Fuzzy Relational Database

International Journal an Fuzzy Systems (IJFS) is a forum for presenting new advances and research results in the fields of Fuzzy Logic Systems. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences.All submissions must describe original research, not published or currently under review for another conference or journal.

We present an overview of the most important proposals for human-oriented query languages for relational databases, based on fuzzy sets theory. To highlight important issues concerning communication with databases, we propose two taxonomies: the first taxonomy deals with flexible query languages in crisp relational databases and the second deals with flexible query languages in fuzzy relational databases. They can help database designers and users understand and select the best approaches to solve their problems.

International Journal of Fuzzy Logic Systems (IJFLS) is an open access peer-reviewed journal that covers all topics in theoretical, experimental and applied fuzzy techniques and systems. It is aimed to bring together researchers and developers from both academia and industry to discuss the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems. The journal solicits original technical papers that were not previously published and are not currently under review for publication elsewhere.

Fuzzy Logic Systems: an International Journal(FLSIJ)
http://flyccs.com/jounals/FLSIJ/Home.html
Scope
Fuzzy Logic Systems: an International Journal(FLSIJ) is a forum for presenting new advances and research results in the fields of Fuzzy Logic Systems. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences.All submissions must describe original research, not published or currently under review for another conference or journal.
Topics of interest include, but are not limited to, the following
• Fuzzy logic Techniques & Algorithm
• Fuzzy Mathematics
• Fuzzy Measure and Integral
• Type 2 Fuzzy Logic
• Possibility Theory and Imprecise Probability
• Fuzzy Database
• Fuzzy Clustering
• Fuzzy Decision Support System
• Fuzzy Expert System
• Fuzzy Mathematical Programming
• Fuzzy Decision Making and Decision Support Systems
• Fuzzy Modeling and Fuzzy Control of Biotechnological Processes
• Fuzzy Neural Systems, Neuro-Fuzzy Systems
• Fuzzy Systems Modeling and Identification
• Fuzzy Pattern Recognition
• Fuzzy Process Control
• Fuzzy Reasoning System
• Fuzzy-Rule based System
• Fuzzy System in Multimedia and Web-based Applications
• Fuzzy System Applications in Computer Vision
• Hybrid Fuzzy Systems (fuzzy-neuro-evolutionary-rough)
• Fuzzy System Applications in E-commerce
• Fuzzy Sets in Bioinformatics
• Fuzzy System Applications in Human-Machine Interface
• Fuzzy System Applications in Robotics
• Fuzzy System Applications in System and Control Engineering
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit

Contacts
Here's where you can reach us :flsijjournal@yahoo.com(or) flsijjournal@gmail.com

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Scope
International Journal of Education Management Systems(IJEMS) is a Quarterly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of Education. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of Educational research. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Educational advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Education.
Topics of interest include, but are not limited to, the following
• Education Policy and Leadership
• Business Education
• Educating the educators
• Professional Development for teachers in ICT
• Teacher Evaluation
• Virtual and remote laboratories
• Pedagogy Enhancement with E-Learning
• Course Management Systems
• Web-based tools for education
• Games and simulations in Education
• Learning / Teaching Methodologies and Assessment
• Curriculum, Research and Development
• Counselor Education
• Integrating technology in curriculum: Challenges & Strategies
• Collaborative & Interactive Learning
• Tools for 21st Century learning
• Learning Analysis
• Student Selection Criteria in Interdisciplinary Studies
• Global Issues in Education and Research
• Technology Support for Pervasive Learning
• Artificial Intelligence, Robotics and Human computer Interaction in Education
• Mobile/ubiquitous computing in education
• Web 2.0, Social Networking, Blogs and Wikis
• Multimedia in Education
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Other journals
• International Journal of Computer Vision and machine learning(IJCVML)
• International Journal of Mobile Robot Navigation(IJMRN)
• Fuzzy Logic Systems: an International Journal(FLSIJ)
Important Dates
• Submission Deadline :December 09, 2018
• Notification :January 24, 2019
• Final Manuscript Due :January 30, 2019
• Publication Date : Determined by the Editor-in-Chief

________________________________________ TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us :ijemsjournal@yahoo.com(or) ijecejournal78@gmail.com

