Computer Science
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ISSN 1508-2806
e-ISSN: 2300-7036
Issue Date
2020
Volume
Vol. 21
Number
No. 2
Description
Reviewed by: Aleksander Smywinski-Pohl, Pawel Russek, Filip Malawski, Steven Chien, Maciej Paszynski, Antoni Ligeza, Marcin Kurdziel, Samed Jukic, Nemanja Macek, Aleksander Mendyk
Journal Volume
Computer Science
Vol. 21 (2020)
Projects
Pages
Articles
Survey of scientific document summarization methods
(Wydawnictwa AGH, 2020) Kurian, Sheena K.; Mathew, Sheena
The number of research papers published every year is growing at an exponential rate, which has led to intensive research in scientific document summarization. The different methods commonly used in automatic text summarization research are discussed in this paper, along with their pros and cons. Commonly used evaluation techniques and datasets in this field are also discussed. Rouge and Pyramid scores are tabulated for easy comparison of the results of various summarization methods.
Forward and backward static analysis for critical numerical accuracy in floating-point programs
(Wydawnictwa AGH, 2020) Thushara M. G.; Somasundaram, Kanagasabapathi
In this article, we introduce a new static analysis for numerical accuracy. We address the problem of determining the minimal accuracy on the inputs and on the intermediary results of a program containing foating-point computations in order to ensure a desired accuracy on the outputs. The main approach is to combine a forward and a backward static analysis, done by abstract interpretation. The backward analysis computes the minimal accuracy needed for the inputs and intermediary results of the program in order to ensure a desired accuracy on the results, specied by the user. In practice, the information collected by our analysis may help to optimize the formats used to represent the values stored in the variables of the program or to select the appropriate sensors. To illustrate our analysis, we have shown a prototype example with experimental results.
Salt and pepper noise reduction and edge detection algorithm based on neutrosophic logic
(Wydawnictwa AGH, 2020) Arulpandy, P.; Trinita, Pricilla M.
Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that affects a gray-scale image significantly.Generally, the median filter is used to reduce salt and pepper noise, it gives optimum results while compared to other image filters. Median filter works only up to a certain level of noise intensity. Here we proposed a neighborhoodbased image filter called nbd-filter, it works perfectly for gray image regardless of noise intensity. It reduces salt and pepper noise significantly at any noise level and produces a noise-free image. Further, we proposed an edge detection algorithm based on the neutrosophic set, it detects edges efficiently for images corrupted by noise and noise-free images. Neutrosophic set (NS) is a powerful tool to deal with indeterminacy. Since most of the real-life images consists of indeterminate regions, Neutrosophy is a perfect tool for edge detection. In this paper, the neutrosophic set is applied to the image domain and a novel edge detection technique is proposed.
Extracting class diagram from hidden dependencies in data set
(Wydawnictwa AGH, 2020) Hnatkowska, Bogumiła; Huzar, Zbigniew; Tuzinkiewicz, Lech
A conceptual model is a high-level, graphical representation of a specic domain, presenting its key concepts and relationships between them. In particular, these dependencies can be inferred from concepts' instances being a part of big raw data files. The paper aims to propose a method for constructing a conceptual model from data frames encompassed in data files. The result is presented in the form of a class diagram. The method is explained with several examples and verified by a case study in which the real data sets are processed. It can also be applied for checking the quality of a data set.
Efficient implementation of Chinese remainder theorem in minimally redundant residue number system
(Wydawnictwa AGH, 2020) Selianinau, Mikhail
The Chinese remainder theorem is widely used in many modern computer applications. This paper presents an efficient approach to the calculation of the rank of a number, a principal positional characteristic that is used in the residue number system. The proposed method does not use large modulo addition operations as compared to a straightforward implementation of the Chinese remainder theorem algorithm. The rank of a number is equal to the sum of an inexact rank and a two-valued correction factor that only takes on values of 0 or 1. We propose a minimally redundant residue number system that provides a low computational complexity of the rank calculation. The effectiveness of the novel method is analyzed regarding a conventional non-redundant residue number system. Owing to the extension of the residue code, the complexity of the rank calculation goes down from $O(k^{2})$ to $O(k)$ by adding the extra residue modulo 2 (where $k$ equals the number of non-redundant residues).