PHYSICAL LAYER SECURITY USING MASSIVE MIMO AND RIS TECHNOLOGY

Massive Multiple-Input-Multiple-Output (MIMO) systems and Reconfigurable Intellegent Surfaces (RIS) are considered to be the key technologies for next generations wireless communication, which are aimed to achieve higher data rates, massive connectivity and more secure data transmission. Combined use of these technologies together with artificial noise (AN) gives high hopes for strengthening Physical Layer Security (PLS) in wireless networks. This capstone work considers configuring phase shifts of RIS such that the impact of AN is maximized for illegitimate user, while its impact on legitimate user is not significant compared to the actual signal received from base station. In the proposed system model, some antennas is dedicated for AN and the rest are transmitting the actual data. The main objective of this model is to maximize Secrecy Capacity (SC) of the communication link, while satisfying the users’ quality of service (QoS). To achieve that, we optimize the phase shifts of RIS and find the optimal number of base station antennas transmitting AN. Obtained results validate theoretical concepts and show that proposed RIS-assisted Massive MIMO incorporated with AN transmission can be an effecting tool for establishing and improving PLS in wireless communication

Blended learning adoption in Kazakhstan

This study investigates the impact of secondary school teachers’ attitudes towards technology on the adoption of blended learning in Northern Kazakhstan, guided by the main research question: “What are the attitudes of secondary school teachers in Kazakhstan towards the use of technology in education?”. I used a qualitative research design, and it was informed by the Technology Acceptance Model and Social Cognitive Theory. I conducted in-depth interviews with ten teachers, selected through stratified sampling from various subjects and experience levels. The thematic analysis revealed a clear connection between teachers’ positive attitudes towards technology and the adoption of blended learning. The participants recognized technology’s potential to enhance student engagement in education but highlighted challenges such as technical difficulties and unequal access to technology. Moreover, the resistance towards technology integration demonstrated by some participants was rooted in a preference for traditional methods and concerns over technology’s impact and further compounded by a significant gap in professional development. The combination resulted in the hesitancy in adopting blended learning approaches. The findings also suggest that participants who view technology positively are more likely to support and adopt blended learning approaches. This indicates that positive attitudes towards technology can significantly enhance the integration of blended learning methods. These attitudes were influenced by factors such as prior technology experiences, training, and peer support. Overall, the findings call for the urgent need for targeted professional development and infrastructure improvements to address these barriers and enhance digital literacy among teachers, facilitating more effective blended learning environments

FINAL PROJECT REPORT DOCUMENT– SPRING 2024

The NU Life Hub project aims to address the fragmentation of information and resources for Nazarbayev University (NU) students by offering a centralized platform designed specifically for their needs. The project addresses students' challenges in finding and participating in campus activities, accessing a convenient marketplace to fulfill their needs, and staying informed about various campus events. The NU Life Hub solution will be a comprehensive platform that combines event management, marketplace, and community engagement functions to improve the overall university experience. During the project, extensive research was conducted to understand existing solutions and approaches to address similar challenges university communities face. This analysis informed the design and development of the NU Life Hub, ensuring that best practices were embedded into the platform and critical challenges were effectively addressed

CHARACTERIZATION AND PERFORMANCE ASSESSMENT OF A NOVEL NIO-FE3O4-POLYTHIOPHENE NANOCOMPOSITE FOR ASPHALTENE PRECIPITATION INHIBITION

Precipitation and deposition of asphaltene represents a significant challenge in the oil industry. Nanomaterials are considered as proper candidates for asphaltene adsorption and precipitation owing to their exceptional physical and chemical features. In this dissertation, first, a novel NiO-Fe3O4-Polythiophene nanocomposite (NC) was characterized using various advanced analytical methods to ensure its authenticity. X-ray diffraction (XRD) was used to determine the crystallite size and explore structures of the NC. Scanning electron microscopy (SEM) was used to investigate surface morphology and assess the particle size of the NC qualitatively. Fourier transform infrared spectroscopy (FTIR) methods was used to identify functional groups and elemental bonding of the NC. Brunauer-Emmett-Teller (BET) method was used to determine surface area of the NC. Thermogravimetric analyzer (TGA) was used to explore thermal stability of the NC. Using the XRD data the crystallite size was determined 33.2 nm. The particle size of the NC ranges from 60 to 400 nm based on SEM images, and surface area of the NC was determined 55.83 m2/g using the BET test data. TGA analysis revealed that the NC is thermally stable with a negligible mass loss under reservoir conditions (80°C). To assess efficacy of the novel NC for adsorption and inhibition of asphaltene, UV-spectroscopy technique was used to determine Asphaltene Onset Point (AOP) in presence and absence of the NC and then supernatant obtained from TGA analysis was used for adsorption kinetics isotherm modeling. Adsorption kinetics isotherm modeling was done using the Langmuir (R2 = 0.98) and Freundlich (R2 = 0.95) isotherm models. The experimental data matched well both models which suggests monolayer and multilayer adsorption behavior for adsorption of asphaltene onto the surface of the NC. A maximum adsorption capacity of 1.116 mg/m2 was obtained for the NC. TGA analysis confirmed that oxidation of virgin asphaltene started at around 400-450℃; while oxidation of 5,000 ppm sample with NC started at around 350℃. The NC has catalyzed oxidation of the asphaltene. An optimum NC concentration of 0.3 wt% was obtained and an AOP shifting from 40% to 48% volume of n-heptane was observed for the optimum concentration. The outcomes prove that, the novel NC is an effective nano-inhibitor for asphaltene under laboratory conditions

