Pub Date : 2016-09-08DOI: 10.1109/IConAC.2016.7604932
Hamza Alzarok, S. Fletcher, A. Longstaff
Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm.
{"title":"A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information","authors":"Hamza Alzarok, S. Fletcher, A. Longstaff","doi":"10.1109/IConAC.2016.7604932","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604932","url":null,"abstract":"Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128161453","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 : 2016-09-07DOI: 10.1109/IConAC.2016.7604887
J.Ch. Bao, H. Yue, W. Leithead, Jiqiang Wang
A gain-scheduled feedforward controller employing pseudo-LIDAR wind measurement is designed to augment the baseline feedback controller for wind turbine load reduction during above rated operation. The feedforward controller is firstly designed based on a linearised wind turbine model at one specific wind speed, then expanded for full above rated operational envelope with gain scheduling. The wind evolution model is established using the pseudo-LIDAR measurement data which is generated from Bladed using a designed sampling strategy. The combined feedforward and baseline control system is simulated on a 5MW industrial wind turbine model developed at Strathclyde University. Simulation results demonstrate that the gain scheduling feedforward control strategy can improve the rotor and tower load reduction performance for large wind turbines.
{"title":"LIDAR-assisted wind turbine gain scheduling control for load reduction","authors":"J.Ch. Bao, H. Yue, W. Leithead, Jiqiang Wang","doi":"10.1109/IConAC.2016.7604887","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604887","url":null,"abstract":"A gain-scheduled feedforward controller employing pseudo-LIDAR wind measurement is designed to augment the baseline feedback controller for wind turbine load reduction during above rated operation. The feedforward controller is firstly designed based on a linearised wind turbine model at one specific wind speed, then expanded for full above rated operational envelope with gain scheduling. The wind evolution model is established using the pseudo-LIDAR measurement data which is generated from Bladed using a designed sampling strategy. The combined feedforward and baseline control system is simulated on a 5MW industrial wind turbine model developed at Strathclyde University. Simulation results demonstrate that the gain scheduling feedforward control strategy can improve the rotor and tower load reduction performance for large wind turbines.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122249580","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 : 2016-09-07DOI: 10.1109/IConAC.2016.7604952
Pengcheng Liu, Hongnian Yu, S. Cang, L. Vlădăreanu
Urbanization and changes in modern infrastructure have introduced new challenges to current firefighting practices. The current manual operations and training including fire investigation, hazardous chemicals detection, fire and rescue are insufficient to protect the firefighter's safety and life. The firefighting and rescue functions of the existing equipment and apparatus and their dexterity are limited, particularly in the harsh firefighting environments. It is well-established that data and informatics are key factors for efficient and smart firefighting operation. This paper provides a review on the robot-assisted firefighting systems with interdisciplinary perspectives to identify the needs, requirements, challenges as well as future trends to facilitate smart and efficient operations. The needs and challenges of robot-assisted firefighting systems are firstly investigated and identified. Subsequently, prevailing firefighting robotic platforms in literature as well as in practices are elaborately scrutinized and discussed, followed by investigation of localization and navigation support methods. Finally, conclusions and future trends outlook are provided.
{"title":"Robot-assisted smart firefighting and interdisciplinary perspectives","authors":"Pengcheng Liu, Hongnian Yu, S. Cang, L. Vlădăreanu","doi":"10.1109/IConAC.2016.7604952","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604952","url":null,"abstract":"Urbanization and changes in modern infrastructure have introduced new challenges to current firefighting practices. The current manual operations and training including fire investigation, hazardous chemicals detection, fire and rescue are insufficient to protect the firefighter's safety and life. The firefighting and rescue functions of the existing equipment and apparatus and their dexterity are limited, particularly in the harsh firefighting environments. It is well-established that data and informatics are key factors for efficient and smart firefighting operation. This paper provides a review on the robot-assisted firefighting systems with interdisciplinary perspectives to identify the needs, requirements, challenges as well as future trends to facilitate smart and efficient operations. The needs and challenges of robot-assisted firefighting systems are firstly investigated and identified. Subsequently, prevailing firefighting robotic platforms in literature as well as in practices are elaborately scrutinized and discussed, followed by investigation of localization and navigation support methods. Finally, conclusions and future trends outlook are provided.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124076764","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 : 2016-09-07DOI: 10.1109/IConAC.2016.7604899
A. Yusupov, Yang Liu
This paper introduces a current research project carried out in the Robert Gordon University for developing the prototype of the vibro-impact capsule robot for pipeline inspection. The project aims to address the technical bottlenecks which have been encountered by current pipeline technologies with a particular focus on oil industry. In order to verify the concept, a dummy capsule prototype with a diameter of 80 mm is designed and manufactured for testing in a 2.5 meter long section of 140 mm nominal diameter clear PVCu pipe with a flow velocity up to 0.3 m/s. By using the experimental test bed, the prototype of the capsule system can be tested at various flow rates, and the experimental results could be used for comparing with CFD simulation results for optimization.
