Compared with the stable orders of traditional manufacturing, cloud manufacturing (CMfg) fulfilled with masses of random orders, so the CMfg server needs an algorithm with low time and space complexity to prevent the server from crashing due to excessive instantaneous data. Besides, the random changes of manufacturing resources and service must be considered when establishing a scheduling model for CMfg. To solve this problem, we propose an adaptive Deep Q-Networks (ADQN) method with a resizable network that converts cloud manufacturing scheduling problems with multiple objectives into specific reinforcement learning goal and can adapt to changing environments. Our experimental results show that ADQN is comparable to other real-time scheduling methods, the average subtask completion time and the standard deviation of occupation obtained by ADQN keep at a low level.
{"title":"Deep Reinforcement Learning Based Dynamic Scheduling of Random Arrival Tasks in Cloud Manufacturing","authors":"Leyao Chen, Longfei Zhou, Muer Zhou, Xilong Yu, Yipeng Zhu, Wenbo Song, Zixuan Lu, Jiayin Li","doi":"10.1109/UV56588.2022.10185485","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185485","url":null,"abstract":"Compared with the stable orders of traditional manufacturing, cloud manufacturing (CMfg) fulfilled with masses of random orders, so the CMfg server needs an algorithm with low time and space complexity to prevent the server from crashing due to excessive instantaneous data. Besides, the random changes of manufacturing resources and service must be considered when establishing a scheduling model for CMfg. To solve this problem, we propose an adaptive Deep Q-Networks (ADQN) method with a resizable network that converts cloud manufacturing scheduling problems with multiple objectives into specific reinforcement learning goal and can adapt to changing environments. Our experimental results show that ADQN is comparable to other real-time scheduling methods, the average subtask completion time and the standard deviation of occupation obtained by ADQN keep at a low level.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"71 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":"129472809","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/UV56588.2022.10185479
Mingyu Hu, Yajun Fang
The development of natural language processing (NLP) has revealed its huge potential power and wide implementation. However, in the current status of natural language processing and smart communication design, there are some problems and limitations. First, most of the NLP and smart communication research mainly focus on the direction of the algorithm but lacks communication and relationship model design. The second, algorithm and memory implementations of models seldom separate for different tasks and situations. The third, wide use of unsupervised learning makes the model difficult to interpret, uncontrollable, and inflexible. To solve those problems, we designed memory-relationship classification categories to classify and guide the implementation of NLP and smart communication. With the implementation of model basing learning concept and communication model, we designed a sequential controllable semantic dimension and relationship dimension system to classify smart communication.
{"title":"Model Based Smart Communication System Design","authors":"Mingyu Hu, Yajun Fang","doi":"10.1109/UV56588.2022.10185479","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185479","url":null,"abstract":"The development of natural language processing (NLP) has revealed its huge potential power and wide implementation. However, in the current status of natural language processing and smart communication design, there are some problems and limitations. First, most of the NLP and smart communication research mainly focus on the direction of the algorithm but lacks communication and relationship model design. The second, algorithm and memory implementations of models seldom separate for different tasks and situations. The third, wide use of unsupervised learning makes the model difficult to interpret, uncontrollable, and inflexible. To solve those problems, we designed memory-relationship classification categories to classify and guide the implementation of NLP and smart communication. With the implementation of model basing learning concept and communication model, we designed a sequential controllable semantic dimension and relationship dimension system to classify smart communication.","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":"131978123","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/UV56588.2022.10185490
Ke Xu, Longfei Zhou, Fan He, Siyu Wu, Haoliang Liu, Fei Teng, Zehang Li, Yuliang Gai, Pengfei Liu, Yifan Mo
With the increasing number of family cars, urban traffic congestion has become more and more common, which has a great impact on people’s lives. In order to alleviate the traffic pressure caused by traffic congestion, the roundabout came into being. Compared with ordinary intersections, roundabouts are superior in traffic efficiency and traffic control. However, research has found that the number of halts per vehicle at roundabouts has increased relative to ordinary intersections, which means that there is an increased possibility of large-scale congestion and driving conflicts in today’s huge traffic flow. This makes it possible to add traffic lights to the roundabout to control traffic flow to alleviate traffic congestion and driving conflicts. This paper aims to improve the traffic model of the ordinary two-lane roundabout and analyze whether different traffic light control methods are conducive to improving the traffic efficiency of the roundabout in the scenario of heavy traffic flow. Four improved models are established and compared with basic two-lane roundabout and signalized intersection. Based on two scenarios with different traffic volume, we analyze these models’ performance through multiple evaluation metrics. Results illustrates that roundabout with central cross has the best performance in the two scenarios, and proves that these two traffic light control methods failed to improve the traffic efficiency of roundabout in heavy traffic scenarios.
