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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 8 Documents
 1 
Search results for , issue "Vol 4, No 4 (2020): August" : 8 Documents clear
A Study on Multisecret-Sharing Schemes Based on Linear Codes Selda Çalkavur
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-2020-01229

Abstract

Secret sharing has been a subject of study since 1979. In the secret sharing schemes there are some participants and a dealer. The dealer chooses a secret. The main principle is to distribute a secret amongst a group of participants. Each of whom is called a share of the secret. The secret can be retrieved by participants. Clearly the participants combine their shares to reach the secret. One of the secret sharing schemes is  threshold secret sharing scheme. A  threshold secret sharing scheme is a method of distribution of information among  participants such that  can recover the secret but  cannot. The coding theory has been an important role in the constructing of the secret sharing schemes. Since the code of a symmetric  design is a linear code, this study is about the multisecret-sharing schemes based on the dual code  of  code  of a symmetric  design. We construct a multisecret-sharing scheme Blakley’s construction of secret sharing schemes using the binary codes of the symmetric design. Our scheme is a threshold secret sharing scheme. The access structure of the scheme has been described and shows its connection to the dual code. Furthermore, the number of minimal access elements has been formulated under certain conditions. We explain the security of this scheme.
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.
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.
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.
Multitasking in Knowledge Intensive Business Services Inese Suija-Markova; Liene Briede; Elīna Gaile-Sarkane; Iveta Ozoliņa-Ozola
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-2020-01233

Abstract

The objectives of this study were two-fold. First, to analyze multitasking activities in Knowledge Intensive Business Services (KIBS) and the employees’ perception of multitasking effects on individual and organizational performance. Second, to explore associations between the perception of multitasking and individual Time Management Orientation (TMO). The research study employed an online survey methodology. The questionnaire contained 56 questions organised in four groups. Methods of relationship analysis and regression analysis were applied to get answers to the research questions. The study indicated that the employees of surveyed KIBS were strongly engaged in multitasking activities in their workplaces. The informants estimated that on average they worked on nine different tasks per day. Additionally, their working days were filled with interruptions, caused either by external factors or self-interruptions. The majority of respondents also admitted that the ability to multitask was considered their job requirement, thus supporting the findings of other studies that KIBS do prefer multitasking employees. The effects of multitasking on individual and organizational performance were perceived ambiguously by the respondents. Meanwhile, the majority of respondents (above 70%), regardless of the level of polychronicity, admitted that they were able to make good decisions and concentrate better when they worked on one task at a time. The data analysis confirmed the findings reported earlier that individuals with more polychronic TMO did perceive multitasking as having more positive than negative effects both at the individual and organisational levels. Human multitasking has been widely researched in such fields as medicine, command and control, aviation, information technologies, but there is little detailed empirical evidence on multitasking in KIBS such as management consulting, research and development, architecture, engineering services, design, and advertising. Our research provides a fresh view on the human aspects of KIBS companies which can be of help in addressing the related managerial issues. The setting of the optimal number of tasks, task allocation considering employees’ individual differences, designing of workflows require further research as this may give the KIBS company managers guidelines and tools for organizing productive multitasking towards enhanced work efficiency and effectiveness and employees’ well-being.
An Analysis of the Transformation of Mega-Pharma’s Business Model toward the Emerging Market Yaeko Mitsumori
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-2020-01228

Abstract

The Trade-Related Aspects of Intellectual Property Rights（TRIPS) requires all member countries of the World Trade Organization (WTO) to introduce a TRIPS-compatible patent law into their countries. Due to the enforcement of TRIPS in 1995, India in 2005 revised its patent law and enacted the Patents (Amendment) Act, 2005. The 2005 ACT included product patent in pharmaceutical field. Due to the new patent law with product patent protection, large foreign capital pharmaceutical companies one after another re-entered the Indian market and started engaging in both R&D and production targeting the Indian market. However recent data shows the number of patent applications has been declining over the past several years and the number of patented drugs launched in India did not increase so rapidly. This study analyzes transitions of business models of foreign pharmaceutical companies in India based on the patent application data, and the trend of patented drugs in the market. A data analysis and a series of interviews with stakeholders were conducted. As a result of both a quantitative and a qualitative analysis, it was found that foreign pharmaceutical companies changed their strategies in the Indian pharmaceutical market. Since India was required to introduce product patents in the pharmaceutical area, there have been many arguments that once India introduces a product patent, the Indian pharmaceutical industry may decline due to the rapid introduction of foreign pharmaceutical products in the country; many academic papers were published in this context during that time. However, since 2005, when product patents were actually introduced in India, few academic papers were published. This study is unique as it discusses the effects of the introduction of product patents on the Indian pharmaceutical market.

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