Paladyn : journal of behavioral robotics最新文献

Application of vibration compensation based on image processing in track displacement monitoring 基于图像处理的振动补偿在轨道位移监测中的应用

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0090

P. Yu, Honglin Wang

{"title":"Application of vibration compensation based on image processing in track displacement monitoring","authors":"P. Yu, Honglin Wang","doi":"10.1515/pjbr-2022-0090","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0090","url":null,"abstract":"Abstract The track state detection is of great significance to timely understand the operation state of track and find track defects and prevent operation accidents. This article initially analyzes the key technologies of track detection system and then proposes an image detection technology and image processing method for analyzing track detection at home and abroad, thus putting forward the scheme of track detection using image processing. The characteristics of onsite track images are analyzed, and a track state detection system based on track image preprocessing, image position correction, image defect comparison, and track section size measurement is designed in this article. Further in this article, a study of image linear transformation, noise filtering, defect recognition, and edge detection in track image processing is applied. Furthermore, a robust piecewise linear transformation is designed using the combination of image threshold transformation and image gray transformation. It reduces the loss of detailed information in the process of image processing. The center point of track bright band is determined by the image region segmentation method, which effectively reduces the error of image track measurement and improves the measurement accuracy.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86941030","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

IoT-Fog-enabled robotics-based robust classification of hazy and normal season agricultural images for weed detection 基于物联网雾的基于机器人的模糊和正常季节农业图像鲁棒分类，用于杂草检测

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0105

I. Kansal, Vikas Khullar, Jyoti Verma, Renu Popli, Rajeev Kumar

{"title":"IoT-Fog-enabled robotics-based robust classification of hazy and normal season agricultural images for weed detection","authors":"I. Kansal, Vikas Khullar, Jyoti Verma, Renu Popli, Rajeev Kumar","doi":"10.1515/pjbr-2022-0105","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0105","url":null,"abstract":"Abstract The mechanization of farming is currently the most pressing problem facing humanity and a burgeoning academic field. Over the last decade, there has been an explosion of Internet of Things (IoT) application growth in agriculture. Agricultural robotics is bringing about a new era of farming because they are growing more intelligent, recognizing causes of variation on the farm, consuming fewer resources, and optimizing their efficiency to more flexible jobs. The purpose of this article is to construct an IoT-Fog computing equipped robotic system for the categorization of weeds and soy plants during both the hazy season and the normal season. The used dataset in this article included four classes: soil, soybean, grass, and weeds. A two-dimensional Convolutional Neural Network (2D-CNN)-based deep learning (DL) approach was implemented for data image classification with dataset of height and width of 150 × 150 and of three channels. The overall proposed system is considered an IoT-connected robotic device that is capable of applying classification through the Internet-connected server. The reliability of the device is also enhanced as it is enabled with edge-based Fog computing. Hence, the proposed robotic system is capable of applying DL classification through IoT as well as Fog computing architecture. The analysis of the proposed system was conducted in steps including training and testing of CNN for classification, validation of normal images, validation of hazy images, application of dehazing technique, and at the end validation of dehazed images. The training and validation parameters ensure 97% accuracy in classifying weeds and crops in a hazy environment. Finally, it concludes that applying the dehazing technique before identifying soy crops in adverse weather will help achieve a higher classification score.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76949318","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: 3

Digital healthcare: A topical and futuristic review of technological and robotic revolution 数字医疗:技术和机器人革命的主题和未来回顾

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0108

Shilpa, Tarandeep Kaur, R. Garg

{"title":"Digital healthcare: A topical and futuristic review of technological and robotic revolution","authors":"Shilpa, Tarandeep Kaur, R. Garg","doi":"10.1515/pjbr-2022-0108","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0108","url":null,"abstract":"Abstract Healthcare sector has become one of the challenging sectors to handle patient records as well as to provide better treatment to patients within a limited period. Covid-19 also exposed the limitations of the healthcare system due to the lack of better services. So, the involvement of information and communication technologies (ICTs) with the healthcare sector brings radical changes at global as well as local levels such as in hospitals and dispensaries. The article enlightened a novel survey technological paradigm that helps to facilitate the digital healthcare. With the use of technologies, the healthcare sectors are becoming more digital, innovative, patient-centric, and more effective. This article explores the proposed technological developments such as real-time health monitoring, generation of electronic health records, patient health record, mhealth, robotics, as well as robot sensors that are associated with healthcare sectors. This article also highlights the role of ICTs in different healthcare-related fields such as education, hospital management, health-related research, and data management as well as lightening the delivery levels of healthcare services. The article deals with the robotic applications in the healthcare field. This article categorizes the technologies as current and futuristic technological innovations enabling healthcare-as-a-service with benefits.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80246292","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

