• 공학교육연구
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• 제22권6호
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• pp.12-20
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• 2019

The purpose of this study is to development of a teaching-learning model for active learning in engineering education. For this, the adequacy between educational objectives and active learning activities is verified and furthermore an "active learning teaching-learning model" is suggested. This suggested teaching-learning model is expected to supplement weakness of traditional lecture-type teaching-learning activity. Based on the literature review, first, the representative activities of active learning were derived. there are twenty active learning activities, which compose of five of individual learning activity, five of pair-learning activity and five of group-learning activity, and five of alternative- learning activity. In addition, a survey on adequacy between designed active learning activities and learning outcomes were conducted to ten educational experts. Lawshe's content validity calculation method was applied to analyze the validity of this study. Second, five teaching-learning principles, such as thinking, interaction, expression, reflection, and evaluation were derived to develop an "active learning teaching-learning model" which supplements lecture-type classes and then the "TIERA teaching-learning model" which consists of five stages was designed. Finally, based on the survey on educational experts, adequate active learning activities were proposed to apply in each stage of the "TIERA teaching-learning model" and as a result the TIERA model's active learning activities were developed. The result of this study shows that some activities of active learning are appropriate to induce high cognitive learning skills from the learners even in traditional lecture-type classrooms and therefore this study suggests meaningful direction to new paradigm of teaching-learning for engineering education. This study also suggests that instructors of engineering education can turn their traditional teaching-learning activities into dynamic learning activities by utilizing "active learning teaching-learning model".

• 보건행정학회지
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• 제11권2호
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• pp.141-168
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• 2001

Healthcare service organizations can apply the cost of quality(COQ) model as a method to evaluate a service quality improvement project such as Total Quality Management (TQM). COQ model has been used to quantify and evaluate the efficiency and effectiveness of TQM project through estimation between cost and benefit in intervention for a quality Improvement to provide satisfied services for a customer, and to identify a non value added process. For estimating cost of quality, We used activities and activity costs based on Activity Based Costing(ABC) system. These procedures let the researchers know whether the process is value-added by each activity, and identify a process to require improvement in TQM project. Through the series of procedures, health care organizations are service organizations can identify a problem in their quality improvement programs, solve the problem, and improve their quality of care for their costumers with optimized cost. The study subject was a quality improvement program of the department of radiology department in a hospital with n bed sizes in Metropolitan Statistical Area (MSA). The principal source of data for developing the COQ model was total cases of retaking shots for diagnoses during five months period from December of the 1998 to April of the 1999 in the department. First of the procedures, for estimating activity based cost of the department of diagnostic radiology, the researchers analyzed total department health insurance claims to identify activities and activity costs using one year period health insurance claims from September of the 1998 to August of the 1999. COQ model in this study applied Simpson & Multher's COQ(SM's COQ) model, and SM's COQ model divided cost of quality into failure cost with external and internal failure cost, and evaluation/prevention cost. The researchers identified contents for cost of quality, defined activities and activity costs for each content with the SM's COQ model, and finally made the formula for estimating activity costs relating to implementing service quality improvement program. The results from the formula for estimating cost of quality were following: 1. The reasons for retaking shots were largely classified into technique, appliances, patients, quality management, non-appliances, doctors, and unclassified. These classifications by reasons were allocated into each office doing re-taking shots. Therefore, total retaking shots categorized by reasons and offices, the researchers identified internal and external failure costs based on these categories. 2. The researchers have developed cost of quality (COQ) model, identified activities by content for cost of quality, assessed activity driving factors and activity contribution rate, and calculated total cost by each content for cost for quality, except for activity cost. 3. According to estimation of cost of quality for retaking shots in department of diagnostic radiology, the failure cost was ￦35,880, evaluation/preventive cost was ￦72,521, two times as much as failure cost. The proportion between internal failure cost and external failure cost in failure cost is similar. The study cannot identify trends on input cost and quality improving in cost of qualify over the time, because the study employs cross-sectional design. Even with this limitation, results of this study are much meaningful. This study shows possibility to evaluate value on the process of TQM subjects using activities and activity costs by ABC system, and this study can objectively evaluate quality improvement program through quantitative comparing input costs with marginal benefits in quality improvement.

