Pub Date : 2022-10-28DOI: 10.1109/ecice55674.2022.10042833
{"title":"ECICE 2022 Cover Page","authors":"","doi":"10.1109/ecice55674.2022.10042833","DOIUrl":"https://doi.org/10.1109/ecice55674.2022.10042833","url":null,"abstract":"","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123096328","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042828
Yuxiao Luo
Due to the rapid development of network technology and the rapid spread of information through the network, the security of information systems is also threatened in many aspects. The purpose of this study is to build a security evaluation model of network information based on machine learning algorithms and to improve the model and the accuracy of model evaluation. Firstly, a hierarchical network information security assessment index system is constructed. Secondly, to improve the accuracy of security assessment, an improved AFSA algorithm and TWSVM model are introduced for enhancing classification accuracy. A security assessment based on improved AFSA-TWSVM is proposed to evaluate the model. Finally, the experiments are carried out to compare with the AFSA-SVM-based security assessment model and the PSO-LLSVM security assessment model. The experimental results show that the average classification accuracy of the AFSA-SVM-based security assessment model and the PSO-LLSVM-based security assessment model is S7.5 and 83.33%, respectively. The average classification accuracy of the improved AFSA-TWSVM reaches 90%, which is better than the other two evaluation models in classification accuracy. Therefore, the model proposed in this study is more suitable for network information security evaluation.
{"title":"Analysis and Research of Network Information Security Evaluation Model Based on Machine Learning Algorithm","authors":"Yuxiao Luo","doi":"10.1109/ECICE55674.2022.10042828","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042828","url":null,"abstract":"Due to the rapid development of network technology and the rapid spread of information through the network, the security of information systems is also threatened in many aspects. The purpose of this study is to build a security evaluation model of network information based on machine learning algorithms and to improve the model and the accuracy of model evaluation. Firstly, a hierarchical network information security assessment index system is constructed. Secondly, to improve the accuracy of security assessment, an improved AFSA algorithm and TWSVM model are introduced for enhancing classification accuracy. A security assessment based on improved AFSA-TWSVM is proposed to evaluate the model. Finally, the experiments are carried out to compare with the AFSA-SVM-based security assessment model and the PSO-LLSVM security assessment model. The experimental results show that the average classification accuracy of the AFSA-SVM-based security assessment model and the PSO-LLSVM-based security assessment model is S7.5 and 83.33%, respectively. The average classification accuracy of the improved AFSA-TWSVM reaches 90%, which is better than the other two evaluation models in classification accuracy. Therefore, the model proposed in this study is more suitable for network information security evaluation.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123222731","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042910
Rong-Guey Chang, Cheng-Yan Siao, Chia-ying Lee
In recent years, many fields have been related to introducing artificial intelligence to natural language generation. Although these natural language models have excellent results and generate smooth sentences, they are still not effective learning features such as character relationships, especially in the Chinese language. When a sentence is generated, it is necessary to pay attention to the following words to correctly predict and generate, such as quantifiers, which causes the generated words to be inappropriate and then affects the generation of subsequent words. Therefore, we developed a set of attention mechanism enhancement models, aiming at the generative language model that controls the ordering of generated speech parts, revising the different mechanisms of character fighting relationship and quantifier design, and adopting the traditional classification model one-against-all support vector machine training. The results show that the generated sentences are arranged in the same order as the original ones so the generation can be reliably controlled.
