Emerging Science Journal (ESJ)
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Assessment of the Development of the Circular Economy in the EU Countries: Comparative Analysis by Multiple Criteria Methods
Get PDFIn recent decades, attention to environmental resource management has increased worldwide. Circular economy (CE) is a concept that is increasingly being considered as a solution to this range of challenges. Therefore, it is important to monitor the development of CE. This research is an attempt to contribute to the CE surveillance literature by providing a framework for comparing the positions of states and their classifications. The main goal of the article is to assess the level of circular economy development in EU countries according to the chosen methodology. The indicators used in this study are sourced from the European Commission Monitoring Framework database, which includes data from 27 European Union (EU) countries over the time frame from 2016 to 2020. The analysis was carried out using Multi-Criteria Decision Methods (MCDM), such as Simple Additive Weighing (SAW), and the objective method of estimating weights in accordance with proportional differences (APROD), which helped to assess the state of CE. The results showed that EU countries can be divided into three groups based on the level of performance of the CE, and their level of development in relation to the circular economy is different. The level of circular economy development in most EU countries is low. Germany, the Netherlands, France, and Italy demonstrated the best positions. The study findings were derived from the combination of two MCDMs, thus increasing the refinement of the overall methodology. Doi: 10.28991/ESJ-2024-08-02-013 Full Text: PD
Asymmetric Role of Economic Growth, Globalization, Green Growth, and Renewable Energy in Achieving Environmental Sustainability
Get PDFThis study fills the gap in the literature by applying novel quantile regression and spectral Granger causality frameworks to evaluate the asymmetric effect of GDP, globalization, green growth, and renewable energy consumption on CO2 emissions in India. The results suggest that in all quantiles, green growth, globalization, and renewable energy consumption impact environmental quality negatively, and the effect of economic growth on CO2 emissions is positive in most of the quantiles. In addition, the nexus between the regressors and CO2 emissions is significant across different time horizons. More specifically, the results from the spectral Granger causality test unveil that all the indicators would predict CO2emissions across various time scales. Several policy implications have been proposed based on the research's findings so that India might move toward achieving sustainable development. Doi: 10.28991/ESJ-2024-08-02-05 Full Text: PD
Multilingual Question Answering for Malaysia History with Transformer-based Language Model
Get PDFIn natural language processing (NLP), a Question Answering System (QAS) refers to a system or model that is designed to understand and respond to user queries in natural language. As we navigate through the recent advancements in QAS, it can be observed that there is a paradigm shift of the methods used from traditional machine learning and deep learning approaches towards transformer-based language models. While significant progress has been made, the utilization of these models for historical QAS and the development of QAS for Malay language remain largely unexplored. This research aims to bridge the gaps, focusing on developing a Multilingual QAS for history of Malaysia by utilizing a transformer-based language model. The system development process encompasses various stages, including data collection, knowledge representation, data loading and pre-processing, document indexing and storing, and the establishment of a querying pipeline with the retriever and reader. A dataset with a collection of 100 articles, including web blogs related to the history of Malaysia, has been constructed, serving as the knowledge base for the proposed QAS. A significant aspect of this research is the use of the translated dataset in English instead of the raw dataset in Malay. This decision was made to leverage the effectiveness of well-established retriever and reader models that were trained on English data. Moreover, an evaluation dataset comprising 100 question-answer pairs has been created to evaluate the performance of the models. A comparative analysis of six different transformer-based language models, namely DeBERTaV3, BERT, ALBERT, ELECTRA, MiniLM, and RoBERTa, has been conducted, where the effectiveness of the models was examined through a series of experiments to determine the best reader model for the proposed QAS. The experimental results reveal that the proposed QAS achieved the best performance when employing RoBERTa as the reader model. Finally, the proposed QAS was deployed on Discord and equipped with multilingual support through the incorporation of language detection and translation modules, enabling it to handle queries in both Malay and English. Doi: 10.28991/ESJ-2024-08-02-019 Full Text: PD
Political Study Analyses of Education Policy to Improve Education Quality
