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Emerging Science Journal
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2610-9182
Published by Ital Publication Homepage  [2 journals]
  • An Intelligent Controller Based on LAMDA for Speed Control of a
           Three-Phase Inductor Motor

    • Authors: Luis A. Morales, Paúl Fabara, David Fernando Pozo
      Pages: 676 - 690
      Abstract: Three-phase induction motors are widely used in the industrial field due to their low cost and robustness; therefore, it is essential to continuously develop new proposals that improve their behavior and response in applications where speed control is required. This paper proposes the development of an intelligent controller programmed in a PLC and interconnected with a three-phase induction motor through a VFD. The novel intelligent controller bases its operation on the LAMDA algorithm, which acts as a decision-making system based on the state of the error with respect to the speed reference and its derivative, obtaining a closed-loop controller. In addition, the VFD receives commands from the PLC to operate the motor at a constant voltage-frequency ratio in which flux remains constant. The proposed controller has been validated in two study cases: i) reference changes and ii) rejection of disturbances. The results obtained are promising and show a good performance of the LAMDA controller when compared qualitatively and quantitatively with the controller most commonly used in industrial systems, such as PID, and controllers with similar characteristics, such as fuzzy, based on Mamdani and Takagi-Sugeno inference. Doi: 10.28991/ESJ-2023-07-03-01 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-01
      Issue No: Vol. 7, No. 3 (2023)
  • State of Charge Estimation of Lead Acid Battery using Neural Network for
           Advanced Renewable Energy Systems

    • Authors: Ryo G. Widjaja, Muhammad Asrol, Iwan Agustono, Endang Djuana, Christian Harito, G. N. Elwirehardja, Bens Pardamean, Fergyanto E. Gunawan, Tim Pasang, Derrick Speaks, Eklas Hossain, Arief S. Budiman
      Pages: 691 - 703
      Abstract: The Solar Dryer Dome (SDD), an independent energy system equipped with Artificial Intelligence to support the drying process, has been developed. However, inaccurate state-of-charge (SOC) predictions in each battery cell resulted in the vulnerability of the battery to over-charging and over-discharging, which accelerated the battery performance degradation. This research aims to develop an accurate neural network model for predicting the SOC of battery-cell level. The model aims to maintain the battery cell balance under dynamic load applications. It is accompanied by a developed dashboard to monitor and provide crucial information for early maintenance of the battery in the SDD. The results show that the neural network estimates the SOC with the lowest MAE of 0.175, followed by the Random Forest and support vector machine methods with MAE of 0.223 and 0.259, respectively. A dashboard was developed to help farmers monitor batteries efficiently. This research contributes to battery-cell level SOC prediction and the dashboard for battery status monitoring. Doi: 10.28991/ESJ-2023-07-03-02 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-02
      Issue No: Vol. 7, No. 3 (2023)
  • Adaptive Learning and Integrated Use of Information Flow Forecasting

    • Authors: Ilya S. Lebedev, Mikhail E. Sukhoparov
      Pages: 704 - 723
      Abstract: This research aims to improve quality indicators in solving classification and regression problems based on the adaptive selection of various machine learning models on separate data samples from local segments. The proposed method combines different models and machine learning algorithms on individual subsamples in regression and classification problems based on calculating qualitative indicators and selecting the best models on local sample segments. Detecting data changes and time sequences makes it possible to form samples where the data have different properties (for example, variance, sample fraction, data span, and others). Data segmentation is used to search for trend changes in an algorithm for points in a time series and to provide analytical information. The experiment performance used actual data samples and, as a result, obtained experimental values of the loss function for various classifiers on individual segments and the entire sample. In terms of practical novelty, it is possible to use the obtained results to increase quality indicators in classification and regression problem solutions while developing models and machine learning methods. The proposed method makes it possible to increase classification quality indicators (F-measure, Accuracy, AUC) and forecasting (RMSE) by 1%–8% on average due to segmentation and the assignment of models with the best performance in individual segments. Doi: 10.28991/ESJ-2023-07-03-03 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-03
      Issue No: Vol. 7, No. 3 (2023)
  • Utilizing Machine Learning to Reassess the Predictability of Bank Stocks

