European Journal of Science, Innovation and Technology

Academic Background, Engagement, and Self-Efficacy: A Correlational Analysis to Academic Achievement of Pre-service Mathematics Teachers

2025-01-27T15:35:46+02:00

Pre-service mathematics teachers’ academic success is a crucial indicator of effective and competent mathematics educators. Identifying the factors influencing their academic achievement offers valuable insights for teacher preparation programs. This study investigates the interplay between academic background, academic engagement, mathematics self-efficacy, and academic achievement. The study employed a descriptive-correlational research design encompassed 71 pre-service mathematics teachers who participated voluntarily. Findings indicate pre-service teachers had diverse academic backgrounds and held moderate levels of academic achievement, academic engagement, and mathematics self-efficacy. Notably, disparities in mathematics achievement are evident, with male pre-service teachers and those aspiring to specialize in mathematics achieving higher levels. Furthermore, the study underscores a positive correlation between heightened academic engagement, self-efficacy, and enhanced mathematics achievement, underscoring the pivotal role of active engagement and confidence in fostering mathematical proficiency among pre-service teachers.

Feasibility of Radiation Schemes to Predict Extreme Temperature Conditions over Bangladesh

2025-01-30T20:04:06+02:00

An extreme temperature is a weather phenomenon that is distinguished by marked cooling or heating of the air, or with the invasion of very cold or hot air, over a large area. The present study is associated with the simulation of regional climate using the Weather Research and Forecasting (WRF) model that was experimented through 30 different combinations of radiation parameterization schemes over Bangladesh. The intention was to investigate the response to the radiation parameters schemes for dynamic down-scaling of climatic variables. The predicted temperature of 30 different WRF setups were analyzed and compared with the Bangladesh Meteorological Department (BMD) recorded data and were found sensitive to the radiation physics on the basis of Root Mean Square Error (RMSE) at 2-meter air temperature on 02-05 January 2019, 02-05 February 2019 and 28-31 December 2019 for Cold Wave (CW), and 24-27 April 2019, 09-12 May 2019 and 19-22 May 2019 for Heat Wave (HW) at 34 stations over Bangladesh. We conclude that the Rapid Radiative Transfer Model (RRTM) for long wave and Dudhia for short wave schemes are the most appropriate combinations to simulate in the extreme temperature. Using the selected combinations of WRF parameterizations to downscale the extreme weather events, which showed good agreement with the reference data. It was suggested WRF parameters from this study could be utilized for regional climate modeling of Bangladesh.

Quality Health Information for Health Annual Work Plans in Implementing Strategic Plans to Reduce Maternal Morbidity and Mortality, Migori County, Kenya

2025-02-08T20:29:58+02:00

It is important to determine quality of health information for supporting health annual work plans in implementing strategic plans to reduce/prevent maternal morbidity and mortality in the four study health facilities in Migori county; County referral, St Joseph mission, Rongo Sub County referral and Isebania county hospitals. The study used cross-section design. The sample frame population was 260 and the sample size was 155 determined by Cochran method. Data were collected using closed ended questionnaires and were analyzed using statistical package for social scientists (SPSS). The methods of analysis of data were descriptive. Results were presented in charts and percentage tables. In the four facilities data were collected from healthcare workers and analyzed to determine quality of health information to support annual plans in implementing strategic health plans. The study results revealed that the most used system was electronic; 86% at St Joseph mission hospital while Migori county referral hospital was 40%. Routine health information software (RHIS) was most used ranging between 54% and 92%. Then analytic software knowledge among healthcare workers was 28% and electronic health records (EHR) 19%. Achievements in midwifery training were 93%, health information systems 61%, data analytics 28% and data quality improvement training covered 68%, and financial support 17%. The use of electronic health records was highly limited and yet it is key to quality data, information and healthcare services. Therefore, there is high need for investment as county in electronic healthcare systems including healthcare data framework to improve information quality.

