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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
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Emerging Technological Methods for Effective Farming by Cloud Computing and IoT A. R. Abdul Rajak
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-07

Abstract

Agriculture provides a solution to the vast majority of problems that threaten human existence. When it comes to agriculture, new or contemporary technology can have a significant impact on a number of factors, including how much food is produced and how long it stays edible. The application of best management practices, for instance, is very common these days in the quest to improve agriculture. New hybrids are resistant to illnesses, use fewer pesticides, have natural defenses against pests, and may be grown in methods that minimize the number of diseases and pests that can affect them. Plants are capable of producing oxygen and medicines in addition to the food that they provide. Consequently, agriculture depends on plants that are in good health. A plant needs water, sunlight, and crucial fertilizer in order to receive the nutrients it needs to have a healthy plant. So, it is necessary to keep an eye on the health of the plant. The article discusses various technological solutions that can be implemented to automate the plant monitoring system. The Internet of Things and cloud computing are two technologies that are contributing to the development of intelligent technology by supplanting traditional agricultural practices. This clever device checks on the well-being of the plants. In order to enable intelligent agriculture, the technology relies on sensors that are dependent on IoT sensors. These sensors monitor the temperature, soil moisture, intensity of the sun's light, air quality value of the soil, vibration, and humidity in the immediate environment of the plant. The networking of these sensors ensures that the plant will continue to be healthy and will function in the appropriate manner. The findings that have been obtained up to this point are encouraging for the continuance of this strategy, which results in the highest possible profit for farmers. Doi: 10.28991/ESJ-2022-06-05-07 Full Text: PDF
Motivational Factors Influencing Telework during the COVID-19 Pandemic Chittipa Ngamkroeckjoti; Worasak Klongthong; Jakkrit Thavorn
Emerging Science Journal Vol 6 (2022): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2022-SPER-016

Abstract

During the COVID-19 pandemic, teleworking has proven to be an effective countermeasure to overcome the spread of this disease while enabling businesses to continue. However, little is known about the extent of their adjustment to daily life routine, interaction among self-control, assignments, family life matters, and coordination with colleagues. This study explores the impact of motivational factors on the performance of teleworkers. An exploratory study was conducted using an in-depth interview with 27 interviewees who work in Thailand and have more than a year of experience switching between being a teleworker and working on-site. The NVivo and SPSS software were performed to reveal deeper data insights and apply non-parametric tests in order to compare findings with various demographic profiles. The findings revealed that environment, time management, and reward are the strongest motivational factors, whereas labour intensity and job security present the weakest relationships with teleworkers’ performance. Numerous implications and strategies to enhance their performance for both organizations and workers are provided. Firms can support a well-prepared environment and manage the flexibility of working time to increase employees’ effectiveness. Moreover, the result-oriented approach can be one of the tools in evaluating their performance rather than attending to their full working time at home. Doi: 10.28991/esj-2022-SPER-016 Full Text: PDF
Assessing Blockchain Adoption in Supply Chain Management, Antecedent of Technology Readiness, Knowledge Sharing and Trading Need Athapol Ruangkanjanases; Taqwa Hariguna; Ade Maharini Adiandari; Khaled Mofawiz Alfawaz
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-01

Abstract

The present research aimed to establish a framework integrating the concept of technology readiness with variables that accomplished the blockchain adoption theory to identify the impact of blockchain adoption on supply chain transparency, blockchain transparency, and supply chain performance. The methodology used was quantitative with PLS-SEM as the analysis method. There were 295 validated datasets used. The procedure of data collection involved questionnaires. The key finding of the research confirmed the six proposed hypotheses. It was also confirmed that technology readiness, knowledge sharing, and trading needs were significant for the profitability of blockchain technology adoption in supply chain management. On the other hand, blockchain adoption played a significant role in supply chain transparency, blockchain transparency, and supply chain performance. The novelty of this research is in the integration of technology readiness into blockchain in the field of supply chain management. This research can be used to improve and analyze the success rate of blockchain adoption in supply chain management systems. The findings of this study contribute to several aspects, namely practical and academic implications, by providing more insights that correlate with blockchain integration into supply chain management systems. Doi: 10.28991/ESJ-2022-06-05-01 Full Text: PDF
The Impact of Macroeconomic Factors on Non-performing Loans in the Western Balkans Adelina Gashi; Saranda Tafa; Roberta Bajrami
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-08

