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Since ECG is huge in size sending large volume data over resource constrained wireless networks is power consuming and will reduce the energy of nodes in Body Sensor Networks (BSN). Therefore, compression of ECGs and diagnosis of diseases from compressed ECGs will play key roles in enhancing the life-time of body sensor networks. Moreover, discrimination between ventricular Tachycardia and Ventricular...
The strategy of feature extraction and selection enabling to improve efficiency of fault detection methods for analog nonlinear circuits is presented in the paper. Simple algorithm for data selection, ensuring the proper diagnosis of faulty circuits having limited number of testing points, under assumption, that complex signal processing tools are not available, is proposed and tested.
This paper presents a position-varied plate utilized for Thai license plate recognition using back propagation neural network (BPNN). In this method, a dimension image of the car is suitably decreased by image resizing (e.g. interpolation method), and then they are converted to gray images for inputs to plate localization process. The plate localization process is used to find the area position of...
The paper proposes a novel neuron model termed as Generalized Power Mean Neuron model (GPMN). The paper focuses on illustrating the computational power and the generalization capability of this model. In this model, the aggregation function is based on generalized power mean of the inputs. The performance of the neural network using GPMN model is compared with traditional feed-forward neural network...
Rough sets theory is a new tool for processing fuzzy and uncertain knowledge, and has already been applied to many areas successfully. In this paper, a freeway traffic flow model based on rough sets and Elman neural network is put forward. The main idea of this approach is that some redundant features of sample data are reduced by rough sets firstly, then Elman neural network is used to build traffic...
Fault diagnosis of induction motor is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. Due to environmental stress and many others reasons different faults occur in induction motor. Many researchers proposed different techniques for fault detection and diagnosis. However, many techniques available presently...
This paper presents a novel method on coloring the grayscale images. For this purpose, a combination of artificial neural networks and some image processing algorithms was developed to transfer colors from a user-selected source image to a target grayscale image. According to the results of this combining method, a survey where volunteers were asked to rate the plausibility of the colorings generated...
In distributed virtual environment many methods of data distribution management (DDM) are presented to efficiently improve network traffic situation and save system resources, these technologies are based on virtual environment partition. The grid size of the partition affects the data distribution results. This paper aims to present a neural-network based study mechanism, which adjusts the grid size...
In this paper, 36 coats, which had different ease and made from different fabrics, were made and their profile appearance were evaluated by seven experts. These coats were scanned by using [TC]2 three dimensional body scanner and their three dimensional virtual pictures was shown according to the OpenGL software surface display theory. Key factors witch affected garments appearance ease most were...
Telecommunication fraud prediction in this paper is an interpolation problem that uses the daily telecommunication network services information to analyze and predict the alarm information generated from a detection engine by minimizing false cases. This paper proposed the use of backpropagation neural network (BPNN) to perform telecommunication interpolation based on local telecommunication network...
This paper studies learning transfer based on the adaptive learning theory, intelligence cognitive model theory and knowledge input theory under the large framework of updated cognitive theory of psychology. It mainly focuses on the method and experiment of positive transfer in production system self-adaptability model with the help of updated Artificial Neural Networks communication technology. These...
A new technique for fast detection of power islands in a distribution network, which uses transient signals generated during the islanding event is investigated. Performance comparison of several pattern recognition techniques in classifying the transient generating events as islanding or non-islanding is presented. Features for the classifiers are extracted using the Discrete Wavelet Transform of...
In Grid computing resource selection is a challenging problem, because Grid scheduler is usually operating in a dynamic and uncertain environment. Conventional scheduling algorithms will fail due to the static rules specified at design time and much user intervention required. Neural networks with a fast and accurate learning paradigm are promising to solve the Grid resource selection problem. This...
In the field of Computer Science, neural networks are being implemented to solve problems more reliably and accurately. To serve artificial intelligence, computer program using neural can be one of the effective solution. So a program can be learned, trained up and after a certain stage it will able to take applicable decisions. This makes our works performing in reachable and well accepted dynamically...
Data transformation method is well known in Knowledge Discovery in Databases (KDD) process and data mining in order to transform raw data into concepts at higher levels concepts. A number of promising data transformation methods have been studied and developed. Despite the great advantages offered by these data transformation methods, these methods still requires further improvement. In order to handle...
This paper presents the classification of benign and malignant breast tumor based on fine needle aspiration cytology (FNAC) and probabilistic neural network (PNN). Five hundred and sixty nine sets of cell nuclei characteristics obtained by applying image analysis techniques to microscopic slides of FNAC samples of breast biopsy have been used in this study. These data were obtained from the University...
The driver emergency braking behavior to be distinguished and predicted exactly was difficult. In order to gain the testing data of driver emergency braking action, 7 professional drivers were selected and 3 scenes of driver braking behavior were designed and simulated by means of road test. And the testing data were captured by the data acquisition system with sensors. Utilizing relative fuzzy membership...
The techniques of eigenfaces and neural net-based algorithms (LS-SVM and BP NNs) are combined to categorize gender from facial images in this paper. Based on exploration of the related techniques, the eigenfaces were firstly established from the training images, and the projection coefficients for training and testing images obtained in the space spanned by the eigenfaces; after that the LS-SVM and...
In order to resolve the wrapper optimization and TAM co-optimization issues, this paper presented a new technique based on neural network combined with genetic algorithm to achieve dynamic scheduling test resources.The result of experiments on ITC'02 benchmark indicates that this method could make minimize the testing time for SOC.
The paper introduces BP neural network technology and establishes the evaluation index system of credit of practicing qualification personnel in construction market based on relevant characteristics. Then a classification model of the two kinds of practicing qualification personnel based on BP neural network technology is proposed. In order to test the validity of the classification model, the paper...
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