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This work introduces NOVAK, a modular gradient-based optimization algorithm that integrates adaptive moment estimation, rectified learning-rate scheduling, decoupled weight regularization, multiple variants of Nesterov momentum, and lookahead synchronization into a unified, performance-oriented framework. NOVAK adopts a dual-mode architecture consisting of a streamlined fast path designed for production. The optimizer employs custom CUDA kernels that deliver substantial speedups (3-5 for critical operations) while preserving numerical stability under standard stochastic-optimization assumptions. We provide fully developed mathematical formulations for rectified adaptive learning rates, a memory-efficient lookahead mechanism that reduces overhead from O(2p) to O(p + p/k), and the synergistic coupling of complementary optimization components. Theoretical analysis establishes convergence guarantees and elucidates the stability and variance-reduction properties of the method. Extensive empirical evaluation on CIFAR-10, CIFAR-100, ImageNet, and ImageNette demonstrates NOVAK superiority over 14 contemporary optimizers, including Adam, AdamW, RAdam, Lion, and Adan. Across architectures such as ResNet-50, VGG-16, and ViT, NOVAK consistently achieves state-of-the-art accuracy, and exceptional robustness, attaining very high accuracy on VGG-16/ImageNette demonstrating superior architectural robustness compared to contemporary optimizers. The results highlight that NOVAKs architectural contributions (particularly rectification, decoupled decay, and hybrid momentum) are crucial for reliable training of deep plain networks lacking skip connections, addressing a long-standing limitation of existing adaptive optimization methods.
The National Botanical Garden, Mirpur (Bangladesh), was established in 1961 with a wide landscape of 214 acres. The garden is located in one of the fastest-developing communities of Mirpur 1, at the center of the capital, Dhaka. The garden has a large herbarium with 100,000 samples, including rare collections of mammals (70 species), birds (190 species), and various plants and trees (1042 species), as well as six water bodies. Despite such a wonderful collection, the garden attracts only about 100,000 visitors annually. The main visitors are local senior citizens, some students, and a couple of tourists, according to witnesses. However, reports say the ecotourism market valuation was USD 235.54 billion in the year 2023. It is expected to reach around 665.20 billion USD within this decade (till 2030). Additionally, global market reports say that garden tourism alone accounts for USD 5.02 billion of the ecotourism industry. Besides these, scholars have reported that the current generations (Millennials and Generation Z) have serious concerns and an attraction to natural sustainability, as well as sensitivity to animal lives worldwide. Considering the potential of the botanical garden in Dhaka, the authors found that a gap in public relations and marketing is a major barrier to the garden reaching its full capacity as a tourist attraction. This paper is based on a systematic literature review (SLR) and participant observation to analyze the current situation and develop a marketing model specific to the national botanical garden in Mirpur.
Introduction: The importance of psychological support for witnesses during war is determined by the need to protect their mental health and, at the same time, collect reliable evidence to bring perpetrators to criminal responsibility. Objective: To evaluate an Integrated Psychosocial Support Model combining Rational Emotive Behavior Therapy (REBT) and Dance Movement Therapy (DMT) to reduce Post-Traumatic Stress Disorder (PTSD) symptoms and improve emotional regulation in war crime witnesses. Methods: The sample was formed from 100 people. The experimental group received the Integrated Psychosocial Support Model, which included the techniques of REBT and DMT, while the control group received standard psychological care. The data were collected using self-report assessment methods at baseline and after the intervention. A mixed-design analysis of variance (ANOVA) was used to test for differences in symptom reduction between groups. Results: Statistical analysis showed significantly greater reductions in core PTSD symptoms, hyperarousal, and dissociation in the experimental group (EG) compared to the control group (CG). The reduction in the average level of dissociation reached 35% in the EG, which is confirmed by a high efficiency indicator (large effect size ηp2 = 0.21). Conclusions: The Integrated Psychosocial Support Model appears to be a promising and contextually appropriate intervention. These findings suggest that implementation in humanitarian and international justice settings may support both mental health recovery and forensic evidence integrity.
Статтю присвячено обґрунтуванню інтегративної моделі взаємодії держави і громадянського суспільства у сфері охорони здоров’я України. Вихідною є теза, що ефективність такої взаємодії визначається не кількістю консультацій або спільних заходів, а здатністю перетворювати суспільні потреби, професійні знання і досвід пацієнтів на обов’язкові для розгляду управлінські сигнали, прозорі рішення та коригування політики. Проаналізовано конституційні гарантії права на охорону здоров’я, законодавство про громадське здоров’я, стратегічні орієнтири розвитку галузі до 2030 року та сучасні підходи до соціальної участі. Запропонована модель охоплює інформаційно-аналітичний, дорадчо-деліберативний, організаційний, сервісний і контрольний контури, між якими встановлюються чіткі права доступу до інформації, процедури представництва, повноваження, строки реагування та механізми підзвітності. Наукова новизна полягає у розмежуванні інтеграції, адміністративного підпорядкування та підміни державних функцій. Громадянське суспільство зберігає автономію, критичну й контрольну роль, тоді як держава несе кінцеву відповідальність за гарантії, стандарти, фінансування та рівний доступ. Результативність моделі запропоновано оцінювати за доступністю допомоги, справедливістю представництва, якістю мотивованої відповіді, усуненням бар’єрів, довірою та фактичним впливом участі на рішення.
Purpose: This study aims to examine how AI-based tools and automated learning analytics influence management processes in higher education institutions to improve the effectiveness of educational management. Design/Methodology/Approach: This is a quantitative study employing a comparative, cross-sectional design with a longitudinal component (2021–2024). Purposive sampling was applied to select three EU countries (Germany, Estonia, Poland) that represent different stages of digital maturity. The sample consists of aggregated statistical data from reports by the OECD and the EUA on national higher education systems, with indicators standardised to a percentage scale (N ≥ 1,000 students per data point). The tool for analysis is the structured data extraction matrix, conceptualised by the author, which focuses the data into three sections: digital infrastructure, educational efficiency, and AI analytics adoption. Results: Data were analysed using descriptive and comparative quantitative analyses (percentage-point changes), trend analysis, and cross-tabulation of indicators by country and year. Research Limitation: The research is limited by reliance on secondary statistical data, suggesting the need for future empirical studies at the institutional level. Findings: The results indicate that increased use of analytical and predictive tools is associated with reduced academic losses and higher program completion rates. The implementation of predictive analytics and early warning systems supports timely managerial interventions and enhances student success. The study confirms that AI adoption facilitates a transition from reactive governance to system-based educational modelling. Practical Implication: The findings justify integrating analytical platforms into university digital processes and strengthening managers’ digital competencies. Social Implication: Effective use of AI contributes to more inclusive, transparent, and sustainable higher education systems. Originality/Value: The originality of this study lies in its management-focused approach, which empirically verifies a positive correlation between digital analytical maturity in HEIs and improved educational outcomes (i.e., dropout and completion rates).
