Journal of Automation, Mobile Robotics and Intelligent Systems最新文献_第5页

EEG Signal Analysis for Monitoring Concentration of Operators 监测操作员浓度的脑电信号分析

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-21 DOI: 10.14313/2cnmqm79

Ł. Rykała

引用次数: 0

Model-Free Sliding Mode Control for a Nonlinear Teleoperation System with Actuator Dynamics 带执行器动态特性的非线性远程操纵系统的无模型滑动模式控制

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-21 DOI: 10.14313/v5snhs97

Henni Mansour Abdelwaheb, Kacimi Abderrahmane, Belaidi Aek

{"title":"Model-Free Sliding Mode Control for a Nonlinear Teleoperation System with Actuator Dynamics","authors":"Henni Mansour Abdelwaheb, Kacimi Abderrahmane, Belaidi Aek","doi":"10.14313/v5snhs97","DOIUrl":"https://doi.org/10.14313/v5snhs97","url":null,"abstract":"Teleoperation robotic systems control, which enables humans to perform activities in remote situations, has become an extremely challenging field in recent decades. In this paper, a Model Free Proportional-Derivative Sliding Mode Controller (MFPDSMC) is devoted to the synchronization problem of teleoperation systems subject to actuator dynamics, time-varying delay, model uncertainty, and input interaction forces. For the first time, the teleoperation model used in this study combines actuator dynamics and manipulator models into a single equation, which improves model accuracy and brings it closer to the actual system than in prior studies. Further, the proposed control approach, called Free, involves the simple measurement of inputs and outputs to enhance the system's performance without relying on any knowledge from the mathematical model. In addition, our strategy includes a Sliding Mode term with the MFPD term to increase system stability and attain excellent performance against external disturbances. Finally, using the Lyapunov function under specified conditions, asymptotic stability is established, and simulation results are compared and provided to demonstrate the efficacy of the proposed strategy.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"44 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138951832","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

Inverse Kinematics Model For a 18 Degrees of Freedom Robot 18 自由度机器人的逆运动学模型

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-21 DOI: 10.14313/t4yf9254

Miguel-Angel Ortega-Palacios, Amparo Dora Palomino-Merino, Fernando Reyes-Cortes

引用次数: 0

A Model of Continual and Deep Learning for Aspect Based in Sentiment Analysis 情感分析中基于方面的持续深度学习模型

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-21 DOI: 10.14313/vs1zaw06

Dionis López Ramos, Fernando J. Artigas Fuentes

{"title":"A Model of Continual and Deep Learning for Aspect Based in Sentiment Analysis","authors":"Dionis López Ramos, Fernando J. Artigas Fuentes","doi":"10.14313/vs1zaw06","DOIUrl":"https://doi.org/10.14313/vs1zaw06","url":null,"abstract":"Sentiment Analysis is a useful tool in several social and business contexts. Aspect Sentiment Classification is a subtask in Sentiment Analysis that gives information about features or aspects of people, entities, products, or services present in reviews. Different Deep Learning models have been proposed to solve Aspect Sentiment Classification focus on a specific domain such as restaurant,hotel, or laptop reviews. However, there are few proposals for creating a single model with high performance in multiple domains. The Continual Learning approach with neural networks has been used to solve aspect classification in multiple domains. However, avoid low aspect classification performance in Continual Learning is challenging. As a consequence, potential neural networkweight shifts in the learning process in different domains or datasets.In this paper, a novel Aspect Sentiment Classification approach is proposed. Our approach combines a Transformer Deep Learning technique with a Continual Learning algorithm in different domains. The input layer used is the pre‐trained model Bidirectional Encoder Representations from Transformers. The experiments show the efficacy of our proposal with 78 .","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"136 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138953307","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

People Tracking in Video Surveillance Systems Based on Artificial Intelligence 基于人工智能的视频监控系统中的人员跟踪

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-01 DOI: 10.14313/jamris-1-2023-8

Abir Nasry, Abderrahmane Ezzahout, F. Omary

引用次数: 0

Feature Selection for the Low Industrial Yield of Cane Sugar Production Based on Rule Learning Algorithms 基于规则学习算法的蔗糖生产低工业产量特征选择

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-01 DOI: 10.14313/jamris-1-2023-2

Yohan Gil Rodríguez, Raisa Socorro Llanes, Alejandro Rosete, Lisandra Bravo Ilisástigui

引用次数: 0

Real-Time Face Mask Detection in Mass Gatherings to Reduce Covid-19 Spread 在大规模集会中实时检测人脸面具，减少 Covid-19 传播

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-01 DOI: 10.14313/jamris-1-2023-7

Swapnil Soner, R. Litoriya, Ravi Khatri, Ali Asgar Hussain, Shreyas Pagrey, Sunil Kumar Kushwaha

