Pub Date : 2017-08-23DOI: 10.1109/COASE.2017.8256233
Feifan Wang, Feng Ju, Yan Lu
In concert with advances in information and communication technology and their application to manufacturing environments, physical entities in factories are acquiring more intelligence via integration with cyber systems. This integration brings about Cyber-Physical Production Systems and leads to smart manufacturing, the next generation manufacturing paradigm. In the new paradigm, high levels of agility, flexibility, and real-time control make it possible to keep the system running efficiently and self-organized. At the same time, however, it becomes difficult in a self-organized and decentralized system to capture the system's status, evaluate the system's performance, and predict the system's future events. In this article, we suggest improvements to smart manufacturing systems where the intelligence from smart entities could be fully utilized without losing system control. To achieve this goal, a solution for integrating schedule-driven production (push systems) and event-driven production (pull systems) is proposed to optimize both material flow and information flow for manufacturing operations. For each entity in a smart manufacturing system, details of decision making are encapsulated and its status is exposed. The status-based decisions filter out unimportant information and make smart manufacturing systems loosely-coupled and predictable. A simulation case study based on Devices Profile for Web Services [1] is used to illustrate the effectiveness of such an approach. The case study suggests that status-based decisions could be applied to smart manufacturing and that they can be part of an approach that balances the self-organized control with overall performance. Therefore, we can make full use of intelligent entities in lower levels of a factory while keeping the entire system under control.
{"title":"A study on performance evaluation and status-based decision for cyber-physical production systems","authors":"Feifan Wang, Feng Ju, Yan Lu","doi":"10.1109/COASE.2017.8256233","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256233","url":null,"abstract":"In concert with advances in information and communication technology and their application to manufacturing environments, physical entities in factories are acquiring more intelligence via integration with cyber systems. This integration brings about Cyber-Physical Production Systems and leads to smart manufacturing, the next generation manufacturing paradigm. In the new paradigm, high levels of agility, flexibility, and real-time control make it possible to keep the system running efficiently and self-organized. At the same time, however, it becomes difficult in a self-organized and decentralized system to capture the system's status, evaluate the system's performance, and predict the system's future events. In this article, we suggest improvements to smart manufacturing systems where the intelligence from smart entities could be fully utilized without losing system control. To achieve this goal, a solution for integrating schedule-driven production (push systems) and event-driven production (pull systems) is proposed to optimize both material flow and information flow for manufacturing operations. For each entity in a smart manufacturing system, details of decision making are encapsulated and its status is exposed. The status-based decisions filter out unimportant information and make smart manufacturing systems loosely-coupled and predictable. A simulation case study based on Devices Profile for Web Services [1] is used to illustrate the effectiveness of such an approach. The case study suggests that status-based decisions could be applied to smart manufacturing and that they can be part of an approach that balances the self-organized control with overall performance. Therefore, we can make full use of intelligent entities in lower levels of a factory while keeping the entire system under control.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124924002","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 : 2017-08-20DOI: 10.1109/COASE.2017.8256226
Zhou He, Zhiwu Li, A. Giua
This paper is motivated by the optimization of manufacturing systems such as assembly lines and job-shops. Therefore, the main problem for designers is to find a trade-off between minimizing the cost of the resources and maximizing the system's throughput. Timed marked graphs, a special class of Petri nets, are extensively used to model and analyze cyclic manufacturing systems. Weighted marked graphs are convenient to model systems with bulk services and arrivals. We consider two problems of practical importance for this class of nets. The marking optimization problem consists in finding an initial marking to minimize the weighted sum of tokens in places while the average cycle time is less than or equal to a given value. The cycle time optimization problem consists in finding an initial marking to minimize the average cycle time while the weighted sum of tokens in places is less than or equal to a given value. We propose two heuristic algorithms to solve these problems. Several simulation studies show that the effectiveness of the proposed approach is significantly faster than existing ones.
