• ETRI Journal
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• v.43 no.4
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• pp.694-701
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• 2021

Catastrophic events cause casualties, damage property, and lead to huge social impacts. To build common standards and facilitate international communications regarding disasters, the relevant authorities in social management rank them in subjectively imposed terms such as direct economic losses and loss of life. Terrorist attacks involving uncertain human factors, which are roughly graded based on the rule of property damage, are even more difficult to interpret and assess. In this paper, we collected 114 183 open-source records of terrorist attacks and used a machine learning method to grade them synthetically in an automatic and objective way. No subjective claims or personal preferences were involved in the grading, and each derived common factor contains the comprehensive and rich information of many variables. Our work presents a new automatic ranking approach and is suitable for a broad range of gradation problems. Furthermore, we can use this model to grade all such attacks globally and visualize them to provide new insights.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.29-29
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• 2023

To mitigate the damaging impacts of floods, accurate prediction of runoff, streamflow and flood inundation is needed. Conventional approach of simulating hydrology and hydraulics using loosely coupled models cannot capture the complex dynamics of surface and sub-surface processes. Additionally, the scarcity of data in ungauged basins and quality of data in gauged basins add uncertainty to model predictions, which need to be quantified. In this presentation, first the role of integrated modeling on creating accurate flood simulations and inundation maps will be presented with specific focus on urban environments. Next, the use of machine learning in producing streamflow predictions will be presented with specific focus on incorporating covariate shift and the application of theory guided machine learning. Finally, a framework to quantify the uncertainty in flood models using Hierarchical Bayesian Modeling Averaging will be presented. Overall, this presentation will highlight that creating accurate information on flood magnitude and extent requires innovation and advancement in different aspects related to hydrologic predictions.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.134-138
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• 2023

The field of digital forensics requires good theoretical and practical knowledge, so practitioners should have an in-depth understanding and knowledge of both theory and practical as they need to take decisions which impacts human lives. With the demand and advancements in the realm of digital forensics, many universities around the globe are offering digital forensics programs, but there is a huge gap between the skills acquired by the student's and the market needs. This research work explores the problems faced by digital forensics programs, and provides solution to overcome the gap between the skills acquired by the student's and the market needs using Activity led learning pedagogy for digital forensics programs.

• Earthquakes and Structures
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• v.25 no.1
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• pp.15-26
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• 2023

It is of great importance to assess the residual displacement demand in the performance-based seismic design. In this paper, a hybrid deep learning model for predicting the residual displacement spectra under near-fault (NF) ground motions is proposed by combining the long short-term memory network (LSTM) and back-propagation (BP) network. The model is featured by its capacity of predicting the residual displacement spectrum under a given NF ground motion while considering the effects of structural parameters. To construct this model, 315 natural and artificial NF ground motions were employed to compute the residual displacement spectra through elastoplastic time history analysis considering different structural parameters. Based on the resulted dataset with a total of 9,450 samples, the proposed model was finally trained and tested. The results show that the proposed model has a satisfactory accuracy as well as a high efficiency in predicting residual displacement spectra under given NF ground motions while considering the impacts of structural parameters.

• Asia Marketing Journal
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• v.4 no.3
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• pp.23-41
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• 2002

본 연구는 신제품 개발 과정을 시장지식과 기술지식을 흡수, 활용하는 일종의 학습(learning)과정으로 인식하고 신제품 개발 팀을 하나의 학습 조직(learning organization)으로 파악하여 개발 팀의 학습 능력과 학습 능력을 지원할 수 있는 팀의 구조/분위기적인 특성이 신제품 경쟁우위의 달성에 중요한 요인임을 제시하고자 하였다. 신제품의 시장 성과는 신제품 경쟁우위(품질 우수성, 시간 효율성)의 확보에서 비롯되며 이러한 경쟁우위에 영향을 미치는 조직 학습의 요인은 마케팅 부서와 R&D부서의 정보 공유 행동과 조직기억의 활용도에 영향을 받는다. 또한 신제품 개발팀의 자율적인 분위기 및 신뢰의 분위기는 조직학습을 원할하게 수행할 수 있는 요인이 될 뿐만 아니라 신제품 개발과정의 시간 효율성을 달성함에 있어 중요한 요인이 된다.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.71-82
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• 2024

This paper proposes a new communication system for e-learning applications to mitigate the negative impacts of COVID-19 where the online massive demands impact the current commu-nications systems infrastructures and capabilities. The proposed system utilizes high-altitude platforms (HAPs) for fast and efficient connectivity provision to bridge the communication in-frastructure gap in the current pandemic. The system model is investigated, and its performance is analyzed using adaptive antenna arrays to achieve high quality and high transmission data rates at the student premises. In addition, the single beam and multibeam HAP radio coverage scenarios are examined using tapered uniform concentric circular arrays to achieve feasible communication link requirements.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.111-120
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• 2009

