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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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Methodology for the Application of Nonparametric Control Charts into Practice Tereza Smajdorová; Darja Noskievičová
Emerging Science Journal Vol 4, No 4 (2020): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01230

Abstract

Classical parametric statistical methods are based on several basic assumptions about data (normality, independence, constant mean and variance). Unfortunately, these assumptions are not always fulfilled in practice, whether due to problems arising during manufacturing or because these properties are not typical for some processes. Either way, when we apply parametric methods to such data, whether Shewhart’s or other types of parametric control charts, it is not guaranteed that they will provide the right results. For these cases, reliable nonparametric statistical methods were developed, which are not affected by breaking assumptions about the data. Nonparametric methods try to provide suitable procedures to replace commonly used parametric statistical methods. The aim of this paper is to introduce the reader to an alternative way of evaluating the statistical stability of the process, in cases where the basic assumptions about the data are not met. First, possible deviations from the data assumptions that must be met in order to use classical Shewhart control charts were defined. Subsequently, simulations were performed to determine which nonparametric control chart was better suited for which type of data assumption violation. First, simulations were performed for the in-control process. Then simulations for an out-of-control process were performed. This is for situations with an isolated and persistent deviation. Based on the performed simulations, flow charts were created. These flow charts give the reader an overview of the possibilities of using nonparametric control charts in various situations. Based on the performed simulations and subsequent verification of the methodology on real data, it was found that nonparametric control charts are a suitable alternative to the standard Shewhart control charts in cases where the basic assumptions about the data are not met.
A Machine Learning Approach to Predict Creatine Kinase Test Results Zehra Nur Canbolat; Gökhan Silahtaroğlu; Özge Doğuç; Nevin Yılmaztürk
Emerging Science Journal Vol 4, No 4 (2020): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01231

Abstract

Most of the research done in the literature are based on statistical approaches and used for deriving reference limits based on lab results. As more data are available to the researchers, ML methods are more effectively used by the clinicians and practitioners to reduce cost and provide more accurate diagnoses. This study aims to contribute to the medical laboratory processes by providing an automated method in order to predict the lab results accurately by machine learning from the previous test results. All patient data obtained have been anonymized, and a total of 449,471 test results have been used to build an integrated dataset. A total of 107,646 unique patients’ data has been used. This study aims to predict the value range of the Creatine Kinase tests, which are taken in separate tubes and usually needs more processing time than the other tests do. Using the lab results and the Random Forest Algorithm, this study reports that the outcome of the Creatine Kinase test can be determined with 97% accuracy by using the AST and ALT test values. This is an important achievement for the practitioners and the patients, as this study submits significant reduction in Creating Kinase test evaluation time.
The Impact of Foreign Direct Investment on Unemployment: Panel Data Approach Alalawneh, Mustafa Mohammad; Nessa, Azizun
Emerging Science Journal Vol 4, No 4 (2020): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01226

Abstract

The purpose of this study was to investigate the impact of foreign direct investment on unemployment in six countries in the Middle East and North Africa, Egypt, Jordan, Lebanon, Morocco, Tunisia, and Turkey, as this region is considered one of the most regions in the world with a high rate of unemployment. The study employed panel data for the period from 1990 to 2018, where three economic models were used to examine the impact of FDI on unemployment, male unemployment, and female unemployment, in the long run, using the Fixed Effect Model (FEM) and Random Effect Model (REM), in addition to finding the causal relationship in the short term using Panel VAR (Granger causality tests). The results showed that FDI reduces the unemployment rate, the male unemployment rate, and the female unemployment rate in the long run. The results of the study also revealed that there is no causal relationship in the short term between FDI and unemployment in its various forms, while there is a bidirectional causal relationship between FDI and exports according to the three economic models. This paper is the first of its kind in terms of examining the effect of FDI on unemployment in the six countries as a grouped and a sample of the MENA region.
Parametric Study of an Organic Rankine Cycle Using Different Fluids Touaibi, Rabah; Koten, Hasan; Boydak, Ozlem
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01216

