http://ijaers.com/ Open Access international Journal to publish research paper en-us January This study investigates how the distribution of accountants’ and Sharia Supervisory Board (SSB) akhlaq and professional behavior strengthens good corporate governance in Indonesian Sharia financial institutions. Drawing on a distribution perspective, the study conceptualizes akhlaq as an ethical resource distributed across governance actors rather than as an individual moral attribute. It emphasizes the role of ethical distribution in enhancing accountability, transparency, and Sharia compliance within institutional governance structures. This study adopts a qualitative interpretive approach. Data were collected through in-depth interviews with accountants and SSB members from Indonesian Sharia financial institutions, supported by an analysis of governance documents, ethical guidelines, and Sharia compliance reports. The akhlaq construct is adapted from Islamic ethical frameworks integrating faith (akidah), normative obedience (sharia), and moral consciousness (ihsan). Thematic analysis was used to identify patterns of ethical distribution, professional behavior, and governance mechanisms. The findings show that akhlaq is distributed through formal mechanisms, such as governance structures, standard operating procedures, and supervisory routines, as well as informal mechanisms, including role modeling, ethical deliberation, and moral self-regulation. This distribution shapes professional behavior among accountants and SSB members, strengthening accountability, transparency, and Sharia compliance, and thereby reinforcing good corporate governance. This study contributes to the accounting behavior by extending the concept of distribution to ethical and behavioral dimensions within Sharia governance. It offers a novel perspective on how intangible ethical resources can be systematically distributed to enhance governance quality in Islamic financial institutions. http://ijaers.com/detail/the-distribution-of-accountants-and-sharia-supervisory-board-ssb-akhlaq-and-behavior-in-strengthening-good-corporate-governance-evidence-from-indonesian-sharia-financial-institutions/ Lince Bulutoding, Murtiadi Awaluddin http://ijaers.com/uploads/issue_files/1IJAERS-1220256-TheDistribution.pdf Care Hub is an educational mobile application created to support interactive learning through structured modules, playful activities, and brief daily insights designed to build foundational awareness in self-care and general wellbeing. The present research focuses on reviewing user experience gaps while also considering how previously envisioned development directions, such as broader accessibility, deeper personalization, and community-linked engagement, can be incorporated into a unified enhancement pathway. Core limitations identified within the current design relate to language accessibility, the absence of instructor-oriented support features, and limited avenues for collaborative or peer-driven interaction. These aspects are integrated with forward-looking design intentions to understand how functional improvements can reinforce the app’s educational purpose. The findings indicate that Care Hub already contributes to sustained learner engagement and supports gradual cognitive development, yet several interaction points require strengthening to meet the diverse needs of minority adolescent users. Emerging directions include the addition of localized language interfaces, an educator-accessible progress environment, structured peer challenges, adaptive feedback mechanisms, and analytic tools capable of offering more detailed learning insights. The combined consideration of existing gaps and prospective features positions Care Hub for stronger continuity between its present capabilities and its long-term role in adolescent education. http://ijaers.com/detail/care-hub-educational-app-a-review-of-user-experience-gaps-and-potential-innovations-for-adolescent-learning/ Cao Diem Phan http://ijaers.com/uploads/issue_files/2IJAERS-0120261-CareHub.pdf The Findhorn Ecovillage, founded in 1962 in Scotland, stands as one of the world’s longest-standing community experiments in sustainability, ecological spirituality and social innovation. This article analyzes Findhorn as a micro civilizational process unfolding over time, drawing on Norbert Elias’s process sociology and the Transformative Social Innovation Theory (TSI). A qualitative methodology was adopted—comprised of participant observation, semi-structured interviews and document analysis—allowing the identification of sociocultural and ecosystemic patterns that sustain the community over six decades. Findings indicate enduring practices of cooperation, ethical self-regulation, participatory governance and experiential learning, expressed through four fractal patterns of social innovation: ecological regeneration, solidarity economy, reflexive governance and spirituality as public ethics. These patterns correspond to concrete responses to environmental, social, institutional and symbolic crises. We conclude that Findhorn functions as a civilizational laboratory offering principles with potential for translation to other contexts. http://ijaers.com/detail/social-innovations-and-civilizational-processes-in-the-findhorn-ecovillage-scotland-fractals-for-sustainable-societies-and-responses-to-multiple-contemporary-crises/ Pollyana de Freitas Andrade, Magda de Lima Lucio, Cleoni Virginio da Silveira http://ijaers.com/uploads/issue_files/3IJAERS-1220257-Social.pdf Biometric authentication using Electroencephalogram (EEG) signals is a promising method for secure and unique user identification due to the inherent complexity of brain signals and their variability among individuals. This study introduces a deep learning approach for EEG-based biometric authentication. The proposed method attains elevated classification accuracy by employing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) models on time-series EEG data. We analyze the performance using publicly available datasets such as the PhysioNet EEG Motor Movement/Imagery Dataset and DEAP. The results demonstrate superior accuracy and robustness in comparison to traditional machine learning models. We also did a thorough analysis of 20 related studies to put our work in the context of the present. http://ijaers.com/detail/a-cnn-lstm-based-model-for-eeg-based-biometric-authentication/ Rajesh Rajaan, Mani Butwall, Loveleen Kumar http://ijaers.com/uploads/issue_files/4IJAERS-12202599-ACNN-LSTM.pdf The rapid advancement of artificial intelligence has positioned Machine Learning (ML) as a cornerstone technology across scientific and industrial domains. In parallel, the emergence of quantum computing has catalyzed a new interdisciplinary field—Quantum Machine Learning (QML)—which promises to transcend the computational barriers faced by classical algorithms. This review paper systematically examines the evolution of ML from foundational statistical models to contemporary transformer architectures, and provides a structured analysis of QML paradigms including variational quantum circuits (VQCs), quantum kernel methods, and quantum neural networks (QNNs). Drawing from 95+ peer-reviewed publications indexed in Scopus and Science Citation Index (SCI) journals—with particular emphasis on 2025–2026 publications in IEEE Access, Nature Communications, Nature Computational Science, and Physical Review Letters—we analyze performance benchmarks, identify hardware constraints, and outline algorithmic innovations shaping the near-term quantum advantage landscape. Our findings indicate that while classical ML retains superiority in large-scale perception tasks, QML demonstrates significant advantages in combinatorial optimization and quantum chemistry simulation. Recent 2025 advances in error mitigation on superconducting qubits and improved VQC barren-plateau mitigation are narrowing this gap rapidly. The paper concludes with a forward-looking research agenda covering fault-tolerant QML, hybrid architectures, and quantum NLP. http://ijaers.com/detail/machine-learning-and-quantum-machine-learning-a-comprehensive-review-of-algorithms-applications-and-future-directions/ Loveleen Kumar, Rajesh Rajaan, Nilam Choudhary, Aakriti Sharma http://ijaers.com/uploads/issue_files/5IJAERS-12202591-Machine.pdf