Pub Date : 2022-10-22DOI: 10.1109/UV56588.2022.10185488
Feng Zhang, Feng Liu, Xin Liu, Xiangyu Chen, Kai Zhou
Oilfield companies with oil and gas as their main products are not only large energy producers, but also large energy consumption and carbon emission producers. Large application of efficient, clean and low-carbon energy is an effective way for oilfield companies to achieve carbon peaks and ultimately achieve carbon neutrality goals. The oil and gas gathering and transportation system is the main body of the oilfield ground engineering. The oil transfer station is an important link in the oil and gas gathering and transportation system. It is mainly responsible for the heating and pressurization of crude oil in the process of crude oil transportation. The existing energy supply system is powered by grid electricity and natural gas boilers to meet the electrical load and low temperature heat load requirements respectively. The complementary multi-energy distributed energy system is applied to the oil transfer station. Through the complementation of solar energy, cross-seasonal heat storage, natural gas and other energy sources, the cascade utilization technology of energy is used to provide a stable power supply and low-temperature heat to the transfer station. The annual energy saving rate of the proposed system is 42.2 percent, and the carbon reduction rate is 45.6 percent. The replacement of the energy supply system can effectively improve the energy utilization rate of the oil transfer station, thereby reducing carbon emissions and contributing to the energy conservation and carbon reduction of oil fields.
{"title":"Application of Complementary Multi-energy Distributed Energy System in Oil Transfer Station","authors":"Feng Zhang, Feng Liu, Xin Liu, Xiangyu Chen, Kai Zhou","doi":"10.1109/UV56588.2022.10185488","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185488","url":null,"abstract":"Oilfield companies with oil and gas as their main products are not only large energy producers, but also large energy consumption and carbon emission producers. Large application of efficient, clean and low-carbon energy is an effective way for oilfield companies to achieve carbon peaks and ultimately achieve carbon neutrality goals. The oil and gas gathering and transportation system is the main body of the oilfield ground engineering. The oil transfer station is an important link in the oil and gas gathering and transportation system. It is mainly responsible for the heating and pressurization of crude oil in the process of crude oil transportation. The existing energy supply system is powered by grid electricity and natural gas boilers to meet the electrical load and low temperature heat load requirements respectively. The complementary multi-energy distributed energy system is applied to the oil transfer station. Through the complementation of solar energy, cross-seasonal heat storage, natural gas and other energy sources, the cascade utilization technology of energy is used to provide a stable power supply and low-temperature heat to the transfer station. The annual energy saving rate of the proposed system is 42.2 percent, and the carbon reduction rate is 45.6 percent. The replacement of the energy supply system can effectively improve the energy utilization rate of the oil transfer station, thereby reducing carbon emissions and contributing to the energy conservation and carbon reduction of oil fields.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206905","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185528
Lingyan Li, Sicheng Liu, Lin Zhang
With the coming of the third industrial revolution, multiple industries have mass manufacturing needs. In order to save production costs and maximize profit, businesses in these industries hurry to improve the level of manufacturing and carry out intelligent transformation. Thus, intelligent manufacturing has become the top priority in the modern industrial system. In addition, in the intelligent manufacturing aspect, not only cost-saving problems but also unexpected events (e.g. service broken) during the manufacturing process is a crucial challenge. Therefore, it is necessary to investigate the above problem of uncertainty scheduling mechanisms in cloud manufacturing (CMfg) as one of the important representative forms of intelligent manufacturing. This paper proposes a two-layer scheduling model based on the Stackelberg game in CMfg. In this model, a triple-layer iteration algorithm is designed to get the Nash equilibrium in the game theory. Also, to better analyze and solve the uncertainty during the manufacturing process, the main service broken cases are discussed using the real-time scheduling method, and the corresponding solutions of each case are presented. The case study verifies the efficiency and necessity of the proposed scheduling method by setting automobile manufacturing as the research case.