Abstract

This work is an energy study of an organic Rankine cycle (ORC) for the recovery of thermal energy by comparing three organic fluids. This cycle is considered to be a promising cycle for the conversion of heat into mechanical energy suitable for low temperature heat sources; it uses more volatile organic fluids than water, which generally has high molecular weights, thus allowing operating pressures at temperatures lower than those of the traditional Rankine cycle. A thermodynamic model was developed using the Engineering Equation Solver (EES) software to determine its performance using different working fluids (toluene, R245fa and R123) under the same operating conditions, taking into account the effect of certain operating parameters and the selection of organic fluids on cycle performance. The results obtained show that the toluene organic fluid has the best thermal efficiency of the cycle compared to the other fluids; 14.38% for toluene, 13.68% for R123 and 13.19 for R245fa.
Digital Readiness and Competitiveness of the EU Higher Education Institutions: The COVID-19 Pandemic Impact Grinberga Zalite, Gunta; Zvirbule, Andra
Emerging Science Journal Vol 4, No 4 (2020): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01232

Abstract

Nowadays, students expect that their university will not only provide a valuable source of practical knowledge for them, but will also be ready to offer appropriate distance learning opportunities both on a daily basis to diversify and enrich the study process experience and during global pandemic crises, which will probably be the reality of their lives in the next decades. The novelty and topicality of this study is justified by the need to assess the COVID-19 pandemic impact on the European Union higher education system and its adaptability to switch from traditional to remote study forms. The objectives of the study were: 1) to analyse the need to improve digital skills in the European Union by investigating the achievements of the Digital Economy and Society Index; 2) to assess the current digital environment of Latvian public universities and conduct an in-depth study of the digital environment of Latvia University of Life Sciences and Technologies. The research methodology is based on the desk study, social survey, comparative analysis and logical construction research methods. The results of the study revealed the digital gap that still exists between the more developed Nordic European countries and the less developed Southern and Eastern European countries. However, detailed analysis of the situation in Latvia leads to the conclusion that Latvian higher education institutions have significantly increased the amount of digital content in both external and internal communication systems and can offer competitive educational services that comply with the contemporary education requirements.
Integrating 3D Printing Technologies into Architectural Education as Design Tools Boumaraf, Hemza; Ä°nceoÄŸlu, Mehmet
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01211

Abstract

3D printing technology offers the chance to produce very small-scale, complex forms that could help to improve educational materials for architectural design. In this age of technological advances, architectural education needs to integrate modern teaching methods that could enhance students’ visual perception. This research thus examined the impact of computational design modeling and 3D printing technology on the spatial cognition of architecture students. It starts with the premise that the use of the 3D printed models will support design logic and improve the deep understanding of spatial perception among students. Thirty architecture students were asked about a designed project realized for the purpose of this study. They were presented both a project designed via computer modeling software and a printed model of the same project. The outcomes indicate that the use of 3D printing gave better results in the development of students’ spatial abilities. The findings also confirm that adopting this technology in the development of teaching tools will enhance students’ spatial perception and extend beyond the seamless materialization of the digital model which can continuously inform design ideation through emerging perception qualities.
Analyzing Navigational Data and Predicting Student Grades Using Support Vector Machine Damuluri, SriUdaya; Islam, Khondkar; Ahmadi, Pouyan; Qureshi, Namra Shafiq
Emerging Science Journal Vol 4, No 4 (2020): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01227

Abstract

The advent of Learning Management System (LMS) has unfolded a unique opportunity to predict student grades well in advance which benefits both students and educational institutions. The objective of this study is to investigate student access patterns and navigational data of Blackboard (Bb), a form of LMS, to forecast final grades. This research study consists of students who are pursuing a Networking course in Information Science and Technology Department (IST) at George Mason University (GMU). The gathered data consists of a wide variety of attributes, such as the amount of time spent on lecture slides and other learning materials, number of times course contents are accessed, time and days of the week study material is reviewed, and student grades in various assessments. By analyzing these predictors using Support Vector Machine, one of the most efficient classification algorithms available, we are able to project final grades of students and identify those individuals who are at risk for failing the course so that they can receive proper guidance from instructors. After comparing actual grades with predicted grades, it is concluded that our developed model is able to accurately predict grades of 70% of the students. This study stands unique as it is the first to employ solely online LMS data to successfully deduce academic outcomes of students.
European Nordic Countries Stock Market Listed Companies’: Factor and Cluster Analysis Approach Aija Pilvere-Javorska; Irina Pilvere
Emerging Science Journal Vol 4, No 6 (2020): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01244

