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Offloading the computation-intensive task of mobileinteractive applications into cloudlets has become a popularway to reduce the response time in mobile cloud computingarea. In response to the rapid change of mobile environment, researchers have proposed online offloading decisions for variousapplications. However, the pruning method they used wouldperform poorly for the non-linear topology of applications...
We survey the recent progress in the research and development of RRAM technology in the past decade, ranging from compact models to involving applications. In particular, we first present an overview of the representative compact models that have been developed to capture essential electrical/chemical/thermal properties of RRAM such as IV characteristics, switching dynamics, variability and reliability,...
In this paper, we propose a computational model of visual attention for stereoscopic video. Low-level visual features including color, luminance, texture and depth are used to calculate feature contrast for spatial saliency of stereoscopic video frames. Besides, the proposed model adopts motion features to compute the temporal saliency. Here, we extract the relative planar and depth motion for temporal...
Most nonlinear unmixing algorithms are based on the nonlinear mixing models with different forms. This paper focuses on the well-known generalized bilinear model (GBM). Though the GBM has shown interesting and promising for nonlinear unmixing, currently almost all the GBM-based unmixing algorithms are supervised. That is, the endmembers must be assumed known in advance. This paper develops an unsupervised...
Cognitive diagnostic models (CDMs) are a new class of test models developed for educational assessment. They have gained growing attention in recent years for their distinctive ability to provide detailed feedback about examinees' ability. Automatic test assembly (ATA), as in other test models, has been one of the most critical issues in the development and applications of CDMs. However, developing...
Hand gesture recognition is an important topic in human-computer interaction. However, most of the current methods are complicated and time-consuming, which limits the use of hand gesture recognition in real-time circumstances. In this paper, we propose a data fusion-based hand gesture recognition model by fusing depth information and skeleton data. Because of the accurate segmentation and tracking...
In order to solve parallel algorithm of Petri net system with concurrent functions and implement parallel control and execution of Petri net, parallel programming model of Petri net based on multi-core clusters is put forward. First, P-invariant technology is used to do the functional division of Petri net system and the parallel analysis of Petri net process. Next, based on architecture of multi-core...
We present a large-scale eye tracking database for stereo-scopic video. A set of participants were involved in this eye tracking experiment. The human fixation maps were created as the ground truth for stereoscopic video from the gaze data from participants. To the best of our knowledge, this is the first large-scale eye tracking database of visual attention modeling for stereoscopic video. The details...
Getting good viewpoints has been considered important for promoting the efficiency when investigating a model. Many view selection methods therefore have been proposed. In particular, measuring semantic meaning of the model features through segmentation is regarded more effective to get optimal viewpoints. Unfortunately, the semantic meanings of the model are usually obtained through experiences,...
Defending against spam in tagging system is a verychallenging task. This paper presents ReSpam, a novel reputationbased mechanism of defending against tag spam in taggingsystems. In ReSpam, timing behaviors and voting methods areintroduced to defend tag spam. Each user has a global reputationwhich can increase or decrease after some judgement given bythe tagging system. When the system finds that...
In this paper, we propose a fast MPI algorithm for Monte Carlo approximation PageRank vector of all the nodes in a graph, named Fast Fibonacci Series-Based Personal PageRank. In the latter paper we will call it FFSB algorithm for short. The basic ideal is very efficiently computing single random walks of a given length starting at each node in a graph. More precisely, we design FFSB, which given a...
Recently, the employment demand has been paid a lot of attention to so that the research with respect to the forecasting methods such as linear regression, artificial intelligence and the grey prediction method have been comprehensively investigated. Since the predictive focus and the characteristics of the methods are different, the outcomes of predictions cannot achieve the accuracy by simply hybridizing...
Data analyzing and processing are important tasks in cloud computing. The MapReduce framework has been increasingly used to analyze large-scale data over large clusters. Compared with parallel relational database, it has the advantages of excellent scalability and good fault tolerance. However, its performance is not as good as that of parallel relational database. How to efficiently implement join...
With the popularity of Internet of Things, the next logical step will focus on the application layer on top of network connectivity, especially Web of Things. While most of the existing efforts on Web of Things are focused on device mash up and data collection, in this paper a semantic web of things framework is proposed to leverage Semantic Web as the unified mechanism for monitoring, tasking, presentation,...
With the aim of solving the problems of the Petri nets to the place/transition nets automatic conversion and realization of Petri nets parallel control and running, the algorithm is proposed to transform Color Petri net systems transform into P/T nets. The algebraic model of colored Petri nets and P/T nets, and its intrinsic mechanism is analyzed, the process and theory verification of the colored...
Increasingly, software needs to dynamically adapt its structure and behavior at runtime in response to changing conditions in the supporting computing, network infrastructure, and in the surrounding physical environments. By high complexity, adaptive programs are generally difficult to specify, verify, and validate. Assurance of high dependability of these programs is a great challenge. Efficiently...
Quality of Service (QoS) has been widely used to support dynamic Web Service (WS) selection and composition. Due to the volatile nature of QoS parameters, QoS prediction has been put forward to understand the trend of QoS data volatility and estimate QoS values in dynamic environments. In order to provide adaptive and effective QoS prediction, we propose a WS QoS prediction approach, named WS-QoSP,...
Abnormal behavior detection refers to the problem of finding patterns in data that do not conform to expected behavior. Detection of abnormal behavior is an important area of research in computer vision and is also driven by a wide of application domains, such as smart video surveillance. In this paper, we present a novel based-energy approach for abnormal behavior detection. Use an adaptive optical...
Electronic Commerce has offered a convenient way for people to go shopping on the Internet. However, it is difficult for Internet customers to select a valuable item from the great number of various products available on line. When we use a keyword and search in a EC website, the ranking algorithm of products is usually based on statistics or simply the shop manager's preference, which does not fully...
Spectrum allocation is one of the key techniques of spectrum management in cognitive radio. In this paper, we introduce a new spectrum allocation algorithm named multi-level allocation algorithm based on cost minimized matching algorithm. Characteristics of both spectrum holes and cognitive users are taken into account in the new algorithm. Based on the statistical information of the characteristics,...
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