scholarly journals FUZZY RECURSIVE RELATIONSHIPS IN RELATIONAL DATABASES

2018 ◽  
Vol 7 (1) ◽  
pp. 35-46
Author(s):  
Krzysztof Myszkorowski
Keyword(s):  
Set Theory ◽  
Relational Databases ◽  
Real Life ◽  
Database Systems ◽  
Relational Algebra ◽  
Groups And Teams ◽  
Definition Of ◽  
Interval Valued ◽  
Fuzzy Interval ◽  
Modelling Problems

Recursive relationships are used for modelling problems coming from the real life, such as, for example, a relationship describing formal dependencies between employees of an enterprise, where creation of work groups and teams requires analysis of many elements. In conventional database systems, the precision of data is assumed. If our knowledge of the fragment of reality to be modelled is imperfect one should apply tools for describing uncertain or imprecise information. One of them is the fuzzy set theory. The paper deals with recursive relationships in fuzzy databases. The analysis is performed with the use of the theory of interval-valued fuzzy sets. A definition of a fuzzy interval recursive relationship has been presented. The paper defines different connections of entities which participate in such relationships. Op-erations of the extended relational algebra are also discussed.

Evaluation of Quantified Statements Using Gradual Numbers

2011 ◽  
pp. 246-269 ◽  
Author(s):  
Ludovic Liétard ◽  
Daniel Rocacher
Keyword(s):  
Decision Making ◽  
Expert Systems ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Relational Databases ◽  
Fuzzy Numbers ◽  
Theoretical Background ◽  
Definition Of ◽  
Flexible Querying

This chapter is devoted to the evaluation of quantified statements which can be found in many applications as decision making, expert systems, or flexible querying of relational databases using fuzzy set theory. Its contribution is to introduce the main techniques to evaluate such statements and to propose a new theoretical background for the evaluation of quantified statements of type “Q X are A” and “Q B X are A.” In this context, quantified statements are interpreted using an arithmetic on gradual numbers from Nf, Zf, and Qf. It is shown that the context of fuzzy numbers provides a framework to unify previous approaches and can be the base for the definition of new approaches.

scholarly journals GRANULAR-INFORMATION-BASED RISK ANALYSIS IN UNCERTAIN SITUATIONS

2006 ◽  
Vol 1 ◽  
pp. 385
Author(s):  
A. Vališevskis
Keyword(s):  
Negative Impact ◽  
Real Life ◽  
Problem Area ◽  
Environmental Risks ◽  
Probabilistic Information ◽  
Future Events ◽  
Definition Of ◽  
Almost All ◽  
Measure Of Uncertainty ◽  
Interval Valued

In the real life almost all of the decisions that we have to make incorporate uncertainty about the future events. Assessment of the uncertainty and, thus, the risk that is inherent in these decisions models can be critical. It is even truer if we are talking about the possibility of negative impact on the environment. It is very important to assess all the environmental risks in a project if there is any hazard to the environment. In this paper the possibility of using granular information is considered. The main advantage of the granular information is that it can be used to assess risks in situations when information about future events is incomplete and imprecise. Moreover, we can use natural language to describe the problem area, as granular information paradigm uses both fuzzy and probabilistic information. We propose to use entropy as the measure of uncertainty. However, the definition of entropy should be generalised, as values of probabilities, upon which the calculation of entropy is based on, are interval-valued. We propose several possibilities of generalizing the definition of entropy. Furthermore, we analyse these approaches to see whether the additivity feature holds for the generalized entropy.

Nested Optional Join for Efficient Evaluation of SPARQL Nested Optional Graph Patterns

2010 ◽  
pp. 281-308
Author(s):  
Artem Chebotko ◽  
Shiyong Lu
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Real Life ◽  
Query Languages ◽  
Efficient Algorithms ◽  
Relational Algebra ◽  
Nested Loops ◽  
Web Data Management ◽  
Rdf Data ◽  
Rdf Query Languages

Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. This chapter studies how RDF queries with the so called well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. The authors propose to extend relational algebra with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. They design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm, NL-NOJ, (2) sort-merge NOJ algorithm, SM-NOJ, and (3) simple hash NOJ algorithm, SH-NOJ. Using a real life RDF dataset, the authors demonstrate the efficiency of their algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of these algorithms.