The purpose of this study was to analyze the lifestyles of tourists visiting rural experience tourist destinations and the influential relations of the attributes to affect rural experience tourism. The research findings show that the lifestyles of tourists had significant impacts on their preference for rural experience programs(0.2502/3.0l2). Second, their lifestyles had also significant impacts on the need for rural experience tourist destinations(5.039/3.363). Third, their preference for rural experience programs had significant influences on their intentions for revisits(0.386/3.l60). Fourth, their preference for rural experience programs had significant influences on their intentions for word of mouth(1.448/8.073). Fifth, their need for rural experience tourist destinations had significant impacts on their intentions for revisits(1.940/5.594). And finally, their need for rural experience tourist destinations had no significant influences on their intentions for word of mouth(-1.0611-1.421). According to the analysis results of the regression coefficient of the measuring model, enjoying leisure(1.130/6.775) and pursuing health(1.110/9.001) were large influential factors in lifestyle; pursuing learning(1.47317.946) was the biggest influential factor in preference for rural experience programs; and a natural environment(1.220/8.990) was the biggest influential factor in the need for rural experience tourist destinations.

• International Journal of Contents
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• v.6 no.3
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• pp.65-70
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• 2010

This paper addresses the importance of knowledge management (KM) and the relationship of that theory when applied to improving interior design organizational performance in four areas: people, processes, design products, and organizational performance. Included is the way knowledge theory manifests in three different professional settings: coaching and training, designing, and service settings. Knowledge management, although well established in interior design services, requires effort in coaching and training as motivation is a critical variable. Whereas, strategies for knowledge management vary from industry to industry given diversity in situational variables, knowledge in each professional setting can be significantly aided by capturing and storing empirical, tacit, and explicit information, providing real-time electronic storage and retrieval of information [5] and consistent with transformational theory, through opening communication channels across the full range of the organization, inspiring and motivating individuals, and aligning all members of the organization toward a common vision [8]. Professional settings discussed in this paper are:(a)an learning organization enumerated in KM; (b)designing factors for managing knowledge theory themes; and (c)service, effective, efficient, and innovative KM application that is relevant to the process of developing effective KM for interior design service organizations. Folded within each will be a discussion on KM's impacts on visions, strategies, costs, and organizational performance. It has reiterated the impact of KM on one level might lead to synergistic impacts on another. Thus, KM has the potential to produce several interconnected impacts on people, design products, processes, and organizations.

• Korean Journal of Veterinary Service
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• v.45 no.4
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• pp.253-262
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• 2022

The applications of artificial intelligence (AI) can provide useful solutions to animal infectious diseases and their impact on humans. The advent of AI learning algorithms and recognition technologies is especially advantageous in applied studies, including the detection, analysis, impact assessment, simulation, and prediction of environmental impacts on malignant animal epidemics. To this end, this study specifically focused on environmental pollution and animal diseases. While the number of related studies is rapidly increasing, the research trends, evolution, and collaboration in this field are not yet well-established. We analyzed the bibliographic data of 1191 articles on AI applications to environmental pollution and animal diseases during the period of 2000~2019; these articles were collected from the Web of Science (WoS). The results revealed that PR China and the United States are the leaders in research production, impact, and collaboration. Finally, we provided research directions and practical implications for the incorporation of AI applications to address environmental impacts on animal diseases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.4984-4993
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• 2012

This study was initiated with the need of studies to promote learning and use of collaboration skills that learners should have in collaborative learning in CSCL. The researcher carried out research on 96 students taking the course of 'educational methods and educational technology' in K collage to take a look at the impact of prior training on collaboration in CSCL and interaction of types of collaborative scripts. To answer the first research question, the scores of each group's chatting in collaborative learning process and messages represented in the process of task performance based on collaborative skills were measured and analyzed. In addition, to answer the second research question, the scores of each group's shared mental model formulation based on relevant evaluation standards were analyzed. This study results, First, there was no significant difference in the acquisition of collaboration skills caused by interaction of prior training on collaboration and collaboration skills and collaborative scripts. However, it turned out that types of collaborative scripts give significant impacts on acquisition of collaboration skills. Second, there was also no significant difference between prior training on collaboration and the formulation of shared mental model by the interaction of collaborative scripts. However, it is showed that types of collaborative scripts have significant impacts on the formation of shared mental model.