{"title":"Postprocessing System for Word-Filling and Quantifiers Based on Chinese Story Generation","authors":"Rong-Guey Chang, Cheng-Yan Siao, Chia-ying Lee","doi":"10.1109/ECICE55674.2022.10042910","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042910","url":null,"abstract":"In recent years, many fields have been related to introducing artificial intelligence to natural language generation. Although these natural language models have excellent results and generate smooth sentences, they are still not effective learning features such as character relationships, especially in the Chinese language. When a sentence is generated, it is necessary to pay attention to the following words to correctly predict and generate, such as quantifiers, which causes the generated words to be inappropriate and then affects the generation of subsequent words. Therefore, we developed a set of attention mechanism enhancement models, aiming at the generative language model that controls the ordering of generated speech parts, revising the different mechanisms of character fighting relationship and quantifier design, and adopting the traditional classification model one-against-all support vector machine training. The results show that the generated sentences are arranged in the same order as the original ones so the generation can be reliably controlled.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125066524","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042852
Songhua Hu, J. Bao, Chunhao Yang, Zuwei Hu, Xinbo Zhou, Nan Pan
In order to optimize the range of the wearable industrial lower limb exoskeleton during operation, firstly, the kinematic analysis of the lower limb exoskeleton is carried out, and the driving force model of each joint is derived through Lagrange ’s equation. Secondly, the motion stability constraint is derived by combining ZMP theory and D’Alembert’s principle. Finally, an optimization model with the optimal joint driving energy consumption as the objective function is constructed based on the continuous periodic motion of the lower limb exoskeleton. An improved Chameleon Swarm Algorithm (TNECSA) based on Tent chaos mapping, Niching behavior, and elite perturbation mechanism is designed to solve the model. Firstly, the Tent chaos mapping is used to generate high-quality initial feasible solutions. The small habitat technique is introduced to maintain the diversity of the population and expand the search range. Based on the elite perturbation mechanism, the elite individuals are perturbed by the sine cosine search operator to avoid the algorithm from falling into the local optimum. The designed algorithm is compared with other cutting-edge population intelligence algorithms in cross-sectional simulations respectively. The results validate the feasibility of the developed model and the improved algorithm in the human-machine dynamics optimization problem of exoskeleton robots.
{"title":"Optimization of Driving Energy Consumption for Wearable Industrial Lower Limb Exoskeleton Based on Improved Chameleon Algorithm and Human-machine Dynamics","authors":"Songhua Hu, J. Bao, Chunhao Yang, Zuwei Hu, Xinbo Zhou, Nan Pan","doi":"10.1109/ECICE55674.2022.10042852","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042852","url":null,"abstract":"In order to optimize the range of the wearable industrial lower limb exoskeleton during operation, firstly, the kinematic analysis of the lower limb exoskeleton is carried out, and the driving force model of each joint is derived through Lagrange ’s equation. Secondly, the motion stability constraint is derived by combining ZMP theory and D’Alembert’s principle. Finally, an optimization model with the optimal joint driving energy consumption as the objective function is constructed based on the continuous periodic motion of the lower limb exoskeleton. An improved Chameleon Swarm Algorithm (TNECSA) based on Tent chaos mapping, Niching behavior, and elite perturbation mechanism is designed to solve the model. Firstly, the Tent chaos mapping is used to generate high-quality initial feasible solutions. The small habitat technique is introduced to maintain the diversity of the population and expand the search range. Based on the elite perturbation mechanism, the elite individuals are perturbed by the sine cosine search operator to avoid the algorithm from falling into the local optimum. The designed algorithm is compared with other cutting-edge population intelligence algorithms in cross-sectional simulations respectively. The results validate the feasibility of the developed model and the improved algorithm in the human-machine dynamics optimization problem of exoskeleton robots.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121905503","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042934
Kuan-Yu Lu, Gadi Ashok Kumar Reddy, Nguyen Ngoc Thai, K. Lee
Lenses are widely used in many areas mostly in mobile cameras and security cameras. Before installation, inspection is very important to check the lenses condition like dust particles and any other damages. lenses are very sensitive and easy to scratch when using clamping device to pick up lenses. So, we use vacuum to provide suction to pick up the lenses to avoid wear and scratches. In this study, combined servo motor with EDM to create micro-hole array, to place the lenses. User interface helps the user to control the XY-Table for exact coordinate location to make fine hole array. In the experiment, it shows that by adjusting the gap voltage, pulse on-time, pulse off-time and outlet water pressure, the machining speed can be controlled without reaming and scorching. The average error during machining operation to make a micro-hole array is 0.00405 mm. User interface application save a lot of time and helps to improve accuracy to make fine hole.
