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Teachers’ Perceptions toward Teaching English in Mixed- Ability classrooms at the Secondary Level of Education in Bangladesh
No full textThis article reports on a qualitative study examining secondary school teachers’ attitudes and perceptions toward teaching English in mixed-ability classrooms in Dhaka, Bangladesh. The study’s primary objective was to identify the challenges English teachers face when instructing students with varying levels of proficiency and to propose strategies for more inclusive and effective teaching practices. Data was collected through semi-structured interviews and classroom observations. Ten English language teachers five from each of two secondary schools were interviewed using open-ended questions, and six classroom observations were conducted, each involving approximately fifty students. The observations aimed to explore teachers’ psychological attributes, tolerance, and adaptive strategies in managing diverse learning needs, as well as patterns of student participation. Thematic analysis revealed key challenges related to differentiated instruction, classroom management, and assessment fairness. However, teachers also demonstrated creativity and resilience in employing learner-centered techniques to foster inclusion. Aligned with SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities), this study highlights the importance of supporting teachers through professional development and policy initiatives that promote inclusive pedagogies and equitable access to English language learning in mixed-ability classroom
A Smart Drone-Based Solution for Natural Disaster Management and Emergency Response
No full textNatural disasters present a major global challenge, often leaving millions in urgent need of aid. Floods disrupt transportation routes, delaying critical relief. As such events intensify, traditional emergency response systems face growing limitations. This research investigates how intelligent unmanned aerial systems (UAS) can enhance disaster response, especially when ground access is compromised. Focusing on flood scenarios, it evaluates how aerial platforms improve situational awareness, speed up search efforts, and enable targeted aid delivery. Using case studies and qualitative analysis, the study finds that UAS can reduce response times by 65–80%, deliver 2–4 kg of medical supplies to isolated areas, and provide detailed damage assessments via advanced imaging. A proposed cloud-integrated architecture connects aerial operations with analytical tools for coordinated emergency management. Despite challenges like limited flight endurance and environmental constraints, the system offers a scalable solution for humanitarian logistics in resource-constrained settings. This work contributes practical insights into deploying aerial technologies for disaster relief and outlines strategies to enhance autonomous capabilities and inter-agency coordination
Tracing the Path from Industry 4.0 to Industry 5.0 through Topic Modeling Analysis
No full textThis study explores the evolution of research from Industry 4.0 to Industry 5.0 using Latent Dirichlet Allocation (LDA) to uncover key research topics and trends. This paper utilizes the Web of Science (WOS) database to collect literature on Industry 4.0 and 5.0 from 2015 to 2024. Through an LDA-based analysis, five key topics were identified, including IoT and automation, adoption frameworks, digital business transformation, smart manufacturing systems, and AI-driven models. The research highlights the growing importance of human-machine collaboration, blockchain security, and sustainable practices in the transition from Industry 4.0 to Industry 5.0. This study contributes to the understanding of evolving industrial research and offers insights into the future direction of industrial innovation
Embedding Concepts of Sustainable Development in Environmental Education
No full textHumans evolved in the realm of nature. During evolution, anthropogenic activities led to an
imbalance of natural ecosystems thereby causing environmental disasters. An increase in population,
rapid industrialization, urban development, and changes in food consumption patterns are major
drivers of environmental degradation. Though these are inevitable as a part of development, the
nexus of environmental degradation and economic growth are directly linked with the conservation
of various environmental compartments including soil, water, air, and biodiversity. Hence,
sustainable development is considered the ultimate goal of the interrelationship of Man and the
environment. In this context, environmental education is the need of the hour in educating society
about the rational use of natural resources and the importance of Sustainable Development. To build
a responsible society, the idea of including environmental education in the broader scope of
education for development is imperative. Therefore, to assess the importance of environmental
education for sustainable development, a perspective on Sustainable Development Goals (SDGs)
from college students is attempted. The major objective of the paper was to assess the sensitization
and dissemination of skills, attitudes, and behavior of the students with respect to Sustainable
Development of Goals in Environmental Education. Methods of environmental education for
sustainable development were imparted to the experimental and control group of students. Results
indicated a significant difference between the groups in terms of environmental education,