    • Authors: Hera Antonopoulou, Leonidas Theodorakopoulos, Constantinos Halkiopoulos, Vicky Mamalougkou
      Pages: 724 - 732
      Abstract: Objectives: Accurate prediction of stock market returns is a very challenging task due to the volatile and non-linear nature of the financial stock markets. In this work, we consider conventional time series analysis techniques with additional information from the Google Trend website to predict stock price returns. We further utilize a machine learning algorithm, namely Random Forest, to predict the next day closing price of four Greek systemic banks. Methods/Analysis: The financial data considered in this work comprise Open, Close prices of stocks and Trading Volume. In the context of our analysis, these data are further used to create new variables that serve as additional inputs to the proposed machine learning based model. Specifically, we consider variables for each of the banks in the dataset, such as 7 DAYS MA,14 DAYS MA, 21 DAYS MA, 7 DAYS STD DEV and Volume. One step ahead out of sample prediction following the rolling window approach has been applied. Performance evaluation of the proposed model has been done using standard strategic indicators: RMSE and MAPE. Findings: Our results depict that the proposed models effectively predict the stock market prices, providing insight about the applicability of the proposed methodology scheme to various stock market price predictions. Novelty /Improvement: The originality of this study is that Machine Learning Methods highlighted by the Random Forest Technique were used to forecast the closing price of each stock in the Banking Sector for the following trading session. Doi: 10.28991/ESJ-2023-07-03-04 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-04
      Issue No: Vol. 7, No. 3 (2023)
  • Anticancer Activity Study of Modified Artocarpin Compound from Pudau Plant
           (Artocarpus kemando Miq.)

    • Authors: Tati Suhartati, Khalimatus Sa’diah, Yandri Yandri, Sutopo Hadi
      Pages: 733 - 743
      Abstract: This research is a continuation of the successful isolation of artocarpin from the root of Artocarpus kemando Miq reported in our previous study. In the previous study, the artocarpin was characterized with UV-Vis and FTIR techniques. In this follow-up investigation, the artocarpin was subjected to a transesterification reaction using acetic anhydride and pyridine as catalysts, and the product of the reaction was specified as compound 1. The compound 1 was further characterized with different techniques to gain more complete data and then tested for anticancer activity test against P-388 murine leukemia cells. Characterizations of the compound 1 using 1H-NMR and 13C-NMR techniques suggest that the modification reaction resulted in the conversion of the -OH groups at C2' and 4' at the artocarpin molecule to -OOCH3, and based on the MS analysis, the compound was proposed to have the molecular formula of C30H32O8. Another important feature of compound 1 that should be noted is the significant improvement in stability compared to the unmodified artocarpin. Anticancer activity tests against P-388 murine leukemia cells revealed that compound 1 has an IC50of 2.35 g/mL, confirming that the compound is categorized as an active anticancer agent and suggesting that the compound has promising potential that deserves further investigations. Doi: 10.28991/ESJ-2023-07-03-05 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-05
      Issue No: Vol. 7, No. 3 (2023)
  • Para-Social Interaction and Trust in Live-Streaming Sellers

    • Authors: Thoai Diem Phuong Mai, Anh Tho To, Thi Hong Minh Trinh, Thi Thoa Nguyen, Thi Thanh Trang Le
      Pages: 744 - 754
      Abstract: Live streaming is one of the modern methods that allows sellers to create, transmit, or broadcast some content on the internet in real-time, and it has been used by many small individual merchants. Understanding how live streaming contributes to online consumption is becoming increasingly important in social commerce as the live-streaming industry has grown more and more popular. However, the number of studies on live streaming is still quite limited in Vietnam. Therefore, this research will look at the mechanism that enables live streaming to boost customer trust in streamers. Using PLS-SEM on a sample of 360 respondents who viewed selling live streams on social network sites in Vietnam, we discovered that other members' endorsement, value similarity, hedonic value, and utilitarian value contribute to good para-social interaction. Next, utilitarian and hedonic values, streamer product expertise, and para-social interaction all positively affect trust in the streamers. The findings could help live-streaming sellers better understand their social interactions with viewers, resulting in increased customer trust. Doi: 10.28991/ESJ-2023-07-03-06 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-06
      Issue No: Vol. 7, No. 3 (2023)
  • Exploring the Asymmetric Effect of Internal and External Economic Factors
           on Poverty: A Fresh Insight from Nonlinear Autoregressive Distributive Lag

    • Authors: Rui M. Dantas, Shahzad Ali, Muhammad Rafiq, José Moleiro Martins, António Abreu, Mário Nuno Mata
      Pages: 755 - 767
      Abstract: Objective: This study examines the asymmetric impact of both internal (military, education, and health expenditures) and external (trade opening and foreign direct investment) factors that contribute to poverty reduction. Methodology: To find an asymmetric relationship between the proposed variables, we used a non-linear ARDL co-integration approach for the period ranging from 1981-2019. Findings: The findings of the study confirm the asymmetric impact of internal (education, military, health expenditures, quality of governance) and external (foreign direct investment, openness) factors on poverty. The finding confirms that ignoring nonlinear or asymmetric properties of macroeconomic variables may mislead inferences. This study has policy implications for government officials to reduce poverty. Novelty: theeconomic theory of poverty is studied from different perspectives by using internal and external factors that have direct and indirect effects on poverty. Furthermore, for in-depth analysis, a nonlinear approach is used to determine which factor has a strong contribution to eliminating poverty. Doi: 10.28991/ESJ-2023-07-03-07 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-07
      Issue No: Vol. 7, No. 3 (2023)
  • Impact of Corporate Social Responsibility on the Effectiveness of
           Companies' Business Activities

