Pub Date : 2022-10-22DOI: 10.1109/UV56588.2022.10185477
Ling Chen, Yaman Wang, Yuchen Long, Zengfeng Duan, Yanyan Li
Complex precision parts of electronic products are essential to defense information technology equipment and the manufacturing industry. The workshop testing process for electronic products is crucial to ensuring their quality is qualified. Due to its multi-breed, multi-batch, and complex structure, its experimental process design is challenged by more and more indicators and complex processes. Currently, the process of detecting complex electronic products still adopts manual process document design, which is inefficient and inconsistent, and it is difficult to guarantee accuracy by manual experience. Therefore, a new intelligent test process method is designed to complete the process design. The method first automatically extracts test indicators and related parameters from the imported unstructured technical files or sop files, then automatically matches the test indicators with the test table, then automatically fills the test parameters under each index, then clusters and outputs XML test procedures for each indicator. Moreover, the key technology of each process is studied, the intelligent test process system for complex electronic products is developed, and the application of one model of microwave component products in a military industry enterprise is used as an example. The test program generated by the system can be directly used for subsequent workshop machine execution.
{"title":"Research and Development of Intelligent Tests and a Process Design System for Complex and Precision Parts of Electronic Products","authors":"Ling Chen, Yaman Wang, Yuchen Long, Zengfeng Duan, Yanyan Li","doi":"10.1109/UV56588.2022.10185477","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185477","url":null,"abstract":"Complex precision parts of electronic products are essential to defense information technology equipment and the manufacturing industry. The workshop testing process for electronic products is crucial to ensuring their quality is qualified. Due to its multi-breed, multi-batch, and complex structure, its experimental process design is challenged by more and more indicators and complex processes. Currently, the process of detecting complex electronic products still adopts manual process document design, which is inefficient and inconsistent, and it is difficult to guarantee accuracy by manual experience. Therefore, a new intelligent test process method is designed to complete the process design. The method first automatically extracts test indicators and related parameters from the imported unstructured technical files or sop files, then automatically matches the test indicators with the test table, then automatically fills the test parameters under each index, then clusters and outputs XML test procedures for each indicator. Moreover, the key technology of each process is studied, the intelligent test process system for complex electronic products is developed, and the application of one model of microwave component products in a military industry enterprise is used as an example. The test program generated by the system can be directly used for subsequent workshop machine execution.","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":"131303271","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/UV56588.2022.10185472
Fan He, Longfei Zhou, Siyu Wu, Haoliang Liu, Zehang Li, Ke Xu, Yuliang Gai, Fei Teng, Pengfei Liu
Vehicular traffic congestion is a severe global problem, leading to a range of issues such as increased travel times, increased fuel consumption, and increased pollutant emissions. The signal timing of traffic lights is one of the major factors that we can change to reduce traffic congestion at signalized intersections. Most traffic lights used in real life are hard-coded which means the fixed timing is applied for traffic control. In these hard-coded signalized intersection models, we do not have much to do to deal with real-time congestion, especially for large traffic volumes. In this study, we propose an adaptive signal timing control approach to reduce traffic congestion according to real-time traffic flow situations. In this novel approach, the signal timing can be changed over time based on real-time information about traffic flows. The Eclipse SUMO is used to simulate traffic conditions at real-world intersections to optimize road traffic light control and reduce real-time traffic delays for signalized intersections. Simulation results show that the proposed method obtains better performance than typical traffic light timing control strategies.
