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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 25 Documents
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Search results for , issue "Vol 8, No 5 (2024): October" : 25 Documents clear
Neural Networks in Optimizing the Performance of the Elliptical-Plasmonic Sensor Ramadhan, Khaikal; Syamsul, Andi M. N. F.; Marwan, Arip; Agustirandi, Beny; Yasir, Mhd; Christian, Hadi
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-07

Abstract

In this work, we report the capability of a PCF-SPR sensor with an elliptical core, which has high sensitivity, and it is explained using a machine learning approach. The sensor component consists of fused silica as the background material, TiO2 as the adhesive material between the dielectric material and the plasmonic material, and Au was chosen as plasmonic material with optimal thicknesses of 35 nm for TiO2and 45 nm for Au. Numerical results show that the sensor component has a high sensitivity of 24,000 nm/RIU for four modes that have consistent shifts, including x-polarized, x-odd, y-polarized, and y-odd. Meanwhile, AS maximums were found of -91.82 1/RIU for x-polarized, -91.88 1/RIU for y-polarized, -90.98 1/RIU for x-odd, and -89.276 1/RIU for y-odd respectively, on the refractive index of the analyte of 1,365 RIU. The ML algorithm was used to optimize the sensor parameters, and it was found that the algorithm had a very low MSE of 0.00083; this result is better than the previous report work. Doi: 10.28991/ESJ-2024-08-05-07 Full Text: PDF
Strategies for Pedagogical Interventions to Develop Emotional Intelligence (EI) of Employees in a Hybrid Work Schedule Matulčíková, Marta; Breveníková, Daniela; Vaľko, Michal; Gawrych, Roman; Procházka, David A.
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-023

Abstract

The purpose of the research article is to identify the educational methods suitable for developing employee emotional intelligence. The focus was on the number of hours that small and medium sized enterprises are willing to invest in training their employees in emotional intelligence and on the benefits, i.e., changes in work outcomes as evaluated by respondents. The questionnaire method and interviews were used to obtain data from respondents, line managers, and education managers. Based on correlation coefficient calculations, brainstorming was identified as a frequently used method of active learning, which is related to the physical presence in the learning premises. The analysis of the responses of the respondents and their calculation using the correlation coefficient surprisingly showed that the lecture method gained great support and was considered by the respondents, i.e., managers and education managers, as very important to achieve the cognitive, affective, and psychomotor goals of education. Moreover, it was assessed as a method suitable for remote learning, i.e., for virtual educational spaces. Doi: 10.28991/ESJ-2024-08-05-023 Full Text: PDF
Assessing the Impact of Innovation Processes on Electronic Systems Technology Adoption Ouheda, Salem; Murray, Peter A.; Alam, Khorshed; Ali, Omar
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-02

Abstract

Objectives: This study aims to explore the adoption of electronic health records (EHRs) in the Australian private healthcare sector by integrating three prominent innovation models, namely the Technology Acceptance Model (TAM), the Diffusion of Innovation (DOI) model, and the Technology-Organization-Environment (TOE) framework. The objective of the study is to understand how these combined models might better inform the EHR adoption process and identify the key factors influencing successful implementation. Methods/Analysis: An exploratory qualitative research design employing a phenomenological approach was utilized to investigate the research. Data were collected through semi-structured interviews with senior managers at a private hospital in South-East Queensland. Purposive sampling was employed to select participants, ensuring representation from key decision-makers involved in the EHRs planning process. Thematic analysis, guided by the reflexive thematic analysis (RTA) approach of Braun and Clarke, was used to analyze the data and derive insights into the factors influencing EHRs adoption. Findings: Key findings indicate that perceived usefulness and job relevance (from TAM), innovation attributes and communication channels (from DOI), and technological, organizational, and environmental contexts (from TOE) are critical elements for successful EHRs implementation. The study also highlights the importance of user engagement, comprehensive training, leadership support, and financial resources. Novelty/Improvement: This study offers a novel contribution by integrating the TAM, DOI, and TOE models to provide a more holistic understanding of EHRs adoption in the private healthcare sector. It also introduces the concept of time as a critical innovation artefact, highlighting its significance in the adoption process. Doi: 10.28991/ESJ-2024-08-05-02 Full Text: PDF
The Effect of EAP on Job Performance Based on Psychological Contract and Perceived Organizational Support Cai, Yinquan; Yii, Josephine Ling Chen; Pathak, Shubham
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-018