    • Authors: Marina V. Vasiljeva, Alexander N. Semin, Vadim V. Ponkratov, Nikolay V. Kuznetsov, Evgeniy V. Kostyrin, Nadezhda N. Semenova, Marina I. Ivleva, Angelina O. Zekiy, Natalia V. Ruban-Lazareva, Alexander L. Elyakov, Iskandar Muda
      Pages: 768 - 790
      Abstract: Background: Corporate social responsibility (CSR) has a great influence on the sustainability of company development, so it can be considered a business model for business effectiveness. Objective: The objective of the research is to determine the mutual influence of real-estate companies’ activities and CSR effectiveness in different countries. This study examines indicators for assessing companies’ financial stability, CSR, and working capital management's influence on the activity effectiveness of real-estate companies. Methods/Analysis: Questionnaires, the principal component method, the Sobel test, and linear regression analysis are used to evaluate the relationship between CSR and the business performance of autocratic management-style companies. The authors’ algorithm for assessing a company’s financial stability, CSR, and capital management, which affect the efficiency of companies, is proposed. Findings: Empirical analysis has shown that management has no mediating effect on CSR and enterprise performance relationships for companies with high financial stability and working capital, though it has a stimulating effect for low financial stability companies. CSR and business performance have positive relationships in companies, but despite financial stability growing, the autocratic leadership style reduces interest in CSR development. This paper conceptualizes the impacts of CSR on the effectiveness of companies. Novelty: The novelty of this study is to create theoretical and practical provisions aimed at laws and regulations. Doi: 10.28991/ESJ-2023-07-03-08 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-08
      Issue No: Vol. 7, No. 3 (2023)
  • Implementation of Takagi Sugeno Kang Fuzzy with Rough Set Theory and
           Mini-Batch Gradient Descent Uniform Regularization

    • Authors: Sugiyarto Surono, Zani Anjani Rafsanjani Hsm, Deshinta Arrova Dewi, Annisa Eka Haryati, Tommy Tanu Wijaya
      Pages: 791 - 798
      Abstract: The Takagi Sugeno Kang (TSK) fuzzy approach is popular since its output is either a constant or a function. Parameter identification and structure identification are the two key requirements for building the TSK fuzzy system. The input utilized in fuzzy TSK can have an impact on the number of rules produced in such a way that employing more data dimensions typically results in more rules, which causes rule complexity. This issue can be solved by employing a dimension reduction technique that reduces the number of dimensions in the data. After that, the resulting rules are improved with MBGD (Mini-Batch Gradient Descent), which is then altered with uniform regularization (UR). UR can enhance the classifier's fuzzy TSK generalization performance. This study looks at how the rough sets method can be used to reduce data dimensions and use Mini Batch Gradient Descent Uniform Regularization (MBGD-UR) to optimize the rules that come from TSK. 252 respondents' body fat data were utilized as the input, and the mean absolute percentage error (MAPE) was used to analyze the results. Jupyter Notebook software and the Python programming language are used for data processing. The analysis revealed that the MAPE value was 37%, falling into the moderate area. Doi: 10.28991/ESJ-2023-07-03-09 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-09
      Issue No: Vol. 7, No. 3 (2023)
  • Enhancing Learning Object Analysis through Fuzzy C-Means Clustering and
           Web Mining Methods

    • Authors: Meryem Amane, Karima Aissaoui, Mohammed Berrada
      Pages: 799 - 807
      Abstract: The development of learning objects (LO) and e-pedagogical practices has significantly influenced and changed the performance of e-learning systems. This development promotes a genuine sharing of resources and creates new opportunities for learners to explore them easily. Therefore, the need for a system of categorization for these objects becomes mandatory. In this vein, classification theories combined with web mining techniques can highlight the performance of these LOs and make them very useful for learners. This study consists of two main phases. First, we extract metadata from learning objects, using the algorithm of Web exploration techniques such as feature selection techniques, which are mainly implemented to find the best set of features that allow us to build useful models. The key role of feature selection in learning object classification is to identify pertinent features and eliminate redundant features from an excessively dimensional dataset. Second, we identify learning objects according to a particular form of similarity using Multi-Label Classification (MLC) based on Fuzzy C-Means (FCM) algorithms. As a clustering algorithm, Fuzzy C-Means is used to perform classification accuracy according to Euclidean distance metrics as similarity measurement. Finally, to assess the effectiveness of LOs with FCM, a series of experimental studies using a real-world dataset were conducted. The findings of this study indicate that the proposed approach exceeds the traditional approach and leads to viable results. Doi: 10.28991/ESJ-2023-07-03-010 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-010
      Issue No: Vol. 7, No. 3 (2023)
  • Numerical Schemes for Fractional Energy Balance Model of Climate Change
           with Diffusion Effects

