• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.77-82
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• 2023

The article considers online discussion as an interactive learning method in the conditions of distance learning. The essence of discussion and the stages of its organization are described. The main objective of discussion in distance learning is defined as the stimulation of interest in learning and the involvement of various viewpoints in an active discussion of the stated problems. The key role in ensuring the efficiency of a discussion is identified. The article develops a model for organizing asynchronous online discussions on the Moodle platform, highlighting the sequence of stages and their content. An experimental study of the use of the discussion method in the training of students in distance learning conditions is carried out. Based on the results of the methodological experiment, conclusions are drawn about student interest in online discussions. The authors conclude that the interest of students of different specialties in asynchronous online discussions varies, and the greatest interest is demonstrated by linguistics students. Nevertheless, the differences in student interest in online discussions by groups (specialties) are more likely attributable to subjective factors, which do not affect the overall picture in a major way.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.11-20
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• 2023

The primary aim of this study is to investigate the influence of Service Provider Quality (SPQ), System Quality (SQ), Information Quality (IQ), and Training Quality (TQ) on the interconnected aspect of organizational performance known as growth and development (GD). The study examined the influence of information systems (IS) on organisational performance and provided a theory-based technique for conducting research. The theoretical foundation for this study is derived from the widely employed [1]. IS success model in information systems research. The study's framework incorporates several novel elements, drawn from a comprehensive review of both recent and earlier literature, which researchers have utilized to evaluate the dimensions of [1]. In this study, we collected data from a diverse group of 348 individuals representing various industries through a web-based questionnaire. The collected data were subjected to analysis using SPSS. We conducted a multiple regression analysis involving 15 factors to assess several hypotheses regarding the relationship between the independent construct IS effectiveness and the dependent construct organizational performance. Several noteworthy descriptive statistics emerged, which hold significance for management. The study's findings strongly indicate that information systems exert a significant and beneficial influence on organizational performance. To sustain and continually enhance organizational effectiveness, the study recommends that managers periodically scrutinize and assess their information systems.

• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.59-74
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• 2015

This study aims to estimate optimal harvesting production, fishing efforts, and stock levels of yellow croaker caught by the offshore Stow Net and the offshore Gill Net fisheries using the current value Hamiltonian method and the surplus production model. As analyzing processes, firstly, this study uses the Gavaris general linear model to estimate standardized fishing efforts of yellow croaker caught by the above multiple fisheries. Secondly, this study applies the Clarke Yoshimoto Pooley(CY&P) model among the various exponential growth models to estimate intrinsic growth rate(r), environmental carrying capacity(K), and catchability coefficient(q) of yellow croaker which inhabits in offshore area of Korea. Thirdly, the study determines optimal harvesting production, fishing efforts, and stock levels of yellow croaker using the current value Hamiltonian method which is including average landing price of yellow croaker, average unit cost of fishing efforts, and social discount rate based on standard of the Korean Development Institute. Finally, this study tries sensitivity analysis to understand changes in optimal harvesting production, fishing efforts, and stock levels of yellow croaker caused by changes in economic and biological parameters. As results drawn by the current value Hamiltonian model, the optimal harvesting production, fishing efforts, and stock levels of yellow croaker caught by the multiple fisheries were estimated as 19,173 ton, 101,644 horse power, and 146,144 ton respectively. In addition, as results of sensitivity analysis, firstly, if the social discount rate and the average landing price of yellow croaker continuously increase, the optimal harvesting production of yellow croaker increases at decreasing rate and then finally slightly decreases due to decreases in stock levels of yellow croaker. Secondly, if the average unit cost of fishing efforts continuously increases, the optimal fishing efforts of the multiple fisheries decreases, but the optimal stock level of yellow croaker increases. The optimal harvest starts climbing and then continuously decreases due to increases in the average unit cost. Thirdly, when the intrinsic growth rate of yellow croaker increases, the optimal harvest, fishing efforts, and stock level all continuously increase. In conclusion, this study suggests that the optimal harvesting production and fishing efforts were much less than actual harvesting production(35,279 ton) and estimated standardized fishing efforts(175,512 horse power) in 2013. This result implies that yellow croaker has been overfished due to excessive fishing efforts. Efficient management and conservative policy on stock of yellow croaker need to be urgently implemented.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.193-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein. 1967: Fishbein & Ajzen. 1975). the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances. continuing education opportunity. rigidity of the administration. paticipative decision making, latitude, group support, role conflict, work load, need for achievement. experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however. that path analysis can not count measurment errors: measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%), pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment, the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support, role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention, The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment', 'Rigidity of the administration' and latitude were also found to have important roles in predictingr the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.183-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein, 1967;Fishbein & Ajzen. 1975), the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances, continuing education opportunity, rigidity of the administration, paticipative decision making, latitude, group support, role conflict, work load, need for achievement, experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however, that path analysis can not count measurement errors; measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%). pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment. the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support. role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention. The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment'. 'Rigidity of the administration' and latitude were also found to have important roles in predictor for the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of the Korea Institute of Building Construction
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• v.16 no.1
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• pp.77-85
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• 2016

