Indoor positioning system based on Zigbee is to obtain the RSSI value to calculate the distance between point and point rely on empirical formula, then determine the location of the positioning point.But there is a big error in the positioning result in this location method because the signal intensity of Zigbee is very easy to be disturbed by the external environment, and it is difficult to compensate for the complex and changeable environment in the room. So, in this paper, we design a system based on the Zigbee indoor positioning system, and using the inertial system to stable po University sitioning result, to improve the positioning accuracy of Zigbee indoor positioning system.
{"title":"Indoor Positioning System Based on Zigbee and Inertial System","authors":"Cheng-de Han, Zhongtao Wang, Longxu Wang","doi":"10.1109/dsa.2018.00023","DOIUrl":"https://doi.org/10.1109/dsa.2018.00023","url":null,"abstract":"Indoor positioning system based on Zigbee is to obtain the RSSI value to calculate the distance between point and point rely on empirical formula, then determine the location of the positioning point.But there is a big error in the positioning result in this location method because the signal intensity of Zigbee is very easy to be disturbed by the external environment, and it is difficult to compensate for the complex and changeable environment in the room. So, in this paper, we design a system based on the Zigbee indoor positioning system, and using the inertial system to stable po University sitioning result, to improve the positioning accuracy of Zigbee indoor positioning system.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121096614","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}
The current product development process has the characteristics of short period, high technical demand and rapid production after finalization. Therefore, it is necessary to ensure the output quality of the product development process. This paper evaluates the development process capability of several models of products. Firstly, based on information entropy, the concept of quality entropy is proposed. Secondly, the capability evaluation model of product development process is established, and the quantitative capability evaluation of product development process is carried out by using quality entropy. Finally, a case is given to verify the rationality of the method.
{"title":"Process Capability Evaluation of Product Development Based on Information Entropy","authors":"Lixiang Wang, W. Dai, Yubing Huang","doi":"10.1109/dsa.2018.00025","DOIUrl":"https://doi.org/10.1109/dsa.2018.00025","url":null,"abstract":"The current product development process has the characteristics of short period, high technical demand and rapid production after finalization. Therefore, it is necessary to ensure the output quality of the product development process. This paper evaluates the development process capability of several models of products. Firstly, based on information entropy, the concept of quality entropy is proposed. Secondly, the capability evaluation model of product development process is established, and the quantitative capability evaluation of product development process is carried out by using quality entropy. Finally, a case is given to verify the rationality of the method.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123773540","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":"DSA 2018 Program Committee","authors":"","doi":"10.1109/dsa.2018.00009","DOIUrl":"https://doi.org/10.1109/dsa.2018.00009","url":null,"abstract":"","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129469972","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}
W. Tsai, Zihao Zhao, Chi Zhang, Lian Yu, Enyan Deng
Recently digital currency has received significant attention, and among many topics within digital currency, CBDC (Central Bank issued Digital Currency) has been a hot topic as it will affect national currency systems. RSCoin is the first CBDC model sponsored by Bank of England, and it uses the UTXO model from Bitcoin. This paper proposes a new CBDC model Panda model that can store account balance like current banking systems, but use efficient consensus protocols to ensure that relevant parties have consistent views of transactions and accounts. The Panda model is scalable as it can include as many financial institutions or individuals as possible in the system with increasing or decreasing workloads. The model has been simulated in the TaiShan Sandbox in Qingdao.
{"title":"A Multi-Chain Model for CBDC","authors":"W. Tsai, Zihao Zhao, Chi Zhang, Lian Yu, Enyan Deng","doi":"10.1109/DSA.2018.00016","DOIUrl":"https://doi.org/10.1109/DSA.2018.00016","url":null,"abstract":"Recently digital currency has received significant attention, and among many topics within digital currency, CBDC (Central Bank issued Digital Currency) has been a hot topic as it will affect national currency systems. RSCoin is the first CBDC model sponsored by Bank of England, and it uses the UTXO model from Bitcoin. This paper proposes a new CBDC model Panda model that can store account balance like current banking systems, but use efficient consensus protocols to ensure that relevant parties have consistent views of transactions and accounts. The Panda model is scalable as it can include as many financial institutions or individuals as possible in the system with increasing or decreasing workloads. The model has been simulated in the TaiShan Sandbox in Qingdao.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127621342","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}
GO methodology is a significant system probability analysis technique. Because the GO model is similar to system schematic diagram, it is easy to establish and often used to evaluate the reliability and safety of complex systems. The GO model can not only describe multi-state and time-sequential characteristics, but also express maintenance behaviors of systems. However, the solutions for repairable GO model through analytical approaches such as the numerical method and methods combined with Markov models or dynamic Bayesian networks have limitations in terms of shared signals, complex dynamic maintenance behaviors, the number of operators, non-exponential failure or repair probability distributions and the size of networks. Based on this, a Monte Carlo simulation-based algorithm for repairable GO model is proposed in this paper. The process of generating state time diagrams and the simulation principle of several typical operators are given and the result of an example validates the algorithm. By this new algorithm, the curves of reliability with time and the instantaneous reliability indices on determined time can be figured out without considering the limitations mentioned above.
