of chili crops usually based on their color, shape, and texture. The goal of this study was to develop a portable sorting machine that will be able to segregate chili based on their color by using Artificial Neural Network (ANN) and to analyze the performance by using the Plot Confusion method. A sample of ten green chili images and ten red chili images was trained by using Learning Algorithm in MATLAB program that included a feature extraction process and tested by comparing the performance with a larger dataset, which are 40 samples of chili images. The trained network from 20 samples produced an overall accuracy of 80 percent and above, while the trained network from 40 samples produced an overall accuracy of 85 percent. These results indicate the importance of further study as the design of the smart sorting machine was general enough to be used in the agricultural industry that requires a high volume of chili crops and with other differentiating features to be processed at the same time. Improvements can be made to the sorting system but will come at a higher price.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82354755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simple and Flexible Way to Integrate Heterogeneous Information Systems and Their Services into the World Data System 将异构信息系统及其服务集成到世界数据系统中的简单而灵活的方法

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/29

Grzegorz Nowakowski, S. Telenyk, K. Yefremov, V. Khmeliuk

引用次数: 0

Trajectory Planning for Narrow Environments That Require Changes of Driving Directions 需要改变行驶方向的狭窄环境的轨迹规划

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/23

Joerg Roth

引用次数: 0

Experimental Research of Veles Planetary Rover Performing Simple Construction Tasks Veles行星漫游者执行简单构造任务的实验研究

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/24

M. Trojnacki, Przemysław Brzęczkowski, Dominik Kleszczyński

引用次数: 0

The Identification Method of the Sources of Radiated Electromagnetic Disturbances on the Basis of Measurements in the Near-Field Zone 基于近场测量的辐射电磁干扰源识别方法

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-09-28 DOI: 10.14313/jamris/4-2021/27

Krzysztof Trzcinka

引用次数: 0

Robust H∞ Fuzzy Approach Design Via Takagi-Sugeno Descriptor Model. Application for 2-DOF Serial Manipulator Tracking Control 基于Takagi-Sugeno描述子模型的稳健H∞模糊方法设计。二自由度串行机械手跟踪控制的应用

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-08-01 DOI: 10.14313/jamris/3-2022/21

Van Anh Nguyen Thi, Duc Binh Pham, D. H. Nguyen, T. Nguyen

引用次数: 0

Design of a Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control 基于遗传模型参考自适应控制的线性二次型调节器设计

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-08-01 DOI: 10.14313/jamris/3-2022/26

A. Abdullah, A. Mahmood, Mohammad A. Thanoon

{"title":"Design of a Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control","authors":"A. Abdullah, A. Mahmood, Mohammad A. Thanoon","doi":"10.14313/jamris/3-2022/26","DOIUrl":"https://doi.org/10.14313/jamris/3-2022/26","url":null,"abstract":"Abstract The conventional control system is a controller that controls or regulates the dynamics of any other process. From time to time, a conventional control system may not behave appropriately online; this is because of many factors like a variation in the dynamics of the process itself, unexpected changes in the environment, or even undefined parameters of the system model. To overcome this problem, we have designed and implemented an adaptive controller. This paper discusses the design of a controller for a ball and beam system with Genetic Model Reference Adaptive Control (GMRAC) for an adaptive mechanism with the MIT rule. Parameter adjustment (selection) should occur using optimization methods to obtain an optimal performance, so the genetic algorithm (GA) will be used as an optimization method to obtain the optimum values for these parameters. The Linear Quadratic Regulator (LQR) controller will be used as it is one of the most popular controllers. The performance of the proposed controller with the ball and beam system will be carried out with MATLAB Simulink in order to evaluate its effectiveness. The results show satisfactory performance where the position of the ball tracks the desired model reference.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"16 1","pages":"75 - 81"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76038688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated and Deep Learning–Based Social Surveillance System: a Novel Approach 基于集成和深度学习的社会监控系统:一种新方法

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2022-08-01 DOI: 10.14313/jamris/3-2022/22

R. Litoriya, Dev Ramchandani, Dhruvansh Moyal, Dhruv Bothra

{"title":"Integrated and Deep Learning–Based Social Surveillance System: a Novel Approach","authors":"R. Litoriya, Dev Ramchandani, Dhruvansh Moyal, Dhruv Bothra","doi":"10.14313/jamris/3-2022/22","DOIUrl":"https://doi.org/10.14313/jamris/3-2022/22","url":null,"abstract":"Abstract In industry and research, big data applications are gaining a lot of traction and space. Surveillance videos contribute significantly to big unlabelled data. The aim of visual surveillance is to understand and determine object behavior. It includes static and moving object detection, as well as video tracking to comprehend scene events. Object detection algorithms may be used to identify items in any video scene. Any video surveillance system faces a significant challenge in detecting moving objects and differentiating between objects with same shapes or features. The primary goal of this work is to provide an integrated framework for quick overview of video analysis utilizing deep learning algorithms to detect suspicious activity. In greater applications, the detection method is utilized to determine the region where items are available and the form of objects in each frame. This video analysis also aids in the attainment of security. Security may be characterized in a variety of ways, such as identifying theft or violation of covid protocols. The obtained results are encouraging and superior to existing solutions with 97% accuracy.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"106 1","pages":"30 - 39"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76067793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1