• Journal of Korean Society of Disaster and Security
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• 제10권2호
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• pp.7-19
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• 2017

Recently, the incidence of disasters and safety incidents is increasing rapidly, and the interest and demands of the people are increasing. In particular, traffic accidents in Korea are decreasing due to the continuous efforts of the government and the local governments, but still higher than the OECD average. In response to such demands of the times, the 'Regional Safety Index', a numerical value that quantifies the level of safety of each local government, is being publicized every year to awaken public awareness. The Regional Safety Index covers seven categories of accidents (traffic accidents, crimes, suicide, infectious diseases, fire, safety accidents, and natural disasters) in local governments. But, this study focuses on the traffic accident area and analyzed. The target local government is Ulju county of Ulsan Metropolitan City. Based on the traffic accident statistical data of Ulju county, the analysis of the traffic accidents and vulnerable points were analyzed. Among them, 3 key improvement districts were selected and 15 vulnerable branches were selected for each key improvement district. Next, we prepared measures for improvement of each accident vulnerable site through analysis of geographic information through traffic data related to traffic accidents and interview with related organizations. In addition, the improvement measures are divided into the structural infrastructure improvement, the institutional improvement, and the traffic safety culture movement from the viewpoint of traffic accident prevention. Finally, the implications of this study are to clarify the duties and roles of the relevant departments in the municipality, based on the implementation schedule of the improvement projects for the prevention of traffic accidents and the budget plan. In addition, it is very important that the participating agencies involved in traffic accidents and the private sector participate in the project.

• Korean Journal of Food Science and Technology
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• 제40권2호
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• pp.152-159
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• 2008

The purpose of this study was to determine the accurate quantification of vitamin A in infant formula by comparing two different standard stock solutions as well as various sample weights using high performance liquid chromatography. The sources of uncertainty in measurement, such as sample weight, final smaple vloume, and the instrumental results, were identified and used as parameters to determine the combined standard uncertainty based on GUM(guide to the expression of uncertainty in measurement) and the Draft EURACHEM/CITAC Guide. The uncertainty components in measuring were identified as standard weight, purity, molecular weight, dilution of the standard solution, calibration curve, recovery, reproducibility, sample weight, and final sample volume. Each uncertainty component was evaluated for type A and type B and included to calculate the combined uncertainty. The analytical results and combined standard uncertainties of vitamin A according to the two different methods of stock solution preparation were 627 ${\pm}$ 33 ${\mu}$g R.E./100 g for 1,000 mg/L of stock solution, and 627 ${\pm}$ 49 ${\mu}$g R.E./100 g for 100 mg/L of stock solution. The analytical results and combined standard uncertainties of vitamin A according to the various sample weighs were 622 ${\pm}$ 48 ${\mu}$g R.E./100 g, 627 ${\pm}$ 33 ${\mu}$g R.E./100 g, and 491 ${\pm}$ 23 ${\mu}$g R.E./100 g for 1 g, 2 g, and 5 g of sampling, respectively. These data indicate that the preparation method of standard stock solution and the smaple amount were main sources of uncertainty in the analysis results for vitamin A. Preparing 1,000 mg/L of stock solution for standard material sampling rather than 100 mg, and sampling not more than 2 g of infant formula, would be effective for reducing differences in the results as well as uncertainty.

• Journal of Intelligence and Information Systems
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• 제19권1호
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.

• KIPS Transactions on Software and Data Engineering
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• 제10권7호
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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.

• The Korean Journal of Archival Studies
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• 제33호
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• pp.85-112
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• 2012

