Shailender Kumar ¹, Rahul Rishi ¹

Affiliations
1 Computer Science and Engineering, University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak - 124001, Haryana, IN

Abstract

Objectives: In this paper, tuple time-stamping temporal model is proposed for the retrieval of meteorological data. Methods/ Statistical Analysis: This paper accentuate upon the retrieval of temporal database by extending the functionality of Postgres database system. The tuple time-stamping approach is used to query the time-varying data. Conventional databases are not capable of managing temporal data as it is a series of snapshot relations. Findings: We proposed and implemented a temporal model for the retrieval of temporal data using the meteorological dataset of a particular location in the National Capital Region of Delhi for the year 2014.The results may be used for the analysis of climate trends. Applications/Improvement: Various temporal models have been proposed and implemented by the researchers but fewer efforts have been put in the real world problems.

Keywords

Temporal Database Model, Tuple Time-stamping, Temporal Relational Algebra, Valid Time.

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Sanjay Kumar ¹, Rahul Rishi ², Rajkumar ²

Affiliations
1 University Campus School MDU, Rohtak - 124001, Haryana, IN
2 University Institute of Engineering and Technology MDU, Rohtak - 124001, Haryana, IN

Abstract

Objectives: The ultimate goal of the proposed metrics is to develop a quality software product, which is possible only when the product is certified at the end of each phase, so that there will be no place for errors and faults. Methods/Statistical Analysis: Project A and B are “School Management Software” in C++ language. The project A is developed using the “Software quality and productivity enhancement model” procedure and verified by metrics at every phase of development and maintenance whereas project B is developed in general procedure by another group. Both the software projects are observed for six months under similar work and conditions. Metrics are applied on observations from time to time and compared. Findings: Results from proposed metrics certify that undefined (hidden) task in product SRS or design phase constitute the major risks associated (product failure, quality, productivity etc.) with the product. Poor requirement identification and management laid greater role in product failure. It is certified in this paper that increase in the value of product failure % decrease the quality and productivity of product. The product whose failure rate is greater than 1% is risky to use, this value varies as per the product use and its working environment. Product effectiveness curve help the user in decision making regarding the working process of the software process, if it moves downward continue the use, but if it moves upward after a time period then the product should be abort or replaced. In this paper the application of proposed metrics on small project in different phases of its development, prerelease stage and in maintenance of the product enhance the quality and productivity of the product. Application/Improvements: The proposed metrics are applied on small projects; they can also be applied on large, complex software products. The application of the proposed metrics reduces the risk associated with the product that enhances the product quality

Keywords

Development Phases, Productivity, Software Development, Software Metrics, Quality.

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Rainu Nandal ¹, Rahul Rishi ¹

Affiliations
1 University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak – 124001, Haryana, IN

Abstract

Objectives: The appraisal of data set in databases is expanding at a monster rate. These offers rise to a necessity for inventive systems and gadgets to help individuals in normally and astutely investigate gigantic data sets to gather profitable data. Here, the role of Events R-Trees in Knowledge Discovery Process for Spatio-Temporal Databases is presented. Methods: Taking into account the execution of R-tree, the thoughts of scope and cover are vital. Scope of a level of an R-tree is described as the total range of the extensive number of rectangles associated with the hubs of that level. Cover of a stage of an R-tree is described as the total zone contained inside at least two hubs. Obviously, powerful R-tree seeking demands that together cover and scope be limited. Findings: In this division, outfit a portrayal of KDD as well as Data Mining, recitation its assignments, techniques, along with correlations. In this paper, the role of Events R-Trees for powerful Knowledge Discovery Process for Spatio-Temporal Databases is explained. Improvements: The R-tree is a standout amongst the most referred to spatial information structures and it is all the time utilized for correlation with new structures.

Keywords

Events R-Tree, GSA (Gravitational Search Optimization Algorithms), KDD (Knowledge Discovery in Database), Patterns, Spatio-Temporal Database.

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