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Subspace learning has been widely used in signal processing, machine learning, computer vision and so on. Matrix rank minimizing is a fundamental model. Nuclear norm is a convex relaxation for rank minimizing. In this paper, we propose a polynomial function to smoothen the nuclear norm. Lagrange multipliers method is employed to solve the problem. The optimal solution is obtained by iterative procedure...
In this article, we propose a new dynamic reliability management (DRM) techniques at the system level for emerging low power dark silicon manycore microprocessors operating in near-threshold region. We mainly consider the electromigration (EM) failures. To leverage the EM recovery effects, which was ignored in the past, at the system-level, we propose a new equivalent DC current model to consider...
In this article, we propose a new behavioral thermal modeling method for fast building performance analysis, which is critical for energy-efficient smart building control and management. The new approach is based on two recurrent neutral network architecture to obtain the compact nonlinear thermal models for complicated building. We start with a more realistic building simulation program, EnergyPlus,...
In daily life, people carry smartphones every where. The sensors included in smartphones can tell us much information. Activity recognition by smartphone can be used for healthcare and sports management. People carry smartphones in different positions, such as the pocket of the trousers, hands or bags. We use accelerometer embedded in the smartphones to classify five activities, such as staying still,...
Gas pipe flow simulation is used to optimize, verify design and to throw light on various operational issues. This paper illustrates some of the different parameters affecting how complicated it is to do those computations, arranged so that the simplest alternatives are on top.
This paper proposes a novel sentence ranking approach to query-biased summarization where ranking performance can be boosted by encouraging biased information richness in a multi-view framework. To investigate how the final ranking result can benefit from diverse local ranking's combination, the proposed approach firstly constructs two base rankers to rank all the sentences in a document set from...
In this paper, we introduce a new model order reduction tool, UiMOR - UC Riverside Model Order Reduction Tool. UiMOR fills the gap between parasitic extraction and post-layout simulation to improve the efficiency of VLSI circuit validation. UiMOR is a stand-alone circuit complexity reduction tool. It can perform accurate reduction for wideband frequency range with negligible loss of accuracy and is...
A BP artificial neural network model was established to optimize the final slope angle of open-pit mine, which was based on its powerful self-learning, nonlinear processing capabilities and advantages of simulation for the slope stability with nonlinear relationship among the parameters. The consideration of effect on the stability of the slope includes Protodrakonov scale of hardness, dip angle of...
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment...
In this paper, we propose a new wideband model order reduction method for interconnect circuits by using a novel adaptive sampling and error estimation scheme. We try to address the outstanding error control problems in the existing sampling-based reduction framework. In the new method, called WBMOR, we explicitly compute the exact residual errors to guide the sampling process. We show that by sampling...
To keep balance of global and local searching ability, and to overcome the slow convergence and prematurely of particle swarm optimization, a new algorithm that isolation niches embedded in particle swarm optimization (INPSO) is introduced. Solving the heavy traffic problem in existing condition is also worth considering. In this paper, the method of two-intersections traffic controlling is proposed...
Current methods of service discovery, using the same mechanism to describe both request and advertisement and does not take into account the asymmetry between the two. Service advertisement discovery is a complete description of descriptive, information-rich features, and service request description is concerned only with some of the characteristics of services, usually does not constitute a complete...
Spectrum access scheme is a fundamental component in building efficient wireless networks. Conventional methods such as proactive channel assignment is costly due to large amount of protocol overhead. Also, those algorithms suffer from its inability in dealing with channel dynamics. The opportunistic methods however, spend more time on probing, and suffer from the myopic decisions as well. We present...
The popularization of computer applications has prompted us to research into the teaching experiment and curriculum design on computer English curriculum reforms both in computer and correlative majors and in non-computer majors at two different levels. In the research, four parts of curriculum structure, known as curriculum objectives, curriculum contents, learning resources and learning models have...
Data mining has been widely considered as an effective tool for knowledge discovery. This paper discusses the important role of medical experts for medical data mining, and presents a model of medical knowledge acquisition through data mining.
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from high-dimensional data streams. We conduct a case study of SPOT in this paper by deploying it on 1999 KDD Intrusion Detection application. Innovative approaches for training...
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