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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 874 Documents
 55   56   57   58   59 
Factors Affecting Technological Readiness and Acceptance of Induction Stoves: A Pilot Project Retno W. Damayanti; Haryono Setiadi; Pringgo W. Laksono; Dania L. Rizky; Nisa A. E. Entifar
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-04

Abstract

In 2022, through the state electricity company, the Indonesian government launched a pilot experiment to cut imports of liquefied petroleum gas by giving program packages to 1,000 families in five districts in Surakarta. Objectives: Using the technology readiness and acceptance model (TRAM), this study examined the elements influencing the readiness and acceptability of the induction stove program in Surakarta. Method/Analysis: The empirical findings from a 389-respondent survey showed that the program’s public acceptance was supported by favorable technological preparedness, including elements like innovation and optimism. Findings: Perceived use, enjoyment, usefulness, cost level, and confirmation were all factors that affected participants' happiness and willingness to continue using induction stoves and participating in the program. Interestingly, acceptability, general contentment, and the willingness to use induction stoves were not always affected by issues like discomfort and insecurity. Additionally, this research emphasized how crucial the social context is for successfully implementing a program and embracing new technologies. Novelty:This is the first study that concurrently identifies, assesses, and analyzes the integration of factors impacting technology readiness and acceptance (TRAM) into the community's intention to continue participating in the induction stove conversion program. These empirical results offer practical guidance for stakeholders in induction stove conversion projects, particularly in developing nations, and also add to a theoretical understanding of TRAM factors. Doi: 10.28991/ESJ-2023-07-06-04 Full Text: PDF
Blockchain and AI-Driven Framework for Measuring the Digital Economy in GCC Julian Hoxha; Marsela Thanasi-Boçe
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-019

Abstract

The rapid growth of the digital economy presents opportunities and challenges, particularly in the Gulf Cooperation Council (GCC) region, where economic diversification is essential. Accurate measurement of digital economic activity is crucial for developing effective policies and strategic decision-making. This study introduces a comprehensive Digital Economy Measurement (DEM) framework tailored for the GCC. The framework integrates blockchain technology for secure and transparent data management, FinGPT for advanced financial data analysis, and Conversational Agent (CA) for enhanced user interaction. The research methodology involves a step-by-step design, starting with identifying and categorizing relevant data sources, collecting data through APIs and web scraping, and utilizing smart contracts and oracles for validation and recording. The data is managed securely using decentralized storage solutions and regional nodes. We propose using FinGPT and CA to analyze data in-depth and extract valuable insights. User interaction is prioritized through CA, interactive dashboards, and natural language processing, which prioritize user interaction with interfaces tailored to GCC-specific languages and cultures. The study's contribution to the literature lies in its novel, integrated approach to measuring the digital economy in the GCC, addressing challenges related to data accuracy, privacy, and regulatory compliance. By leveraging blockchain, FinGPT, and CA, the DEM-GCC framework offers a robust and adaptable solution for understanding and fostering the region's digital economy. Doi: 10.28991/ESJ-2024-08-04-019 Full Text: PDF
New Concept of Teaching English to Students from Non-English Speaking Countries Ratna Rintaningrum; Aleksandar Kavgić; Marina Garaeva; Lyudmila Shcherbatykh; Mikhail Kosov; Próspero Morán; Kundharu Saddhono; Olga Shalina; Larisa Vatutina; Olesya Dudnik
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-020

Abstract

The objective of this study is to compare and underscore the advantages and disadvantages of learning English in non-English speaking countries to propose the concept of a new English teaching method for students from non-English speaking countries (the case of Russia, Spain, Serbia, and Indonesia). The study used a mixed-methods approach with qualitative analysis of literature from Russia, Serbia, Spain, and Indonesia, and a research questionnaire was developed. 1595 participants were recruited for a survey determining their experiences of learning English and students’ perspectives on English teaching methods in non-English speaking countries. The data went through thematic analysis in the qualitative part of the research and descriptive analysis in the quantitative survey-based design. Findings of the qualitative analysis revealed both advantages and disadvantages of teaching English to students in selected countries; however, the main findings reported the presence of cultural barriers and students finding it difficult to form meanings from the English language context. Conceptual thinking helped to understand the role of memory and comprehension when learning a foreign language, whereby research focuses on more novel concepts. Future researchers can focus on the area of neural development of students' memory, which can help guide strategies to teach the English language effectively. Doi: 10.28991/ESJ-2023-07-06-020 Full Text: PDF
Optimizing Cr(VI) Reduction in Plastic Chromium Plating Wastewater: Particle Size, Irradiation, Titanium Dose Angelica Santis; Oscar Arbeláez; Luz Angelica Cardenas; Jaritza Castellanos; Pablo Velasquez
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-02