{"title":"Development of a self-propelled capsule robot for pipeline inspection","authors":"A. Yusupov, Yang Liu","doi":"10.1109/IConAC.2016.7604899","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604899","url":null,"abstract":"This paper introduces a current research project carried out in the Robert Gordon University for developing the prototype of the vibro-impact capsule robot for pipeline inspection. The project aims to address the technical bottlenecks which have been encountered by current pipeline technologies with a particular focus on oil industry. In order to verify the concept, a dummy capsule prototype with a diameter of 80 mm is designed and manufactured for testing in a 2.5 meter long section of 140 mm nominal diameter clear PVCu pipe with a flow velocity up to 0.3 m/s. By using the experimental test bed, the prototype of the capsule system can be tested at various flow rates, and the experimental results could be used for comparing with CFD simulation results for optimization.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121627372","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 : 2016-09-07DOI: 10.1109/IConAC.2016.7604939
Hui Yu, Hening Yu, H. Yue, Jinglin Zhou
The optimal experimental design (OED) for observation strategy is investigated in this paper to collect the most informative experimental data for parameter estimation. The aim is to determine the best sampling time points and also select the most valuable measurement state variables through OED. The two design objectives are integrated together as a single-objective optimisation problem in which the variables and their sampling times are weighted in an expanded time sampling framework. Three optimisation methods, i.e., the Powell's method, the sequential selection method, and the sequential quadratic programming method, are employed to solve the optimisation problem. Their computation efficiencies are compared using a biodiesel case study system simulation. Simulation results demonstrate the effectiveness of the proposed method in reducing parameter estimation uncertainties as well as reducing parameter correlations. It can also be observed that the integrated OED doesn't cost extra computation efforts when variable selection is considered together with the time sampling task.
{"title":"Integrated time sampling design and measurement set selection for biochemical systems","authors":"Hui Yu, Hening Yu, H. Yue, Jinglin Zhou","doi":"10.1109/IConAC.2016.7604939","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604939","url":null,"abstract":"The optimal experimental design (OED) for observation strategy is investigated in this paper to collect the most informative experimental data for parameter estimation. The aim is to determine the best sampling time points and also select the most valuable measurement state variables through OED. The two design objectives are integrated together as a single-objective optimisation problem in which the variables and their sampling times are weighted in an expanded time sampling framework. Three optimisation methods, i.e., the Powell's method, the sequential selection method, and the sequential quadratic programming method, are employed to solve the optimisation problem. Their computation efficiencies are compared using a biodiesel case study system simulation. Simulation results demonstrate the effectiveness of the proposed method in reducing parameter estimation uncertainties as well as reducing parameter correlations. It can also be observed that the integrated OED doesn't cost extra computation efforts when variable selection is considered together with the time sampling task.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127398622","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 : 2016-09-01DOI: 10.1109/IConAC.2016.7604931
Rehan Qayyum, K. Kamal, T. Zafar, S. Mathavan
Machine vision based inspection system are in great focus nowadays for quality control applications. The paper presents a novel approach for classification of wood knot defects for an automated inspection. The proposed technique utilizes gray level co-occurrence matrix based features and a particle swarm optimization trained feedforward neural network. It takes contrast, correlation, energy, homogeneity as input parameters to a feedforward neural network to predict wood defects. PSO is used as a learning algorithm. The MSE for training data is found to be 0.3483 and 78.26% accuracy is achieved for testing data. The proposed technique shows promising results to classify wood defects using a PSO trained neural network.
