• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.82-96
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• 2019

This study evaluated the status of watershed health in Geum River Basin by SWAT (Soil and Water Assessment Tool) hydrology and water quality. The watershed healthiness from watershed hydrology and stream water quality was calculated using multivariate normal distribution from 0(poor) to 1(good). Before evaluation of watershed healthiness, the SWAT calibration for 11 years(2005~2015) of streamflow(Q) at 5 locations with 0.50~0.77 average Nash-Sutcliffe model efficiency and suspended solid (SS), total nitrogen(T-N), and total phosphorus(T-P) at 3 locations with 0.67~0.94, 0.59~0.79, and 0.61~0.79 determination coefficient($R^2$) respectively. For 24 years (1985~2008) the spatiotemporal change of watershed healthiness was analyzed with calibarted SWAT and 5 land use data of 1985, 1990, 1995, 2000, and 2008. The 2008 SWAT results showed that the surface runoff increased by 40.6%, soil moisture and baseflow decreased by 6.8% and 3.0% respectively compared to 1985 reference year. The stream water quality of SS, T-N, and T-P increased by 29.2%, 9.3%, and 16.7% respectively by land development and agricultural activity. Based on the 1985 year land use condition. the 2008 watershed healthiness of hydrology and stream water quality decreased from 1 to 0.94 and 0.69 respectively. The results of this study be able to detect changes in watershed environment due to human activity compared to past natural conditions.

• The Korean Journal of Archival Studies
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• no.34
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• pp.3-28
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• 2012

The year of 2013 is the first year that the new president takes the power and administrates the national affairs. In Korea, when the new president comes, the new administration brings big changes in the politics, economy, and society. The government management style has been changed according to the orientation and styles of the new president. Public records management is a critical and effective business tool to establish and carry out the government policies as well as an essential tool for democracy. Modern democracy is based on good governance. Creation and free use of full and accurate public records makes the good communication between the government and the public possible, and people's participation in the policy-making and surveillance of government activities for public good can work. During the present administration, communication between the president and the people was cutoff and people's participation in the national affairs have been further limited. Furthermore, in the present administration, the public records management was not regarded important, Whatever new administration comes, the year of 2013 is the time for the new administration to realize again the importance of the public records management and put it back to the normal track. Here are the major issues in the public records management to be concerned and resolved; (1) to ensure technological and institutional management of the electronic records in the government and safe transfer of the massive electronic records, (2) to establish an independent national records management and archives authority to be based on good governance, (3) to innovate the public records management in the public agencies including their agency records offices (RMO) and records management systems (RMS) (4) to establish local government archives and document local government policies and activities (5) supporting and promotion for documentation of the total society as a public service (6) expanding employment of professional records managers and archivists in the central and local governments, and standardization of professional competency and certification. In this paper, I will introduce the major issues in the public records management and suggest the policies and solutions that the Korean records professionals considered and discussed. This analysis and suggestions are the outcome of our professional considerations and discussions.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.722-732
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• 2021

Purpose: Due to the coronavirus infection-19 (COVID) pendemics, all educational institutions were required to provide full non-face-to-face real-time education, and fire officials were required to provide fire-fighting education by applying non-face-to-face education. In this difficult situation, the National Fire Service Academy tries to find the direction of the non-face-to-face real-time education and suggest ways to improve it through a survey of the status of non-face-to-face real-time education conducted by the NFSA to fire officials. Method: A survey was conducted on fire officials under the theme of "Consciousness Survey for Improving the Quality and Specialization of Non-face-to-face Real-Time Remote Education" and an in-depth analysis was conducted based on the results. Result & Conclusion: First, professors or educational operators shall actively utilize remote education programs suitable for educational characteristics by utilizing various programs. Second, a dedicated notebook for non-face-to-face training should be provided to provide an educational environment where all learners can participate in the training without difficulty. Third, in the case of education and training that requires the use of equipment due to the nature of fire officials' education and training, it is necessary to consider it as a non-face-to-face training place by arranging educational equipment at each fire station. Fourth, it is hard to expect a satisfactory educational effect to cope with practical education with theoretical education. Therefore, facilities and programs that enable non-face-to-face real-time hands-on training should be developed. It is worth considering the proper combination of face-to-face education while maintaining the social distance as much as possible until such non-face-to-face training is possible. Fifth, non-face-to-face education is considered to have high eye fatigue due to the light and electromagnetic waves of the computer screen, and as time goes by, the concentration level decreases. Therefore, it is necessary to form an education time to reduce the eye fatigue of learners and increase concentration through proper class and rest time. Finally, professors should operate a learner participation-oriented education that allows professors and learners to interact rather than one-sided knowledge transfer education. In addition, technical problems of non-face-to-face remote education should be thoroughly prepared through preliminary system checks to ensure that education is not disrupted.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Journal of Nutrition and Health
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• v.56 no.4
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• pp.419-438
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• 2023