perception, and skills of the students from both groups. Further, students who imparted the
knowledge on SDGs in Environmental Education showed more sensitization and perception with
respect to SDGs, especially on water, biodiversity, climate change, poverty & hunger when
compared to the students who were exposed to the conventional teaching methods of environmental
education. Outcomes of the study contribute to the development of new methods of environmental
education for sustainable development among college students
Conducted Electromagnetic Susceptibility Analysis of Chips Based on BCI Method
No full textThe bulk current injection (BCI) technique can simulate electromagnetic interference in the environment coupled with the power or signal cables of electronic devices. It is an important method for studying the conducted electromagnetic susceptibility in electromagnetic compatibility. This paper focuses on the conducted electromagnetic susceptibility of chips using the bulk current injection technique. The bulk current injection probe is integrated with various types of interference signals to design a conducted electromagnetic susceptibility test for chips based on multi-waveform interference. According to the results of the conducted electromagnetic susceptibility test, the susceptibility of integrated circuits to different types of interference signals is analyzed. The effectiveness of the test system is verified through experimental testing and data analysis. The research results show that the bulk current injection test method can accurately assess the conducted electromagnetic susceptibility of chips. It provides valuable references for the design optimization of electronic systems and the improvement of electromagnetic compatibility. This study contributes to improving the reliability of chips in complex electromagnetic environment
A Review of Electromagnetic Safety Protection Technologies
No full textThis paper provides a systematic review and comparative analysis of five pivotal electromagnetic-compatibility (EMC) and safety-protection technologies: the “OODA-loop”-based intelligent protection system, shielding techniques, energy-selective electromagnetic protection, cooperative electromagnetic-security suppression, and electromagnetic-noise jamming. By clarifying their technical principles, applicable scenarios, and current state-of-the-art, the study offers a reference for technology selection under diverse application requirements and for future research directions. A systematic review and analysis of the relevant technical literature and experimental reports was conducted, focusing on the working principles, typical applications, and measured performance of each technology. The results indicate that OODA-loop-based systems offer high automation and rapid response, making them well-suited for facility-wide protection of large-scale infrastructures; shielding techniques are the most mature and lowest-cost solution, hence the most widely deployed; energy-selective protection achieves nanosecond-level adaptive suppression, effectively countering high-power electromagnetic pulses entering through intended apertures, but at higher expense; cooperative suppression technology significantly improves jamming effectiveness and resource utilization through optimized algorithms; and electromagnetic-noise jamming, being mature and straightforward, is mainly employed for low-level information-leakage prevention. Each technology presents distinct advantages and limitations, necessitating judicious selection according to the specific operational scenario. This review compares their application contexts and highlights advantages/limitations
Exploring Drivers of Customer Repurchase Intention: Extending the 7Ps Marketing Mix to Niche Training Services
No full textThis study investigates the marketing mix strategies that influence customer repurchase intentions for niche training programs offered by a private training provider. Such programs, including mandatory safety training, play a critical role in ensuring regulatory compliance, protecting lives and property, and sustaining the long-term revenue of training organizations. Despite this importance, limited research has explored the factors that drive customer loyalty and repeat purchases in this niche service sector. This study aims to fill the gap by analyzing how the seven elements of the marketing mix, namely product, price, promotion, place, people, process and physical evidence, influence repurchase intention. The primary objective is to gain a deeper understanding of the factors shaping customers' repurchase intentions, which is essential for optimizing marketing efforts and increasing program adoption rates. A quantitative research approach was employed, utilizing a structured survey distributed to 217 identified respondents, which yielded 186 valid responses. The descriptive and correlation analyses revealed that product quality, pricing strategies, and service process efficiency are the most significant predictors of repurchase intentions. In contrast, place, people, physical evidence, and promotions were found to have limited impact on repurchase decisions. These findings extend the application of the 7Ps marketing mix by demonstrating its differentiated predictive power in compliance-driven industries, where customers prioritize value, trust, and operational reliability over peripheral marketing efforts. Based on these insights, the study proposes strategic recommendations to strengthen marketing strategies and enhance customers’ likelihood of repurchase. The findings offer both theoretical contributions to the literature on services marketing and practical guidance for organizations aiming to enhance pricing strategies, maintain quality standards, and streamline operations to encourage repurchase intentio