{"title":"A Novel Two-Lane Roundabout Model with Central Cross Structure","authors":"Ke Xu, Longfei Zhou, Fan He, Siyu Wu, Haoliang Liu, Fei Teng, Zehang Li, Yuliang Gai, Pengfei Liu, Yifan Mo","doi":"10.1109/UV56588.2022.10185490","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185490","url":null,"abstract":"With the increasing number of family cars, urban traffic congestion has become more and more common, which has a great impact on people’s lives. In order to alleviate the traffic pressure caused by traffic congestion, the roundabout came into being. Compared with ordinary intersections, roundabouts are superior in traffic efficiency and traffic control. However, research has found that the number of halts per vehicle at roundabouts has increased relative to ordinary intersections, which means that there is an increased possibility of large-scale congestion and driving conflicts in today’s huge traffic flow. This makes it possible to add traffic lights to the roundabout to control traffic flow to alleviate traffic congestion and driving conflicts. This paper aims to improve the traffic model of the ordinary two-lane roundabout and analyze whether different traffic light control methods are conducive to improving the traffic efficiency of the roundabout in the scenario of heavy traffic flow. Four improved models are established and compared with basic two-lane roundabout and signalized intersection. Based on two scenarios with different traffic volume, we analyze these models’ performance through multiple evaluation metrics. Results illustrates that roundabout with central cross has the best performance in the two scenarios, and proves that these two traffic light control methods failed to improve the traffic efficiency of roundabout in heavy traffic scenarios.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"190 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":"132008800","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}
The spine is the most complex load-bearing structure in the human body, and herniated discs, spinal stenosis, and degenerative discs are common spinal disorders. MRI is an effective imaging method in medicine, but the identification and quantitative analysis of lesions require physician judgment, which is not only a huge workload but also carries the subjective judgment of physicians, and such drawbacks can be solved by using image segmentation technology. In this paper, we propose an efficient spine segmentation method consisting of selective preprocessing and post-processing and an improved UNET network structure. In the selective pre-post processing, meaningful parts of the MRI are selected for random input, and the selected parts are effectively restored back to the original size of the segmented image. In the improved UNET network, differing from the traditional UNET structure, the perceptual field of the image input is increased by using inflated convolution, and the attention mechanism is added in the up-sampling and down-sampling end parts for better filtering of features. The experimental results show that our method outperforms the traditional method by substantially reducing the training elapsed time and performing well in terms of the accuracy of the model.
{"title":"An Efficient Spine Segmentation Method","authors":"Yuhang Meng, Longfei Zhou, Tianrun Xu, Junrui Wan, Xinyu Zhang, Zhong Wang","doi":"10.1109/UV56588.2022.10185522","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185522","url":null,"abstract":"The spine is the most complex load-bearing structure in the human body, and herniated discs, spinal stenosis, and degenerative discs are common spinal disorders. MRI is an effective imaging method in medicine, but the identification and quantitative analysis of lesions require physician judgment, which is not only a huge workload but also carries the subjective judgment of physicians, and such drawbacks can be solved by using image segmentation technology. In this paper, we propose an efficient spine segmentation method consisting of selective preprocessing and post-processing and an improved UNET network structure. In the selective pre-post processing, meaningful parts of the MRI are selected for random input, and the selected parts are effectively restored back to the original size of the segmented image. In the improved UNET network, differing from the traditional UNET structure, the perceptual field of the image input is increased by using inflated convolution, and the attention mechanism is added in the up-sampling and down-sampling end parts for better filtering of features. The experimental results show that our method outperforms the traditional method by substantially reducing the training elapsed time and performing well in terms of the accuracy of the model.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"39 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":"132637655","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/UV56588.2022.10185480
Tomoko Nariai, S. Itai, Hiroaki Kojima
In order to facilitate active communication among people of various cultural and linguistic backgrounds, it is necessary to learn a second language that is linguistically different from one’s native language. The difficulty in learning second language is thought to depend on readability. Most research on the validity of readability assessment has focused on native speakers. Moreover, most of the few studies of readability with second language learners have focused on textual data. This study analyzed actual speech data to determine the effects of word frequencies, syllable structures, and grammatical functions used to estimate the relation with readability on word duration. We compared English word durations in native English speakers and native Japanese speakers. It is hypothesized that highly readable words, i.e., those that are simple and familiar, would be easier for Japanese to utter and shorter in duration, but the opposite was found in the experiment. This suggests that the features adopted for native English speakers as readability indicators are not fully compatible with Japanese speakers.