{"title":"Real-Time Face Mask Detection in Mass Gatherings to Reduce Covid-19 Spread","authors":"Swapnil Soner, R. Litoriya, Ravi Khatri, Ali Asgar Hussain, Shreyas Pagrey, Sunil Kumar Kushwaha","doi":"10.14313/jamris-1-2023-7","DOIUrl":"https://doi.org/10.14313/jamris-1-2023-7","url":null,"abstract":"Abstract The Covid 19 (coronavirus) pandemic has become one of the most lethal health crises worldwide. This virus gets transmitted from a person by respiratory droplets when they sneeze or when they speak. According to leading and well-known scientists, wearing face masks and maintaining six feet of social distance are the most substantial protections to limit the virus’s spread. In the proposed model we have used the Convolutional Neural Network (CNN) algorithm of Deep Learning (DL) to ensure efficient real-time mask detection. We have divided the system into two parts—1. Train Face Mask Detector 2. Apply Face Mask Detector—for better understanding. This is a realtime application that is used to discover or detect the person who is wearing a mask at the proper position or not, with the help of camera detection. The system has achieved an accuracy of 99% after being trained with the dataset, which contains around 1376 images of width and height 224×224 and also gives the alarm beep message after the detection of no mask or improper mask usage in a public place.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"47 9","pages":"51 - 58"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139191999","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

Automated Anonymization of Sensitive Data on Production Unit 生产单元敏感数据的自动匿名化

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-01 DOI: 10.14313/jamris-1-2023-5

Marcin Kujawa, R. Piotrowski

引用次数: 0

Hybrid Adaptive Beamforming Approach for Antenna Array Fed Parabolic Reflector for C-Band Applications 用于 C 波段应用的天线阵列馈电抛物面反射器的混合自适应波束成形方法

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-12-01 DOI: 10.14313/jamris-1-2023-6

Sheetal Bawane, D. K. Panda

{"title":"Hybrid Adaptive Beamforming Approach for Antenna Array Fed Parabolic Reflector for C-Band Applications","authors":"Sheetal Bawane, D. K. Panda","doi":"10.14313/jamris-1-2023-6","DOIUrl":"https://doi.org/10.14313/jamris-1-2023-6","url":null,"abstract":"Abstract This paper presents the design of a parabolic reflector fed through a patch antenna array feed to enhance its directivity and radiation properties. Adaptive beam formers steer and alter an array’s beam pattern to increase signal reception and minimize interference. Weight selection is a critical difficulty in achieving low SLL and beam width. Low Side Lobe Level [SLL]and narrow beam reduce antenna radiation and reception. Adjusting the weights reduces SLL and tilts the nulls. Adaptive beam formers are successful signal processors if their array output converges to the required signal. Smart antenna weights can be determined using any window function. Half Power Beam Width and SLL could be used to explore different algorithms. Both must be low for excellent smart antenna performance. In noisy settings, ACLMS and CLMS create narrow beams and side lobes. AANGD offers more control than CLMS and ACLMS. The blend of CLMS and ACLMS is more effective at signal convergence than CLMS and AANGD. It presents an alternative to the conventionally used horn-based feed network for C-band applications such as satellite communication. Broadside radiation patterns and 4x4 circular patch antenna arrays are used in the proposed design. 1400 aperture illumination is provided by the array’s feed parabolic reflector, whose F/D ratio is 0.36. The proposed design’s efficacy is assessed using simulation analysis.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"39 5","pages":"45 - 50"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139192830","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

Automatic Detection of Brain Tumors Using Genetic Algorithms with Multiple Stages in Magnetic Resonance Images 基于多阶段遗传算法的脑肿瘤磁共振图像自动检测

Journal of Automation, Mobile Robotics and Intelligent Systems Pub Date : 2023-10-02 DOI: 10.14313/jamris/4-2022/31

Karthik Annam, Sunil Kumar G, Ashok Babu P, Narsaiah Domala

{"title":"Automatic Detection of Brain Tumors Using Genetic Algorithms with Multiple Stages in Magnetic Resonance Images","authors":"Karthik Annam, Sunil Kumar G, Ashok Babu P, Narsaiah Domala","doi":"10.14313/jamris/4-2022/31","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/31","url":null,"abstract":"Biomedicine is still working to solve the problem of detecting brain tumours, one of the biggest problems in the profession today. With improved technology or instrument, early diagnosis of brain cancers is feasible. Classifying brain tumour kinds using patent brain pictures enables automation in automated procedures. Furthermore, the suggested new method is utilised to tell the difference between brain tumours and other brain diseases. To split the tumour and other brain areas, the input picture is first pre-processed. After this, the pictures are divided into different colours and levels, and then they are run through the Gray Level Co-Occurrence and SURF extraction methods to uncover the important details in the photographs. Using genetic optimization, the retrieved characteristics are made smaller. For training and testing tumour classification, the cut-down characteristics are used using an advanced learning technique. The technique's accuracy, error, sensitivity, and specificity are all evaluated alongside the current method. The method has a 90%+ accuracy rate, with less than 2% inaccuracy for all kinds of cancers. Finally, the specificity and sensitivity of every kind are above 90% and 50% correspondingly. Using a genetic algorithm to support the approach is more efficient, since the method it uses has both higher accuracy and specificity than the other techniques.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830061","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