Abstract

The preservation of the aquatic environment and water systems has been a fundamental objective that has led great scientists and researchers to seek new alternatives or techniques that allow the decontamination of water sources. The plastic chromium plating industries have been identified as important sources of contamination since their residues are characterized by having considerable amounts of hexavalent chromium Cr (VI), which alters the stability of water resources and can affect effluents on the surface and the subsoil. Given this problem, the need to improve the usual methods and techniques for wastewater treatment with more effective solutions, such as photocatalysis, which presents significant advantages over the inefficiency of traditional methods, is recognized. However, given the limited availability of research in the country that addresses the removal of hexavalent chromium from the wastewater of these industries, this work focuses on optimizing the process by varying conditions of variables such as particle size, catalyst dose, and irradiation time. The optimization of the photocatalysis process was evaluated using the Box-Behnken experimental design. The results show that contaminant removal occurred when the particle size was 0.177 mm. This particle size showed the highest photocatalytic activity, with 100% removal at 45 minutes. These findings represent a significant step towards solving the problem of contamination in this business sector by this pollutant and contribute to preserving our water resources. Doi: 10.28991/ESJ-2024-08-01-02 Full Text: PDF
Design and Analysis of a Bandwidth Aware Adaptive Multipath N-Channel Routing Protocol for 5G Internet of Things (IoT) Satyanand Singh; Joanna Rosak-Szyrocka; Balàzs Lukàcs
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-018

Abstract

Large numbers of mobile wireless nodes that can move randomly and join or leave the network at any moment make up mobile ad-hoc networks. A significant number of messages are delivered during information exchange in populated regions because of the Internet of Things' (IoT) exponential increase in connected devices. Congestion can increase transmission latency and packet loss by causing congestion. More network size, increased network traffic, and high mobility that necessitate dynamic topology make this problem worse. An adaptive Multipath Multichannel Energy Efficient (AMMEE) routing strategy is proposed in this study, in which route selection strategies depend on forecasted energy consumption per packet, available bandwidth, queue length, and channel utilization. While multichannel uses a channel-ideal assignment process to lessen network collisions, multipath offers various paths and balances network strain. The link bandwidth is split up into a few sub-channels in the multichannel mechanism. To reduce network collisions, several source nodes simultaneously access the channel bandwidth. The cooperative multipath multichannel technique offers several paths from a single source or from several sources to the destination without colliding or becoming congested. The AMMEE routing approach is the basis for path selection. A load- and bandwidth-aware routing mechanism in the proposed AMMEE chooses the path based on node energy and forecasts their lifetime, which improves network dependability. The outcome demonstrates a comparative analysis of various multichannel medium access control (MMAC) techniques, including Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning-based Multipath Routing (QMR), and Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV) and the proposed AMMEE method. The results show that the AMMEE approach outperforms alternative systems. Doi: 10.28991/ESJ-2024-08-01-018 Full Text: PDF
Using Semicircular Sampling to Increase Sea Water/Ice Discrimination Altitude Alexey Nekrasov; Alena Khachaturian; Colin Fidge
Emerging Science Journal Vol 8, No 2 (2024): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-02-07

Abstract

The 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: PDF
The Effect of Felt Accountability on User Satisfaction with Accounting Information Dang Anh Tuan
Emerging Science Journal Vol 8, No 2 (2024): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-02-023

Abstract

Felt accountability affects an account-givers’ behavior, decisions, and organizational performance. Accounting information (AI) is provided for decision-making and accountability in the public sector. This study investigated the effects of felt accountability on expertise, legitimacy, and AI disclosure level for accountability on users’ satisfaction. Survey data included 401 responses across public institutions in Vietnam, and SEM linear structure analysis was used to examine the results. The research findings indicate that felt accountability directly affects users’ satisfaction and their expertise and legitimacy, and the level of AI disclosure. The expertise and legitimacy of the account-holder and the level of AI disclosure partially mediate the relationship between felt accountability and users’ satisfaction. This implies that AI's needs, purposes, and importance are determined based on hypothetical users that are not useful in reality. In practice, AI must meet accountability requirements to bring satisfaction to users. The satisfaction level of actual users of AI is influenced by the account-givers’ perceived accountability regarding the needs, expertise, and legitimacy of the account-holder. Therefore, it is essential to identify the type of information needed, the timing of AI disclosure, and the actual AI users to reduce the gap between the supply and demand of AI. The research results provide evidence supporting agency and social contingency theories in accountability relationships. Doi: 10.28991/ESJ-2024-08-02-023 Full Text: PDF
Enhancing GI Cancer Radiation Therapy: Advanced Organ Segmentation with ResECA-U-Net Model S. M. Nuruzzaman Nobel; Omar Faruque Sifat; Md Rajibul Islam; Md Shohel Sayeed; Md Amiruzzaman
Emerging Science Journal Vol 8, No 3 (2024): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-03-012

