Flexible fuzzy OWA querying method for hemodialysis database

The hemodialysis quality contains the subjective opinions of the physicians. However, the range of good/bad quality of one physician’s perspective usually differs from the others, so we use the fuzzy theory to solve this vague situation. This paper proposes the fuzzy ordered weighting average (OWA) technique to evaluate fuzzy database queries about linguistic or precise values, which can improve the crisp values’ constrains of traditional database. Besides, we deal with the dynamical weighting problem more rationally and flexibly according to the situational parameter α value from the user’s viewpoint. In this paper, we focus on hemodialysis adequacy and develop the query system of practical hemodialysis database for a regional hospital in Taiwan. From the experimental result, we can find the overall accuracy rate is better than other methods and our result is more matching the doctor’s view. That is, the fuzzy OWA query is more flexible and more accurate     

Database design and querying within the fuzzy semantic model

Fuzzy semantic model (FSM) is a data model that uses basic concepts of semantic modeling and supports handling fuzziness, uncertainty and imprecision of real-world at the attribute, entity and class levels. The paper presents the principles and constructs of the FSM. It proposes ways to define the membership functions within all the constructs of the FSM. In addition, it provides a proposal for specifying FSM schema and introduce a query language adapted to FSM-based databases.     

Representation of spatial data in an OODB using roughand fuzzy set modeling

This paper introduces and formally defines a fuzzy rough object-oriented database (OODB) model based on a formal framework using an algebraic type system and formally defined constraints. This generalized model incorporates both rough set and fuzzy set uncertainty, while remaining compliant with object-oriented database standards set forth by the Object Database Management Group. Rough and fuzzy set uncertainty enhance the OODB model so that it can more accurately model real world applications. Spatial databases have a particular need for uncertainty management that can be achieved through rough and fuzzy techniques.     

A formal approach to object-oriented databases

Object-oriented database systems are the focus of current research and development efforts. Yet, there is no commonly accepted object model, nor is it clear whether such a model can be developed. This paper reports on efforts to develop a formal framework that contains most features found in current object oriented database systems. The framework contains two parts. The first is a structural object model, including concepts such as structured objects, identity, and some form of inheritance. For this model, we explain the distinction between values and (abstract) objects, describe a system as a directed graph, and discuss declarative languages. The second part deals with higher-order concepts, such as classes and functions as data, methods, and inheritance. This part is a sketch, and leaves many issues unresolved. Throughout the paper, the emphasis is on logic-oriented modeling.     

Approximation algorithms for querying incomplete databases

Certain answers are a widely accepted semantics of query answering over incomplete databases. As their computation is a coNP-hard problem, recent research has focused on developing (polynomial time) evaluation algorithms with correctness guarantees, that is, techniques computing a sound but possibly incomplete set of certain answers. The aim is to make the computation of certain answers feasible in practice, settling for under-approximations.In this paper, we present novel evaluation algorithms with correctness guarantees, which provide better approximations than current techniques, while retaining polynomial time data complexity. The central tools of our approach are conditional tables and the conditional evaluation of queries. We propose different strategies to evaluate conditions, leading to different approximation algorithms—more accurate evaluation strategies have higher running times, but they pay off with more certain answers being returned. Thus, our approach offers a suite of approximation algorithms enabling users to choose the technique that best meets their needs in terms of balance between efficiency and quality of the results.     

Storing and querying fuzzy XML data in relational databases

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data management has been extensively investigated in various database management systems. Currently, introducing native support for XML data in relational database management systems (RDBMs) has attracted considerable interest with a view to leveraging the powerful and reliable data management services provided by RDBMs. Although there is a rich literature on XML-to-relational storage, none of the existing solutions satisfactorily addresses the problem of storing fuzzy XML data in RDBMs. In this paper, we study the methodology of storing and querying fuzzy XML data in relational databases. In particular, we present an edge-based approach to shred fuzzy XML data into relational data. The unique feature of our approach is that no schema information is required for our data storage. On this basis, we present a generic approach to translate path expression queries into SQL for processing XML queries.     

