This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing...This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing the trilinear PARAFAC model.Relying on the uniqueness of the low-rank three-way array decomposition and the trilinear alternating least squares regression, the proposed algorithm achieves nominal DOA estimation and outperforms the conventional estimation of signal parameter via rotational technique CD（ESPRIT-CD） and propagator method CD（PM-CD）methods in terms of estimation accuracy. Furthermore, by means of the initialization via the propagator method, this paper accelerates the convergence procedure of the proposed algorithm with no estimation performance degradation. In addition, the proposed algorithm can be directly applied to the multiple-source scenario,where sources have different angular distribution shapes. Numerical simulation results corroborate the effectiveness and superiority of the proposed fast PARAFAC-based algorithm.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on containe...Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on container startup(e.g.,distributed deep learning application),the image“warm-up”technique which prefetches images of these replicas to destination nodes in the cluster is proposed.However,the current image“warm-up”technique solely focuses on identical image distribution,which fails to take effect when distributing different images to destination nodes.To address this problem,this paper proposes Hound,a simple but efficient cluster image distribution system based on Docker.To support diverse image distribution requests of cluster nodes,Hound additionally adopts node-level parallelism(i.e.,downloading images to destination nodes in parallel)to further improve the efficiency of image distribution.The experimental results demonstrate Hound outperforms Docker,kubernetes container runtime interface(CRI-O),and Docker-compose in terms of image distribution performance when cluster nodes request different images.Moreover,the high scalability of Hound is evaluated in the scenario of ten nodes.展开更多
The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parall...The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.展开更多
This paper simulated the optimal refrigerant charge inventory of a refrigeration system in air-conditioning operation and heat-pump operation respectively,and studied the refrigerant control strategies in this system....This paper simulated the optimal refrigerant charge inventory of a refrigeration system in air-conditioning operation and heat-pump operation respectively,and studied the refrigerant control strategies in this system.The void fraction in two-phase fluid region was calculated by Harms model.And based on distributed parameter model and Harms model,the refrigerant charge inventory in condenser and evaporator were calculated and analyzed in air-conditioning conditions and heat-pump conditions,respectively.The calculating results of different refrigerant mass between refrigeration and heating conditions indicate that the optimal refrigerant charge inventory in heat-pump conditions is lower than that in air-conditioning conditions.To avoid the decrease of COP due to the surplus refrigerant in heating conditions,we introduced the liquid reservoir control method and associate capillary control method.Both of them could increase the heating capacity of the air-source heat pump.The difference of optimal refrigerant charge inventory in air-conditioning and heat-pump system can be controlled by the liquid reservoir or the associate capillary.展开更多
A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original...A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.展开更多
基金supported by the National Natural Science Foundation of China(6137116961601167)+2 种基金the Jiangsu Natural Science Foundation(BK20161489)the open research fund of State Key Laboratory of Millimeter Waves,Southeast University(K201826)the Fundamental Research Funds for the Central Universities(NE2017103)
文摘This paper links parallel factor（PARAFAC） analysis to the problem of nominal direction-of-arrival（DOA） estimation for coherently distributed（CD） sources and proposes a fast PARAFACbased algorithm by establishing the trilinear PARAFAC model.Relying on the uniqueness of the low-rank three-way array decomposition and the trilinear alternating least squares regression, the proposed algorithm achieves nominal DOA estimation and outperforms the conventional estimation of signal parameter via rotational technique CD（ESPRIT-CD） and propagator method CD（PM-CD）methods in terms of estimation accuracy. Furthermore, by means of the initialization via the propagator method, this paper accelerates the convergence procedure of the proposed algorithm with no estimation performance degradation. In addition, the proposed algorithm can be directly applied to the multiple-source scenario,where sources have different angular distribution shapes. Numerical simulation results corroborate the effectiveness and superiority of the proposed fast PARAFAC-based algorithm.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金supported by the National Natural Science Foundation of China(61872423)Industry Prospective Primary Research&Development Plan of Jiangsu Province(BE2017111)+1 种基金the Scientific Research Foundation of the Higher Education Institutions of Jiangsu Province(19KJA180006)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX20_0764)。
文摘Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on container startup(e.g.,distributed deep learning application),the image“warm-up”technique which prefetches images of these replicas to destination nodes in the cluster is proposed.However,the current image“warm-up”technique solely focuses on identical image distribution,which fails to take effect when distributing different images to destination nodes.To address this problem,this paper proposes Hound,a simple but efficient cluster image distribution system based on Docker.To support diverse image distribution requests of cluster nodes,Hound additionally adopts node-level parallelism(i.e.,downloading images to destination nodes in parallel)to further improve the efficiency of image distribution.The experimental results demonstrate Hound outperforms Docker,kubernetes container runtime interface(CRI-O),and Docker-compose in terms of image distribution performance when cluster nodes request different images.Moreover,the high scalability of Hound is evaluated in the scenario of ten nodes.
基金Project(KC18071)supported by the Application Foundation Research Program of Xuzhou,ChinaProjects(2017YFC0804401,2017YFC0804409)supported by the National Key R&D Program of China
文摘The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.
基金Supported by Hubei Provincial Natural Science Foundation(2008CDB363)
文摘This paper simulated the optimal refrigerant charge inventory of a refrigeration system in air-conditioning operation and heat-pump operation respectively,and studied the refrigerant control strategies in this system.The void fraction in two-phase fluid region was calculated by Harms model.And based on distributed parameter model and Harms model,the refrigerant charge inventory in condenser and evaporator were calculated and analyzed in air-conditioning conditions and heat-pump conditions,respectively.The calculating results of different refrigerant mass between refrigeration and heating conditions indicate that the optimal refrigerant charge inventory in heat-pump conditions is lower than that in air-conditioning conditions.To avoid the decrease of COP due to the surplus refrigerant in heating conditions,we introduced the liquid reservoir control method and associate capillary control method.Both of them could increase the heating capacity of the air-source heat pump.The difference of optimal refrigerant charge inventory in air-conditioning and heat-pump system can be controlled by the liquid reservoir or the associate capillary.
基金supported by the National Natural Science Foundation of China(11273017)
文摘A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.
