2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)最新文献
Pub Date : 2021-11-24DOI: 10.1109/SNPD51163.2021.9705007
Kento Matsuba, S. Saiki, Masahide Nakamura
In this study, we conducted a multifaceted analysis of heatstroke cases using the emergency transported big data in Kobe City, and discovered the characteristics of heatstroke incidents in Kobe City in 2020 that differed from previous years. As a result of the analysis, it was found that the peak period of WBGT in 2020 was later than usual, and it was found that the peak period of WBGT is later than usual in 2020, and the occurrences of heatstroke in 2020 is characterized by an increase in the occurrences of heatstroke in people over 65 years old and outdoors, and a decrease in the occurrences of heatstroke in people under 65 years old and indoors.
{"title":"Analyzing heatstroke patients in 2020 using Emergency Big Data","authors":"Kento Matsuba, S. Saiki, Masahide Nakamura","doi":"10.1109/SNPD51163.2021.9705007","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9705007","url":null,"abstract":"In this study, we conducted a multifaceted analysis of heatstroke cases using the emergency transported big data in Kobe City, and discovered the characteristics of heatstroke incidents in Kobe City in 2020 that differed from previous years. As a result of the analysis, it was found that the peak period of WBGT in 2020 was later than usual, and it was found that the peak period of WBGT is later than usual in 2020, and the occurrences of heatstroke in 2020 is characterized by an increase in the occurrences of heatstroke in people over 65 years old and outdoors, and a decrease in the occurrences of heatstroke in people under 65 years old and indoors.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133315132","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704964
Qi-Xian Huang, Shu-Pei Shi, Guo-Shiang Lin, D. Shen, Hung-Min Sun
In this paper, we use Deep Convolutional Generative Adversarial Networks (DCGANs) method to generate more images with multiple views to increase our dataset diversity. We use 3D-model different views for training DCGAN to make interpolation between the leftest and rightest random vectors, which means it can generate leftest to rightest images. After producing many of multi-view images, we combine with CNN based modules called co-attention map generator to look for common features of the same class but in different views clothing. By applying the learned generator to all images, the corresponding co-attention maps are obtained. we can fluently apply the proposed method can function well for multi-view objects on different types of clothing classes.
{"title":"A Co-Attention Method Based on Generative Adversarial Networks for Multi-view Images","authors":"Qi-Xian Huang, Shu-Pei Shi, Guo-Shiang Lin, D. Shen, Hung-Min Sun","doi":"10.1109/SNPD51163.2021.9704964","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704964","url":null,"abstract":"In this paper, we use Deep Convolutional Generative Adversarial Networks (DCGANs) method to generate more images with multiple views to increase our dataset diversity. We use 3D-model different views for training DCGAN to make interpolation between the leftest and rightest random vectors, which means it can generate leftest to rightest images. After producing many of multi-view images, we combine with CNN based modules called co-attention map generator to look for common features of the same class but in different views clothing. By applying the learned generator to all images, the corresponding co-attention maps are obtained. we can fluently apply the proposed method can function well for multi-view objects on different types of clothing classes.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124954710","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704888
Xing Yong Kek, C. Chin, Ye Li
This paper investigates how time scale affects the classification accuracy of log Mel-frequency coefficients and deep scattering spectrum for acoustic scene classification. Currently, log Mel-frequency coefficients has dominated in most acoustic classification task as observed in DCASE challenge. However, log Mel-frequency coefficients have two flaws; the first flaw is the Heisenberg uncertain property of short-time Fourier transform, which is caused by a fixed window size. A trade-off between having high frequency resolution while suffering from poor time resolution and vice versa. The next flaw occurs when applying mel-filter banks along frequency axis, resulting in a loss of information when the time scale is more than 25ms. To overcome this limitation, this paper explored deep scattering spectrum with various window intervals. Following the current framework of log Mel-frequency coefficients integration with convolution neural network, we proposed a two-stage convolution neural network model approach. The two-stage model is designed to tackle the huge disparity in magnitude of the deep scattering spectrum's first and second order coefficients. Next, we explored various feature normalization technique and applied on the input representation directly, thus allowing learning to occur. Lastly, our experimentation uses the DCASE 2020 Task 1a dataset, consisting of acoustic recordings from various environments or scenes and demonstrated that DSS has a slight advantage against MFSC and scored 70.36% and 69.42%, respectively.
