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With the increasing number of network comments, mining product reviews is an emerging area of research which fundamental work is focused on feature extraction. Previous studies mainly focus on explicit features extraction while often ignore implicit features which haven't been stated clearly but containing necessary information for analyzing comments. Actually in our study, we find a lot of implicit...
State Grid Jibei Electric Power Company (Jibei) has accumulated a large number of operation data through the maintenance of the equipment, devices in power grids. It is of great significance to study this data and extract the useful information by the data mining and statistics techniques. While the theories and methods of Naive Bayes have been widely studied, this paper utilizes such technique to...
Sports video summarization and classification is becoming a very important topic due to the pressing need to automatically classify sports scenes to enable better sport analysis, refereeing, training and advertisement. The vast majority of the techniques applied to sports video classifications involved black box techniques such as support vector machines (SVMs) and neural networks, which do not provide...
The recent years have witnessed significant progress in the automation of sports video summarization. The vast majority of the techniques applied to sports video classifications involved black box techniques such as support vector machines (SVMs) and neural networks, which do not provide models that could be easily analysed and understood by human users. Video scenes can be regarded as continuous...
This article proposes two modifications of a new unsupervised method of word segmentation consisting of three phases: Evaluation, Selection, and Adjustment (ESA), which was presented in our early paper. Lowest Relative Value (LRV) is the core algorithm in ESA The whole method has only one parameter (the exponent in LRV) that can be approximately predicted by the empirical formulae. In this article,...
Cooperation among wireless nodes at the medium access control (MAC) layer has attracted a lot of research attention in recent years. Most of existing cooperative MAC protocols focus on the scenarios with static helpers (relay nodes). However, when the helpers are moving around, the source node may choose a leaving helper with out-of-date information, which could cause performance deterioration. Hence,...
The authors propose a scheme of simulation training system based on SOA for switching operation. This system is developed by Microsoft Visual Studio 2010, and realizes the basic functions such as Switching Operation, Monitoring panel display. The system provides students with the online training platform to help them as soon as possible into the work role as a qualified professional and technical...
Recently, the research on Brain-Computer Interface (BCI) technology has achieved great progress, and the BCI system based on Motor Imagery (MI) has been intensively studied in many labs. The essential part of signal processing in BCI is how to extract the MI features in electroencephalographic (EEG) and recognize the MI task accurately. One challenge lies in that EEG signals are non-stationary, whose...
In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)-based electroencephalographic (EEG) classification. However, the computation of decision function during SVM classification stage for a new EEG trial is time-consuming due to the large number of support vectors (SV). This paper proposes a new method to reduce the number of support vectors so that...
The integrated brake controller involves in one electronic unit the antilock control, traction control, yaw stability control and braking force distribution that manipulate forces and timing of braking on each wheel. Main difficulty is that the vehicle-tire dynamics is a nonlinear process. Secondly, controls of antilock, traction, yaw stability and braking force distribution operate for different...
The traditional intensity evaluation method of land use is highly influenced by man's subjective impact, thus the evaluation result is not accurate enough. In this paper, a BP artificial neural networks model was set up to evaluate the urban land intensive use. On the basis of that, Ezhou Municipal in Hubei province was taken as a case study. The results show that urban land use of Ezhou Municipal...
Intention-oriented computational visual attention (ICVA) model attempts to imitate human vision by computational intelligence. This paper contributes to enabling the ICVA model with learning ability so as to acquire or change intention according to assigned image samples. This innovative design is called the self-learning ICVA model which contains a neuro-fuzzy network to learn intention from image...
In this paper, we present a system of patient robot developed with the aim at improving abilities of nursing student's medical treatment, such as injection to vein. We propose to realize variable emotion of patient robot by using chaos orbit of non-linear time-differentiation equation. To evaluate the effectiveness of the robot through actual injection training, we measure heartbeat rate of nurse...
This paper proposed a new segmentation algorithm of 3D medical image based on Hopfield neural networks. The method makes Hopfield neural networks and genetic algorithm (GA) combined and use texture analysis to achieve segmentation of tumor CT image. This method not only overcome shortcoming that the Hopfield neural network easily converge to local optimal solution, but also break the constraints that...
A new algorithm of Web text clustering mining is presented, which is based on the Discovery Feature Sub-space Model (DFSSM). This algorithm includes the training stage of SOM and the clustering stage, which characterizes self-stability and powerful antinoise ability. It can distinguishes the most meaningful features from the Concept Space without the evaluation function. we have applied the algorithm...
This paper proposes a new email classification model using a linear neural network trained by perceptron learning algorithm (PLA) and a nonlinear neural network trained by back propagation neural network (BPNN). A semantic feature space (SFS) method has been introduced in this classification model. The bag of word based email classification system has the problems of large number of features and ambiguity...
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