Business Rules in Databases

2005 ◽  
pp. 47-53
Author(s):  
Antonio Badia
Keyword(s):  
Information Systems ◽  
Relational Databases ◽  
Database Systems ◽  
Business Rules ◽  
Business Rule ◽  
The Subject ◽  
Entity Relationship ◽  
Definition Of ◽  
Definition Of Information ◽  
Exact Definition

Though informal, the concept of business rule is very important to the modeling and definition of information systems. Business rules are used to express many different aspects of the representation, manipulation and processing of data (Paton, 1999). However, perhaps due to its informal nature, business rules have been the subject of a limited body of research in academia. There is little agreement on the exact definition of business rule, on how to capture business rules in requirements specification (the most common conceptual models, entity-relationship and UML, have no proviso for capturing business rules), and, if captured at all, on how to express rules in database systems. Usually, business rules are implemented as triggers in relational databases. However, the concept of business rule is more versatile and may require the use of other tools.

scholarly journals Some Root Level Modifications in Interval Valued Fuzzy Graphs and Their Generalizations Including Neutrosophic Graphs

Mathematics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 72 ◽  
Author(s):  
Naeem Jan ◽  
Kifayat Ullah ◽  
Tahir Mahmood ◽  
Harish Garg ◽  
Bijan Davvaz ◽  
...  
Keyword(s):  
Decision Making ◽  
Essential Role ◽  
Real Life ◽  
Current Definition ◽  
Fuzzy Graphs ◽  
Life Problems ◽  
Decision Making Problem ◽  
Neutrosophic Graph ◽  
Definition Of ◽  
Interval Valued

Fuzzy graphs (FGs) and their generalizations have played an essential role in dealing with real-life problems involving uncertainties. The goal of this article is to show some serious flaws in the existing definitions of several root-level generalized FG structures with the help of some counterexamples. To achieve this, first, we aim to improve the existing definition for interval-valued FG, interval-valued intuitionistic FG and their complements, as these existing definitions are not well-defined; i.e., one can obtain some senseless intervals using the existing definitions. The limitations of the existing definitions and the validity of the new definitions are supported with some examples. It is also observed that the notion of a single-valued neutrosophic graph (SVNG) is not well-defined either. The consequences of the existing definition of SVNG are discussed with the help of examples. A new definition of SVNG is developed, and its improvement is demonstrated with some examples. The definition of an interval-valued neutrosophic graph is also modified due to the shortcomings in the current definition, and the validity of the new definition is proved. An application of proposed work is illustrated through a decision-making problem under the framework of SVNG, and its performance is compared with existing work.

Application of Functional Approach to Lists for Development of Relational Model Databases and Petri Net Analysis

2014 ◽  
pp. 407-444
Author(s):  
Sasanko Sekhar Gantayat ◽  
B. K. Tripathy
Keyword(s):  
Characteristic Function ◽  
Query Processing ◽  
Data Structures ◽  
Petri Net ◽  
Relational Databases ◽  
Functional Approach ◽  
Relational Algebra ◽  
Relational Model ◽  
Algebraic Operations ◽  
Definition Of

The concept of list is very important in functional programming and data structures in computer science. The classical definition of lists was redefined by Jena, Tripathy, and Ghosh (2001) by using the notion of position functions, which is an extension of the concept of count function of multisets and of characteristic function of sets. Several concepts related to lists have been defined from this new angle and properties are proved further in subsequent articles. In this chapter, the authors focus on crisp lists and present all the concepts and properties developed so far. Recently, the functional approach to realization of relational databases and realization of operations on them has been proposed. In this chapter, a list theory-based relational database model using position function approach is designed to illustrate how query processing can be realized for some of the relational algebraic operations. The authors also develop a list theoretic relational algebra (LRA) and realize analysis of Petri nets using this LRA.

Vertical Fragmentation in Databases Using Data-Mining Technique

2009 ◽  
pp. 2543-2563 ◽  
Author(s):  
Narasimhaiah Gorla ◽  
Pang Wing Yan Betty
Keyword(s):  
Data Mining ◽  
Relational Databases ◽  
Real Life ◽  
Optimal Solution ◽  
Database Systems ◽  
Future Research ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Vertical Fragmentation ◽  
Using Data

A new approach to vertical fragmentation in relational databases is proposed using association rules, a data-mining technique. Vertical fragmentation can enhance the performance of database systems by reducing the number of disk accesses needed by transactions. By adapting Apriori algorithm, a design methodology for vertical partitioning is proposed. The heuristic methodology is tested using two real-life databases for various minimum support levels and minimum confidence levels. In the smaller database, the partitioning solution obtained matched the optimal solution using exhaustive enumeration. The application of our method on the larger database resulted in the partitioning solution that has an improvement of 41.05% over unpartitioned solution and took less than a second to produce the solution. We provide future research directions on extending the procedure to distributed and object-oriented database designs.

