• Korean Journal of Health Education and Promotion
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• v.18 no.1
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• pp.35-47
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• 2001

As the complexity of the our environment is further complicated by advancements in industry and increase in vehicle traffic flow, the incidents of injury causing accidents are on the rise. Consequently, there is increasing emphasis on the importance of systematic and continual safety education for injury preventive behaviors. This study investigates safety related problems of elementary school students based on the PRECEDE model, proposed by Green et al.(1980 Green), to comprehensively identify the requirements of school safety education. The identified requirements were used to diagnose the current state of elementary school safety education through the analysis of multidimensional factors. A questionnaire survey was conducted on 594 sixth grade students from randomly selected 4 schools in Seoul to examine their injury preventive behaviors and to determine the educational diagnosis variables that affect it. The duration of the survey was 3 weeks starting from April 12, 1999 to May 8, 1999. A summary of the survey results are presented below; 1. Situations in which accidents have occurred were, in their order of frequency, ‘during play or sports activities within the school grounds’ was most frequent at 59.6％, ‘during play on local streets’ at 49.5％, and ‘traffic accidents’ at 41.6％. 2. Categorization of the injury preventive behavior showed that ‘not playing at high traffic flow locations such as streets and construction sites’ had the higher level of observance, while ‘wearing of helmets and joint protection devices during playing’ was least observed. 3. Considering injury preventive behaviors in relation to educational diagnosis variables indicated, for predisposing factors, lower ‘perception to injury accidents’ (p〈0.001) combined with higher ‘concerns for injury accidents’(p〈0.001), ‘practice of preventive behavior’(p〈0.001), and ‘the level of safety knowledge’(p〈0.001) resulted in significantly higher observance of injury preventive behaviors. For enabling factors, higher ‘perceived level of the school safety education’ (p〈0.001) and ‘availability of safety education resources’(p〈0.01) indicated significantly higher observance of injury preventive behaviors. For the reinforcing factor, frequent exposure to ‘safety education brochure’ (p〈0.01) and ‘audio-visual material for safety education’(p〈0.01) combined with more ‘regional safety education’ (p〈0.01), ‘home safety education’ (p〈0.01), ‘school safety education’(p〈0.001), and, ‘parents’ observance of preventive behaviors' (p〈0.001) showed significantly higher observance of injury preventive behaviors. 4. An analysis of the factors that affect injury preventive behaviors showed that the enabling factor ‘awareness of school safety education’ had the highest correlation with injury preventive behaviors followed by factors, in their order of significance, ‘practice of preventive behavior’, ‘perception to injury accidents’, ‘level of safety knowledge’, ‘parents’ observances of preventive behaviors', and ‘concerns for injury accidents.’

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

• Journal of Information Management
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• v.43 no.1
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• pp.63-87
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• 2012

This study aims to analyse the actual condition of the ebook services and propose the improvements of ebook services for children in the Korean public library. For this purpose, the current condition of the ebook services in the public libraries were analyzed and categorized by three criteria. Secondly, the ebook use analysis was conducted using PCs and mobile devices in terms of access to ebook library site, searching method, contents type and viewer, lending process, and user help. As a result of the analysis, several issues such as the difficulty in access to ebook site, the complexity of setting and usage depending on the file format, the insufficient user guide, the relatively lower quality service than the commercial's, and the lack of retrieval functions specialized for the ebook were presented. The improvement plan for the ebook services, especially for children in the public library was suggested.

• Journal of Korea Technology Innovation Society
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• v.11 no.2
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• pp.145-170
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• 2008

The existence of network is indeed the single most important factor that brings about new business phenomena in the new digital economy, especially in the IT industry. Network effect refers to a phenomenon that the increase in size of the network leads to increased network value and user utility. It determines the competitive structure of an industry and the performances of industry competitors (Shapiro and Varian, 1999). The phenomenon of increasing returns and winner-take-all enjoyed by the early winner in the competition can be attributed to the existence of positive feedback which increases the value of network and induces more users into join the network (Arthur, 1996; Shapiro and Varian, 1999; Song and Lee, 2003). This research attempts to shed light on the topic of innovation and competitive strategy of network-based industries. We analyze the case of the Korean mobile communications industry, in which a shift in technological paradigm from 2G to 3G brought new changes to the competitive structure of the industry. The Korean mobile communications industry makes an ideal case for analysis since it is an industry whose value is inherently dependent upon its user network. It is characterized by the typical increasing returns, in which a monopolizing player is enjoying firstmover's network effects. Because of the existence of network in the mobile communications industry, latecomers' disruptive innovations could not outcompete the incumbent's sustaining innovations. The contribution of this research lies in laying a groundwork for future studies by introducing a numerical simulation model to analyze the complexity theory and network effect.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.325-338
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• 2004