Framework for Improving Quality Health Information to Reduce Maternal Morbidity and Mortality in Migori County, Kenya

2025-02-08T20:28:02+02:00

Quality health framework is a reference guide to evaluate and improve healthcare. It provides guidance to health services, on what good quality care entails and how it can be evaluated and demonstrated. Healthcare and quality are complex and highly vary between low and high income countries. Using quality health information reduces maternal morbidity and mortality among healthcare facilities; County referral, St Joseph mission, Rongo Sub County referral and Isebania county hospitals. Therefore, a framework was developed to improve data/ information quality and in turn maternal healthcare. The study used cross-sectional design and the population sample size for the study was 155 healthcare workers. The sample size was determined by Cochran method and closed ended questionnaires were used to collect data. Data analysis used statistical package for social scientists (SPSS), and results were presented in percentages using tables and charts. These data were collected from healthcare workers and analyzed to determine quality of health information to reduce/ prevent maternal morbidity and mortality in Migori County. The study revealed that, the framework can improve quality of data, information and healthcare services. This resulted from data collected and analyzed using basic variables; Agree/ strongly agree achieving 95% for Migori county referral hospital, St Joseph 94%, Rongo subcounty referral hospital 96% and Isebania county hospital 95% and on average coverage was 95%. The frame is good for improving data/ information quality and its implementation is necessary due to its effectiveness.

Enhanced Crude Oil Pipeline Leakage Detection System Using Reinforcement Learning

2025-02-10T19:22:44+02:00

This work used advanced reinforcement learning (RL) techniques to enhance crude oil pipeline leakage detection systems to address the frequent occurrence of undetected or misidentified leaks, which can lead to significant financial losses and safety risks. The existing pipeline monitoring system's performance was analysed, identifying the detection accuracy and response time limitations. Reinforcement learning algorithms were then integrated to optimize the system's ability to detect leaks and minimize false positives. The RL model was trained to enhance its performance through iterative learning and feedback, ultimately improving its accuracy to 100% and increasing precision to 100%. This was achieved by adjusting detection thresholds and refining control actions based on real-time data. When the system detected a pressure drop from 55 psi to 36 psi, reinforcement control measures were successfully implemented to restore pressure to 55 psi. Additionally, a leakage was accurately located at 600 meters along the pipeline, allowing for targeted intervention. The results also demonstrated the impact of flow rate and pressure variations on detection performance, emphasizing the importance of dynamic and responsive control strategies. The integration of RL techniques offers a significant advancement over traditional methods, providing a robust framework for managing pipeline integrity and ensuring environmental safety. This study sets a precedent for future developments in pipeline monitoring and management, advocating for the continuous incorporation of innovative technologies in maintaining infrastructure resilience.

Real-Time Monitoring and Control of Crude Oil Export Pumps

2025-02-10T19:25:42+02:00

This paper is on the application of Model Reference Adaptive Control (MRAC) in optimizing the performance of crude oil export pumps with the goals of improving pump performance, enhancing system reliability, and increasing energy efficiency, by dynamically adjusting operational parameters in response to real-time changes in flow rates and crude oil properties. Manual control was compared to MRAC control, with a focus on error rate and accuracy rate evaluation. The MRAC method was implemented to reduce error rates and enhance control precision. The findings revealed significant improvements in both error and accuracy rates. The efficiency of the manual control is 84.5% while the efficiency of the MRAC is 90%. These results demonstrate the effectiveness of MRAC in optimizing pump operations, enhancing reliability, and reducing energy consumption. This work recommends the integration of MRAC in crude oil export pump systems to ensure sustained performance improvements, operational efficiency, efficient management of energy resources and the reduction of operational anomalies in oil export operations.