{"title":"A Novel Adaptive Signal Timing Control Approach for Signalized Intersections","authors":"Fan He, Longfei Zhou, Siyu Wu, Haoliang Liu, Zehang Li, Ke Xu, Yuliang Gai, Fei Teng, Pengfei Liu","doi":"10.1109/UV56588.2022.10185472","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185472","url":null,"abstract":"Vehicular traffic congestion is a severe global problem, leading to a range of issues such as increased travel times, increased fuel consumption, and increased pollutant emissions. The signal timing of traffic lights is one of the major factors that we can change to reduce traffic congestion at signalized intersections. Most traffic lights used in real life are hard-coded which means the fixed timing is applied for traffic control. In these hard-coded signalized intersection models, we do not have much to do to deal with real-time congestion, especially for large traffic volumes. In this study, we propose an adaptive signal timing control approach to reduce traffic congestion according to real-time traffic flow situations. In this novel approach, the signal timing can be changed over time based on real-time information about traffic flows. The Eclipse SUMO is used to simulate traffic conditions at real-world intersections to optimize road traffic light control and reduce real-time traffic delays for signalized intersections. Simulation results show that the proposed method obtains better performance than typical traffic light timing control strategies.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"31 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":"128831401","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/UV56588.2022.10185468
Cheuk Wang Su, Ruiyang Gao, Mingyu Hu, Yajun Fang
At present, rapid urbanization has resulted in increased production of commodities, thereby enhancing the convenience of human lives. However, these products generate a lot of waste, which leads to severe environmental challenges damaging mother earth. Plastic has been an essential part of the world as society continues to develop. Bottles, toys, cars, and electronic products all have plastic components. With plastic becoming an increasingly ubiquitous presence in our daily lives, the production of plastic has also soared. A study estimated that 8.3 billion metric tons of plastic have been produced from the early 1950s to 2017 [1]. As production increases, disposal methods also need to improve. However, according to UNEP, less than 10% are recycled [2]. If plastic is not properly processed, it would remain in the world forever and create mass destruction to our environment. The oceans serve as a pertinent example, wherein a significant influx of plastic finds its way through waterways and beaches. As time moves on, plastic will start to degrade and become microplastic. According to the data, there is 51 trillion microplastic litter in the ocean [3]. They then affect our health entering the food chain, since a lot of sea animals see them as food. Overwhelmed plastics also affect human health. A research found that an apple has around 195,500 plastic particles per gram, ranking the highest among items they tested [4]. A report estimates that a person could eat a credit-card-size of plastics per week. Out of all types of plastics, including PET, HDPE, PVC, LDPE, PP, PS, and others [5]. PVC is estimated to be the most toxic to the human body. It contains a lot of phthalates, which can damage the liver, kidneys, lungs, and reproductive system. In this paper, we evaluate plastic pollution based on the framework of a closed feedback control loop: data acquisition, communication, decision-making, and action. Currently, there are multiple ways to collect data. For example, researchers can capture images from unmanned aerial vehicles and self-designed trucks. There are existing operational technologies that are actively engaged in the collection of plastics, particularly within the marine environment, such as 4ocean’s skimmer and Mr. Trash Wheel in Baltimore [6], [7]. There are also innovations such as turning used plastics into bricks [8]. In addition, We propose that effective smart plastic recycling should ideally interact with the other seven smart city subsystems proposed by UV: Smart Home, Smart Medicine and Healthcare, Smart ITS, Urban planning and Crowd management, Smart Energy Management, Smart City Infrastructure, Smart Response System for City Emergencies, and Smart Humanity.
{"title":"Evaluation of Plastic Recycling and Novel UV-Oriented Solution for Integration, Resilience, Inclusiveness, and Sustainability","authors":"Cheuk Wang Su, Ruiyang Gao, Mingyu Hu, Yajun Fang","doi":"10.1109/UV56588.2022.10185468","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185468","url":null,"abstract":"At present, rapid urbanization has resulted in increased production of commodities, thereby enhancing the convenience of human lives. However, these products generate a lot of waste, which leads to severe environmental challenges damaging mother earth. Plastic has been an essential part of the world as society continues to develop. Bottles, toys, cars, and electronic products all have plastic components. With plastic becoming an increasingly ubiquitous presence in our daily lives, the production of plastic has also soared. A study estimated that 8.3 billion metric tons of plastic have been produced from the early 1950s to 2017 [1]. As production increases, disposal methods also need to improve. However, according to UNEP, less than 10% are recycled [2]. If plastic is not properly processed, it would remain in the world forever and create mass destruction to our environment. The oceans serve as a pertinent example, wherein a significant influx of plastic finds its way through waterways and beaches. As time moves on, plastic will start to degrade and become microplastic. According to the data, there is 51 trillion microplastic litter in the ocean [3]. They then affect our health entering the food chain, since a lot of sea animals see them as food. Overwhelmed plastics also affect human health. A research found that an apple has around 195,500 plastic particles per gram, ranking the highest among items they tested [4]. A report estimates that a person could eat a