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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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Determinants Affecting the Use of the Internet by Older People Blanka Klimova; Pavel Prazak; Petra Poulova; Ivana Simonova
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01317

Abstract

Objectives: The purpose of this study is to detect and analyze some factors which hinder or contribute to the positive use of the Internet by older people living in Central Europe, specifically in one region of the Czech Republic. Methods: The key method is a questionnaire whose results were processed by using a model of logistic regression. The research sample includes 432 seniors from senior houses, municipal ICT courses and the University of the Third Age, all coming from the region of Hradec Kralove in the Czech Republic. Findings: The findings of the proposed model confirmed that the key determinants in the Internet use by older people were age, previous experience with IT in their past occupation and active use of IT enhanced by some kind of training, in this case attending IT courses of the University of the Third Age. Education and gender have not proved to be significant determinants in this study. Novelty/ improvement: The introduced model of logistic regression enriches current literature on the subject by emphasizing the possible factors that influence the use of the Internet by seniors in the region. The survey also investigates which factors in comparison with each other act more and which less, and which factors are significant within the model and which are not. Doi: 10.28991/esj-2021-01317 Full Text: PDF
Distribution Network Optimization with Scattered Generator Integration Using Immune-Clonal Selection Method Ramadoni Syahputra; Indah Soesanti
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01312

Abstract

This paper proposes distribution network optimization with scattered generator integration using the immune-clonal selection (ICS) method. Nowadays, the high popularity of scattered generators (SG) has made distribution networks essential to manage appropriately. This interest is because SG is usually injected into the distribution network due to the ease of accessing the network and the voltage level of the distribution network, which is easier for SG to reach. However, the presence of SG as a distribution network is increasingly dynamic, so that appropriate techniques are needed to achieve adequate network performance through network optimization. The ICS method is expected to be the right solution for this task. The ICS technique was chosen for its excellence in accurately optimizing for multi-objectives while avoiding premature convergence to local minima. The ICS approach was applied to IEEE model distribution networks of 33-bus and 71-bus. The optimization results show that the effectiveness and superiority of the ICS method, which is indicated by shallow power losses with a better voltage profile, and the load balance on each feeder is maintained. Doi: 10.28991/esj-2021-01312 Full Text: PDF
PID-based with Odometry for Trajectory Tracking Control on Four-wheel Omnidirectional Covid-19 Aromatherapy Robot . Iswanto; Alfian Ma’arif; Nia Maharani Raharja; Gatot Supangkat; Fitri Arofiati; Ravi Sekhar; Dhiya Uddin Rijalusalam
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-13

Abstract

Inhalation therapy is one of the most popular treatments for many pulmonary conditions. The proposed Covid-19 aromatherapy robot is a type of Unmanned Ground Vehicle (UGV) mobile robot that delivers therapeutic vaporized essential oils or drugs needed to prevent or treat Covid-19 infections. It uses four omnidirectional wheels with a controlled speed to possibly move in all directions according to its trajectory. All motors for straight, left, or right directions need to be controlled, or the robot will be off-target. The paper presents omnidirectional four-wheeled robot trajectory tracking control based on PID and odometry. The odometry was used to obtain the robot's position and orientation, creating the global map. PID-based controls are used for three purposes: motor speed control, heading control, and position control. The omnidirectional robot had successfully controlled the movement of its four wheels at low speed on the trajectory tracking with a performance criterion value of 0.1 for the IAEH, 4.0 for MAEH, 0.01 for RMSEH, 0.00 for RMSEXY, and 0.06 for REBS. According to the experiment results, the robot's linear velocity error rate is 2%, with an average test value of 1.3 percent. The robot heading effective error value on all trajectories is 0.6%. The robot's direction can be monitored and be maintained at the planned trajectory. Doi: 10.28991/esj-2021-SPER-13 Full Text: PDF
Nexus between FDI, Infrastructure Investment, Tourism Revenues, and Economic Growth: Mega Event Evidence Mustafa Mohammad Alalawneh; Jeyhun Mammadov; Ameen Alqasem
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01323