    • Authors: Muhammad Shoaib Arif, Kamaleldin Abodayeh, Yasir Nawaz
      Pages: 808 - 820
      Abstract: This study aims to propose numerical schemes for fractional time discretization of partial differential equations (PDEs). The scheme is comprised of two stages. Using von Neumann stability analysis, we ensure the robustness of the scheme. The energy balance model for climate change is modified by adding source terms. The local stability analysis of the model is presented. Also, the fractional model in the form of PDEs with the effect of diffusion is given and solved by applying the proposed scheme. The proposed scheme is compared with the existing scheme, which shows a faster convergence of the presented scheme than the existing one. The effects of feedback, deep ocean heat uptake, and heat source parameters on global mean surface and deep ocean temperatures are displayed in graphs. The current study is cemented by the fact-based popular approximations of the surveys and modeling techniques, which have been the focus of several researchers for thousands of years.Mathematics Subject Classification:65P99, 86Axx, 35Fxx. Doi: 10.28991/ESJ-2023-07-03-011 Full Text: PDF
      PubDate: 2023-05-03
      DOI: 10.28991/ESJ-2023-07-03-011
      Issue No: Vol. 7, No. 3 (2023)
  • Characteristics and Antibacterial Properties of Film Membrane of
           Chitosan-Resveratrol for Wound Dressing

    • Authors: Basri A. Gani, Nur Asmah, Cut Soraya, Dharli Syafriza, Sri Rezeki, Muhammad Nazar, Subhaini Jakfar, Nurtami Soedarsono
      Pages: 821 - 842
      Abstract: The research aimed to evaluate the film membrane of Nano Chitosan Resveratrol (NCHR) for biological, physicochemical, and antibacterial properties. Psychochemically, the functional groups of chitosan compounds were examined by FTIR, chemical compounds by GCMS, and the morphology of chitosan and chemical elements by SEM-EDS. Biologically, the characteristics of NCHR were examined by solubility, swelling, permeability, and biodegradation tests. Meanwhile, the antibacterial properties were examined for inhibition of Porphyromonas gingivalis (P. gingivalis) ATCC 33277 by Minimal inhibition concentration (MIC) and growth assessment by spectrophotometry. Nano Chitosan (NCH) has appeared at 1033.85 cm-1 as a sharp peak indicating the P=O group and contains anti-toxicity compounds (Ethane, 1,1-diethoxy- (CAS) 1,1-Diethoxye) is 81.06% and antioxidant compounds Limonene is (1.28%). In addition, NCH has chemical elements, Oxygen Weight (69.4%), calcium (19.7%), magnesium (6.6%), and phosphorus (4.3%). NaCl 0.9%, PBS, and Aquades. In addition, it has an excellent index of water vapor transmission rate (WVTR) in all solvents (R2³ 0.95). The NCHR membrane film is bacteriostatic (≤ 300 CFU/mL) with each value of Minimal Inhibition Concentration (MIC) >15 mm. The Nano chitosan contains antitoxic, antioxidant, and antibacterial compounds with high oxygen elements. The film membrane of nano chitosan resveratrol can maintain the stability of changes in pH with a very high solubility index, swelling index, and WVTR index, as well as good biodegradation and antibacterial properties. Doi: 10.28991/ESJ-2023-07-03-012 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-012
      Issue No: Vol. 7, No. 3 (2023)
  • Human Resource Management across Generations within the Context of World
           of Work 4.0

    • Authors: Renta Skýpalová, Hana Stojanová, Hermann Troger, Zdeněk Caha
      Pages: 843 - 853
      Abstract: The aim of the paper is to evaluate the expectations of cohorts of workers from Generations X, Y, and Z with regards to their perceptions of what a "good workplace" is. Two research questions were formulated accordingly. Respondents representing workers from Generations X, Y, and Z, from Italy and Austria, were asked to consider and rate (on a 1-5 scale) eighteen criteria on work environment and managerial approach. Multi-sample testing was applied during processing with the ANOVA and Shapiro-Wilk and the Kruskal-Wallis test was subsequently used for multi-sample testing. The findings show that the most popular criterion for all three generational cohorts is "good work atmosphere", followed by "all employees are valued, treated, and rewarded fairly". Interestingly, generational differences were observed for "customer orientation", which was more important for Generation X, and "autonomous organization of work (time)", which was more important for Generations Y and Z. The most surprising result was the significance of corporate image, with less than 4% identifying this as an important issue across all three generations. These findings can help human resource managers create appropriate working environments and motivational tools that meet the real expectations of employees. Doi: 10.28991/ESJ-2023-07-03-013 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-013
      Issue No: Vol. 7, No. 3 (2023)
  • Mixed Tukey Exponentially Weighted Moving Average-Modified Exponentially
           Weighted Moving Average Control Chart for Process Monitoring