{"title":"Optimization of deterministic timed weighted marked graphs","authors":"Zhou He, Zhiwu Li, A. Giua","doi":"10.1109/COASE.2017.8256226","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256226","url":null,"abstract":"This paper is motivated by the optimization of manufacturing systems such as assembly lines and job-shops. Therefore, the main problem for designers is to find a trade-off between minimizing the cost of the resources and maximizing the system's throughput. Timed marked graphs, a special class of Petri nets, are extensively used to model and analyze cyclic manufacturing systems. Weighted marked graphs are convenient to model systems with bulk services and arrivals. We consider two problems of practical importance for this class of nets. The marking optimization problem consists in finding an initial marking to minimize the weighted sum of tokens in places while the average cycle time is less than or equal to a given value. The cycle time optimization problem consists in finding an initial marking to minimize the average cycle time while the weighted sum of tokens in places is less than or equal to a given value. We propose two heuristic algorithms to solve these problems. Several simulation studies show that the effectiveness of the proposed approach is significantly faster than existing ones.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125008434","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 : 2017-08-20DOI: 10.1109/COASE.2017.8256069
Anastasia Bolotnikova, Kevin Chappellet, Antonio Paolillo, Adrien Escande, G. Anbarjafari, Adolfo Suarez-Roos, P. Rabaté, A. Kheddar
Automation of large-scale aircraft manufacturing with wheeled or embedded platforms requires costly changes of the manufacturing process and the environment. Humanoid robots could address this issue. We present a use-case of HRP-4 humanoid operating circuit-breakers. We show the feasibility of using visual feedback and force control in an integrated and unified multi-contact and multimodal task space quadratic programming (QP) whole-body control framework to enable HRP-4 to perform the task. We discuss the experimental results and outline the limitations of the current platform design and control implementation.
{"title":"A circuit-breaker use-case operated by a humanoid in aircraft manufacturing","authors":"Anastasia Bolotnikova, Kevin Chappellet, Antonio Paolillo, Adrien Escande, G. Anbarjafari, Adolfo Suarez-Roos, P. Rabaté, A. Kheddar","doi":"10.1109/COASE.2017.8256069","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256069","url":null,"abstract":"Automation of large-scale aircraft manufacturing with wheeled or embedded platforms requires costly changes of the manufacturing process and the environment. Humanoid robots could address this issue. We present a use-case of HRP-4 humanoid operating circuit-breakers. We show the feasibility of using visual feedback and force control in an integrated and unified multi-contact and multimodal task space quadratic programming (QP) whole-body control framework to enable HRP-4 to perform the task. We discuss the experimental results and outline the limitations of the current platform design and control implementation.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133157464","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 : 2017-08-20DOI: 10.1109/COASE.2017.8256167
M. Prodel, V. Augusto, Xiaolan Xie, B. Jouaneton, L. Lamarsalle
This paper presents a method to automatically create stochastic simulation models of clinical pathways from raw databases. We introduce an automatic procedure to convert a process model, discovered with process mining, into an actionable simulation model. The concept of state charts is used and enriched to incorporate the distinctive features of healthcare processes into the model. The clinical pathway model is used to simulate new patients' sequence of events. The resulting model is validated by comparing key performances indicators with historical data. Finally, we use the model to perform an automatically setup sensitivity analysis. The whole process is automated and can be used with any input data.
{"title":"Stochastic simulation of clinical pathways from raw health databases","authors":"M. Prodel, V. Augusto, Xiaolan Xie, B. Jouaneton, L. Lamarsalle","doi":"10.1109/COASE.2017.8256167","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256167","url":null,"abstract":"This paper presents a method to automatically create stochastic simulation models of clinical pathways from raw databases. We introduce an automatic procedure to convert a process model, discovered with process mining, into an actionable simulation model. The concept of state charts is used and enriched to incorporate the distinctive features of healthcare processes into the model. The clinical pathway model is used to simulate new patients' sequence of events. The resulting model is validated by comparing key performances indicators with historical data. Finally, we use the model to perform an automatically setup sensitivity analysis. The whole process is automated and can be used with any input data.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"82 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131147611","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 : 2017-08-20DOI: 10.1109/COASE.2017.8256166
T. Franck, V. Augusto, Xiaolan Xie, R. Gonthier
The growing number of elderly people is one of the most important problems for the next years. This part of the population is often dependent and does not tolerate environment changes so that long term care structure assignment should be well prepared. This paper proposes a new optimization-simulation approach to (i) solve the long term care structure assignment problem for a population of elderly people and (ii) validate and calibrate the model depending on stakeholders objectives and territory special features. A Mixed-Integer Linear Program is proposed to solve the tactical assignment problem, while a stochastic simulation is used to assess the key performance indicators relevant for elderly on the long term.
