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The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach...

Information technology (IT) has been extensively adopted in banking industries. The reasons for this massive adoption of IT are mainly twofold: for individual banks, IT can reduce banks’ operational costs (the cost advantage), and facilitate transactions among customers within the same network (the network...

Most researches have focused on the use of document feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively weak, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis...

A general phenomenon puzzles all investors is that on one hand, most individual investors believe they need to construct the portfolio consisting of 15 or more stocks to prevent risk because that large investment companies frequently get high returns is due to they obey the existing investment theory...

As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies...

The medical care industry has been dramatically developed in the last two decades in Taiwan and it has resulted in an extremely risky position. The purpose of the research was the development of a neural network model to recognize profitable customers for dental services marketing. Data set was built...

With the development of computer graphics and virtual realities, the demand for a content-based 3D model retrieval system becomes urgent. In this study, two features, grid sphere and dodecahedral silhouettes, are proposed and combined for 3D model retrieval. The experiments are conducted on a 3D model...

We propose a new feature selection procedure based on a combination of a pruning algorithm, Apriori mining techniques and fuzzy C-mean clustering. The feature selection algorithm is designed to mine on a multiresolution filter bank composed of rotationally invariant moments. The numerical experiments,...

A finger finding procedure has been presented to recognize the finger number of the hand gesture. The hand gesture is extracted from the stationary background and transformed into a binary image. The hue attribute, that is, the I value in the YIQ color space is used to extract the hand gesture shape....

This paper proposed an effective and robust method to detect the rare behavior events within the compressed video directly. New motion feature called object-based accumulative motion vector (OAMV) is generated to extract a prominent motion feature and then polar histograms are used to describe the distribution...

This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation...

Generalized Lloyd Algorithm(GLA) is important in vector quantizer design. It runs fast, but it is sensitive to initial conditions and it may find a local optimum. We propose an improved approach based on GLA, named vector quantized codebook reorganization algorithm (VQCRA). VQCRA finds better codebooks...

As a new general machine-learning tool based on structural risk minimization principle, Support Vector Machines (SVM) has the advantageous characteristic of good generalization. For this reason, the application of SVM in fault diagnosis field has becomes one growing reach focus. In this paper, data fusion...

This paper proposes a new approach for tracking the contour of moving object for head-shoulder video sequence using initial shape model. First, we can utilize manual process or some segmentation approach to obtain the initial shape model. Then, we detect the changing ratio of intensity outside the bounding...

The purpose of this research is to use the visual inspection technique for the automatic tool wear measurement of different coated drills. The tool wear images with the different coated drilling are captured using a machine vision system incorporating with an effective vertex detection algorithm based...

Due to the flood of pornographic web sites on the internet, content-based web filtering has become an important technique to detect and filter inappropriate information on the web. This is because pornographic web sites contain many sexually oriented texts, images, and other information that can be helpful...

In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching...

Correct classification of various kinds of scenes in sport videos is essential for higher-level content analysis such as event detection. The paper presents a novel technique for the classification of the typical scenes of baseball videos. The spatial color features are employed to detect pitch scene...

SIGNATURE RECOGNITION USING CONJUGATE GRADIENT NEURAL NETWORKS Transforming the input before training yields much lower error, but is more sensitive. Most importantly, we have presented system can vary in security depending on the situation. Uses for such a system range from securing a credit card transaction...

A method to analyze and assess knowledge sharing risks in the virtual enterprise is proposed. Firstly, based on risks analysis, an index system is set up to assess such risks as the core competence losing risk, the enterprise culture risk, the knowledge spillover effect risk and the moral risk, etc.....

The portfolio optimization model, initially proposed by Markowitz in 1952 and known as mean-variance model (MV model), is applied to find the optimized allocation among assets to get higher investment return and lower investment risk. However, the MV model did not consider some practical limitations...

This paper introduces the least absolute deviation estimators to construct an interval regression model, having interval output and crisp input data when the data contains interval outliers.

In this paper we introduce a practicable system by combining a vision processing algorithm and a fuzzy controller to obtain an efficient active tracker. Target tracking performance is heavily dependent on a good blend of vision algorithm and control. Because of performance and computational complexity,...

Most decision-making and problem-solving tasks are too complex to be understood quantitatively. People perform such tasks using knowledge that is imprecise rather than precise. This study presents consistent fuzzy linguistic preference relations rather than fuzzy analytic hierarchy process (FAHP) to...

Based on the fuzzy set theory, this study introduces three novel three-phase fuzzy feeder models for fast distribution system calculations. These fuzzy models are formulated using three lumped individual phase loads to represent single-phase, three-phase unbalanced, and nonuniformly distributed loads...

Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism...

In this paper, we present a search model, which divide symptoms into two sets, i.e., the positive symptom set (J1) and the negative symptom set (J2), to eliminate the causes of low possibility in the cause set to more effectively find various possible breakdown causes occurred during spinning process....