{"title":"Design of a Micro-hole Array Device for Picking the Micro Lenses","authors":"Kuan-Yu Lu, Gadi Ashok Kumar Reddy, Nguyen Ngoc Thai, K. Lee","doi":"10.1109/ECICE55674.2022.10042934","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042934","url":null,"abstract":"Lenses are widely used in many areas mostly in mobile cameras and security cameras. Before installation, inspection is very important to check the lenses condition like dust particles and any other damages. lenses are very sensitive and easy to scratch when using clamping device to pick up lenses. So, we use vacuum to provide suction to pick up the lenses to avoid wear and scratches. In this study, combined servo motor with EDM to create micro-hole array, to place the lenses. User interface helps the user to control the XY-Table for exact coordinate location to make fine hole array. In the experiment, it shows that by adjusting the gap voltage, pulse on-time, pulse off-time and outlet water pressure, the machining speed can be controlled without reaming and scorching. The average error during machining operation to make a micro-hole array is 0.00405 mm. User interface application save a lot of time and helps to improve accuracy to make fine hole.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122164685","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042826
Shih-Chia Wang, Dena Gabriela
Environmental rules that restrict pollution emissions into the atmosphere are getting stricter. Therefore, it is essential to create new air pollution control technologies and enhance those that presently exist. A wet scrubber system is one of the most practical systems to control and remove pollutants that is used fluid mechanics and a little bit of propulsion system on its operation. The operation of a wet scrubber mainly concentrates on the water flow performance and filter design to capture the dust particles. This study focuses on analyzing the appropriate waterflow that will deliver a consistent flow through the filter at a specific velocity and briefly discusses the available filter performance for efficiency. Solid Works ST’s computer-aided drawing (CAD) program is used to design the pieces for 3D printing. In order to achieve the desired design, this study uses Computational Fluid Dynamic (CFD) simulation software (COMSOL Multiphysics 5.5) to evaluate the water tank design and filter performance in order to take the models’ accuracy and efficiency into account before they are combined to create a prototype and carry out the model’s experiment. The efficiency of filter with certain velocity if water flow is expected to be more than 70% on capturing the dust particles.
限制污染物排放到大气中的环境法规越来越严格。因此，必须创造新的空气污染控制技术，并加强现有的技术。湿式洗涤器系统是一种最实用的控制和去除污染物的系统，它使用了流体力学和少量的推进系统。湿式洗涤器的操作主要集中在水流性能和过滤器设计上，以捕获粉尘颗粒。本研究的重点是分析适当的水流，以特定的速度通过过滤器，并简要讨论了有效的过滤器性能。Solid Works ST的计算机辅助绘图(CAD)程序用于设计3D打印的部件。为了实现预期的设计，本研究使用计算流体动力学(CFD)仿真软件(COMSOL Multiphysics 5.5)对水箱设计和过滤器性能进行评估，以考虑模型的准确性和效率，然后将它们组合在一起创建原型并进行模型实验。当水流量达到一定流速时，过滤器对粉尘颗粒的捕集率可达70%以上。
{"title":"Filtering Analysis of a Wet Scrubber with Computational Fluid Dynamics Simulation","authors":"Shih-Chia Wang, Dena Gabriela","doi":"10.1109/ECICE55674.2022.10042826","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042826","url":null,"abstract":"Environmental rules that restrict pollution emissions into the atmosphere are getting stricter. Therefore, it is essential to create new air pollution control technologies and enhance those that presently exist. A wet scrubber system is one of the most practical systems to control and remove pollutants that is used fluid mechanics and a little bit of propulsion system on its operation. The operation of a wet scrubber mainly concentrates on the water flow performance and filter design to capture the dust particles. This study focuses on analyzing the appropriate waterflow that will deliver a consistent flow through the filter at a specific velocity and briefly discusses the available filter performance for efficiency. Solid Works ST’s computer-aided drawing (CAD) program is used to design the pieces for 3D printing. In order to achieve the desired design, this study uses Computational Fluid Dynamic (CFD) simulation software (COMSOL Multiphysics 5.5) to evaluate the water tank design and filter performance in order to take the models’ accuracy and efficiency into account before they are combined to create a prototype and carry out the model’s experiment. The efficiency of filter with certain velocity if water flow is expected to be more than 70% on capturing the dust particles.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128648449","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042831
Xue Li
Medical and health services are important in people's livelihood. Thus, governments attach great importance to the development of medical and health services. In this study, the gynecological outpatient clinic of Q hospital is taken as the research object as Q hospital outpatient operation efficiency still has a lot of problems. A long queue of patients in the hospital shows a problem in receiving medical treatment and low operational efficiency. For doctors on duty in outpatient departments, there are different periods in the day for outpatient departments, so the feature of the queue is different. Therefore, according to the difference, a reasonable arrangement of the number of on-duty doctors in Q hospital is needed for improving the utilization of resources and reducing the operation cost. It also improves the quality of hospital service and the satisfaction of patients.