Control Process Stability Analysis of a Solid-Liquid Separation System

2025-02-13T17:37:10+02:00

A key performance indicator in any control process is the sustainability of steady state operation for attainment of stability of the applicable control mechanism. In this work, analysis is carried out on the response of a pressure controller with set pressure of 3bar, 7bar and 12bar and the time stability is attained. Pressure is considered as the operating parameter of the control process using a Differential Pressure Cell (DPC) as the controller mechanism. Using a Proportional Integral Derivative (PID) process controller, the performance of a desander was monitored. At 12 bar set point, the result showed that, with PID values of 0.09518, 0.1438/s, 0s, the operation attained stability in 5.53s in the automatic mode, whereas in the manual mode operation, stability was achieved after 7.96s with PID values of 13, 8/s and 7s manually selected. At 7bar set point, stability was attained in 4.7s with PID values of 1.076, 0.87798/s, 0.19657s in automatic mode whereas in manual mode the system stabilized in 4.79s with PID values of 7, 9/s, 5s. At 3bar set point, the controller gain stability in 5.19s, with PID values of 1.3608, 1.0562, 0.41093s in automatic mode whereas in manual mode, stability was attained in 12.5s with PID values of 12, 8/s, 5s respectively.

Vote Buying and the Integrity of 2019 and 2023 General Elections in Nigeria

2025-02-14T12:46:17+02:00

Vote buying is a persistent challenge that has undermined the integrity of elections in Nigeria. It is a practice where political actors offer material inducements, such as cash, food, or other gifts, in exchange for votes. This practice subverts the principles of free and fair elections by distorting the electorate's will and compromising the democratic process. This study examines the impact of vote buying on the Integrity of 2019 and 2023 in Nigerian General Elections. The study utilized the Principal-Agent Theory as the theoretical framework and secondary data were sourced from textbooks, journal articles, newspaper, government reports. The collected data were analyzed with content analysis and the findings revealed that the widespread vote buying in 2019 and 2023 distorted and compromised the election integrity. It was also revealed that the persistent vote buying in the 2019 and 2023 general elections has contributed to low voter turnout and further erosion of public trust in the electoral process. The study concluded that the widespread prevalence of vote buying has distorted the electoral process, eroded public trust, concentrated political power, and perpetuated the status quo, with long-term implications for democratic consolidation. The study therefore made the following recommendations: (1) enacting robust legislation that clearly defines and prohibits vote buying, with stringent penalties for offenders, (2) adopting biometric voter registration and identification systems to enhance the integrity of the voter roll and reduce the potential for vote buying, and (3) implementing comprehensive civic and voter education programs to raise awareness among citizens about the negative impacts of vote buying on the democratic process.

Factors Affecting the Operational Efficiency of Commercial Banks in Bac Giang, Vietnam

2025-02-23T14:32:08+02:00

This study investigates the factors affecting the operational efficiency of commercial banks in Bac Giang, Vietnam. Data was collected from a survey of 400 bank employees and managers in Bac Giang. The study employs the Exploratory Factor Analysis (EFA) method to identify key factors influencing bank efficiency and regression analysis to examine the relationship between these factors and bank performance. Five independent variables are considered: management capacity, financial capacity, technological capacity, service quality, and competitive environment, and the dependent variable is operational efficiency. The findings reveal that all five independent variables have a significant positive impact on banks’ operational efficiency. The study provides valuable insights for bank managers and policymakers in Bac Giang to improve the performance of commercial banks.

Exploring Emerging Tech and Challenges in 5G Development: Seeking Solutions for Future Wireless Communication Systems

2025-02-25T22:21:44+02:00

Advancements in wireless communication technology are pivotal in shaping the modern landscape of connectivity, with 5G serving as a central focus of these developments. The integration of cutting-edge technologies such as the Internet of Things (IoT) and artificial intelligence is driving unprecedented capacities for data transfer, enabling a multitude of applications across various sectors, from healthcare to smart cities. However, these enhancements come with their own set of challenges, including cybersecurity threats and the need for robust infrastructure. Addressing these issues requires a comprehensive understanding of existing communication frameworks and emerging technologies, as well as innovative solutions that prioritize both performance and security. For instance, the various communication modes illustrated in the image referencing, such as Vehicle-to-Pedestrian (V2P) and Vehicle-to-Vehicle (V2V), exemplify the multifaceted nature of interconnected systems that can be facilitated by advanced 5G networks, thereby reinforcing the critical importance of developing resilient communication strategies.