{"title":"An Investigation on Multiscale Normalised Deep Scattering Spectrum with Deep Residual Network for Acoustic Scene Classification","authors":"Xing Yong Kek, C. Chin, Ye Li","doi":"10.1109/SNPD51163.2021.9704888","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704888","url":null,"abstract":"This paper investigates how time scale affects the classification accuracy of log Mel-frequency coefficients and deep scattering spectrum for acoustic scene classification. Currently, log Mel-frequency coefficients has dominated in most acoustic classification task as observed in DCASE challenge. However, log Mel-frequency coefficients have two flaws; the first flaw is the Heisenberg uncertain property of short-time Fourier transform, which is caused by a fixed window size. A trade-off between having high frequency resolution while suffering from poor time resolution and vice versa. The next flaw occurs when applying mel-filter banks along frequency axis, resulting in a loss of information when the time scale is more than 25ms. To overcome this limitation, this paper explored deep scattering spectrum with various window intervals. Following the current framework of log Mel-frequency coefficients integration with convolution neural network, we proposed a two-stage convolution neural network model approach. The two-stage model is designed to tackle the huge disparity in magnitude of the deep scattering spectrum's first and second order coefficients. Next, we explored various feature normalization technique and applied on the input representation directly, thus allowing learning to occur. Lastly, our experimentation uses the DCASE 2020 Task 1a dataset, consisting of acoustic recordings from various environments or scenes and demonstrated that DSS has a slight advantage against MFSC and scored 70.36% and 69.42%, respectively.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122129946","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9705015
H. Nieto-Chaupis
Apparition of abnormal vasculature is common at the first phases of tumor growth. It is known as angiogenesis having the whole process various phases. This is also seen as a random migration of cells that require the flux of blood in order to accomplish the consolidation of tumor. This paper provides a hybrid approach by the which it is assumd that sprouting angiogenesis has a well-defined part that would have to be described by classical electrodynamics. A closed-form model that allows to perform computational simulations is presented. In this manner, while the electrically charged compounds such as ions (cations and anions) are described by Coulomb forces, nano particles can be well described by the diffusion equation. According to the model nanoparticles would interact to ions by generating an electric work to cancel cell-ion interactions at the tubular formation of angiogenesis. With this the period of interaction with nano particles is estimated theoretically.
{"title":"Computational Simulation of Charged Nanoparticles Diffusion in Vascular Tissue","authors":"H. Nieto-Chaupis","doi":"10.1109/SNPD51163.2021.9705015","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9705015","url":null,"abstract":"Apparition of abnormal vasculature is common at the first phases of tumor growth. It is known as angiogenesis having the whole process various phases. This is also seen as a random migration of cells that require the flux of blood in order to accomplish the consolidation of tumor. This paper provides a hybrid approach by the which it is assumd that sprouting angiogenesis has a well-defined part that would have to be described by classical electrodynamics. A closed-form model that allows to perform computational simulations is presented. In this manner, while the electrically charged compounds such as ions (cations and anions) are described by Coulomb forces, nano particles can be well described by the diffusion equation. According to the model nanoparticles would interact to ions by generating an electric work to cancel cell-ion interactions at the tubular formation of angiogenesis. With this the period of interaction with nano particles is estimated theoretically.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125253947","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704889
Hayato Ozono, Sinan Chen, Masahide Nakamura
Japan is currently facing super-aging society and the assistive technology for self-help and mutual aid of the elderly is becoming urgent. The purpose of this paper is to build a system that can execute various services through dialogue with agents, in order to support elderly people who cannot use Internet services due to lack of access to devices. To achieve the goal, we discuss a framework for executing microservices using dialogue agents. More specifically, the framework consists of the next two essential elements: (1) Managing user information for the various microservices centrally. (2) Configuring the behavior of the agents when executing the services correctly. In the proposed method, we first discuss each element in detail. Then, we demonstrate the effectiveness of the framework by applying it to the actual integration of a dialogue agent and several microservices.