{"title":"The Effect of English Text Readability on Speech Duration of Second Language Learners","authors":"Tomoko Nariai, S. Itai, Hiroaki Kojima","doi":"10.1109/UV56588.2022.10185480","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185480","url":null,"abstract":"In order to facilitate active communication among people of various cultural and linguistic backgrounds, it is necessary to learn a second language that is linguistically different from one’s native language. The difficulty in learning second language is thought to depend on readability. Most research on the validity of readability assessment has focused on native speakers. Moreover, most of the few studies of readability with second language learners have focused on textual data. This study analyzed actual speech data to determine the effects of word frequencies, syllable structures, and grammatical functions used to estimate the relation with readability on word duration. We compared English word durations in native English speakers and native Japanese speakers. It is hypothesized that highly readable words, i.e., those that are simple and familiar, would be easier for Japanese to utter and shorter in duration, but the opposite was found in the experiment. This suggests that the features adopted for native English speakers as readability indicators are not fully compatible with Japanese speakers.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"379 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":"132831839","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/UV56588.2022.10185469
Jiawei Ruan
The opinion dynamics, which utilizes mathematical and physical models to investigate the spreading of opinions in social networks, has drawn attention of researchers in related fields these years, on its excellent performance in evaluating and predicting the public mind on various general issues. In this paper, inspired by the Spiral of Silence (SOS) theory that shows people tend to alter their opinion to be confirmed with the dominant one considering the fear to be isolated, a novel Dynamical Weight Hegselmann-Krause (DWHK) model is proposed. Specifically, the variation of interpersonal influence as opinion spread in the community is considered, represented by dynamic weight in networks according to the SOS theory. Extensive experiments in different types of networks show the effectiveness and efficiency of the proposed model, considering the crowds corresponding to specific kinds of the spiral of silence.
{"title":"A Novel Dynamical Weight Hegselmann–Krause Model based on Spiral of Silence","authors":"Jiawei Ruan","doi":"10.1109/UV56588.2022.10185469","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185469","url":null,"abstract":"The opinion dynamics, which utilizes mathematical and physical models to investigate the spreading of opinions in social networks, has drawn attention of researchers in related fields these years, on its excellent performance in evaluating and predicting the public mind on various general issues. In this paper, inspired by the Spiral of Silence (SOS) theory that shows people tend to alter their opinion to be confirmed with the dominant one considering the fear to be isolated, a novel Dynamical Weight Hegselmann-Krause (DWHK) model is proposed. Specifically, the variation of interpersonal influence as opinion spread in the community is considered, represented by dynamic weight in networks according to the SOS theory. Extensive experiments in different types of networks show the effectiveness and efficiency of the proposed model, considering the crowds corresponding to specific kinds of the spiral of silence.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"47 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":"133304830","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/UV56588.2022.10185501
Xuefei Huang, Wei Ke, Hao Sheng
Video caption is the automatically generated of abstract expressions for the content contained in videos. It involves two important fields — computer vision and natural language processing, and has become a considerable research topic in smart life. Deep learning has successfully contributed to this task with good results. As we know, video contains various modals of information, yet most of the existing solutions start from the visual perspective of video, while ignoring the equally important audio modal information. Therefore, how to benefit from additional forms of cues other than visual information is a huge challenge. In this work, we propose a video caption generation method that fuses multimodal features in videos, and adds attention mechanism to improve the quality of generated description sentences. The experimental results demonstrate that the method is well validated on the MSR-VTT dataset.
{"title":"Enhanced Video Caption Generation Based on Multimodal Features","authors":"Xuefei Huang, Wei Ke, Hao Sheng","doi":"10.1109/UV56588.2022.10185501","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185501","url":null,"abstract":"Video caption is the automatically generated of abstract expressions for the content contained in videos. It involves two important fields — computer vision and natural language processing, and has become a considerable research topic in smart life. Deep learning has successfully contributed to this task with good results. As we know, video contains various modals of information, yet most of the existing solutions start from the visual perspective of video, while ignoring the equally important audio modal information. Therefore, how to benefit from additional forms of cues other than visual information is a huge challenge. In this work, we propose a video caption generation method that fuses multimodal features in videos, and adds attention mechanism to improve the quality of generated description sentences. The experimental results demonstrate that the method is well validated on the MSR-VTT dataset.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"71 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":"133315364","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/UV56588.2022.10185511
Ting He, Yufan Wen, Mingen Huo
As a distributed energy technology, hybrid solar-fossil fuel energy system (HS-FFES) has characteristics not only in the hybrid utilization of the renewable and conventional energy, but also in the efficient storage of thermal energy. The HS-FFES system obtains outstanding performance in upgrading solar heat to high-grade solar fuel and storing thermochemical energy with high energy density. However, investigations on the dynamic behaviors are inadequate. This paper constructs a dynamic model including the thermal inertia, reaction kinetics and turbomachinery rotational inertia. Then, the design/off-design working condition properties are presented to show the non-linearity of this system. Last, several typical day scenarios under different building types, seasons and cities were simulated. Simulation results show that the proposed HS-FFES can reach high efficiency with energy saving rate above 35 percent.