Abstract

Public financial markets are crucial in the access to the funding and as a platform for investments to the investors in today’s world. Nordic European Union countries such as Sweden, Finland and Denmark are considered to have advanced and well-developed stock markets, while neighboring three Baltic States have rather small stock market. Backbone of the stock market are there listed companies. In this analysis authors attempt to analyze 510 Nordic countries listed companies’ absolute value indicators using factor and cluster analysis and to compare results with similar analysis of the Baltic States. Factor and cluster analysis revealed the homogeneity of Nordic countries stock market listed companies’ absolute values, authors obtained three complex factors, explaining 89% of dispersion within the indicators, which in turn resulted in being able to obtain the portrait of Nordic States stock market listed company. Similar results were obtained for Baltic States listed companies, though on different scale. Authors have not seen as detailed analysis of Nordic Stock market on the level of listed companies financial statement analysis. Time period covered in this research of the financials are from 2004 to 2018. The analysis could be beneficial for other researchers focusing on the Nordic region stock market companies and also to the policy makers in the Baltic States, how the neighboring well-developed countries indicators could be interpreted and obtained results used for the enhancement of Baltic States stock market. Doi: 10.28991/esj-2020-01244 Full Text: PDF
Explaining an Adoption and Continuance Intention to Use Contactless Payment Technologies: During the COVID-19 Pandemic Wilert Puriwat; Suchart Tripopsakul
Emerging Science Journal Vol 5, No 1 (2021): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01260

Abstract

The COVID-19 pandemic has affected the lives of people and services, pushing them toward new technologies that are in step with the development of a “New Normal” way of life. Contactless technologies have been realized as a mechanism to reduce the risks of infection, accelerating the move to touchless behaviors. The purpose of this study is to develop an Integrated Expectation-Confirmation and Health Belief Model (ECHBM) to explain an adoption and continuance intention to use contactless technologies during the COVID-19 pandemic in Thailand. Based on an empirical research survey of 142 samples, the proposed conceptual model was empirically validated using structural equation modelling (SEM). The study found that perceived usefulness, perceived susceptibility, perceived seriousness, and satisfaction significantly influenced continuance usage intention of contactless payment technologies, whereas perceived usefulness and confirmation were found to be significant determinants of consumer satisfaction. The effect of perceived susceptibility was found to be relatively higher than that of satisfaction, and confirmation was found to have an indirect effect on continuance usage intention through perceived usefulness and satisfaction. The integrated ECHBM model has strong explanatory power (56.8%) to predict customers’ continuance usage intention toward use of contactless payment technologies during the COVID-19 pandemic. The study proposes a novel challenge to explain an adoption and continuance intention to use contactless payment technologies as a protective health behavior to mitigate risks of being infected by COVID-19. Doi: 10.28991/esj-2021-01260 Full Text: PDF
Digital Transformation: Opportunities and Challenges for Leaders in the Emerging Countries in Response to Covid-19 Pandemic Thanh Nguyen Hai; Quang Nguyen Van; Mai Nguyen Thi Tuyet
Emerging Science Journal Vol 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-03

Abstract

Digital transformation is in a period of strong development, playing an important role in the development of public and private organizations. Its implications are still being clarified. However, up to now, the category of digital transformation has many different conceptions. Therefore, the objective of the paper contributes to the interpretation and discovery of the perception of digital transformation, the cognitive development of digital transformation, the positive aspects of the digital transformation process, the achievements achieved, the urgency of the digital transformation before the impact of the Covid-19 pandemic and challenges and limitations in the initiative of the contingent of civil servants and leaders in the digital transformation process. The research method is mainly based on the available documents from journals, books, research works, and the views of the authors expressed on the websites as a basis for making the analysis evaluate. The discoveries in the research will contribute to building the theoretical basis and direction in making some suggestions for leaders. In practical terms, research has shown that digital transformation can be a challenge, but perceive and prepare for leadership thinking innovation that drives successful digital transformation across countries, especially emerging countries is essential. Doi: 10.28991/esj-2021-SPER-03 Full Text: PDF

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