• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.801-809
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• 2017

The purpose of this study is to contribute to the prevention of ship collisions by investigating real ship collision cases and statistically analyzing causes of human error for captains and Officers of the Watch (OOW). This study encompassed a total of 109 cases for 218 vessels, which were suitable for the analysis of ship accidents between merchant ships or merchant ships and fishing boats over the 7 years from 2010 to 2016. Data was collected while classifying vessels according to type, Give-way and Stand-on vessels, along with the cause of human error. Factors causing human error were identified after focusing on the cause of each collision given by the OOW ; frequency and cross tabulation analyses were conducted using SPSS, a statistical analysis tool. As a result, the main causes of human error by an OOW in a ship collision situation were that lookout was neglected in a Give-way vessel including radar surveillance (74.3 %) or continuous observation of an opponent vessel was carried out (17.4 %). A major factor for Stand-on vessels was failure to act to avoid collision with another vessel (63.3 %). In particular, most neglect for lookout type merchant ships occurred after the opponent ship was first observed, and a common cause of lookout neglect and neglect of duty was a focus on other tasks during navigational watch time.

• Journal of Science and Technology Studies
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• v.19 no.1
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• pp.91-135
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• 2019

As we live a life increasingly mediated by computers, we often outsource our critical judgments to artificial intelligence(AI)-based algorithms. Most of us have become quite dependent upon algorithms: computers are now recommending what we see, what we buy, and who we befriend with. What happens to our lives and identities when we use statistical models, algorithms, AI, to make a decision for us? This paper is a preliminary attempt to chronicle a historical trajectory of judging people's economic and moral worth, namely the history of credit-rating within the context of the history of capitalism. More importantly this paper will critically review the history of credit-rating from its earlier conception to the age of big data and algorithmic evaluation, in order to ask questions about what the political implications of outsourcing our judgments to computer models and artificial intelligence would be. Some of the questions I would like to ask in this paper are: by whom and for what purposes is the computer and artificial intelligence encroached into the area of judging people's economic and moral worth? In what ways does the evolution of capitalism constitute a new mode of judging people's financial and personal identity, namely the rated self? What happens in our self-conception and identity when we are increasingly classified, evaluated, and judged by computer models and artificial intelligence? This paper ends with a brief discussion on the political implications of the outsourcing of human judgment to artificial intelligence, and some of the analytic frameworks for further political actions.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.89-100
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• 2021

The National Cyber Capability Assessment(NCCA) could be used as meaningful information for improving national cyber security policy because it provides information on the elements necessary for strengthening national cyber capabilities and the level of each country. However, there were few studies on improving cyber capabilities using the NCCA result in Korea. Therefore, we analyzed the result of National Cyber Power Index(NCPI) conducted by Belfer Center of Harvard Univ. by applying modified-IPA method to derive cybersecurity policy agendas for Korea. As a result, the need to set agendas on surveillance and offensive cyber capability and improve the effectiveness of policy implementation for intelligence and defense was drawn. Moreover, we suggested need for in-depth study of each policy agenda deduced from preceding research data as a future tasks. And it is expected to increase practical use of NCCA for domestic policy analysis by developing and using our own NCCA model which considered analysis framework proposed in this study.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.44-56
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• 2018

Researches on military weapons are actively studied to improve national defense power of each country. The military weapon system is being used not only as a weapon but also as a reconnaissance and surveillance device for places where it is difficult for people to access. If such a weapon system becomes an object of attack, military data that is important to national security can be leaked. Furthermore, if a device is taken, it can be used as a terrorist tool to threaten its own country. So, security of military devices is necessarily required. In order to enhance the security of a weapon system such as drone, it is necessary to form a chain of trust(CoT) that gives trustworthiness to the overall process of the system from the power on until application is executed. In this paper, by analyzing the trusted computing-based boot technology, we derive trusted boot technology components and classify them based on hardware dependence/independence. We expect our classification of hardware dependence/independence to be applied to the trusted boot technology of our self-development ultraprecision weapon system to improve the defense capability in our military.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.570-588
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• 2022

We scrutinized the acoustic outputs from the 70 shock wave generators of the 15 product models whose technical documents were available, among the 46 ballistic extracorporeal shock wave therapeutic devices of 11 domestic and 6 foreign manufacturers, approved by the Minster of Food & Drug Safety (Rep. Korea). We found that the acoustic Energy Flux Density (EFD), the most popular exposure parameter, was different by up to 563.64 times among shock wave generators at their minimum output settings and by up to 74.62 times at their maximum settings. In the same product model, the EFD was shown to vary depending on shock wave transmitters by up to 81.82 times at its minimum output setting and by up to 46.15 times at its maximum setting. The lowest EFD 0.013 mJ/mm² at the maximum output settings was much lower (2.1 %) than the maximum value 0.62 mJ/mm² at the minimum settings. The Large acoustic output differences (tens to hundreds of times)from the therapeutic devices approved for the same clinical indications imply that their therapeutic efficacy & safety may not be assured. The findings suggest the regulatory authority to revise her guideline to give clearer criteria for clinical approval and equality in performance, and recommend the authority to initiate a post-approval surveillance as well as a test in conformance between the data in technical documents and the real acoustic outputs clinically used.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.195-202
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• 2006

The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

• Journal of Trauma and Injury
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• v.36 no.3
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• pp.187-195
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• 2023

Purpose: This study aimed to determine the risk factors associated with the severity of fall-related injuries among patients who suffered a fall from similar heights and analyze differences in injury sites according to intentionality and injury severity. Methods: The Emergency Department-based Injury In-depth Surveillance (EDIIS) data collected between 2019 and 2020 were used in this retrospective study. Patients with fall-related injuries who fell from a height of ≥6 and <9 m were included. Patients were categorized into the severe and mild/moderate groups according to their excessive mortality ratio-adjusted Injury Severity Score (EMRISS) and the intention and non-intention groups. Injury-related and outcome-related factors were compared between the groups. Results: In total, 33,046 patients sustained fall-related injuries. Among them, 543 were enrolled for analysis. A total of 256 and 287 patients were included in the severe and mild/moderate groups, respectively, and 93 and 450 patients were included in the intention and non-intention groups, respectively. The median age was 50 years (range, 39-60 years) and 45 years (range, 27-56 years) in the severe and mild/moderate groups, respectively (P<0.001). In multivariable analysis, higher height (odds ratio [OR] 1.638; 95% confidence interval [Cl], 1.279-2.098) and accompanying foot injury (OR, 0.466; 95% CI, 0.263-0.828) were independently associated with injury severity (EMR-ISS ≥25) and intentionality of fall (OR, 0.722; 95% CI, 0.418-1.248) was not associated with injury severity. The incidence of forearm injuries was four (4.3%) and 58 cases (12.9%, P=0.018) and that of foot injuries was 20 (21.5%) and 54 cases (12.0%, P=0.015) in the intention versus non-intention groups, respectively. Conclusions: Among patients who fell from a similar height, age, and fall height were associated with severe fall-related injuries. Intentionality was not related to injury severity, and patients with foot injury were less likely to experience serious injuries. Injuries in the lower and upper extremities were more common in intentional and unintentional falls, respectively.