• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.138-147
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• 2021

The purpose of this study was to develop a measuring tool for the health promotion behavior of Korean nurses. This would address the lack of a proven tool that reflects the nature of the nurses' nursing environment. This study was conducted on 530 nurses from January to December 2019. A literature review and focus group interview were conducted, data analysis was carried out to measure validity and reliability, and the conceptual framework was constructed by applying the IMB model. Five factors namely self-concept (2 questions), hospital life management (4 questions), knowledge and information regarding health (5 questions), physical and mental stress management (3 questions), and work adaptation (2 questions) were framed into 16 questions. The model fit was 346.23 (��<.001), Parsimonious Normed Fit Index (PNFI) was 0.60, and Parsimonious Comparative Fit Index (PCFI) was 0.63, which met the acceptance criteria, and the Root Mean Square Error of Approximation (RMSEA) was 0.10. Goodness of Fit Index (GFI) was 0.88, Comparative Fit Index (CFI) was 0.85, and Incremental Fit Index (IFI) was 0.85 which were found to be acceptable as per the applicable standards. All items had a Cronbach's �� score of .85, which ensured stable reliability. The nurse's health promotion behavior measurement tool developed in this study will be used to measure the nurse's health promotion behavior in terms of nursing practice which will help in understanding the broad contours of this behavior.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1393-1405
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• 2020

UAV (Unmanned Aerial Vehicle) can acquire high-resolution images due to low-altitude flight, and it can be photographed at any time. Therefore, the UAV images can be updated at any time in map production. Due to these advantages, studies on the possibility of producing large-scale digital maps using UAV images are actively being conducted. Precise digital maps can be used as base data for digital twins or smart cites. For producing a precise digital map, precise sensor modeling using GCPs (Ground Control Points) must be preceded. In this study, geometric models of UAV images were established through a precision sensor modeling algorithm developed in house. Then, a digital map by stereo plotting was produced to evaluate the possibility of large-scale digital map. For this study, images and GCPs were acquired for Ganseok-dong, Incheon and Yeouido, Seoul. As a result of precision sensor modeling accuracy analysis, high accuracy was confirmed within 3 pixels of the average error of the checkpoints and 4 pixels of the RMSE was confirmed for the two study regions. As a result of the mapping accuracy analysis, it satisfied the 1:1,000 mapping accuracy announced by the NGII (National Geographic information Institute). Therefore, the precision sensor modeling technology suggested the possibility of producing a 1:1,000 large-scale digital map by UAV images.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.93-108
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• 2023

In manufacturing productivity analysis, understanding the intricate interplay among factors like facility performance, layout design, and workforce allocation within the production line is imperative. This paper introduces a simulation-based methodology tailored to food manufacturing, progressively expanding scenarios to analyze production enhancement. The target system is a food processing plant, encompassing production processes, including warehousing, processing, subdivision, packaging, inspection, loading, and storage. First, we analyze the target system and design a simulation model according to the actual layout arrangement of equipment and workers. Then, we validate the developed model reflecting the real data obtained from the target system, such as the workers' working time and the equipment's processing time. The proposed model aims to identify optimal factor values for productivity gains through incremental scenario comparisons. To this end, three stages of simulation experiments were conducted by extending the equipment and worker models of the subdivision and packaging processes. The simulation experiments have shown that productivity depends on the placement of skilled workers and the performance of the packaging machine. The proposed method in this study will offer combinations of factors for the specific production requirements and support optimal decision-making in the real-world field.

• Korean small business review
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• v.41 no.3
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• pp.1-22
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• 2019

The purpose of this research was to investigate the impact of the partner types (supplier, customer, competitor, research institution, more than one partner type) for SMEs on radical and incremental innovation. Another purpose was to examine how the relation varies according to the technological intensity of an industry to which the focal firm belongs. To test the hypotheses, we used the 'KIS(Korean Innovation Survey) 2014' data and the empirical analysis was done with the effective survey from 3,846 Korean SMEs. We employed STATA 14 for validity, confirmatory factor analysis, and binary logistic regression analysis. The results revealed that, when viewed the entire manufacturing SMEs, cooperation with suppliers, customers and research institutes has all been shown to have a positive effect on the radical and gradual innovations of SMEs. However, The relationship between partner type and radical innovation has been significantly different depending on the technical intensity of the industry. When cooperating with suppliers, the impact on radical innovation of SMEs was significant only in low-tech and medium-low tech industries. In contrast, when working with customers, the impact on the radical innovation of SMEs was significant only in the high-tech, medium-high tech, and medium-low tech industries, except for low tech industries. Meanwhile, although cooperation with competitors has a positive effect on radical innovation, this has been only significant in the medium-high tech industries.