QAZAQ SIGN LANGUAGE DICTIONARY

Our 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

NEURAL NETWORK BASED FILTER MODELING AND OPTIMIZATION FOR 5G AND BEYOND APPLICATIONS

Designing high-performance microwave and millimeter-wave filters is difficult because small changes in geometric dimensions and electrical sizes can significantly affect the filter’s characteristic. Typically, in filter design, the initial values of design variables are optimized to achieve the desired performance. In the field of high-frequency RF device modeling, the use of machine learning (ML) through artificial neural networks (ANN) has gained popularity in recent years. Unlike other RF modeling techniques, ANN-based models require training with sufficient datasets to achieve the desired accuracy level. The input data could be the device’s dimensions, while the output could be the S-parameters. Once trained, the ANN-based model can provide EM-level accuracy and equivalent-circuit-level speed. Additionally, it is highly scalable, allowing for the introduction of more input parameters to make the model more versatile and complex. Therefore, the ANN-based model is an excellent option for high-frequency RF modeling compared to other techniques. The main objective of this research project is to develop an AAN that can be used in design of RF Filters

IMPROVED RESULTS ON FINITE-TIME SYNCHRONIZATION OF SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS VIA HYBRID IMPULSIVE PINNING CONTROL

This thesis explores finite-time synchronization in shunting inhibitory cellular neural networks (SICNNs) with time-varying delays. An advanced hybrid controller is introduced to achieve this, serving as a state-feedback and pinning-impulsive controller during impulsive intervals and instants, respectively. Considering the basic Lyapunov function, the paper proposes finite-time synchronization for the SICNNs-based master-slave model structured along with the hybrid controller. This proposition is validated through a series of case studies highlighting the effectiveness of the hybrid controller. Furthermore, this paper compares the settling time of finite-time synchronization using the proposed hybrid controller against the classic state-feedback and pinning-impulsive controller, demonstrating the advantages of the hybrid approach. The effectiveness of the proposed hybrid controller is exemplified through a numerical example, showcasing consensus between MATLAB software simulations and manual computations. The comparison analysis includes assessing the proposed hybrid controller against the classic state-feedback and pinning-impulsive controllers

WOMEN’S LEADERSHIP AND MOTHERHOOD IN HIGHER EDUCATION: A CASE STUDY OF WOMEN ADMINISTRATORS IN A REGIONAL UNIVERSITY IN EAST KAZAKHSTAN

This research explores the experiences of mothers who hold administrative positions in a regional university in East Kazakhstan. The study examines the challenges and benefits of balancing motherhood and administrative duties in higher education, aiming to inform the development of supportive structures for these women. This study used a qualitative method with semi-structured interviews as the data collection instrument. It delves into the challenges these mother administrators face, including work-life conflicts, workplace dynamics, and access to institutional support. The study also identifies positive aspects of having the dual role, including personal fulfillment, career advancement, and contributions to diversity within the institution. The findings highlight the significance of implementing flexible work schedules, providing leadership training and coping strategies to support female administrators. These measures can contribute to increasing job satisfaction, improving retention rates, and fostering a more inclusive and supportive work environment. This study adds to the existing body of knowledge on female leadership in higher education by providing practical insights for educational institutions to enhance their support systems for female administrators

TRIMOMIAL TREE METHOD FOR OPTION PRICING WITH TRANSACTION COST

This paper describes the progression of research initiated in MATH 424: Mathematical Finance course, with an emphasis on the creation and development of the Trinomial Tree Method for option pricing, particularly in the presence of transaction costs. We begin by reviewing the Cox-Ross-Rubenstein binomial scheme and then go on to trinomial approaches in financial literature, demonstrating their enhanced effectiveness over the binomial method. Our study includes complex models such as the Boyle and Vorst model, widening the scope beyond the standard Black-Scholes model covered in the course. However, the Boyle and Vorst’s method only covers transaction cost for binomial models. Our objective is to review the literature on the Trinomial Tree Method considering transaction cost which requires solving the absolute value matrix equation Ax − |X| = b along the tree. We have extended the results of the Boyle and Vorst from a binomial to trinomial method for a European call option. We implemented numerically our method and these results were inconsistent with the results of the Boyle and Vorst’s method comparable to the binomial results. The research extends the practical application of option pricing models by providing a complete framework for solving absolute value equations in the setting of trinomial trees, yielding useful insights for the Trinomial Tree Method with transaction cost

MOTIVATION AND REMOTE WORKING: CASE STUDY OF ONE NATIONAL HIGHER EDUCATION INSTITUTION IN KAZAKHSTAN

The COVID19 pandemic has upended our life in many aspects. When the virus raged in 2020, many countries announced a state of emergency and launched a complete lockdown. In the conditions of the severe lockdown, social isolation and remote working came to the fore and were applied by all organizations, including higher education institutions. Kazakhstani institutions also pursued this route by launching remote work options for all university staff. This single descriptive qualitative case study explores motivation of university staff who worked remotely during the period of pandemic. Overall, 15 university staff members were interviewed. Data analysis revealed some fluctuations in motivation of university staff when they worked remotely during the pandemic. Along with this, it was clear that working remotely affected the perception of work and work setting by revealing both advantages and disadvantages. Thus, this research fills in the gap in the previous literature on motivation, focusing particularly on the period of the pandemic and remote working by bringing in the perspective of university staff