Hybrid controller-based solar-fuel cell-integrated UPQC for enrichment of power quality 基于混合控制器的太阳能燃料电池集成UPQC，提高电能质量

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0110

Narala Chitti Sai Sarita, Sanna Suresh Reddy, P. L. Sujatha

引用次数: 0

The role of prior exposure in the likelihood of adopting the Intentional Stance toward a humanoid robot 先前暴露在对人形机器人采取意向姿态的可能性中的作用

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0103

Cecilia Roselli, Serena Marchesi, D. D. Tommaso, A. Wykowska

{"title":"The role of prior exposure in the likelihood of adopting the Intentional Stance toward a humanoid robot","authors":"Cecilia Roselli, Serena Marchesi, D. D. Tommaso, A. Wykowska","doi":"10.1515/pjbr-2022-0103","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0103","url":null,"abstract":"Abstract One of the key questions in human–robot interaction research is whether humans perceive robots as intentional agents, or rather only as mindless machines. Research has shown that, in some contexts, people do perceive robots as intentional agents. However, the role of prior exposure to robots as a factor potentially playing a role in the attribution of intentionality is still poorly understood. To this end, we asked two samples of high school students, which differed with respect to the type of education they were pursuing (scientific/technical vs. artistic) to complete the InStance Test, measuring individual tendency to attribute intentionality toward robots. Results showed that, overall, participants were more prone to attribute intentionality to robots after being exposed to a theoretical lecture about robots’ functionality and use. Moreover, participants’ scientific/technical education resulted in a higher likelihood of attribution of intentionality to robots, relative to those with artistic education. Therefore, we suggest that the type of education, as well as individually acquired knowledge, modulates the likelihood of attributing intentionality toward robots.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81495292","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

Early prediction of cardiovascular disease using artificial neural network 人工神经网络在心血管疾病早期预测中的应用

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0107

Jyotismita Talukdar, T. Singh

{"title":"Early prediction of cardiovascular disease using artificial neural network","authors":"Jyotismita Talukdar, T. Singh","doi":"10.1515/pjbr-2022-0107","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0107","url":null,"abstract":"Abstract In recent years, there has been a noticeable rise in the mortality rate, and heart disease is a significant contributor to this trend. According to the California Association for Diabetes Investigation, by 2015, cardiovascular disease would be the primary cause of death in India, where 62 billion people live. Deficiencies in the heart’s ability to pump blood to and from the rest of the body are the leading cause of cardiovascular disease. The healthcare industry is a prime example of a sector poised to greatly benefit from the availability of massive amounts of data and analytical insights. Increasingly, it will be important to extract medical data to predict and treat the high fatality rate caused by heart attacks. Every day, humanity generates terabytes worth of data. Medical errors with dire effects can be avoided only with high-quality services. Hospitals can reduce the price of expensive clinical testing by using decision support systems. Hospitals in the modern-day use hospital information systems to keep track of patient records. The health care sector generates vast amounts of data, but little of it is really put to good use. It will be important to adopt a new strategy to reduce costs and make accurate predictions about heart disease. To determine which machine learning and deep learning approaches are most useful and accurate for predicting and classifying cardiac illnesses, this article reviews the existing literature on the topic and subsequently tries to detect the most probable factors leading to heart disease. This study introduces and models an artificial neural network methodology for identifying potential cardiovascular disease risk factors. In this study, we examine and present the various full and partial correlations among risk attributes. In addition, a number of risk variables are analysed to generate a predicted list of risk features most likely to result in cardiovascular disease.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"190 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86457711","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: 3

Path reader and intelligent lane navigator by autonomous vehicle 自动驾驶汽车的路径读取器和智能车道导航仪

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0117

Amar Shukla, Ankit Verma, Hussain Falih Mahdi, T. Choudhury, T. Singh

引用次数: 0

Hybrid optimization to enhance power system reliability using GA, GWO, and PSO 利用遗传算法、GWO和粒子群算法的混合优化提高电力系统可靠性

