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In the literature, a number of methods have been proposed for semi-supervised learning. Recently, graph-based methods of semi-supervised learning have become popular because of their capability of handling large amounts of unlabeled data. However, the existing graph based semi-supervised learning algorithms do not optimize the process of selecting better labeled data. We have developed a new selective...
Feature representation plays an important role in text classification. Feature mapping based on labels information is an algorithm suitable for Binary Relevance. Compared with the conventional text representation, it makes the dimension of the text under control by means of word embedding. More importantly, it takes full advantage of the general characteristics of the label on text representation...
Spectrum sensing is one of the key technologies of cognitive radio. Based on noise characteristics estimation and support vector machine (SVM) technology, this paper proposed a frequency domain two-stage spectrum sensing method to improve sensing accuracy under low signal-to-noise ratio scenarios with low system complexity and high generalization ability. In the slow sensing stage, the frequency-domain...
There are nonlinearities in an electro-hydraulic shaking table, causing harmonic distortion when it corresponds to a sinusoidal excitation, due to higher harmonics in the acceleration response. This paper aims to develop a harmonic identification method for a hydraulic shaking table by using Fourier series based Back Propagation (BP) network. The learning problem of hidden layer is solved by selecting...
Term weighting schemes have been widely used in information retrieval and text categorization models. In this paper, we first investigate into the limitations of several state-of-the-art term weighting schemes in the context of text categorization tasks. Considering that category-specific terms are more useful to discriminate different categories, and these terms tend to have smaller entropy with...
In this paper, we propose a novel extension to the Class-specific Hough Forest (CHF) framework for object detection and localization. Our approach utilizes depth information during training to build a more discriminative codebook which simultaneously encodes features from the object and the surrounding context. In particular, we augment the CHF with contextual image patches, and design a series of...
The teaching of equipment training is one of the necessary means of equipment safeguard. Facing increasingly complicated structure of equipments, there are many limitations about the real machine teaching while virtual reality technology can simulate actual structure of equipment vividly which can highlight the training characteristics. This article is combined with professional teaching and designs...
This paper introduces a simulation and training systems of protective relaying based on competent technology, which takes fault filter data and simulation data as data sources. Visual C++ programming language is used for data modeling base on IEC61850 standard. A base model describing the function of protection and control devices and the principle of action logic and its training applications are...
Boosting algorithms attract much attention in computer vision and image processing because of their strong performance in a variety of applications. Recent progress on the theory of boosting algorithms suggests a close link between good generalization and the margin distrubtion of the classifier \wrt a dataset. In this paper, we propose a novel data-dependent margin distribution learning criterion...
Medical imaging devices have been growing exponentially around the world with the advancements in CT, MRI, Ultrasound and other devices. With these advancements come growing opportunities for medical image analysis which can support diagnostics, surgical assistance, rehabilitation and patient care. The applications of medical imaging in emerging economies like India include automatic TB detection,...
We present a novel boosting cascade based face detection framework using SURF features. The framework is derived from the well-known Viola-Jones (VJ) framework but distinguished by two key contributions. First, the proposed framework deals with only several hundreds of multidimensional local SURF patches instead of hundreds of thousands of single dimensional haar features in the VJ framework. Second,...
According to the new execution of 2010 International cardiopulmonary resuscitation (CPR) & Emergency Cardiovascular Care (ECC) Guide Standard above American Heart Association(AHA), this paper designs the main control system and the measurement system of CPR Simulation Control System based on SCM LPC932 and SCM LPC935. According to the strength of artificial respiration and cardiopulmonary press...
The teaching reform and exploration have been taken in the course of introduction to biotechnology for developing the innovation, practice ability and professional skills. The content system and organization way of this course had been adjusted by the educational thought of Blending Learning. Lots of teaching methods were adopted, such as diverse forms of classroom instruction, optimizing the experimental...
In this paper, we first discuss the current conditions of education on software engineering talents. Then we recommend an example adopted by school of computer in Hubei University of Economics, in which we address the education model of talents training, and raise the opinion that education model of software engineering must orient vocation and utilize the iterative approach. To the end, we summarize...
This paper presents an Elman neural network based on Genetic algorithms for the identification of dynamic equivalents of power system. The Elman neural network is one of the dynamic recurrent neural networks. In this paper, a modified Elman network is introduced first. Then we propose its training algorithm using Genetic algorithms. Lastly, the proposed method is demonstrated and compared with the...
This paper presents a proposal for a person authentication system, which localizes facial landmarks and extracts biometrical features for face authentication. An efficient algorithm for eye localization and biometrical feature extraction and person identification is developed by using Gabor filters. We build artificial average eye models for eye location. Databases of biometrical features around the...
Diagnosis of power transformer abnormality is very important for power system reliability. This paper presents a novel approach for power transformer fault diagnosis based on probabilistic neural network and dissolved gas-in-oil analysis (DGA) technique. A new hybrid evolutionary algorithm combining particle swarm optimization (PSO) algorithm and back- propagation (BP)algorithm, referred to as HPSO-BP...
Local binary pattern histogram (LBPH) is one of the popular and excellent image texture descriptor. However, conventional LBPH lacks of the description of spatial structure information. This paper proposes an extension of LBPH called Markov chain local binary patterns (MCLBP) to alleviate this limitation. We apply MCLBP to the task of TRECVID video concept detection. Experimental results demonstrate...
This paper focuses on continuous attributes handling for mining data stream with concept drift. Data stream is an incremental, online and real time model. Domingos and Hulten have presented a one-pass algorithm. Their system VFDT use Hoeffding inequality to achieve a probabilistic bound on the accuracy of the tree constructed. VFDTpsilas extended version CVFDT handles concept drift efficiently. In...
In many real world data mining and classification tasks, we face with the problem of high cost in making training data sets. In addition, in many domains, different misclassification errors involve different costs. These two issues are often addressed by semi-supervised learning and cost-sensitive learning separately. Sometimes the two issues can happen at the same time in real world applications...
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