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FUNCTIONAL CHARACTERIZATION OF OSMOTIC STRESS RESPONSE IN HALOARCHAEA ISOLATED FROM THE KOBEITUZ LAKE
No full textHalobacterium KBTZ01, a halophile archaea species from Kobeituz Lake, Kazakhstan, thrives in hypersaline environments. Therefore, these serve as good models for studying molecular mechanisms underlying the tolerance to high salt concentrations. This study investigates the impact of osmotic stress on these cells, induced by exposure to varying NaCl concentrations (0.6/1/1.5M) in a hypotonic growth medium at 3 and 9 hours. The experimental approach involves studying stress response by incubating cells in hypotonic media, followed by protein extraction and analysis using SDS-PAGE and mass spectrometry. The morphology and viability parameters were analyzed with confocal microscopy. Low NaCl concentrations (600) are deadly for the haloarchaea, while 1M and 1.5M NaCl can be tolerated for a certain amount of time. Proteomic findings include upregulation of certain proteins related to metabolism, biogenesis and signal processing. Significant decrease in motility was observed and was validated by downregulation of motility proteins. Some proteins indicate varying abundance levels with progression of hypotonic stress. This research contributes valuable insights into the molecular mechanisms enabling halophilic archaea to thrive in challenging environments
DIGITAL TWIN FRAMEWORK FOR SOLAR POWER PLANTS IN KAZAKHSTAN
No full textThe renewable energy sector (RES) is a fast-growing industry that provides sustainable
and clean energy. The adoption and integration of such technologies positively affect the
environment and boost the country's economy. The global trend for sustainability opens new
opportunities to integrate sophisticated technologies and improve existing energy infrastructure.
This project aims to propose a detailed Digital Twin (DT) framework indicating important
implementation steps and providing insights into DT technology that improves operational
efficiency, optimizes performance, and creates a user-friendly platform for real-time monitoring.
This study has produced several deliverables through collaboration with the domestic
company TechnoGroupService (TGS), which specializes in constructing and operating solar
power plants in Kazakhstan. Deliverables include a detailed investigation of the 50MW solar
power plant's operational process, infrastructure, and data transfer models. That detailed plant
information helped to build a strong foundation for a comprehensive DT implementation
framework that describes all the steps and procedures required to obtain a working DT platform.
The framework provides a DT architecture consisting of six main phases, from plant
infrastructure exploration to DT application description. The entire framework was then used to
create a detailed roadmap for the implementation of DT in the context of Kazakhstan, taking into
account the peculiarities of the region and adapting international standards to the realities of the
country. As one part of the development phase, an online web platform has been developed.
These include real-time monitoring indicating the current status of the solar plant which is
further used in reactive-maintenance capabilities. The results offered have been reviewed by
industry experts and capstone supervisors to ensure applicability, reliability, and actuality
BAND SELECTION USING 3D REGION GROWING ALGORITHM FOR HYPERSPECTRAL IMAGE ANALYSIS
No full textAdvancements in sensor technology have significantly increased the importance of hyperspectral imaging (HSI) in various computer vision applications for remote sensing. Modern HSI sensors provide unmatched spectral resolution by capturing images from satellites and drones, encompassing the electromagnetic spectrum from 400 to 2500 nanometers. This study explores how to use the abundant spectral data effectively, specifically addressing the issue caused by the high dimensionality of HSI data. We propose a new method that improves the selection of spectral bands for better segmentation accuracy through the use of a 3D Region Growing Algorithm (RGA). Unlike other selection methods that primarily identify statistically distinct bands, our approach focuses on heuristically searching for the most informative bands. This approach introduces a flexible stopping rule dependent on seed pixel intensity, providing precise control over segmentation by adjusting to different image contrasts. Our approach combines spatial and spectral information to achieve context-aware segmentation. This method has been proven to be effective in various datasets like Salinas, Indian Pines, Pavia Centre, and a real-world dataset, showing its potential in remote sensing
EXPLORING KAZAK LANGUAGE TEACHER EDUCATORS' CURRICULUM IDEOLOGIES AND LIVED EXPERIENCES: A THIRD SPACE PERSPECTIVE
No full textThis phenomenological study investigates Kazakh language teacher educators' curriculum ideologies and lived experiences through a third-space lens in the context of educational reforms in Kazakhstan. It aims to uncover how these educators navigate changes imposed by the updated curriculum and the implications of these changes for Kazakh language education. The study employs three research instruments—multimodal interviews, the art-based research tool "significant circles," and semi-structured interviews with image cards—to gather rich qualitative data from five experienced teacher educators. The findings reveal that the updated curriculum profoundly influences educators' practices and ideologies, often generating a complex interplay between traditional Soviet teaching methodologies and modern, learner- centered approaches. Despite these challenges, a third space emerges where educators negotiate and hybridize these influences, fostering innovative pedagogies that integrate local knowledge with global educational standards. Embracing this third space can lead to more culturally and contextually relevant teaching strategies, potentially shaping the future of language education in Kazakhstan. This study contributes to the broader discourse on curriculum ideologies in post-Soviet contexts, highlighting the pivotal role of teacher educators in bridging curriculum reforms and practice. It calls for reforms that support educators' transition towards hybrid practices, thereby enriching the educational landscape
A PIMPLE'S MY PRIDE: THE SOCIAL ACCEPTANCE OR REJECTION OF ACNE IN ASTANA
