Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Kudubayeva, Saule
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Research of semantic aspects of the Kazakh language when translating into the Kazakh sign language Nurgazina, Dana; Kudubayeva, Saule
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4488-4497

Abstract

The article discusses the semantic aspects of Kazakh sign language and its characteristics. Semantics, a field within linguistics, focuses on examining the meanings conveyed by expressions and combinations of signs. The author delves into the inquiry of the degree of similarity between verbal and sign languages, highlighting their fundamental distinctions. The primary objective of the research is to scrutinize the characteristics of parts of speech in the Kazakh language when expressed gesturally, along with the principles governing the translation of verbs and adverbial tenses. The article explains in detail the formulas for translating the text into sign language, based on the subject-object-predicate. Examples are given that illustrate the subject-object relationship and determine who acts as the speaker, "object" or "subject" of the utterance. It is necessary to note that for successful translation it is necessary first to understand the meaning of the sentence. The article concludes by emphasizing the importance of understanding both structural elements and contextual nuances in the fascinating world of the semantics of the Kazakh sign language. It inspires further research aimed at uncovering the complexities and exceptions that contribute to a deep understanding of linguistic nuances in this unique form of communication.
Combined-adaptive image preprocessing method based on noise detection Shamshanovna, Razakhova Bibigul; Amangeldy, Nurzada; Kassymova, Akmaral; Kudubayeva, Saule; Kurmetbek, Bekbolat; Barlybayev, Alibek; Gazizova, Nazerke; Buribayeva, Aigerim
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1584-1592

Abstract

The image processing method involves several critical steps, with image preprocessing being particularly significant. Segmentation and contour extraction on digital images are essential in fields ranging from image recognition to image enhancement in various recording devices, such as photo and video cameras. This research identifies and analyzes the main drawbacks of existing segmentation and contour extraction methods, focusing on object recognition. Not all filters effectively remove noise; some may clear areas of interest, affecting gesture recognition accuracy. Therefore, studying the impact of image preprocessing on gesture recognition outcomes is crucial for improving pattern recognition performance through more efficient preprocessing methods. This study seeks to find an optimal solution by detecting specific features during the preprocessing stage that directly influence gesture recognition accuracy. This research is a key component of the AP19175452 project, funded by the ministry of science and higher education. The project aims to create automated interpretation systems for Kazakh sign language, promoting inclusivity and technological innovation in communication aids. By addressing these challenges, the study contributes to the development of more robust and adaptive image preprocessing techniques for gesture recognition systems.
Co-Authors Amangeldy, Nurzada Barlybayev, Alibek Buribayeva, Aigerim Gazizova, Nazerke Kassymova, Akmaral Kurmetbek, Bekbolat Nurgazina, Dana Shamshanovna, Razakhova Bibigul