Group for the People without History(GPH) was launched at September 2002 and had worked for around five years with the following purposes; Firstly, GPH collects first-hand data on people's everyday lives based on fieldworks. Secondly, GPH constructs digital archives of the collected data. Thirdly, GPH guarantees the accessibility to the archives for people. And lastly, GPH promotes users to utilize the archived data for the various levels. GPH has influenced on the construction of archives on everyday life history as well as the research areas such as anthropology and social history. What is important is that GPH tried to construct digital archives even before the awareness on archives was not widely spreaded in Korea other than formal sectors. Furthermore, the GPH archives proposed a model of open archives which encouraged the people's participation in and utilization of the archives. GPH also showed the ways in which archived data were used. It had published forty seven books of people's life histories and five photographic books, and held six photographic exhibitions on the basis of the archived data. Though GPH archives had contributed to the ignition of the discussions on archives in various areas as leading civilian archives, it has a few limitations. The most important problem is that the data are vanishing too fast for researchers to collect. It is impossible for researchers to collect the whole data. Secondly, the physical space and hardware for the data storage should be ensured. One of the alternatives to solve the problems revealed in the works of GPH is to construct community archives. Community archives are decentralized archives run by people themselves to preserve their own voices and history. It will guarantee the democratization of archives.

• Journal of Nutrition and Health
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• 제54권1호
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• pp.10-22
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• 2021

Purpose: Key Foods refers to foods that have a high contribution in the nutrient intake of individuals, and exert important effects on their health. This study was undertaken to identify Korean Key Foods, using data from the 7th Korea National Health and Nutrition Examination Survey (KNHNES). Methods: The data source for the extraction of Key Foods was the 24-hour dietary survey data obtained from the 7th KNHNES (2016-2018), and 21,271 subjects were evaluated. A total of 17 nutrients were selected as the key nutrients for identifying the Key Foods, including energy, carbohydrates, protein, lipid, dietary fiber, calcium, phosphorus, iron, sodium, potassium, vitamin A, thiamin, riboflavin, niacin, vitamin C, cholesterol, and sugars. The nutrient consumption approach was applied to generate a list of potential Key Foods. Foods included in 85% of the cumulative intake contribution from one or more key nutrients, were subsequently selected as Key Foods. Results: Of the 1,728 foods consumed by survey respondents, we extracted 728 Key Foods. These Key Foods explained 94% key nutrient intakes of the subjects. Based on the contribution rate to key nutrient intake, the top 10 Key Foods identified were multigrain rice (5.32%), plain white rice (4.23%), milk (3.3%), cabbage kimchi (2.82%), grilled pork belly (1.56%), apples (1.52%), fried eggs (1.49%), cereal (1.36%), instant coffee mix (1.21%), and sweet potatoes (1.12%). These 10 foods accounted for 23.93% total key nutrient intake of the survey respondents. Conclusion: Seven hundred and twenty-eight foods were extracted and identified as the 2020 Korean Key Foods. These Key Foods can be considered the priority foods to be analyzed for establishing a national nutrient database.

• MISULJARYO - National Museum of Korea Art Journal
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• 제98권
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• pp.130-153
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• 2020

Using stylistic analysis and historical documents, this paper examines the production details of images enshrined in Myeongbujeon (Hall of the Underworld) at Magoksa Temple in Gongju, focusing on the wooden seated Ksitigarbha Bodhisattva and the stone Ten Kings of Hell. Inside Myeongbujeon, the wooden seated Ksitigarbha Bodhisattva is placed at the center, flanked by standing images of Mudokgwiwang and Domyeong-jonja, with images of the Ten Kings and their attendants along the walls. All of these images were transferred to Magoksa Temple in the latter half of the 1930s. The wooden seated Ksitigarbha Bodhisattva came from Jeonghyesa Temple in Cheongyang, the other sculptures came from Sinheungsa Temple in Imsil, and a painting of the Ten Kings came from Jeongtosa Temple in Nonsan. The wooden seated Ksitigarbha Bodhisattva is known to have been produced in 1677, around the same time as the stone sculptures of the Ten Kings. A close analysis of the details of the bodhisattva sculpture-including the facial features, body proportions, and drapery characteristics-strongly suggests that it was produced in the 1620s or 1630s by the monk sculptor Suyeon (who was active in the early half of the seventeenth century) or his disciples. In particular, the rendering of the drapery on the lower half of the body closely resembles Buddhist sculptures produced by Suyeon that are now enshrined at Bongseosa Temple in Seocheon (produced in 1619) and at Sungnimsa Temple in Iksan (produced at Bocheonsa Temple in Okgu in 1634). According to the votive inscription, the stone sculptures of the Ten Kings and their attendants were produced in 1677 under the supervision of the monk sculptor Seongil. However, these are the only known Buddhist images produced under Seongil, and no details about other monks involved in the production have ever been found, making it difficult to speculate about their lineage. Historical records do suggest that Seongil worked on other projects to produce or repair sculptures with disciples of the monk sculptors Hyehi or Unhye, indicating amicable relations between the two groups. Unlike most such images in the Honam or Yeongseo regions, the Ten Kings at Magoksa Temple are made from stone, rather than wood or clay. Also, the overall form and the drapery conform to statues of the Ten Kings that were popularly produced in the Yeongnam region. Thus, the images are believed to be the work of monks who were primarily active in Yeongnam, rather than Honam. In the future, a systematic investigation of wooden seated Ksitigarbha Bodhisattva images and stone Ten Kings of Hell images produced in the Chungnam region could illuminate more details about the production of the images at Magoksa Temple, and perhaps shed light on the conditions that led to the production of stone Buddhist sculptures in the Honam area during the late seventeenth century.