Get PDFObjective: This case study analyzes the influence of political education policies on the educational standards in Aceh, Indonesia. Methods/Analysis: The study examines the impact of political stability and governance changes on educational frameworks and outcomes, specifically focusing on reforms made after 2005. The study used qualitative methods, analyzed data from interviews with educators, policymakers, and students, and reviewed relevant government documents and education statistics. Finding: Increased political autonomy in Aceh has led to a more culturally and regionally adapted education policy, improving student participation and learning. A more inclusive educational atmosphere for various students has been created by including local language and culture studies. According to the report, political stability also facilitates school finance and resource distribution, increasing infrastructure and teacher training. Balancing national education standards with local requirements and ensuring fair access to quality education in Aceh's districts remain challenges. According to the report, policymakers should spend in teacher training, infrastructure, and inclusive curriculum to preserve and strengthen Aceh education. Novelty/Improvement:Political stability and governance in Aceh have affected curriculum creation, teaching methods, and learning results, according to this study. These political dynamics present problems and opportunities for sustainable education programs, which the study examines. Doi: 10.28991/ESJ-2024-08-04-011 Full Text: PD
Optimizing Cr(VI) Reduction in Plastic Chromium Plating Wastewater: Particle Size, Irradiation, Titanium Dose
Get PDFThe preservation of the aquatic environment and water systems has been a fundamental objective that has led great scientists and researchers to seek new alternatives or techniques that allow the decontamination of water sources. The plastic chromium plating industries have been identified as important sources of contamination since their residues are characterized by having considerable amounts of hexavalent chromium Cr (VI), which alters the stability of water resources and can affect effluents on the surface and the subsoil. Given this problem, the need to improve the usual methods and techniques for wastewater treatment with more effective solutions, such as photocatalysis, which presents significant advantages over the inefficiency of traditional methods, is recognized. However, given the limited availability of research in the country that addresses the removal of hexavalent chromium from the wastewater of these industries, this work focuses on optimizing the process by varying conditions of variables such as particle size, catalyst dose, and irradiation time. The optimization of the photocatalysis process was evaluated using the Box-Behnken experimental design. The results show that contaminant removal occurred when the particle size was 0.177 mm. This particle size showed the highest photocatalytic activity, with 100% removal at 45 minutes. These findings represent a significant step towards solving the problem of contamination in this business sector by this pollutant and contribute to preserving our water resources. Doi: 10.28991/ESJ-2024-08-01-02 Full Text: PD
Exploring Individuals' Experiences with Security Attacks: A Text Mining and Qualitative Study
Get PDFCyber-attacks have become increasingly prevalent with the widespread integration of technology into various aspects of our lives. The surge in social media platform usage has prompted users to share their firsthand experiences with cyber-attacks. Despite this, previous literature has not extensively investigated individuals' experiences with these attacks. This study aims to comprehensively explore and analyze the content shared by cyber-attack victims in Saudi Arabia, encompassing text, video, and audio formats. The primary objective is to investigate the factors influencing victims' perceptions of the security risks associated with these attacks. Following data collection, preparation, and cleaning, Latent Dirichlet Allocation (LDA) is employed for topic modeling, shedding light on potential factors impacting victims. Sentiment analysis is then utilized to examine the nuanced negative and positive perceptions of individuals. NVivo is deployed for data inspection, facilitating the presentation of insightful inferences. Hierarchical clustering is implemented to explore distinct clusters within the textual dataset. The study's results underscore the critical importance of spreading awareness among individuals regarding the various tactics employed by cyber attackers. Doi: 10.28991/ESJ-2024-08-01-010 Full Text: PD
The Impact of Liquidity and Corporate Efficiency on Profitability
Get PDFThis study aims to investigate and determine the trend and extent of the impact of a company's liquidity and efficiency on profitability. Research data is collected on the audited financial statements of Vietnam's top 100 listed companies. Regression models (pooled OLS, FEM, and REM) and necessary tests are used to select the appropriate analysis model. Model defects are overcome by GLS regression. The research results confirm the strong, positive impact of liquidity, company efficiency, and company growth rate on profitability. In addition, the research results also demonstrate a significant negative impact between financial leverage and profitability. This article is the first study to simultaneously address the effects of liquidity and corporate efficiency on profitability. Furthermore, it is the first empirical study applying GLS regression to analyze the impact of liquidity and corporate efficiency on the top 100 listed companies in the Vietnamese market. This market provides an ideal analytical framework because of its heterogeneity in terms of its history of origin and development and its political, cultural, social, and governance characteristics. To make the research results more general, future studies can expand the scope of the survey to all companies listed on the stock market. Doi: 10.28991/ESJ-2024-08-01-013 Full Text: PD