{"title":"Dynamical Simulation Study of Hybrid Solar-Fossil Fuel Thermochemical Storage and Electricity, Heat and Cold Generation System","authors":"Ting He, Yufan Wen, Mingen Huo","doi":"10.1109/UV56588.2022.10185511","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185511","url":null,"abstract":"As a distributed energy technology, hybrid solar-fossil fuel energy system (HS-FFES) has characteristics not only in the hybrid utilization of the renewable and conventional energy, but also in the efficient storage of thermal energy. The HS-FFES system obtains outstanding performance in upgrading solar heat to high-grade solar fuel and storing thermochemical energy with high energy density. However, investigations on the dynamic behaviors are inadequate. This paper constructs a dynamic model including the thermal inertia, reaction kinetics and turbomachinery rotational inertia. Then, the design/off-design working condition properties are presented to show the non-linearity of this system. Last, several typical day scenarios under different building types, seasons and cities were simulated. Simulation results show that the proposed HS-FFES can reach high efficiency with energy saving rate above 35 percent.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"16 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":"114379280","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/UV56588.2022.10185491
Cui Wang, Wei Ke, Zewei Wu, Z. Xiong
Pedestrian tracking studies have been facilitated by a large amount of surveillance apparatus in the city while also raising public privacy concerns. In this paper, we propose X-Tracking, a privacy-aware pedestrian tracking paradigm designed for vision systems in Smart City. It allows low-cost compatibility with existing surveillance architecture. To protect entities’ privacy, X-Tracking uses video pre-processing with desensitization so that identity information is unexposed to the tracking algorithm. We implement system-level privacy protection by redesigning the tracking framework that decouples all services based on a single responsibility principle. Then, we elaborate on the roles, behaviors, and protocols used in the new system and illustrate how the paradigm strikes a favorable balance between privacy protection and convenience services. Furthermore, we propose a new tracking task that aims to track humans in masking surveillance video. It is comparable to previous tracking tasks but considering the target with a distorted appearance poses new challenges for visual tracking. Finally, we evaluate the baseline algorithm on the task with a demo dataset.
{"title":"A Multi-Hypothesis Tracker with Enhanced Appearance Model for Generic Crowded Scene","authors":"Cui Wang, Wei Ke, Zewei Wu, Z. Xiong","doi":"10.1109/UV56588.2022.10185491","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185491","url":null,"abstract":"Pedestrian tracking studies have been facilitated by a large amount of surveillance apparatus in the city while also raising public privacy concerns. In this paper, we propose X-Tracking, a privacy-aware pedestrian tracking paradigm designed for vision systems in Smart City. It allows low-cost compatibility with existing surveillance architecture. To protect entities’ privacy, X-Tracking uses video pre-processing with desensitization so that identity information is unexposed to the tracking algorithm. We implement system-level privacy protection by redesigning the tracking framework that decouples all services based on a single responsibility principle. Then, we elaborate on the roles, behaviors, and protocols used in the new system and illustrate how the paradigm strikes a favorable balance between privacy protection and convenience services. Furthermore, we propose a new tracking task that aims to track humans in masking surveillance video. It is comparable to previous tracking tasks but considering the target with a distorted appearance poses new challenges for visual tracking. Finally, we evaluate the baseline algorithm on the task with a demo dataset.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"9 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":"115161172","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/UV56588.2022.10185502
Boxuan Lai, Hongjun Chen
As the global pandemic becomes inevitable, it is necessary to promote large-scale vaccination as quickly as possible. This paper studies the allocation of COVID-19 vaccine in urban areas. First, the Wave-net method is used to predict the trend of future vaccination, and then the prediction results are fitted to obtain a mathematical model of vaccination in the next 90 days. Then, according to the queuing model, taking Daoli District and Gongshu District as examples, the policies of vaccine distribution in cities with different levels of development are analyzed. Finally, some practical suggestions on vaccine allocation in different cities are given.
{"title":"A COVID-19 Vaccine Allocation Scheme Based on Queuing Model","authors":"Boxuan Lai, Hongjun Chen","doi":"10.1109/UV56588.2022.10185502","DOIUrl":"https://doi.org/10.1109/UV56588.2022.10185502","url":null,"abstract":"As the global pandemic becomes inevitable, it is necessary to promote large-scale vaccination as quickly as possible. This paper studies the allocation of COVID-19 vaccine in urban areas. First, the Wave-net method is used to predict the trend of future vaccination, and then the prediction results are fitted to obtain a mathematical model of vaccination in the next 90 days. Then, according to the queuing model, taking Daoli District and Gongshu District as examples, the policies of vaccine distribution in cities with different levels of development are analyzed. Finally, some practical suggestions on vaccine allocation in different cities are given.","PeriodicalId":211011,"journal":{"name":"2022 6th International Conference on Universal Village (UV)","volume":"26 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":"123386788","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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