{"title":"Study of Microservice Execution Framework Using Spoken Dialogue Agents","authors":"Hayato Ozono, Sinan Chen, Masahide Nakamura","doi":"10.1109/SNPD51163.2021.9704889","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704889","url":null,"abstract":"Japan is currently facing super-aging society and the assistive technology for self-help and mutual aid of the elderly is becoming urgent. The purpose of this paper is to build a system that can execute various services through dialogue with agents, in order to support elderly people who cannot use Internet services due to lack of access to devices. To achieve the goal, we discuss a framework for executing microservices using dialogue agents. More specifically, the framework consists of the next two essential elements: (1) Managing user information for the various microservices centrally. (2) Configuring the behavior of the agents when executing the services correctly. In the proposed method, we first discuss each element in detail. Then, we demonstrate the effectiveness of the framework by applying it to the actual integration of a dialogue agent and several microservices.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117014426","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704971
Takumi Akashi, Masahide Nakamura, K. Yasuda, S. Saiki
In this study, we aim to realize an assistive technology that can present necessary information to elderly people with cognitive concerns or dementia in a way that is adaptable to their home life. To achieve this goal, we propose ALPS (Assisted Living by Personalized Speaker), a system that presents appropriate information according to various locations and times in the home. We installs IoT speakers with motion sensors at key locations in the home, and by linking them to ECA(Event-Condition-Action) rules in the cloud, ALPS provides information based on location and time in voice. We implemented a prototype of the proposed ALPS and conducted a case study of two elderly people. As a result, it was found that by defining ECA rules for each problem, the system can present information according to the individual’s lifestyle.
{"title":"Proposal for a Personalized Adaptive Speaker Service to Support the Elderly at Home","authors":"Takumi Akashi, Masahide Nakamura, K. Yasuda, S. Saiki","doi":"10.1109/SNPD51163.2021.9704971","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704971","url":null,"abstract":"In this study, we aim to realize an assistive technology that can present necessary information to elderly people with cognitive concerns or dementia in a way that is adaptable to their home life. To achieve this goal, we propose ALPS (Assisted Living by Personalized Speaker), a system that presents appropriate information according to various locations and times in the home. We installs IoT speakers with motion sensors at key locations in the home, and by linking them to ECA(Event-Condition-Action) rules in the cloud, ALPS provides information based on location and time in voice. We implemented a prototype of the proposed ALPS and conducted a case study of two elderly people. As a result, it was found that by defining ECA rules for each problem, the system can present information according to the individual’s lifestyle.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408738","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9705010
Kenichi Matsumoto
This paper proposes a conceptual framework for developing new technologies that will solve today’s technical issues in software development and operations (DevOps) and support the future software ecosystems. The proposed framework perceives resources essential for software DevOps from three perspectives: products, people, and technical information, and actively utilizes and link the latest digital technologies such as AI, natural language processing, microservices, and blockchain. The goal is not to aim fully automate software DevOps, but also to achieve high economic efficiency and sustainability by eliminating waste in software DevOps, assuming a human-centered society. The principal approaches of new technology development in the framework are "product up-cycling", "placement of the right people and AI in the right places", and "quality control linked to external technical information." New technologies to be developed with these approaches will expand conventional concepts in software DevOps with three dimensions of "reuse," "human resources," and "quality control."
{"title":"Conceptual Framework for Next-Generation Software Ecosystems","authors":"Kenichi Matsumoto","doi":"10.1109/SNPD51163.2021.9705010","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9705010","url":null,"abstract":"This paper proposes a conceptual framework for developing new technologies that will solve today’s technical issues in software development and operations (DevOps) and support the future software ecosystems. The proposed framework perceives resources essential for software DevOps from three perspectives: products, people, and technical information, and actively utilizes and link the latest digital technologies such as AI, natural language processing, microservices, and blockchain. The goal is not to aim fully automate software DevOps, but also to achieve high economic efficiency and sustainability by eliminating waste in software DevOps, assuming a human-centered society. The principal approaches of new technology development in the framework are \"product up-cycling\", \"placement of the right people and AI in the right places\", and \"quality control linked to external technical information.\" New technologies to be developed with these approaches will expand conventional concepts in software DevOps with three dimensions of \"reuse,\" \"human resources,\" and \"quality control.\"","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124461658","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9705002
Souha Ben Hamouda, Wafa Gabsi
One key perspective when communicating with deaf people is sign language recognition. Many experts agree upon the fact that using a system communication is a key for bridging the gap between deaf and non deaf people since ordinary people can not exchange using the sign language. As a result, researchers, deaf people, parents and deaf-mute community are striving to have a bidirectional communication system based on translation with lower costs. The importance of the research is related to its goal of helping these categories of unvoiced people communicate with others and enhance their contributions to growth and capacity building and vice versa.This paper gives an overview of the most used techniques and technologies (gloves, android application, image processing, …) in order to translate sign language to written or spoken language. Furthermore, this paper provides a critical and comparative analysis of the studied approaches and stands out major challenges to overcome their limits. Finally, we propose in this paper a dual way communication system ensuring arabic sign language translation into spoken language based on image processing and deep learning.