Design of a Gas Turbine for the Conversion of Flare Gases to Energy Using Aspen HYSYS: A Case Study of an Oil Field in Niger Delta

2025-03-07T12:20:09+02:00

Gas flaring is among the main issues being discussed in the oil and gas industry for decades now. The present study is motivated by concerns over the environmental impact associated with gas flaring activities in the industries and the economic waste. The case study selected was from an oil mining lease in Nigeria. A total volume of gas flared daily for a period of June, July and August, 2022 along with the analyzed composition of the flare gas was collected. The volume of gas flared daily was estimated as 13,000 Sm³ per day which is equivalent to 542 m³/h flowrate. The combined cycle energy plant (gas turbine-steam turbine systems) simulation carried out in Aspen HYSYS v.10 using Peng-Robinson fluid package, a 98.61% removal of CO₂, H₂S and other heavier hydrocarbons in the flare gas was achieved in the flare gas absorber and separator units. The net energy output from the combined turbine plant was found to be 346.5MW of electricity daily; this is sufficient enough to power Port Harcourt city. Estimation of the total capital and operating costs was performed using Aspen Process Economic Analyzer (APEA), total capital cost of 67,907,300 USD, total operating cost of 19,345,800 USD/Year, total utilities cost of 14,247,500 USD/Year, equipment cost of 45,097,500 USD, and total installation cost of 48,724,000 USD. This shows that the model used in this work can solve the problem of gas flaring in an oil mining lease in Niger Delta.

Effect of Present Bias on Dropout Among Higher Secondary Children in Tribal and Urban Region in Maharashtra

2025-03-07T12:23:21+02:00

Leaving higher secondary education has lasting impact on not just the individual but also on the society and economy at large. With government’s efforts the enrolment rate has increased but the transition rate is still considerably low at higher secondary education in India. This creates a persisting skill gap in the country. The present article is a novel attempt to understand the behavioural factors associated with dropping out. The study is based on primary survey conducted in Pune city and Tribal area of Mahad in Maharashtra among children between 16-20 years of age. The study captures the impact of present bias/ delay discounting, a cognitive bias, along with socio-economic and demographic variables. Employing cluster analysis and multivariate analysis it was highlighted that children with low present bias behaviour are 4 times less likely to dropout from school and children with higher standard of living index are 4 percent less likely to dropout. It was also found that boys are more likely to leave school, additionally, age is a significant determinant of dropping out. It was further elicited that SLI, and education of parents and siblings significantly impacts present bias/ delay discounting behaviour among children. The findings imply that low-cost nudges such as commitment devices, inculcating positive identities and emphasising long run benefits of education can overcome present bias among children thereby increasing their education progression.

Development of a Maintenance Strategy for Centrifugal Pumps

2025-03-07T12:43:48+02:00

In this work, a maintenance strategy was developed for centrifugal pumps. The strategy involves running the centrifugal pump for a predetermined period and the mechanical seal is taken out for maintenance and reused. The period of first usage of the mechanical seal depends on the level of debris in the fluid (low level, medium level and high level). The centrifugal pumps of an oil multinational company based in Rivers state was used as a case study. The cost implications of the existing maintenance strategy and the developed maintenance strategy were evaluated and compared. Selected reliability-centred maintenance tools were also applied to assess the level of criticality of the various components. It was observed that the impeller, the mechanical seal and the shaft are the most critical components of the centrifugal pump with relative criticality values of 16.80, 15.08 and 13.35 respectively. In applying the new maintenance strategy, it is possible to run the centrifugal pump for up to 11 days, 8 days and 5 days respectively for the three different cases of fluid before the mechanical seal is reused. Reused mechanical seals on the average can run to failure in 9 days, 7 days and 4.5 days respectively. Applying the new maintenance strategy leads to reduction in maintenance cost of the mechanical seal between N13.6 million to N24.4 million annually. The developed maintenance strategy can be applied to other devices which has components that fail often.