Conventional Relational Database Management Systems (RDMS) presents difficulties when they try to give information which is requested in a vague, imprecise or fuzzy way, and world researchers have seen this situation. Some trends about the solution of this problem in the world: Fuzzy Databases and Fuzzy Features Incorporation in conventional RDBMS are summarized. Furthermore, in this paper a new methodological

The objective of this paper to investigate the notion of complex fuzzy set in general view. In constraint to a
traditional fuzzy set, the membership function of the complex fuzzy set, the range from [0.1] extended to a
unit circle in the complex plane. In this article the comprehensive mathematical operations on the complex
fuzzy set are presented. The basic operation of complex fuzzy set such as union, intersection, complement
of complex fuzzy set and complex fuzzy relation are studied. Also vector aggregation and fuzzy relation
over the complex fuzzy set are discussed. Two novel operations of complement and projection for complex
fuzzy relation are introduced

A novel, information-theoretic fuzzy approach to discovering unreliable data in a relational database is presented. A multilevel information-theoretic connectionist network is constructed to evaluate activation functions of partially reliable database values. The degree of value reliability is defined as a fuzzy measure of difference between the maximum attribute activation and the actual value activation. Unreliable values can be removed from the database or corrected to the values predicted by the network. The method is applied to a real-world relational database which is extended to a fuzzy relational database by adding fuzzy attributes representing reliability degrees of crisp attributes. The highest connection weights in the network are translated into meaningful if, then rules. This work aims at improving reliability of data in a relational database by developing a framework for discovering, accessing and correcting lowly reliable data.

The representation of inexact or incomplete information has become an important area of database research. A number of authors have proposed a variety of generalizations to parts of classical database theory so as to be able to deal with vague or incomplete information. For the most part, the generalizations have been of one specific data model, the relational data model. One of the features of the relational data model is that its associated query language, though algebraic in nature, is equivalent to a fragment of predicate calculus, the relational calculus. Many of the generalizations use fuzzy set theory to provide an interpretation of impreciseness in relational databases. An excellent review of the literature pertaining to this approach can be found in [Raju and Majumdar 1989].

In this paper, we define the concept of generalized rule for making classical deduction with imprecise data, stored both data and rules in a fuzzy relational database represented in the GEFRED model. We propose a way of measuring the imprecision related to the calculation of a fact based on the matching degree of the facts in the database and the facts calculated while expanding the rules. In order to achieve this, classical algorithms for deduction are not appropriated and we propose the modifications that have to be applied on a classical tuple-oriented algorithm in order to design a new algorithm for deducing from imprecise data with generalized rules.

Starting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of

Department of Computer Science Wright State University Dayton, Ohio 45345 ... Standard relational database management systems are in-capable of representing and manipulating the imprecise, in-complete and vague iaformation that is typically encountered in complex ...

In this paper we deal with the problem of defining projection and join operators in the frameworkof a fuzzy relational database. We study the properties of such an operators relating to the conceptof fuzzy functional dependency. There are two main properties to achieve: On the one hand, if arelation r satisfies a dependency between two sets of attributes, X and

Scope
International Journal an Fuzzy Systems (IJFS) is a forum for presenting new advances and research results in the fields of Fuzzy Logic Systems. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences.All submissions must describe original research, not published or currently under review for another conference or journal.

... (IDEAS 00), December 18 20, Yokohama, Japan, pp. 47 54. [25] R. Intan, M. Mukaidono, Application of conditional probability in constructing fuzzy functional dependency, in: Proc. AFSS 00,2000, pp. ... 23 41. [27] SY Liao, HQ Wang, WY Liu, Functional dependencies with null ...

A natural language interface is one that allows a database to be accessed using common language, in this case English, rather than a query language, such as SQL. A fuzzy database is one in which membership is not an absolute yes or no condition. This research expands the implementation of a Fuzzy Relational Database with Community Defined Membership values to include a set of synonyms to the fuzzy modifiers. The user community makes the determination of synonym status with respect to the fuzzy modifiers. By allowing the community to define the meaning of each synonym within the context of the fuzzy database, the semantics of a database request in the users own language is unambiguous.