Abstract

In order to study whether employee assistance programs have a significant impact on job performance, whether psychological contract and perceived organizational support play a mediating role in job performance, and thus provide practical operational strategies for relevant enterprises to propose human resource management suggestions to promote job performance, the implementation of employee assistance programs has been the subject of practical research. The findings indicate that addressing issues related to high turnover, job burnout, and absences cannot be separated from the importance of the psychological contract, perceived organizational support, and employee performance in organizational change. By applying structural equation modeling (SEM) to the data from front-line employees of several units in China, this research tested the relationships among employee assistance programs, psychological contracts, perceived organizational support, and job performance using SPSS and AMOS. The results indicate that employee assistance programs positively affect job performance; psychological contracts and perceived organizational support play a mediating role between employee assistance programs and employee job performance (JOP). Our research suggests that an employee assistance program can optimize frontline employee assistance work, build a mechanism to stimulate frontline employees' psychological contracts, and create an organizational environment full of perceived organizational support. This study innovatively uses the structural equation model for quantitative research. In addition, most previous studies on EPA were based on a single variable, psychological contract, and POS were used as the main intermediary variables to explore the mechanism of their impact on job performance so as to enhance the explanatory power of employee job performance. Doi: 10.28991/ESJ-2024-08-05-018 Full Text: PDF
An Explainable Deep Learning Approach for Classifying Monkeypox Disease by Leveraging Skin Lesion Image Data Maseleno, Andino; Huda, Miftachul; Ratanamahatana, Chotirat Ann
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-013

Abstract

According to the World Health Organization's (WHO) external situation report on the multi-country outbreak of Monkeypox in 2023, from 11 countries in Southeast Asia Regions, Thailand recorded the highest reported cases, totaling 461. The ongoing Monkeypox outbreak has raised significant public health concerns due to its rapid spread across several nations. Early detection and diagnosis are imperative for effectively treating and controlling Monkeypox. Given this context, this study aimed to determine the most efficient model for detecting Monkeypox by employing interpretable deep learning techniques. This study utilizes deep learning techniques to diagnose Monkeypox based on images of skin lesions. We evaluate based on four models—convolutional neural network (CNN), gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short term memory (BiLSTM)—using a publicly available dataset. Additionally, we incorporate Local Interpretable Model-Agnostic Explanations (LIME) and techniques for explainable AI, facilitating visual interpretation of model predictions for healthcare practitioners. The CNN model's performance and LSTM model's performance have an accuracy of 100%, while the GRU model's performance and BiLSTM model's performance have an accuracy of 99.88% and 99.45%. Our findings demonstrate the effectiveness of deep learning models, including the suggested CNN model leveraging the pre-trained MobileNetV2 and LSTM. These models can play a pivotal role in combating the Monkeypox virus. Doi: 10.28991/ESJ-2024-08-05-013 Full Text: PDF
Influence of Non-Economic Factors on the Formation and Development of the Design of Financial Systems Fiapshev, Alim; Travkina, Elena; Belova, Marianna
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-08

Abstract

The purpose of this scientific work is to investigate the impact of non-economic factors on the design of financial systems, focusing on the concept of institutional quality, which is measured using six indices according to the World Bank's methodology. To assess this impact, we utilized data from 1996 to 2022 for a wide range of countries, grouped into five clusters based on per capita income. The comparative analysis of these country clusters revealed a direct and consistent relationship between per capita income dynamics and financial development with changes in institutional quality. It also highlighted the significant influence of this relationship on the structural features of national financial systems. The study demonstrates that institutional quality is the starting point of this entire process, determining the effectiveness of the link between financial development and economic growth through changes in the financial structure. The findings confirm the convergence of financial development levels among countries with different financial system structures and legal traditions, provided they maintain high-quality institutions. The study underscores the importance of institutional quality in minimizing the consequences of structural distortions in the financial system and addressing gaps in financial and economic development. These results are crucial for economic policymakers in developing countries and those with low per capita incomes. Doi: 10.28991/ESJ-2024-08-05-08 Full Text: PDF
Air Pollution Forecasting in a Regional Context for Sustainable Management Guayjarernpanishk, Pannarat; Chutiman, Nipaporn; Piwpuan, Narumol; Kong-ied, Butsakorn; Chiangpradit, Monchaya
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-024

Abstract

The aim of this research was to develop and apply a statistical model that can be used to forecast long-term daily maximum particulate matter with a diameter of less than 2.5 microns (PM2.5) concentrations. In order to predict the daily maximum PM2.5 concentrations in the northeastern region of Thailand, the extreme value theory was analyzed, and an appropriate distribution model was identified by employing the Generalized Pareto distribution (GPD). The data of daily maximum PM2.5 concentrations during the years 2021–2023 obtained from six stations was used. These stations are located in Khon Kaen, Loei, Nakhon Ratchasima, Nong Khai, Nakhon Phanom, and Ubon Ratchathani provinces. The results of this study reveal that the GPD is appropriate based on the results of Kolmogorov-Smirnov Statistics Test. Estimating the return levels during the following return periods: 2 years, 5 years, 10 years, 25 years, 50 years, and 100 years showed that the area in the upper northeastern region, particularly Loei and Nakhon Phanom, has daily maximum PM2.5 concentrations above 500 micrograms per cubic meter. These results can also be used as information to support decision-making when conducting response planning in high-risk areas, which can be helpful for efficient resource planning and prevention actions. Doi: 10.28991/ESJ-2024-08-05-024 Full Text: PDF
Design of Modified UWB Microstrip Antenna for UHF Partial Discharge Sensor Khayam, Umar; Hamdani, Yuda M.; Rachmawati, .
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-03

