• Journal of Food Hygiene and Safety
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• v.32 no.2
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• pp.96-100
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• 2017

Through the increasing use of internet and smart device, consumers can search the information what they want to find. The information has been accumulated and become into a big data. Analyzing the big data regarding key words associated with foods and foodborne pathogens could be a method for predicting foodborne illness outbreaks, especially in school food services. Therefore, the objective of this study was to elucidate the correlations between key words associated with foods and food safety issues. Frequencies of the key words for foodborne pathogens and food safety issues were searched using an internet portal site from January 1, 2012 to December 31, 2014. In addition, foodborne outbreak data were collected from Ministry of Food and Drug Safety for the same period of time. There was correlation between the time having maximum key word frequencies of foods and foodborne pathogens, and the time for foodborne illness outbreak occurred. In addition, the search frequencies for foods and foodborne pathogens were generally increased right after foodborne outbreaks occurred. However, in some cases foodborne outbreaks occurred after the search frequencies for certain seasonal foods increased These results could be useful in food safety management for reducing foodborne illness and in food safety communication.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.725-731
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• 2020

In mineral resource development, resource exploration is a task to find economical minerals on the surface and underground, and the success rate is low compared to the development and production stages, and it is necessary to collect a lot of data through exploration and accurately analyze the collected information. In this study, mine spatial information was constructed using a 3D (Three-dimensional) laser scanner, and accuracy evaluation was performed to obtain a maximum deviation of 0.140 m and an average of 0.095 m in the X, Y and Z directions, and the possibility of utilizing the construction of mine geospatial information through a 3D laser scanner could be presented. In addition, the ore body modeling was performed by applying the interpolation method of the ore body section using the resource exploration results. The ore body modeling result was superimposed with the modeling result of the mine geospatial information built through the 3D laser scanner to construct the ore body modeling result based on the precise mine geospatial information. The results of ore body modeling based on mine geospatial information built through research can increase the ease of data interpretation and the accuracy of the calculated data, which will greatly increase the efficiency of work related to mineral resource development and mine damage prevention in the future.

• The Korean Journal of Franchise Management
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• v.10 no.3
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• pp.25-35
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• 2019

Purpose - The major objective of this study was to investigate the effect of franchisor's (economic and philanthropic) CSR in inspiring franchisee's loyalty for the franchisor. Another aim of this investigation also was to clarify the mediating role of economic and social satisfaction in the relationship between franchisor's CSR and franchisee's loyalty. Research design, data, and methodology - This study explores the structural relationship between franchisor's CSR and franchisee's loyalty and in these relationships, the mediating role of relationship satisfaction. Data were gathered from employees(above manager) in food-service franchisee companies in Seoul, Korea. The questionnaires were distributed to managers of the franchise stores. A total of 251 questionnaires were collected. Data management and analysis were performed using SPSS 21.O and SmartPLS 3.0. Evaluation of measurement model and structural model was carried out using confirmatory factor analysis and correlation analysis. Result - The results of this study show as follows. First, economic CSR had positive effects on economic satisfaction and social satisfaction. Second, philanthropic CSR had positive effects on social satisfaction. Third, economic satisfaction and social satisfaction had positive effects on franchisee's loyalty to the franchisor. Conclusions - The important implications of this study have as follows. First, this study has found that economic CSR can create a high economic satisfaction and social satisfaction of franchisee. Second, this findings suggest that the philanthropic CSR can improve the social satisfaction of franchisee. Third, this results demonstrate, for the first time, that the economic satisfaction and social satisfaction of franchisees can play a crucial role to improve their loyalty for the franchisor and pursue mutual development by maintaining the stable business relationship with a franchisor. In this investigation there are at least three limitations. First, Because the research sample is limited to the foodservice franchisee in Seoul, it is not possible to be representativeness of the national franchisee. Second, CSR activities are mostly focused on large franchise companies. Therefore, there is a limit to the research approach. Finally, this study examined the effect of economic CSR and philanthropic CSR on the loyalty of franchisors, but in the future study, it is necessary to analyze the relationship between CSR and loyalty of franchise companies by collecting specific quantitative data such as re-contract rate and management performance of franchisees.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.88-96
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• 2021

There have been many efforts to identify and eliminate the direct causes of the construction accident, but many accidents are still occurring in the construction industry. The main reason for the construction accident is not because of ignorance of the causes, but because of safety insensitivity. This paper analyzes why construction workers feel safety insensitivity and how safety insensitivity varies depending on their age and work experience. A survey of 103 construction workers confirmed that systematic safety education is the most important factor in minimizing safety insensitivity of construction workers. On the other hand, economic reasons such as cost reduction were identified as the most tempting factor to increase safety insensitivity. In addition, the survey results showed that those in their 40s and 50s, the largest proportion of construction workers, have a significantly higher level of safety insensitivity than those in their 20s and 60s. These findings are expected to be valuable source that can be used to prevent construction safety accidents.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.1-11
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• 2021

