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UNDERSTANDING UNDERGRADUATE INTERNATIONAL STUDENTS EXPERIENCES, CHALLENGES, AND COPING STRATEGIES AT EMI UNIVERSITIES IN KAZAKHSTAN
No full textUnderstanding Undergraduate International Students Experiences, Challenges, and Coping Strategies at an EMI University in Kazakhstan
The globalization of higher education (HE) has led to a rise in the number of international students globally, including in Kazakhstan. Despite their crucial role in the internationalization of HE, there is a noticeable scarcity of research on the experiences, challenges, and coping strategies of international students in Kazakhstan. To close this gap, phenomenological research was carried out at two English-medium instruction (EMI) universities in Kazakhstan, which are well-known for having substantial numbers of international students. Seven participants from various countries studying in Kazakhstan participated in semi-structured interviews to discuss their experiences, difficulties, and coping mechanisms for overcoming obstacles. The results, which are presented through Lyysgards' (1955) U-Curve theory used as a conceptual framework, show that although the participants had good experiences that they attributed to the friendly atmosphere of the university and the local community, they also faced considerable challenges and employed number of coping strategies. These challenges are related to adaptation to new academic environments and curricula, linguistic challenges, and socio-cultural adjustments. Students employed several strategies to cope with these issues, including leveraging university resources, engaging in social activities, practicing the local language, and seeking personal space. The study's findings highlight the need for a comprehensive support system that integrates institutional support for international students through which they could attract many international students and enhance students’ experiences at their university. This study offers valuable insight into the particular difficulties foreign students face in Kazakhstan and offers practical solutions that stakeholders in education could consider. From this qualitative study, areas for further research are suggested.
Keywords: international students, Kazakhstan, EMI Universities, experiences, challenges, coping strategies, phenomenological study
VIDEO-BASED MONITORING OF RED-LIGHT TRAFFIC LAW VIOLATION
No full textThe need for remote road traffic monitoring is essential to reduce accident possibilities.
It encourages drivers to abide by the traffic laws. Recently, researchers have been
focused on automatic traffic monitoring using edge devices, Computer Vision (CV),
and Machine Learning (ML) due to the increase in vehicle numbers. However, due
to the number of edge devices, the problems of high-cost hardware for cloud-based
computations and scalability of the bandwidth are arising. Therefore, this paper
proposes a low-cost microprocessor-based traffic monitoring system that will conduct
all processing on the edge. The system will be used near traffic lights and detect
law violations on red lights. It will make drivers more careful by adding certain
consequences which will lead to fewer accidents. The microprocessor is equipped with
a camera module and is used to run a video processing algorithm and Convolutional
Neural Network (CNN) for law violation detection, and its further classification. The
device will be installed on the traffic light pole in Astana, Kazakhsta
«Анализ «Серпин-2050: Молодежь Вечного Государства в индустрию»
No full text“Serpin-2050 - The Youth of Eternal State to the Industry” is a program aimed at providing scholarships to young people from rural southern regions of Kazakhstan. The participants can study only in the assigned northern regions and are provided with a comprehensive scholarship with a range of assistance measures from the government. The official goal is to move people from the southern labor-excessive regions with high unemployment to the northern regions with a deficit of labor force. In return for government support, the participants are obliged to stay for two years in one of the assigned regions. However, numerous reports indicate that the program is not working and the number of the program graduates that leave assigned regions far exceeds the number of those who stay. This study aimed to understand the causes of this situation and make recommendations to alleviate it. Using statistical data, interviews with students and university administrators of three universities participating in the program, and the central government officials, we discovered that housing is the main issue for the graduates. This problem is further complemented by low salaries, not speaking Russian, social integration, and other issues. Based on the findings and the analysis of the government's proposed measures, we put forward the recommendations to develop the program
“‘ОППЫ НЕ ПОНИМАЮТ НАШ LINGO’: THE ROLE OF ENGLISH BORROWINGS IN CONVEYING TABOO-RELATED MEANINGS IN RUSSIAN HIP-HOP MUSIC”