{"title":"Stackelberg Game Based Manufacturing Service Uncertainty Scheduling Toward Intelligent Manufacturing","authors":"Lingyan Li, Sicheng Liu, Lin Zhang","doi":"10.1109/UV56588.2022.10185528","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185528","url":null,"abstract":"With the coming of the third industrial revolution, multiple industries have mass manufacturing needs. In order to save production costs and maximize profit, businesses in these industries hurry to improve the level of manufacturing and carry out intelligent transformation. Thus, intelligent manufacturing has become the top priority in the modern industrial system. In addition, in the intelligent manufacturing aspect, not only cost-saving problems but also unexpected events (e.g. service broken) during the manufacturing process is a crucial challenge. Therefore, it is necessary to investigate the above problem of uncertainty scheduling mechanisms in cloud manufacturing (CMfg) as one of the important representative forms of intelligent manufacturing. This paper proposes a two-layer scheduling model based on the Stackelberg game in CMfg. In this model, a triple-layer iteration algorithm is designed to get the Nash equilibrium in the game theory. Also, to better analyze and solve the uncertainty during the manufacturing process, the main service broken cases are discussed using the real-time scheduling method, and the corresponding solutions of each case are presented. The case study verifies the efficiency and necessity of the proposed scheduling method by setting automobile manufacturing as the research case.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122692240","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185489
Rongsheng Wang, Yukun Li, Yaofei Duan, Tao Tan
Object detection has been a popular task in deep learning. In marine microalgae detection, the dimension of the image in the marine microalgae is too large, but the object is too small compared with the images. Additionally, the number of images in each category differs greatly, which brings a great challenge to object detection. We propose EfficientNet-YOLOv5 to solve the two problems mentioned above. Based on YOLOv5, we improved the Backbone of YOLOv5 with EfficientNet. To further strengthen our proposed EfficientNet-YOLOv5, we offer a variety of useful tricks, such as offline and online data augmentation, multi-scale testing, multi-model ensembled, and LabelSmooling. Extensive experiments on marine microalgae have shown that EfficientNet-YOLOv5 has good performance. It also has very strong interpretability in the marine microalgae scenario. On the marine microalgae detection in microscopy dataset, we used only the EfficientNet-YOLOv5 model and obtained an online score of 44.73 percent. Compared with the baseline model (scored 42.38 percent), EfficientNet-YOLOv5 improved by 2.35 percent. In model ensembled, we received an online score of 50.683 percent using the ensembled model of EfficientNet-YOLOv5 and YOLOv5s for detection. Overall, our model obtained a considerable improvement in detection accuracy. Moreover, it also has excellent performance in inference speed and model size.
{"title":"EfficientNet-YOLOv5: Improved YOLOv5 Based on EfficientNet Backbone for Object Detection on Marine Microalgae","authors":"Rongsheng Wang, Yukun Li, Yaofei Duan, Tao Tan","doi":"10.1109/UV56588.2022.10185489","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185489","url":null,"abstract":"Object detection has been a popular task in deep learning. In marine microalgae detection, the dimension of the image in the marine microalgae is too large, but the object is too small compared with the images. Additionally, the number of images in each category differs greatly, which brings a great challenge to object detection. We propose EfficientNet-YOLOv5 to solve the two problems mentioned above. Based on YOLOv5, we improved the Backbone of YOLOv5 with EfficientNet. To further strengthen our proposed EfficientNet-YOLOv5, we offer a variety of useful tricks, such as offline and online data augmentation, multi-scale testing, multi-model ensembled, and LabelSmooling. Extensive experiments on marine microalgae have shown that EfficientNet-YOLOv5 has good performance. It also has very strong interpretability in the marine microalgae scenario. On the marine microalgae detection in microscopy dataset, we used only the EfficientNet-YOLOv5 model and obtained an online score of 44.73 percent. Compared with the baseline model (scored 42.38 percent), EfficientNet-YOLOv5 improved by 2.35 percent. In model ensembled, we received an online score of 50.683 percent using the ensembled model of EfficientNet-YOLOv5 and YOLOv5s for detection. Overall, our model obtained a considerable improvement in detection accuracy. Moreover, it also has excellent performance in inference speed and model size.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128467557","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}
Ever since the birth of panoramic technology, it has been a hot topic in the digital media field, especially in the digital display field. Against the background of epidemic prevention and control on a regular basis, the government has presented more and more support for the development of online culture, entertainment and service industries. Nevertheless, in the panoramic field, Baidu, Google and other companies valued their products very much and conducted a monopoly of techniques, hindering the development of the industry. The panoramic roaming technology now faces many problems, including a lack of data acquisition criteria, nonstandard scene construction and unsmooth scene switching. To break the technical monopoly, promote industrial development and improve user experience, the design provided a grid spherical panoramic scene modeling technique that can be switched smoothly. In the premise of the reproduction of the industrial grade panoramic technology, its application in the indoor panoramic scene has experienced improvement and innovation. Major contributions of this design include: It broke the monopoly of commercial panoramic technologies and optimized the image effect and the interactive mode, providing more functions; and it formulated reference standards for panoramic data acquisition and indoor scene modeling; and it designed and realized the smooth switching among spherical panoramas.