Abstract

The development of printable ultrahigh-frequency (UHF) antennas as partial discharge (PD) sensors for high-voltage equipment has been extensively studied. However, achieving ultrawideband (UWB) UHF PD sensors frequently requires larger sizes, unsuitable for certain applications requiring compact sensors for dielectric windows in HV equipment. This research objective is to obtain PD sensors with a wider bandwidth (0.3–3 GHz) and a compact size fitting a less-than-100mm-length gas-insulated switchgear (GIS) dielectric window. A circular patch microstrip antenna (CPMA) was chosen for its small size and potential for UWB performance. This paper discusses the design modification of the CPMA to obtain a wider bandwidth for PD detection in GIS. Simulations and lab-scale experimental verifications were conducted to evaluate the optimized sensor. The modified sensor, with a size of 60 × 73 mm², achieved a bandwidth of 3.08–3.14 GHz, a reflection coefficient of -44 dB, and several resonant frequencies of 0.3–2.3 GHz. This is a seven-time wider bandwidth compared to earlier bowtie antennas while keeping a dimension of less than 100 mm². These properties allow for efficient PD detection in GIS and other insulating media. Experimental results indicate the sensor's capacity to reliably detect and analyze PD signals while responding appropriately to variations in voltage. Doi: 10.28991/ESJ-2024-08-05-03 Full Text: PDF
Modelling School Zone Border as Rich Modelling Problem for Secondary School Students Suweken, Gede
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-019

Abstract

This article explores the potential of using the school zoning problem in Indonesia as a vehicle for teaching mathematical modeling to secondary school students. This problem is highly suitable for students as a modeling challenge because it is (i) contextual, (ii) rich, (iii) challenging, and (iv) within students' Zone of Proximal Development (ZPD). School zoning involves a concept called Voronoi, essentially a partitioning problem. For simpler or special-case problems, these partitions can be created using concepts already taught in secondary schools, such as perpendicular bisectors and radical axes. However, for more complex problems with multiple sites, an algorithm is required, which involves advanced mathematical concepts beyond the typical secondary curriculum. Yet, with the rise of visual programming languages like Scratch, Snap!, StarLogo, and TurboWarp, it becomes possible to tackle these partitioning challenges using coding and only basic mathematical principles. This approach not only enhances students' understanding of foundational mathematical concepts but also fosters the integration of computational thinking and coding within mathematics. In summary, the school zoning problem serves as an ideal topic for mathematical modeling for secondary school students, promoting the integration of mathematical concepts, computational thinking, and coding skills. Doi: 10.28991/ESJ-2024-08-05-019 Full Text: PDF
New Assessment Model of Financing Treatment of Patients with Complete Tooth Loss Grachev, Dmitry I.; Martynenko, Aleksandr V.; Perekhodov, Sergey N.; Kostyrin, Evgeniy V.; Mustafaev, Magomet Sh.; Akhmedov, Kamalutdin G.; Deshev, Aslan V.; Rozanov, Daniil G.; Korotkova, Nadezhda L.; Kerasov, Stefan N.; Arutyunov, Sergey A.
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-014

Abstract

According to the World Health Organization, the global prevalence of complete tooth loss is estimated to be 7% among individuals aged 20 years and older, while for those aged 60 and over, this rate significantly increases to 23%. This study is relevant due to the psychological trauma, social challenges, and functional limitations caused by tooth loss, as well as the uneven availability of dental care worldwide. The goal of this research is to develop and implement a new model to assess the socioeconomic feasibility of investing in digital technologies for diagnosing and treating patients with complete tooth loss using removable polymer prostheses produced through additive 3D printing. The study employs scenario analysis, the clustered rankings coordination method, statistical methods, expert opinion assessment using Kendall’s coefficient of rank concordance, system analysis and design, questionnaires, sociometry, and functional modeling. The practical significance of this research lies in providing a quantitative assessment of economic opportunities for effectively using RPDs in three groups: RPDs without additional fixation means; those with special adhesive agents for improved fixation; and implant-supported prosthetics with conditionally removable dentures similar to RPDs. The scientific novelty of this study is the development of a new evaluation model that justifies the choice of prosthetic treatment technology for patients with complete tooth loss, enabling the most rational use of resources. Doi: 10.28991/ESJ-2024-08-05-014 Full Text: PDF

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