2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)最新文献_第3页

Enhanced Energy Optimization of Structured Random Matrix Model in Industrial Automation 工业自动化中结构随机矩阵模型的增强能量优化

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151131

A. Bishnoi, Vivek V

{"title":"Enhanced Energy Optimization of Structured Random Matrix Model in Industrial Automation","authors":"A. Bishnoi, Vivek V","doi":"10.1109/ICDCECE57866.2023.10151131","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151131","url":null,"abstract":"The Structured Random Matrix (SRM) model is an increasingly popular approach to industrial automation. This model is based on the idea that the control systems of industrial machines are \"structured\" in a certain way, with certain properties that can be predicted and used to model the behavior of the system. SRM incorporates the principles of random matrix theory in order to provide an efficient, reliable, and realistic model for industrial automation. The SRM model works by taking a large set of variables, such as the type of machine, the speed of the machine, the number of required parts, and the number of different components to be used in the system. These variables are then used to generate a random matrix, which can then be analyzed to identify patterns and correlations between the different variables. This allows engineers to develop more accurate models of the system, as well as to identify potential problems and solutions. In addition to providing a more accurate model, the SRM model also allows engineers to simplify the design process by reducing the number of variables used in the system. This simplification means that fewer parts are needed in the system, which reduces the cost and complexity of the system. Furthermore, by reducing the complexity of the system, engineers can reduce the amount of time spent on maintenance and repairs, which saves money and increases efficiency.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124530737","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

The Smart Development of Short Range Communication Protocol Development in Efficient Device Discovery 高效设备发现中短距离通信协议的智能开发

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151263

Narasimhayya B E, Ravikumar Lanke

{"title":"The Smart Development of Short Range Communication Protocol Development in Efficient Device Discovery","authors":"Narasimhayya B E, Ravikumar Lanke","doi":"10.1109/ICDCECE57866.2023.10151263","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151263","url":null,"abstract":"The development of short-range communication protocols has been essential for efficient device discovery. Short-range communication allows two devices to communicate over short distances, typically up to 10 meters, using low-power radio frequencies. This type of communication is used extensively in applications such as Wi-Fi, Bluetooth, and Zigbee. Short-range communication protocols allow devices to discover each other without the need for a central server or intermediary. This is important for applications such as home automation, where it is necessary for various devices to be able to find each other and communicate. In order for efficient device discovery, short-range communication protocols must be reliable and secure. Reliable protocols are necessary to ensure that devices can find each other, while secure protocols are necessary to ensure that only authorized devices can access one another. Protocols such as Bluetooth, Wi-Fi, and Zigbee have been designed to be reliable and secure. The development of short-range communication protocols can be improved by using predictive algorithms. Predictive algorithms allow devices to automatically detect and respond to changes in the network environment. This enables devices to more efficiently discover each other and establish connections.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128059863","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

The Quality Evaluation of College Students’ Innovation and Entrepreneurship Education based on Grey Correlation Algorithm 基于灰色关联算法的大学生创新创业教育质量评价

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151251

Yanyu Xu

{"title":"The Quality Evaluation of College Students’ Innovation and Entrepreneurship Education based on Grey Correlation Algorithm","authors":"Yanyu Xu","doi":"10.1109/ICDCECE57866.2023.10151251","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151251","url":null,"abstract":"In today's fast-paced economy, innovation and entrepreneurship education are becoming increasingly important. As a result, colleges and universities have begun to provide courses and programs focused on these skills. However, assessing the quality of such education to ensure that students obtain the best learning experience is crucial. The grey system theory provides a useful framework for evaluating the quality of innovation and entrepreneurship education. This theory allows the analysis of complex systems with limited information, making it an ideal choice for evaluating educational plans. The evaluation process should consider several factors, including curriculum design, teaching methods, student engagement, and results. In addition, feedback from students and industry professionals can provide valuable insights into the effectiveness of the plan. Overall, comprehensive evaluation based on grey system theory can help universities improve their innovation and entrepreneurship education plans. By identifying areas for improvement, institutions can better provide students with the skills they need to succeed in today's competitive job market.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128084845","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

Rainfall Prediction using Ground Based Cloud Images 基于地面云图的降雨预测

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151110

Geeta Ambilduke, Hemanth Raj Dugyala, Atluri Venkat Srikar Chowdary, Garimireddy Siva Prakash Reddy, Vudatha Sri Santosh Narayan

引用次数: 0

Smart EV Charging to Mitigate Range Anxiety in VANET Backbone Guided by Named Data Networking and Block-Chain 基于命名数据网络和区块链的智能充电缓解VANET主干网里程焦虑