{"title":"Innovative Application and Improvement of Panoramic Digital Technology in Indoor Display Scenes","authors":"Fenglei Huang, Xingshi Luo, Hao S. Lin, Ying-Sheng Chen, Zhiling Xu, Keyu Wan, Mengchen Zhang, Pengyi Peng, Xinyu Wen, Longfei Zhou, Zimo Li, Yihan Wang","doi":"10.1109/UV56588.2022.10185467","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185467","url":null,"abstract":"Ever since the birth of panoramic technology, it has been a hot topic in the digital media field, especially in the digital display field. Against the background of epidemic prevention and control on a regular basis, the government has presented more and more support for the development of online culture, entertainment and service industries. Nevertheless, in the panoramic field, Baidu, Google and other companies valued their products very much and conducted a monopoly of techniques, hindering the development of the industry. The panoramic roaming technology now faces many problems, including a lack of data acquisition criteria, nonstandard scene construction and unsmooth scene switching. To break the technical monopoly, promote industrial development and improve user experience, the design provided a grid spherical panoramic scene modeling technique that can be switched smoothly. In the premise of the reproduction of the industrial grade panoramic technology, its application in the indoor panoramic scene has experienced improvement and innovation. Major contributions of this design include: It broke the monopoly of commercial panoramic technologies and optimized the image effect and the interactive mode, providing more functions; and it formulated reference standards for panoramic data acquisition and indoor scene modeling; and it designed and realized the smooth switching among spherical panoramas.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125638204","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185473
Ya Gao, Zhoulai Li
Smart city is a new stage of development after industrial city, and a product of human science and society. Task 1: Based on the development of smart city, it selects 26 indicators of 7 main factors and draws the hierarchical structure chart by holding the scientific selection principle. When determining the weight of factors at each layer, it uses the consistent matrix method to compare the pair and pair factors, judges the consistency ratio of the obtained matrix, and finally determines the weight of each indicator. The smart city development index is the value of the second-level index multiplied by their respective weights and then summed, and the development level of the city is divided with 0.5 as the standard. Task 2: Firstly, compared with China’s GDP, it is found that Hangzhou’s growth rate is always higher than that of China, while Harbin’s GDP is lower than Hangzhou’s and its development is slower. According to the development index proposed in the first question, the scores of Hangzhou and Harbin are calculated and the trend chart is drawn. It is found that before 2017, the development of Harbin was higher than that of Hangzhou, but after that, the growth rate of Hangzhou was faster and Hangzhou surpassed Harbin. After 2017, the scores of Hangzhou both exceeded 50, that is, both were above the average development level. Task 4: Based on the system dynamics theory, the smart city system dynamic model is constructed based on the data of Hangzhou City. The model includes seven parts: smart economy, intelligent humanity, intelligent energy management, intelligent medical treatment, intelligent urban infrastructure, intelligent environmental protection, and urban planning and crowd management. Vensim was used to simulate the model, and the results showed that the future construction level of Hangzhou would be stable but rising, and all subsystems would play an important role in urban development, among which the smart economy was the most obvious. Finally, according to the conclusions of the research, some suggestions and plans are provided for Hangzhou and Harbin from the aspects of green development, science and technology, government leadership and so on.
{"title":"Smart City Development Index","authors":"Ya Gao, Zhoulai Li","doi":"10.1109/UV56588.2022.10185473","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185473","url":null,"abstract":"Smart city is a new stage of development after industrial city, and a product of human science and society. Task 1: Based on the development of smart city, it selects 26 indicators of 7 main factors and draws the hierarchical structure chart by holding the scientific selection principle. When determining the weight of factors at each layer, it uses the consistent matrix method to compare the pair and pair factors, judges the consistency ratio of the obtained matrix, and finally determines the weight of each indicator. The smart city development index is the value of the second-level index multiplied by their respective weights and then summed, and the development level of the city is divided with 0.5 as the standard. Task 2: Firstly, compared with China’s GDP, it is found that Hangzhou’s growth rate is always higher than that of China, while Harbin’s GDP is lower than Hangzhou’s and its development is slower. According to the development index proposed in the first question, the scores of Hangzhou and Harbin are calculated and the trend chart is drawn. It is found that before 2017, the development of Harbin was higher than that of Hangzhou, but after that, the growth rate of Hangzhou was faster and Hangzhou surpassed Harbin. After 2017, the scores of Hangzhou both exceeded 50, that is, both were above the average development level. Task 4: Based on the system dynamics theory, the smart city system dynamic model is constructed based on the data of Hangzhou City. The model includes seven parts: smart economy, intelligent humanity, intelligent energy management, intelligent medical treatment, intelligent urban infrastructure, intelligent environmental protection, and urban planning and crowd management. Vensim was used to simulate the model, and the results showed that the future construction level of Hangzhou would be stable but rising, and all subsystems would play an important role in urban development, among which the smart economy was the most obvious. Finally, according to the conclusions of the research, some suggestions and plans are provided for Hangzhou and Harbin from the aspects of green development, science and technology, government leadership and so on.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122736596","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185506
Richard Liao, J. Wan
This paper introduces different resources of renewable energy including biomass, hydroelectricity, tidal, solar, wind and geothermal. The advantages and disadvantages of each renewal energy resource in relation to the environment are compared.