From Crisis to Competitiveness: A Schumpeterian Perspective on Entrepreneurial Orientation and SME Sustainability in Malaysia
No full textSmall and medium-sized enterprises (SMEs) form the backbone of Malaysia’s economy but continue to face high failure rates due to market volatility, resource limitations, and technological disruptions. The COVID-19 crisis further intensified these challenges, exposing structural weaknesses that threaten both performance and survival. While Entrepreneurial Orientation (EO) has long been recognised as a key driver of business success, the effectiveness of its dimensions: innovativeness, proactiveness, and risk-taking, in ensuring post-crisis sustainability remains underexplored from a Schumpeterian perspective. This study investigates the relationship between EO dimensions and firm performance among Malaysian SMEs, focusing on how entrepreneurial behaviour contributes to competitiveness in the aftermath of crisis. Using data analysed through IBM SPSS and AMOS, the results reveal that only risk-taking shows a significant negative effect on firm performance, whereas innovativeness and proactiveness are not significant predictors. These findings suggest that excessive or unmanaged risk may weaken firm resilience in volatile environments, while innovation and proactive strategies may require longer time horizons to yield benefits. By framing the analysis within Schumpeter’s theory of innovation and creative destruction, this study provides empirical insights into how SMEs can transition from crisis to competitiveness. It highlights the importance of balanced entrepreneurial behaviour, where calculated risk-taking, continuous learning, and adaptive strategies are essential for long-term sustainability in uncertain economic conditions
Integrating Digital Intelligence into Transportation Economics Education: A Teaching Reform Based on ADDIE-PBL Framework for Sustainable Development
No full textThe global push toward Sustainable Development Goals (SDGs) demands that transportation education equip students with integrated skills in data analysis and sustainability. Traditional curricula, however, often lack digital intelligence tools and multidimensional (economic-social-environmental) analysis training. This study reformed the Transportation Economics and Analysis course by integrating Virtual Reality (VR), Python, GIS, Tableau, and a blended learning platform within a Project-Based Learning (PBL) framework guided by the ADDIE model. Over 16 weeks, 137 undergraduates (2023 cohort) engaged in real-world projects such as carbon footprint optimization for urban rail transit. Quantitative pre/post assessments showed a 34% improvement in sustainability quantification skills (p<0.01), and qualitative analysis of policy briefs revealed that 89% of students demonstrated advanced ethical reasoning. Comparative analysis with 2022 cohort (n=130) taught under the traditional curriculum confirmed the effectiveness of the reform. The results indicate that digital-pedagogical integration significantly enhances students’ ability to address sustainable transportation challenges, offering a replicable model for engineering education aligned with SDG
A Comprehensive Review of Machine Learning Applications in Wastewater Treatment: Current State, Comparative Analysis, and Future Directions
No full textAs the world’s need for clean water keeps rising and pollution continues to worsen, there is a growing push for better wastewater treatment systems. Treatment plants (WWTPs) are essential not only for protecting public health but also for keeping the environment safe. Still, running these plants is not easy because the quality of incoming water often changes, the biological processes are complex, and regulations are very strict. Traditional methods usually fall short, being slow and inefficient. Newer approaches, like machine learning (ML) and artificial intelligence (AI), bring fresh opportunities by making it possible to predict issues in real time, spot irregularities, improve processes, and support better decision-making. This literature review brings together findings from five key research papers and over 40 additional studies published between 2018 and 2025. The review highlights a significant shift towards advanced deep learning (e.g., LSTM, GRU) and ensemble models, demonstrating superior performance in capturing complex, time-dependent data. Key trends include multi-source data fusion, expanding focus on effluent quality prediction for regulatory compliance, nutrient removal, energy optimization, and predictive maintenance. Despite these advancements, persistent challenges include data quality and availability, model interpretability ("black box" nature), generalizability across diverse WWTPs, and integration with existing infrastructure. Future research directions emphasize hybrid and physics-informed models, Explainable AI (XAI), Digital Twins, Reinforcement Learning for optimal control, and fostering interdisciplinary collaboration. Ultimately, ML/AI holds immense potential to revolutionize wastewater management, transitioning from reactive to proactive strategies, contingent on addressing these critical limitations for widespread and sustainable adoption