• Journal of Environmental Impact Assessment
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• v.32 no.5
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• pp.269-278
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• 2023

The pollution status of heavy metals in the soils of children's playground was investigated for a sustainable soil environment in urban parks of Seoul. As sampling sites, 281 locations were selected from a 7 districts in the Seoul city. The overall mean concentrations of the heavy metals (Cd 0.21 mg/kg, Cu 5.97 mg/kg, As 2.40 mg/kg, Pb 7.55 mg/kg, Zn 34.08 mg/kg, Ni 4.22 mg/kg, Hg 0.02 mg/kg and Cr6+ not detected.) in the soils of the palygrounds were lower than the worrisome level in criteria for area 1 in Korea soil environment conservation act. In addition, when the soil pollution grade (SPC) was evaluated as an average value, it was found to be less than 100, the first grade, at all points in the seven autonomous districts, indicating thatthe soil was in good soil condition. However, when evaluated as the maximum value, some of the five districts showed values of 100 or more. Therefore, it was found that continuous management and interest of the local government, which is the management body of children's playgrounds, is necessary for a safe soil environment.

• Fire Science and Engineering
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• v.15 no.4
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• pp.24-33
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• 2001

This article proposes a strategy for producing accident scenarios in quantitative risk, which is peformed in process design or operation steps. Present worldwide chemical processes need off-site risk assessment as well as on-site one. Most governments in the world require industrial companies to submit the proper emergency plans through off-site risk assessment. Korea is also preparing for executing Integrated Risk Management System along with PSM and SMS. However.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.113-132
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• 2021

This study is a new evaluation using the Arrhenius equation, which is known as the chemical reaction rate estimation equation, to evaluate the intrinsic and extrinsic value elements of patents as a model. The performance of the evaluation model was superior to the SVM, Logistic reg. and ANN models that were used as patent evaluation models in prior studies. In addition, there was a strong correlation between the predicted lifespan of the patent and the actual lifespan of the patent. These evaluation models may be used for evaluation purposes only, or if an evaluation is required, including a commercialization entity or technical characteristics.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.655-657
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• 2001

인터넷 기술의 급속한 발전으로 교육분야에서도 많은 변화를 가져오고 있고 특히, 웹을 활용하는 수업들이 증가하고 있다. 특히, 가상대학에서 홈페이지를 토해 교수자들이 교과학습과 관련 있는 웹 문서들을 제공함으로써 강의가 진행되고 있으나, 웹의 속성과 자원을 효과적으로 이용하여 유의미한 학습 환경을 제공하고 있는가를 고려해 볼 때, 웹 문서들의 질적인 차이가 많을 것으로 예상된다. 따라서, 교육용 웹 문서들을 평가하여 등급을 매기고 이를 다시 문서에 반영함으로써 보다 양질의 교육이 될 수 있도록 하는 것은 중요한 일이다. 본 논문에서는 최근 웹을 활용한 수업에 대해 평가할 수 있는 평가 항목을 제시하고, 이들을 실제로 한 가상대학에서 이루어지는 강의에 대해 적용시켜 평가한다. 이를 통해 점차 확산되어지고 있는 가상대학의 양질의 강의를 위한 평가의 기초 자료로 사용될 수 있을 것이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.495-496
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• 2023

최근 보급되고 있는 스크린 야구장을 많은 이용자가 단순한 타격만을 하고 피드백이 없이 일회성으로 이용하고 있고 이용자의 타격 자세를 평가해주는 기능을 제공하지 않고 있다. 부정확한 자세로 타격을 하게 되면 부상의 위험도 있고, 타격 실력도 향상될 수 없다. 따라서 이용자가 올바른 타격자세를 취할 수 있도록 자세를 평가 해주는 시스템이 필요하다. 본 논문에서는 구글의 미디어 파이프와 딥러닝 기술을 활용하여 타격 자세 영상을 인식하여 타격 자세를 평가해주는 시스템을 개발하였다. 제안한 시스템은 사전에 다양한 영상을 LSTM 알고리즘으로 학습하여 이용자의 타격자세를 4개 등급으로 평가해준다. 이를 활용하여 스크린 야구장에서 카메라만 설치하여 간단하게 사용 가능하며 이용자들이 타격 자세를 자체 평가할 수 있다.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.85-94
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• 2009

This paper presents the capability to use QuickBird imagery for effects of forest disturbance in Okgye burned area. Particular attention of this paper deals with the NBR-derived mapping burn severity on QuickBird imagery to locate reliable rehabilitation(namely, secondary succession) over postfire surface. Comparisons of the mapping forest disturbance derived from QuickBird NBR data and the mapping burn severity derived from Landsat ${\Delta}NBR$ data show substantial agreement (KHAT value =0.7886). The method calculated from the correlation between QuickBird wetness and Landsat ETM+ band7 may have application to forest harvest disturbance.

• Journal of Korean language education
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• v.29 no.3
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• pp.255-292
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• 2018

Most grading scales of Korean language proficiency tests are based on existing grading scales that are not empirically verified. The purpose of this study is to develop an empirically verified scale descriptor. The 'Performance data-driven approach' that is suggested by Fulcher (1987) was used to develop the detailed description of characteristics for each level of performance. This study is focused on the functional phase of speech samples analysis (coding data) to create explanatory categories of discourse skills into which individual observations of speech phenomena can be scored. The speech samples that were collected through this study demonstrated stages of speech that can be a foundation of a grading scale. The data used in the study was collected from 23 native speakers of Korean. Speech samples were recorded from simulated speaking tests using the 'REFUSAL' task, and transcribed for analysis. The transcript was analyzed using discourse analysis. The result showed that the 'REFUSAL' task needs to go through four functional phases in actual communication. Furthermore, this study found specific and detailed explanatory categories of discourse competence based on the actual native speaker's speech data. Such findings are expected to contribute to the development of more valid and reliable speaking assessment.

• Journal of Technology Innovation
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• v.28 no.1
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• pp.31-52
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• 2020

This study was started to verify the preliminary(Ex-ante) discrimination power of the firm's high-activity using the 'Forward-looking' oriented technology appraisal model used in technology financing. The analytical firms are classified into the industry (manufacturing / non-manufacturing) and the age of company (initial / non-initial). High-activity SMEs are defined as those that achieve at least twice the average asset turnover ratio of the cluster. As a result of the discriminant model by applying C5.0 method, which is one of decision tree models, classification accuracy is more than 99% in all industries and the age of company, and it is confirmed that the discriminant power of the model is stable. As a result, the management expertise, capital involvement and funding capacity items were identified as a critical variable for the high-activity SMEs. In addition, the technology management capability and technology life cycle were also confirmed to be the items to determine high-activity SMEs in the manufacturing industry. Through this, it was possible to confirm some possibility of prior discrimination and policy utilization of high-activity SMEs by using technology appraisal items.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.11-16
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• 2022

As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.