• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.130-137
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• 2023

Smart farms, which have been receiving attention as a solution to recent rural problems, refer to technologies that optimize the growing environment of crops and increase the productivity and quality of crops through efficient management. If the relationships between environmental data in smart farms are analyzed, additional productivity enhancement and crop management will be possible. In this paper, we propose a method for acquiring and analyzing nine environmental data, including temperature, humidity, CO2, soil temperature, soil moisture, insolation, soil EC, EC, and pH. Data acquisition is done through RS-485 communication between the main board and the sensor board and stored in the database after acquisition. The stored data is downloaded in Excel sheet format and analyzed through histograms, data charts, and correlation heatmaps. First, we analyze the distribution of total, day, and night data through histogram analysis, and identifiy the average, median, minimum, and maximum values by month through data chart analysis separating day and night to see how the data changes by month. Finally, we analyze the correlation of the data through a correlation heatmap analysis separating day and night. The results show a very strong positive correlation between temperature and soil temperature and soil EC and EC during the day, and a very strong positive correlation between temperature and soil temperature and soil EC and EC at night, and a strong negative correlation between temperature and soil EC.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.5-24
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• 2022

As a new academic publication model is attempted to improve the transparency, efficiency, and speed of scientific knowledge production and distribution, the open peer review platform for verification and openness of peer review history is also activated. Publons is a global platform for tracking, validating, disclosing, and recognizing the peer-reviewed histories of more than 3 million researchers worldwide. This study analyzed the review activities of 579 researchers from domestic universities who are actively reviewing international journals through Publons. As a result of the analysis, first, researchers from domestic universities who actively review international academic journals were found to be in the fields of medicine and electrical and electronics, and in most fields, assistant professors or higher with high WOS indexed research papers are participating. Second, there was a long-tail phenomenon in which a small number of reviewers with extremely high number of review papers existed in all academic fields, and there was no significant difference in the number of review papers and review report length depending on the nationality, academic status, and age of the reviewers. Lastly, although there was a weak correlation between the amount of papers reviewed by reviewers and the number of published papers, it was found that researchers with an extremely large number of reviews do not necessarily produce as many research papers.

• The Korean Journal of Franchise Management
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• v.9 no.2
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• pp.7-16
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• 2018

Purpose - Turnover Intention in the franchise industry is becoming a very important issue. This study examines the structural relationships between organizational justice, emotion, job satisfaction, and turnover intention in the franchise industry. In this model, emotion was classified into two sub-dimensions such as positive and negative emotion. Research design, data, methodology - The sample of this study collected from employees of a food-service franchise company is representative. Copies of the questionnaire along with a cover letter were delivered by a research assistant to the human resources manager or the general manager of the selected food-service franchise firms after they agreed to participate in the study. In order to increase the response rate of the respondents, a small gift was provided to the respondents who completed the questionnaire. A total of 300 questionnaires were distributed and 285 returned responses, 9 responses were not usable due to missing information. Thus, a total of 276 responses were used using structural equation modeling with Smartpls 3.0. Results - The results showed that organizational justice had positive significant effects on positive emotion and job satisfaction. Job satisfaction had negative a significant effect on turnover intention. And negative emotion had positive significant effect on turnover intention. Conclusions - The results of this study provide some implications. If employees feel that the franchise headquarters is fair about the methods and procedures of decision making, resource allocation, information sharing, etc., it means that employees feel better. If the franchise's decision-making processes and methods and results are transparently disclosed and processed in accordance with the internal rules of the company, the employees will be able to fully understand and accept them. The results of this study also show that positive and negative emotions of service-based franchise employees have different effects on job attitude and organizational behavior. In particular, when negative emotions of employees are passed on to others and the results are negative, employees may feel that they are disoriented or wrong. Therefore, the franchise headquarters should try to inspire employees' sense of organizational community, and should pay attention to how to relieve the job stress and the fair distribution of work and rewards.

• The Korean Journal of Franchise Management
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• v.3 no.1
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• pp.73-91
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• 2012

This study is in the purpose for the revitalization of traditional market as comparing to the relevancy between the central characteristics of a floating population going around for buying something or eating food and lots of small-sized businesses comprising of the commercial districts. The several traditional markets such as Cheonan station, Dujeong-dong, Sinbu-dong in Cheon-An city has been investigated repeatedly almost every two or three years by the Small Enterprise development Agency(SEDA) since 2001. By analyzing the raw data of those commercial districts made by SEDA, we can calculate the number of firms andthe ratio of business type of each commercial districts. In this research, the type of each business is classified into four groups such as restaurant, service, retail and the rest. Moreover, the central character of the floating population is derived from the raw data, which means the customer information about sex, age structure or the most populous time zones. From these characteristics, one commercial districts has his own specific features distinguishing from the others. The most important differences of past researches are firstly the dynamic viewpoint rather than a static one. Secondly it suggests that the relation between the central characteristics of districts and the floating population would exist. Lastly, it suggests that the interaction between both of them have a significant effect on the growth or decline of the districts and the rates of business type, other adjacent commercial districts as well. Eventually, this study provides several meaningful points for the revitalization of commercial districts to government or stakeholder such as management organization, business owners and new starter etc.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.360-363
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• 2022

