{"title":"ICONS 2022: International Conference on Neuromorphic Systems, Knoxville, TN, USA, July 27 - 29, 2022","authors":"","doi":"10.1145/3546790","DOIUrl":"https://doi.org/10.1145/3546790","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80554584","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}
{"title":"ICONS 2021: International Conference on Neuromorphic Systems 2021, Knoxville, TN, USA, July 27-29, 2021","authors":"","doi":"10.1145/3477145","DOIUrl":"https://doi.org/10.1145/3477145","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87119469","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}
Sreerag R K, Shobin S, Vishnu A, Vivek Sasidharan, Sudheesh Kumar C. P.
Rainfall creates noise as it strikes roofing sheets and most of the time this noise causes a lot of disturbance and distractions to the occupants. A simulation study using COMSOL Multiphysics is presented in this paper to predict the rainfall induced noise inside a room with roofing sheet. The main aim of the present study is to observe the effects of various roof structure parameters (material, profile, thickness and the slope with which the sheets are placed) on the rainfall induced noise inside the room. The results presented in this paper will help the industry to manufacture roofing sheets that can play a major role in significantly reducing rainfall induced noise.
{"title":"Influence of Roofing Sheet Geometry on Reduction of Rainfall Induced Noise","authors":"Sreerag R K, Shobin S, Vishnu A, Vivek Sasidharan, Sudheesh Kumar C. P.","doi":"10.2139/ssrn.3791071","DOIUrl":"https://doi.org/10.2139/ssrn.3791071","url":null,"abstract":"Rainfall creates noise as it strikes roofing sheets and most of the time this noise causes a lot of disturbance and distractions to the occupants. A simulation study using COMSOL Multiphysics is presented in this paper to predict the rainfall induced noise inside a room with roofing sheet. The main aim of the present study is to observe the effects of various roof structure parameters (material, profile, thickness and the slope with which the sheets are placed) on the rainfall induced noise inside the room. The results presented in this paper will help the industry to manufacture roofing sheets that can play a major role in significantly reducing rainfall induced noise.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89178794","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}
{"title":"Proceedings of the International Conference on Neuromorphic Systems, ICONS 2020, Oak Ridge, Tennessee, USA, July, 2020","authors":"","doi":"10.1145/3407197","DOIUrl":"https://doi.org/10.1145/3407197","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79026201","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 : 2019-11-01DOI: 10.1109/ICSAI48974.2019.9010366
Z. Kai, Xie Yuan, Li Shaopeng, He Yaoting
Permanent magnet synchronous motor (PMSM) has a wide range of applications. For its nonlinear and strong coupling characteristics, a vector control scheme for permanent magnet synchronous motor based on proportional resonance (PR) control is proposed. The mathematical model of permanent magnet synchronous motor is established. The principle of proportional resonance control is analyzed. The three-phase PMSM vector control system based on PR controller is designed and built with MATLAB simulation tool. Compared with the PI control in the traditional current closed-loop control, the simulation results show that the proposed method is relatively simple, improve the robustness of the control system, and meet the high-performance vector control of permanent magnet synchronous motor.
{"title":"Vector Control of PMSM Based on Proportional Resonance Control","authors":"Z. Kai, Xie Yuan, Li Shaopeng, He Yaoting","doi":"10.1109/ICSAI48974.2019.9010366","DOIUrl":"https://doi.org/10.1109/ICSAI48974.2019.9010366","url":null,"abstract":"Permanent magnet synchronous motor (PMSM) has a wide range of applications. For its nonlinear and strong coupling characteristics, a vector control scheme for permanent magnet synchronous motor based on proportional resonance (PR) control is proposed. The mathematical model of permanent magnet synchronous motor is established. The principle of proportional resonance control is analyzed. The three-phase PMSM vector control system based on PR controller is designed and built with MATLAB simulation tool. Compared with the PI control in the traditional current closed-loop control, the simulation results show that the proposed method is relatively simple, improve the robustness of the control system, and meet the high-performance vector control of permanent magnet synchronous motor.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90985671","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 : 2019-11-01DOI: 10.1109/ICSAI48974.2019.9010467
C. Ning, Hou Yaochun, Wu Dazhuan, Ali Mohammed Djafari
Recently infrared thermal imaging with high-precision has been widely investigated to detect abnormal thermal defects caused by current leakage, component heating and temperature fluctuation etc. However, two major factors seriously limit the imaging precision: measure uncertainty and small dataset. Therefore, this paper presents a variational Bayesian inference (VBI) with sparsity-enforcing prior so as to solve the above challenges. Though the sampled information is incomplete and measurement error are not trivial, especially in fault diagnosis of electrical power system, the advantages of VBI are that Bayesian cost function will still combine prior model (of abnormal thermal source) and likelihood model (of measurement errors) together to regulate the uncertainty from both physics and measurements. Meanwhile, sparsity priors of irregular temperature features will not only embody the health characteristics of electrical device, but also reduce the dimension of prior model parameters. Such sparsity priors will be modelled in terms of the sparsity-enforcing distributions. Indeed, most of signals can be sparsely represented in certain transformed domain and key knowledge of signatures will be deeply studied using sparse samples rather than condensed data. More importantly, both the prior model and cost function will be trained on-line and updated according to actual and historical data, instead of replying only on definite mechanisms or empirical rules which are hard to be adapted in industry application. Moreover, the proposed method can calibrate the uncertainty of conventional thermal radiation model by updating the model hyper-parameters and latent variables. Through a moderate infrared sensor, results of thermal imaging on ABB controllers and Schneider switches etc. confirm that proposed VBI has the advantages of high-precision( 2.0m) and fast inspection (<.8s for 160x120 pixels), and it is cost-effective to fast detect abnormal thermal sources.