Abstract

This paper analyzes the relationship of macroeconomic factors to the level of non-performing loans (NPLs) using the econometric models GMM, the Fixed Effect model, and the Random Effect model. This study aims to identify macroeconomic factors at the level of non-performing loans in the Western Balkans, measure their impact on non-performing loans, and thus fill the gap that exists between macroeconomic factors (consisting of economic growth) and those with more impact on NPLs. The methodology used to carry out this research was desk research. We used World Bank data from 2000–2019, processed with STATA software. Results show that macroeconomic factors have an impact on non-performing loans. It also proves that even when interacting with other variables, the level of bad debt has not been completely eliminated, despite economic growth in many countries. Third, throughout the study period, fixed effects estimates show that variables are not significant in a static context. According to the findings, the annual rates of GDP growth, final government consumption, the real interest rate, gross domestic savings, and the unemployment rate all have a favorable impact on NPLs. This research contributes to a deeper understanding of the relationship between macroeconomic factors and non-performing loans in the Western Balkans. Based on this, to help reduce loan risk and bad debt by the proper criteria, we propose a series of policy implications. These implications aim to improve the efficiency of banks in particular and the banking system as a whole. Doi: 10.28991/ESJ-2022-06-05-08 Full Text: PDF
Examination of Students’ Academic Performance in Selected Mechanical Engineering Courses Prior-to-and-During COVID-19 Era Olanrewaju M. Oyewola; Olusegun O. Ajide; Ibukun S. Osunbunmi; Yemisi V. Oyewola
Emerging Science Journal Vol 6 (2022): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2022-SPER-017

Abstract

Advances in Information and Communications Technology (ICT) as well as the present challenges of COVID-19 have led to a new paradigm causing an absolute or partial transition from in-person classroom teaching-learning to online. There is little information available on research efforts that investigated the impact of an online learning approach on the academic performance of students in mechanical engineering-based courses. Therefore, the objective of this paper is the impact study of online learning mode as compared to in-person on academic performance of students in selected mechanical engineering courses in one of the Universities in South Pacific Islands prior-to-and-during COVID-19 Era. Data on grades obtained for 178 students that offered Fluid Mechanics, Thermodynamics, Heat Transfer, and Advanced Thermofluids (FTHA) courses were subjected to descriptive and non-parametric (Mann-Whitney and Kruskal-Wallis) statistical tests. Although descriptive analysis showed that online mode of instruction might influence a better academic performance in FTHA courses in comparison with in-person mode of instruction, the outcome of Mann-Whitney U and Kruskal-Wallis tests at specific p-values and corresponding z-values generally exhibited p-values higher than of 0.05, implying insignificant difference in performance between the two modes of learning investigated. Though the non-parametric statistical test results showed there was no significant difference in academic performance of students when online and in-person modes of learning were used, this, however, does not imply that a difference does not exist at all. Although the difference may be very trivial, descriptive analysis has shown that the online learning mode has at least exhibited better students’ academic performance when compared to in-person. It can be inferred from the foregoing that the online learning mode does not yield a negative response in respect of the performance of students who offered all four mechanical engineering courses. Based on the findings of this study, online is considered a reliable alternative to in-person or at least a suitable complement to in-person in the in-person-online hybrid mode during the ongoing COVID-19 era and other inevitable constraints in the future. Doi: 10.28991/esj-2022-SPER-017 Full Text: PDF
Thermal Regeneration and Reuse of Carbon and Glass Fibers from Waste Composites Alexey V. Nistratov; Natalya N. Klimenko; Igor V. Pustynnikov; Long Kim Vu
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-04

Abstract

This article aims to develop a method for regenerating and reusing carbon and glass fibers extracted from unrecyclable scraps of carbon plastics, printer parts, and laminating coating. A comparison of known methods of fiber regeneration revealed the advantages of thermal treatment: absence of costs of reagents and complex equipment; better preservation of composition; and strength of fibers. Based on the results of thermographic analysis of wastes in nitrogen and air, the destruction temperatures of their organic matrices were determined (200-460°С), and the use of calcination instead of pyrolysis was justified. The appearance and surface quality of the regenerated fibers are characterized by optical and electron microscopy. It has been established that quantitative extraction of pure carbon and glass fibers from waste crushed to 1 cm is efficient by their calcination at 700 °C for 0.5 h and 500 °C for 1 h, respectively. The principle of creating new composites with the obtained fibers based on the similarity of their composition and binding materials (matrices) has been proposed. It was shown that the introduction of 1 wt% of fibers into slag blocks and active carbon pellets considerably increases their compressive strength, but the bending strength does not change due to dispersed reinforcement. Possible improvement of mechanical properties of products requires reagent treatment of the fiber surface or the introduction of binder additives. Calculations show that the developed method of recycling composite waste can produce 2.3 tons/hour of reinforced building materials that are good for the environment and the economy, excluding expenses for landfill waste disposal and reducing the cost of the product by replacing the primary fiber for the secondary one. Doi: 10.28991/ESJ-2022-06-05-04 Full Text: PDF
A YOLO Detector Providing Fast and Accurate Pupil Center Estimation using Regions Surrounding a Pupil Wattanapong Kurdthongmee; Piyadhida Kurdthongmee; Korrakot Suwannarat; Jeremy K. Kiplagat
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-05

