globusjournal

Border management is vital for protecting a nation’s territorial integrity and maintaining internal security. In India, significant reforms have been introduced in recent years – particularly under the Modi government – to modernize and secure the country’s vast and sensitive borders. These reforms include the development of physical infrastructure like roads and border outposts, the adoption of advanced technologies such as drones and smart fencing, and various policy-level changes aimed at improving efficiency and responsiveness. However, despite these advancements, challenges remain – especially in areas like personnel training, cyber security, and coordination between multiple security agencies. This paper explores both the progress made and the gaps that persist, ultimately recommending a holistic approach that integrates modern technology, skilled human resources, and effective governance to build a more robust and future-ready border management system.

Keywords: Border Management, Infrastructure, Cyber security, Training, Surveillance, Policy Reforms, India, Modi Government.

This research integrates numerical modeling techniques and statistical analysis to study ocean wave dynamics in the Atlantic Ocean. Key steps include deriving the one-dimensional wave equation, incorporating fluid properties, and applying statistical methods to analyze wave height distributions. The final equation combines fluid properties with the cumulative distribution function to estimate the probability of extreme wave events. This research contributes to understanding wave behavior and its implications for coastal engineering and climate studies.

Keywords: Numerical Modeling Techniques, Ocean Wave Dynamics, Atlantic Ocean, Wave Equation, Fluid.

The integration of Multi-Agent Systems (MAS) with Digital Twins (DTs) has emerged as a transformative strategy for dynamic scheduling challenges in discrete manufacturing. This review systematically explores architectures, integration factors, technological enablers, and research gaps. Through a comprehensive analysis of 70+ studies from 2016 to 2024, we categorize integration frameworks, compare scheduling strategies, and highlight critical success factors. Findings suggest that interoperability, real-time data synchronization, intelligent agent autonomy, system scalability, and security are decisive in successful MAS-DT deployment. Future pathways for industrial adoption are outlined. This paper offers an advanced synthesis for researchers and practitioners aiming to build intelligent, resilient manufacturing scheduling systems.

Keywords: Digital Twin, Multi-Agent Systems, Dynamic Scheduling, Discrete Manufacturing, Intelligent Manufacturing, Cyber-Physical Systems.

Digital tax platforms have emerged as a transformative tool in modern tax administration, significantly influencing voluntary tax compliance among taxpayers. This study examines how the adoption of digital tax systems affects compliance behavior by improving accessibility, transparency, and efficiency in tax processes. The research focuses on key factors such as ease of use, system reliability, awareness, and institutional support in shaping taxpayers’ willingness to comply voluntarily. The study indicates that digital tax platforms significantly enhance voluntary compliance by simplifying filing procedures, reducing errors through automation, and providing real-time access to tax information. Increased transparency and reduced human interaction minimize opportunities for corruption and build trust in the tax system. The study also highlights that awareness and institutional support strengthen the effectiveness of digital platforms by enabling users to utilize these systems more efficiently. The research contributes to the existing literature by providing empirical evidence on the role of digitalization in promoting voluntary compliance. It offers practical implications for policymakers and tax authorities to improve digital infrastructure, enhance user education, and strengthen support systems. Digital tax platforms are found to be a crucial factor in fostering a more compliant, transparent, and efficient tax environment.

Keywords: Digital Tax Platforms, Voluntary Tax Compliance, E-Governance, Digitalization, Tax Administration, SMEs, Transparency, Structural Equation Modeling.

Post-harvest losses represent a major challenge in the agricultural sector, particularly in developing economies where inefficiencies in supply chain management, storage infrastructure, and demand forecasting contribute to significant food wastage. A considerable portion of agricultural produce deteriorates before reaching consumers due to inaccurate demand estimation, poor inventory planning, and inefficient distribution systems. In recent years, Artificial Intelligence (AI) has emerged as a powerful technological solution capable of improving demand forecasting and optimizing decision-making processes within agri-business supply chains. This study examines the role of AI-driven demand forecasting systems in reducing post-harvest losses in agri-business. AI technologies such as machine learning, predictive analytics, and big data processing enable the analysis of large datasets related to market demand, seasonal consumption patterns, weather conditions, and consumer behavior. These technologies provide more accurate demand predictions, allowing farmers, distributors, and retailers to align production, storage, and distribution strategies with actual market requirements. As a result, overproduction, excess inventory, and spoilage of perishable agricultural products can be significantly minimized. AI-based forecasting systems support better coordination among supply chain stakeholders and improve overall operational efficiency. The integration of AI into agri-business forecasting practices therefore offers a promising pathway toward reducing post-harvest losses, improving supply chain resilience, and promoting sustainable agricultural development.

Keywords: Artificial Intelligence, Demand Forecasting, Post-Harvest Losses, Agri-Business, Predictive Analytics, Supply Chain Optimization, Smart Agriculture, Food Waste Reduction.

Background: The increasing need for the effective and technology-based healthcare has resulted in the expanded use of the wearable health devices in healthcare facilities. The devices, which monitor the vital signs and health data in real time, have demonstrated a potential to improve the patient outcomes, facilitate early diagnosis, and lower the hospital readmission. Their effectiveness, however, depends on the nurses’ willingness and capacity to adopt them into a routine practice. Considerations like the user-friendliness, compatibility with hospital systems, and the existence of adequate training have a large impact on the adoption. Nurses as frontline providers hold the key to ensuring the greatest possible potential for wearable technology and therefore must have their challenges and facilitators considered when implementing it.