Abstract

This research introduces a pioneering solution to the challenges posed by gastrointestinal tract (GI) cancer in radiation therapy, focusing on the imperative task of precise organ segmentation for minimizing radiation-induced damage. GI imaging has historically used manual demarcation, which is laborious and uncomfortable for patients. We address this by introducing the ResECA-U-Net deep learning model, a novel combination of the U-Net and ResNet34 architectures. Furthermore, we further augment its functionality by incorporating the Efficient Channel Attention (ECA-Net) methodology. By utilizing data from the UW-Madison Carbone Cancer Center, we carefully investigate several image processing techniques designed to capture critical local characteristics. With its foundation in computer vision concepts, the ResECA-U-Net model is excellent at extracting fine details from GI images. Sophisticated metrics such as intersection over union (IoU) and the dice coefficient are used to evaluate performance. Our study's outcomes demonstrate the effectiveness of the suggested method, yielding an impressive 96.27% Dice coefficient and 91.48% IoU. These results highlight the significant contribution that our strategy has made to the advancement of cancer therapy. Beyond its scientific merits, this work has the potential to significantly enhance cancer patients' quality of life and provide better long-term outcomes. Our work is a significant step towards automating and optimizing the segmentation process, which can potentially change how GI cancer is treated completely. Doi: 10.28991/ESJ-2024-08-03-012 Full Text: PDF
Beyond COVID-19 Lockdowns: Rethinking Mathematics Education from a Student Perspective Almarashdi, Hanan Shaher
Emerging Science Journal Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-SIED1-010

Abstract

The COVID-19 pandemic has recently reshaped education and life around the world. Undoubtedly, the return to face-to-face learning has been affected after two years of distance learning. However, research that focuses on post-COVID-19 is still limited. Therefore, this study investigates how students perceive the experience of returning to face-to-face learning after distance learning within the context of the United Arab Emirates (UAE). It emphasizes the possibilities and challenges that could be faced in improving face-to-face mathematics education. This study applied an exploratory sequential mixed-method approach, which involved collecting qualitative data from 13 students through a focus group, and then quantitative data was collected from 243 Cycle 2 and 3 students. The qualitative data were coded and analyzed thematically, while descriptive analysis was used to analyze the quantitative data. The qualitative and quantitative results revealed consensus on the main challenges that students experience as they return to face-to-face learning. On top of these challenges are students' lack of study skills, excessive use of technology, and high levels of math test anxiety. Research findings showed students’ preference for face-to-face learning while adding some aspects of distance learning. The results of this study are also expected to be a reference in the development of a new sustainable paradigm of face-to-face learning and as study material for subsequent research related to rethinking math education after COVID-19. Doi: 10.28991/ESJ-2024-SIED1-010 Full Text: PDF
Validation of the GAEU-1 Acale to Assess the Learning Management of University Students Carlos Ramos-Galarza; Patricia García-Cruz; Nancy Lepe-Martínez; Milenko Del Valle; Mónica Bolaños-Pasquel; Jorge Cruz-Cárdenas
Emerging Science Journal Vol 7 (2023): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-SIED2-019

Abstract

Introduction: The self-management of university learning encompasses a series of aspects that allow students to be conscious and autonomous in their professional training. Objective: In this article, we present the process of creation and validation of a scale to assess essential factors of this phenomenon: self-management of learning, conscious motivation strategies for learning, perception of academic performance, and techniques for deep learning. Method: The design is a cross-sectional quantitative process with the purpose of carrying out validity and reliability analysis of a psychological measurement instrument. The research was conducted with 1373 university students from Chile and Ecuador. Results: The scale consists of 19 items that conform the four factors mentioned and whose results indicate adequate psychometric properties, allowing it to be applied in the Latin American context. Novelty:This research proposes a new instrument to assess the self-management of the university learning process, which contributes to carrying out new research in the university educational context. Doi: 10.28991/ESJ-2023-SIED2-019 Full Text: PDF

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