The Impact of AI Explainability on Cognitive Dissonance and Trust in Human-AI Recruitment Teams

2025-03-07T17:30:51+02:00

This study examined how varying levels of AI explainability affect trust and cognitive dissonance within human-AI teams, focusing on collaborative recruitment scenarios. The results indicate a complex interplay: while no significant differences were observed between the high-explainability and no-explainability conditions, low explainability led to a statistically significant increase in cognitive dissonance. This finding suggests that partial explanations may exacerbate rather than mitigate uncertainty, possibly due to confirmation bias, where users selectively interpret incomplete information to align with pre-existing beliefs. In such cases, explanations may provide enough detail to provoke skepticism but insufficient justification to resolve doubts, leaving users conflicted between their intuition and the AI's suggestions. These results highlight the need to prioritize explanation quality and completeness over sheer detail when designing XAI systems for collaboration.

Patent Stability and Current Technological Trend of Asynchronously Communicated Gendered Communicative Pattern Patent: Unfiltered Fieldwork Discourse Analysis

2025-03-07T17:34:02+02:00

In a time when computer technology can be used to prevent "built-in natural communication", communication transmission is directly being damaged via the "insertion installation" of "communicative taboo objects" that cause the intentional professional ruin of people for whom communication is a working tool, imposing the obsolescence of asynchronous communication as primary and essential. Asynchrony as a time lag in a communicative performance, the very equivalent to gender-conditioned redaction, could be seen as the only solution to cyberbullying communicative issue because the problem of "synchronous interference" in the conception of discourse does not necessarily have to be visible in the asynchronously delivered communicative act usually performed via its written result markers. The paper is conceived as an attempt to present the timelessness of a professionally needed asynchronous communication pattern. The patent originality of the asynchronicity research itself is a gender-edited communicative phenomenon need derived as a social communicative consequence that urges asynchronously conscious communicative practice. Humanoid, manually processed corpora analysis methodology practice of the study as a current rarity enables descriptive innovation conditions and depicts the daily communicative needs via descriptive, schematically evaluated discourse elements, and unfiltered discourse analysis results are reassuringly accompanied with a cumulative statistical method. The problem of structurally unintentionally imposed aftermath of socially derived communicatively necessary gendered language is being presented via an introductory discussion insight into the current mainly cyberbullying issue of interpreting structuralism in linguistics, poststructuralist and gender variation, the need for interdisciplinarity and the classification of asynchronous as a socially conditioned patent result of variation in the aftermath of linguistic asynchrony, cyberbullying and social-communicative anxiety via the territorially researched unfiltered discourse sample.

Resolving Human Concerns about AI and Technology with Non-Axiomatic Reasoning Systems

2025-03-19T19:00:33+02:00

This article discusses some of the challenges humanity experiences with modern technologies and argues some potential ways to address these challenges with AI. The challenges include our lack of access to the technologies, lack of trust in technologies, inadequate understanding of why these technologies behave as they do, and inequalities related to technology. We discuss how the non-axiomatic reasoning system (NARS), an AI model capable of general-purpose reasoning, can provide solutions to these issues in a trustworthy and explainable way.

Strategies for Accessible Learning and Differentiation in Middle Eastern Primary Schools

2025-03-24T17:47:43+02:00

Over the past few years, the governments and other stakeholders have woken up to the challenge of providing quality education to all the students, especially the students in the primary schools in the Middle East. The populations in the region are as a result, culturally, linguistically and socio-economically diverse. These approaches of learning are very significant in the current learning arena since every child is unique in his or her ability, language, or cultural background. This paper aims to examine the approaches in the Middle Eastern primary schools to enhance basic education’s inclusively for all children who need different support and attention. Through exploring the notions of universal design of learning and differentiation, as well as early field experiences of using these concepts in the classroom, this present paper seeks to offer an understanding of the difficulties and accomplishments of developing inclusion of learning environments. Recommendations are provided for educators, policy makers, and school leaders to continue enhancing educational opportunities for all and address any student’s needs more effectively in the region. Given the current trends towards inclusion and equity in education policies at the international level, this paper is evidence of a continuous discussion on the enhancement of provision of education for all children with special attention to the Middle Eastern environments (Booth & Ainscow, 2011).