{"title":"Wood defects classification using GLCM based features and PSO trained neural network","authors":"Rehan Qayyum, K. Kamal, T. Zafar, S. Mathavan","doi":"10.1109/IConAC.2016.7604931","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604931","url":null,"abstract":"Machine vision based inspection system are in great focus nowadays for quality control applications. The paper presents a novel approach for classification of wood knot defects for an automated inspection. The proposed technique utilizes gray level co-occurrence matrix based features and a particle swarm optimization trained feedforward neural network. It takes contrast, correlation, energy, homogeneity as input parameters to a feedforward neural network to predict wood defects. PSO is used as a learning algorithm. The MSE for training data is found to be 0.3483 and 78.26% accuracy is achieved for testing data. The proposed technique shows promising results to classify wood defects using a PSO trained neural network.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115337908","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 : 2016-09-01DOI: 10.1109/IConAC.2016.7604943
E. Eze, Sijing Zhang, E. Liu, Emmanuel N. Nweso, E. C. Joy
In an unreliable cluster-based, broadcast-oriented vehicular network setting, we investigate the transmission reliability and throughput performance of random network coding (RNC) as a function of the packet generate rate. Our proposed model consists of a source vehicle broadcasting packets to a set of receivers (i.e. one-to-many) over independent broadcast erasure channels. The source vehicle performs RNC on N packets and broadcasts the encoded message to a set of receivers. In each hop, several vehicles form a cluster and cooperatively transmit the encoded or re-encoded packet. The combination of RNC, cluster based, and cooperative communications enables RECMAC to optimally minimize data redundancy, which means less overhead, and improve reliability as opposed to existing coding-based solutions. Theoretic analyses and simulation results show that RECMAC scheme can achieve optimal performance in terms of transmission reliability and throughput.
{"title":"RECMAC: Reliable and efficient cooperative cross-layer MAC scheme for vehicular communication based on random network coding technique","authors":"E. Eze, Sijing Zhang, E. Liu, Emmanuel N. Nweso, E. C. Joy","doi":"10.1109/IConAC.2016.7604943","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604943","url":null,"abstract":"In an unreliable cluster-based, broadcast-oriented vehicular network setting, we investigate the transmission reliability and throughput performance of random network coding (RNC) as a function of the packet generate rate. Our proposed model consists of a source vehicle broadcasting packets to a set of receivers (i.e. one-to-many) over independent broadcast erasure channels. The source vehicle performs RNC on N packets and broadcasts the encoded message to a set of receivers. In each hop, several vehicles form a cluster and cooperatively transmit the encoded or re-encoded packet. The combination of RNC, cluster based, and cooperative communications enables RECMAC to optimally minimize data redundancy, which means less overhead, and improve reliability as opposed to existing coding-based solutions. Theoretic analyses and simulation results show that RECMAC scheme can achieve optimal performance in terms of transmission reliability and throughput.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124927044","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 : 2016-09-01DOI: 10.1109/IConAC.2016.7604892
M. Ilyas, Qaisar Javaid, M. A. Shah
In this paper, the objective is to investigate different performance enhancement attributes in multiprocessors architectures. We investigate the problem of cache hit and cache miss by efficient cache partitioning technique. We improved power efficiency by handling cache misses during data transfer from main memory to cache. The focus is on cache utilization techniques, cache partitioning techniques, power utilization by different components, parallel processing issues and limitation in multiple processors. We evaluate the parameters which use the cache and processors to achieve highest level performance. In this way the workload between different processes can be handled easily.