    • Authors: Khanittha Talordphop, Saowanit Sukparungsee, Yupaporn Areepong
      Pages: 854 - 866
      Abstract: The goal of this study is to present the mixed Tukey exponentially weighted moving average-modified exponentially weighted moving average control chart (MEME-TCC) for monitoring process location with symmetric and skewed distributions in an attempt to significantly improve detection ability. With the benefits of nonparametric assumption robustness. The average and median run lengths are supporting measurements for assessing the performance of a monitoring scheme using Monte Carlo simulation. Furthermore, the average extra quadratic loss (AEQL), relative mean index (RMI), and performance comparison index (PCI) can all be used to evaluate overall performance criteria. The proposed chart is compared with existing charts such as; EWMA, MEWMA, TCC, MEME, MMEE, and MMEE-TCC. The comparison result shows that the proposed chart is the best control chart for detecting small to moderate shifts among all distributional settings. Nevertheless, the EWMA chart detects large shifts more effectively than other charts, except in the case of the gamma distribution, where MEWMA performs best. The results of adapting the proposed control chart to two sets of real data corresponded to the research findings. Doi: 10.28991/ESJ-2023-07-03-014 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-014
      Issue No: Vol. 7, No. 3 (2023)
  • Demystifying Tourists’ Intention to Visit Destination on Travel Vlogs:
           Findings from PLS-SEM and fsQCA

    • Authors: Pantas H. Silaban, Wen-Kuo Chen, Bernard E Silaban, Andri Dayarana K. Silalahi, Ixora Javanisa Eunike, Hanna Meilani Damanik
      Pages: 867 - 889
      Abstract: With the advent of digital technologies (i.e., social media), tourism has evolved its marketing strategies. Even though published literature discusses the importance of tourism content on social media from various consumer perspectives, much more work must be done to examine how consumers make travel decisions based on tourism content. This study proposes a model for analyzing travel intent based on consumer motivations (e.g., novelty, entertainment, and relaxation) to watch social media travel videos. Consumers' travel intentions are influenced by trust and parasocial relationships. Through an online survey, 215 responses were collected and analyzed using a structural equation modeling (SEM) approach using Smart-PLS 3.0 and fuzzy set qualitative comparative analysis (fsQCA). In the study, relaxation ranked most highly among the three motivations for viewers to watch travel videos on YouTube for building parasocial relationships. In contrast, consumers seeking entertainment are more likely to form trust, which will result in consumers' intentions to travel. Based on intermediate solutions generated by the fsQCA, two causal configurations can be used to explain consumer travel decisions influenced by social media tourism content. The study also discusses theoretical and practical guidelines in depth. Doi: 10.28991/ESJ-2023-07-03-015 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-015
      Issue No: Vol. 7, No. 3 (2023)
  • An Empirical Analysis of Fintech's Impacts on the Financial
           Performance of Banks in Kosovo

    • Authors: Hiflobina Dermaku, Muhamet Hajdari, Kastriot Dermaku, Liridon Hoti
      Pages: 890 - 896
      Abstract: This analysis aims to empirically investigate the impact of different forms of Fintech on the financial performance of banks in Kosovo from 2010 to 2021. The research is based on secondary data, accounting for 48 observations at quarterly frequencies. The model treats bank performance (i.e., net profits of the bank sector) as an endogenous variable of ATMs, POS, and e-payments. The methodology applied in the research is based on the OLS technique and diagnostic tests for evaluating the normality of distribution, multicollinearity, autocorrelation, specification error, and heteroscedasticity. Results show that the variability of ATMs and e-payments determines bank performance variability. In particular, e-payments show a significant positive impact on bank profitability, whereas ATM payments display a negative impact on bank profitability. In addition, an increase in ATM payments by 1% decreases bank profitability by 0.367%. While an increase in e-payments by 1% increases bank profitability by 0.11%. The POS payments were found to have no significant relationship with bank profitability. Doi: 10.28991/ESJ-2023-07-03-016 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-016
      Issue No: Vol. 7, No. 3 (2023)
  • Economic and Mathematical Modeling for the Process Management of the
           Company's Financial Flows