credit-card-size of plastics per week. Out of all types of plastics, including PET, HDPE, PVC, LDPE, PP, PS, and others [5]. PVC is estimated to be the most toxic to the human body. It contains a lot of phthalates, which can damage the liver, kidneys, lungs, and reproductive system. In this paper, we evaluate plastic pollution based on the framework of a closed feedback control loop: data acquisition, communication, decision-making, and action. Currently, there are multiple ways to collect data. For example, researchers can capture images from unmanned aerial vehicles and self-designed trucks. There are existing operational technologies that are actively engaged in the collection of plastics, particularly within the marine environment, such as 4ocean’s skimmer and Mr. Trash Wheel in Baltimore [6], [7]. There are also innovations such as turning used plastics into bricks [8]. In addition, We propose that effective smart plastic recycling should ideally interact with the other seven smart city subsystems proposed by UV: Smart Home, Smart Medicine and Healthcare, Smart ITS, Urban planning and Crowd management, Smart Energy Management, Smart City Infrastructure, Smart Response System for City Emergencies, and Smart Humanity.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"13 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":"122883279","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/UV56588.2022.10185482
Guangli Luo, Jiaqi Yan, Yixuan Guo
These days, the epidemic have evolved from a huge disaster to a protracted war. And as a precious and indispensable protecting resource, vaccine is definitely deserved our reminding because of its lack to some extents. In this paper, we develop mathematical models to predict the daily vaccination numbers in a short phase and more crucially, analysis a number of factors to Figure out a more efficient plan to allocate the vaccine among the central hospitals, community hospitals and health centers. And based on the conclusion, we give a brief note to the medical institutions.
{"title":"A New Mindset about the Vaccination Allocation","authors":"Guangli Luo, Jiaqi Yan, Yixuan Guo","doi":"10.1109/UV56588.2022.10185482","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185482","url":null,"abstract":"These days, the epidemic have evolved from a huge disaster to a protracted war. And as a precious and indispensable protecting resource, vaccine is definitely deserved our reminding because of its lack to some extents. In this paper, we develop mathematical models to predict the daily vaccination numbers in a short phase and more crucially, analysis a number of factors to Figure out a more efficient plan to allocate the vaccine among the central hospitals, community hospitals and health centers. And based on the conclusion, we give a brief note to the medical institutions.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"50 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":"123534534","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/UV56588.2022.10185507
Yiqiao Zhang, Ping Cui, Guijin Xie
This paper uses the LSTM network to predict the number of vaccinations in China from December 2022 to February 2023. In addition, according to the number of residents in different regions, the number of medical staff and other factors, the vaccine allocation optimization model is built. The model is solved by particle swarm optimization. The distribution strategy is applied to the analog data of Gongshu District of Hangzhou City and Daoli District of Harbin City. Finally, we give some implementable suggestions for the vaccination.
{"title":"Predict The Number of Vaccinated People and Formulate Vaccine Distribution Strategy of COVID-19 Based on LSTM and Particle Swarm optimization","authors":"Yiqiao Zhang, Ping Cui, Guijin Xie","doi":"10.1109/UV56588.2022.10185507","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185507","url":null,"abstract":"This paper uses the LSTM network to predict the number of vaccinations in China from December 2022 to February 2023. In addition, according to the number of residents in different regions, the number of medical staff and other factors, the vaccine allocation optimization model is built. The model is solved by particle swarm optimization. The distribution strategy is applied to the analog data of Gongshu District of Hangzhou City and Daoli District of Harbin City. Finally, we give some implementable suggestions for the vaccination.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"60 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":"127620712","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/UV56588.2022.10185529
Mostafa Zaman, Maher Al Islam, A. Tantawy, S. Abdelwahed
A well-designed water distribution system is crucial for maintaining high service standards in any modern smart city. Moreover, as the population is sky-rocketing, the demand for energy and water is increasing more rapidly than a decade before. Therefore, ensuring a steady clean water supply with optimized energy and water consumption has become necessary. To accurately monitor water distribution systems, the accuracy of input data plays a vital role in determining how accurate the system’s status estimations are. There must be a way for system operators to know what is going on at any given time to make practical decisions about how reliable the data they are receiving is. The input data uncertainty can induce flow and pressure calculation inaccuracies, which can be fatal while planning for future demands and needs to be quantified.Knowing the degree of uncertainty in predicting the water distribution system’s capacity or load can help people better prepare for future capacity or load predictions. Accurate uncertainty calculations are critical to time series forecasting. Probabilistic formulae are widely employed with classical time series models to estimate uncertainty. But incorporating new data and fine-tuning these models is a challenging task. This research paper presents a Bayesian LSTM network that computes both time series prediction and uncertainty assessment at the same time. In this paper, a real-time data set from VCU’s OpenCity test bed is employed to evaluate the efficacy of the suggested strategy.
