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Item Open Access Breaking Barriers with AI: The Evolution and Challenges of Automated Sign Language Recognition(SDU University, 2025) Joshi M.; Khankriyal P.; Chandola Y.; Uniyal V.Communication remains a significant challenge for individuals with hearing impairments and speechrelated disabilities, especially when others are not familiar with sign language. Developing technologies that facilitate seamless communication for these individuals is crucial to promote equality for disabled people and accessibility for all. Sign language recognition systems have emerged as a promising solution, typically implemented using a hardware or software-based approach. Hardware solutions, such as sensor-equipped gloves, often pose usability and cost barriers, making them less appealing for widespread adoption. In contrast, software-driven approaches using artificial intelligence (AI), deep learning (DL) and machine learning (ML) offer a more practical and scalable alternative. This paper provides a complete review of recent developments in AI-based sign language recognition systems, with a particular attention towards deep learning architectures such as Convolution Neural Networks (CNNs). The aim is to evaluate current methodologies, highlight their strengths and limitations, and identify potential directions for future research to improve communication technologies for hearing-impaired people.Item Open Access Well-Posedness for a Degenerate Hyperbolic Equation with Weighted Initial Data(SDU University, 2025) Kakharman N.; Zhumabayeva A.The focus of this study is an initial-boundary value problem associated with the degenerate hyperbolic equation t∂ttu + 1 2 ∂tu − ∆u = g in a bounded domain. Due to the singularity at t = 0, standard initial conditions lead to an ill-posed problem. To achieve solvability of the problem, we introduce a ”modified” Cauchy problem using weighted initial conditions for this degeneracy. The main result of the study is the proof of the well-posedness of this problem within the framework of classical Sobolev spaces, as well as the obtaining of a priori estimates of the solution. Furthermore, the general boundary conditions for the one-dimensional equation were derived by using the restriction and extension theoryItem Open Access Predictive Analytics for Student Engagement in E-Learning Systems(SDU University, 2025) Murattaly Y.; Serek A.To increase the success of students’ education, it is important to be able to predict the level of their involvement in the online educational environment. This study uses the Open University Learning Analytics (OULAD) open dataset to develop a systematic and reproducible approach to classifying student engagement. On the other hand, many other studies depend on specific datasets or limited definitions of engagement. A full cycle of data preprocessing and feature extraction was implemented, aimed at obtaining informative behavioral indicators based on click data and evaluation results. We trained and tested two traditional supervised machine learning model, Random Forest and Logistic Regression, using weight and macro-average metrics. The random forest model demonstrated high efficiency across all interaction classes and showed higher accuracy (0.926) compared to logistic regression (0.896). The results obtained emphasize the importance of high-quality data preprocessing and thoughtful design of features. In addition, they confirm that such signs provide valuable information for the development of early warning systems and the further development of educational analytics in higher education institutions.Item Open Access A MULTILEVEL CONVERTER WITH TRIPLE VOLTAGE BOOST FOR RENEWABLE ENERGY SOURCES(SDU University, 2025) Taissariyeva K.; Ayapbergen Zh.A compact, single-supply, multilevel inverter (SC-MLI) topology based on a switched-capacitor structure for high-efficiency power conversion is proposed. The overall goal of the study is to develop a three-stage inverter that increases the voltage by a factor of 13 while simultaneously reducing the number of required components. As a result, the proposed design reduces circuit complexity and cost while also increasing reliability. The inverter’s performance was evaluated using theoretical analysis, MATLAB/Simulink and PLECS simulations, and experimental verification. In addition, tests using a natural capacitor without a control circuit or with resistive and inductive loads confirmed the stable generation of multi-level voltage and voltage balance with additional sensors. For example, when operating in sinusoidal pulsewidth modulation (SPWM) and low-level control (NLC) modes, the inverter maintained low harmonic distortion and a uniform current waveform. As a result, the system achieved a maximum efficiency of 97.2% in modeling and 95.3% experimentally. The results of this study confirm the Recommended Level 13 SC-MLI compliance for renewable energy integration and other advanced power electronics applications.