    • Authors: Evgeniy Kostyrin, Daniil Rozanov
      Pages: 897 - 916
      Abstract: This paper presents an analysis of existing methods and models designed to solve the problem of planning the distribution of financial flows in the operational management cycle of the enterprise; it also offers tools for process management of enterprise financial flows based on the method of dynamic programming, which allows for determining the optimal combination of factors affecting the financial flow of the enterprise, taking into account existing restrictions on changes in the influencing parameters of the model. The current study develops an innovative model that maximizes the economic efficiency of investment in the sale of food products through retail chains and the practical implementation of the developed model based on the data from the financial reports of LLC "Kraft Heinz Vostok". The theoretical and methodological basis of the research includes the works of Russian and foreign experts in the fields of methodology of economic and mathematical modeling and decision-making, dynamic programming, system analysis, information approach to the analysis of systems, process management of enterprise financial flows, and human resource management. The author's methodology makes it possible to increase the company's profitability in key clients and categories in the range of 4 to 6 million dollars and to increase the return on investment by 10–17%. The scientifically innovative aim is to develop a toolkit for process management of enterprise financial flows, characterized by a systematic combination of methods of dynamic programming, social financial technologies, and economic evaluation of investments, which allows for the creation of mechanisms for managing the development of enterprises of all organizational and legal forms and the development of model projects of decision support systems with the prospects of their incorporation into existing information and analytical systems. Doi: 10.28991/ESJ-2023-07-03-017 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-017
      Issue No: Vol. 7, No. 3 (2023)
  • Taguchi Experiment Design for DES K2CO3-Glycerol Performance in RBDPO

    • Authors: Susila Arita, Leily Nurul Komariah, Winny Andalia, Fitri Hadiah, Cindi Ramayanti
      Pages: 917 - 927
      Abstract: Biodiesel production using novel glycerol and potassium carbonate-based catalysts has not been developed under the Taguchi technique. This study aims to determine the most influential parameter in biodiesel production from refined bleach-deodorized palm oil (RBDPO) using DES K2CO3-Glycerol as the novel catalyst. The raw material was subjected to transesterification at the desired reaction parameters estimated by the orthogonal 16-run (L16) approach with 2 levels and 4 factors of the Taguchi technique. Signal-to-noise ratio (SNR) and ANOVA were used to confirm the predicted value. From the results, the catalyst is the most influential variable in the TG value of biodiesel, placed in the first rank of the influence factor. Biodiesel production with a minimum total glycerol value (0.210%) using DES K2CO3-Glycerol as a catalyst is most optimally produced at 95 °C for 4 h and 400 rpm using 30 wt% methanol and 4 wt% catalysts achieved by the Taguchi technique. The biodiesel obtained from RBDPO complies with the required international standards. Doi: 10.28991/ESJ-2023-07-03-018 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-018
      Issue No: Vol. 7, No. 3 (2023)
  • Metaverse Technology in Communication Practices: A Case Study of IT
           Products Retailers in the UAE

    • Authors: Faycal Farhi, Riadh Jeljeli, Khaled Zamoum, Yamine Boudhane, Faten Ben Lagha
      Pages: 928 - 942
      Abstract: Introduction: Retail companies aim to provide their customers with improved customer support and public relations services. For this purpose, metaverse technology is one of the most preferred approaches to improving customers’ buying and post-purchase experiences. Aims: This research also examined metaverse technology acceptance among the IT products and services companies in the United Arab Emirates. Methods: The researchers employed a self-proposed study model and used the structural equation modeling approach. Results: Results revealed that relative advantage significantly affects customer support and public relations. However, transparency does not affect customer service and public relations significantly, while the effect of perceived compatibility on customer support remained insignificant while public relations remained significant. Finally, the effect of public relations on metaverse technological acceptance remained insignificant. Besides, the effect of customer support on metaverse technology acceptance remained significant. Overall, the results supported the role of certain factors proposed by the diffusion of innovation theory in the context of PR and customer support, which is further accelerating the metaverse technology adoption among the IT retailers in the UAE. Conclusion: Thus, this study concludes that the role and adoption of metaverse technology not only highlight its acceptance but also address its importance in improving IT retail products and services. Doi: 10.28991/ESJ-2023-07-03-019 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-019
      Issue No: Vol. 7, No. 3 (2023)
  • STEM Talent: A Game Changer in Organizational Digital Transformation

    • Authors: Piyawat Jriyasetapong, Supaporn Kiattisin, Smitti Darakorn Na Ayuthaya
      Pages: 943 - 962
      Abstract: Although organizational digital transformation (ODT) is implemented globally, Thailand and the Lao People's Democratic Republic do not possess the right factors for success under the tech-no-socio-economic paradigm. Organizations must modernize their capital resources, particularly their talent, in order to become agile, competitive, and resilient in the digital era. In this research, we identify and validate by proposing talent success factors and a framework for enabling and promoting ODT in Thailand and the Lao People's Democratic Republic. The statistical population consisted of 410 individuals who were observed in their digital businesses. Confirmatory factor analysis (CFA) shows that a four-factor model fits. The most influential factor for ODT was found to be transdisciplinary ontology talent (TOT), followed by mental model talent (MMT), enterprise architecture talent (EAT), and strategic agile talent (SAT). The findings demystified the four factors, entitled "STEM talent," in a comprehensive framework and its artifacts while explaining their respective influences. The article proposes a STEM talent and its framework for ODT with high potential, including but not limited to Thailand and the Lao People's Democratic Republic. Doi: 10.28991/ESJ-2023-07-03-020 Full Text: PDF
      PubDate: 2023-05-10
      DOI: 10.28991/ESJ-2023-07-03-020
      Issue No: Vol. 7, No. 3 (2023)
  • Concentration of B-CG and sFlt-1 in Rattus Norvegicus Model of
           Preeclampsia with Swimming Exercise Treatment