{"title":"A Variational Bayesian Inference with Small Dataset for High-Precision Infrared Thermal Imaging","authors":"C. Ning, Hou Yaochun, Wu Dazhuan, Ali Mohammed Djafari","doi":"10.1109/ICSAI48974.2019.9010467","DOIUrl":"https://doi.org/10.1109/ICSAI48974.2019.9010467","url":null,"abstract":"Recently infrared thermal imaging with high-precision has been widely investigated to detect abnormal thermal defects caused by current leakage, component heating and temperature fluctuation etc. However, two major factors seriously limit the imaging precision: measure uncertainty and small dataset. Therefore, this paper presents a variational Bayesian inference (VBI) with sparsity-enforcing prior so as to solve the above challenges. Though the sampled information is incomplete and measurement error are not trivial, especially in fault diagnosis of electrical power system, the advantages of VBI are that Bayesian cost function will still combine prior model (of abnormal thermal source) and likelihood model (of measurement errors) together to regulate the uncertainty from both physics and measurements. Meanwhile, sparsity priors of irregular temperature features will not only embody the health characteristics of electrical device, but also reduce the dimension of prior model parameters. Such sparsity priors will be modelled in terms of the sparsity-enforcing distributions. Indeed, most of signals can be sparsely represented in certain transformed domain and key knowledge of signatures will be deeply studied using sparse samples rather than condensed data. More importantly, both the prior model and cost function will be trained on-line and updated according to actual and historical data, instead of replying only on definite mechanisms or empirical rules which are hard to be adapted in industry application. Moreover, the proposed method can calibrate the uncertainty of conventional thermal radiation model by updating the model hyper-parameters and latent variables. Through a moderate infrared sensor, results of thermal imaging on ABB controllers and Schneider switches etc. confirm that proposed VBI has the advantages of high-precision( 2.0m) and fast inspection (<.8s for 160x120 pixels), and it is cost-effective to fast detect abnormal thermal sources.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87521757","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 : 2016-11-01DOI: 10.1109/ICSAI.2016.7811036
Xiong Peng
The identity of the vehicle is the only legal identification of the vehicle at the trusted center. It is directly related to the information of the vehicle user, and the anonymous authentication of the vehicle identity is an embodiment of the user privacy protection. Based on this, an on-board network anonymous authentication protocol is designed on the basis of certificateless signature scheme. The protocol does not require certificate management and there is no key escrow problem. The results show that the protocol authentication efficiency is significantly higher than that of the certificate-based authentication protocol and the identity-based authentication protocol, while satisfying the requirements of anonymity, non-repudiation, mutual authentication, conditional privacy protection and Anti-replay aggression.