System Parameters Sensitivity Analysis of Ocean Thermal Energy Conversion
Get PDFOcean Thermal Energy Conversion (OTEC) is a technology to harvest the solar energy stored in the ocean by utilizing the temperature difference between warm surface and cold deep seawater. Considering that the OTEC system works in a low-temperature range, the present paper assessed the technical resources comprehensively by acquiring in-situ thermocline data and conducting a sensitivity analysis of the system parameters. The in-situ temperature profile data were measured in the waters of North Bali, Indonesia. The temperature gradient data based on field measurements were then compared with the HYCOM consortium model. The data were then used as input in the OTEC power and efficiency estimation through a single-stage ranking cycle. The analysis was conducted by varying the type of working fluid, the performance of the heat exchanger, and the location to investigate how the system parameters influenced the power produced. Using an unusual combination of parameters made it difficult to analyze the resulting data multiple times. However, with reference-based analysis and the formulation of calculations, the sensitivity of each parameter could be assessed at both locations. As a result, the ammonia working fluid provided the highest net power output of the system but had the lowest efficiency of all working fluids. The heat exchanger performance in terms of net power and efficiency cannot be separated from the seawater mass flow requirement. This referred to the results where the heat exchanger with a temperature difference of 3°C before and after the seawater passed through the heat exchanger and produced the highest net power and efficiency. Additionally, the net power output reached its convergence level at a water depth of 400m for the Bungkulan site and 450m for Celukan Bawang, which was proportional to the thermocline tendency. Doi: 10.28991/ESJ-2024-08-02-04 Full Text: PD
Environmental Effects on Parameters of Leakage Current Equivalent Circuits of Outdoor Insulators
Get PDFThe performance of outdoor insulators in transmission lines may deteriorate due to aging and can even be enhanced by the presence of pollutants. Leakage current (LC) measurement is one of the most effective methods to diagnose the insulator condition, utilizing LC parameters such as magnitude and total harmonic distortion (THD). However, research on the interpretation of these parameters is still limited. This paper discusses the diagnostic method by simulation, employing the LC equivalent circuits of different types of insulators and examining the influence of environmental factors, such as humidity and pollutant levels. LC waveforms are first obtained through experiments on various insulator types, including traditional ceramic and glass insulators, advanced composite insulators, or the hybrid type of RTV silicone rubber-coated and conducting glazed insulators. Subsequently, simulations on the LC circuits of Suwarno's and Kizilcay's models are performed to obtain similar LC waveforms and properties. The values of the equivalent circuit parameters are then used to diagnose each insulator's characteristics and environmental effects. The results indicate that composite insulators of epoxy resin or SiR have a larger intrinsic resistance of ~40 GΩ and nonlinear resistance (a few MΩ to tens of GΩ), representing high surface resistance of the insulators against water and pollutants. A comparison of these parameters is expected to indicate the severity levels of insulator condition. Doi: 10.28991/ESJ-2024-08-01-022 Full Text: PD
Improving the Quality Indicators of Multilevel Data Sampling Processing Models Based on Unsupervised Clustering
Get PDFThis paper presents a solution for building and implementing data processing models and experimentally evaluates new possibilities for improving ensemble methods based on multilevel data processing models. This study proposes a model to reduce the cost of retraining models when transforming data properties. The research objective is to improve the quality indicators of machine learning models when solving classification problems. The novelty is a method that uses a multilevel architecture of data processing models to determine the current data properties in segments at different levels and assign algorithms with the best quality indicators. This method differs from the known ones by using several model levels that analyze data properties and assign the best models to individual segments of data and training. The improvement consists of using unsupervised clustering of data samples. The resulting clusters are separate subsamples for assigning the best machine-learning models and algorithms. Experimental values of quality indicators for different classifiers on the whole sample and different segments were obtained. The findings show that unsupervised clustering using multilevel models can significantly improve the quality indicators of "weak” classifiers. The quality indicators of individual classifiers improve when the number of data clusters is increased to a certain threshold. The results obtained are applicable to classification when developing models and machine learning methods. The proposed method improved the classification quality indicators by 2–9% due to segmentation and the assignment of models with the best quality indicators in individual segments. Doi: 10.28991/ESJ-2024-08-01-025 Full Text: PD