Development of DSP Unit for Online Tuning and Application to Neural Pattern Recognition System

Recently, smaller and more effective recognition system is required in various fields. In our previous researches, the recognition system using neural network (NN) and DSP had been developed. In some research fields, such as biometrics, the target of the system was to recognize patterns whose data varied widely because of the difference of individuals and surroundings, but its recognition ability was not enough. So the online tuning system is proposed in this paper. The proposed system, which is consisted of DSP unit and the NN continuous learning and recognition parts, is used to recognize the patterns whose data varied widely. We discuss to adjust the recognition system to data varied widely by continuous leaning. In experiment, performance of the online tuning system is checked, and we attempt to apply the system to electromyogram (EMG) pattern recognition.Knowledge-Based Intelligent Information and Engineering Systems 8th International Conference, KES 2004, Wellington, New Zealand, September 20-25, 2004, Proceedings, Part

On the incorporation of interval-valued fuzzy sets into the Bousi-Prolog system: declarative semantics, implementation and applications

In this paper we analyse the benefits of incorporating interval-valued fuzzy sets into the Bousi-Prolog system. A syntax, declarative semantics and im- plementation for this extension is presented and formalised. We show, by using potential applications, that fuzzy logic programming frameworks enhanced with them can correctly work together with lexical resources and ontologies in order to improve their capabilities for knowledge representation and reasoning

Some applications of possibilistic mean value, variance, covariance and correlation

In 2001 we introduced the notions of possibilistic mean value and variance of fuzzy numbers. In this paper we list some works that use these notions. We shall mention some application areas as wel

A Framework for Automatic SLA Creation

Negotiation is fundamental to business. Increased automation of business to business or business to customer interaction is demanding efficient but flexible systems that can manage the negotiation process with minimal direct human intervention. Industries that provide online services rely on Service Level Agreements as the basis for their contractual relationship. Here we look at a means for generating these with a negotiating tool (SLA Negotiation Manager) that complies with e-negotiation rules and creates the agreements from existing business objectives

Enhanced ontology-based text classification algorithm for structurally organized documents

Text classification (TC) is an important foundation of information retrieval and text mining. The main task of a TC is to predict the text‟s class according to the type of tag given in advance. Most TC algorithms used terms in representing the document which does not consider the relations among the terms. These algorithms represent documents in a space where every word is assumed to be a dimension. As a result such representations generate high dimensionality which gives a negative effect on the classification performance. The objectives of this thesis are to formulate algorithms for classifying text by creating suitable feature vector and reducing the dimension of data which will enhance the classification accuracy. This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. The third algorithm is the Ontology Based Text Classification (OBTC) and is designed to reduce the dimensionality of training sets. The fourth and fifth algorithms, Concept Feature Vector_Text Classification (CFV_TC) and Structure Feature Vector_Text Classification (SFV_TC) classify the document to its related set of classes. These proposed algorithms were tested on five different scientific paper datasets downloaded from different digital libraries and repositories. Experimental obtained from the proposed algorithm, CFV_TC and SFV_TC shown better average results in terms of precision, recall, f-measure and accuracy compared against SVM and RSS approaches. The work in this study contributes to exploring the related document in information retrieval and text mining research by using ontology in TC

Intraday trading rules based on Self Organizing Maps

Working with five minutes data, we have studied a number of trading rules based on the responses of Kohonen's Self Organizing Maps, evaluating the results with both financial and statistical indicators, as well as by comparison with classical buy and hold strategy. At the current stage our major findings may be summarized as follows: a) Kohonen's maps are helpful to localize profitable intraday patterns, and b) they generally make possible to achieve higher performances than common buy and hold strategy

Comparison of the “Hori-gotatsu” in the Traditional Japanese House and the “Kürsü” in the Traditional Divriği House

The use of the wooden low table “kotatsu” in the center of the traditional Japanese house in the fourteenth century(Muromachi period), the hori-gotatsu, is similar to the use of the wooden low table in traditional Divriği house in traditional Turkish Anatolian house, the “kürsü”. The “kotatsu” and the “kürsü” used in winter in both places with similar climate characteristics are the table usage, which is collected around the place and where the warm-up needs are met. The origins of these similar uses in the traditional Japanese house and the traditional Divriği house, located in different and distant geographies, can be traced back to Central Asia. In this study, the shape and use characteristics of “hori-gotatsu”, a form of traditional Japanese house in the past, and the shape and use characteristics of the “kürsü” in the traditional Divriği house are compared