{"title":"An optimization-simulation approach for long term care structure assignment problem for elderly people","authors":"T. Franck, V. Augusto, Xiaolan Xie, R. Gonthier","doi":"10.1109/COASE.2017.8256166","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256166","url":null,"abstract":"The growing number of elderly people is one of the most important problems for the next years. This part of the population is often dependent and does not tolerate environment changes so that long term care structure assignment should be well prepared. This paper proposes a new optimization-simulation approach to (i) solve the long term care structure assignment problem for a population of elderly people and (ii) validate and calibrate the model depending on stakeholders objectives and territory special features. A Mixed-Integer Linear Program is proposed to solve the tactical assignment problem, while a stochastic simulation is used to assess the key performance indicators relevant for elderly on the long term.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128569315","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 : 2017-08-01DOI: 10.1109/COASE.2017.8256325
Qishuai Liu, Qing Hui
This paper proposes a new class of cooperative bat-inspired consensus protocols including a collection of nonlinear dynamics for multi-agent coordination. The proposed consensus protocols embed a suggested convergence direction which can improve the performance of convergence time. This suggested convergence direction can be used to design a distributed algorithm for controlling multi-agent systems while simultaneously solving a large-scale optimization problem. By virtue of a Lyapunov-based method, we show that the proposed bat-inspired consensus protocols can reach the global consensus asymptotically. Meanwhile, the bat-inspired consensus protocols subjected to external disturbance are also considered. We give the theoretical proof of a sufficient condition for guaranteeing the convergence of the extended consensus protocols with disturbances.
{"title":"The convergence analysis of bat-inspired consensus protocols with nonlinear dynamics","authors":"Qishuai Liu, Qing Hui","doi":"10.1109/COASE.2017.8256325","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256325","url":null,"abstract":"This paper proposes a new class of cooperative bat-inspired consensus protocols including a collection of nonlinear dynamics for multi-agent coordination. The proposed consensus protocols embed a suggested convergence direction which can improve the performance of convergence time. This suggested convergence direction can be used to design a distributed algorithm for controlling multi-agent systems while simultaneously solving a large-scale optimization problem. By virtue of a Lyapunov-based method, we show that the proposed bat-inspired consensus protocols can reach the global consensus asymptotically. Meanwhile, the bat-inspired consensus protocols subjected to external disturbance are also considered. We give the theoretical proof of a sufficient condition for guaranteeing the convergence of the extended consensus protocols with disturbances.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124258381","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 : 2017-08-01DOI: 10.1109/COASE.2017.8256142
Cui Zhang, Y. Jia
This note concerns about the problem of target tracking over distributed sensors which measure range and azimuth with time-varying bias. First, the pseudo-measurements are generated to transform the biased nonlinear measurements into Cartesian coordinates. Then a modified two-stage filter is proposed to decouple the estimation of target state and sensor bias. Moreover, a distributed fusion algorithm for sensor network is derived based on local estimates. The effectiveness of the proposed filters are demonstrated by the Monte Carlo simulation results.
{"title":"Target tracking over distributed sensor networks by polar measurements with time-varying bias","authors":"Cui Zhang, Y. Jia","doi":"10.1109/COASE.2017.8256142","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256142","url":null,"abstract":"This note concerns about the problem of target tracking over distributed sensors which measure range and azimuth with time-varying bias. First, the pseudo-measurements are generated to transform the biased nonlinear measurements into Cartesian coordinates. Then a modified two-stage filter is proposed to decouple the estimation of target state and sensor bias. Moreover, a distributed fusion algorithm for sensor network is derived based on local estimates. The effectiveness of the proposed filters are demonstrated by the Monte Carlo simulation results.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127324906","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}
In a manufacturing system, the machines have many idle statuses which consumed large quantity energy but with non-value added activities. Real time idle status control is important and challenging for the energy efficient manufacturing. With the sensible ability improved, more and more data can be collected from the manufacturing system. A fuzzy decision method is proposed to decrease the idle status by switching on-off the machine based on the real time data of the system. The serial manufacturing system is decomposed to basic control modules. A fuzzy controller with a fuzzy logic model and an on-off decision model is design based on the real time data of buffers and machines in order to switch the machine status. The fuzzy rules are described by analyzing the decision intention according to the human knowledge. After a series of simulation experiments, it has been observed that the proposed approach can be a simple, practical way to energy saving operation with accepted throughput loss.