{"title":"A novel authentication protocol for vehicle network","authors":"Xiong Peng","doi":"10.1109/ICSAI.2016.7811036","DOIUrl":"https://doi.org/10.1109/ICSAI.2016.7811036","url":null,"abstract":"The identity of the vehicle is the only legal identification of the vehicle at the trusted center. It is directly related to the information of the vehicle user, and the anonymous authentication of the vehicle identity is an embodiment of the user privacy protection. Based on this, an on-board network anonymous authentication protocol is designed on the basis of certificateless signature scheme. The protocol does not require certificate management and there is no key escrow problem. The results show that the protocol authentication efficiency is significantly higher than that of the certificate-based authentication protocol and the identity-based authentication protocol, while satisfying the requirements of anonymity, non-repudiation, mutual authentication, conditional privacy protection and Anti-replay aggression.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82767869","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 : 2016-11-01DOI: 10.1109/ICSAI.2016.7810944
Du Liyong, Li Guangkai, Wang Qinghong, Yang Xu, W. Peng
This paper researches a new distribution network reconfiguration method considering access of energy storage devices. Firstly, a new distribution network reconfiguration model considering access of energy storage devices is built. This model takes the minimum of network losses as objective function and considers the new constraints of power and voltage caused by the energy storage devices. The dual power flow directions are also considered in reconfiguration schemes. The improved genetic algorithm is adopted to solve the proposed model to get the optimal reconfiguration scheme. Lastly, two distribution networks with access of energy storage devices are tested to verify the correctness and effectiveness of proposed method.
{"title":"Distribution network reconfiguration method considering energy storage devices","authors":"Du Liyong, Li Guangkai, Wang Qinghong, Yang Xu, W. Peng","doi":"10.1109/ICSAI.2016.7810944","DOIUrl":"https://doi.org/10.1109/ICSAI.2016.7810944","url":null,"abstract":"This paper researches a new distribution network reconfiguration method considering access of energy storage devices. Firstly, a new distribution network reconfiguration model considering access of energy storage devices is built. This model takes the minimum of network losses as objective function and considers the new constraints of power and voltage caused by the energy storage devices. The dual power flow directions are also considered in reconfiguration schemes. The improved genetic algorithm is adopted to solve the proposed model to get the optimal reconfiguration scheme. Lastly, two distribution networks with access of energy storage devices are tested to verify the correctness and effectiveness of proposed method.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79150432","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 : 2016-11-01DOI: 10.1109/ICSAI.2016.7811068
Song Xuchen, Gao Xue, Ding Yanfang, W. Zhixin
Convolutional neural networks (CNN) is a powerful technology for classification of visual inputs. However, both the scale and quality of the training set are an important factor to the performance of a learned system. In real applications, it is generally difficult to obtain a high-quality and large-scale handwritten Chinese characters sample set. Insufficient samples of handwritten Chinese characters would cause poor recognition performance. In this paper, we propose a handwritten Chinese character recognition method based on dataset expansion and CNNs. Firstly, the topology of proposed Convolutional neural networks model is addressed. Then, several dataset expansion techniques are utilized to expand the scale of available samples, which include random elastic deformation, shear transformation and rotation within a small range, etc. A series of experiments on the HCL2000 Chinese character handwriting database have shown that our method can effectively improve the recognition performance, with a reduction in error rate of 35.01%, verified the effectiveness of our proposed approach.
{"title":"A handwritten Chinese characters recognition method based on sample set expansion and CNN","authors":"Song Xuchen, Gao Xue, Ding Yanfang, W. Zhixin","doi":"10.1109/ICSAI.2016.7811068","DOIUrl":"https://doi.org/10.1109/ICSAI.2016.7811068","url":null,"abstract":"Convolutional neural networks (CNN) is a powerful technology for classification of visual inputs. However, both the scale and quality of the training set are an important factor to the performance of a learned system. In real applications, it is generally difficult to obtain a high-quality and large-scale handwritten Chinese characters sample set. Insufficient samples of handwritten Chinese characters would cause poor recognition performance. In this paper, we propose a handwritten Chinese character recognition method based on dataset expansion and CNNs. Firstly, the topology of proposed Convolutional neural networks model is addressed. Then, several dataset expansion techniques are utilized to expand the scale of available samples, which include random elastic deformation, shear transformation and rotation within a small range, etc. A series of experiments on the HCL2000 Chinese character handwriting database have shown that our method can effectively improve the recognition performance, with a reduction in error rate of 35.01%, verified the effectiveness of our proposed approach.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77546093","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 : 2016-09-07DOI: 10.1007/978-3-319-48944-5_18
A. Alessandrini, P. D. Site, D. Stam, V. Gatta, E. Marcucci, Qing Zhang
{"title":"Using Repeated-Measurement Stated Preference Data to Investigate Users’ Attitudes Towards Automated Buses Within Major Facilities","authors":"A. Alessandrini, P. D. Site, D. Stam, V. Gatta, E. Marcucci, Qing Zhang","doi":"10.1007/978-3-319-48944-5_18","DOIUrl":"https://doi.org/10.1007/978-3-319-48944-5_18","url":null,"abstract":"","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91398173","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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