Vertical Fragmentation in Databases Using Data-Mining Technique

2010 ◽  
pp. 2248-2268
Author(s):  
Narasimhaiah Gorla ◽  
Pang W.Y. Betty
Keyword(s):  
Data Mining ◽  
Relational Databases ◽  
Real Life ◽  
Optimal Solution ◽  
Database Systems ◽  
Future Research ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Vertical Fragmentation ◽  
Using Data

A new approach to vertical fragmentation in relational databases is proposed using association rules, a data-mining technique. Vertical fragmentation can enhance the performance of database systems by reducing the number of disk accesses needed by transactions. By adapting Apriori algorithm, a design methodology for vertical partitioning is proposed. The heuristic methodology is tested using two real-life databases for various minimum support levels and minimum confidence levels. In the smaller database, the partitioning solution obtained matched the optimal solution using exhaustive enumeration. The application of our method on the larger database resulted in the partitioning solution that has an improvement of 41.05% over unpartitioned solution and took less than a second to produce the solution. We provide future research directions on extending the procedure to distributed and object-oriented database designs.

Is Treat-to-target in Lupus Nephritis Realistic in Clinical Practice?

2018 ◽  
Vol 15 (1) ◽  
pp. 2-6 ◽  
Author(s):  
Chi Chiu Mok
Keyword(s):  
Lupus Nephritis ◽  
Disease Activity ◽  
Safety Concern ◽  
Real Life ◽  
Current Treatment ◽  
Treat To Target ◽  
Low Disease Activity ◽  
Activity State ◽  
Definition Of ◽  
Comparative Trials

The Treat-to-Target (T2T) principle has been advocated in a number of inflammatory and non-inflammatory medical illnesses. Tight control of disease activity has been shown to improve the outcome of rheumatoid arthritis and psoriatic arthritis as compared to the conventional approach. However, whether T2T can be applied to patients with lupus nephritis is still under emerging discussion. Treatment of lupus nephritis should target at inducing and maintaining remission of the kidney inflammation so as to preserve renal function and improve survival in the longterm. However, there is no universal agreement on the definition of remission or low disease activity state of nephritis, as well as the time points for switching of therapies. Moreover, despite the availability of objective parameters for monitoring such as proteinuria and urinary sediments, differentiation between ongoing activity and damage in some patients with persistent urinary abnormalities remains difficult without a renal biopsy. A large number of serum and urinary biomarkers have been tested in lupus nephritis but none of them have been validated for routine clinical use. In real life practice, therapeutic options for lupus nephritis are limited. As patients with lupus nephritis are more prone to infective complications, tight disease control with aggressive immunosuppressive therapies may have safety concern. Not until the feasibility, efficacy, safety and cost-effectiveness of T2T in lupus nephritis is confirmed by comparative trials, this approach should not be routinely recommended with the current treatment armamentarium and monitoring regimes.

Generalized interval-valued hesitant intuitionistic fuzzy soft sets

2021 ◽  
pp. 1-12
Author(s):  
Admi Nazra ◽  
Yudiantri Asdi ◽  
Sisri Wahyuni ◽  
Hafizah Ramadhani ◽  
Zulvera
Keyword(s):  
Hesitant Fuzzy Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Binary Operations ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Comparison Table ◽  
Definition Of ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

This paper aims to extend the Interval-valued Intuitionistic Hesitant Fuzzy Set to a Generalized Interval-valued Hesitant Intuitionistic Fuzzy Soft Set (GIVHIFSS). Definition of a GIVHIFSS and some of their operations are defined, and some of their properties are studied. In these GIVHIFSSs, the authors have defined complement, null, and absolute. Soft binary operations like operations union, intersection, a subset are also defined. Here is also verified De Morgan’s laws and the algebraic structure of GIVHIFSSs. Finally, by using the comparison table, a different approach to GIVHIFSS based decision-making is presented.

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