No full textBorn in marginalized communities of the South Bronx, hip-hop music often addresses highly sensitive topics in its lyrics. Inspired by American rappers, hip-hop artists all over the world, including Russian rappers, started to address sensitive topics in their songs. In Russia, rappers cover taboo topics more indirectly because of the strict government censorship on what can be said in the media. Within this context, one of the linguistic tools frequently used by Russian rappers to address taboo topics is borrowing taboo-related words from English. The present study examines the role of such English borrowings in covering taboo-related meanings in Russian hip-hop music, based on the artistry of the Russian rapper nicknamed MAYOT. To conduct the analysis, I compiled a corpus of 33 songs (around 4500 words total) by MAYOT across 3 albums from 2020, 2021, and 2022, which I then annotated using tags for borrowed/non-borrowed taboo words, taboo/non-taboo borrowings, and four semantic fields of taboos, including Drugs, Violent and Criminal acts (VC), Sex, and Profanity. I discovered that even though the total number of non-taboo borrowings was larger than the number of borrowed taboo words, the mean number of borrowings per taboo-related semantic field was on average 3 times more than that of non-taboo. I also discovered that MAYOT only expressed 25% of taboo meanings with borrowings whilst using other linguistic tools such as regionalisms, euphemisms, and jargonisms to rap about taboos in Russian. Another discovery was the uneven distribution of taboo words across different semantic fields. It turned out that the words from the domains of Drugs and VC were more likely to be borrowed than the ones from the fields of Sex and Profanity. Finally, contrary to what I hypothesized, the number of taboos and borrowings in MAYOT’s songs did not increase with each subsequent year. The results of this study help us understand what taboo topics seem to be most sensitive within Russian culture, and how Russian rappers deal with censorship of taboo discourse through their linguistic choice to borrow taboos from English
RAILWAY WARNING SYSTEM APPLICATION
No full textThis paper presents the development and implementation of a Railway Warning System application designed to enhance railway safety by facilitating real-time communication between train drivers and maintenance personnel. The system leverages GPS tracking to provide up-to-date information on train locations and maintenance activities, ensuring drivers receive timely alerts about upcoming repair sites. This proactive notification mechanism aims to prevent accidents by allowing sufficient time for drivers to slow down or stop. The application features an intuitive user interface and integrates advanced notification capabilities, addressing the limitations of existing solutions. Developed using React JS for the front end, Django for the backend, and hosted on DigitalOcean, the system demonstrates significant improvements in operational efficiency, safety, and reliability within the railway network. Evaluation feedback indicates that the application effectively enhances communication and safety, suggesting potential for future enhancements and wider adoption
THE COMMODIFICATION OF CULTURE: HOW AI AFFECTS KAZAKHSTANI ARTISTS' ART PRODUCTION
No full textThe emergence of generative Artificial Intelligence on the global stage has brought
much controversy regarding its impact on artists. While some artists embraced this
technology by using it as a new medium, others were concerned about the unemployment
following it. At the moment, we see how generative Artificial Intelligence is gradually
spreading in Kazakhstan. However, since the issue of generative AI has not been previously
studied in this country, and since most artists around the world express concerns about this
technology, it was decided to explore the degree and complexity of Kazakhstani artists’ social
acceptance of such technology. For this purpose, semi-structured in-depth in-person
interviews with traditional and digital artists from Almaty and Astana were conducted.
Participants were identified through convenience sampling followed by snowball sampling.
The project also featured the art exhibition with AI-generated and artist-created works, where
the audience had to distinguish these works. As a result of the interviews, it was discovered
that Kazakhstani artists are resistant to accepting generative AI due to concerns about
unemployment, uncertainty, and enslavement. Whereas the exhibition demonstrated the
similarity of the AI-generated and artists-created works and the audience’s inability to
distinguish them, leading to the aforementioned concerns. Furthermore, it was discovered that
the unemployment affected by generative AI in Kazakhstan may be higher in future,
compared to Western countries. In this way, such resistance to accept the technology is
explained by the devaluation of artists’ cultural capital. It would be beneficial to conduct a
similar study in the future with a larger sample size, possibly using a combination of
qualitative and quantitative research methods, since the AI field is rapidly evolving, which
was demonstrated by the exhibition results
ENERGY EFFICIENT SCHEDULER FOR EDGE/CLOUD COMPUTING BASED ON OFFLOADING AND DEEP LEARNING
No full textResource-intensive applications have created a growing demand for efficient computation offloading in edge computing.
This project investigates schedulers for energy efficiency in edge computing, utilizing a PicoCluster 20H with 20 Jetson
Nano devices as the edge infrastructure. The system uses the RAPID and COSCO frameworks for container
orchestration and task scheduling while incorporating a custom workload based on real-time intermediate flow
estimation (RIFE) model. Five different schedulers, including algorithmic (ROS, MAD-MC, LR-MMT) and machine
learning (ML)-based (GOBI, GOSH) approaches, were implemented and evaluated.