Abstract

The object of this study is to examine the response of economic growth in Germany to 2006 FIFA World Cup hosting (represented by the heavily influenced variables of this huge event: Growth of Infrastructure Spending, Tourism Revenues, and Foreign Direct investment) during the period (2000 – 2017). The study employed Dynamic Ordinary Least Square (DOLS) approach to estimate the long-run equilibrium relationships amongst the variables. The results indicate that there is a co-integrating long-run relationship among the studied variables and provide empirical evidence showing that an increase in the growth of infrastructure spending (GINFR) 1 unit leads to an increase in the growth of GDP (GGDP) by 0.374 unit, an increase in the tourism revenues (TR) 1 unit leads to increase in the growth of GDP (GGDP) by 0.155 unit, and an increase in foreign direct investment (FDI) 1 unit leads to an increase in the growth of GDP (GGDP) by 0.055 unit. What distinguishes this paper is that it is one of the rare studies that went beyond the short effect of mega-events on the host country and investigated the long-term economic impact of the most important macro variables associated with mega-events on economic growth. Doi: 10.28991/esj-2021-01323 Full Text: PDF
The Local Impact on the Concurrent Sentiment-Return Nexus: Asian versus European Markets Ngoc Bao Vuong; Yoshihisa Suzuki; Anh Tho To
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01318

Abstract

We examine the relationship between investor sentiment and contemporaneous returns in sixteen Asian and European stock markets between 2004 and 2016. To identify the sentiment-return nexus, we use the OLS models with Newey-West standard errors as well as the panel regressions with cross-country fixed effects and time dummies. We report the regional outcomes for Asia, Europe, and the individual markets. Our empirical results reveal a significant effect of sentiment on stock returns, although those effects are nonidentical across markets. We find the dissimilarities in the sentiment-return relationship among the sample markets are driven negatively by almost all national factors, with the strongest determinants being the development of financial institutions and the quality of regulation. The impact of cultural dimensions among the sample markets, on the contrary, is relatively weak and mixed. Our research is the first to compare Asian and European outcomes and reveal which region is more vulnerable to the influence of the local components. We detect that, except cultural aspects, European markets are more sensitive to country-specific characteristics than Asian ones. Doi: 10.28991/esj-2021-01318 Full Text: PDF
Cancellation Techniques for Co-channel Interference in MIMO-OFDM Systems and Evaluating Their Performance Varshini Rajesh; A. R. Abdul Rajak
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01313

Abstract

In a wireless communication system, the transmitted signal is exposed to various surfaces where it bounces and results in several delayed versions of the same signal at the receiver end. The delayed signals are in the form of electromagnetic waves that are diffracted and reflected from the various object surfaces. These result in co-channel interferences for wireless systems. MIMO has proven to be a striking solution for the new generation of wireless systems. MIMO-OFDM system with QPSK modulation is considered as the wireless system for studying the performance of interference cancellation techniques. The BER performance is studied in channels such as Rayleigh and Rician Fading Channels. The effects of interference are reduced to a certain extent by the inclusion of CDMA (spread spectrum technique) as Technique 1. The effects of interference on this system have been further reduced using the LMS filter as Technique 2. Hence, to show better performance in MIMO-OFDM systems, it is recommended to employ both CDMA and LMS filters to decrease the effects of co-channel interference. It is observed that the parameter BER reduces as the SNR increases for both these channels. Doi: 10.28991/esj-2021-01313 Full Text: PDF
Developing Methods and Algorithms for Cloud Computing Management Systems in Industrial Polymer Synthesis Processes Eldar Miftakhov; Svetlana Mustafina; Andrey Akimov; Oleg Larin; Alexei Gorlov
Emerging Science Journal Vol 5, No 6 (2021): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-01324

Abstract

To date, the resources and computational capacity of companies have been insufficient to evaluate the technological properties of emerging products based on mathematical modelling tools. Often, several calculations have to be performed with different initial data. A remote computing system using a high-performance cluster can overcome this challenge. This study aims to develop unified methods and algorithms for a remote computing management system for modelling polymer synthesis processes at a continuous production scale. The mathematical description of the problem-solving algorithms is based on a kinetic approach to process investigation. A conceptual scheme for the proposed service can be built as a multi-level architecture with distributed layers for data storage and computation. This approach provides the basis for a unified database of laboratory and computational experiments to address and solve promising problems in the use of neural network technologies in chemical kinetics. The methods and algorithms embedded in the system eliminate the need for model description. The operation of the system was tested by simulating the simultaneous statement and computation of 15 to 30 tasks for an industrially significant polymer production process. Analysis of the time required showed a nearly 10-fold increase in the rate of operation when managing a set of similar tasks. The analysis shows that the described formulation and solution of problems is more time-efficient and provides better production modes. Doi: 10.28991/esj-2021-01324 Full Text: PDF
Comparisons of SVM Kernels for Insurance Data Clustering Irfan Nurhidayat; Busayamas Pimpunchat; Samad Noeiaghdam; Unai Fernández-Gámiz
Emerging Science Journal Vol 6, No 4 (2022): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-04-014

