• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.75-84
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• 2022

The efficiency of the regional fiscal policy implementation is based on the achievement of target criteria in the formation and distribution of own financial resources of local budgets, reducing their deficit and reducing dependence on transfers. It is also relevant to compare the development of financial autonomy of regions in the course of decentralisation of fiscal relations. The study consists in the cluster analysis of the effectiveness of fiscal policy implementation in the context of 24 regions and the capital city of Kyiv (except for temporarily occupied territories) under conditions of fiscal decentralisation. Clustering of the regions of Ukraine by 18 indicators of fiscal policy implementation efficiency was carried out using Ward's minimum variance method and k-means clustering algorithm. As a result, the regions of Ukraine are grouped into 5 homogeneous clusters. For each cluster measures were developed to increase own revenues and minimize dependence on official transfers to increase the level of financial autonomy of the regions. It has been proved that clustering algorithms are an effective tool in assessing the effectiveness of fiscal policy implementation at the regional level and stimulating further expansion of financial decentralisation of regions.

• Journal of Korea Trade
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• v.24 no.2
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• pp.68-82
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• 2020

Purpose - This study investigates the impact of inland port development in China on the promotion of bilateral trade flows between China and South Korea. Design/methodology - The probable association between the establishment of inland ports and Sino-Korea trade was estimated using gravity models. In this regards, two sets of data were collected. The first dataset consists of the baseline variables of a gravity model, while the second one includes variables of logistics infrastructure development. The indicators of logistics infrastructure development include inland ports, the amount of government expenditure on transport infrastructure, the lengths of roads and railways, the number of trucks and the number of logistics industry workforce. Findings - The results show that inland port development has a positive impact on facilitating bilateral trade between China and South Korea. However, the positive association holds only for Chinese regions with a large trade volume and a proximity to seaports. In other regions, the impact of inland ports is not statistically significant. Originality/value - To the best knowledge of the authors, this study is the first attempt to explore the economic impact of inland ports in China. In addition, the findings in this paper provide both policy and managerial implications for the future development of inland ports, such as the strategic location of inland ports and integrated intermodal operations.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.201-212
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• 2022

Prior to the emergence of Covid-19, Saudi Arabia (SA) had never faced the challenge of dealing with a global pandemic. Significantly, the current crisis has impacted all industries and sectors in the country, including the healthcare system, and has led to an emphasis on human life being more precious and valuable than economic profit. This study focuses on the impact of Covid-19 on the health of nurses, including their quality of life, during 2020. Understanding the position of the nursing profession during the pandemic, including the most effective methods of preventing work-related stress is important. Information was acquired through an online survey method (i.e. self-completion), known as the Expanded Nursing Stress Scale (ENSS), which was distributed to nurses in all regions of SA. It was found that the main aspects impacting nurses' work-related stress include gender, employment type, training, and dealing with infected patients. In addition, they highlight that such stress plays a substantial role in patient safety and nurses' satisfaction at work, as well as the future survival of organizations. The emergence of Covid-19 as a novel infectious disease has increased nurses' uncertainty and work-related stress. The results of this research will provide insights into the views of both nurses and their managers, in order to identify the main indicators of stress.

• Journal of Distribution Science
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• v.20 no.10
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• pp.67-77
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• 2022

Purpose: This study aims to determine the online shop service performance of fresh food products distribution, consumer motivation, and their relationship during the COVID-19 pandemic. Research design, data, and methodology: A survey was conducted online using Google Forms on 100 consumers of TaniHub application users. Data in the form of scale were analyzed descriptively to explain the service performance and consumer motivation. The service performance consists of technical services and marketing services. Technical service indicators consist of payment, delivery, and products. Meanwhile, the marketing service indicator consists of promotions and prices. The consumer motivation is characterized by reference, actualization, and lifestyle. The relationship between the two was analyzed using Spearman's rank correlation. Results: The most consumers are millennial generation who were active in social media. They are employees with Bachelor's and Master's qualifications and included in the middle economic groups. TaniHub online shop had good technical and fair marketing performance. The motivation of online shop consumers of fresh food products through the TaniHub application was high. Conclusions: The findings discovered a significant relationship between online shop service performance and consumer motivation. It indicates the need for improvement in marketing services, especially promotions, to improve the performance of this e-agribusiness company.

