Authored By: Farhat Nasar & Akshay Kumar Mishra
Year of Publication: 2019
|Pages: 232||Binding: Hardback(HB)|
Category: Journalism / Digital Media / Modern Communication
|Price in Rs. 696.50||Price in (USA) $. 55.72|
A database management system, or popularly known as ‘DBMS’, is a type of software designed to assist in maintaining and utilizing large collections of data. The underlying structure of databases has been the primary focus of researches that has led to the development of various data models. The most well-known and widely used data model is the relational model (Codd,1970). However, presently database systems are being applied to a range of years with a view to enhancing the functionality of database system domains associated with highly complex information processing and substantial quantities of data, or highly stringent performance requirements in which the conventional relational model proved to be unsatisfactory. During the past few decades, many more expressive data models and systems have been developed. Among the fields that have received attention in recent are database programming, temporal databases, spatial databases, multimedia databases, active databases and deductive databases. Among these, Database systems, Active and Deductive databases have gained widespread popularity. Thus, keeping in view the importance and the paucity of a unified approach, this present study focuses primarily on Active and Deductive database systems. Active Database Management Systems may be defined as “databases that allow the specification and implementation of reactive behaviors”. Active database support this functionality by implementing an event-driven behavior in its domain. In contrast, Deductive Database is an integration of the relational database system and logic programming. This combines the benefits of the two approaches, such as representational uniformity and operational uniformity, reasoning capabilities, recursion, declarative querying, and efficient secondary storage access etc. capability to the overall system. The relation contains explicit information and the rules elicit implicit information from the explicit information. More recently, a strong interest in investigating whether there is any intuitive, clean and efficient way of reconciling the two kinds of rules has been developed. The problem of endowing deductive databases with rule-based active behavior has been addressed in different ways. Typical approaches include accounting for active behavior by extending the operational semantics of deductive databases, or, conversely accounting for deductive capabilities by constraining the operational semantics of active databases. An alternative approach has been proposed by Fernandes et al., (1997), in which a class of active databases is defined whose operational semantics is naturally integrated with the operational semantics of deductive databases without either of them strictly subsuming to others. However, it is strongly felt that a lot of research works still needs to be done in this field.
Dr. (Mrs.) Farhat Nasar, Assistant Professor, Yanbu University College, Kingdom of Saudi Arabia, P.G. Dip in Personnel Management (NIPM), Dip. in Software Management (APTECH), studied in T.M. Bhagalpur University where she successfully completed her Ph.D in Statistics in 2005, after completing her Masters in Statistics & Computer Applications with first class first position. She has taught Probability and Statistics for more than 14 years and has also contributed YUC, as the Academic Coordinator and the Head of the General Studies Department. Her publications are mainly in the field of the computational statistics. She has delivered several workshops and lectures, highlighting the significance and development of Statistics in the present era of digital technology.
Professor Akshay Kumar Mishra, Professor and Head of the Department of Statistics and Computer Applications, T.M. Bhagalpur University. His research area is Applied Statistics and within the domain of this broad area he has published in the field of Probability Network and Bayesian Statistics. In terms of innovation in teaching hecontributed in popularising PC-based computer education as head of the department of Statistics and Computer Applications in T.M.B.U.