    • Authors: Oktalia Sabrida, Muslim Akmal, Sri Wahyuni, Khairan Khairan, Gholib Gholib
      Pages: 963 - 973
      Abstract: Preeclampsia (PE) is a life-threatening pregnancy complication for the mother and fetus. High concentrations of human chorionic gonadotrophin (hCG) and soluble fms-like tyrosine kinase-1 (sFLt-1) during pregnancy may have a role in the pathophysiology of PE. Swimming Exercise (SE) is one of the physical activities recommended for pregnant women and carries a minimal risk. This study is aimed at analyzing the interaction between the conditions of rats (normal and PE), the onset of PE (early onset and late onset), and the time of SE (SE 0 minutes; SE 5 minutes; SE 10 minutes) on the concentrations of B-CG and sFlt-1 in the Rattus norvegicus (R. norvegicus) model of PE. 72 R. norvegicus were included in this study and divided into 12 experimental groups (each group n = 6 individuals). R. norvegicus PE was prepared by inducing L-Nitro-Arginine-Methyl Ester (L-NAME) at a 75 mg/kg BW/day dose. The determination of PE was supported by the observation of differences in the values of urine protein (PU), urine glucose (GU), and urine leukocytes (LU) in R. norvegicus before and after injection of L-NAME. The three-factorial statistical test showed a significant interaction between the concentration of B-CG and the condition of R. norvegicus, the onset of PE, and the time of SE, with a p-value <0.001. The three-factorial statistical test also showed a significant interaction between the sFLt-1 concentration and the condition of R. norvegicus, the onset of PE, and the time of SE with p<0.05. The difference in the concentration of B-CG and sFLt-1 R. norvegicus in each treatment group was influenced by the condition of the rats (normal and PE), the onset of PE (early onset and late onset), and the time of SE (SE 0 minutes; SE 5 minutes; SE 10 minutes). Research related to SE on PE still needs to be continued to decide on recommendations on whether SE can be used as a preventive measure in complementary midwifery care for preventing and reducing symptoms of PE in pregnancy. Doi: 10.28991/ESJ-2023-07-03-021 Full Text: PDF
      PubDate: 2023-05-14
      DOI: 10.28991/ESJ-2023-07-03-021
      Issue No: Vol. 7, No. 3 (2023)
  • Global Metabolic Changes by Bacillus Cyclic Lipopeptide Extracts on Stress
           Responses of Para Rubber Leaf

    • Authors: Paiboon Tunsagool, Pongsakorn Kruaweangmol, Anurag Sunpapao, Arnannit Kuyyogsuy, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Wanwipa Vongsangnak
      Pages: 974 - 990
      Abstract: Changing environmental conditions can generate abiotic stress, such as the scarcity of water and exposure to chemicals. This includes biotic stress like Phytophthora palmivora infection, which causes leaf fall disease and inhibits the growth rate of para rubber seedlings, resulting in economic loss. To prevent abiotic and biotic stresses, biocontrol agents such as cyclic lipopeptides (CLPs) from Bacillus spp. have been introduced to reduce the use of chemically synthesized fungicides and fertilizers. This study aimed to use Bacillus CLP extracts as a biological agent to stimulate the plant growth system in para rubber seedlings under stress conditions compared with the exogenous plant hormone (salicylic acid, SA). CLP extracts obtained from B. subtilis PTKU12 and exogenous SA were applied to the leaves of para rubber seedlings. The extracted metabolites from each treatment were analyzed by untargeted metabolomics for metabolite identification and metabolic networks under stress responses. In both treatments, 1,702 and 979 metabolites were detected in the positive and negative ion modes of electrospray ionization, respectively. The differential analysis revealed that the accumulation of up-regulated metabolites in the treatment of CLP extracts was higher than in the exogenous SA treatment, belonging to 56 metabolic pathways. The analysis of metabolic pathways indicated that CLP extracts employed alanine, aspartate, and glutamate metabolisms for stress responses leading to plant growth promotion. These findings revealed that the metabolic network for plant growth promotion induced by BacillusCLP extracts could be considered a protective option for para rubber plantations. Doi: 10.28991/ESJ-2023-07-03-022 Full Text: PDF
      PubDate: 2023-05-14
      DOI: 10.28991/ESJ-2023-07-03-022
      Issue No: Vol. 7, No. 3 (2023)
  • Investigation of Ni- and Co-Based Bifunctional Electrocatalysts for
           Carbon-Free Air Electrodes Designed for Zinc-Air Batteries

