Emerging Science Journal (ESJ)
Not a member yet
960 research outputs found
Sort by
Real-Time FPGA-Based ADAS Solution for Driver Drowsiness Detection and Autonomous Stopping
Full text linkThis study addresses driver drowsiness, a leading cause of traffic accidents, by developing a real-time Advanced Driver Assistance System that integrates biometric detection and autonomous vehicle control. The objective of this study is to enhance road safety through the early detection of drowsiness and automated intervention. The proposed system detects signs of drowsiness by monitoring facial and ocular features using a real-time video stream. Once a predefined threshold is exceeded, an audible alert is triggered. If the driver remains unresponsive, the system gradually reduces the vehicle’s speed and initiates an automated stop procedure. Methodologically, the system employs OpenCV for image processing and a convolutional neural network for lane detection and vehicle control. It is implemented on a high-performance hardware platform using field-programmable gate arrays programmed via Vivado High-Level Synthesis to ensure low-latency operation. The results confirm the system’s real-time capability, accuracy in drowsiness detection, and effective vehicle control under drowsy driving conditions. The system’s novelty lies in its combination of biometric monitoring, deep learning, and hardware acceleration to provide faster and more reliable intervention than existing Advanced Driver Assistance System technologies. This integration sets a new benchmark for proactive road safety measures
The Influence of Work Motivation on Job Performance: Engagement and Burnout as Mediators
No full textBased on self-determination theory, a conceptual model is proposed in which work motivation operates as the antecedent variable, with work engagement and occupational exhaustion acting as dual mediators. To test this framework, data were collected through a structured questionnaire from 469 academic staff members across 24 private higher education colleges in Jiangxi Province and analyzed using structural equation modeling (SEM). The results demonstrate that greater levels of educators' work motivation are significantly correlated with improved job performance and that this effect is channeled through increased work engagement and reduced burnout. By elucidating these mediatory pathways, the findings deepen theoretical comprehension of how motivation drives performance and yield practical guidance for devising effective motivation and performance-management strategies within private higher education institutions
E-Service Quality and Loyalty Driving E-Satisfaction and E-WOM in Higher Education
Full text linkThis study examines the influence of core e-service quality dimensions, information quality, website performance, and website confidentiality, on perceived emotional value, e-satisfaction, student loyalty, and electronic word-of-mouth (e-WOM) within the digital delivery of higher education services in Vietnam. Drawing upon the Stimulus–Organism–Response (SOR) framework, the Expectation–Confirmation Theory (ECT), and the Value-Based Adoption Model (VAM), this research investigates behavioral outcomes through psychological mediators. Data were collected from 311 university students with prior experience in using their universities’ electronic service platforms, including learning and academic management systems. Measurement scales were adapted from established studies, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS–SEM). The results reveal that e-service quality positively influences perceived emotional value, which subsequently drives e-satisfaction, student loyalty, and e-WOM. Furthermore, student loyalty reinforces e-WOM, underscoring the critical role of digital engagement in higher education. This study contributes to existing theory by integrating service quality dimensions, emotional responses, and behavioral intentions into a unified model. It also offers practical insights for enhancing student engagement, optimizing digital learning environments, and strengthening institutional reputation in today’s increasingly competitive digital education landscape
Effect of One-Time Application of Biochar and Compost on Soil and Maize During 5-Time Consecutive Periods of Crop Cultivation
Full text linkThis study evaluates the impact of a single-time biochar application during initial cultivation on the performance of five consecutive crop cycles. The research compares the effects of biochar alone versus biochar combined with soybean compost on maize yield and soil properties over a period of 2.8 years. Fundamental soil properties”including pH, cation exchange capacity, organic matter content, and macronutrient levels”were assessed before each planting cycle and at the end of the fifth cycle. Maize yield and productivity were evaluated based on the number of maize ears, kernel biomass, and both fresh and dry kernel weights. Five experimental plots, each with four replicates, were established with the following treatments: compost applied at 0.56 