{"title":"A Monte Carlo Simulation-Based Algorithm for a Repairable System in GO Methodology","authors":"Ang Li, Yi Ren, Dezhen Yang, Zhifeng Li","doi":"10.1109/DSA.2018.00029","DOIUrl":"https://doi.org/10.1109/DSA.2018.00029","url":null,"abstract":"GO methodology is a significant system probability analysis technique. Because the GO model is similar to system schematic diagram, it is easy to establish and often used to evaluate the reliability and safety of complex systems. The GO model can not only describe multi-state and time-sequential characteristics, but also express maintenance behaviors of systems. However, the solutions for repairable GO model through analytical approaches such as the numerical method and methods combined with Markov models or dynamic Bayesian networks have limitations in terms of shared signals, complex dynamic maintenance behaviors, the number of operators, non-exponential failure or repair probability distributions and the size of networks. Based on this, a Monte Carlo simulation-based algorithm for repairable GO model is proposed in this paper. The process of generating state time diagrams and the simulation principle of several typical operators are given and the result of an example validates the algorithm. By this new algorithm, the curves of reliability with time and the instantaneous reliability indices on determined time can be figured out without considering the limitations mentioned above.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126496657","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":"Message from the DSA 2018 Program Chairs","authors":"","doi":"10.1109/dsa.2018.00007","DOIUrl":"https://doi.org/10.1109/dsa.2018.00007","url":null,"abstract":"","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127583709","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":"Publisher's Information","authors":"","doi":"10.1109/dsa.2018.00034","DOIUrl":"https://doi.org/10.1109/dsa.2018.00034","url":null,"abstract":"","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124447902","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}
Wei Jiang, Siwei Zhou, Luyao Ye, Dongdong Zhao, Jing Tian, W. E. Wong, Jianwen Xiang
Dynamic fault tree (DFT) is an extension of traditional static fault tree, in which several dynamic gates are introduced to model sequential dependency between fault events. As for the quantitative analysis of DFT, sequential binary decision diagram (SBDD) has been proposed by incorporating sequential nodes into traditional binary decision diagram (BDD). With SBDD, a DFT can be reduced into a sum of disjoint products (SDP) of basic events and sequential nodes, which can avoid the space explosion problem and exponential complexity caused by traditional Markov chain and inclusion/exclusion based solutions, respectively. However, the SBDD is not developed base on a well-defined temporal or sequential algebra. Rather, it is developed based on a precedence operator with specific and very limited number of reduction rules. The applications of SBDD is thus restricted to the DFTs whose dynamic gates consist of inputs of only basic events or some specific events. In this paper, we present an algebraic binary decision diagram (ABDD) based on the algebraic framework for DFT proposed by G. Merle et al. In addition to the existing laws for the reduction of arbitrary DFT with any structure, we introduce a set of new laws for the reduction of SDP in the ABDD. Thanks to the sound algebraic framework and complete set of laws, ABDD is applicable for the analysis of general DFT without any structure restriction. We illustrate our approach and compare the difference with SBDD by several examples.
