• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.3
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• pp.197-204
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• 2021

If a failure or an abnormal maneuver occurs during the flight test of a missile, the missile is deliberately self-destructed so as not to continue the flight. At this time, debris are produced and it is important to estimate the impact area in real-time whether it is out of the safety area. In this paper, we propose a method to estimate the debris dispersion area and falling time in real-time using a Fully-Connected Neural Network (FCNN). We applied the Unscented Transform (UT) to generate a large amount of training data. UT parameters were selected by comparing with Monte-Carlo (MC) simulation to secure reliability. Also, we analyzed the performance of the proposed method by comparing the estimation result of MC.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.113-122
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• 2021

This study aims to investigate the effects of fiscal policy instruments on economic growth in Jordan using annual data from 1970 to 2019, by applying the VAR model (Vector Auto regression) and the Vector Error Correction Model (VECM). The study also examines the dynamic relationship among economic variables over time using the Granger casualty test, Impulse Response Function, and Variance Decomposition. The results show that not only the public expenditures have a positive effect on economic growth in Jordan, but also the tax revenues positively affect the economic growth in the short-run, and this is because of using the tax revenues to finance the government activities in Jordan. This effect becomes negative in the long run, and this is explained because the tax seems a source of distortions in the economy, The extreme taxes may cause huge distortions in the economy, and these distortions destroys the purchasing power, the aggregate demand, and supply. More governmental dependence on tax revenues is the main source of tax evasion and less efficiency. The effect of taxation will curb any prosperity in the economy. Therefore, the government should estimate the fair tax rates to generate sufficient revenues to finance the public expenditure required to enhance economic prosperity.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.441-449
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• 2021

Bankruptcy is indicated by the inability of the company to meet its maturity obligations. The Covid-19 pandemic has had a terrible impact on the economy and businesses. The aim of this study to determine the effect of the ratios of activity, growth, leverage, and profitability in predicting bankruptcy projected by earnings per share (EPS). The sample of this research was non-banking financial sector companies listed on the Indonesia Stock Exchange in 2015-2019 and the purposive sampling technique was used. The data analysis method used was the logistic regression method to test the hypotheses. Company growth shows the company's ability to manage sales and generate high company profits, as such, the probability of the company experiencing bankruptcy will be lower. The results of this study showed that the debt to assets ratio (DAR), debt to equity ratio (DER), and return on assets (ROA) can predict bankruptcy. Meanwhile, this research found that the total assets turnover (TATO) ratio, sales growth, and net profit margin (NPM) cannot be used to predict bankruptcy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.147-165
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• 2021

In this work, we empirically evaluated the efficiency of the recent EfficientNetB0 model to identify and diagnose malaria parasite infections in blood smears. The dataset used was collected and classified by relevant experts from the Lister Hill National Centre for Biomedical Communications (LHNCBC). We prepared our samples with minimal image transformations as opposed to others, as we focused more on the feature extraction capability of the EfficientNetB0 baseline model. We applied transfer learning to increase the initial feature sets and reduced the training time to train our model. We then fine-tuned it to work with our proposed layers and re-trained the entire model to learn from our prepared dataset. The highest overall accuracy attained from our evaluated results was 94.70% from fifty epochs and followed by 94.68% within just ten. Additional visualization and analysis using the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm visualized how effectively our fine-tuned EfficientNetB0 detected infections better than other recent state-of-the-art DCNN models. This study, therefore, concludes that when fine-tuned, the recent EfficientNetB0 will generate highly accurate deep learning solutions for the identification of malaria parasites in blood smears without the need for stringent pre-processing, optimization, or data augmentation of images.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.135-144
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• 2021

In railway systems, it is common to obtain train location information through an infrastructure-based train detection system. However, this system has a problem that may provide incorrect location information due to non-detection and erroneous detection, which may cause an accident. Therefore, in this study, we propose a method of providing train location information using a sensor-based integrated navigation system. In order to provide accurate information; however, the reliability of the integrated navigation system must be verified. Therefore, in this paper, we develop a simulator that can generate a reference trajectory and sensor data based on the real trajectory and analyze the performance of the integrated navigation system according to various scenarios on the real trajectory.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.81-91
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• 2021

Drone related research has been increasing recently due to the development and distribution of commercial unmanned aerial vehicles. However, most of the previous studies focused on the accuracy and utility of drone surveying. For drones, the resolution of the result is determined according to the flight altitude, but since 70% of Korea is mountainous, it is necessary to analyze the quality of the drone image according to the flight plan. In this study, the quality of drone photogrammetry results according to flight plans was analyzed. The flight plan was established by fixed altitude and considering the height of the terrain. Images were acquired for both cases and data was processed to generate ortho images. As a result of evaluating the accuracy of the generated ortho image, the accuracy was found to be -0.07 ~ 0.09m. The accuracy of Case I and Case II did not show a significant difference, but for RMSE, Case I showed a good value. These results indicate that the drone flight plan affects the quality of the results. Also, when flying at a fixed altitude, II showed a lower value than the originally set overlap according to the altitude of the object. In future surveys using drones, flight planning taking into account the height of the object will contribute to the improvement of the quality of the results.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.37-45
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• 2021

The purpose of this study to examine the effect of strategic innovation on organization development, organizational effectiveness, and firm performance of companies in the Industrial Estate of Thailand. The sample of this study was 360 companies and data was collected by distributing questionnaires through mail and Google form. Out of the 360 questionnaires, 192 responses were received and usable. The study period was November 2020 to February 2021. Structural equation modeling (SEM) was used to test hypotheses regarding the influence of strategic innovation on organization development, organizational effectiveness, and firm performance. The results of this study show that strategic innovation has a positive direct effect on organization development, organizational effectiveness, and firm performance. Organizational development has no significant relationship with organizational effectiveness and firm performance, and organizational effectiveness has no significant relationship with firm performance. Strategic innovation has a strong direct positive effect on the company's performance. It indicated that strategic innovation is essential for organizations to drive business growth, generate value for the company and its customers, and create a competitive advantage. This type of innovation is essential for organizations to adapt to the speed of technology change. In addition, theoretical contributions, managerial contributions, limitations, and future research recommendations were presented in this study, including conclusions were shown.

• Journal of Sport and Applied Science
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• v.5 no.2
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• pp.47-53
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• 2021

Purpose: The purpose of this study is to generate industrial insights for developing sports movie industry. Related studies are scare. Research design, data, and methodology: The study employed case study and selected typical case samples who seem informative about sport movie industry. The authors interviewed six experts who are experienced in sport movie and related academic sector. Interviews were audio-taped and the text were decoded by multiple reading. Through this process, the study categorized significant meanings and produced results. Interviewees reviewed again the final findings to confirm validity, which calls member check. Results: It was suggested that developmental factors of sports movie were the realization of realistic sports scenes by using technologies. Second, participants told that contents of sport movie need to reflect real stories and it should tell the stories. Regarding constraints of sport movies, movie producers feel difficulty to make scenes in that sports are inherently quickly performed. Another constraints are that production cost is expensive but audiences are barely attended. Conclusions: For promoting economic outcomes and developing sport movie industry, government needs to financially support related markets to support sport movie producers assisting them to concentrate their movie works. Future directions for related-studies were discussed.