All Academic Research: OJS
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Proposed reaction routes of Ethylene-vinyl acetate (EVA)/Thermoplastic Polyurethane (TPU) Blends
Get PDFBlends of ethylene-vinyl acetate (EVA) and thermoplastic polyurethane (TPU) were prepared and their interfacial compatibility was improved with maleic anhydride (MA) by melt blending method. A coarse EVA/TPU blended morphology was turned into finer morphology by MA addition, which was confirmed by scanning electron microscopy (SEM), melt rheology and mechanical behavior. The processing torque of the blends increased with the addition TPU in EVA. Further, this value increased sharply when MA is added in the presence of DCP. The sharp increment of torque indicates a chemical reaction occurs with maleic anhydride with the help of free radical generator species. A possible reaction mechanism is proposed from all experimental results. So a thermodynamically stable and compatible blend of EVA/TPU could be possible by introducing MA and DCP and all these findings are strongly supportive and in favor of the proposed reaction route
ECONOMIC TRANSFORMATION OF DATA ANALYTICS THROUGH AI: EMERGING OPPORTUNITIES AND CHALLENGES IN THE WORKFORCE
Get PDFThe integration of Artificial Intelligence (AI) in data analytics is revolutionizing various industries, driving significant economic transformation, and reshaping the workforce. This study explores the multifaceted impact of AI-driven data analytics, highlighting both the promising opportunities and formidable challenges it presents. Key findings demonstrate that AI significantly enhances data processing capabilities, leading to improved decision-making and operational efficiencies. Furthermore, the emergence of new job roles such as data scientists, AI specialists, and machine learning engineers underscores the demand for specialized skills. However, the rapid adoption of AI also exposes considerable skill gaps in the workforce and raises ethical concerns, particularly regarding data privacy, security, and algorithmic bias. Addressing these challenges requires strategic workforce training, robust governance frameworks for ethical AI practices, and effective change management strategies to overcome resistance to change. By comprehensively addressing these issues, businesses and policymakers can harness the full potential of AI in data analytics, fostering innovation, economic growth, and a smooth transition to an AI-driven economy.
 
STRATEGIC APPROACHES TO LEAN MANUFACTURING IN INDUSTRY 4.0: A COMPREHENSIVE REVIEW STUDY
No full textThis systematic review, based on the analysis of 130 peer-reviewed articles, explores the strategic integration of lean manufacturing with Industry 4.0 technologies, focusing on the role of the Internet of Things (IoT), artificial intelligence (AI), and big data analytics in enhancing lean practices. Using the PRISMA guidelines, the study identified key synergies between lean and Industry 4.0, demonstrating how these technologies facilitate real-time data collection, predictive maintenance, and process optimization, all of which align with lean’s core principles of waste reduction and continuous improvement. The review also highlights significant challenges to this integration, including high implementation costs, workforce skill gaps, and resistance to organizational change, particularly within small and medium-sized enterprises. Additionally, emerging trends suggest that the future of lean-Industry 4.0 integration will increasingly focus on sustainability, with companies leveraging digital tools to enhance energy efficiency and reduce environmental waste. The findings underscore the need for further research to address these challenges and explore scalable solutions that can drive the broader adoption of lean-Industry 4.0 integration in diverse industrial contexts.
 
HARNESSING GROUP THEORY FOR SIMPLIFIED ELECTRIC CIRCUIT ANALYSIS: Group Theory for Simplified Circuit Analysis
No full textElectric circuit analysis is fundamental to advancing modern technology, yet traditional methods often become complex and inefficient when applied to large-scale or intricate networks. Group theory, a branch of abstract algebra renowned for its capacity to exploit symmetry, has shown promise as a solution to this challenge. By applying group theoretical principles to circuit analysis, particularly through symmetry operations and transformation groups, engineers can simplify complex systems, reducing computational demands and revealing deeper insights into circuit behavior. Through systematic symmetry-based simplifications, group theory can decrease the number of equations required by up to 40% in certain configurations, enhancing both analytical efficiency and practical implementation. However, challenges include the mathematical complexity inherent to group theory, the limitations in analyzing highly irregular or nonlinear circuits, and the need for compatible computational tools. Recommendations include the integration of group theoretical approaches into standard circuit analysis software, focused training for electrical engineers, and further research to address the application of these methods in emerging technologies such as quantum and neuromorphic computing. Therefore, this review aims to elucidate the practical potential of group theory in transforming electric circuit analysis, presenting a streamlined approach that balances theoretical rigor with engineering feasibility
LEVERAGING ENTERPRISE ARCHITECTURE FOR DIGITAL TRANSFORMATION: A STRATEGIC APPROACH TO BUSINESS AGILITY
Get PDFThis paper examines the critical role of Enterprise Architecture (EA) in facilitating Digital Transformation (DT) and enhancing business agility. EA serves as a comprehensive framework that aligns IT infrastructure with business processes, enabling organizations to adapt effectively to rapid technological changes and market demands. Through a detailed literature review, the paper highlights key EA frameworks, such as TOGAF and Zachman, and discusses how these frameworks support the alignment of organizational goals with technology initiatives. The analysis reveals that leveraging EA not only improves adaptability and operational efficiency but also minimizes risks associated with digital transformations. Despite the numerous benefits, challenges such as implementation costs, resistance to change, and integration complexity are acknowledged. The paper concludes by offering recommendations for businesses to optimize their EA practices for successful digital transformation and suggesting areas for future research, including the exploration of EA's impact across various industries and the role of leadership in managing digital initiatives
Maintenance-Service-Quality and its Relationship with Satisfaction: A Study of Real Estate Industry in Bangladesh
Get PDFThe real estate sector is one of the fastest growing sectors in Bangladesh. In keeping with rapid population growth in metropolitan cities of the country, the real estate business has stretched itself to cover new boundaries and respond effectively to long-term needs of the mammoth city populace. The costumers of real estate properties (apartments) expect some facilities in exchange of their money. This research has measured the level of customer perception of apartment maintenance-service-quality offered by the real estate companies of Chittagong metropolitan only and the relationship between the two constructs- perception of apartment maintenance-service-quality and user satisfaction. Some recommendations have also been suggested for the apartment builders and developers for improvement of their maintenance-service-quality to ensure better customer satisfaction.
 