{"title":"Optimization of Outpatient Doctor Allocation in Q Hospital Based on Queuing Theory","authors":"Xue Li","doi":"10.1109/ECICE55674.2022.10042831","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042831","url":null,"abstract":"Medical and health services are important in people's livelihood. Thus, governments attach great importance to the development of medical and health services. In this study, the gynecological outpatient clinic of Q hospital is taken as the research object as Q hospital outpatient operation efficiency still has a lot of problems. A long queue of patients in the hospital shows a problem in receiving medical treatment and low operational efficiency. For doctors on duty in outpatient departments, there are different periods in the day for outpatient departments, so the feature of the queue is different. Therefore, according to the difference, a reasonable arrangement of the number of on-duty doctors in Q hospital is needed for improving the utilization of resources and reducing the operation cost. It also improves the quality of hospital service and the satisfaction of patients.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124797281","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}
We investigated the different effects of mood induction in depressed and healthy people through an eyetracking study. In the early stage of attention, negative mood induction affects the speed and time of the attention focus of depressed people, while the control group is not be affected. However, in the late stage of attention, depressed people are less affected by emotional stimulation, while the healthy control group shows protective and attentional bias.
{"title":"Research and Analysis of Attentional Biases on Clinical Depression: Eye Tracking Study","authors":"Meng Zhang, Yue Chen, Shuo Tang, Ting Zhou, Zheng Huang","doi":"10.1109/ECICE55674.2022.10042888","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042888","url":null,"abstract":"We investigated the different effects of mood induction in depressed and healthy people through an eyetracking study. In the early stage of attention, negative mood induction affects the speed and time of the attention focus of depressed people, while the control group is not be affected. However, in the late stage of attention, depressed people are less affected by emotional stimulation, while the healthy control group shows protective and attentional bias.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125855646","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042926
Daniel Joy, O. Kotevska, Eyhab Al-Masri
Although the number of smart Internet of Things (IoT) devices has grown in recent years, the public's perception of how effectively these devices secure IoT data has been questioned. Many IoT users do not have a good level of confidence in the security or privacy procedures implemented within IoT smart devices for protecting personal IoT data. Moreover, determining the level of confidence end users have in their smart devices is becoming a major challenge. In this paper, we present a study that focuses on identifying privacy concerns IoT end users have when using IoT smart devices. We investigated multiple smart devices and conducted a survey to identify users’ privacy concerns. Furthermore, we identify five IoT privacy-preserving (IoTPP) control policies that we define and employ in comparing the privacy measures implemented by various popular smart devices. Results from our study show that the over 86% of participants are very or extremely concerned about the security and privacy of their personal data when using smart IoT devices such as Google Nest Hub or Amazon Alexa. In addition, our study shows that a significant number of IoT users may not be aware that their personal data is collected, stored or shared by IoT devices.