• Journal of Intelligence and Information Systems
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• 제27권1호
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Korea Entertainment Industry Association
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• 제15권2호
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• pp.169-178
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• 2021

The Korean girl group "Kara" has suffered the trilemma of its de facto failure to debut, the crisis of team breakup, and the CEO crisis of the agency. But the group has made an outstanding achievement in the history of Korean pop music after overcoming all odds. Their success strategy has never been disclosed by insiders involved in Kara's total music projects. This study has been carried out in the analysis of the strategy to provide academic implications and to honor the contribution of the late CEO Ho-yeon Lee and Kara's key member Ha-ra Gu. Therefore, between Nov. and Dec. 2020, we conducted in-depth interviews with managers, composers, stylists and Ha-ra Gu(Only in 2019, before her death) who took part in the project. The research model is set up by combining Porter's Competitive Advantage Strategy and the music value chain model into categories of "Product Innovation Differentiation (PD)" (producing, album production, performance activities) and "Marketing Differentiation (MD)" (market targeting, image specialization, promotion and communication). The analysis showed that the PD focused on complete rediscovered harmonization and revalued members' personality and sincerity with peppy songs and dainty dances as well as emission of "bright energy" which caused healing effects instead of mimicking other star singers recklessly. In terms of MD, they selected Japan's 10-20s as their main market, increasing intimacy with fans and media with the image of cute+pretty+classy+sexy. The result suggests that Poter's differentiation can function as a meaningful strategy frame in the fostering, hit, and revival of idol groups. In addition, it reaffirmed that spontaneous and passionate activities of early-stage or celebrity fan may serve as a valid catalyst for realizing differentiation, as Kara's caller of Japanese actor Gekidan Hitori caused a strong "priming effect" that drove Kara's unexpected wonderful success in Japan.

• The Korean Journal of Franchise Management
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• 제2권1호
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• pp.173-199
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• 2011

A franchisee has to depend on the overall system, such as knowhow and management support, from a franchisor in the franchise system and the two parties do not start with the same position in economic or information power because the franchisor controls or supports through selling or management styles. For this, unfair trades the franchisor's over controlling and limiting the franchisee might occur and other side effects by the people who give the franchisee scam trades has negatively influenced on the development of franchise industry and national economy. So, the purpose of this study is preventing unfair trade for the franchisee from understanding the causes and problems of dispute between the franchisor and the franchisee focused on the dispute cases submitted the Korea Fair Trade Mediation Agency and seeking ways to secure the transparency of recruitment process and justice of franchise management process. The results of the case analysis are followed; first, affiliation contracts should run on the franchisor's exact public information statement and the surely understanding of the franchisee. Secondly, the franchisor needs to use their past experiences and investigated data for recruiting franchisees. Thirdly, in the case of making a contract with the franchisee, the franchisor has to make sure the business area by checking it with franchisee in person. Fourthly, the contracts are important in affiliation contracts, so enacting the possibility of disputes makes the disputes decreased. Fifthly, lots of investigation and interests are needed for protecting rights and interests between the franchisor and franchisee and preventing the disputes by catching the cause and more practical solutions of the disputes from the government.