The paper deals with fuzzy attribute logic (FAL) and shows its completeness over all complete residuated lattices. FAL is a calculus for reasoning with if-then rules describing particular attribute dependencies in object-attribute data. Completeness is proved in two versions: classical-style completeness...

We present Pavelka-style fuzzy logic for reasoning about attribute implications, i.e. formulas $A\Rightarrow B$. Fuzzy attribute implications allow for two different interpretations, namely, in data tables with graded (fuzzy) attributes and in data tables over domains with similarity relations. The axioms...

The teachers and the school authorities often call the parents in connection with a child’s ‘performance’ in school. The children have to face the wrath of both the parents and the teachers. This tension slowly builds up and the child decides to quit the school forever. This paper analyzes the causes...

In this paper, a comparison study for the non-stationary power signal prediction by using several neural models is presented. A reliable and accurate neural forecasting model is trying to be found and concluded. This study is expected to provide some suggestions and could be treated as a reference for...

In the fast-changing business environment, supply chains are affected by the production and inventory strategies, which influence the amount of information needed by the chains. The firms must therefore determine the best supply chain inventory strategies for their products. The lack of precise market...

Fuzzy controllers in general are designed using the experts’ knowledge or human experience in order to decide the settings of a number of system factors. However, the relations between the factors and system performance are not easy to be determined. Usually, more than one system performance characteristic...

As the modern construction market and environment encounter drastic changes, a single company alone can no longer manage a complex project and satisfy project owner’s needs. Joint venture (JV) of companies, formed to integrate various expertises, becomes a necessity to obtain competitive advantages to...

A fuzzy logic controlled protocol that enables each station to tune its contention window based on the on-line channel sensing results is proposed for the wireless local area networks. Extensive simulations are provided to compare the performance of the proposed protocol with that of the distributed...

This work proposes a two-stage immune algorithm that embeds the compromise programming to perform multi-objective optimal capacitor placement. A new problem formulation model that involves fuzzy sets to reflect the imprecise nature of objectives and incorporates multiple planning requirements is presented....

The purpose of this paper is to extend the theory of Hierarchies Consistency Analysis (HCA) to establish a multiple structures evaluation model for the AHP. Traditionally, the AHP process is based on a single evaluation hierarchy, according to statistics and group decision theories, a more objective...

The self-organizing map (SOM), as a kind of unsupervised neural network, has been applied for both static data management and dynamic data analysis. To further exploit its ability in search, in this paper, we propose an SOM-based search algorithm (SOMS) for dynamic systems, in which the SOM is employed...

The forum system is useful for knowledge sharing and help-seeking. However, the existed forums are having the same problem such like nobody to answer the given questions. In order to attack the problem, this study proposes a human-expert oriented forum architecture to perform efficient knowledge sharing....

In this paper, a progressive road analyzes using fuzzy technique is proposed. In this system, only the low cost GPS receivers are used. The road attribute and map are constructed only using the received data.

There is a significant problem associated with the fuzzy time series. That is a strict increasing and decreasing case. Under the discussion case, fuzzy time series model arise a continuous increasing/decreasing forecasting value. From the illustrative example, we can see that our definition not only...

Modern axiomatic uncertainty theories (fuzzy logic, probability theory and others) provide a calculus for manipulating with probabilities, membership functions, and degrees of belief when the initial values such as probabilities of elementary events are already given. These theories do not include a...

By the grey-based Taguchi methods, this study attempts to analyze the process parameters pertinent to the multiple performance characteristics of linear motion guides and obtain the multiple performance characteristics of the noise level, push force value and horizontal combination precision of the linear...

This paper presents a neuro-fuzzy system to speech classification. We propose a multi-resolution feature extraction technique to deal with adaptive frame size. We utilize fuzzy adaptive resonance theory (FART) to cluster each frame. FART was an extension to ART, performs clustering of its inputs via...

This paper discusses an evaluation method of fuzzy numbers as mean values and measurement of fuzziness defined by fuzzy measures, and the presented method is also applicable to fuzzy random variables and fuzzy stochastic processes in decision making modeling.We compare the measurement of fuzziness and...

In Dense Wavelength Division Multiplexing (DWDM) technologies, the optimal packet scheduling is a common encounter issue in multiple channels network. NP-hard problem deals with finding a way to rearrange packets in multiple channels into a finite and rare channel. Genetic algorithm (GA) is one of the...

In this paper, we issue a hybrid system, which is integrated with the fuzzy system and Petri net models. We exploit the characteristics, imprecise or ambiguous information, of fuzzy theory to map the algorithm of crisp inputs and outputs, furthermore, model problems, product a nonlinear function, and...

An image-based fire detection method using neural networks is proposed in this paper. First, flame color features, based on the HSI color model, are trained by a backpropagation neural network for flame recognition. Then, based on the learned flame color features, regions with fire-like colors are roughly...

Automatic incident detection and characterization is urgently require in the development of advanced technologies used for reducing non-recurrent traffic congestion on urban traffic. This paper presents a new method using data mining to identify automatically freeway incidents. As a component of a real-time...