Abstract

Eye-tracking technology has many useful applications, including Virtual Reality (VR) devices, Augmented Reality (AR) devices, and assistive technology. The main objective of eye-tracking technology is to detect eye position and track eye movements. It is possible to determine the eye position when the pupil center is detected. In this paper, a deep learning-based approach to the detection of pupil centers from webcam images is presented. As opposed to all previous approaches to object detection based on training the detector with objects to be detected, our object detector was trained with both the region surrounding a pupil and the region between an eye and the region surrounding a pupil. The latter set of regions has been found to increase the overall detection accuracy. A novel post-processing algorithm is also presented to estimate the pupil center from all the detected regions. To achieve real-time performance, we have adopted the tiny architecture of YOLOv3, which has 23 layers and can be executed without requiring a GPU accelerator. To train the detectors, different variations of regions covering a pupil and an eye were used, as well as expanding regions surrounding a pupil and an eye. The PUPPIE dataset was used as the primary input for training the detector. The setting with the best detection accuracy was applied to all publicly available datasets: I2Head, MPIIGaze, and U2Eyes. In terms of accuracy, the results indicate that pupil center estimation is comparable to the state-of-the-art approach. It achieves pupil center estimation errors below the size of a constricted pupil in more than 98.24% of images. Furthermore, the detection time is 2.8 times faster than the state-of-the-art approach. Doi: 10.28991/ESJ-2022-06-05-05 Full Text: PDF
Deep Learning Based Gait Recognition Using Convolutional Neural Network in the COVID-19 Pandemic Md Shohel Sayeed; Pa Pa Min; Md Ahsanul Bari
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-012

Abstract

Gait recognition is the behavioral biometric trait that tracks humans based on their walking motion. It has gained attention because of its non-invasive and unobtrusive behaviors and applicable to the different application area. In this paper, we target model-free gait recognition with the deep learning approach for the Muslim community in the COVID-19 pandemic. The different convolutional neural network architectures (CNN) are examined by using the spatio-temporal gait representation called Gait Energy Images (GEI). We explored both the identification and verification problems to determine the suitability of the proposed CNN frameworks. In gait recognition, the intraclass variation is larger than the inter-class variation because of the shooting view, the walking speed, the wearing condition, and so on. To tackle this challenge, the verification framework is more suitable for the 1:1 association of gait recognition. As for the verification problem, we implemented the Siamese network with the parallel CNN architecture. All the proposed methods are tested against the public gait datasets called OUISIR-LP and OUISIR-MVLP to determine the identification and verification performance in terms of recognition accuracy and error rate. Doi: 10.28991/ESJ-2022-06-05-012 Full Text: PDF
Digital Disconnection as an Opportunity for the Tourism Business: A Bibliometric Analysis Juan F. Arenas-Escaso; José A. Folgado-Fernández; Pedro R. Palos-Sanchez
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-013

Abstract

The aim of this study is to carry out a bibliometric review of the existing research on digital disconnection and Digital Free Tourism (DFT) to discover the extent to which this new trend affects technology users and the tourism market. To do this, a systematic literature review and a bibliometric analysis of the research on digital disconnection contained in the Scopus and Web of Science databases were used. This research includes publications from 2012 to December 2021, which included a total of 37 publications about digital disconnection and digital free tourism in scientific journals indexed in the main scientific databases. The analysis concludes that DFT is a growing economic trend in research and that the phenomenon of digital disconnection is beginning to be a peremptory need for more and more users. This work is original and interesting for researchers specialising in technology addictions, as well as academics and professionals in the tourism sector, because the extensive use of smart devices is becoming a type of addiction in many areas and can be a new opportunity for the tourism market. The DFT phenomenon can improve the response to these types of addictions and be a temporary escape and alternative to technological devices. Doi: 10.28991/ESJ-2022-06-05-013 Full Text: PDF
Tourist Motivation as an Antecedent of Destination and Ecotourism Loyalty Sinh Duc Hoang; Tien Phat Pham; Zuzana Tučková
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-014

Abstract

Objective: This study evaluates the role of tourist motivation in the determination of destination and ecotourism loyalty using push and pull motivation theory and the theory of planned behavior. The paper also analyses the mediating effects of satisfaction and destination image in the relationships between motivation and the two types of loyalty. Method/analysis: Primary data has been gathered from surveys involving 522 Vietnamese tourists traveling to the Bohemian Switzerland National Park in the Czech Republic. Data analysis was conducted using structural equation modeling (SEM) techniques in R. Findings: The findings support both direct and indirect positive associations between tourist motivation and destination and ecotourism loyalty. In terms of ecotourism loyalty, the effect is mediated by destination image. In terms of destination loyalty, the effect is mediated by satisfaction and destination image. Novelty/improvement: This study has further expanded the theory of planned behavior in the context of ecotourism by linking it to travel career pattern theory and functionalist theory. These are complementary theories that can explain the behavior of ecotourists and help operators and marketers adjust their strategies to attract and retain visitors to ecotourist destinations. Doi: 10.28991/ESJ-2022-06-05-014 Full Text: PDF

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