Pub Date : 2019-01-25DOI: 10.3934/ELECTRENG.2019.1.33
H. Hadj-Mabrouk
As part of the process of certification and commissioning of a new guided or automated rail transport system, the domain experts and in particular the National Safety Authority are responsible for reviewing the safety of the system to ensure that the safety level of the new transport system is at least equivalent to the railway systems already in service and deemed safe. This critical task of evaluating safety essentially concerns all the safety files prepared by the manufacturer and in particular safety studies such as the Preliminary Hazard Analysis (PHA), the functional safety analysis (FSA), the analysis of failure modes, their effects and of their criticality (AFMEC) or Software Error Effect Analysis (SEEA). The study presented in this paper is part of the SEEA analysis. To respect the completeness and consistency of this safety analysis (SEEA), the experts carry out complementary analyses of safety. They are brought to imagine new scenarios of potential accidents to perfect the exhaustiveness of the safety studies. In this process, one of the difficulties then consists in finding the abnormal scenarios being able to lead to a particular potential accident. This is the fundamental point that motivated this work. To help experts in this complex process of evaluating safety studies, we agreed to use artificial intelligence techniques and in particular machine learning to systematize, streamline and strengthen conventional approaches to safety analysis and critical software certification. The approach which was adopted in order to design and implement an assistance tool for safety analysis involved the following two main activities: – Extracting, formalizing and storing hazardous situations to produce a library of standard cases which covers the entire problem. This process entailed the use of knowledge acquisition techniques; – Exploiting the stored historical knowledge in order to develop safety analysis know-how which can assist experts to judge the thoroughness of the manufacturer’s suggested safety analysis. This second activity involves the use of machine learning techniques in particular the use of case-based reasoning (CBR).
{"title":"Contribution of artificial intelligence and machine learning to the assessment of the safety of critical software used in railway transport","authors":"H. Hadj-Mabrouk","doi":"10.3934/ELECTRENG.2019.1.33","DOIUrl":"https://doi.org/10.3934/ELECTRENG.2019.1.33","url":null,"abstract":"As part of the process of certification and commissioning of a new guided or automated rail transport system, the domain experts and in particular the National Safety Authority are responsible for reviewing the safety of the system to ensure that the safety level of the new transport system is at least equivalent to the railway systems already in service and deemed safe. This critical task of evaluating safety essentially concerns all the safety files prepared by the manufacturer and in particular safety studies such as the Preliminary Hazard Analysis (PHA), the functional safety analysis (FSA), the analysis of failure modes, their effects and of their criticality (AFMEC) or Software Error Effect Analysis (SEEA). The study presented in this paper is part of the SEEA analysis. To respect the completeness and consistency of this safety analysis (SEEA), the experts carry out complementary analyses of safety. They are brought to imagine new scenarios of potential accidents to perfect the exhaustiveness of the safety studies. In this process, one of the difficulties then consists in finding the abnormal scenarios being able to lead to a particular potential accident. This is the fundamental point that motivated this work. To help experts in this complex process of evaluating safety studies, we agreed to use artificial intelligence techniques and in particular machine learning to systematize, streamline and strengthen conventional approaches to safety analysis and critical software certification. The approach which was adopted in order to design and implement an assistance tool for safety analysis involved the following two main activities: – Extracting, formalizing and storing hazardous situations to produce a library of standard cases which covers the entire problem. This process entailed the use of knowledge acquisition techniques; – Exploiting the stored historical knowledge in order to develop safety analysis know-how which can assist experts to judge the thoroughness of the manufacturer’s suggested safety analysis. This second activity involves the use of machine learning techniques in particular the use of case-based reasoning (CBR).","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49376791","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 : 2019-01-01DOI: 10.3934/electreng.2019.2.164
Stephen L. Durden
{"title":"Spatial variability of airborne radar reflectivity and velocity measurements of tropical rain with application to spaceborne radar","authors":"Stephen L. Durden","doi":"10.3934/electreng.2019.2.164","DOIUrl":"https://doi.org/10.3934/electreng.2019.2.164","url":null,"abstract":"","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221784","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 : 2019-01-01DOI: 10.3934/electreng.2019.3.233
Efthymios N. Lallas
{"title":"A survey on key roles of optical switching and labeling technologies on big data traffic of Data Centers and HPC environments","authors":"Efthymios N. Lallas","doi":"10.3934/electreng.2019.3.233","DOIUrl":"https://doi.org/10.3934/electreng.2019.3.233","url":null,"abstract":"","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221844","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 : 2019-01-01DOI: 10.3934/electreng.2019.3.224
Deval V. Jansari, Reza K. Amineh
{"title":"A two-element antenna array for compact portable MIMO-UWB communication systems","authors":"Deval V. Jansari, Reza K. Amineh","doi":"10.3934/electreng.2019.3.224","DOIUrl":"https://doi.org/10.3934/electreng.2019.3.224","url":null,"abstract":"","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221802","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 : 2019-01-01DOI: 10.3934/ELECTRENG.2019.1.1
S. Bateson
A design is presented, in which the DDC112 current-input analogue-to-digital converter is combined with a PIC microcontroller and associated circuitry to give a simple and economical dual-beam photometer / electrometer. The PIC supervises the operation of the analogue-digital converter and performs a lock-in function using a rolling average filter, which enables intensity measurement to parts per million. It also synchronously controls a regulated current source to drive, typically, one or more power LEDs as light sources. It has been applied in various fluorescence and absorbance measurements and can be used with Cavity Enhanced Absorption Spectrometry to determine ultra-low absorbance. An expanded version has been created with a PIC32 processor handling eight channels for a PixelSensor multispectral detector. All circuit details and source code are made available.