No full textThis study explores the degree to which the acne skin condition is accepted, rejected or stigmatized in Kazakhstani society based on the experiences of individuals living with it. This project employed qualitative methods with a focus on semi-structured in-depth interviews. 9 individuals living in Astana at the time of the interview of all genders aged 18 and above, currently dealing with diagnosed acne, were selected using a combination of convenience and snowball sampling. Multiple descriptive and narrative coding approaches were utilized when analysing the transcripts, like ‘structural coding’, ‘secondary labels’ and ‘descriptive coding’. The dimension of gender, although shaping individual experiences with acne, was most notable in the topics of beauty and makeup. This unifies receiving advise, seeing others with acne and socializing and coping methods as more or less universal experiences among the participants. Results demonstrated that individuals with acne are themselves dynamically influencing their internal perception of acne’s degree of social stigma and in turn, through their nonchalant attitude contribute towards the gradual process of this skin condition’s acceptance. While acne’s neutral or negative impact on attractiveness contributes towards the construction of gendered skin beauty – although not a fully socially discrediting trait – its existence implies that eventual treatment is preferable
QAZAQ SIGN LANGUAGE DICTIONARY
No full textOur project aims to deliver a comprehensive digital platform focused on learning and using sign language to revolutionize access for the Deaf community. This platform ensures inclusiveness and improved communication by integrating multiple resources to address different learning styles and needs. The main feature of our platform is the Sign Language Dictionary, which includes several categories. These categories cover various aspects of daily life such as greetings, emotions, nutrition, activities and more. Each category is a collection of carefully selected sign language videos, each containing a particular hand or word associated with that category. These videos are designed to be informative, engaging, and accessible, allowing users to learn sign language and learn at their own pace. The Sign Language Dictionary also has a search function that allows users to search for specific words or specific gestures they want to see or find quickly. This feature enhances the usability and efficiency of the platform by allowing users to easily navigate through a large database of sign language content. In addition, our platform includes user-generated content through licensed downloads. This feature allows qualified professionals, such as certified sign language instructors to upload videos to the platform. These videos go through a process of verification and quality, enhance the content of the platform, and enhance the user’s learning experience. In addition to the dictionary and custom content, our platform offers a reverse dictionary feature. Our platform allows you to record hand gestures and use them to search for words in a large database of words. We achieved this using a model through which we conducted video clips and output them for all possible predictions and saved them in the database
APPLICATION OF DEEP NEURAL NETWORKS AND COMPUTER VISION IN REHABILITATION ROBOTS
No full textThe objective of this research is to develop an automated system for detecting gait-related health issues using Deep Neural Networks (DNNs). The system processes video footage of patients to estimate their 3D body posture through a DNN-based method, then this 3D body posture gets classified using another DNN-based method. The analyzed 3D body pose data is classified into 3 categories: Healthy, Parkinson’s disease and Post Stroke. This technology eliminates the need for bulky, complex equipment and extensive lab space, making it practical for use at home. It also doesn't require specialized knowledge for feature engineering, as it automatically extracts meaningful, high-level features from the data. The test results show classification accuracies ranging from 56% to 96% across different groups. The conclusion of this study indicates that this system is a promising tool for automatically classifying gait disorders and could be a foundational technology for future deep learning applications in clinical gait analysis. The significance of this system is underscored by its use of digital cameras as the sole required equipment, facilitating its use in patient homes and among the elderly for regular monitoring and early detection of gait changes
MUSIC STREAMING APP WITH DEEP LEARNING TECHNIQUES
No full textThis study presents the development of a music classification and recommendation system for web applications, employing deep learning and visualization methodologies to address the demand for refined audio recommendation systems. Through research and experimentation, high accuracy in music genre classification was achieved. Building a CNN model and employing t-SNE visualization resulted in a clear clustering of audio files. Coordinated of individual songs were used in the recommendation system logic
AN EMERGENT COSMOLOGICAL MODEL FROM ASYMPTOTIC SAFETY
No full textThe modern cosmological models tell us that the early universe has gone through a phase of accelerated expansion, known as inflation, which solves the horizon and flatness problems. In this thesis, I present an inflationary cosmological model based on the Asymptotically Safe behavior of the Newton constant at Planckian energies. Unlike
other models, the variability of G is given by a multiplicative coupling constant χ in the
matter Lagrangian with a conserved energy-momentum tensor, and the specific functional
form of χ is deduced from Asymptotically Safe gravity. In the beginning, the universe
undergoes a quasi-de-Sitter phase and, then transitions to the conventional cosmological
evolution after the Planck Era
CREATION OF A MOBILE APP: KAZAKH NATIONAL GAME - TOGYZ QUMALAQ
No full textOur project focuses on preserving and improving the appreciation of Kazakh culture, particularly through the national game ”Togyz Qumalaq.” We are addressing the challenge of cultural practices being overshadowed by modern advancements by creating an interactive mobile application. This initiative is crucial for keeping ”Togyz Qumalaq” noted and accessible in the future. The mobile application features include:
• A modernized digital version of the traditional ”Togyz
Qumalaq” game board.
• An AI offering three levels of difficulty to suit all
players.
• Simple, intuitive gameplay designed to be accessible to
newcomers.
• An online multiplayer function to promote global interaction and cultural sharing.
By transforming ”Togyz Qumalaq” into a digital format, our project not only preserves this important aspect of Kazakh heritage but also makes it engaging and educational for users worldwide