Factors Influencing Smallholder Farmers’ Intention to Implement Food Safety Standards in Agricultural Production: A Case Study of Lam Dong Province, Vietnam

2025-03-25T18:51:13+02:00

This study aims to analyze the factors influencing farmers' intentions to adopt food safety standards in agricultural production in Lam Dong Province. The research integrates the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) with additional variables to explore farmers' behavioral intentions. Data was gathered through direct interviews with 618 smallholder farmers using a structured questionnaire. Results from the structural model indicate factors influencing farmers' intention to adopt food safety standards: perceived behavioral control, attitude, and subjective norms. These factors explained 58.6% of the variance in the intention of farmers to adopt food safety standards. These findings provide valuable insights for policymakers and stakeholders seeking to enhance farmers' willingness to implement food safety standards.

Assessing Thermal Climate and Key Climatic Factors Influenced by Solar Radiation in the Niger Delta

2025-03-25T18:50:55+02:00

The Niger Delta, a critical ecological zone in Nigeria, faces significant environmental challenges due to its complex network of creeks, rivers, and mangrove swamps. Among these challenges, the thermal climate—characterized by temperature variations and influenced by climatic factors—plays a pivotal role in the region's environmental health, agricultural productivity, and human well-being. This study employs a longitudinal correlational research design to assess thermal climate patterns and the influence of solar radiation on key climatic factors in the Niger Delta over an extended period (2014-2023). The analysis reveals that surface air temperatures across the region consistently range from approximately 24°C to 27°C, reflecting the region's tropical climate. Variations in temperature extremes among the states are evident, with Delta and Cross River experiencing minimum temperatures of 24.4°C and 24.1°C, respectively, while Edo and Ondo record maximum temperatures of 27.9°C and 27.3°C. These variations are influenced by local factors such as elevation, air pollution levels, proximity to water bodies, and vegetation cover, which play a critical role in temperature regulation. The mean surface air temperature across the states shows a relatively consistent range between 25.5°C and 26.3°C, while the standard deviation indicates varying degrees of temperature variability. The Mann-Kendall test for surface air temperature trends across the region reveals predominantly positive tau values, indicating an overall increasing temperature trend. However, statistical significance varies across states, with some regions, like Cross River, showing significant warming trends, while others do not, suggesting the impact of localized environmental and land use factors on temperature dynamics. This study provides a comprehensive analysis of the thermal climate in the Niger Delta, highlighting the region's consistent warmth and the importance of understanding local variations for climate adaptation and resilience planning. The findings have significant implications for agriculture, energy, and public health, emphasizing the need for tailored climate mitigation and adaptation strategies that address the unique climatic conditions of each state within the Niger Delta.

Long Term Electricity Demand Forecasting in Nigeria

2025-03-28T15:56:25+02:00

This study focuses on forecasting long-term electricity demand in Nigeria using three distinct methods: Nonlinear Autoregressive with Exogenous Input Neural Network (NARX), Support Vector Regression (SVR), and Exponential Smoothing - Holt Winters (ES-HW). Over eight years of data from the National Control Centre were utilized to develop and compare these models. The ES-HW model, despite its reliance on limited input data, demonstrated ability to replicate the seasonal patterns and trends in electricity demand, even though it resulted in a higher relative root mean square error (RRMSE) than the other method. While SVR showed slightly better performance metrics, ES-HW provided a more accurate depiction of demand fluctuations over time. The study identified key insights, such as the critical impact of data availability on forecasting accuracy and the comparative effectiveness of different modeling approaches. The research highlights the challenges posed by limited historical data in the Nigerian electricity sector, which constrained the accuracy and scope of the forecasts. Overall, this work contributes valuable knowledge to energy modeling and policy-making, offering a foundation for sustainable energy planning in Nigeria.