{"title":"An Algebraic Binary Decision Diagram for Analysis of Dynamic Fault Tree","authors":"Wei Jiang, Siwei Zhou, Luyao Ye, Dongdong Zhao, Jing Tian, W. E. Wong, Jianwen Xiang","doi":"10.1109/DSA.2018.00018","DOIUrl":"https://doi.org/10.1109/DSA.2018.00018","url":null,"abstract":"Dynamic fault tree (DFT) is an extension of traditional static fault tree, in which several dynamic gates are introduced to model sequential dependency between fault events. As for the quantitative analysis of DFT, sequential binary decision diagram (SBDD) has been proposed by incorporating sequential nodes into traditional binary decision diagram (BDD). With SBDD, a DFT can be reduced into a sum of disjoint products (SDP) of basic events and sequential nodes, which can avoid the space explosion problem and exponential complexity caused by traditional Markov chain and inclusion/exclusion based solutions, respectively. However, the SBDD is not developed base on a well-defined temporal or sequential algebra. Rather, it is developed based on a precedence operator with specific and very limited number of reduction rules. The applications of SBDD is thus restricted to the DFTs whose dynamic gates consist of inputs of only basic events or some specific events. In this paper, we present an algebraic binary decision diagram (ABDD) based on the algebraic framework for DFT proposed by G. Merle et al. In addition to the existing laws for the reduction of arbitrary DFT with any structure, we introduce a set of new laws for the reduction of SDP in the ABDD. Thanks to the sound algebraic framework and complete set of laws, ABDD is applicable for the analysis of general DFT without any structure restriction. We illustrate our approach and compare the difference with SBDD by several examples.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125042671","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":"Message from the DSA 2018 Steering Committee Chair","authors":"","doi":"10.1109/dsa.2018.00004","DOIUrl":"https://doi.org/10.1109/dsa.2018.00004","url":null,"abstract":"","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127741167","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}
When a certain UAV conduct a predetermined task, its flying track is planned in advance. The accumulated historical data of position information and respective state of the error can be used to diagnose the real time motion and position information deviation of the UAV-born inertial navigation devices through BP-Adaboost methods. The relationship between the position information deviation and characteristic parameters of UAV-born Inertial Navigation Device are in a high level of nonlinearity. As an efficacious non-linear classifier, BP neural network is capable of delineating the above nonlinear relationship. However, the performance and preciseness of the BP network are sensitively subject to the infuence of its initial weights, which is likely to incur the relatively unstable training outcomes. In order to address the contradiction and attain the training results we want, this paper provides a new approach to the UAV-born inertial navigation devices failure diagnosis based on BPAdaboost model. The first step is utilizing BP neural network as a weak classifier to discern the relationship between the failure states and the parameters. Each of the several BP networks chosen beforehand are applied to the repeated training process to become weak classifier one by one. Secondly, Adaboost algorithm is conducted by amalgamating the volidated weak classifier aiming at a strong classifier to diagnose the failure of UAV-born Inertial Navigation Device. Then, application of the BP-Adaboost method to a practical cases evinces that the failure diagnosis model of the strong classifier gains more satisfied accuracy than the weak classifiers, which can meet the requirements of the practices and offer another reference for the position deviation judgment during some repeating tasks for UAV-born inertial navigation devices, especially under the condition that GPS and inertial navigation devices are not stable and reliable.
{"title":"Failure Diagnosis for UAV-Born Inertial Navigation Device Based on BP-Adaboost Model","authors":"Yingjie Ren, Yang Hu","doi":"10.1109/DSA.2018.00020","DOIUrl":"https://doi.org/10.1109/DSA.2018.00020","url":null,"abstract":"When a certain UAV conduct a predetermined task, its flying track is planned in advance. The accumulated historical data of position information and respective state of the error can be used to diagnose the real time motion and position information deviation of the UAV-born inertial navigation devices through BP-Adaboost methods. The relationship between the position information deviation and characteristic parameters of UAV-born Inertial Navigation Device are in a high level of nonlinearity. As an efficacious non-linear classifier, BP neural network is capable of delineating the above nonlinear relationship. However, the performance and preciseness of the BP network are sensitively subject to the infuence of its initial weights, which is likely to incur the relatively unstable training outcomes. In order to address the contradiction and attain the training results we want, this paper provides a new approach to the UAV-born inertial navigation devices failure diagnosis based on BPAdaboost model. The first step is utilizing BP neural network as a weak classifier to discern the relationship between the failure states and the parameters. Each of the several BP networks chosen beforehand are applied to the repeated training process to become weak classifier one by one. Secondly, Adaboost algorithm is conducted by amalgamating the volidated weak classifier aiming at a strong classifier to diagnose the failure of UAV-born Inertial Navigation Device. Then, application of the BP-Adaboost method to a practical cases evinces that the failure diagnosis model of the strong classifier gains more satisfied accuracy than the weak classifiers, which can meet the requirements of the practices and offer another reference for the position deviation judgment during some repeating tasks for UAV-born inertial navigation devices, especially under the condition that GPS and inertial navigation devices are not stable and reliable.","PeriodicalId":117496,"journal":{"name":"2018 5th International Conference on Dependable Systems and Their Applications (DSA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126134144","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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