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In recent years, facial expressions of pain have been the focus of considerable behavioral research. Such work has documented that pain expressions, like other affective facial expressions, play an important role in social communication. Enabling computer systems to recognize pain expression from facial images is a challenging research topic. In this paper, we present two systems for pain recognition...
Traditional connectionist models place an emphasis on learned weights. Based on neurobiological evidence, a new approach is developed and experimentally shown to be more robust for disambiguating novel combinations of stimuli. It does not require variable weights and avoids many training related issues. This approach is compared with traditional weight-learning methods. The network is better able...
Entropy partition method for complex system has been applied in many ldnds of fields. In this paper, we improve the calculation of correlative measure for both discrete variables and continuous variables, and apply this method in vascular endothelial dysfunction (ED) discrete data and neuro-endocrine-immune (NEI) continuous data respectively. The partition results show this entropy partition methodpsilas...
We develop a data mining system to assist with the elucidation by graphical means of the biochemical changes in the brains of rodents. Manual analysis of such experiments is increasingly impractical because of the voluminous nature of the data that is generated, and the tedious nature of the analysis means that important information can be missed. For this purpose we are constructing an increasingly...
Biometric based person identification systems are used to provide alternative solutions for security. Although many approaches and algorithms for biometric recognition techniques have been developed and proposed in the literature, relationships among biometric features have not been studied in the field so far. In this study, we have analysed the existence of any relationship between biometric features...
In this paper we described a sound-source localization (SSL) system which can be applied to mobile robot and automatic control systems. A novel approach of using artificial neural network was proposed to obtain the horizontal direction angle (azimuth) of the sound source. According to humanoid characteristic only two microphones, which were attached symmetrically on both sides of the robot as its...
A problem solving domain for the application of artificial intelligence (AI) methods towards knowledge discovery for the purposes of modelling and forecasting is urban air quality. This domain has the specific characteristic that the key parameters of interest (pollutant concentration criteria) have multiple temporal (and spatial) scales. The present paper applies ANNs for the operational forecasting...
Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximators. Spiking neural networks offer several advantages over sigmoidal networks, because they can approximate the dynamics of biological neuronal networks, and can potentially reproduce the computational speed observed in biological...
This paper presents the development and design of two software tools for computational intelligence. The software tools include a graphical user interface for construction, edition and observation of the intelligent systems. The software tool are for interval type-2 fuzzy logic and modular neural networks. The interval type-2 fuzzy logic system toolbox (IT2FLS), is an environment for interval type-2...
The present paper illustrates a geodesic-based learning algorithm over a curved parameter space for blind deconvolution application. The chosen deconvolving structure appears as a single neuron model whose learning rule arises from criterion-function minimization over a smooth manifold. In particular, we propose here a learning stepsize selection theory for the algorithm at hand. We consider the blind...
The paper puts forward a concept of cognitive sensor networks and investigates a feasibility of artificial neural networks application for its realization. It describes a design of novel hierarchical configurations imitating the structural topology of brain-like architectures. They are composed from artificial neural networks distributed over network platforms with limited resources. The paper examines...
The multiresolution analysis learning algorithm (MRAL) for neural networks is proposed to get a more precious model from the noisy data set, which based on Multiresolution Analysis (MRA) of the wavelet transformation and nondominated sorting genetic algorithm-II (NSGA-II). Several different scaled signals of the error function are used as the objections, and NSGA-II algorithm is applied to optimize...
Image segmentation has attracted the attention of researcher for many decades. Different approaches have been developed in order to find the solution in many different segmentation situations. In this paper we propose a novel edge detection approach aimed to generate useful information to achieve segmentation. The proposed method is based on analysis of the information provided by the time matrix...
With the computer accurate estimation of electronic parts defect detection in quality control play an important role in the manufacturing industry. In order to realization electronic parts product appearance quality detection control, one kind of processor based on the intelligent knowledge automatic extraction and system integration modeling was presented This paper proposes a method using an adaptive...
Sound localisation is defined as the ability to identify the position of a sound source. The brain employs two cues to achieve this functionality for the horizontal plane, interaural time difference (ITD) by means of neurons in the medial superior olive (MSO) and interaural intensity difference (IID) by neurons of the lateral superior olive (LSO), both located in the superior olivary complex of the...
Aircraft noise is influenced by many complex factors and it is difficult to devise an accurate mathematical model to simulate it with respect to operations at an airport. This paper presents an investigation in simulating airport noise using artificial neural networks. The results show that it is possible to establish a simple neural network model with monitored data for a specific airport and specific...
With the development of market economy in China, the problem of bad debt becomes increasingly serious in enterprises. In this paper, a bad-debt-risk evaluation model is established based on LS-SVM classifier, using a new set of index system which combines financial factors with non-financial factors on the basis of the 5C system evaluation method. The bad debt rating is separated into four classes-...
Measurement of visual quality is of fundamental importance to some image processing applications. And the perceived image distortion of any image strongly depends on the local features, such as edges, flats and textures. Since edges often convey much information of an image, we propose a novel algorithm for image quality assessment based on the edge and contrast similarity between the distorted image...
This study theoretically analyzes and numerically explores the relationship between the physiological data and three diabetic microvascular complications: diabetic retinopathy, diabetic nephropathy, and diabetic neuropathy (foot problem). Method: The analysis results of 8,736 diabetic patients in northern Taiwan by using two data mining models: C5.0 and neural network were presented and compared....
Computational intelligence methods are well-suited for use in computer controlled opponents for video games. In many other applications of these methods, the aim is to simulate near-optimal intelligent behaviour. But in video games, the aim is to provide interesting opponents for human players, not optimal ones. In this study, we trained neural network-based computer controlled opponents to play like...
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