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Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
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
Bio-Mechatronics Development of Robotic Exoskeleton System With Mobile-Prismatic Joint Mechanism for Passive Hand Wearable-Rehabilitation Vargas, Mariela; Mayorga, J.; Oscco, B.; Cuyotupac, V.; Nacarino, A.; Allcca, D.; Gamarra-Vásquez, L.; Tejada-Marroquin, G.; Reategui, M.; Maldonado-Gómez, R. R.; Vasquez, Y.; de la Barra, Daira; Tapia-Yanayaco, P.; Charapaqui, Sandra; V. Rivera, Milton; Palomares, R.; Ramirez-Chipana, M.; Cornejo, Jorge; Cornejo, José; De La Cruz-Vargas, Jhony A.
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-02

Abstract

The World Health Organization (WHO) estimates that 15 million people are affected by stroke each year, causing deterioration of the upper limb, which is reflected in 70-80% of them, decreasing the performance of daily activities and quality of life, mainly affecting hand functions. Thus, the purpose of this study is to present a high-quality alternative to recover muscle tone and mobility, consisting of a hand-exoskeleton for passive rehabilitation. It covers a motion protocol for each finger and pressure sensors to give a safety pressure range during the gripping function. The bio-design method covers standards (ISO 13485 and VDI 2206) based on biomechanic and anthropometric fundamentals, where Fusion 360 was used for mechanical development and electrical-electronic circuit schematics. The prototyping process was based on 3D printing using polylactic acid (PLA); also, the actuators were servomotors DS3218, the pressure sensors were RP-C7.6-LT, and the microcontroller was Arduino Nano. The system has been validated by the Institute of Research in Biomedical Sciences (INICIB) at the Ricardo Palma University, where the novelty of this work lies in the introduction of a new mobile-prismatic joint mechanism. In conclusion, favorable results were achieved regarding the complete flexion and extension of the fingers (91.6% acceptance rate, tested in 100 subjects), so the next step proposes that the wearable device will be used in the Physical Medicine and Rehabilitation Departments of Medical Centers. Doi: 10.28991/ESJ-2024-08-06-02 Full Text: PDF
Enterprise Innovation Decision-Making Towards Green and Sustainability from the Perspective of Cognitive Innovation Tran, Thi Anh Phuong; Hou, Xinshuo
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-013

Abstract

Although numerous current studies on green consumption and sustainable enterprise development have been carried out, the majority of them examined the issues from customers' viewpoints. This study aims to explore the mechanism that shapes firm innovation decision-making in the context of green and sustainable development from the perspective of business awareness under the impact of customer expectations. The study conducted an online survey (via Google Forms) with the participation of 301 employees from different enterprises in the Mekong Delta, Vietnam. To restrict the common method biases, Cronbach’s alpha was checked by using SPSS to ensure the reliability of the initial scales. Based on a deductive approach and testing hypotheses through evaluating the measurement model and structural model using SmartPLS software, the research results determined the mechanism of forming firm innovation decisions in this study via the impact of customer expectations as a stimulating factor leading to awareness of innovation. Customer expectations were positively associated with perceived marketing innovation. Perceived marketing innovation was not only positively associated with perceived process innovation but also related to firm innovation. Similarly, perceived process innovation was significantly positively associated with firm innovation. In alignment with research findings, significant practical and academic contributions were also proposed. Doi: 10.28991/ESJ-2024-08-06-013 Full Text: PDF
Organizational Climate Management in the Context of Initial Mathematics Teacher Education Sagredo-Lillo, Emilio; Zapata, Jorge L.; Parra-Urrea, Yocelyn; Llanos-Lagos, Exequiel
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-SIED1-018

Abstract

Objective: This study aims to analyze the impact of organizational management on motivation, satisfaction and commitment in teacher training in the context of Chilean quality assurance policies that emphasize a positive school climate and good coexistence. Methods: Using a Likert scale with a Cronbach’s alpha of 0.957, we surveyed 62 students in a mathematics teacher education program. A multiple linear regression analysis was conducted to examine how motivation, satisfaction, and engagement were related to organizational management and climate. Findings: The results show that motivation and satisfaction are significant predictors, explaining 61.5% of the variance in organizational management, while commitment also influences climate, but to a lesser extent. These results underscore the importance of motivation and satisfaction for effective organizational management and suggest that these factors may be more important than commitment in shaping a positive organizational climate. Novelty/Improvement:This study contributes to the literature by highlighting the need for management models that are tailored to specific educational contexts and calls for future research to examine additional variables that influence organizational climate in higher education to improve our understanding of the factors that influence educational environments. Doi: 10.28991/ESJ-2024-SIED1-018 Full Text: PDF
Towards the Study of Professional Corporate Education in Terms of Its Thematic Focus and Outcomes Matulčíková, Marta; Breveníková, Daniela; Geršicová, Zuzana; Hanuliaková, Jana
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-SIED1-04

