Emerging Science Journal (ESJ)
Not a member yet
960 research outputs found
Sort by
Assessing the State of Modern Physics Education: Pre-test Findings and Influencing Factors
Get PDFTechnology and our conceptions of reality have both been significantly impacted by modern physics. However, due to a variety of issues, such as disparities in educational resources, differing emphasis on science education, cultural attitudes, and language obstacles, students in Latin America, including Ecuador, have a limited understanding of modern physics. The present work exposes a pre-test methodology to evaluate students' knowledge and pinpoint their areas of weakness. The analysis of the results indicates that most students received lower grades, while a smaller proportion obtained higher scores. Our findings reveal significant knowledge gaps, misconceptions, and uncertainty among the participants regarding various topics related to the constituent and stability of the nucleus, quantum behavior, nuclear models, radioactive decay, and natural radioactive sources. Additionally, it was statistically demonstrated (Kruskal-Wallis H test) that misconceptions, uncertainties, and knowledge gaps are not significantly related to learning styles. The type of college substantially impacts academics, with private university students typically receiving higher grades. These results offer insightful information about student performance, how learning styles and college types affect academic achievement in modern physics, and the effects of living area and academic level. Doi: 10.28991/ESJ-2024-SIED1-01 Full Text: PD
Product Design Cost Estimation for Make-to-Order Industry: A Machine Learning Approach
Get PDFThis research addresses the need for accurate design cost estimation in the Make-To-Order (MTO) industry. The complexity of product customization is key to differentiation. While many studies focus on manufacturing cost estimation, few explore design cost estimation. To improve the accuracy of design cost estimation, this research proposes a new cost driver based on design features available in Computer-Aided Design (CAD) data. The design feature is analyzed to the actual industry cost using machine learning methods, including Artificial Neural Networks (ANNs) and Support Vector Regression (SVR). The cost drivers identified as significant consisted of twenty-six 3D CAD features and four 2D CAD features. The results showed that the ANN models outperformed the SVR models in correctly estimating product design costs, as evidenced by the high R2values in the training and testing phases. The proposed method allows early identification of cost drivers, a significant advantage at the order initiation stage when detailed design features are often ambiguous. The novelty of this research is the use of 3D CAD technology for cost estimation, which quantifies costs based on product design complexity, providing valuable insights into the impact of design adjustments on costs early in the design process. Doi: 10.28991/ESJ-2024-08-03-022 Full Text: PD
The Relationship Between Thinking Ability, Emotional Intelligence, and Decision-Making
Get PDFDespite a significant amount of research on decision-making, academics find it difficult to explain the decision-making process. The purpose of this paper is to examine the relationship between emotional intelligence, thinking ability, and decision-making, as well as develop measurement instruments for thinking ability to better model decision-making. By following a deductive research approach associated with positivist philosophy, a cross-sectional study was conducted and surveyed 547 respondents in South Vietnam via email sent randomly by Google Forms using a convenience sampling method. To avoid common method bias, the reliability and validity of all items were assessed by Cronbach's alpha and using the SPSS program. Then, to assess the structural model and test hypotheses, partial least squares structural equation modeling was applied using the SmartPLS program. The findings not only have proven the significantly positive effects of emotional intelligence and thinking ability on decision-making but also highlight the suitability of the measurement instruments related to thinking ability in explaining decision-making that no research has ever built before. Based on the findings, this research opens up a novel research approach to decision-making and provides the foundation for policymakers and managers to improve decision-making efficiency and human resource quality. Doi: 10.28991/ESJ-2024-08-02-017 Full Text: PD
Artificial Intelligence for Impact Assessment of Administrative Burdens
Get PDFThis study proposes the use of Artificial Intelligence (AI) to automatize part of the legislative impact assessment process. In particular, the focus of this study is the automatic identification of administrative burdens from legislative documents. The goal of impact assessment for administrative burdens is to apply an evidence-based approach toward compliance costs generated by regulation. Employing advanced Natural Language Processing (NLP) techniques based on a transformer architecture, a system was specifically developed and tested using Portuguese legislation. The experimental phase involved the system's ability to accurately and comprehensively identify administrative burdens. Experimental results demonstrated the system's effectiveness, showing its suitability for supporting the legislative impact assessment process by automating a time-consuming task. To the best of our knowledge, this is the first attempt concerning the use of AI for automatizing the identification of administrative burdens. The proposed system may provide governments and policymakers with a tool to speed up the legislative impact assessment process, thereby streamlining decision-making processes. Moreover, the use of AI can make the legislative impact assessment process less subjective, thus increasing its transparency and making citizens more confident about the impartiality of the process that leads to new legislation. Doi: 10.28991/ESJ-2024-08-01-019 Full Text: PD
