Pub Date : 2021-09-24DOI: 10.1109/ICASI52993.2021.9568439
Chia-Fen Hsieh, Che-Min Su
With the rapid development of the network, network security is a relatively important issue. However, traditional intrusion detection systems based on feature selection and classification have some drawbacks, such as processing redundant information and increasing computational time. This paper proposes Intrusion Detection System based on Deep Neural Network (DNNIDS). Our method includes preprocessing stage, model establishment stage, and test stage. Deep Learning (DL) can automatically extract features. Compared with other methods, this method can improve the accuracy to detect attack types.
{"title":"DNNIDS: A Novel Network Intrusion Detection Based on Deep Neural Network","authors":"Chia-Fen Hsieh, Che-Min Su","doi":"10.1109/ICASI52993.2021.9568439","DOIUrl":"https://doi.org/10.1109/ICASI52993.2021.9568439","url":null,"abstract":"With the rapid development of the network, network security is a relatively important issue. However, traditional intrusion detection systems based on feature selection and classification have some drawbacks, such as processing redundant information and increasing computational time. This paper proposes Intrusion Detection System based on Deep Neural Network (DNNIDS). Our method includes preprocessing stage, model establishment stage, and test stage. Deep Learning (DL) can automatically extract features. Compared with other methods, this method can improve the accuracy to detect attack types.","PeriodicalId":103254,"journal":{"name":"2021 7th International Conference on Applied System Innovation (ICASI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132068617","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 : 2021-09-24DOI: 10.1109/ICASI52993.2021.9568427
Tai-Ho Yu, Chiao-Yi Huang, Tang-Wei Guan
This study investigates the voltage amplification function characteristics of a piezoelectric transformer. The impedance curve and equivalent circuit parameters of PTs were measured using an impedance analyzer, and an automatic measurement system based on NI-LabVIEW was established to measure the step-up ratio. OrCAD PSpice software was used to analyze the load characteristics of the PT. This study analyzed the relationship between the step-up ratio and resonance frequency and that between the step-up ratio and the load. Finally, a motor driver must be designed such that the PT can effectively output a high voltage to drive the ultrasonic motor.
{"title":"Characteristic Measurement and Analysis of a Rosen-Type Piezoelectric Transformer","authors":"Tai-Ho Yu, Chiao-Yi Huang, Tang-Wei Guan","doi":"10.1109/ICASI52993.2021.9568427","DOIUrl":"https://doi.org/10.1109/ICASI52993.2021.9568427","url":null,"abstract":"This study investigates the voltage amplification function characteristics of a piezoelectric transformer. The impedance curve and equivalent circuit parameters of PTs were measured using an impedance analyzer, and an automatic measurement system based on NI-LabVIEW was established to measure the step-up ratio. OrCAD PSpice software was used to analyze the load characteristics of the PT. This study analyzed the relationship between the step-up ratio and resonance frequency and that between the step-up ratio and the load. Finally, a motor driver must be designed such that the PT can effectively output a high voltage to drive the ultrasonic motor.","PeriodicalId":103254,"journal":{"name":"2021 7th International Conference on Applied System Innovation (ICASI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126552444","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 : 2021-09-24DOI: 10.1109/ICASI52993.2021.9568470
Cheng-Liang Huang, Yuan-Kang Wu, Yuan-Yao Li
Numerous disasters potentially influence critical infrastruc-tures of an electric power system. Generally, disasters to power systems include extreme natural disasters and artificial attacks such as high-impact/low-probability events. If a disas-ter is severe, it could cause power outages. Therefore, it is im-portant to enhance the resilience of power systems. Improving the resilience of a power system is to propose defense strate-gies, prevent voltage collapse and recover from disconnection immediately. Many countries have paid attentions to the resil-ience related issues for preventing disasters. Although resili-ence has been widely used in power systems, there is no any uniform strategy that was proposed to reduce power system risks. This paper aims to review risk assessments about vari-ous disaster types, indexes and corresponding frameworks. Moreover, this paper discusses about the reliability, availabil-ity and challenges of applying various methods to enhance power system resilience.
{"title":"A Review on the Resilience Assessment of Power Systems under Disasters","authors":"Cheng-Liang Huang, Yuan-Kang Wu, Yuan-Yao Li","doi":"10.1109/ICASI52993.2021.9568470","DOIUrl":"https://doi.org/10.1109/ICASI52993.2021.9568470","url":null,"abstract":"Numerous disasters potentially influence critical infrastruc-tures of an electric power system. Generally, disasters to power systems include extreme natural disasters and artificial attacks such as high-impact/low-probability events. If a disas-ter is severe, it could cause power outages. Therefore, it is im-portant to enhance the resilience of power systems. Improving the resilience of a power system is to propose defense strate-gies, prevent voltage collapse and recover from disconnection immediately. Many countries have paid attentions to the resil-ience related issues for preventing disasters. Although resili-ence has been widely used in power systems, there is no any uniform strategy that was proposed to reduce power system risks. This paper aims to review risk assessments about vari-ous disaster types, indexes and corresponding frameworks. Moreover, this paper discusses about the reliability, availabil-ity and challenges of applying various methods to enhance power system resilience.","PeriodicalId":103254,"journal":{"name":"2021 7th International Conference on Applied System Innovation (ICASI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114907882","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 : 2021-09-24DOI: 10.1109/ICASI52993.2021.9568463
A. D. K. Lam, Kaiqi Zhang, Xiang-Yuan Zeng
Early detection of symptoms and appropriate hygiene standards are the basic public health measures to prevent the spread of COVID-19 community. The main purpose of this study is to design a smart door detection device, which can detect the risk factors of COVID-19 virus. First of all, through the early symptom detection instrument, we can get the health status data from the process of people entering the smart door; Then, the risk factors of the COVID-19 virus entering the population were analyzed through the health status data, and the intelligent isolation method was used to realize the post symptom detection and interactive identification between people, so as to evaluate the potential infection vectors and alleviate the possibility of further transmission. The smart door detection device developed in this research is an automatic device that follows the COVID-19 public health protocol. It provides an effective measure to prevent the early symptom recognition of COVID-19 virus spreading in the community.
{"title":"Design of COVID-19 Smart Door Detection Device for Risk Factor Detection","authors":"A. D. K. Lam, Kaiqi Zhang, Xiang-Yuan Zeng","doi":"10.1109/ICASI52993.2021.9568463","DOIUrl":"https://doi.org/10.1109/ICASI52993.2021.9568463","url":null,"abstract":"Early detection of symptoms and appropriate hygiene standards are the basic public health measures to prevent the spread of COVID-19 community. The main purpose of this study is to design a smart door detection device, which can detect the risk factors of COVID-19 virus. First of all, through the early symptom detection instrument, we can get the health status data from the process of people entering the smart door; Then, the risk factors of the COVID-19 virus entering the population were analyzed through the health status data, and the intelligent isolation method was used to realize the post symptom detection and interactive identification between people, so as to evaluate the potential infection vectors and alleviate the possibility of further transmission. The smart door detection device developed in this research is an automatic device that follows the COVID-19 public health protocol. It provides an effective measure to prevent the early symptom recognition of COVID-19 virus spreading in the community.","PeriodicalId":103254,"journal":{"name":"2021 7th International Conference on Applied System Innovation (ICASI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122280756","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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