Abstract

Aim: The aim of the paper is to characterize how the time for training employees in individual thematic areas is related to the outcomes and changes, facilitated by individual educational activities. Methods: The questionnaire method and interviewing methods were applied for obtaining data from respondents. The starting-point of empirical research was the knowledge and needs of the company, which perceives education as an investment. The respondent sample included 370 lectors/instructors and managers from three countries. The research was conducted in selected companies of section C − Manufacturing, Statistical Classification of Economic Activities. Basic variables include the number of training hours and results of the changes after training activities. Three groups of employee education are analysed: general training, performance-oriented training and digital training. Findings: Our division of educational activities into three groups enables the fulfilment of the basic European Commission targets for the 2021−2027 programme. Recommendations: Invest in developing new skills through future corporate training in the context of innovative transformation of the economy for a smarter Europe. Create conditions for better utilisation of human potential by eliminating the discrepancy between offered and required skills. Novelty of the paper:international comparison of educational activities, focus on the smart Europe and transformation to Industry 4.0. Doi: 10.28991/ESJ-2024-SIED1-04 Full Text: PDF
Government Policy Influence on Land Use and Land Cover Changes: A 30-Year Analysis Rattanarat, Jantira; Jaroensutasinee, Krisanadej; Jaroensutasinee, Mullica; Sparrow, Elena B.
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-2024-08-05-06

Abstract

This 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: PDF
A New Concept of Techno-Economic Institutions within Institutional Economics: Integrating Technologies and Institutional Frameworks Shkalenko, Anna V.; Kozlova, Svetlana 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-2024-08-05-022

Abstract

This study investigates the concept of techno-economic institutions within institutional economics, focusing on the integration of technologies into economic frameworks to foster development. The primary objective is to introduce and advocate for the novel concept of “techno-economic institutions,” which is essential for embedding technologies into the socio-economic environment. This research employs a comprehensive methodological approach, including theoretical analysis, literature review, comparative studies, and case studies, to develop a new analytical model and provide fresh insights. The key findings include a comparative analysis of the interplay between institutions and technologies, a variational model detailing the life cycles of General-Purpose Technologies (GPTs), and an in-depth examination of institutional roles. The econometric models developed in this study demonstrate the significant impact of ICT patents and SCM systems on government efficiency, empirically validating the proposed theoretical framework. This paper contributes to the academic discourse by offering a methodologically robust and empirically substantiated examination of technological advancements in institutional frameworks, highlighting the importance of flexible institutional structures capable of adapting to technological change. These insights provide actionable recommendations for policymakers and suggest strategic investments in technological infrastructure to enhance government performance. Future research should explore the generalizability of these findings in different institutional contexts and examine variability in technology-institution interactions across diverse geopolitical landscapes. Doi: 10.28991/ESJ-2024-08-05-022 Full Text: PDF
PM2.5 IoT Sensor Calibration and Implementation Issues Including Machine Learning Srisang, Wacharapong; Jaroensutasinee, Krisanadej; Jaroensutasinee, Mullica; Khongthong, Chonthicha; Piamonte, John Rex P.; Sparrow, Elena B.
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-08

Abstract

Affordable IoT PM2.5 sensors, enabled by the Internet of Things, offer new ways to monitor air quality. However, concerns exist about their data accuracy. This study aimed (1) to investigate the low-cost PM sensor's performance under various outdoor ambient circumstances and (2) to evaluate seven calibration methods, which include decision trees, gradient-boosted trees, linear regression, nearest neighbors, neural networks, random forests, and the Gaussian Process. The Davis AirLink was used as a reference to compare the Plantower PMS3003 sensor's performance. The data from the Plantower PMS3003 sensor were then compared to the Davis AirLink values using calibration curves created by machine learning algorithms. Calibration curves were generated using machine learning algorithms trained on sensor measurements collected in two Thai cities (Nakhon Si Thammarat and Phuket). Our results show that all machine learning methods outperformed traditional linear regression, with decision trees and neural networks demonstrating the most significant improvement. This research highlights the need for sensor calibration and the limitations of current calibration methods and paves the way for advancements in cloud-based calibration and machine learning for improved data accuracy in IoT PM2.5sensor technology. Doi: 10.28991/ESJ-2024-08-06-08 Full Text: PDF
SlowFast-TCN: A Deep Learning Approach for Visual Speech Recognition Ha, Nicole Yah Yie; Ong, Lee-Yeng; Leow, Meng-Chew
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-024