Methods: The study utilized a descriptive-correlational quantitative approach, collecting responses from 200 nurses through structured questionnaires distributed via Google Forms. The survey focused on understanding nurses’ perspectives regarding wearable health devices, particularly their impact on patient care, clinical decision-making, and the efficiency of daily workflow.

Result: The results are that the nurses tend to have a favorable view of the wearable health devices, specifically the usability, integration into the systems, and worth of training. They see these tools as valuable for enhancing patient care and workflow efficiency. There are issues, such as limited availability in the work environment and complexity in integrating devices into the everyday tasks. Despite these barriers, nurses also indicate a very high intention to accept wearable technology, particularly where there is backed up continuous education, peer instruction, and corporate investment. The overall study shows the potential along with practical need needed to establish complete wearable health devices in medical care.

Conclusion: The study emphasizes that the successful adoption of wearable health devices by nurses depends on user-friendly design, effective system integration, and continuous training. While nurses acknowledge the benefits of these technologies in enhancing patient care and workflow, addressing barriers such as accessibility and workflow compatibility is essential. Strengthening support in these areas can lead to more effective use and greater acceptance of wearable health devices in healthcare settings.

Keywords: Wearable Health Device, Implementation, Balancing Usability, System Integration, Effective Training, Healthcare Setting.

Background: Digital health innovations, including artificial intelligence (AI), electronic health records (EHRs), and digital patient monitoring, are reshaping healthcare delivery by improving efficiency, diagnostic accuracy, and patient outcomes. Understanding healthcare professionals’ perceptions of these tools is essential for effective adoption and sustainability.

Objective: This study aimed to examine healthcare professionals’ perceptions of digital health tools across three domains: (1) AI and telehealth use, (2) EHR implementation, and (3) digital patient monitoring.

Methods: A quantitative-descriptive research design was employed using a structured survey distributed to healthcare professionals in varied clinical settings. The instrument consisted of 15 items grouped into three categories, each rated on a five-point Likert scale. Descriptive statistics, including mean and standard deviation, were used to analyze responses, while verbal interpretations contextualized the findings.

Results: Findings revealed that respondents strongly agreed with the positive contributions of digital health tools across all categories. For AI and telehealth use, the highest-rated items included the role of digital tools in improving telehealth quality (M = 4.55, SD = 0.50) and supporting decision-making (M = 4.55, SD = 0.50). Regarding EHR implementation, participants strongly agreed that digital tools facilitated easy access to patient records (M = 4.54, SD = 0.50) and streamlined documentation (M = 4.50, SD = 0.50). For digital patient monitoring, the strongest agreement was observed in improving patient monitoring (M = 4.55, SD = 0.50) and facilitating continuous care without in-person visits (M = 4.54, SD = 0.50). Category means were consistently high: AI and telehealth (M = 4.50), EHR implementation (M = 4.46), and digital monitoring (M = 4.49).

Conclusion: The study concludes that healthcare professionals strongly perceive digital health tools as beneficial in enhancing AI-driven telehealth, EHR efficiency, and patient monitoring. These findings support the broader integration of digital innovations in healthcare systems to promote quality, safety, and accessibility of care.

Keywords: Digital Health, Artificial Intelligence, Telehealth, Electronic Health Records, Patient Monitoring, Healthcare Innovation.

The 21st century has introduced unprecedented challenges and opportunities for educational leaders who must navigate complex learning environments, diverse student populations, and rapidly evolving technologies. Artificial Intelligence (AI) has emerged as a transformative tool in education, enabling leaders to adopt data-driven strategies for effective decision-making, instructional innovation, and school management. This article explores the role of AI in enhancing data-driven educational leadership, highlighting its applications in predictive analytics, student performance tracking, resource allocation, and administrative efficiency. Drawing upon theories of educational leadership and recent advancements in AI, the study emphasizes how AI technologies reshape leadership practices to promote equity, efficiency, and school effectiveness. Challenges, ethical implications, and future directions are also discussed. The findings suggest that while AI cannot replace human leadership, it serves as a powerful ally, offering evidence-based insights that strengthen the decision-making capabilities of educational leaders in the digital era.

Keywords: Artificial Intelligence, Educational Leadership, Data-Driven Decision Making, School Effectiveness, 21st Century Education.

The researcher always aims at the concept of measuring the financial condition every year. But after a pandemic situation, finding the impact and evaluating the progress of financial development is important. Understanding economic growth and changes in poverty is necessary for future developments. The financial condition earlier plays a minor role in the process of economic growth. But after the pandemic, it is necessary to develop the financial condition of the individual and also the family. As students also started working as their education took place through its online mode. The financial institutions (bank and insurance companies) and financial markets are influenced by economic development, economic stability. The primary data collected and analyzed using the chi-square test.

Keywords: Financial Development, Pandemic Situation, Education, Chi-Square Test.

Work life balance is giving quality time to both family and work. Many of the women faces this challenge while they have to juggle between family and work. In a male dominated society where most people think that household work is women responsibility, it becomes very difficult to balance between work and family. This paper attempts to study some aspects of work life balance of women. Many multinational companies across the globe have given work from home facilities and flexi time to the employees. Companies like google has rooms to take rest, laundry facilities and they provide good food to the employees within the company which saves lot of time in household chores thereby enabling the woman to give quality time to spouse and children.

Keywords: Work life balance, Women, Employees, Pandemic, Covid-19.