kg/sq m (TM), cassava stem (CS) biochar applied alone at 2.5 kg/sq m (TB2.5) and 3.0 kg/sq m (TB3.0), and combinations of compost at 0.56 kg/sq m with CS biochar at 2.5 kg/sq m (TMB2.5) and 3.0 kg/sq m (TMB3.0). Results indicated that the sole application of biochar and its combination with compost positively affected soil properties and maize yield. Biochar applications alone significantly improved soil nutrient levels and maize yields compared to the compost alone. Notably, the beneficial effects of biochar on maize and soil were observed from the first cultivation and persisted throughout all five cycles. Based on these findings, it is recommended to apply biochar at 3.0 kg/sq m, in combination with compost at 0.56 kg/sq m, every three crop cycles to sustain nutrient levels and enhance maize yields effectively. Doi: 10.28991/ESJ-2025-09-01-07 Full Text: PD
NOMA Performance Improvement with Downlink Sectorization
Full text linkThis study tackles the growing challenge of inter-user interference in Non-Orthogonal Multiple Access (NOMA) systems, particularly as user density increases in modern communication networks. The primary objective is to improve system performance by implementing a downlink sectorization strategy, which groups users into distinct sectors to manage interference and optimize resource allocation. A Sequential Power Allocation (SePA) algorithm was introduced to enhance power distribution within sectors, aiming to maximize both user capacity and overall sum rate. The methods employed included detailed simulations comparing the performance of traditional NOMA systems and those incorporating sectorization. The results demonstrate that sectorization can significantly boost the system's sum rate by up to 25% and reduce decoding errors by as much as 51%, particularly when the number of users per sector is kept under 20. However, performance saturation occurs beyond this threshold, where additional users do not contribute to further improvements. The novelty of this research lies in applying spatial sectorization to NOMA, showing that spatial sectorization can minimize intra-sector interference, improve power efficiency, and maintain reliable communication in high-demand environments such as the Internet of Things (IoT). This study provides valuable insights for optimizing NOMA systems, crucial for next-generation wireless networks. Doi: 10.28991/ESJ-2025-09-01-017 Full Text: PD
Intelligence Based Controlling Models for Effective Power Tracking and Voltage Enhancement in Grid-PV Systems
Full text linkThe underlying research work is focused on enhancement in the efficiency and voltage gain for solar PV systems with the help of designing a novel regulating framework that includes advanced converter topologies integrated with intelligent control techniques. Optimization in extracting energy from the solar panel at different climatic conditions, voltage gain with minimum losses, and enhancing overall system efficiency and power quality are major tasks to be undertaken. The proposed control architecture presents a new Fractional Order Proportional-Integral-Derivative Control (FOPTC) technique and its adaptation mechanism for correct MPPT under dynamic variations of meteorological conditions. Consequently, it offers improved energy harvesting because it is able to identify the global maximum power point with higher speed and precision than traditional control techniques that apply hybrid approaches. The improved topological structure will ensure a substantial rise in voltage gain and efficiency with reduced voltage and current stresses upon the circuit components. In addition, the idea of a Neuro Feed Quadratic Controller (NFQC) is introduced to generate the regulating pulses for switching components of the converter for optimizing the voltage conversion process. Simulation and analytical studies confirm the higher efficiency, improved voltage gain, and reduced total harmonic distortion in the proposed framework over conventional systems. Doi: 10.28991/ESJ-2025-09-01-015 Full Text: PD
Examining the Impact of R&D Tax Credits on Employment Growth Across Economic Sectors
Full text linkThe present study probes the impact of Research and Development (R&D) tax credits on employment growth in Portugal from 2014 to 2022, particularly on the total employees, R&D staff, and PhD (Doctor of Philosophy) holders across economic activity sectors. Objectives: We aim to assess whether R&D tax credits lead to employment growth, particularly in industries reliant on highly skilled R&D personnel. Methods/Analysis: Using firm-level data from Portugal's R&D survey, we apply a difference-in-differences (DiD) approach with an event study and staggered design for temporal analysis. This methodology, enhanced by a staggered design, allows us to isolate the effects across periods, comparing treated firms with controls within sectors classified by the NACE Rev. 2 system. Findings: Results reveal that R&D tax credits significantly enhance employment for R&D staff, with the information and communication sector having an 18.4% increase and the manufacturing sector rising 12.3%. Novelty/Improvement: Using firm-level data and a staggered DiD design, this study offers granular insights into sectoral variations, underscoring the importance of sector-specific policies. Findings provide valuable guidance for policymakers optimizing and enhancing the R&D tax credits framework to support employment at different levels of expertise and across different economic activity spheres. Doi: 10.28991/ESJ-2025-09-02-010 Full Text: PD