{"title":"An Uncertainty Based Predictive Analysis of Smart Water Distribution System Using Bayesian LSTM Approach","authors":"Mostafa Zaman, Maher Al Islam, A. Tantawy, S. Abdelwahed","doi":"10.1109/UV56588.2022.10185529","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185529","url":null,"abstract":"A well-designed water distribution system is crucial for maintaining high service standards in any modern smart city. Moreover, as the population is sky-rocketing, the demand for energy and water is increasing more rapidly than a decade before. Therefore, ensuring a steady clean water supply with optimized energy and water consumption has become necessary. To accurately monitor water distribution systems, the accuracy of input data plays a vital role in determining how accurate the system’s status estimations are. There must be a way for system operators to know what is going on at any given time to make practical decisions about how reliable the data they are receiving is. The input data uncertainty can induce flow and pressure calculation inaccuracies, which can be fatal while planning for future demands and needs to be quantified.Knowing the degree of uncertainty in predicting the water distribution system’s capacity or load can help people better prepare for future capacity or load predictions. Accurate uncertainty calculations are critical to time series forecasting. Probabilistic formulae are widely employed with classical time series models to estimate uncertainty. But incorporating new data and fine-tuning these models is a challenging task. This research paper presents a Bayesian LSTM network that computes both time series prediction and uncertainty assessment at the same time. In this paper, a real-time data set from VCU’s OpenCity test bed is employed to evaluate the efficacy of the suggested strategy.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"157 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":"114546647","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/UV56588.2022.10185523
Yang Liu, Shuai Wang, Yubin Wu, Hao Sheng, Z. Xiong
Person image generation is to synthesize realistic pedestrian images that follow the same distribution as the given dataset. Previous attempts can be generally categorized into two classes: some methods use human pose information as guidance and others try to generate person images from scratch. The former is to transfer the pose of a source image to a reference pose. The generated person image have the same identity as the source image. The latter takes a random noise from latent space as input, and the real person images are only used as references for the discriminator. While pose-guided person image generation is widely studied, generating-from-scratch methods are also worth exploring because they can synthesize person image with new identity, which is a useful manner of data augmentation. These two types of generating methods have their different advantages and disadvantages, and sometimes they are complementary. In this work, the authors design a Generative Cooperative Network (GCN) to jointly train two types of GANs. The two GANs serve different purposes, and can learn from each other during the cooperative learning procedure. The proposed approach is verified on public datasets, and the results show that our GCN improves the performance of the baseline methods. Comparisons with state-of-the-art methods also prove the effectiveness of the proposed method.