{"title":"Fuzzy decision of machine switch on-off for energy efficient operation of manufacturing system","authors":"Junfeng Wang, J. Xue, Eliana Torres Duque, Shiqi Li, Q. Chang","doi":"10.1109/COASE.2017.8256259","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256259","url":null,"abstract":"In a manufacturing system, the machines have many idle statuses which consumed large quantity energy but with non-value added activities. Real time idle status control is important and challenging for the energy efficient manufacturing. With the sensible ability improved, more and more data can be collected from the manufacturing system. A fuzzy decision method is proposed to decrease the idle status by switching on-off the machine based on the real time data of the system. The serial manufacturing system is decomposed to basic control modules. A fuzzy controller with a fuzzy logic model and an on-off decision model is design based on the real time data of buffers and machines in order to switch the machine status. The fuzzy rules are described by analyzing the decision intention according to the human knowledge. After a series of simulation experiments, it has been observed that the proposed approach can be a simple, practical way to energy saving operation with accepted throughput loss.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124778183","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 : 2017-08-01DOI: 10.1109/COASE.2017.8256171
Peiyun Zhang, Mengchu Zhou
This work proposes a task scheduling method based on virtual machine (VM) matching in clouds. Its objectives are 1) to maximize task scheduling performance and 2) to minimize non-reasonable task allocation, e.g., a simple task to a high-performance VM and thus causing resource waste. A job classifier is utilized to classify tasks and match to a most suitable VM. This work uses the historical data to pre-create VMs of different types. This can save time of creating VMs during task scheduling. Tasks are efficiently matched with concrete VMs dynamically. Task scheduling is accordingly conducted. Experimental results with the Google Cluster Trace dataset show that the proposed method can effectively improve the cloud's task scheduling performance and achieve desired load balancing among various virtual machines in comparison with some existing methods.
{"title":"Task scheduling based on virtual machine matching in clouds","authors":"Peiyun Zhang, Mengchu Zhou","doi":"10.1109/COASE.2017.8256171","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256171","url":null,"abstract":"This work proposes a task scheduling method based on virtual machine (VM) matching in clouds. Its objectives are 1) to maximize task scheduling performance and 2) to minimize non-reasonable task allocation, e.g., a simple task to a high-performance VM and thus causing resource waste. A job classifier is utilized to classify tasks and match to a most suitable VM. This work uses the historical data to pre-create VMs of different types. This can save time of creating VMs during task scheduling. Tasks are efficiently matched with concrete VMs dynamically. Task scheduling is accordingly conducted. Experimental results with the Google Cluster Trace dataset show that the proposed method can effectively improve the cloud's task scheduling performance and achieve desired load balancing among various virtual machines in comparison with some existing methods.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125835397","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 : 2017-08-01DOI: 10.1109/COASE.2017.8256084
Xiaowo Wang
Quantitative understanding of biological regulation is essential for studying natural biosystems and for constructing synthetic systems. Current studies on gene regulation are used to build models under the assumption that gene regulators acting on a single or few targets. However, many regulators are actually shared between multiple target species with varying binding affinities, and target molecules often exist at different copy number. If the regulator is not in excess relative to target molecule pool, targets could cross talk with each other by competing for a limited pool of sharing regulators. Emerging examples suggest that such competing effects are wide spread in biosystems, including transcription factor binding, ribosome allocation, microRNA regulation, protein degradation, etc. We proposed a mathematical model to describe the common properties of these diverse competing regulatory systems, and implemented synthetic gene circuits to understand the quantitative behaviors of microRNA-target competing effects in human cell (1,2). Our work and several resent papers demonstrate that, molecular competing effects can couple the expression level of target molecules (3), introduce ultra-sensitivity to regulation dose-response curve (1,4), control temporal dynamics of gene expression (5), filter high frequency noises, and influence the stability of synthetic gene circuits (6). Systematic study of competitive regulation is essential for the precise control of synthetic biological systems.
{"title":"Regulation by competing: A hidden layer of gene regulatory networks","authors":"Xiaowo Wang","doi":"10.1109/COASE.2017.8256084","DOIUrl":"https://doi.org/10.1109/COASE.2017.8256084","url":null,"abstract":"Quantitative understanding of biological regulation is essential for studying natural biosystems and for constructing synthetic systems. Current studies on gene regulation are used to build models under the assumption that gene regulators acting on a single or few targets. However, many regulators are actually shared between multiple target species with varying binding affinities, and target molecules often exist at different copy number. If the regulator is not in excess relative to target molecule pool, targets could cross talk with each other by competing for a limited pool of sharing regulators. Emerging examples suggest that such competing effects are wide spread in biosystems, including transcription factor binding, ribosome allocation, microRNA regulation, protein degradation, etc. We proposed a mathematical model to describe the common properties of these diverse competing regulatory systems, and implemented synthetic gene circuits to understand the quantitative behaviors of microRNA-target competing effects in human cell (1,2). Our work and several resent papers demonstrate that, molecular competing effects can couple the expression level of target molecules (3), introduce ultra-sensitivity to regulation dose-response curve (1,4), control temporal dynamics of gene expression (5), filter high frequency noises, and influence the stability of synthetic gene circuits (6). Systematic study of competitive regulation is essential for the precise control of synthetic biological systems.","PeriodicalId":445441,"journal":{"name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125463512","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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