Implications of Big Data in Accounting: Challenges and Opportunities
Get PDFObjectives: This paper aims to comprehensively explore the implications of Big Data within the realm of accounting, dissecting both its potential advantages and the hurdles it presents. The primary goal is to introduce and delineate the potential benefits of Big Data integration in accounting practices. Additionally, it seeks to identify and thoroughly examine the challenges impeding the seamless assimilation of Big Data into accounting methodologies. By delving into diverse applications, including Auditing, Cost Management, and financial reporting, this study aims to shed light on the multifaceted nature of Big Data's role in accounting. Methods/Analysis: This paper commences with an introduction to the concept of Big Data and its anticipated advantages for accounting practices. It proceeds to conduct a meticulous review and synthesis of existing literature, dissecting the intricate relationship between Big Data and accounting. Through this review, it emphasizes the stumbling blocks encountered in integrating Big Data. Subsequently, it offers a detailed exploration of Big Data's applications in accounting. Findings: Big Data exhibits the potential to substantially transform accounting practices, offering avenues for superior decision-making and analysis. However, the challenges related to data management and analysis pose substantial barriers for accountants in effectively integrating Big Data. Novelty/Improvement: This study offers a comprehensive exploration, dissecting both the potential advantages and challenges presented by Big Data within accounting practices. It provides detailed insights into specific applications of Big Data in accounting, going beyond a surface-level understanding and focusing on domains like Auditing, Cost Management, and financial reporting. Doi: 10.28991/ESJ-2024-08-03-024 Full Text: PD
Using Semicircular Sampling to Increase Sea Water/Ice Discrimination Altitude
Get PDFThe rapid development of aircraft and unmanned aerial vehicles (UAV) increases their use, including in polar areas, which are characterized by their remoteness and rather harsh conditions. The dominant trends in airborne radar development are expanding their functionality and increasing the altitude of their applicability. Our study focuses on the functionality enhancement of airborne high-altitude conical scanning radars currently used for circular clouds and precipitation observations as well as for sea wind measurements. Recently, we showed how a semicircular observation scheme, instead of a circular one, can double the maximum applicable altitude of sea wind measurements made with such radars. Here we apply this approach to show how an airborne high-altitude conical scanning radar's functionality can also be expanded for sea water/ice discrimination within a semicircular observation scheme, again doubling the maximum discrimination altitude compared to circular observations. The discrimination is performed in scatterometer mode using the minimum statistical distance of the measured normalized radar cross sections (NRCSs) to the geophysical model functions (GMFs) of the sea water and ice underlying surfaces. However, as no sea ice GMF is available for the considered horizontal transmit and receive polarization at the Ku band, we instead used a substitute sea ice GMF having the same azimuth isotropic property setting for its NRCSs as the averaged value of the measured azimuth NRCSs within the semicircular observations scheme. Our analysis found that incidence angles of 30°, 45°, and 60° are well suited to our sea water/ice discrimination method, and that incidence angles higher than 30° are preferable as they provide a higher difference in the statistical distance of the measured NRCSs to the sea ice and water GMFs, whereas an incidence angle of 30° provides the highest applicable altitude for sea water/ice discrimination and wind retrieval. We also demonstrated the ability of the sea water/ice discrimination procedure's implementation for any airborne wind scatterometer or multimode radar operated in scatterometer mode over freezing seas to avoid entirely erroneous sea wind measurement results when a sea ice surface is observed. The obtained results can also be used for enhancing aircraft and UAV radars and for developing new remote sensing systems. Doi: 10.28991/ESJ-2024-08-02-07 Full Text: PD
Government Policy Influence on Land Use and Land Cover Changes: A 30-Year Analysis
