• Journal of Digital Convergence
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• v.9 no.4
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• pp.253-265
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• 2011

A number of organizations have had big interests in studies concerning leadership and not only academia but also psychological areas do also. Until now, leadership has been accentuated by managers or team leaders especially. Recently, however, the concept of self-leadership directing one's own activities through self-control or self-management is being focused on in practices and in academia. This study is to investigate the influence between self-leadership strategies as predictors and learning performance in IT classes as dependents variables mediated by attitude of attendance focused on the social science students in two universities (Korea(116 samples) and India(36 samples)). And this research tried to compare difference between two university students. As a result of empirical analysis, Korean learners making an effort by themselves show a tendency to think constructively. Namely, even though the level of difficulty may be high, by positive self-talk, respondents usually make an effort to get high academic performance. In case of Indian respondents, students who are in behavior-oriented show higher academic performance. Research results can give us direction of task-taking attitudes in firms or learning attitudes in teaching organizations and implications to human resource managers who are in charge of improving learning performance or productivity.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.363-373
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• 2021

The purpose of this research is to analyze the Spill-over economic effect of the cultural and creative industries(CCI) in Henan Province, China. The research object is the CCI of Henan Province, which is mainly based on five sectors out of 42 industries in the industrial association table of the Statistical Bureau of Henan Province, China in 2017 (culture, sports; recreation and research sector; experimental development and integrated technical services sector; information transmission, computer services and software sector; education sector, etc), and is analyzed through secondary integration and redefinition of the CCI of Henan Province. Through the analysis of Henan Province Industry Association Table, this paper provides some enlightenment to the future direction of the cultural and creative industries. The main analysis results are as follows. The total production inducement of the CCI in Henan province is 48,848 billion yuan, and in particular, the production inducement coefficient of the industry in Henan province is 2.72809, 2.23909 (total of columns and rows), Index of the power of dispersion is 0.26325, and the index of the sensitivity of dispersion is 0.87535. Income induction coefficient is 0.55211, production tax induction coefficient is 0.09291. Because CCI of Henan Province has full development potential, the government needs to provide active support and policy support, in addition to the need for legal provisions and supervision of market management. In order to improve the innovative development of the CCI, it is necessary to develop a new model of "CCI+X".

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.863-871
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• 2018

Existing vulnerability analysis tools are prone to missed detections, incorrect detections, and over-detection, which reduces accuracy. In this paper, cross-checking based on a vulnerability detection method using static and dynamic analysis is proposed, which develops and manages safe applications and can resolve and analyze these problems. Risks due to vulnerabilities are computed, and an intelligent vulnerability detection technique is used to improve accuracy and evaluate risks under the final version of the application. This helps the development and execution of safe applications. Through incorporation of tools that use static analysis and dynamic analysis techniques, our proposed technique overcomes weak points at each stage, and improves the accuracy of vulnerability detection. Existing vulnerability risk-evaluation systems only evaluate self-risks, whereas our proposed vulnerability risk-evaluation system reflects the vulnerability of self-risk and the detection accuracy in a complex fashion to evaluate relative. Our proposed technique compares and analyzes existing analysis tools, such as lists for detections and detection accuracy based on the top 10 items of SANS at CWE. Quantitative evaluation systems for existing vulnerability risks and the proposed application's vulnerability risks are compared and analyzed. We developed a prototype analysis tool using our technique to test the application's vulnerability detection ability, and to show that our proposed technique is superior to existing ones.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.11-22
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• 2023

This study was established to provide basic information necessary for ecological management to restore the naturalness of black locust (Robinia pseudoacacia L.) plantations located in the mountains of Gyeongbuk, Korea. Using vegetation data collected from 200 black locust stands, vegetation types were classified using the TWINSPAN method, the spatial arrangement status according to the environmental gradient was identified through DCA analysis, and a synoptic table of communities was prepared based on the diagnostic species determined by determining community fidelity (Φ) for each vegetation type. The vegetation types were classified into seven types, namely, Quercus mongolica-Polygonatum odoratum var. pluriflorum type, Castanea crenata-Smilax china type, Clematis apiifolia-Lonicera japonica type, Rosa multiflora-Artemisia indica type, Quercus variabilis-Lindera glauca type, Ulmus parvifolia-Celtis sinensis type, and Prunus padus-Celastrus flagellaris type. These types usually reflected differences in complex factors such as altitude, moisture regime, successional stage, and disturbance regime. The mean relative importance value of the constituent species was highest for black locust(39.7), but oaks such as Quercus variabilis, Q. serrata, Q. mongolica, Q. acutissima, and Q. aliena were also identified as important constituent species with high relative importance values, indicating their potential for successional trends. In addition, the total percent cover of constituent species by vegetation type, life form composition, species diversity index, and indicator species were compared.

• The Journal of Bigdata
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• v.6 no.2
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• pp.125-137
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• 2021

The number of CCTV installed in Korea is over 1.3 million, increasing by more than 15% annually. However, due to the limited budget compared to the installation demand, the infrastructure is composed of 500,000 pixel low-quality CCTV, and there is a limits on identification of objects in the video. Public CCTV has high utility in various fields such as crime prevention, traffic information collection (control), facility management, and fire prevention. Especially, since installed in high height, it works as its role in solving diverse crime and is in increasing trend. However, the current public CCTV field is operated with potential problems such as inability to identify due to environmental factors such as fog, snow, and rain, and the low-quality of collected images due to the installation of low-quality CCTV. Therefore, in this study, in order to remove the typical low-quality elements of public CCTV, the method of attenuating scattered light in the image caused by dust, water droplets, fog, etc and algorithm application method which uses deep-learning algorithm to improve input video into videos over quality over 4K are suggested.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.