Null values in fuzzy databases

Since in the real world, it often occurs that information is missing, database systems clearly need some facilities to deal with missing data. With respect to traditional database systems, the most commonly adopted approach to this problem is based on null values and three valued logic. This paper deals with the semantics and the use of null values in fuzzy databases. In dealing with missing information a distinction is made between incompleteness due to unavailability and incompleteness due to inapplicability. Both the database modelling and database querying aspects are described. With respect to attribute values, incompleteness due to unavailability is modelled by possibility distributions, which is a commonly used technique in the fuzzy databases. Domain specific null values, represented by a bottom symbol, are used to model incompleteness due to inapplicability. Extended possibilistic truth values are used to formalize the impact of data manipulation and (flexible) querying operations in the presence of these null values. The different cases of appearances of null values in the handling of selection conditions of flexible database queries are described in detail.     

Rule-based spatiotemporal query processing for video databases

In our earlier work, we proposed an architecture for a Web-based video database management system (VDBMS) providing an integrated support for spatiotemporal and semantic queries. In this paper, we focus on the task of spatiotemporal query processing and also propose an SQL-like video query language that has the capability to handle a broad range of spatiotemporal queries. The language is rule-based in that it allows users to express spatial conditions in terms of Prolog-type predicates. Spatiotemporal query processing is carried out in three main stages: query recognition, query decomposition, and query execution.Received: 11 October 2001, Accepted: 3 October 2003, Published online: 12 December 2003Edited by: A. Buchmann Correspondence to: Özgür UlusoyThis work is supported by the Scientific and Research Council of Turkey (TÜBITAK) under Project Code 199E025. This work was done while the first author was at Bilkent University.     

The MurMur project: Modeling and querying multi-representation spatio-temporal databases

Successful information management implies the ability to design accurate representations of the real world of interest, in spite of the diversity of perceptions from the applications sharing the same database. Current database management systems do not provide representation schemes that preserve each perception while fully supporting their diversity and maintaining their consistency. This is a major hindrance for building an all-embracing view of the world while serving multiple applications, whether it is by developing a single database or by providing transparent access (e.g., via the Web) to several heterogeneous data sources (that would typically hold a great diversity of stored representations). This paper reports on results from the multiple representations and multiple resolutions in geographical databases project,¹ funded by the European Commission under the 5th Framework Programme. The objective of the project has been to enhance GIS (or DBMS) by adding functionality that supports multiple coexisting representations of the same real-word phenomena (semantic flexibility), including representations of geographic data at multiple resolutions (cartographic flexibility). The new functionality enables a semantically meaningful management of multi-scale, integrated, and temporal geo-databases.     

On fuzzy equality and approximation in fuzzy logic

The paper is a contribution to the theory of fuzzy logic in narrow sense with evaluated syntax (FLn). We show that the concepts of fuzzy equality and the provability degree enable to generalize the concept of fuzzy approximation. In the second part of the paper we return to the Mamdani-Assilian formula, which is formed on the basis of the so called totally bounded fuzzy equality and using which we can approximate any function with the prescribed accuracy.This paper has been supported by Grant A1187901/99 of the GA AV R and the project VS96037 of MMT of the Czech Republic.     

ERL: Logic for entity-relationship databases

We develop a logic for entity-relationship databases, ERL, that is a generalization of database logic. ERL provides advantages to the ER model much as FOL (first-order logic) does to the relational model: a uniform language for expressing database schema, integrity constraints, and database manipulation; clearly defined semantics; the capability to express database transformations; and deductive capabilities. We propose three query languages for ER databases called ERRC, ERSQL, and ERQBE, which are generalizations of the relational calculus, SQL, and QBE, respectively. We use example queries and updates to demonstrate the capabilities of these languages. We apply database transformations to introduce the notion of views and to show that both ERRC and ERSQL are relationally complete.Research sponsored in part by the National Science Foundation under grant IRI-8921951 and by Towson State University.     

