• The Journal of Information Systems
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• v.27 no.1
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1623-1631
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• 2016

There are many researches which analyze vulnerability for combat systems, have been progressing, and apply the analyzed result to reflect on design phase. Recently, there have been requirements for integrating the previous module based researches which conducted independently. In this paper, we propose an integrated vulnerability analysis method for the combat system considering characteristics of threats and protection performance of armors through an analysis of the advanced research. In addition, by applying the proposed method improves the existing hit probability analysis program and we are verified based on scenarios for improving survivability of PKM (Petrol Killer Medium) for vulnerability analysis confirmed the results. The proposed method improves reliability of vulnerability analysis by considering threats and defense ability. Also it able to satisfied with the integration requirements. Furthermore, we became buildup for the development of applied system and the method and integrated vulnerability analysis method for combat systems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.6
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• pp.507-515
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• 2015

This paper proposes a filtering method for effective state vector estimation of highly maneuvering target. It is needed to hit the point called 'sweet spot' to increase the kill probability in missile interception. In paper, a filtering method estimates the length of a moving target tracked by a frequency modulated continuous wave (FMCW) radar. High resolution range profiles (HRRPs) is generated from the radar echo signal and then it's integrated into proposed filtering method. To simulate the radar measurement which is close to real, the study on the properties of scattering point of the missile-like target has been conducted with ISAR image for different angle. Also, it is hard to track the target efficiently with existing Kalman filters which has fixed measurement noise covariance matrix R. Therefore the proposed method continuously updates the covariance matrix R with sensor measurements and tracks the target. Numerical simulations on the proposed method shows reliable results under reasonable assumptions on the missile interception scenario.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.4
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• pp.343-355
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• 2021

Eelgrass, Zostera marina L., was widely distributed around Sinyangseopji Beach in Bangdu Bay, on the eastern coast of Jeju Island, until breakwater construction in the late 1990s resulted in its complete loss. Six experimental sites were identified for restoration of the Z. marina bed in Bangdu Bay. Using the staple method, 500 Z. marina shoots were transplanted at each site in January 2019 and 2020. The transplants, along with environmental parameters, were monitored for 10 months following transplantation. There were significant differences in underwater irradiance, water temperature, and salinity among the sites, but all were suitable for Z. marina growth. The Ulva species, an opportunistic alga, appeared in spring and accumulated during summer at all sites; however, there was no significant effect of Ulva species on the survival and growth of the eelgrass transplants. Most of the transplanted Z. marina survived, and after 3 months, the density increased by 112.5-300% due to vegetative propagation, with a rapid rate of increase observed during spring and early summer at all sites. For 1-2 months after transplanting, the Z. marina shoots showed signs of transplant shock, after which the shoot density increased at all sites, confirming that all transplants adapted well to the new environment. However, in both 2019 and 2020, during late summer to early fall, the sites experienced heavy damage from typoons (twice in 2019 and three times in 2020) that hit Bangdu Bay. The transplants at two sites located in the center of Bangdu Bay were completely destroyed, but those at three sites located to the west of the bay showed a 192-312% increase in density. Thus, we confirmed that the Bangdu Bay Z. marina bed can be restored, with the highest probability of success for Z. marina restoration on the western side of Bangdu Bay, which is protected from typhoons.