Purpose: This study examines the effectiveness of personalized goal setting and smartphone-based nutrition counseling among adults in their 20s and 30s. Methods: Nutrition counseling was conducted for a total of 30 adults through a 1:1 chat room of a mobile instant messenger, once a week for 8 weeks. The first week of counseling included a preliminary online questionnaire survey and a dietary intake survey. Based on the results of the preliminary survey, 2 dietary goals were set in the second week and the participants were asked to record their achievements on a daily checklist. From the third week onwards, counselors sent feedback messages based on the checklist and provided information on dietary guidelines in a card news format every week. Post-counseling questionnaires and dietary intake surveys were conducted in the seventh week. Changes in dietary habits during the counseling were reviewed in the eighth week, followed by a questionnaire survey on the evaluation of the counseling process. Results: The nutrition quotient (NQ) scores and self-efficacy scores were significantly higher after nutrition counseling. The NQ scores of consumption frequencies of fruits, milk and dairy products, nuts, fast food, Ramyeon, sweet and greasy baked products, sugarsweetened beverages, the number of vegetable dishes at meals, and breakfast frequency were significantly higher after nutrition counseling. The intake of protein, vitamin A, thiamin, riboflavin, folate, calcium, and iron, and the index of nutritional quality of vitamin A, riboflavin, folate, calcium, and iron were higher after nutrition education. The participants were satisfied with the nutrition counseling program and the provided nutrition information. Conclusion: Personalized goal setting and smartphone-based nutrition counseling were found to be effective in improving the quality of diet and self-efficacy in young adults. Similar results were obtained in both the underweight/normal weight and the overweight/obese groups.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• 한국노년학
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• v.27 no.2
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• pp.459-472
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• 2007

This research has its purpose of developing a tool to assess the needs of the Korean elderly at home population and to provide adequate services by evaluating their physical, psychological, and socio-environmental aspects. This developed tool is composed of two hundred questions and has the advantage of combined physical, psychological and social environmental situation assessment of the elderly at home. The tool also contains not only the objective view of the professionals, but also the subjective appeals of the elderly at home population so that it can reflect their substantial desires. The assessment tool was developed over 21 months from July, 2004 to March, 2006 and this period can be divided into three different stages. In the first stage, collecting of questions for the desire-focused assessment of the elderly by literature investigation and researching foreign source materials was carried out, and this ultimately developed assessment tool was applied to the long-term care insurance pilot project in the second stage. In this process, we revised some insufficiencies of this tool after we applied to elderly of 250 from the pilot project and other 200 elderly from this research team. For the last stage, the tool was completed by using inquiries of the focused group and the group of professionals to ensure its reliability and validity. In the process of developing the tool, the total of 200 questions under 13 subcategories was selected. The 13 subcategories are basic information, subjective appeals, information of the main helper, use of services, house environment, condition of health, condition of rehabilitation, daily living(ADL, IADL, defecation, assistance), social maintenance, behavioral disability, medical health, living habits, and strength. This tool is on the purpose to assess thoroughly the desires that the elderly at home population has and to provide the best service they need.