• 대한교통학회지
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• 제32권5호
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• pp.544-553
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• 2014

활동기반 모형은 개개인의 다양한 일상 활동을 교통계획의 의사결정단위로 파악하고, 인간의 활동으로 인해 파생된 통행을 분석한다. 즉, 동일한 활동패턴 집단의 유형의 사회경제적, 상황적 특성에 따라 어떤 활동을 수행할 것인지를 결정하고 활동수행주체의 활동시간, 공간의 이동, 교통수단을 선택하는 행위에 대한 예측을 수행한다. 통행은 개인과 다른 사람들이 참여하여 이루어지는 복합적인 의사결정 과정으로 간주되기 때문에 이를 통한 활동기반모형은 교통수요 예측에 있어 보다 효율적이면서 현실에 부합한 수요추정을 수행 할 수 있다. 이러한 과정에서 개인의 하루 활동유형을 선택하는 과정은 매우 중요하며, 이에 따라 활동기반 모형의 통행이 발생된다고 할 수 있다. 본 연구에서는 개인의 활동유형 선택에 영향을 주는 요인을 파악하고, 개개인의 특성에 따라 활동유형 선택행태를 분석하였다. 먼저 통행사슬 유형과 활동목적을 검토하여 활동유형을 분류하고, 활동유형선택에 영향을 미치는 개개인의 사회경제적 특성변수를 도출하였다. 다음으로 활동유형별 다항 로지스틱 회귀분석 모형을 구축하여, 활동수행주체의 복합적 특성에 따라 선호되는 활동패턴에 대한 분석을 수행하였다. 결론적으로 활동유형의 선택은 활동수행주체의 복합적인 특성에 의존하며, 장래 활동기반 교통수요 예측에 있어 개인의 복합적인 특성이 활동기반 모형의 활동스케줄 결정 과정에서 고려되어야 함을 시사하고 있다.

• 지역사회간호학회지
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• 제32권3호
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• pp.344-355
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• 2021

Purpose: With low birth rates and aging population problems in Korea, the number of foreign workers grows rapidly. The purpose of this study was to identify factors influencing physical activity of foreign workers based on a Health Promotion Model by examining relationships between acculturation, perceived benefits, perceived barriers, exercise self-efficacy, activity-related affect, social support, and physical activity. Methods: The participants were foreign workers aged 18 to 60 who were employed at eight shipyards. A questionnaire was distributed to 216 participants. Results: As a result of the multivariate ordinal logistic regression analysis, factors affecting physical activity of foreign workers were perceived benefits (B=.65, 95% CI=0.08~1.22), exercise self-efficacy (B=.16, 95% CI=0.05~0.26), integration (B=.41 95% CI=0.14~0.69), and social support for physical activity (B=.48, 95% CI=0.12~0.83). The total explanatory power was 17.7% (x²=41.95, p<.001). Conclusion: Based on these results, there is a need to develop a customized program to increase physical activities of foreign workers by enhancing integration, perceived benefits, exercise self-efficacy and social support.

• 인터넷정보학회논문지
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• 제22권3호
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• 한국지하수토양환경학회지:지하수토양환경
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• 제16권4호
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• pp.23-30
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• 2011

Risk based pollution level of Pb and Cd in metal contaminated soils depending on physicochemical properties of soil in a target site was assessed using biotic ligand model. Heavy metal activity in soil solution defined as exposure activity (EA) was assumed to be toxic to Vibrio fischeri and soil organisms. Predicted effective activity (PEA) determined by biotic ligand model was compared to EA value to calculate risk quotient. Field contaminated soils (n = 10) were collected from a formes area and their risk based pollution levels were assessed in the present study using the calculated risk quotient. Concentrations of Pb determined by aqua regia were 295, 258, and 268 mg/kg in B, H and J points and concentrations of Cd were 4.73 and 6.36 mg/kg in G and I points, respectively. These points exceeded the current soil conservation standards. However, risk based pollution levels of the ten points were not able to be calculated because concentrations of Pb and Cd in soil solution were smaller than detection limits or one (i.e., non toxic). It was because heavy metal activity in soil solution was dominant toxicological form to organisms, not a total heavy metal concentration in soil. In addition, heavy metal toxicity was decreased by competition effect of major cations and formation of complex with dissolved organic carbon in soil solution. Therefore, it is essential to consider site-specific factors affecting bioavailability and toxicity for estimating reliable risk of Pb and Cd.

• 통합자연과학논문집
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• 제8권3호
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• pp.214-220
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• 2015

Cancer has emerged as one of the leading cause of deaths worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of quinazoline-based anticancer agents. Purpose of the study is to understand the structural basis for their inhibitory activity. Comparative molecular field analysis (CoMFA) technique was employed to develop 3D-QSAR model. Ligand-based alignment scheme was used to generate a reliable CoMFA model. The model produced statistically significant results with a cross-validated correlation coefficient ($q^2$) of 0.589 and a non-cross-validated correlation coefficient ($r^2$) of 0.928. Model was further validated by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel and more potent anticancer agents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4176-4197
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• 2020

Botnet is a type of dangerous malware. Botnet attack with a collection of bots attacking a similar target and activity pattern is called bot group activities. The detection of bot group activities using intrusion detection models can only detect single bot activities but cannot detect bots' behavioral relation on bot group attack. