• Korean Security Journal
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• no.27
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• pp.129-159
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• 2011

Physical security has always been an extremely important facet within the security arena. A comprehensive security plan consists of three components of physical security, personal security and information security. These elements are interrelated and may exist in varying degrees defending on the type of enterprise or facility being protected. The physical security component of a comprehensive security program is usually composed of policies and procedures, personal, barriers, equipment and records. Human beings kept restless struggle to preserve their and tribal lives. However, humans in prehistoric ages did not learn how to build strong house and how to fortify their residence, so they relied on their protection to the nature and use caves as protection and refuge in cold days. Through the history of man, human has been establishing various protection methods to protect himself and his tribe's life and assets. Physical security methods are set in the base of these security methods. Those caves that primitive men resided was rounded with rock wall except entrance, so safety was guaranteed especially by protection for tribes in all directions. The Great Wall of China that is considered as the longest building in the history was built over one hundred years from about B.C. 400 to prevent the invasion of northern tribes, but this wall enhanced its protection function to small invasions only, and Mongolian army captured the most part of China across this wall by about 1200 A.D. European lords in the Middle Ages built a moat by digging around of castle or reinforced around of the castle by making bascule bridge, and provided these protections to the resident and received agricultural products cultivated. Edwin Holmes of USA in 20 centuries started to provide innovative electric alarm service to the development of the security industry in USA. This is the first of today's electrical security system, and with developments, the security system that combined various electrical security system to the relevant facilities takes charging most parts of today's security market. Like above, humankind established various protection methods to keep life in the beginning and its development continues. Today, modern people installed CCTV to the most facilities all over the country to cope with various social pathological phenomenon and to protect life and assets, so daily life of people are protected and observed. Most of these physical security systems are installed to guarantee our safety but we pay all expenses for these also. Therefore, establishing effective physical security system is very important and urgent problem. On this study, it is suggested methods of establishing effective physical security system by using system integration on the principle of security design about effective security system's effective establishing method of physical security system that is increasing rapidly by needs of modern society.

• The Korean Journal of Nuclear Medicine
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• v.39 no.3
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• pp.174-181
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• 2005

Purpose: Reduction of respiratory motion artifacts in PET images was studied using respiratory-gated PET (RGPET) with moving phantom. Especially a method of generating simulated helical CT images from 4D-CT datasets was developed and applied to a respiratory specific RGPET images for more accurate attenuation correction. Materials and Methods: Using a motion phantom with periodicity of 6 seconds and linear motion amplitude of 26 mm, PET/CT (Discovery ST: GEMS) scans with and without respiratory gating were obtained for one syringe and two vials with each volume of 3, 10, and 30 ml respectively. RPM (Real-Time Position Management, Varian) was used for tracking motion during PET/CT scanning. Ten datasets of RGPET and 4D-CT corresponding to every 10% phase intervals were acquired. from the positions, sizes, and uptake values of each subject on the resultant phase specific PET and CT datasets, the correlations between motion artifacts in PET and CT images and the size of motion relative to the size of subject were analyzed. Results: The center positions of three vials in RGPET and 4D-CT agree well with the actual position within the estimated error. However, volumes of subjects in non-gated PET images increase proportional to relative motion size and were overestimated as much as 250% when the motion amplitude was increased two times larger than the size of the subject. On the contrary, the corresponding maximal uptake value was reduced to about 50%. Conclusion: RGPET is demonstrated to remove respiratory motion artifacts in PET imaging, and moreover, more precise image fusion and more accurate attenuation correction is possible by combining with 4D-CT.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.41-50
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• 2010

The goal of this study was to develop a suitable ventilation system for high-rise hog building (HRHB) for growing-fattening with combined slatted floor pen in second story and in situ manure management system in Korea. The HRHB was constructed as 29m long, 9m wide and 7.6m high for outer dimension with an indoor height of 3.1m and 2.4 for lower and upper floor, respectively. Ventilation systems for each treatment were installed in separated rooms of HRHB. The ventilation types installed in each room were following 3 types: ventilation type 1 (V1), where air was pulled through a circular duct inlet and exhausted by fans; ventilation type 2 (V2), where air was pulled through eave inlet (side ceiling inlet) and exhausted by fans; and ventilation type 3 (V3), where air was pulled through baffled ceiling inlet and exhausted by fans. For each ventilation system, investigated air velocity under minimum, medium and maximum ventilation ratio and air flow pattern inside. The results were as follows; For air flow pattern from top to bottom, V1 showed a homogeneous vertical type, V2 showed a bilateral symmetry type and V3 showed an vertical umbrella type. Under minimum ventilation ratio, air velocity in upper floor (80cm above the slated floor) was similar for V1, V2, and V3. Under maximum ventilation ratio, air velocity in upper floor was undeviating for V1 (0.10~0.26m/s) and varied for V2 (0.12~0.63m/s) while those for V3 was relatively slow and less varied (0.07~0.15m/s). In conclusion, Duct inlet type (V1) can be applied to the development of a new HRHB with additional evaluations such as field test hog feeding.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1107-1111
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• 2011

Organic fertilizers application has become a popular alternatives to reduce the dependence on chemical fertilizer in Korean farming systems. In this study, we evaluated the nitrogen (N) use efficiency and growth performance of Chinese cabbage grown by black vinyl mulching after application of organic and chemical fertilizers compared with no-mulching. The treatments included chemical fertilizer alone as control (NPK, N-$P_2O_5-K_2O$ : $320-78-198kg\;ha^{-1}$), organic fertilizer alone (OF100), 70% organic fertilizer and 30% chemical fertilizer (OF70+N30), and 30% organic fertilizer and 70% chemical fertilizer (OF30+N70), which were all applied in the no-mulching plots and in plots with black vinyl mulching. Daily means soil temperature was $2^{\circ}C$ higher in the black vinyl mulched treatments throughout the 54 days compared with no-mulched treatments. OF100 with black vinyl mulching gave highest soil inorganic N content. Also, Chines cabbage yield increased 46% by black vinyl mulched compared with no-mulching in OF100 treatment. Without mulching, N use efficiency was, 44, 26, 29, and 27% in NPK, OF100, OF70+N30, and OF30+N70, respectively. However, black vinyl mulching much more effectively increased N use efficiencies by 56, 55, 51, and 39% in the same treatments in the order as mentioned above. Conclusively, combined organic and chemical fertilizers application with black vinyl mulching could be good practical technique to reduce a amount of used nitrogen because of its greater ability to enhance N use efficiency.

• Korean Journal of Heritage: History & Science
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• v.48 no.3
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• pp.80-95
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• 2015

The purpose of this study is to establish an effective protection and management system for World Heritage (WH) nomination of Southwestern Coast Tidal Flat (SCTF) by proposing a model of protection and management. SCTF has a potential to become a representative best practice to achieve a sustainable development for human society. SCTF has a potential Outstanding Universal Values (OUVs) for WH nomination, thus a harmony between human and nature for wise use of natural resources needs to be pursued. It is required to present the system of SCTF's protection and management and to analyze present status of the regions in the Tentative List by comparing the case which were already inscribed as WH. For better protection of nominated areas, SCTF should expand an area for protection with additional designation. For the management system, two separate management systems such as the Department of Culture & Tourism and the Department of Oceans & Fisheries need to be reconciled. Because of this overlapping management structure, the management of the nominated sites has been inefficient and long-term management plan is lacking. Therefore, it is necessary to integrate conflicting management system of each local government and make a long-term, integrated management plan. To make an efficient and sustainable protection and management, it is essential to set up a collaboration system by integrating various stakeholders such as central and local governments, academic organizations, local residents, and NGOs. As in the case of Wadden Sea, the combined community system of the stakeholders mentioned above should be established. Because it is essential for local residents to understand a basic concepts for protection and management, it is necessary to establish capacity-building of local people. The protection and management structure should be set up by bottom-up processes, that is the proper structure shoud be based on thorough research on local society as well as thorough communication with local residents to make relevant laws and policies. This study also propose the proper plan for better conservation and management of SCTF.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.65-73
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• 2019

In order to increase the production efficiency of the ship and shorten the production cycle, it is important to evaluate the accuracy of the ship components efficiently during the drying cycle. The accuracy control of the block is important for shortening the ship process, reducing the cost, and improving the accuracy of the ship. Some systems have been developed and used mainly in large shipyards, but in some cases, they are measured and managed using conventional measuring instruments such as tape measure and beam, optical instruments as optical equipment, In order to perform accuracy control, these tools and equipment as well as equipment for recording measurement data and paper drawings for measuring the measurement position are inevitably combined. The measured results are managed by the accuracy control system through manual input or recording device. In this case, the measurement result is influenced by the work environment and the skill level of the worker. Also, in the measurement result management side, there are a human error about the lack of the measurement result creation, the lack of the management sheet management, And costs are lost in terms of efficiency due to consumption. The purpose of this study is to improve the working environment in the existing accuracy management process by using the augmented reality technology to visualize the measurement information on the actual block and to obtain the measurement information And a smart management system based on augmented reality that can effectively manage the accuracy management data through interworking with measurement equipment. We confirmed the applicability of the proposed system to the accuracy control through the prototype implementation.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.79-87
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• 2021

Because active interactions occur among vegetation, hydrology, and geomorphology in riparian systems, any changes in one of these factors can significantly affect the other two. In this study, we evaluated these interactions at four sites (two in Gajeong and two in Hahan) along the Seomjin-gang River that was substantially devastated by an extreme flood in 2020. We examined the relationship between the riparian vegetation and the hydraulic characteristics of the flood using remote sensing, hydraulic modeling, and field surveys combined. The evaluation results showed that the floods caused a record-breaking rise of up to 43.1 m above sea level at the Yeseong-bridge stage gauge station (zero elevation 27.4 m) located between the Gajeong and Hahan sites, with the shear stress being four times higher in Hahan than in Gajeong. Additionally, the water level during the flood was estimated to be a maximum of 1 m higher depending on the location in the presence of riparian plants. Furthermore, both sites underwent extensive biological damage due to the flood, with 78-80% loss in vegetation, with preferential damage observed in large willow species, compared to Quercus acutissima. The above findings imply that all plant species exhibit different vulnerabilities towards extreme floods and do not induce similar behavior towards events causing a disturbance. In conclusion, we developed strategies for effectively managing riparian trees by minimizing flood hazards that could inevitably cause damage.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.361-381
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• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.