Pub Date : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651099
Wenjie Tu, Kun-Sheng Tseng
This paper presents a simulation on fault diagnosis technology in signal problems of the air and fuel (A/F) system of marine diesel engine. The research method is used the fault tree analysis (FTA) to analyze the signal problems through expert experiences into a tree diagram and to find out the cause of fault. Then, set the tag to different characteristics, the Kernel Principal Component Analysis (KPCA) is used to reduce the dimensionality and feature extraction of the data, it reduces the computational time and defines the relevance of the fault cause with the alarm sensor. For classification and fault diagnosis technology, the Support Vector Machine (SVM) with optimized characteristics is used to train the model. The experimental results show that the proposed techniques would be improved the accuracy and it will help the marine officers to shorten the debugging time and problem diagnosis time.
{"title":"A Simulation on Fault Diagnosis Technology with Air and Fuel (A/F) System of Marine Diesel Engine","authors":"Wenjie Tu, Kun-Sheng Tseng","doi":"10.1109/ISPACS51563.2021.9651099","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651099","url":null,"abstract":"This paper presents a simulation on fault diagnosis technology in signal problems of the air and fuel (A/F) system of marine diesel engine. The research method is used the fault tree analysis (FTA) to analyze the signal problems through expert experiences into a tree diagram and to find out the cause of fault. Then, set the tag to different characteristics, the Kernel Principal Component Analysis (KPCA) is used to reduce the dimensionality and feature extraction of the data, it reduces the computational time and defines the relevance of the fault cause with the alarm sensor. For classification and fault diagnosis technology, the Support Vector Machine (SVM) with optimized characteristics is used to train the model. The experimental results show that the proposed techniques would be improved the accuracy and it will help the marine officers to shorten the debugging time and problem diagnosis time.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121206669","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651047
Ehtesham Iqbal, Asim Niaz, A. Munir, K. Choi
Level set models are extensively used for image segmentation because of their capability to handle topological changes. In this paper, the proposed model uses combined local image information and global image information to evolve the con-tour around the object boundary, making it robust, irrespective of the inhomogeneity. The proposed model is capable to deal with bias conditions, such as intensity inhomogeneity and light effects. We test this model on synthetic, and real images, confirming its superiority over previous models.
{"title":"Hybrid Active Contour Model for Segmentation of Synthetic and Real Images","authors":"Ehtesham Iqbal, Asim Niaz, A. Munir, K. Choi","doi":"10.1109/ISPACS51563.2021.9651047","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651047","url":null,"abstract":"Level set models are extensively used for image segmentation because of their capability to handle topological changes. In this paper, the proposed model uses combined local image information and global image information to evolve the con-tour around the object boundary, making it robust, irrespective of the inhomogeneity. The proposed model is capable to deal with bias conditions, such as intensity inhomogeneity and light effects. We test this model on synthetic, and real images, confirming its superiority over previous models.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123712084","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651001
Hideaki Tanaka, A. Taguchi
This paper presents a contrast enhancement method for images with low contrast areas due to uneven illumination. The multi-scale retinex (MSR) is an excellent contrast enhancement method for such images. However, MSR contains many parameters to be determined and it is not easy to determine those parameters properly. In the proposed method, the dynamic range of the entire image is maintained by adding the single scale retinex (SSR) result to the scaled original image, and the contrast is effectively improved. The proposed method has few parameters to be determined. Therefore, it is clarified that the parameters can be determined by specifying the difference between the average values of the whole image before and after enhancement.
{"title":"Image Contrast Enhancement with High Dynamic Range using Singlescale Retinex","authors":"Hideaki Tanaka, A. Taguchi","doi":"10.1109/ISPACS51563.2021.9651001","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651001","url":null,"abstract":"This paper presents a contrast enhancement method for images with low contrast areas due to uneven illumination. The multi-scale retinex (MSR) is an excellent contrast enhancement method for such images. However, MSR contains many parameters to be determined and it is not easy to determine those parameters properly. In the proposed method, the dynamic range of the entire image is maintained by adding the single scale retinex (SSR) result to the scaled original image, and the contrast is effectively improved. The proposed method has few parameters to be determined. Therefore, it is clarified that the parameters can be determined by specifying the difference between the average values of the whole image before and after enhancement.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123745827","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651092
Shi-Jim Yen, Shi Ye, Chen-Ling Lee
Doctors often observe the appearance of the tongue for diagnosis, especially in Traditional Chinese Medicine (TCM), but also the shape and color of the tongue have been clearly classified. In the past, the machine to judge the appearance of the tongue, mostly with a high-resolution camera with strict shooting environment control to graphics recognition, there are more restrictions on use. This study is based on the development of mobile tongue image recognition, with the camera of a typical mobile device, and without limiting the shooting environment, and is designed as a Bot on community software, as long as there is a mobile device connected to the Internet, greatly increasing convenience. Not only can doctors use it when seeing a patient, but also allow patients to measure at home and monitor the condition at any time.