{"title":"Use of Symmetric Multiprocessor Architecture to achieve high performance computing","authors":"M. Ilyas, Qaisar Javaid, M. A. Shah","doi":"10.1109/IConAC.2016.7604892","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604892","url":null,"abstract":"In this paper, the objective is to investigate different performance enhancement attributes in multiprocessors architectures. We investigate the problem of cache hit and cache miss by efficient cache partitioning technique. We improved power efficiency by handling cache misses during data transfer from main memory to cache. The focus is on cache utilization techniques, cache partitioning techniques, power utilization by different components, parallel processing issues and limitation in multiple processors. We evaluate the parameters which use the cache and processors to achieve highest level performance. In this way the workload between different processes can be handled easily.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126022294","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 : 2016-09-01DOI: 10.1109/IConAC.2016.7604922
Xiaokai Nie, Jihong Wang, O. Kiselychnyk, Jing Chen
Energy storage plays an important role in maintaining energy balance for the future power network. A novel solution by learning human body energy system is explored aiming to determine the best ratio between the energy storage and generation capacity with variations of mixed energy sources. The fluctuation process of energy storage in human body and power network can be approximately represented by a one-dimensional noisy dynamical system. This paper develops a new approach to inferring a piecewise linear semi-Markov transformation of a one-dimensional discrete time dynamical system that is subjected to additive stochastic noise, based on sequences of probability density functions observed from the noisy dynamical system. The reconstructed map that approximates the underlying transformation can be used to predict the amount of stable fat/energy storage, and to achieve the bio-inspired three-point (generation, load and storage) balance structure. A numerical example is used to demonstrate the applicability of the derived algorithm and robustness with respect to additive stochastic noise.
{"title":"Modelling of one-dimensional noisy dynamical systems with a Frobenius-Perron solution","authors":"Xiaokai Nie, Jihong Wang, O. Kiselychnyk, Jing Chen","doi":"10.1109/IConAC.2016.7604922","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604922","url":null,"abstract":"Energy storage plays an important role in maintaining energy balance for the future power network. A novel solution by learning human body energy system is explored aiming to determine the best ratio between the energy storage and generation capacity with variations of mixed energy sources. The fluctuation process of energy storage in human body and power network can be approximately represented by a one-dimensional noisy dynamical system. This paper develops a new approach to inferring a piecewise linear semi-Markov transformation of a one-dimensional discrete time dynamical system that is subjected to additive stochastic noise, based on sequences of probability density functions observed from the noisy dynamical system. The reconstructed map that approximates the underlying transformation can be used to predict the amount of stable fat/energy storage, and to achieve the bio-inspired three-point (generation, load and storage) balance structure. A numerical example is used to demonstrate the applicability of the derived algorithm and robustness with respect to additive stochastic noise.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114896631","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 : 2016-09-01DOI: 10.1109/IConAC.2016.7604885
Fan Wang, Jinling Liang, Xiaohui Liu
This paper is concerned with the H∞ state estimation problem for the time-varying networks with probabilistic delay over a finite horizon. The measurements for the proposed network experience randomly occurring delays (RODs) with changeable probabilities, which could be described by a time-varying Bernoulli distribution stochastic sequence. Stochastic analysis and probability-dependent method are utilized to develop sufficient criteria under which the prescribed H∞ performance can be achieved. It is worth mentioning that, based on the available lower and upper bounds of the varying probabilities, the target estimator gains are transformed into a convex optimization problem subjecting to a set of recursive matrix inequalities which can be applied in a more robust situation. Finally, a simulation example is provided to show the effectiveness of the obtained results.
{"title":"H∞ state estimation for time-varying networks with probabilistic delay in measurements","authors":"Fan Wang, Jinling Liang, Xiaohui Liu","doi":"10.1109/IConAC.2016.7604885","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604885","url":null,"abstract":"This paper is concerned with the H∞ state estimation problem for the time-varying networks with probabilistic delay over a finite horizon. The measurements for the proposed network experience randomly occurring delays (RODs) with changeable probabilities, which could be described by a time-varying Bernoulli distribution stochastic sequence. Stochastic analysis and probability-dependent method are utilized to develop sufficient criteria under which the prescribed H∞ performance can be achieved. It is worth mentioning that, based on the available lower and upper bounds of the varying probabilities, the target estimator gains are transformed into a convex optimization problem subjecting to a set of recursive matrix inequalities which can be applied in a more robust situation. Finally, a simulation example is provided to show the effectiveness of the obtained results.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114952703","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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