Get PDFThis study investigated land use and land cover (LULC) patterns and changes in the Bandon Bay area of Thailand from 1991 to 2021 using satellite imagery, the first comprehensive effort to assess historical LULC trends over the past 30 years and forecast future LULC scenarios using the CA-Markov model for 2031, 2041, and 2051. Results showed the predominant LULC during 1991-2001 was the abandoned paddy fields, and during 2006-2021 was the oil palm plantations. During 1991-2001, the abandoned paddy fields changed significantly, with a net gain of 59.28 km2. From 2001-2011 and 2011-2021, the oil palm plantations experienced the most crucial change, with a net gain of 292.94 km2 and 70.06 km2. In 2031, 2041, and 2051, the LULC was predicted to be oil palms, shrimp farms, mangroves, and urban and built-up lands. The LULC changes were consistent with the government policies implemented and indicated government policy as a driving force in LULC dynamics on Bandon Bay area forestry, aquaculture, and agriculture, particularly on oil palm cultivation. Government management and regulation on land use is crucial for reducing the expansion of agricultural areas, especially oil palm plantations and aquaculture areas, to mitigate negative impacts on the Bandon Bay ecosystem. Doi: 10.28991/ESJ-2024-08-05-06 Full Text: PD
Driving Digital Transformation: How Transformational Leadership Bridges Learning Agility and Digital Technology Adoption in MSMEs
Get PDFObjectives: The utilization of technology within an organization is believed to enhance its effectiveness and efficiency. To reap the benefits of technology, MSMEs must adopt digital technology innovation. Individuals and its capabilities within the organization play a significant role in digital technology innovation adoption. This study aims to examine the nexus between learning agility, transformational leadership, and adoption to digital technology innovations. Methods: This study examines the hypotheses involving 203 employees of MSMEs utilizing PLS-SEM. Results: PLS-SEM results show that learning agility and transformational leadership affect digital technology innovation adoption. Accordingly, transformational leadership mediates the connection between learning agility and the adoption of digital technology innovations. Novelty:This research has implications for organizations in adopting digital innovation, where organizations can optimize individual learning agility and utilize transformational leadership styles to persuade employees to adopt digital technology innovation. Furthermore, this research lies in its comprehensive examination of how transformational leadership can amplify the effects of individual learning agility, thereby fostering a more conducive environment for digital innovation within MSMEs. In addition to a comprehensive discussion, this study provides both theoretical and practical guidelines and provides a thorough examination of both aspects. Doi: 10.28991/ESJ-2024-08-04-020 Full Text: PD
Federated Risk-Based Access Control Model for P2P Lending Platforms: A Multi-Agent Systems (MAS) Approach
Get PDFThis study addresses the inherent risk management challenges in decentralized finance, particularly for peer-to-peer (P2P) lending platforms. We propose a novel framework that leverages a Multi-Agent System (MAS) to establish a collaborative network encompassing loan originators, investors, regulators, and service providers. This distributed approach facilitates federated risk management, where risk assessment and mitigation responsibilities are shared across these entities. The MAS employs a comprehensive nine-factor assessment (detailed in Table 5) to evaluate industry risk profiles, considering industry environment, competition, and internal capabilities. This data is further visualized using a color matrix (Tables 5 & 6) and utilized alongside state diagrams (Figure 2) to depict the workflow and manage tasks within the P2P lending process. Additionally, the MAS informs a novel Federated Risk-Based Access Control (FRkBAC) system that tailors access permissions (lending origination, disbursement, etc.) based on dynamic risk assessments of industry trends and individual borrower profiles. This data-driven approach fosters trust within the P2P ecosystem and represents a significant advancement in decentralized finance risk management compared to traditional methods. Doi: 10.28991/ESJ-2024-08-06-05 Full Text: PD
Measuring Sustainability: A Validation Study of a Triple Bottom Line (TBL) Scale in Portugal
Get PDFStudies on sustainability using the Triple Bottom Line (TBL) approach are increasing. However, there is no consensus on how to measure the economic, social, and environmental dimensions of sustainability based on TBL theory. Despite numerous proposals, there is a lack of integrated measures covering all three dimensions simultaneously and having a human-centered approach. This gap is particularly pronounced in Portugal, where no existing scale adequately meets the needs of academics and practitioners. To address this challenge, and based on existing measures that encompass the nature of each TBL dimension, we present and validate a 15-item TBL scale, with 5 items per dimension: economic, social, and environmental. To test convergent validity and contribute to the discussion regarding the links between TBL and Corporate Social Responsibility (CSR), we also analyzed the association between each TBL dimension and each CSR dimension. Using a sample of 635 participants, divided into two independent sub-samples, we conducted comprehensive statistical analyses, including exploratory and confirmatory factor analysis, reliability testing, and convergent and discriminant analysis, followed by invariance testing of the TBL scale. The results suggest that the proposed measure fits the Portuguese sample, and all psychometric results are robust. We also establish the links between the three dimensions of TBL”economic, social, and environmental”and the CSR dimensions, as convergent validity is verified between social TBL and employees' CSR practices. We discuss theoretical and practical implications, as well as limitations and suggestions for future research. Doi: 10.28991/ESJ-2024-08-03-06 Full Text: PD