{"title":"Introduction and Comparisons of Renewable Energy","authors":"Richard Liao, J. Wan","doi":"10.1109/UV56588.2022.10185506","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185506","url":null,"abstract":"This paper introduces different resources of renewable energy including biomass, hydroelectricity, tidal, solar, wind and geothermal. The advantages and disadvantages of each renewal energy resource in relation to the environment are compared.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125782788","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185505
Ailun Liu
Bullying is hard to define due to its vague boundaries and subjective nature, and often causes misunderstood issues of school bullying. Bullying can lead to both physical and mental devastating outcomes, and thereby managing and addressing bullying effectively become very important. A more accurate and comprehensive definition of bullying, increased awareness and training for teachers, and collaborative efforts between schools and education authorities will undoubtedly help effectively combat this pervasive problem.
{"title":"About Bullying","authors":"Ailun Liu","doi":"10.1109/UV56588.2022.10185505","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185505","url":null,"abstract":"Bullying is hard to define due to its vague boundaries and subjective nature, and often causes misunderstood issues of school bullying. Bullying can lead to both physical and mental devastating outcomes, and thereby managing and addressing bullying effectively become very important. A more accurate and comprehensive definition of bullying, increased awareness and training for teachers, and collaborative efforts between schools and education authorities will undoubtedly help effectively combat this pervasive problem.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126711140","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 : 2022-10-22DOI: 10.1109/UV56588.2022.10185516
Maryam Shoaeinaeini, Oktay Ozturk, Deepak Gupta
The current traffic system requires short-term traffic forecasting to manage and control the traffic flow. Irregular traffic events, such as road closures, accidents, and severe weather, reduce the accuracy of data-driven predictive models. Social media platforms, particularly Twitter can significantly help to realize a real-traffic flow system by representing traffic events. Combining traffic data with information about road disruptions posted on Twitter can improve urban traffic parameter prediction. This paper proposes an urban traffic flow prediction by combining massive traffic, calendar, and weather data with related tweet posts. As a case study, the model is implemented on an urban traffic dataset extracted from the California Performance Measurement System (PeMS) in the USA. To provide a reliable and accurate prediction, the proposed model is evaluated with several machine learning methods. The results from the empirical study show that when Twitter features are combined with traffic, weather, and calendar features, the prediction accuracy is enhanced. As a result, we obtain around 89 percent, 95 percent, 93 percent, 91 percent, 91 percent, and 95 percent R-squared from AdaBoost regression, Random Forest, Gradient Boosting, Artificial Neural Network, Decision Trees, and KNN Regression, respectively.
{"title":"Twitter-informed Prediction for Urban Traffic Flow Using Machine Learning","authors":"Maryam Shoaeinaeini, Oktay Ozturk, Deepak Gupta","doi":"10.1109/UV56588.2022.10185516","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185516","url":null,"abstract":"The current traffic system requires short-term traffic forecasting to manage and control the traffic flow. Irregular traffic events, such as road closures, accidents, and severe weather, reduce the accuracy of data-driven predictive models. Social media platforms, particularly Twitter can significantly help to realize a real-traffic flow system by representing traffic events. Combining traffic data with information about road disruptions posted on Twitter can improve urban traffic parameter prediction. This paper proposes an urban traffic flow prediction by combining massive traffic, calendar, and weather data with related tweet posts. As a case study, the model is implemented on an urban traffic dataset extracted from the California Performance Measurement System (PeMS) in the USA. To provide a reliable and accurate prediction, the proposed model is evaluated with several machine learning methods. The results from the empirical study show that when Twitter features are combined with traffic, weather, and calendar features, the prediction accuracy is enhanced. As a result, we obtain around 89 percent, 95 percent, 93 percent, 91 percent, 91 percent, and 95 percent R-squared from AdaBoost regression, Random Forest, Gradient Boosting, Artificial Neural Network, Decision Trees, and KNN Regression, respectively.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132839497","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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