{"title":"Traditional Chinese Medicine Online Intelligent Tongue Diagnosis Bot","authors":"Shi-Jim Yen, Shi Ye, Chen-Ling Lee","doi":"10.1109/ISPACS51563.2021.9651092","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651092","url":null,"abstract":"Doctors often observe the appearance of the tongue for diagnosis, especially in Traditional Chinese Medicine (TCM), but also the shape and color of the tongue have been clearly classified. In the past, the machine to judge the appearance of the tongue, mostly with a high-resolution camera with strict shooting environment control to graphics recognition, there are more restrictions on use. This study is based on the development of mobile tongue image recognition, with the camera of a typical mobile device, and without limiting the shooting environment, and is designed as a Bot on community software, as long as there is a mobile device connected to the Internet, greatly increasing convenience. Not only can doctors use it when seeing a patient, but also allow patients to measure at home and monitor the condition at any time.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115540633","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651035
W. Shyr, C. Chiou, C. Lin
This study uses the expansion augmented reality technology combined with the virtual integration networking platform to realize the maintenance and diagnosis of equipment guarantee for engineers in the factory production line, as well as the establishment of the basic process of equipment operation, regular inspection of equipment to maintain the normal operation of production line equipment major tasks. Equipment operators in factory production lines are subject to rigorous education and training, with varying quality differences among employees, and some require experienced operators to be effective in achieving operational efficiency. In addition, in response to the rapid changes in the global pneumonia epidemic (COVID-19) and the mature development of Internet of Things technology to change the operating mode of most industries in Taiwan, the problem of personnel diversion to work groups, the data adjustment of traditional production line equipment parameters depended on paper records, data experience is not easy to pass on.
{"title":"Expansion augmented reality technology applied to the maintenance and diagnosis of equipment","authors":"W. Shyr, C. Chiou, C. Lin","doi":"10.1109/ISPACS51563.2021.9651035","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651035","url":null,"abstract":"This study uses the expansion augmented reality technology combined with the virtual integration networking platform to realize the maintenance and diagnosis of equipment guarantee for engineers in the factory production line, as well as the establishment of the basic process of equipment operation, regular inspection of equipment to maintain the normal operation of production line equipment major tasks. Equipment operators in factory production lines are subject to rigorous education and training, with varying quality differences among employees, and some require experienced operators to be effective in achieving operational efficiency. In addition, in response to the rapid changes in the global pneumonia epidemic (COVID-19) and the mature development of Internet of Things technology to change the operating mode of most industries in Taiwan, the problem of personnel diversion to work groups, the data adjustment of traditional production line equipment parameters depended on paper records, data experience is not easy to pass on.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116045291","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9650979
Chun-Chen Yao, Jun-Yuan Zheng, Jau‐Ji Jou, Chun-Liang Yang
Advances in high-speed communication network technologies have spurred interest in signal performance monitoring. This study proposed a 25-Gb/s non-return-to-zero (NRZ) signal performance monitoring method using an artificial neural network (ANN), which can estimate the five parameters of Q factor, signal-to-noise ratio, time jitter, rise time, and fall time. Using 5000 data sets and adopting seven neurons in the hidden layer, the mean relative errors of the five estimated parameters are about 5.76% to 11.74%. This parameter extraction technique based on machine learning can apply to real-time optical network performance monitoring for high-speed NRZ signals.
{"title":"Performance Monitoring of High-Speed NRZ Signals Using Machine Learning Techniques","authors":"Chun-Chen Yao, Jun-Yuan Zheng, Jau‐Ji Jou, Chun-Liang Yang","doi":"10.1109/ISPACS51563.2021.9650979","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9650979","url":null,"abstract":"Advances in high-speed communication network technologies have spurred interest in signal performance monitoring. This study proposed a 25-Gb/s non-return-to-zero (NRZ) signal performance monitoring method using an artificial neural network (ANN), which can estimate the five parameters of Q factor, signal-to-noise ratio, time jitter, rise time, and fall time. Using 5000 data sets and adopting seven neurons in the hidden layer, the mean relative errors of the five estimated parameters are about 5.76% to 11.74%. This parameter extraction technique based on machine learning can apply to real-time optical network performance monitoring for high-speed NRZ signals.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"660 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114057446","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651131
Bojun Zheng, Takefumi Masuda, Tsugumichi Shibata
Utilization of machine learning is effective in improving the accuracy of indoor positioning systems. We constructed an experimental positioning trial system in our laboratory for the study of watching over the elderly using a wearable sensor with the air interface of EnOcean wireless standard. The results confirmed that the position estimation accuracy was improved by applying machine learning using a neural network model of TensorFlow. The neural network enables highly accurate position estimation in consideration of the complex indoor radio wave environment by learning the mapping from the RSS data space to the physical space. In this paper, we show the necessity of machine learning based on the observed RSS data set and illustrate the effect of improving accuracy for the case of EnOcean air interface.