The results demonstrate that ML-based schedulers, specifically GOBI and GOSH, achieve superior energy efficiency
compared to algorithmic methods, highlighting the potential of deep learning (DL) for optimizing resource allocation in
edge computing. We were also successful at setting up and executing custom workloads with the corresponding
schedulers on our cluster. Future work will focus on covering a larger selection of schedulers and novel methods of DL
applications in scheduling algorithms
SYNTHESIS OF PS/CU MOF NANOFIBERS FOR THE ADSORPTION OF LEAD (II) CATION FROM AN AQUEOUS SOLUTION
No full textWater pollution, particularly with heavy metals like lead, poses a severe threat to human health and the environment. This study explores the synthesis and application of polystyrene (PS)-supported copper metal-organic frameworks (MOFs) for efficient lead (Pb²⁺) ion removal from aqueous solutions. MOFs were synthesized using organic ligands biphenyl-4,4-dicarboxylic acid (BDC) and benzene-1,4-dicarboxylic acid (BTC) and integrated into PS nanofibers through electrospinning. The resulting nanofibers were characterized by Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), and Fourier Transform Infrared Spectroscopy (FTIR). Adsorption experiments demonstrated that PS/Cu-BTC nanofibers exhibited superior lead removal efficiency compared to other tested configurations, with optimal adsorption observed at 0.05g for PS/Cu-BTC nanofibers. Pure MOF powders showed even higher adsorption efficiency, highlighting the potential for improved water treatment methods. The study suggests that modifying the MOF structures and exploring new materials could further enhance lead ion removal capabilities
INVESTIGATING THE ROLE OF PERIOSTIN IN RHEUMATOID ARTHRITIS
No full textRheumatoid Arthritis (RA) is a chronic inflammatory disease, in which the immune system of the organism attacks its own tissue on different body parts (Finckh et al. 2022). Mostly, RA affects the joints of hands, feet, knees, shoulders, etc. According to the World Health Organization, in 2019, about 18 million people worldwide had RA and 70% were women (“Rheumatoid Arthritis,” n.d.). The specific causes of the disease are unknown, but several disease-associated risk factors have been identified, like, smoking, obesity, genetics, gender, and age (Weyand and Goronzy 2021). There are a few publications suggesting some possible roles of periostin in RA disease progression (Brown et al. 2018). Periostin is an extracellular matrix protein that has varying roles in inflammation and tissue remodeling (Sonnenberg-Riethmacher, Miehe, and Riethmacher 2021). It was revealed that periostin is upregulated in synovial cells and fluid of RA patients, which suggests that it may worsen inflammatory conditions in the RA affected body parts (Chijimatsu et al. 2015; Kasperkovitz et al. 2005). However, there are some studies that provide contradictory evidence, which demonstrate after artificial induction of RA in mice, disease progression is more severe in periostin-deficient mice compared to wild-type mice. So, the precise function of periostin in RA pathogenesis remains enigmatic. The aim of this master thesis project was to elucidate the unknown role of the periostin in the RA progression and examine its potential anti-inflammatory properties. Firstly, it was planned to establish a mouse model of rheumatoid arthritis to investigate the comprehensive role of periostin in the disease progression (Caplazi et al. 2015). For this purpose, RA was induced in wild-type and periostin-deficient mice using a collagen-induced arthritis method (Brand, Latham, and Rosloniec 2007; Inglis et al. 2008). After the RA induction, mice were monitored for the disease progression based on the 3 assessment methods: measurement of paw thickness, observation of walking and behavior, and palpation. Then, mice were euthanized and inflamed joints were used for the comparative analysis. Expression of periostin and IL-17 receptor A were analyzed with fluorescent immunohistochemistry. For the histopathological analysis, hematoxylin and eosin staining was implemented to identify structural differences in the inflamed tissue joints. This master thesis project contributes to advancing the knowledge of the periostin role in RA pathogenesis
VARYING INTEREST RATES AND ANNUITIES
No full textIn this paper, we first applied a piecewise linear regression model to best fit the discrete varying interest rate data and then we applied these results for the calculation of annuities with time variable interest rates. We used two different approaches to calculate annuities with time-varying interest rates, namely, the Yield Curve Method and the Portfolio Rate Method