{"title":"Investigating Users’ Privacy Concerns of Internet of Things (IoT) Smart Devices","authors":"Daniel Joy, O. Kotevska, Eyhab Al-Masri","doi":"10.1109/ECICE55674.2022.10042926","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042926","url":null,"abstract":"Although the number of smart Internet of Things (IoT) devices has grown in recent years, the public's perception of how effectively these devices secure IoT data has been questioned. Many IoT users do not have a good level of confidence in the security or privacy procedures implemented within IoT smart devices for protecting personal IoT data. Moreover, determining the level of confidence end users have in their smart devices is becoming a major challenge. In this paper, we present a study that focuses on identifying privacy concerns IoT end users have when using IoT smart devices. We investigated multiple smart devices and conducted a survey to identify users’ privacy concerns. Furthermore, we identify five IoT privacy-preserving (IoTPP) control policies that we define and employ in comparing the privacy measures implemented by various popular smart devices. Results from our study show that the over 86% of participants are very or extremely concerned about the security and privacy of their personal data when using smart IoT devices such as Google Nest Hub or Amazon Alexa. In addition, our study shows that a significant number of IoT users may not be aware that their personal data is collected, stored or shared by IoT devices.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126247357","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}
Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042821
Singhen Suos, Lixiao Cong
The high voltage overhead transmission line system is one of the methods of delivering electric power at a high voltage of Electricity Du Cambodia (EDC) is the largest company in Cambodia’s location, which transmitted from one source to another distribution, especially over a long distance to the customers. In an electrical power system, compression dead end and jumper terminal is one of the most important pieces of equipment and play important roles in the transmission system high voltage as well. Moreover, a bad or loose connection can be made a hot spot for generating the thermal that affecting for transmitting power, for the survey thermal energy of electrical equipment that they can to observed and quantified as thermography by applying infrared imaging and measuring the camera techniques. This method of detecting heat output is known as infrared thermography (IRT). Infrared thermography is not only a cost-effective technology but also powerful diagnostic equipment for improving system efficiency and dependability, power quality, and worker safety, and preventing outages, expensive equipment failure, and line losses. Using the Neural Network (NN) in the comparison to the Linear Regression (LR) model. This paper regarded schedule working actual base on the history of transmission line reports of using IRT which was noted by EDC, and the input parameters were the weather factors, wind speed, duration of operation, and load on the line. The prediction accuracy of these two methodologies was calculated with the use of the mean absolute percentage error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). Based on the act result of the two models, the Neural Network (NN) model is better performance accuracy.
{"title":"Prediction the Thermal of Compression Dead-end and Jumper Terminal for Electrical Equipment Based on High Voltage Transmission Lines, Case Study of Electricity Du Cambodia (EDC)","authors":"Singhen Suos, Lixiao Cong","doi":"10.1109/ECICE55674.2022.10042821","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042821","url":null,"abstract":"The high voltage overhead transmission line system is one of the methods of delivering electric power at a high voltage of Electricity Du Cambodia (EDC) is the largest company in Cambodia’s location, which transmitted from one source to another distribution, especially over a long distance to the customers. In an electrical power system, compression dead end and jumper terminal is one of the most important pieces of equipment and play important roles in the transmission system high voltage as well. Moreover, a bad or loose connection can be made a hot spot for generating the thermal that affecting for transmitting power, for the survey thermal energy of electrical equipment that they can to observed and quantified as thermography by applying infrared imaging and measuring the camera techniques. This method of detecting heat output is known as infrared thermography (IRT). Infrared thermography is not only a cost-effective technology but also powerful diagnostic equipment for improving system efficiency and dependability, power quality, and worker safety, and preventing outages, expensive equipment failure, and line losses. Using the Neural Network (NN) in the comparison to the Linear Regression (LR) model. This paper regarded schedule working actual base on the history of transmission line reports of using IRT which was noted by EDC, and the input parameters were the weather factors, wind speed, duration of operation, and load on the line. The prediction accuracy of these two methodologies was calculated with the use of the mean absolute percentage error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). Based on the act result of the two models, the Neural Network (NN) model is better performance accuracy.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132560361","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}
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