An Analysis of a Web Service based Approach for Experimental Data Sharing

Kralev, Velin; Kraleva, Radoslava; Sinyagina, Nina; Koprinkova–Hristova, Petia; Bocheva, Nadejda

doi:10.3991/ijoe.v14i09.8740

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…The VertexCoverFinder application was run on a standard computer configuration with Windows 10 Home 64-bit operating system and the following hardware configuration: CPU: Intel(R) Core(TM) i7-7700MQ CPU @ 2.80GHz 2.81GHz; RAM memory: 16.00 GB. The experiment results may be stored in a database and accessed by a web service, as presented in [50] and [51].…”

Section: Fig 6 Activity Diagram For the Vertexcoverfinder Applicationmentioning

confidence: 99%

An Interactive Application for Learning and Analyzing Different Graph Vertex Cover Algorithms

2023

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This paper deals with an analysis of three algorithms for the graph vertex cover problem. Certain methods for solving this problem are analyzed. In addition, different studies on the problem and some approaches to its solution are discussed as well. An exact algorithm (based on the backtracking approach) is presented. Calculating the average time for execution of this algorithm is consistent with the multitasking way of work of the operating system. For this purpose, four different starts of the algorithm are made and then the average time of all of them is calculated. The exact algorithm found the optimal solutions for all analyzed graphs. Besides this algorithm, two other heuristic algorithms for solving the problem are discussed. For this study, an interactive application is developed to visualize the performance of the three algorithms and display the obtained results. The results show that for small graphs with no more than 25 vertices the exact algorithm can be used to solve optimally the graph vertex cover problem. For the largest graphs, none of the two heuristic algorithms found the optimal solutions, but these algorithms generated solutions that are very close to the optimal ones. In summary, when the size of the graph increases linearly, the execution time of the heuristic algorithms increases linearly, while the execution time of the exact algorithm increases exponentially.

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Section: Fig 6 Activity Diagram For the Vertexcoverfinder Applicationmentioning

confidence: 99%

An Interactive Application for Learning and Analyzing Different Graph Vertex Cover Algorithms

2023

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“…One important problem associated with this type of research is the processing of the data used. Different data models are used, for example relational and object-oriented [5], [19], [20], different data access technologies, for example, remote database servers and web services [21], and different software approaches [22], [23].…”

Section: Introductionmentioning

confidence: 99%

“…Access to such a database can be done through a database management system-DBMS [1], [31]. Architectures of multi-user systems based on remote database servers with the ability to perform calculations and analysis of experimental data have been presented in other research [21], [30].…”

Section: Introductionmentioning

confidence: 99%

Data modelling and data processing generated by human eye movements

Kralev

Kraleva

Koprinkova–Hristova

2021

IJECE

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Data modeling and data processing are important activities in any scientific research. This research focuses on the modeling of data and processing of data generated by a saccadometer. The approach used is based on the relational data model, but the processing and storage of the data is done with client datasets. The experiments were performed with 26 randomly selected files from a total of 264 experimental sessions. The data from each experimental session was stored in three different formats, respectively text, binary and extensible markup language (XML) based. The results showed that the text format and the binary format were the most compact. Several actions related to data processing were analyzed. Based on the results obtained, it was found that the two fastest actions are respectively loading data from a binary file and storing data into a binary file. In contrast, the two slowest actions were storing the data in XML format and loading the data from a text file, respectively. Also, one of the time-consuming operations turned out to be the conversion of data from text format to binary format. Moreover, the time required to perform this action does not depend in proportion on the number of records processed.

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“…Problems from other scientific fields, such as [6]- [10] can also be described and analyzed by graphs. The graph structures can be stored in databases and retrieved by web services [11].…”

Section: Introductionmentioning

confidence: 99%

Methods for Software Visualization of Large Graph Data Structures

Kralev

Kraleva

2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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In this paper, three different methods for software visualization of large graph structures, respectively Rectangle, Intersection and Combined are presented. The basic concepts for using software development environments are outlined. Their capabilities for visual designing and event-oriented programming are discussed. A brief analysis of the basic features of the environment used to develop the ClipRect Monitor application is made. The main functions of this software are also presented. All experimental results in this study are generated with this application. According to the methodology, six graphs are prepared to determine the effectiveness of the three methods. The number of vertices and the edges of these graphs are proportional to the size of the drawing area (canvas). The drawing areas are also six and have different sizes, such that each subsequent area has a height and width twice the size of the previous one. Besides, for all areas, the width/height ratio is exactly 16:9. This ratio is widely used in monitors as well as laptops, mobile phones and tablets. The largest drawing area that the ClipRect Monitor application scanned during the experiments is 128 000 x 72 000 pixels. This scan is performed for graph G_6 with 1 415 vertices and 100 000 edges. The visualization area is diagonally positioned relative to the drawing area. For each visualization area, each of the three methods, respectively Rectangle, Intersection and Combined is performed. The Combined method executes the Rectangle method first and then the Intersection method. The results show that the Intersection method was the slowest compared to the other two methods in terms of the number of edges of the graph that are analyzed. When the visualization area is internal to the drawing area, the Rectangle method performs better than the Combined method. The Rectangle method gives the best result in terms of time for analysis and drawing of the edges of the graph. The Combined method combines the characteristics of the other two methods. This method is optimal in terms of the time of analysis of the need to draw the edges of the graph relative to the number of drawn edges.

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An Analysis of a Web Service based Approach for Experimental Data Sharing

Cited by 7 publications

References 23 publications

An Interactive Application for Learning and Analyzing Different Graph Vertex Cover Algorithms

An Interactive Application for Learning and Analyzing Different Graph Vertex Cover Algorithms

Data modelling and data processing generated by human eye movements

Methods for Software Visualization of Large Graph Data Structures

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