According to the 2018 Kaggle ML & DS Survey, among the proportions of frameworks for machine learning and data science, TensorFlow and Keras each account for 41.82%. It was found to be 34.09%, and in the case of development programming, it is confirmed that about 82% use Python. A significant number of machine learning and deep learning structures utilize the Keras framework and Python, but in the case of Python, distribution and execution are limited to the Python script environment due to the script language, so it is judged that it is difficult to operate in various environments. This paper implemented a machine learning and deep learning system using C# and Keras running in Visual Studio 2019. Using the Mnist dataset, 100 tests were performed in Python 3.8,2 and C# .NET 5.0 environments, and the minimum time for Python was 1.86 seconds, the maximum time was 2.38 seconds, and the average time was 1.98 seconds. Time 1.78 seconds, maximum time 2.11 seconds, average time 1.85 seconds, total time 37.02 seconds. As a result of the experiment, the performance of C# improved by about 6% compared to Python, and it is expected that the utilization will be high because executable files can be extracted.

• Asia Marketing Journal
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• v.15 no.4
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• pp.1-32
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• 2014

The purpose of this paper is to investigate upon a diversification strategy through market creation of CJ Group, which has contributed in positioning of the firm as one of the leading conglomerates in South Korea. With such objective, the background of CJ Group, followed by its business diversification strategies were explored, with reference to several case studies. The history of CJ Group began with establishment of CheilJedang Industrial Corporation in 1953, as the first domestic sugar producer and exporter of South Korea. The corporation gradually expanded its business ever since at both national and global level, to include the fields of food production, pharmaceutical, biotechnology, and life chemicals. Later, CheilJedang (CJ) Group was established as an affiliate of CheilJedang Industrial Corporation. With such independence, extension of business has been witnessed across the industries of media, entertainment, finance, information technology and distribution. Thus, the current CJ Group pursues to define itself as a progressive global living culture company with four major business categories from food and food service, biotechnology, entertainment and media, and logistics. Despite its success in today's market, CJ Group underwent hardships in its business diversification in 1990s due to indiscreet management, along with the Asian financial crisis. Here, many firms overcame the financial difficulties by taking advantage of the exchange rate for overseas expansion. Though, CJ Group tried to differentiate itself by focusing on the domestic market by creating something out of nothing. Hence, CJ Group takes a unique position among many cases of business diversification and their categorization. In an effort to identify and classify the types of growth experienced by the top 30 companies in South Korea, the firms were categorized into four groups according to their diversification strategies adapted after the Asian financial crisis. Based on the mode and time of entry, corporations were identified either as the 'Explorer', 'Invader', 'Venture Capitalist', or 'Assimilator'. Here, the majority of the firms showed the qualities of Invader, entering mature markets through large-scaled mergers and acquisitions. However, CJ Group was the only firm that was categorized as an Explorer, for its focus on the newly emerging service sector in culture-contents industry. This diversification strategy through market creation is worth examining, due to its contribution in generating simultaneous growth between the market and the company itself. Diverse brands of CJ Group have been referred to as case studies in this regard, from 'Hatban', 'Cine de Chef', 'VIPS' to 'CJ GLS'. These four businesses, each to represent processed food, film, restaurant service, and logistics industries respectively, show CJ Group's effectiveness in creating a whole new category of goods and services that are innovative. In fact, such businesses not only contributed in advancement of consumers' wellbeing, but toward generating additional value and employment. It is true that the diversification strategy of CJ Group requires long-term capital investment with high risk, compared to the other strategies mentioned in the paper. However, this model does create high employment and additional values that are positive to both the society and the firm itself. Therefore, the paper comes to a conclusion that the diversification strategy through market creation conveys the most positive impact relative to the others.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.201-228
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• 2023

This study was conducted to analyze the trends of librarian job recruitment in Korea and overseas. A total of 489 librarian job postings posted on the internet portal site "Saseo e-Ma-eul" were collected for the Korean data, and 6,600 data were collected from "ALAJobList" for the international data. The research period spans from January 2020 to August 2022. The data were subjected to regional distribution analysis, frequency analysis, and topic modeling. As a result of the study, the number of Korean librarian job postings was the highest in Seoul with 280, while California was the state with the highest number of job postings overseas with 662. According to the frequency analysis, the main task of Korean data is 'management' 23.42%, and the core competency is 'certificate' 16.61%. For overseas data, 'Library Service' is the main task of 8.72%, and 'Communication Skills' is the most important core competency of 10.13%. In topic modeling, five topics were identified for each area 4 in total, including Korean and international job description and requirements. The analysis results confirm that the duties and qualifications derived from Korean and international job postings for librarians are related to the core competencies proposed by major library associations such as the American Library Association (ALA) and the Korean Library Association.