• Journal of Advanced Technology Convergence
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• v.3 no.2
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• pp.25-31
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• 2024

In recent industrialization and development due to information and communication technology, modern women in modern society are exposed to physical and mental health due to numerous stresses. Popular inflammations are attributable to a decrease in lactic acid bacteria, frequent antibiotic use, and a decrease in immunity. It is necessary to develop products that are helpful and reflected. The inner care gel currently introduced on the market can increase beneficial bacteria and maintain a healthy y-zone. The inner gel contains a hydrogel component. 90% is made up of water, and other components act as support for supporting water and are formed through crosslinking between polymer chains. Hydroxyethyl cellulose (HEC) is a hydroxyethyl ethylenetel of cellulose. The purpose of use is to act as a binder, an emulsion stabilizer, a viscosity enhancer (water-soluble), and a film forming agent. CA (crosslinker) is a crosslinking agent and serves to bind. Hydrogel in the beauty field acts as a film forming agent that gently wraps around the skin by forming a thin film and serves as an emulsion stabilizer that helps to prevent separation of other raw materials. It also acts as a thickener by increasing viscosity in cosmetics. In addition, it is used for glucose monitoring, nursing care, cell transplantation, and wound treatment in the bio field. Currently, it is understood that no products using functional hydrogel have been released, so in this study, a Y zone care hydrogel solution was manufactured to find out the antibacterial properties of the functional hydrogel, and a new solution was developed. As a result, it was confirmed that the appropriate Ph was applied to the Y zone, and after culturing Candida albicans in PDB medium, all three products of the Y zone care hydrogel solution showed an antibacterial effect of 0.5-1.0mm

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.93-109
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• 2020

Purpose: The radiochromic film (Gafchromic EBT3, Ashland Advanced Materials, USA) and 3-dimensional analysis system dosimetry checkTM (DC, MathResolutions, USA) were evaluated for patient-specific quality assurance (QA) of helical tomotherapy. Materials and Methods: Depending on the tumors' positions, three types of targets, which are the abdominal tumor (130.6㎤), retroperitoneal tumor (849.0㎤), and the whole abdominal metastasis tumor (3131.0㎤) applied to the humanoid phantom (Anderson Rando Phantom, USA). We established a total of 12 comparative treatment plans by the four geometric conditions of the beam irradiation, which are the different field widths (FW) of 2.5-cm, 5.0-cm, and pitches of 0.287, 0.43. Ionization measurements (1D) with EBT3 by inserting the cheese phantom (2D) were compared to DC measurements of the 3D dose reconstruction on CT images from beam fluence log information. For the clinical feasibility evaluation of the DC, dose reconstruction has been performed using the same cheese phantom with the EBT3 method. Recalculated dose distributions revealed the dose error information during the actual irradiation on the same CT images quantitatively compared to the treatment plan. The Thread effect, which might appear in the Helical Tomotherapy, was analyzed by ripple amplitude (%). We also performed gamma index analysis (DD: 3mm/ DTA: 3%, pass threshold limit: 95%) for pattern check of the dose distribution. Results: Ripple amplitude measurement resulted in the highest average of 23.1% in the peritoneum tumor. In the radiochromic film analysis, the absolute dose was on average 0.9±0.4%, and gamma index analysis was on average 96.4±2.2% (Passing rate: >95%), which could be limited to the large target sizes such as the whole abdominal metastasis tumor. In the DC analysis with the humanoid phantom for FW of 5.0-cm, the three regions' average was 91.8±6.4% in the 2D and 3D plan. The three planes (axial, coronal, and sagittal) and dose profile could be analyzed with the entire peritoneum tumor and the whole abdominal metastasis target, with planned dose distributions. The dose errors based on the dose-volume histogram in the DC evaluations increased depending on FW and pitch. Conclusion: The DC method could implement a dose error analysis on the 3D patient image data by the measured beam fluence log information only without any dosimetry tools for patient-specific quality assurance. Also, there may be no limit to apply for the tumor location and size; therefore, the DC could be useful in patient-specific QAl during the treatment of Helical Tomotherapy of large and irregular tumors.

• Proceedings of the Korean DIstribution Association Conference
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• 2001.11b
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• pp.125-141
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• 2001

In this paper, the current problems of logistics industry in Korea and their possible solutions were discussed. With Korea Telecoms KT-Logis, the supplier and demander of logistics service would not have to invest large sum of money into their computer system. All they need is just a computer with internet connected. What KT-Logis influence on the logistics industry are the following; 1. Many logistics service supplier and demander can do the business on the web with one computer system. 2. This web based computer system does not only work on the office but also apply on the field worker such as delivery personnel or even the forwarder with mobile phone. 3. KT-Logis is an integrated system which cover the broad arrange of logistics management from truck management to customer relations management. 4. Finally, KT-Logis is web based systems which suits for current e-business and mobile environment. In future, more studies should be done to develop more progressive integrated logistics information systems with enterprise resource planning(ERP) and supply chain management(SCM).