Abstract

Visual Speech Recognition (VSR), commonly referred to as automated lip-reading, is an emerging technology that interprets speech by visually analyzing lip movements. A challenge in VSR where visually distinct words produce similar lip movements is known as homopheme problem. Visemes are the basic visual units of speech that are produced by the lip movements and positions. Furthermore, visemes are typically having shorter durations than words. Consequently, there is less temporal information for distinguishing between different viseme classes, leading to increased visual ambiguity during classification. To address this challenge, viseme classification must not only extract lip image spatial features, but also to handle visemes of varying durations and temporal features. Therefore, this study proposed a new deep learning approach SlowFast-TCN. SlowFast network is used as the frontend architecture to extract the spatio-temporal features of the slow and fast pathways. Temporal Convolutional Network (TCN) is used as the backend architecture to learn the features from the frontend to perform the classification. A comparative ablation analysis to dissect each component of the proposed SlowFast-TCN is performed to evaluate the impact of each component. This study utilizes a benchmark dataset, Lip Reading in Wild (LRW), that focuses on English language. Two subsets of the LRW dataset, comprising of homopheme words and unique words, represent the homophemic and non-homophemic dataset, respectively. The proposed approach is evaluated on varying lighting conditions to assess its performance in real-world scenarios. It was found that illumination can significantly affect the visual data. Key performance metrics, such as accuracy and loss are used to evaluate the effectiveness of the proposed approach. The proposed approach outperforms traditional baseline models in accuracy while maintaining competitive execution time. Its dual-pathway architecture effectively captures both long-term dependencies and short-term motions, leading to better performance in both homophemic and non-homophemic datasets. However, it is less robust when dealing with non-ideal lighting scenarios, indicating the need for further enhancements to handle diverse lighting scenarios. Doi: 10.28991/ESJ-2024-08-06-024 Full Text: PDF
Effect of Gadolinium Doping on the Structure of Ce1-xGdxO2-x/2 Solid Solutions Prepared by Ionic Gelation Approach Ilcheva, V.; Boev, V.; Lefterova, E.; Avdeev, G.; Dimitrov, O.; Bojanova, N.; Kolev, H.; Petkova, T.
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-2024-08-05-01

Abstract

The current research aims to present the structural characterization of Gd-doped ceria powders and ceramics, investigating the structural evolution resulting from cerium substitution with Gd across the entire composition range from 0 to 100 mol.% Gd2O3. Ce1-xGdxO2-x/2 powders with varying Gd contents (0 ≤ x ≤ 1) were synthesized using the ionic gelation method followed by thermal annealing. The resulting powders were subjected to high-temperature treatment to obtain ceramics. Characterization methods included X-ray diffraction (XRD) to identify phase composition and confirm the formation of Ce1-xGdxO2-x/2 solid solutions, infrared spectroscopy (IR) and scanning electron microscopy (SEM) for structural and morphological studies, and X-ray photoelectron spectroscopy (XPS) to evaluate the electronic structure. Comparative analysis of Gd-doped calcined powders and sintered pellets revealed the impact of thermal treatment on the structural features of the resulting solid solutions, elucidating the influence of gadolinium substitution. The novelty of this research lies in demonstrating the successful preparation of Ce1-xGdxO2-x/2solid solutions via an alginate-mediated ion-exchange process and providing a detailed structural investigation over the entire range of dopant concentrations. This assessment highlights the feasibility for further research of these materials as suitable candidates for intermediate-temperature solid oxide fuel cells (IT-SOFCs) or catalyst applications. Doi: 10.28991/ESJ-2024-08-05-01 Full Text: PDF
Effects of Social Media Marketing Activities on Perceived Values, Online Brand Engagement, and Brand Loyalty Nguyen, Ngoc Minh; Nguyen, Huyen Thi; Cao, Thao Anh
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-2024-08-05-017

Abstract

This study aims to validate the model on the effects of social media marketing activities on the perceived values of social media marketing activities and the effects of these perceived values on online brand engagement and, consequently, on brand loyalty. The data used in this study were collected through an online self-administered survey of 501 young social media users in Vietnam. Partial Least Squares Algorithm, Bootstrapping, PLSpredict/CVPAT, and Multi-Group Analysis methods embedded in Smart-PLS software were used to validate the measurement model and test the research hypotheses. The findings confirm that the positive effects of social media marketing activities on brand loyalty are transmitted through the perceived values of these activities and online brand engagement. These effects are more substantial for luxury brands compared to non-luxury brands. Importantly, our study offers a new approach to explaining the impact of social media marketing activities on brand loyalty by focusing on the perceived values of these activities and their effects on online brand engagement. To enhance brand loyalty, businesses should prioritize creating hedonic and utilitarian values through their social media marketing activities and use these values and online brand engagement as key performance indicators for planning and controlling their strategies. Doi: 10.28991/ESJ-2024-08-05-017 Full Text: PDF

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