A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored In the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks of designing a warehouse is the selection of materialized views to be maintained in the warehouse. The goal is to select a set of views so that the total query response time over all queries can be minimized while a limited amount of time for maintaining the views is given(maintenance-cost view selection problem). In this paper, we propose an efficient solution to the maintenance-cost view selection problem using a genetic algorithm for computing a near-optimal set of views. Specifically, we explore the maintenance-cost view selection problem in the context of OR view graphs. We show that our approach represents a dramatic improvement in terms of time complexity over existing search-based approaches that use heuristics. Our analysis shows that the algorithm consistently yields a solution that only has an additional 10% of query cost of over the optimal query cost while at the same time exhibits an impressive performance of only a linear increase in execution time. We have implemented a prototype version of our algorithm that is used to evaluate our approach.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.1
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• pp.32-48
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• 2018

The mechanisms of $CH_4$ uptake into and release from the ocean are not well understood due mainly to complexity of the biogeochemical cycle and to lack of regional-scale and/or process-scale observations in the marine boundary layers. Without complete understanding of oceanic mechanisms to control the carbon balance and cycles on a various spatial and temporal scales, however, it is difficult to predict future perturbation of oceanic carbon levels and its influence on the global and regional climates. High frequency, high precision continuous measurements for carbon isotopic compositions from dissolved $CH_4$ in the surface ocean and marine atmosphere can provide additional information about the flux pathways and production/consumption processes occurring in the boundary of two large reservoirs. This paper introduces recent advances on optical instruments for real time $CH_4$ isotope analysis to diagnose potential applications for in situ, continuous measurements of carbon isotopic composition of dissolved $CH_4$. Commercially available, three laser absorption spectrometers - quantum cascade laser spectroscopy (QCLAS), off-axis integrated cavity output spectrometer (OA-ICOS), and cavity ring-down spectrometer (CRDS) are discussed in comparison with the conventional isotope ratio mass spectrometry (IRMS). Details of functioning and performance of a CRDS isotope instrument for atmospheric ${\delta}^{13}C-CH_4$ are also given, showing its capability to detect localized methane emission sources.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.115-120
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• 2019

In this paper, we present the results of the performance statistical analysis of the multi-robot formation control based on receding horizon particle swarm optimization (RHPSO). The formation control problem of multi-robot system can be defined as a constrained nonlinear optimization problem when considering collision avoidance between robots. In general, the constrained nonlinear optimization problem has a problem that it takes a long time to find the optimal solution. The RHPSO algorithm was proposed to quickly find a suboptimal solution to the optimization problem of multi-robot formation control. The computational complexity of the RHPSO increases as the number of candidate solutions and generations increases. Therefore, it is important to find a suboptimal solution that can be used for real-time control with minimal candidate solutions and generations. In this paper, we compared the formation error according to the number of candidate solutions and the number of generations. Through numerical simulations under various conditions, the results are analyzed statistically and the minimum number of candidate solutions and the minimum number of generations of the RHPSO algorithm are derived within the allowable control error.

• Smart Media Journal
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• v.10 no.2
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• pp.61-69
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• 2021

Wayfinding is a 'Process solving problem to find destination', and it is important to select spatial data for optimal way. Recently, due to the complexity of space and the expansion of the medium of the wayfinding service, it is necessary to the approach on the information design for them. Therefore, the purpose of this study is to propose a meta guideline on the information design for the design of orientation sign, which is an important cognitive clue in the wayfinding. It was conducted in 3 stages, First, a design process was proposed and design elements were derived for each step by literature research related to information and sign design, and analysis of manual for signage design. Second, a meta guideline for information organization and visualization in the three-stage design process was proposed by FGI and analysis. Third, the meta guideline was applied to the sign design on an area for user evaluation to inspect the applicability of the meta guideline. Through the user questionnaire, the possibility of applying the guideline for visualization of directions and spaces, information hierarchy according to spatial characteristics and information priority was identified. It is meaningful in that necessary element for signage design are systematized centering on the process and that it presents a macroscopic methodology according to spatial characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.10-23
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• 2019

Although social big data can provide a multi-faceted perspective on school bullying experiences among children and adolescents, the complexity and variety of unstructured text presents a challenge for systematic collection and analysis of the data. Development of an ontology, which identifies key terms and their intricate relationships, is crucial for extracting key concepts and effectively collecting data. The current study elaborated on the definition of an ontology, carefully described the 7 stage development process, and applied the ontology for collecting and analyzing school bullying social big data. As a result, approximately 2,400 key terms were extracted in top-, middle-, and lower-level categories, concerning domains of participants, causes, types, location, region, and intervention. The study contributes to the literature by explaining the ontology development process and proposing a novel alternative research model that uses social big data in school bullying research. Findings from this ontology study may provide a basis for social big data research. Practical implications of this study lie in not only helping to understand the experience of school bullying participants, but also in offering a macro perspective on school bullying as a social phenomenon.