    • Authors: Emiliya Mladenova, Miglena Slavova, Borislav Abrashev, Valentin Terziev, Blagoy Burdin, Gergana Raikova
      Pages: 991 - 1003
      Abstract: Ni- and Co-oxide materials have promising electrocatalytic properties towards the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR), and attract with low cost, availability, and environmental friendliness. The stability of these materials in alkaline media has made them the most studied candidates for practical applications such as a gas diffusion electrode (GDE) for rechargeable metal-air batteries. In this work, we propose a novel concept for a carbon-free gas GDE design. A mixture of catalyst (Co3O4, NiCo2O4) and polytetrafluoroethylene was hot pressed onto a stainless-steel mesh as the current collector. To enhance the electrical conductivity and, thus, increase ORR performances, up to 70 wt.% Ni powder was included. The GDEs produced in this way were examined in a half-cell configuration with a 6 M KOH electrolyte, stainless steel counter electrode, and hydrogen reference electrode at room temperature. Electrochemical tests were performed and coupled with microstructural observations to evaluate the properties of the present oxygen electrodes in terms of their bifunctionality and stability enhancement. The electrochemical behavior of the new types of gas-diffusion electrodes, Ni/Co3O4 and Ni/NiCo2O4, shows acceptable overpotentials for OER and ORR. Better mechanical and chemical stability of electrodes consisting of Ni/NiCo2O4 (70:30 wt.%) was registered. Doi: 10.28991/ESJ-2023-07-03-023 Full Text: PDF
      PubDate: 2023-05-14
      DOI: 10.28991/ESJ-2023-07-03-023
      Issue No: Vol. 7, No. 3 (2023)
  • Development of the “1+2+X” Modular Course System for Information
           Technology Majors from the Perspective of Dual-Mode IT

    • Authors: Ming Li, Hira Batool, Yun Mo, Guangyun Lu, Tuo Wang
      Pages: 1004 - 1018
      Abstract: As the third generation of IT is developing rapidly, higher education institutions in China are looking to produce innovation-minded talent who can adapt to the dual-mode IT work environments of modern enterprises to meet the demands of the intelligent manufacturing national development strategy. So, this research aims to specify the hierarchical talent training system and mechanism for information technology majors in the higher education system. A 1+2+X modular curriculum system was proposed for the information technology majors based on the group-chain development model that focuses on combining discipline and industry (also known as vertical and horizontal integration). The data analysis was performed through a comparative analysis of the talent training objectives of the Chinese institutes and course systems’ national development strategies. The results support the idea that the 1+2+X modular curriculum system can help universities produce innovation-minded talent by designing their curriculum based on the industry and trends rather than just focusing on specialization training. The novelty of this research is that it promotes the idea of professional development along with course training. This paper recommends that future researchers implement the concept in vocational institutes. Doi: 10.28991/ESJ-2023-07-03-024 Full Text: PDF
      PubDate: 2023-05-14
      DOI: 10.28991/ESJ-2023-07-03-024
      Issue No: Vol. 7, No. 3 (2023)
  • Overview on Case Study Penetration Testing Models Evaluation

    • Authors: Ahmad S. Al-Ahmad, Hasan Kahtan, Yehia I. Alzoubi
      Pages: 1019 - 1036
      Abstract: Model evaluation is a cornerstone of scientific research as it represents the findings' accuracy and model performance. A case study is commonly used in evaluating software engineering models. Due to criticism in terms of generalization from a single case study and testers, deciding on the number of case studies used for evaluation and the number of testers has been one of the researchers’ challenges. Multiple case studies with multiple testers can be difficult in some domains, such as penetration testing, due to the complexity and time needed to prepare test cases. This study aims to review the literature and examine the evaluation methods used pertaining to the number of case studies and testers involved. This study is beneficial for researchers, students, and penetration testers as it provides case study design steps that are useful to determine the appropriate number of test cases and testers required. The paper's findings and novelty highlight that a single case study with a single tester is enough to evaluate a model. It also strikes a balance between what is enough for the evaluation and the need to reduce criticisms of a single case study by using two case studies with a single tester. Doi: 10.28991/ESJ-2023-07-03-025 Full Text: PDF
      PubDate: 2023-05-14
      DOI: 10.28991/ESJ-2023-07-03-025
      Issue No: Vol. 7, No. 3 (2023)
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