{"title":"Generative Cooperative Network for Person Image Generation","authors":"Yang Liu, Shuai Wang, Yubin Wu, Hao Sheng, Z. Xiong","doi":"10.1109/UV56588.2022.10185523","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185523","url":null,"abstract":"Person image generation is to synthesize realistic pedestrian images that follow the same distribution as the given dataset. Previous attempts can be generally categorized into two classes: some methods use human pose information as guidance and others try to generate person images from scratch. The former is to transfer the pose of a source image to a reference pose. The generated person image have the same identity as the source image. The latter takes a random noise from latent space as input, and the real person images are only used as references for the discriminator. While pose-guided person image generation is widely studied, generating-from-scratch methods are also worth exploring because they can synthesize person image with new identity, which is a useful manner of data augmentation. These two types of generating methods have their different advantages and disadvantages, and sometimes they are complementary. In this work, the authors design a Generative Cooperative Network (GCN) to jointly train two types of GANs. The two GANs serve different purposes, and can learn from each other during the cooperative learning procedure. The proposed approach is verified on public datasets, and the results show that our GCN improves the performance of the baseline methods. Comparisons with state-of-the-art methods also prove the effectiveness of the proposed method.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"45 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":"114045108","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/UV56588.2022.10185504
Lei Wang, Tian-Ze Zhang, Yingting Chen, Yongyang Huang, Xitong Yin, Xiao Fan Liu, Daning Hu
Start-ups have emerged as key drivers of economic growth, fostering innovation, job creation, and knowledge dissemination across various industries. Accurately forecasting start-up life spans is critical for investors, policymakers, and entrepreneurs to make informed decisions and optimize resource allocation. However, existing predictive models, such as linear regression and survival analysis, face challenges in capturing the complex interactions and dynamic nature of factors influencing start-up success. This paper proposes applying the XGBoost algorithm, an advanced machine learning technique, to enhance the accuracy and reliability of start-up life span predictions. XGBoost offers several advantages over traditional methods, including adaptability to various data types, robustness to outliers, and efficient computational performance. By incorporating a wide range of features, such as financial, organizational, and death reasons, the algorithm can effectively capture the complex relationships among these factors without explicit feature engineering. Moreover, applying SHAP values provides an additional layer of interpretability, aiding stakeholders in better understanding the factors driving start-up life span. Utilizing the IT Orange dataset, we investigate the determinants of startup life spans, offering valuable insights for stakeholders in the entrepreneurial ecosystem.
{"title":"Machine Learning-based Start-up Company Lifespan Prediction: the Chinese Market as an Example","authors":"Lei Wang, Tian-Ze Zhang, Yingting Chen, Yongyang Huang, Xitong Yin, Xiao Fan Liu, Daning Hu","doi":"10.1109/UV56588.2022.10185504","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185504","url":null,"abstract":"Start-ups have emerged as key drivers of economic growth, fostering innovation, job creation, and knowledge dissemination across various industries. Accurately forecasting start-up life spans is critical for investors, policymakers, and entrepreneurs to make informed decisions and optimize resource allocation. However, existing predictive models, such as linear regression and survival analysis, face challenges in capturing the complex interactions and dynamic nature of factors influencing start-up success. This paper proposes applying the XGBoost algorithm, an advanced machine learning technique, to enhance the accuracy and reliability of start-up life span predictions. XGBoost offers several advantages over traditional methods, including adaptability to various data types, robustness to outliers, and efficient computational performance. By incorporating a wide range of features, such as financial, organizational, and death reasons, the algorithm can effectively capture the complex relationships among these factors without explicit feature engineering. Moreover, applying SHAP values provides an additional layer of interpretability, aiding stakeholders in better understanding the factors driving start-up life span. Utilizing the IT Orange dataset, we investigate the determinants of startup life spans, offering valuable insights for stakeholders in the entrepreneurial ecosystem.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"80 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":"134550583","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}
Aqueous ammonia is a commonly working fluid used in absorption refrigeration cycles, and high energy consumption exists during the working process due to incomplete separation of ammonia and water. To address this problem, several cations and anions are selected to form ionic liquids in this paper. Then these substances are added into the ammonia-water system to form ternary systems. The energy analysis between different particles of new systems is carried out by using the density flooding theory. The results indicate that dimethylimidazolium-dimethylphosphate has a high affinity for water and shows a more obvious potential to promote ammonia to separate from water in the energy calculation, and the theoretically predicted results are also consistent with the experimental data in the literature.
{"title":"Density Functional Theory Study of Adding Ionic Liquid to Aqueous Ammonia System","authors":"Zhibin Wu, Yun Li, Ping Cheng, Zhenbin Lei, Weijia Huang","doi":"10.1109/UV56588.2022.10185493","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185493","url":null,"abstract":"Aqueous ammonia is a commonly working fluid used in absorption refrigeration cycles, and high energy consumption exists during the working process due to incomplete separation of ammonia and water. To address this problem, several cations and anions are selected to form ionic liquids in this paper. Then these substances are added into the ammonia-water system to form ternary systems. The energy analysis between different particles of new systems is carried out by using the density flooding theory. The results indicate that dimethylimidazolium-dimethylphosphate has a high affinity for water and shows a more obvious potential to promote ammonia to separate from water in the energy calculation, and the theoretically predicted results are also consistent with the experimental data in the literature.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"1 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":"114541985","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}
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