Organizational Internal Factors and Sustainable Performance: A Serial Mediation Model
Full text linkObjective: The present study aims to explore the relationships between big data analytics capability, circular economy practices, and SMEs' sustainable performance in Pakistan. It investigates notable factors determining SMEs' sustainable performance, including employees' perceived usefulness, data-driven culture, and leadership competency mediating the mentioned relationships. Method: The study employs quantitative research based on a positivist philosophy orientation. Data were collected through a structured questionnaire distributed among the employees of 350 SMEs operating in Pakistan's different regions. Findings: The study's results demonstrated the direct effects of big data analytics capability on sustainable performance, employee perceived usefulness, and data-driven culture. Additionally, circular economy practices influence sustainable performance; employee perceived usefulness and leadership competency. Finally, the results highlighted that each relationship is subject to partial mediation, which indicates the role of employee-perceived usefulness and data-driven culture in the relationship between big data analytics and sustainable performance and employee-perceived usefulness associated with the relationship between circular economy practices and sustainable performance. Novelty:The present study highlights that all three of the previous topics are consistent and significantly contribute to the existing literature by providing a model with the main factors that determine SMEs' sustainable performance, which can be sufficient for countries' developing economies. Doi: 10.28991/ESJ-2025-09-01-020 Full Text: PD
Public Service Provisions for Land Resource Planning
Full text linkThis study explored the intricate nexus between public service provision and land use planning, specifically focusing on the conservation of local plant species in Tambon Khao Phanom, Amphoe Khao Phanom, Krabi Province. The research aimed to explore, understand, and analyze Thailand's land use resources, planning, and implementation. This study employed a multi-method research approach to gather an exhaustive set of data and insights. The researcher collected data from documentation research and secondary data sources in this research study. Based on the grounded theory, this research adopts the triangulation method. The data analysis was done using the 5P model and strengths, weaknesses, threats, and opportunities. This multidisciplinary approach integrates the one-map method with the Sustainable Development Goals (SDGs). The findings depict the lack of adequate implementation of government policies and awareness among the landholders, which are required for sustainable community development. This study underscores the critical synergy between public service delivery and land use planning, highlighting their collective potential to advance community well-being and sustainable development. Doi: 10.28991/ESJ-2025-09-01-021 Full Text: PD
Exploring the Spatial Spillovers of Digital Finance on Urban Innovation and Its Synergy with Traditional Finance
Full text linkResearch on the driving role of digital finance in urban innovation is scarce. Most existing literature focuses on whether digital or traditional finance contributes more to innovation, ignoring the spatial spillover effect of digital finance and failing to explore whether digital finance complements traditional finance in promoting innovation. Moreover, current studies focus on the provincial dimension but elaborate very little on the implications of BRI node cities. This study fills in the gaps by focusing on the spatial spillover effects of digital finance on urban innovation and complementary functions of traditional finance. It applies the spatial Durbin model to 26 China BRI node cities from 2013 to 2020. The results indicated that digital finance has a significant positive effect on the innovation level of these cities, suggesting that digital and traditional finance systems are complementary in promoting innovation. Moreover, the evidence of spatial spillover proves that innovations in node cities influence neighboring regions. This paper contributes to the interaction between digital finance and urban innovation with new insights. It also fills the literature gap by underlining the spatial dynamics rather than traditional panel approaches. The results are useful for policymakers in harnessing financial mechanisms for innovation and economic growth. Doi: 10.28991/ESJ-2025-09-01-024 Full Text: PD