A note on congruence permutability and fuzzy logic

We study congruence permutability of algebras with fuzzy equalities. The notion of degree of congruence permutability naturally arises in this context. We present a Mal'cev-like characterization of congruence permutable varieties of algebras with fuzzy equalities. Our note presents a way to generalize various congruence conditions from the point of view of fuzzy logic.     

加密数据的一种高效查询方法

加密技术是保护数据库中数据安全的一种有效方法,但如何对加密数据进行高效查询是一个难点,引起了研究界的重视。针对这个问题,除了采用常规加密方法对字符数据进行加密外,还对字符数据进行扁平化和扰乱化处理,并把处理后的特征值作为附加字段与加密数据一起存储。该方法不仅安全性很好,而且通过实验证明其性能较传统方法有很大提高。     

Modeling, simulation and fuzzy control of an anthropomorphic robot arm by using Dymola

Analysis and fuzzy control of an anthropomorphic robot arm on a special trajectory is the subject of this paper. These types of systems are used in cutting operations on materials, joining materials by welding, material handling in remote and dangerous environments, packing of foods, inspection/testing electronic parts or medical products. This robot arm realizes the handling motion on a special trajectory. In this study, the first three links of Mitsubishi RV-2AJ Industrial Robot, are like an anthropomorphic arm, have been modeled and simulated by using Dymola. Kinematic equations have been obtained and mathematical model of this system has been formed by using Lagrange’s Equations. Fuzzy logic controller for the joint angles for the motion trajectory has been designed and the simulation results have been presented at the end of the study.     

RSS-based e-learning recommendations exploiting fuzzy FCA for Knowledge Modeling

Nowadays, Web 2.0 focuses on user generated content, data sharing and collaboration activities. Formats like Really Simple Syndication (RSS) provide structured Web information, display changes in summary form and stay updated about news headlines of interest. This trend has also affected the e-learning domain, where RSS feeds demand for dynamic learning activities, enabling learners and teachers to access to new blog posts, to keep track of new shared media, to consult Learning Objects which meet their needs.This paper presents an approach to enrich personalized e-learning experiences with user-generated content, through a contextualized RSS-feeds fruition. The synergic exploitation of Knowledge Modeling and Formal Concept Analysis techniques enables the design and development of a system that supports learners in their learning activities by collecting, conceptualizing, classifying and providing updated information on specific topics coming from relevant information sources. An agent-based layer supervises the extraction and filtering of RSS feeds whose topics cover a specific educational domain.     

Goguen's contributions to fuzzy logic in retrospect

ABSTRACT

In the very early stage of the development of fuzzy logic, Joseph Goguen published profound work with lasting influence. Fifty years later, we provide an assessment of his contributions to fuzzy logic and thus pay tribute to Goguen, a former long-term member of the editorial board of this journal. We cover both Goguen's technical results, the research directions inspired by him, which have later been pursued, as well as his suggestions, which as yet remained explored to a lesser extent or practically unexplored.     

Interval-valued fuzzy coimplications and related dual interval-valued conjugate functions

The aim of this paper is to introduce the dual notion of interval conjugate implications, the interval coimplications, as interval representations of corresponding conjugate fuzzy coimplications. Using the canonical representation, this paper considers both the correctness and the optimality criteria, in order to provide interpretation for fuzzy coimplications as the non-truth degree of conditional rule in expert systems and study the action of interval automorphisms on such interval fuzzy connectives. It is proved that interval automorphisms acting on N$\mathbb{N}$-dual interval coimplications preserve the main properties of interval implications discussed in the literature including the duality principle. Lastly, the action of interval automorphisms on interval classes of border, model and S-coimplications are considered, summarized in commutative diagrams.     

Mediative fuzzy logic: a new approach for contradictory knowledge management

In this paper we are proposing a novel fuzzy method that can handle imperfect knowledge in a broader way than Intuitionistic (in the sense of Atanassov) fuzzy logic does (IFL). This fuzzy method can manage non- contradictory, doubtful, and contradictory information provided by experts, providing a mediated solution, so we called it Mediative Fuzzy Logic (MFL). We are comparing results of MFL, with IFL and traditional Fuzzy logic (FL).