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151066

Vetri Vendan, Anamika Chaudhary

{"title":"Smart EV Charging to Mitigate Range Anxiety in VANET Backbone Guided by Named Data Networking and Block-Chain","authors":"Vetri Vendan, Anamika Chaudhary","doi":"10.1109/ICDCECE57866.2023.10151066","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151066","url":null,"abstract":"A interesting area of research for future connected car application is the development of an effective charging management system for on-the-go EVs, which is especially important given the inherent unpredictability in EV mobility. The main technological hurdles here are the necessity for intelligent decision making when choosing a CS and the related communication infrastructure for exchanging data between the grid and mobile EVs. Switching to electric vehicles has the potential to reduce pollution, vehicle maintenance expenses, and increasing gas prices (EVs). The range anxiety issue is a significant impediment to the rapid adoption of EV. Range anxiety can be alleviated by guaranteeing that a charging point will be found within the vehicle’s driving range, subject to other constraints such as waiting time, reliability, cost, and so on. In this research, we suggest building a P2P infrastructure on top of a VANET so that users may trade power with one another in a secure and reliable manner. Although the labour itself is decentralised, secure, and reliable, the associated financial transactions are not. The proposed framework for exchanging electric charge is based on the intersection of three concepts from the realm of automotive social networks: data connectivity, the bitcoin, and the anxiety of having insufficient battery power. We address reliability using an established collaborative paradigm rooted in the field of automotive social networks. Organizational verification previous to trading and encrypted parameter exchange provide safety. With the help of named data networking, reliable charging points may be located using a set of criteria. The simulation results demonstrate that the proposed technique decreases the amount of time it takes to complete an energy transaction by 17%, boosts coverage for picking charging providers by 13%, and decreases the amount of erroneous provider filtering by 18%.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132014787","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

Energy Optimized Route Selection in WSNs for Smart IoT Applications 面向智能物联网应用的wsn能量优化路由选择

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150824

Poongodi T, Rahul Kumar Sharma

{"title":"Energy Optimized Route Selection in WSNs for Smart IoT Applications","authors":"Poongodi T, Rahul Kumar Sharma","doi":"10.1109/ICDCECE57866.2023.10150824","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150824","url":null,"abstract":"Interest in the IoT and smart cities has been growing as people learn about its potential applications in fields as diverse as healthcare, remote monitoring, and transportation. In these Internet of Things (IoT)-based systems, wireless networked sensors (WSNs) gather data critical to the operation of smart surroundings. IoT-enabled WSNs face challenges such high latency, low bandwidth, and short network lifespan due to the copious amounts of data generated by a wide variety of sensors. This study presents a deep reinforcement learning-based efficient routing method for IoT-enabled WSNs to combat latency as well as electricity consumption (DRL). The proposed strategy separates the network into unequal cluster according to the present data transmission existing in the sensors, hence preventing the network from collapsing prematurely. Extensive testing has been performed in ns3 using the recommended strategy. The results of the experiments are contrasted to the state-of-the-art methodologies to demonstrate that the proposed method is effective in the areas in received packets, connectivity latency, clean energy, and the amount of living nodes within a network.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132035953","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

The Smart Development of Human Thinking Prediction Using Complex Fuzzy Systems 利用复杂模糊系统进行人类思维预测的智能开发

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151005

Devi Kanniga, A. S

{"title":"The Smart Development of Human Thinking Prediction Using Complex Fuzzy Systems","authors":"Devi Kanniga, A. S","doi":"10.1109/ICDCECE57866.2023.10151005","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151005","url":null,"abstract":"The use of complex fuzzy systems to predict human thinking is an area of active research. These systems are based on fuzzy logic, which is an approach to computing based on approximation and imprecision. Fuzzy logic has been used in a variety of areas, such as control systems, image processing, decision support systems, and even robotics. The idea behind fuzzy logic is to use a combination of fuzzy rules, fuzzy sets, and fuzzy inference to approximate the decisions that humans make in complex situations. This means that the system can take into account the uncertainty of the situation and make a decision based on available data. The system can also be trained to recognize patterns in the data and make predictions about future decisions. In order to predict human thinking, a complex fuzzy system needs to be able to take into account a variety of factors, such as situational context, emotions, and values. For example, if a person is deciding whether to buy a car, the system would need to consider factors such as price, reliability, and environmental impact. The system would also need to consider the person's preferences, such as their preferred color or style.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130100121","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