• Information Systems Review
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• v.25 no.4
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• pp.183-204
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• 2023

Due to the COVID-19 pandemic, lots of occasions need to be held in online environment. This is the reason why "Metaverse" gets lots of attention in 2021. A number of companies made announcements on Metaverse, and this situation also boomed stock market. This paper investigates the relationship between Metaverse initiatives and business value of the firm (i.e., stock prices). We examine this relationship by using event study method with Lexis-Nexis News data from 2019 to 2021. The results indicate that Metaverse initiatives significantly impact positive influence on firm's value. In the technological perspective, technical factors affect more positive market returns, including Metaverse enablers (e.g., NFT, VR devices, digital twin) and common infrastructure (e.g., semiconductor, AI, cloud), and especially virtual environment was emphasized. Additionally, in the strategical perspective, radical innovation (e.g., pivoting, acquisition) impact more positive market return rather than incremental innovation (e.g., partnership, investment). Also, firms from non-service industries can achieve benefits from Metaverse initiatives rather than service industry in some degree.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.788-805
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• 2023

Purpose: This study aimed to verify the impact of Habitat for Humanity Korea's disaster risk reduction intervention on the mental health and satisfaction with life among residents of southern Bangladesh who had constantly suffered from disaster stress due to perennial flooding. Method: The target group was 138 residents who were pre-surveyed in August 2020 and post-surveyed in November 2021. The interventions consisted of individual incremental housing, public facilities for evacuation, and disaster response training for capacity development. The data were analysed using paired sample t-tests for pre-post changes and one-way analysis of variance to identify differences between treatment groups. Result: The results showed significant improvements in residents' depression, anxiety, somatisation and satisfaction with life after the intervention, with significant differences in mental health levels between the intervention treatments. Specifically, relatively higher disaster mitigation effects were found for individual infrastructure improvements and employment facilities compared to disaster response drills. Conclusion: These results demonstrate the positive role of Habitat for Humanity Korea's disaster risk reduction interventions on the mental health recovery of disaster victims and suggest practical approaches that can be applied in disaster risk areas.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.291-298
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• 2024

As an important fishing ground in the southern coast of Korea, Jinhae Bay is characterized by a high level of fisheries production. However, its marine-ecosystem has shifted owing to environmental changes such as industrial development and high water temperatures over the decades. This study analyzes the fisheries production, discards, mean trophic level, and fishing-in-balance index using annual fishing data from five regions surrounding Jinhae Bay for the period 2005-2022, as well as using additional forecasting trends by 2027 using ARIMA (Auto Regressive Intergrated Moving Average). The results shows, that the production in Goseong will decrease continuously by 2027, as compared with that in other areas. Additionally, byproduct management is considered necessary in Tongyeong. For the marine-ecosystem index, Tongyeong indicates stable catch ratio of large fish species and a fishing-in-balance exceeding 0. Finally, the annual catch variation for six pelagic fish species in Jinhae Bay by 2060 is estimated based on the IPCC climate-change scenario, in which the recent low level that decreased to approximately 20 thousand ton in early 2020 is projected to recover to approximately 40 thousand ton in the 2020s and 2040s, followed by an incremental decline by 2060.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.127-137
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• 2014

The main purpose of this study is to estimate tradial growth response and to predict the potential spatial distribution of major tree species(Pinus densiflora, Quercus mongolica, Quercus spp., Castanea crenata and Larix kaempferi) in South Korea, considering climate and topographic factors. To estimate radial growth response, $5^{th}$ National Forest Inventory data, Topographic Wetness Index (TWI) and climatic data such as temperature and precipitation were used. Also, to predict the potential spatial distribution of major tree species, RCP 8.5 Scenario was applied. By our analysis, it was found that the rising temperature would have negative impacts on radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi, and positive impacts on that of Quercus mongolica, Quercus spp.. Incremental precipitation would have positive effects on radial growth of Pinus densiflora and Quercus mongolica. When radial growth response considered by RCP 8.5 scenario, it was found that the radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi would be more vulnerable than that of Quercus mongolica and Quercus spp. to temperature. According to the climate change scenario, Quercus spp. including Quercus mongolica would be expected to have greater abundance than its present status in South Korea. The result of this study would be helpful for understanding the impact of climatic factors on tree growth and for predicting the distribution of major tree species by climate change in South Korea.