The Neis System is a system integrating administrative information that was operated in elementary and secondary schools in Korea. Currently, this system is operated by a central server method and contains school administration information and important educational information of students. Among student information, the student life record contains important information for a student to advance to a higher level institution, but problems such as information leakage or manipulation may occur due to malicious attacks. In this paper, we propose a hybrid blockchain system that combines the server and blockchain technology managed by the existing Neis system. The proposed system records the query information of the database in a block when student information is accessed. When a request for correction of student information or issuance of a certificate is received, the query of the blockchain, the information in the database, and the student's key value are checked to determine whether the information has been leaked or manipulated, and only if the data is normal, the request for revision of the record is performed. This process is more secure than the existing central server because it checks the manipulation of data through the blockchain. The proposed system was implemented on the Ethereum platform, and the query information of the blockchain was experimentally verified using smart contracts. This study contributes to enhancing the reliability of the Nice system by strengthening the security against forgery and alteration of student data by combining the existing Nice system with a block chain.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.140-155
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• 2020

This study was conducted to identify the location characteristics of infected farms in the areas where livestock diseases were clustered(southern Gyeonggi-do and Chungcheong-do), analyze the probability of disease occurrence in poultry farms, find out the areas corresponding to the conditions, and use them as the basis for prevention of livestock diseases, selection of discriminatory prevention zones, and establishment of prevention strategies and as the basic data for complementary measures. The increase of one poultry farm within a radius of 3-kilometers increases the risk of HPAI infection by 10.9% compared to the previous situation. The increase of 1m in distance from major roads with two lanes or more reduces the probability of HPAI infection by 0.001% compared to the previous situation. If the distance of the poultry farm located with 15 kilometers from a major migratory bird habitat increases by 15 to 30 kilometers, the chance of infection with HPAI is reduced by 46.0%. And if the distance of the same poultry farm increase by more than 30 kilometers, the chances of HPAI infection are reduced by 88.5%. Based on the results of logistic regression, the predicted probability was generated and the actual area of the location condition with 'more than 15 poultry farms within 3km a radius of, within 1km distance from major roads, and within 30km distance from major migratory birds habitat was determined and the infection rate was measured. It is expected that the results of this study will be used as basic data for preparing the data and supplementary measures when the quarantine authorities establish discriminatory quarantine areas and prevention strategies, such as preventive measures for the target areas and farms, or control of vehicles, by identifying the areas where livestock diseases are likely to occur in the region.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.165-175
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• 2022

The objective of this study is to identify the relationships among app attribution(perceived usefulness, design, information quality, and mobility), user satisfaction, trust, and continuous use intention of bus information apps; The structural equation of AMOS 21.0 was used to test the hypothesis of this study. The results of the analysis are as follows. First, perceived usefulness, design, information quality, and mobility positively impact user satisfaction. Second, only mobility has a positive effect on trust, but the remaining perceived usefulness, design, and information quality have no effect at the significance level of 5%. Third, user satisfaction has a positive impact on trust and continuous use intention. Fourth, trust has a positive impact on continuous use intention. Therefore, it was confirmed that the characteristics of the bus information mobile app are important influencing factors for the improvement of user satisfaction, trust, and continuous use intention. Local governments and bus companies will be able to establish strategic directions for the activation of bus information mobile apps. The limitation of this study is that it is somewhat lacking in generalizing the study results, so future research needs to focus on improving this part.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.171-177
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• 2022

In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.61-71
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• 2023

As differences in the impact of each species on a spatial scale occur, analysis at the landscape scale is necessary to evaluate the impact of a development project. In previous studies, the Incidence Function Model (IFM) based on meta population theory was used to analyze the impact of species on the environment that changes according to urban development. However, since the model was required at least 10 occupied areas, it is difficult to use it for species that are difficult to monitor such as endangered species. Therefore, we proposed the Incidence Function Model (IFM) using species distribution model to fill the species data. In addition, we reviewed whether the developed model can be used in environmental impact assessment. As a result of the analysis, the minimum occupancy of Prionailurus bengalensis on urban development decreased to 56.5% and the possibility of survival to 28.7%. We confirmed that It rapidly decreased from the reference points of 230 and 70habitats through analysis of the meta-population capacity according to the decrease in the number of habitats. These results can be assessing the environment impact of each species on habitat loss. And it can support decision-making on the minimum number and area of habitat for species protection. This study is expected to be used as basic data for environment impact assessment on before and after development projects and mitigation measures plans, thereby increasing the effectiveness of reduction plans.