{"title":"A USB high resolution lock-in photometer","authors":"S. Bateson","doi":"10.3934/ELECTRENG.2019.1.1","DOIUrl":"https://doi.org/10.3934/ELECTRENG.2019.1.1","url":null,"abstract":"A design is presented, in which the DDC112 current-input analogue-to-digital converter is combined with a PIC microcontroller and associated circuitry to give a simple and economical dual-beam photometer / electrometer. The PIC supervises the operation of the analogue-digital converter and performs a lock-in function using a rolling average filter, which enables intensity measurement to parts per million. It also synchronously controls a regulated current source to drive, typically, one or more power LEDs as light sources. It has been applied in various fluorescence and absorbance measurements and can be used with Cavity Enhanced Absorption Spectrometry to determine ultra-low absorbance. An expanded version has been created with a PIC32 processor handling eight channels for a PixelSensor multispectral detector. All circuit details and source code are made available.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221733","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 : 2019-01-01DOI: 10.3934/ELECTRENG.2019.1.16
Yipeng Yang
In order to overcome the constraints of Networked Control Systems (NCSs) such as random packet delays or dropouts, it is a natural idea to estimate the system state and compensate for the time delays on the controller side. This paper provides an estimate on the scale of the complete dynamical system that uses this idea of control. The structure of the complete system is clearly illustrated. Then a concise sufficient and necessary stability condition is provided. In the numerical example, it is shown that this seemingly small system turns out to have a very large scale.
{"title":"Stability analysis of networked control systems with bounded random delay and state compensation: How large is the actual system scale?","authors":"Yipeng Yang","doi":"10.3934/ELECTRENG.2019.1.16","DOIUrl":"https://doi.org/10.3934/ELECTRENG.2019.1.16","url":null,"abstract":"In order to overcome the constraints of Networked Control Systems (NCSs) such as random packet delays or dropouts, it is a natural idea to estimate the system state and compensate for the time delays on the controller side. This paper provides an estimate on the scale of the complete dynamical system that uses this idea of control. The structure of the complete system is clearly illustrated. Then a concise sufficient and necessary stability condition is provided. In the numerical example, it is shown that this seemingly small system turns out to have a very large scale.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221775","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 : 2019-01-01DOI: 10.3934/electreng.2019.4.397
Gavin C Rider
{"title":"A critique of the approach to controlling electrostatic risk in semiconductor production and identification of a potential risk from the use of equipotential bonding","authors":"Gavin C Rider","doi":"10.3934/electreng.2019.4.397","DOIUrl":"https://doi.org/10.3934/electreng.2019.4.397","url":null,"abstract":"","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221905","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 : 2014-01-12DOI: 10.5755/J01.EEE.20.1.3948
Huan Zhao, Fei Wang, Zuo Chen, Jun Liu
In this paper, we proposed a novel blind audio watermarking algorithm, which combined Singular Value Decomposition(SVD) with Discrete Wavelet Transform(DWT). In our algorithm, We first partition the rearranged audio signal into blocks, then generate the vector by selecting the biggest singular values after performing SVD on these blocks. Finally we embed the watermark into the approximate components obtained from the DWT decomposition of the vector by means of quantization process. Experimental results showed that our algorithm has good robustness against the common audio signals processing operations. Compared with earlier schemes based on SVD, the proposed scheme has satisfying imperceptibility and improved payload. DOI: http://dx.doi.org/10.5755/j01.eee.20.1.3948
{"title":"A Robust Audio Watermarking Algorithm Based on SVD-DWT","authors":"Huan Zhao, Fei Wang, Zuo Chen, Jun Liu","doi":"10.5755/J01.EEE.20.1.3948","DOIUrl":"https://doi.org/10.5755/J01.EEE.20.1.3948","url":null,"abstract":"In this paper, we proposed a novel blind audio watermarking algorithm, which combined Singular Value Decomposition(SVD) with Discrete Wavelet Transform(DWT). In our algorithm, We first partition the rearranged audio signal into blocks, then generate the vector by selecting the biggest singular values after performing SVD on these blocks. Finally we embed the watermark into the approximate components obtained from the DWT decomposition of the vector by means of quantization process. Experimental results showed that our algorithm has good robustness against the common audio signals processing operations. Compared with earlier schemes based on SVD, the proposed scheme has satisfying imperceptibility and improved payload. DOI: http://dx.doi.org/10.5755/j01.eee.20.1.3948","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"691 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77034784","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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