{"title":"An Indoor Positioning with a Neural Network Model of TensorFlow for Machine Learning","authors":"Bojun Zheng, Takefumi Masuda, Tsugumichi Shibata","doi":"10.1109/ISPACS51563.2021.9651131","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651131","url":null,"abstract":"Utilization of machine learning is effective in improving the accuracy of indoor positioning systems. We constructed an experimental positioning trial system in our laboratory for the study of watching over the elderly using a wearable sensor with the air interface of EnOcean wireless standard. The results confirmed that the position estimation accuracy was improved by applying machine learning using a neural network model of TensorFlow. The neural network enables highly accurate position estimation in consideration of the complex indoor radio wave environment by learning the mapping from the RSS data space to the physical space. In this paper, we show the necessity of machine learning based on the observed RSS data set and illustrate the effect of improving accuracy for the case of EnOcean air interface.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128597613","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651030
K. Funaki
We have already proposed ℓ2-norm regularized TV-CAR speech analysis for an analytic signal that can suppress rapid spectral changes in time-domain and frequency-domain. We have already evaluated the performance using F0 estimation for noise corrupted speech with additive white Gauss noise or Pink noise. The IRAPT algorithm implemented the F0 estimation for the estimated complex AR residual from an analytic signal. We have found that a bone-conducted (BC) pre-filter makes it possible to improve the performance since the BC filter can suppress the additional noise. The BC characteristics are that of a low pass filter; as a result, a first-order AR filter can simulate the BC filter. This paper introduces first-order and second-order AR filters as the pre-filter to improve the F0 estimation performance.
{"title":"On an improvement of F0 estimation based on ℓ2-norm regularized TV-CAR speech analysis using AR pre-filter","authors":"K. Funaki","doi":"10.1109/ISPACS51563.2021.9651030","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651030","url":null,"abstract":"We have already proposed ℓ2-norm regularized TV-CAR speech analysis for an analytic signal that can suppress rapid spectral changes in time-domain and frequency-domain. We have already evaluated the performance using F0 estimation for noise corrupted speech with additive white Gauss noise or Pink noise. The IRAPT algorithm implemented the F0 estimation for the estimated complex AR residual from an analytic signal. We have found that a bone-conducted (BC) pre-filter makes it possible to improve the performance since the BC filter can suppress the additional noise. The BC characteristics are that of a low pass filter; as a result, a first-order AR filter can simulate the BC filter. This paper introduces first-order and second-order AR filters as the pre-filter to improve the F0 estimation performance.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128982156","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 : 2021-11-16DOI: 10.1109/ISPACS51563.2021.9651109
An oblivious signature is a digital signature with some property. The oblivious signature scheme has two parties, the signer and the receiver. First, the receiver can choose one and get one of n valid signatures without knowing the signer’s private key. Second, the signer does not know which signature is chosen by the receiver. In this paper, we propose the oblivious signature which is combined with blind signature and zero-knowledge set membership. The property of blind signature makes sure that the signer does not know the message of the signature by the receiver chosen, on the other hand, the property of the zero-knowledge set membership makes sure that the message of the signature by the receiver chosen is one of the set original messages.
{"title":"Oblivious Signature based on Blind Signature and Zero-Knowledge Set Membership","authors":"","doi":"10.1109/ISPACS51563.2021.9651109","DOIUrl":"https://doi.org/10.1109/ISPACS51563.2021.9651109","url":null,"abstract":"An oblivious signature is a digital signature with some property. The oblivious signature scheme has two parties, the signer and the receiver. First, the receiver can choose one and get one of n valid signatures without knowing the signer’s private key. Second, the signer does not know which signature is chosen by the receiver. In this paper, we propose the oblivious signature which is combined with blind signature and zero-knowledge set membership. The property of blind signature makes sure that the signer does not know the message of the signature by the receiver chosen, on the other hand, the property of the zero-knowledge set membership makes sure that the message of the signature by the receiver chosen is one of the set original messages.","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"1 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114099273","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 : 2021-11-16DOI: 10.1109/ispacs51563.2021.9650932
{"title":"[Copyright notice]","authors":"","doi":"10.1109/ispacs51563.2021.9650932","DOIUrl":"https://doi.org/10.1109/ispacs51563.2021.9650932","url":null,"abstract":"","PeriodicalId":359822,"journal":{"name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114623874","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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