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0119

Rachapalli Sireesha, Srinivasa Rao Coppisetty, Mallapu Vijaya Kumar

{"title":"Hybrid optimization to enhance power system reliability using GA, GWO, and PSO","authors":"Rachapalli Sireesha, Srinivasa Rao Coppisetty, Mallapu Vijaya Kumar","doi":"10.1515/pjbr-2022-0119","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0119","url":null,"abstract":"Abstract An optimization approach is described in the research study that deals with the issue of reconfiguration networks built with certain conditions of power loss reduction and reliability. Furthermore, the reconfigured networking system seeks optimization based on criteria affecting the limitations. This study optimises specific network faults subjecting resources with no supply during reconfiguration to avoid the effect and possess through active power losses. These goals were met using the mathematical method of the optimisation process. The mathematical formulation is generated first in the system development process. As a result, a comprehensive methodology using genetic algorithm, Grey Wolf optimization (GWO), and particle swarm optimization (PSO) was developed. Finally, intended methodologies were estimated. Based on the results, it is clear that the proposed hybrid GWO-PSO approach outperforms all other methods in terms of node voltage, reliability, line currents, and computational duration. Furthermore, when optimally sized distributed generations are placed in optimal locations, total loss is reduced by up to 63% and voltage profiles improve.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85932585","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

Ultra-low latency communication technology for Augmented Reality application in mobile periphery computing 增强现实在移动周边计算中的超低延迟通信技术

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0112

Bharathiraja Nagu, Thiruneelakandan Arjunan, M. Bangare, Pradeepa Karuppaiah, Gaganpreet Kaur, Mohammed Wasim Bhatt

{"title":"Ultra-low latency communication technology for Augmented Reality application in mobile periphery computing","authors":"Bharathiraja Nagu, Thiruneelakandan Arjunan, M. Bangare, Pradeepa Karuppaiah, Gaganpreet Kaur, Mohammed Wasim Bhatt","doi":"10.1515/pjbr-2022-0112","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0112","url":null,"abstract":"Abstract Improved Reliability and Low Latency Communication (IRLC) with Augmented Reality (AR) has become an emerging technology in today’s world. To minimize an accessory adaptation for Customer Equipment (CE) in AR, it may be feasible to offload the AR workload onto the onboard devices. Mobile-Edge Computation (MEC) will improve the throughput of a CE. MEC has caused enormous overhead or communication omissions on wireless media, making it difficult to choose the optimal payload proposition. The proposed system explores on-board devices that work together to achieve an AR goal. Code splitting is a Bayesian network used to examine the overall interdependence of efforts. From a longevity and endurance perspective, it is used to reduce the Probability of Supplier Failure (PSF) of an MEC-enabled AR environment. Weighed Particle Swarm Optimization (WPSO) was proposed despite the reality based on the emphasis on balancing the issue. As a result, a heuristic-based WPSO facilitates to improve the performance measures. A hybrid method could significantly increase the assertion of a predicted PSF in various network scenarios compared to the existing communication technologies. A preliminary iterative approach is suitable for AR operations and IRLC scenarios to generalize the attributes.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75530703","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: 3

Deep auto-encoder network for mechanical fault diagnosis of high-voltage circuit breaker operating mechanism 用于高压断路器操动机构机械故障诊断的深度自编码器网络

Paladyn : journal of behavioral robotics Pub Date : 2023-01-01 DOI: 10.1515/pjbr-2022-0096

Qiuping Yang, Fang Hao

{"title":"Deep auto-encoder network for mechanical fault diagnosis of high-voltage circuit breaker operating mechanism","authors":"Qiuping Yang, Fang Hao","doi":"10.1515/pjbr-2022-0096","DOIUrl":"https://doi.org/10.1515/pjbr-2022-0096","url":null,"abstract":"Abstract To improve the accuracy of the mechanical fault diagnosis of the operating mechanism and fully exploit the characteristic information in the vibration signal of the high-voltage circuit breaker, a mechanical fault diagnosis method of the operating mechanism of the high-voltage circuit breaker based on the deep self-encoding network is proposed. First, the vibration signal of the switch operating mechanism is extracted, the wavelet packet conversion is performed, and the vibration signal of each frequency band is divided into equal times. The energy of the time–frequency subplane of the vibration signal is then calculated, and the time–frequency energy distribution is used as a switch. Finally, a breaker failure diagnostic model based on the deep self-coding network is established. Pretraining and tuning and a 126 kV high-voltage switch are used to simulate different types of faults and validate the method. Experimental results show that this method can acquire sample failure data and perform failure diagnosis, and the diagnosis accuracy rate reaches 97.5%. The deep self-coding network can fully pierce deep information on the switch vibration signal.","PeriodicalId":90037,"journal":{"name":"Paladyn : journal of behavioral robotics","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76123283","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