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Pain is the most common symptom of the many musculoskeletal pathologies. Musculoskeletal pain affects the muscles, ligaments, tendons, nerves and bones and might be caused by diverse factors. Musculoskeletal pain ranges from mild to severe. It can be local or diffuse, and acute or chronic. Due to the wide range of conditions that may cause such a symptom, diagnosing process is challenging and a systematic approach is necessary. In this investigation we present a successful example of generalized nets application in medical diagnosing and propose a novel approach leading to the appropriate diagnostic considerations. The method proposed in this investigation accurately identifies the various steps during the muscle pain diagnosing process and significantly improves the health care level. Obtained so far results could be used to assist in the decision making in the diagnostic processes.

OLAP query answering requirements for a knowledge based treatment of user requests led us to introduce the concept of hierarchical preferences over a universe that has a hierarchical structure. We introduce the automatic analysis of queries according to concepts defined as part of knowledge based hierarchy in order to guide the query answering as part of a data-warehouse environment with the aid of hierarchical Intuitionistic fuzzy sets, H-IFS. Based on the notion of H-IFS we propose an ad-hoc utility build on top of current OLAP tools like Oracle10g that allows us to enhance the query capabilities of by providing better and knowledgeable answers to user’s requests. The theoretical aspects as well the practical issues and achieved results are presented throughout the rest of the paper.

Query answering requirements for a knowledge based treatment of user requests led us to introduce the concept of closure of an Intuitionistic fuzzy set over a universe that has a hierarchical structure. We introduce the automatic analysis of queries according to concepts defined as part of a knowledge based hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical Intuitionistic fuzzy sets, H-IFS. In this paper based on the notion of H-IFS we propose an ad-hoc utility build on top of Oracle10g that allows us to enhance the query capabilities of by providing better and knowledgeable answers to userpsilas requests. The theoretical aspects as well the practical issues and achieved results are presented throughout the rest of the paper.

In this paper we revise the context of ldquovalue imprecisionrdquo, as part of an knowledge-based environment. We present our approach for including value imprecision as part of a non-rigid hierarchical structures of organization. This led us to introduce the concept of closure of an intuitionistic fuzzy set over a universe that has a hierarchical structure. Intuitively, in the closure of this intuitionistic fuzzy set, the ldquokind ofrdquo relation is taken into account by propagating the degree associated with an element to its sub-elements in the hierarchy. We introduce the automatic analysis according to concepts defined as part of a knowledge hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical intuitionistic fuzzy sets.

In the Bulgarian health care system patients are transferred between different health care units within the health care facility, and occasionally between units that are far apart, depending on the stage of the patient's treatment progress. Determining patient resource consumption prior to utilization is vital for the management and planning of health care resources. In this paper we propose a generalized net model of patient flows that can be used to evaluate the current design (or alternative designs) in order to improve the management of the diagnostic consultative centres.

In this paper we revise the context of "value uncertainty", as part of an OLAP based environment. A new multidimensional-cubic model named as the if-cube is introduced which is able to operate over data with imprecision either in the facts or in the dimensional hierarchies. These query requirements led us to introduce the concept of closure of an intuitionistic fuzzy set over a universe that has a hierarchical structure, H-IFS. We introduce the automatic recommendation of analysis according to the concepts defined as part of a domain ontology in order to guide the decision making with the aid of H-IFS.

In recent years, the providers of public and private sector health care services have been faced with some radical changes in the society they serve, and more importantly, development in the way that traditional health care is delivered to Information Technology (I.T) based communities. It is widely believed by health care professionals that the better health care results really come from the improved healthcare systems and more effective health care services' management. This paper focuses on using an agnet-based software engineering approach and design models to the development of an appropriate agent-based healthcare software system is described in which software researchers collaborate with environment builders to enhance the levels of cooperation and support provided within an integrated agent-based community healthcare system.

On-Line Analytical Processing (OLAP) tools use multidimensional views to provide quick access to information. They have become the de facto standard in the business world for analytical databases. In health care, care givers and managers could benefit from being able to perform interactive data exploration, ad-hoc analysis and possibly discover hidden trends and patterns in health data. However, health data have unique characteristics that distinguish them from common business examples, an aspect that makes the direct adaptation of the already established business oriented solutions difficult. In this paper we report the development of an OLAP system for analyzing hospital discharge data and for modeling hospital length of stay.

There is increasing worldwide awareness that bionics and artificial intelligence will play an important role in microbial analysis. An intelligent data-warehouse system consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on neural networks and genetic algorithms have been applied as part of a microbial analysis. The microbiological warehouse environment has, also adopted the concept of fusion of multiple classifiers dedicated to specific feature parameters. The experimental results confirm the soundness of the presented methods.

This work presents a framework for Web mining, which is developed to support and assist existing data mining algorithms in order to preliminarily refine browsing pattern with relevant constraints. Intuitionistic fuzzy sets are used to represent the possibility that backward steps are used while searching for the pages of interest.

With the rapid growing number of WWW users, hidden information becomes ever increasingly valuable. As a consequence of this phenomenon, mining Web data and analysing on-line users' behaviour and their on-line traversal pattern have emerged as a new area of research. Primarily based on the Web servers' log files, the main objective of traversal pattern mining is to discover the frequent patterns in users' browsing paths and behaviors. This paper presents a complete framework for Web mining, allowing users to pre-define physical constraints when analysing complex traversal patterns in order to improve the efficiency of algorithms and offer flexibility in producing the results.

Recently, the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence. It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage and among others, urine volatile compounds have been identified as possible diagnostic markers. A newly developed electronic nose based on chemoresistive sensors has been employed to identify in vitro 13 bacterial clinical isolates, collected from patients diagnosed with urinary tract infections, gastrointestinal and respiratory infections, and in vivo urine samples from patients with suspected uncomplicated UTI who were scheduled for microbiological analysis in a UK Health Laboratory environment. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on a neural networks, genetic algorithms, and multivariate techniques such as principal components analysis and discriminant function analysis-cross validation. The experimental results confirm the validity of the presented methods.

The paper presents a way of integrating conflicting temporal information from multiple information providers considering a property-based resolution. The properties considered in the paper are time and uncertainty because of conflicting information providers. The property based resolution requires a flexible query mechanism, where answers are considered as bounds, taking into account the tendency of things to occur and also the might happen ability of things. Finally, some attention is paid to a database environment with non-static members.

Data warehouses (DWH) have been established as the core of decision support systems. On top of a DWH, different applications can be realised with regard to conventional reporting. On line analytical processing (OLAP) has reached the maturity as an interactive and explorative way of analysing DWH data. However DWH are mostly organised as snapshot databases. For this reason important tasks like "how many times have product of a specific brand been sold in the past?" cannot be answered successfully - in order to control the success of reshuffling the product range it is necessary to compare the sales of old and new products. The same applies in cases where the seasonality aspect for a particular range of products has to be answered. On the other hand, temporal databases allow a valid time to be assigned to data. In this manner, a past state can be reconstructed during retrieval. In this paper, we address the integration of DWH and OLAP with temporal databases semantics.