This study provides the numerical model to assess retrofit and strengthen levels in the dispersal and combat facilities. First of all, it is verified that direct-hitting projectiles are more destructive to the structures rather than close-falling bombs with explosion tests. The protective capacity of dispersal and combat facilities, which are modeled with soil uncertainty and structural field data, is analyzed through finite element method. With structural survivability and facility data, the logistic regression model is drawn. This model could be used to determine the level of the retrofit and strengthen in the dispersal and combat facilities of contact areas. For more reliable model, it could be better to identify more significant factors and adapt non-linear model. In addition, for adapting this model on the spot, appropriate strengthen levels should be determined by hands on staffs associated with military facilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.533-542
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• 2016

The periodic maintenance of bridges is necessary once they have been constructed and its cost depends on various factors, such as their condition, environmental conditions and so on. To make a decision support system, it is essential to establish a basic reconstruction cost model. In this study, a regression model is suggested for calculating the reconstruction cost for typical cases and influential factors, depending on the type of bridge and its components, by analyzing the basic bridge specifications based on the data of the Bridge Management System (BMS). The details for each case were estimated in consideration of the cost calculation variables. The details for each case were estimated in consideration of the cost calculation variables. The cost model for the new construction of the superstructure, substructure and foundation and the temporary bridge construction and demolition costs were drawn from the regression analysis of the estimation results of typical cases according to the cost calculation variables. The reconstruction costs for different types of bridge were obtained using the cost model and compared with those in the literature. The cost model developed herein is expected to be utilized effectively in maintenance decision making.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.65-77
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• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.203-207
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• 2012

The noise emitted from an excavator has long been a cause of environmental disputes, while causing displeasure to the nearby residents. So, the ministry of environment adopted the construction machinery noise labeling system to encourage the construction machinery manufacturing companies to develop the low noise construction machinery voluntarily. But, as the quality of life improves, a growing number of people desire the comfortable and quite environment to live in. Under the situation, noise from the construction machinery has been a major cause for stress and complaints. When the noise dispute happened in the construction site, the sound pressure level of the construction machinery like a excavator was measured at the lot boundary of the noise victim's residence to judge how much noise damage occur. But the sound pressure level of the construction machinery is measured differently according to the acoustic environment of construction site and the measuring position, respectively, which makes it difficulty to judge whether the noise damage occur or not. As the sound power level of noise source is not affected by the acoustic environment of construction site and the measuring position, if we use the information of the sound power level, it will be easy to judge whether the noise damage occur and to establish the soundproofing measures. Therefore, we derive the sound power level regression model of the excavator to judge whether the noise emitted from the excavator damages to residents near the construction site. Also, the sound power level regression model of the excavator drawn in this paper will help construction companies to plan the noise reduction program in the construction sites.