• Industry Promotion Research
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• v.4 no.1
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• pp.45-55
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• 2019

The purpose of this study is to examine the effects of common competency, managerial competency, and job competency, which are perceived management consultants' competencies, on organizational performance and management characteristics of these managers. The hypothesis 2 shows that the influence of the management consultant capacity and the management performance on the Hypothesis 1 and the moderating effect of the hypothesis 2 management characteristics are as follows. First, common competence, management competence, and job competence, which are H1 management consultant capacities, have been shown to have a positive (+) influence on financial performance and non - financial performance. Second, the characteristics of manager in H2 were partially shown by the common competence between management consultant capacity and management performance. Therefore, in order to establish a corporate sustainability management system and implement it strategically, a consulting firm should select a consultant with excellent management consultant capability and execute management consulting. In addition, management consultants were required to have diverse learning, experience and management plans to improve their qualitative performance. Despite the fact that managerial characteristics represent partial regulatory roles, they actively play a central role in the survival and development of corporations, requiring active publicity so that the organizational characteristics of managers can be understood.

• 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 Korean Association of Information Education
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• v.25 no.3
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• pp.437-448
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• 2021

As the core technology of the Fourth Industrial Revolution, AI is applied to various fields of society(e.g. politics, culture, industry, economy, etc.) and causes revolutionary changes. Students who will lead the age of AI need the ability to recognize social changes due to AI, acquire AI related knowledge and utilize AI in various situations. However, it is difficult for elementary school students to understand the concept and principles of AI. Therefore, this study developed an AI education program by selecting educational contents and methods appropriate to the level of elementary school students, and investigated the educational effects of the program by applying it to an actual educational setting. The content selected in this study is 'Social Awareness on AI', 'Understanding AI' and 'Utilizing AI', and eight content elements were selected. To help students learn AI easily and pleasantly at their level, activity-centered education, convergence of subjects and project-based learning were selected as instructional methods, and 20 sessions of education program were developed and implemented. In addition, the effects of the program were analyzed concerning 'perception on AI', 'convergent thinking', 'creative problem-solving' and 'collaboration capability', and positive changes were verified for all four aspects.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.801-806
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• 2022

In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.355-362
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• 2008

Fast track completion of urgent typhoon damage recovery construction project is becoming crucial for the prevention of the secondary damage from the next year typhoon, prompt psychological stabilization of flood sufferers, the early recovery of damaged infrastructure condition and so forth. As the recovery learning process has been continued for last consecutive typhoons and experts suggested, the keys in attaining the goals of the project (preventative, sustainable, cleaner and fast tracking development) are found to be the early contracting and improved competencies in project management especially during the design phase. It can be presumed that the former is attainable through administrative supports in the form of government guidelines, but the latter necessitates more research efforts. In this regards, this study aims to find a way how to lift up the current level of project management capability facing ever changing project mangement environment of urgent typhoon recovery project. By comparing the current level of application of government guidelines in flooded districts and analyzing the time required for each phase from design contracting to construction starting, several reformative ideas are illustrated in association with the necessity of adopting CM method in the deign phase. It is highly expected that CM application in the design phase can be an effective alternative in overcoming current limits in improving the quality of the project and prevent the delay due to the lack of expertise and professional workers in the owner side.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Journal of the International Relations & Interdisciplinary Education
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• v.2 no.1
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• pp.57-82
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• 2022

This study aims to investigate and analyze the perception of communication capability which is one of the sub-competencies of NCS vocational substructure basic competence, and then seek the direction of prospective courses. To do this, the researcher conducts a non-face-to-face survey by creating five questions under the following five categories: The importance and necessity of communicative competence, students and educators of communicative competence classes, contents and methods of curriculum and teaching and learning, communicative competence and writing skills and operation of extracurricular programs. This researcher has been teaching basic education even before the communication skills curriculum was created in college, now, in a situation where communication skills have become selective education, it is intended to grasp the perception of college students about communication skills for first graders. This study attempted to analyze the survey area in more depth through group FGI after conducting an online survey by dividing it into several items. As a result, students felt that communication skills became motktkre important through COVID-19. Among the bottom five communication skills, speaking skills were found to be the most important, reading ability was recognized as the least important. On the other hand, there was a strong hope to know about the level of communication ability, type of communication, and method of communication about oneself. In addition, they recognized that communication skills should be learned in their first year of college, and hoped to be operated at all times as a non-disciplinary program. In particular, in the bottom five areas of communication skills, the expectations and actual hopes for speaking skills were the highest compared to the rest, and in terms of teaching and learning methods, they wanted to improve their skills through feedback and practice rather than theory. These research results have great implications for setting the direction of operation of classes, such as the content and method of classes in communication skills, in the future.

• Journal of Preventive Medicine and Public Health
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• v.26 no.4 s.44
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• pp.628-649
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• 1993

This study was conducted to investigate the factors related to the poor school performance of the elementary school children. Two schools in Taegu, one in the affluent area and the other in the poor area, were selected and a total of 175 children whose school performance was within low 10 percentile (poor performers) and 97 children whose school performance were within high 5 percentile (good performers) in each class of 2nd, 4th and 6th grades were tested for the physical health, behavioral problem and family background. Each child had gone through a battery of tests including visual and hearing acuity, anthropometry (body weight, height, head circumference), intelligence (Kodae Stanford-Binet test), test anxiety (TAI-K), neurologic examination by a developmental pediatrician and heavy metal content (Pb, Cd, Zn) in hair by atomic absorption spectrophotometry. A questionnaire was administered to the mothers for prenatal and prenatal courses of the child, family environment, child's developmental history, and child's behavioral and learning problems. Another questionnaire was administered to the teachers of the children for the child's family background, arithmatic & language abilities and behavioral problem. The poor school performance had a significant correlation with male gender, high birth order, broken home, low educational and occupational levels of parents, visual problem, high test anxiety score, attention deficit hyperactivity disorder (ADHD), poor physical growth (weight, height, head circumference) and low I.Q. score. The factors that had a significant correlation with the poor school performance in multiple logistic regression analysis were child's birth order (odds ratio=2.06), male gender(odds ratio=5.91), broken home(odds ratio=9.29), test anxiety score(odds ratio=1.07), ADHD (odds ratio=9.67), I.Q. score (odds ratio=0.85) and height less than Korean standard mean-1S.D.(odds ratio=11.12). The heavy metal contents in hair did not show any significant correlation with poor school performance. However the lead and cadmium contents were high in males than in females. The lead content was negatively correlated with child's grade(P<0.05) and zinc was positively correlated with grade (P<0.05). among the factors that showed a significant correlation with the poor school performance, high birth order, short stature and ADHD may be modified by a good family planning, good feeding practice for infant and child, and early detection and treatment of ADHD. Also, teacher and parents should restrain themselves from inducing excessive test anxiety by forcing the child to study and over-expecting beyond the child's intellectual capability.