Abstract

This paper will study insurance data clustering using Support Vector Machine (SVM) approaches. It investigates the optimum condition employing the three most popular kernels of SVM, i.e., linear, polynomial, and radial basis kernel. To explore sum insured datasets, kernel comparisons for Root Mean Square Error (RMSE) and density analysis have been provided. It employs these kernels to classify based on sum insured datasets. The objective of this research is to demonstrate to industrial researchers that data grouping may be accomplished in an organized, error-free, and efficient manner utilizing R programming and the SVM approach. In this study, we check the insurance data for the sum insured with statistical methods in the form of Model Performance Evaluation (MPE), Receiver Operating Characteristics (ROC), Area Under Curve (AUC), partial AUC (pAUC), smoothing, confidence intervals, and thresholds. Then, sum insured data are followed up to classify using SVM kernels. This paper finds new ideas for evaluating insurance data using the SVM approach with multiple kernels. This novel research emphasizes the statistical analysis methods for insurance data and uses the SVM method for more accurate data classification. Finally, it informs that this research is a pure finding, and there has never been any research on this subject. This research was conducted using the sum insured data as a sample from the Office of the Insurance Commission (OIC) in Thailand as an independent insurance institution providing actual data. Doi: 10.28991/ESJ-2022-06-04-014 Full Text: PDF
Sustainable Bank Performance Antecedents in the Covid-19 Pandemic Era: A Conceptual Model Steph Subanidja; Fangky Antoneus Sorongan; Mercurius Broto Legowo
Emerging Science Journal Vol 6, No 4 (2022): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-04-09

Abstract

The study proposes a conceptual model of sustainable bank performance antecedents in the Covid-19 Pandemic Era. This study uses a qualitative perspective. Data gathering is done using depth interviews with the Indonesian Central Bank, the Authority of Financial Services, and the National Commercial Banks Association members. Using ethnography analysis from interviews, focus group discussions, and previous studies shows that many variables affect the performance. However, the exogenous variable on performance is without precisely placing fintech and regulations as an antecedent. The study results then constructed the fintech and regulations as intervening and moderating variables for the performance, whereas the other variables were as business driver variables. The study's improvement is that fintech and regulations are the main antecedents for the performance during the pandemic. Fintech is not only an entity outside the bank but also an innovation inside the bank. Moreover, the other improvement is that the bank is not only an institution of customer trust but also an institution with a full touch of technology. Consequently, banks must adopt fintech, and cooperating with fintech entities is a wise choice. The study then proposes a conceptual model of sustainable bank performance that connects business drivers, fintech, and regulations. Doi: 10.28991/ESJ-2022-06-04-09 Full Text: PDF
Estimating Simultaneous Confidence Intervals for Multiple Contrasts of Means of Normal Distribution with Known Coefficients of Variation Kanyanatthanin Sodanin; Sa-Aat Niwitpong; Suparat Niwitpong
Emerging Science Journal Vol 6, No 4 (2022): August
Publisher : Ital Publication

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

Abstract

This study investigated the performance of simultaneous confidence intervals (SCIs) to differentiate the means of multiple normal population distributions with known coefficients of variation (CVs). The researchers aim to find the means of several normal distributions with known coefficients of variation, SCIMOVER, SCIs, and SCIk, which are extended to k populations. The authors constructed SCIs for the difference between multiple normal means with known coefficients of variation. There are three approaches: the method of variance estimates recovery approach (MOVER), and two central limit theorem approaches (CLT). A Monte Carlo simulation was used to evaluate the performance of the coverage probabilities and expected lengths of the methods. The simulation results indicate that the MOVER approach is more desirable than the CLT approaches in terms of the coverage probability. The performance of the proposed approaches is also compared using an example with real data. Moreover, the coverage probability results for SCIMOVER were over the nominal level of 0.95, indicating that it is more stable than SCIs and SCIkand was thus more appropriate for use in this scenario. Finally, the researchers suggest using the MOVER approach for constructing the SCIs to determine the variation to achieve the best solution in related fields in the near future. Doi: 10.28991/ESJ-2022-06-04-04 Full Text: PDF

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