• New & Renewable Energy
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• v.19 no.2
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• pp.13-22
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• 2023

With the increased interest in renewable energy, various hydrogen production technologies have been developed. Hydrogen production can be classified into green, blue, gray, and pink hydrogen depending on the production method; each method has different technical performance, costs, and CO₂ emission characteristics. Hence, selecting the technology priorities that meet the company strategy is essential to develop technologically and economically feasible projects and achieve the national carbon neutrality targets. In addition, in early development technologies, analyzing the technology investment priorities based on the company's strategy and establishing investment decisions such as budget and human resources allocation is important. This study proposes a method of selecting priorities for various hydrogen production technologies as a specific implementation plan to achieve the national carbon neutrality goal. In particular, we analyze key performance indicators for technology, economic feasibility, and environmental performance by various candidate technologies and suggest ways to score them. As a result of the analysis using the aforementioned method, the priority of steam methane reforming (SMR) technology combined with carbon capture & storage (CCS) was established to be high in terms of achieving the national carbon neutrality goal.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.4
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• pp.449-461
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• 2023

The aim of this study was to conduct an ecosystem-based fishery risk assessment of tuna fisheries in the Western Indian Ocean. We selected gillnet, purse seine, hand line, baitboat, and longline fisheries as the target fisheries method, and selected longtail tuna (Thunnus tonggol), narrow-barred Spanish mackerel (Scomberomorus commerson), kawakawa (Euthynnus affinis), skipjack tuna (Katsuwonus pelamis), yellowfin tuna (T. albacares), bigeye tuna (T. obesus), albacore tuna (T. alalunga) and swordfish (Xiphias gladius) as the target species. The risk score for the size at the first capture in sustainability objective was high, especially, for the purse seine and baitboat fisheries using the fish aggregating devices (FADs). The risk score for the bycatch in the biodiversity objective was high for the gillnet fishery, and the gillnet fisheries using FADs showed high risks for the habitat quality objective due to the loss of the fishing gears. With regards to the socio-economic benefits objective, the risk score of the sales profits was low due to high sales of the tuna fisheries. The ecosystem risk score in the Western Indian Ocean was estimated to be moderate, although management is required for some of the indicators that have high-risk scores.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.53-70
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• 2022

Recently, due to the change to SASB(Sustainability Accounting Standards Board) and GRI(Global Reporting Initiative) Standards 2021, the paradigm for non-financial information disclosure is changing significantly, with the number of ESG topics and indicators that must be disclosed by industry from an autonomous material topic selection method. This study revealed that the number of compulsory topics in the oil and gas industry by GRI standards 2021 is up to 2.4 times higher than the average number of material topics disclosed when domestic companies publish sustainability reports using GRI Standards 2020. In the oil and gas industry, I analyzed the similarities and differences between the GRI standards 2021 and the ESG topics covered by SASB by environmental, social, economic, and governance areas. In addition, the materiality test process, which is different in GRI standards 2021, is introduced, and the issues included in the following 10 representative ESG-related initiatives are summarized into 62 and suggested improvement plans for materiality test used in the topic pool.

• The Plant Pathology Journal
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• v.39 no.4
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• pp.319-334
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• 2023

Plant disease is an important factor affecting crop yield. With various types and complex conditions, plant diseases cause serious economic losses, as well as modern agriculture constraints. Hence, rapid, accurate, and early identification of crop diseases is of great significance. Recent developments in deep learning, especially convolutional neural network (CNN), have shown impressive performance in plant disease classification. However, most of the existing datasets for plant disease classification are a single background environment rather than a real field environment. In addition, the classification can only obtain the category of a single disease and fail to obtain the location of multiple different diseases, which limits the practical application. Therefore, the object detection method based on CNN can overcome these shortcomings and has broad application prospects. In this study, an annotated apple leaf disease dataset in a real field environment was first constructed to compensate for the lack of existing datasets. Moreover, the Faster R-CNN and YOLOv3 architectures were trained to detect apple leaf diseases in our dataset. Finally, comparative experiments were conducted and a variety of evaluation indicators were analyzed. The experimental results demonstrate that deep learning algorithms represented by YOLOv3 and Faster R-CNN are feasible for plant disease detection and have their own strong points and weaknesses.

• Asian Journal for Public Opinion Research
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• v.11 no.4
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• pp.327-357
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• 2023

Adopting the Tools of Liberalism and Clash of Civilizations theories of international relations, this study examines the perceptions of 25,406 Arabs in 11 Arab countries as expressed in an Arab Barometer survey exploring their perceptions of violence against the United States (US), American citizens as "good," President Donald Trump's foreign policy in the Middle East, increasing economic relations with the US, and welcoming American foreign aid. As aspects of the Clash of Civilizations theory, this study examines religiosity, religious ritual practices, and political Islam and, as aspects of liberalism, this study explores the roles of online media as well as perceptions about US foreign aid in the prediction of the criterion variables. The findings suggest that religious indicators, and aspects of the Clash of Civilizations generally, were negative predictors of the perceptions, while social media and motivations for US foreign aid as aspects of liberalism, positively predicted the perceptions. The study discusses the results in relation to implications for policy makers.