Suzhen Wang¹, Yanpiao Zhang¹, Lu Zhang¹, Ning Cao^{2, *}, Chaoyi Pang³

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 415-431, 2018, DOI: 10.3970/cmc.2018.03716

Abstract Spark is a fast unified analysis engine for big data and machine learning, in which the memory is a crucial resource. Resilient Distribution Datasets (RDDs) are parallel data structures that allow users explicitly persist intermediate results in memory or on disk, and each one can be divided into several partitions. During task execution, Spark automatically monitors cache usage on each node. And when there is a RDD that needs to be stored in the cache where the space is insufficient, the system would drop out old data partitions in a least recently used (LRU) fashion to release more space. However,… More >

Raquel R. Pinho¹, João Manuel R. S. Tavares¹

CMES-Computer Modeling in Engineering & Sciences, Vol.46, No.1, pp. 51-76, 2009, DOI:10.3970/cmes.2009.046.051

Abstract This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features' movement in every image frame. So as to integrate the measurements obtained from each image into the Kalman filter, a data optimization process has been adopted to achieve the best global correspondence set. The proposed criterion minimizes the cost of global matching, which is based on the Mahalanobis distance. A management model is employed to manage the features being… More >

C. Jiang¹, X. Han^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.22, No.2, pp. 97-118, 2007, DOI:10.3970/cmes.2007.022.097

Abstract A new uncertain optimization method is developed based on intervals and an approximation management model. A general uncertain optimization problem is considered in which the objective function and constraints are both nonlinear and uncertain, and intervals are used to model the uncertainty existing in the system. Based on a possibility degree of interval,anonlinear interval number programming (NINP) method is proposed. A deterministic objective function is constructed to maximize the possibility degree of the uncertain objective function, and the uncertain constraints are changed into deterministic ones by introducing some possibility degree levels. If the optimal possibility degree of the objective function… More >

Xiaodong Liu¹, Qi Liu^1,*

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 179-194, 2018, DOI:10.32604/cmc.2018.04025

Abstract In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load data in a HEMS sensor network, however, problems can be caused on the data due to faulty sensing processes and/or lost links, etc. In order to ensure the quality of retrieved load data, different solutions have been presented, but suffered from low recognition rates and high complexity. In this paper, a validation and repair method is presented to detect potential failures and errors in a domestic… More >