Effect of Interdisciplinary Collaboration on Effectiveness of Mental Health Counselling on Depressed Patients in Yenagoa Metopolis, Bayelsa State, Nigeria

2025-03-30T14:12:55+03:00

The study evaluates the effect of interdisciplinary collaboration on effectiveness of mental health counselling on depressed patients in Yenagoa metopolis, Bayelsa State, Nigeria. The objectives of the study included to evaluate the effect of interdisciplinary collaboration on effectiveness of mental health counselling on depressed patients and to find out the differential effect of the effectiveness of mental health counselling on male and female patients in Yenagoa Metopolis, Bayelsa State, Nigeria. Two research questions and two hypotheses tested at 0.05 significant level guided the study. Sample comprised of 30 patients diagnosed with depression drawn through purposive sampling technique. Three stages were used in collecting data: pre-treatment, treatment and post-treatment. Quasi-experimental design was adopted for the study. Two instruments were used, namely, the Patient Health Questionnaire–9 (PHQ-9) developed by Spitzer et al. (1999) and Mental Health Inventory-18 (MHI) by Veit & Ware (1983). Reliability of the instruments was established through test-retest; coefficients obtained were 0.82 and 0.78 for PHQ-9 and MHI-18 respectively confirming the instruments reliability for use in the study. The data were analyzed using mean and standard deviation while the hypotheses were tested using t-test statistics. Results obtained revealed that interdisciplinary collaboration has effect on effectiveness of mental health counselling on depressed patients and that there was significant differential effect of the effectiveness of mental health counselling on male and female patients in Yenagoa Metopolis, Bayelsa State, Nigeria. Based on the findings of the study, it was recommended that government and educational institutions should provide support in form of sponsorship grants for interdisciplinary collaboration amongst researchers and that counselling support centres should be provided by the State government manned by professional counsellors to provide psycho-social support for clients needing help.

Revolutionizing Forestry with AI GPS and Space Technologies for Sustainable Management

2025-03-30T14:24:44+03:00

Forests play a crucial role in maintaining ecological balance, yet they face growing threats from deforestation, climate change, and illegal logging. Traditional forestry management methods often lack the speed and accuracy required for effective conservation and resource utilization. The integration of artificial intelligence (AI), GPS technology, and space-based monitoring has revolutionized forestry, enabling more precise and efficient management strategies. AI-driven machine learning models analyze vast datasets from satellites, drones, and ground sensors to detect deforestation patterns, predict wildfires, and assess forest health. GPS technology enhances real-time tracking of tree cover, wildlife movement, and illegal logging activities, providing valuable geospatial insights for policymakers and conservationists. Meanwhile, space-based technologies, such as satellite remote sensing, offer high-resolution imagery and spectral analysis for monitoring carbon sequestration, biomass density, and ecosystem changes on a global scale. The synergy of AI, GPS, and space technologies enables data-driven decision-making, improving forest sustainability while mitigating environmental risks. This paper explores the transformative impact of these technologies in forestry, emphasizing their applications, challenges, and future potential in fostering sustainable forest management and climate resilience.

The Impact of Tariff Policies on Global Trade: Challenges and Opportunities

2025-03-30T14:27:22+03:00

Tariff policies play a crucial role in shaping global trade dynamics, influencing economic growth, market competitiveness, and international relations. While tariffs are often implemented to protect domestic industries, generate government revenue, and address trade imbalances, they can also lead to unintended economic consequences, such as retaliatory measures, supply chain disruptions, and increased consumer prices. This paper explores the impact of tariff policies on global trade, analyzing both the challenges and opportunities they present. It examines historical and contemporary tariff policies, their effects on key industries, and the role of international trade agreements in mitigating conflicts. Additionally, the study highlights strategies that businesses and policymakers can adopt to navigate the complexities of tariff regulations while promoting sustainable and inclusive trade practices. Through a comprehensive review of economic data and policy frameworks, this paper aims to provide insights into the evolving landscape of global trade and the future of tariff implementations in an increasingly interconnected world.