{"title":"Arabic sign Language Recognition: Towards a Dual Way Communication System Between Deaf and Non-Deaf People","authors":"Souha Ben Hamouda, Wafa Gabsi","doi":"10.1109/SNPD51163.2021.9705002","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9705002","url":null,"abstract":"One key perspective when communicating with deaf people is sign language recognition. Many experts agree upon the fact that using a system communication is a key for bridging the gap between deaf and non deaf people since ordinary people can not exchange using the sign language. As a result, researchers, deaf people, parents and deaf-mute community are striving to have a bidirectional communication system based on translation with lower costs. The importance of the research is related to its goal of helping these categories of unvoiced people communicate with others and enhance their contributions to growth and capacity building and vice versa.This paper gives an overview of the most used techniques and technologies (gloves, android application, image processing, …) in order to translate sign language to written or spoken language. Furthermore, this paper provides a critical and comparative analysis of the studied approaches and stands out major challenges to overcome their limits. Finally, we propose in this paper a dual way communication system ensuring arabic sign language translation into spoken language based on image processing and deep learning.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121217336","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 : 2021-11-24DOI: 10.1109/snpd51163.2021.9705012
The advancement of image understanding with deep learning neural networks has brought great attraction to those in image analysis into the focus of deep learning networks. The demonstrated capability triggers broad interests of its application into medical image analysis. The characteristics of medical images are extremely different from photos and video images. The application of medical image analysis is also much more critical. For achieving the best effectiveness and feasibility of medical image analysis with deep learning approaches, several issues have to be considered. In this talk we will give a brief overview of the development of neural networks for medical image analysis in the past and the future trends with deep learning. Several issues in regard of the data preparation, techniques, and clinic applications will also be discussed.
{"title":"Keynote Address: Deep Learning Networks for Medical Image Analysis: Its Past, Future, and Issues","authors":"","doi":"10.1109/snpd51163.2021.9705012","DOIUrl":"https://doi.org/10.1109/snpd51163.2021.9705012","url":null,"abstract":"The advancement of image understanding with deep learning neural networks has brought great attraction to those in image analysis into the focus of deep learning networks. The demonstrated capability triggers broad interests of its application into medical image analysis. The characteristics of medical images are extremely different from photos and video images. The application of medical image analysis is also much more critical. For achieving the best effectiveness and feasibility of medical image analysis with deep learning approaches, several issues have to be considered. In this talk we will give a brief overview of the development of neural networks for medical image analysis in the past and the future trends with deep learning. Several issues in regard of the data preparation, techniques, and clinic applications will also be discussed.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115614869","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704925
Yu-Jen Liu, Yuansheng Cheng
Daily used fluorescent lamp or lighting tube is mainly consisted of optical element and power electronic component. The usage of them result in the various distortions on residential electricity supply and impact to power quality due to the nonlinear characteristic from arc phenomenon. In order to seek effectiveness ways for power quality improvement and to prevent any abnormal event on electricity supply, detection work on electric arc becomes important. For the electric arc detection, previous recognition on different arc properties or different forming sources can help to achieve this work. This paper thus propose an idea by using similarity measurement to find the relevance between produced arc signal and the source of arc. Dynamic Time Warping method is proposed in this paper to implement similarity measurement and six kinds of commercial fluorescent lamps from the market are selected for tests. Experimental results indicate that the proposed method can classify the arc signal into different lamp categories accurately.
{"title":"Using Dynamic Time Warping Method for the Similarity Measurement of Fluorescent Lamp Arc","authors":"Yu-Jen Liu, Yuansheng Cheng","doi":"10.1109/SNPD51163.2021.9704925","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704925","url":null,"abstract":"Daily used fluorescent lamp or lighting tube is mainly consisted of optical element and power electronic component. The usage of them result in the various distortions on residential electricity supply and impact to power quality due to the nonlinear characteristic from arc phenomenon. In order to seek effectiveness ways for power quality improvement and to prevent any abnormal event on electricity supply, detection work on electric arc becomes important. For the electric arc detection, previous recognition on different arc properties or different forming sources can help to achieve this work. This paper thus propose an idea by using similarity measurement to find the relevance between produced arc signal and the source of arc. Dynamic Time Warping method is proposed in this paper to implement similarity measurement and six kinds of commercial fluorescent lamps from the market are selected for tests. Experimental results indicate that the proposed method can classify the arc signal into different lamp categories accurately.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126895534","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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