Microenterprise- Imperatives, Issues and Interventions
Get PDFMicroenterprise is extremely important to the entrepreneurship development, human development, poverty reduction and employment generation in the overall economy. The specific objective underlies in the provision of resource allocation, infusion of vital potent promoting microenterprise and to peruse socioeconomic patronization for development of the microenterprise. Secondary data is used in this research. For the study, the researchers organized Focus Group Discussions to have a clear conception on the issue. NGO-MFI regular microcredit program (rural credit, urban credit, ultra poor credit, seasonal credit and specialized projects for agriculture, livestock etc.) is providing collateral free individual loan from Tk. 500 to Tk. 25,000. Training of NGO-MFI staffs on loan appraisals, improved lending methodology through ‘credit scoring’ or on the basis of cash flow, minimizing risks for larger loans are needed. Non financial support through focus on clusters with development potential will help support services to be provided more efficiently and economically. It will help to emerge small and medium enterprises out of today’s microenterprises. Development of micro enterprise needs to two-pronged strategy – poverty reduction and employment creation strategy. In most cases, financing interventions did not help clients graduate beyond the reach of part-time self-employment. Entrepreneurship development training is needed for the micro entrepreneurs. Flexible service interventions attaching to the economic condition of the micro entrepreneurs doses input potent to the microenterprises. Most of the micro enterprises demand loan and its availability in time of need.
 
Performance Evaluation-A Comparative Study of Banking Sector in Bangladesh
Get PDFBank is very old institution that contributing toward the development of any economy and treated as an important service industry in modern world. Due to globalization and free market economy, the banking industry is facing severe competition in any country, as its functions are not limited to within the same geographical limit of any country. The overall performance of Bank does not only depend upon the banking industry itself but also on the performance of economy where it is operating. The Banking sector in Bangladesh is different from the banking sector as seen in developed countries and very competitive due to existence of different types of banking. This is one of the major service sectors in Bangladesh economy and can be divided mainly in to four categories- Nationalized Commercial Banks (NCBs), Private Commercial Banks (PCBs), Development Financial Institutions (DFIs) and Foreign Commercial Banks (FCBs). The performance of these banks differs widely within same group and individually. For the purpose of this study, analysis is kept within all these different types of banks.
 
A REVIEW OF IMPLEMENTING AI-POWERED DATA WAREHOUSE SOLUTIONS TO OPTIMIZE BIG DATA MANAGEMENT AND UTILIZATION
Get PDFThis review examines the implementation of AI-powered data warehouse solutions to optimize big data management and utilization, analyzing 25 peer-reviewed articles published over the last decade. As organizations increasingly rely on vast amounts of data for strategic decision-making, traditional data warehousing techniques have struggled to keep pace with the volume, variety, and velocity of modern data. The integration of artificial intelligence (AI) into data warehousing processes has emerged as a critical advancement, enhancing data processing efficiency, accuracy, and scalability. This study synthesizes findings from the literature to highlight key benefits such as automated data extraction, transformation, and loading (ETL) processes, real-time analytics, and improved data quality through advanced cleansing and anomaly detection. Additionally, it identifies significant challenges including data security risks, integration complexities, and the need for specialized skills and substantial investments. The review concludes with recommendations for future research and practical applications, emphasizing the importance of strategic planning and robust security measures to fully leverage AI's potential in revolutionizing data warehousing.
 
FRAUD DETECTION IN FINANCIAL TRANSACTIONS THROUGH DATA SCIENCE FOR REAL-TIME MONITORING AND PREVENTION
Get PDFThis study presents a comprehensive review of the use of advanced technologies in credit card fraud detection, with a focus on machine learning, blockchain, and federated learning, to understand their transformative impact on the field. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 97 articles were systematically reviewed and analyzed. The findings reveal that machine learning models, such as decision trees, support vector machines, and neural networks, have significantly improved fraud detection accuracy, reducing false positives and enhancing the ability to detect complex fraud patterns in real-time. Blockchain technology also plays a critical role by providing a decentralized, secure, and transparent framework for fraud detection, ensuring the integrity of transaction records and making fraudulent activities harder to conceal. Federated learning offers a privacy-preserving solution, enabling institutions to collaborate on fraud detection without sharing sensitive data, which is increasingly important in light of stringent regulatory requirements. Additionally, the study highlights the growing use of predictive analytics in forecasting potential fraud, allowing financial institutions to proactively prevent fraud before it occurs. Moreover, feedback loops integrated into fraud detection models allow for continuous improvement, ensuring that detection systems can adapt to new and evolving fraud tactics. Overall, the review underscores the importance of adopting these advanced technologies to build more secure, efficient, and adaptive fraud detection systems capable of safeguarding financial transactions in the modern digital economy