The Optimization Algorithm for the Cultivation of Medical Literacy in the Era of Smart Media 智能媒体时代医学素养培养的优化算法

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150740

Ying Huang

{"title":"The Optimization Algorithm for the Cultivation of Medical Literacy in the Era of Smart Media","authors":"Ying Huang","doi":"10.1109/ICDCECE57866.2023.10150740","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150740","url":null,"abstract":"In the era of intelligent media, society has undergone great development. For example, with the continuous innovation of modern communication technology, the role of individuals has changed, and at the same time, a series of social issues and conflicts have also been triggered. Schools are the main position for talent cultivation, and medical universities are a learning environment dedicated to serving the society. Therefore, training medical graduates in media literacy is crucial. With the advent of the era of intelligent media, scientific research has entered a new stage. Since then, there has been an increasing number of literacy research in the fields of education and medicine. The cultivation of medical literacy (ML) of medical workers conforms to the development needs of the information age. It also prepares for the cultivation of high-quality medical talents. In this paper, an acute sampling of medical staff (MS) in major hospitals in a province is used to analyze the literacy of these MS, and use the training optimization algorithm to evaluate their literacy before and after the implementation of the literacy training program. It is hoped that the research in this paper can make MS face up to their own ML problems to a certain extent, and at the same time improve various social factors that affect the formation of MS literacy to enhance their literacy.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130405330","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

The Innovation Development of Data Prediction and Clustered Compressive Sensing (CCS) in Environmental Application 数据预测与聚类压缩感知(CCS)在环境应用中的创新发展

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151340

Sonia Kukreja, Garima Jain

{"title":"The Innovation Development of Data Prediction and Clustered Compressive Sensing (CCS) in Environmental Application","authors":"Sonia Kukreja, Garima Jain","doi":"10.1109/ICDCECE57866.2023.10151340","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151340","url":null,"abstract":"Data prediction in environmental applications is a quickly evolving field that provides tremendous potential for improving environmental management and decision-making. By leveraging the power of data, predictive models can be developed to identify potential environmental risks, mitigate the impacts of climate change, and improve the efficiency of environmental management. Data prediction in environmental applications can be used to better understand the relationships between environmental phenomena and the environment. For instance, predictive models can be used to identify areas that are more likely to experience extreme weather events and inform the development of strategies for responding to such events. Predictive models can also be used to analyze the effects of changing climate on ecosystems and help inform decisions regarding the management of natural resources. Data prediction in environmental applications can also be used to develop more effective management strategies. Predictive models can be used to determine which areas are more likely to experience water scarcity or air pollution, and which areas are more likely to benefit from certain conservation practices. By leveraging data, predictive models can also help predict how certain management practices will affect the environment and inform decision-makers on how to best allocate resources.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134106465","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

Efficient Task Scheduling in Cloud Environment Based on Hyper Min Max Task Scheduling 基于超最小最大任务调度的云环境下高效任务调度

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150869

D. Gnanaprakasam, M. Mohanraj, T. A. S. Srinivas, S. Bhaggiaraj, Baskaran J, S. Sivankalai

{"title":"Efficient Task Scheduling in Cloud Environment Based on Hyper Min Max Task Scheduling","authors":"D. Gnanaprakasam, M. Mohanraj, T. A. S. Srinivas, S. Bhaggiaraj, Baskaran J, S. Sivankalai","doi":"10.1109/ICDCECE57866.2023.10150869","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150869","url":null,"abstract":"The growing field of cloud computing deals with large tasks for processing resources. From the application point of view, the research on task scheduling mechanism of data transfer in large-scale cloud computing environment is relatively poor. Unbalanced scheduling leads to traffic overload, energy loss, and failure of hardware control. In addition, residential appliances do not consider delay reduction in power consumption. Hence, Internet of Things (IoT) dominates the current trends in the Internet. The large number of things (things) associated with the Internet creates a large amount of information that requires a lot of effort and work preparation to make it valuable. To resolve this problem, we propose a Hyper Min max task scheduling (HMMTS) based in cascade shrink priority (CSP) to allocate task to optimize the scheduling. With intent a Changeover Load Balancer (CLB) and The Preemptive Flow Manager (PFM) is responsible for the application of load balancing strategy based on the mixed load balancing algorithm improves the task allocation better to balance load to improve the response time. Experimental results have been demonstrated with respect to better load balancing, lower power rate, and time consumption rate in both phase and random uniform propagation. Simulated results performance of this process can reduce data processing time and achieve load neutralization.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134519963","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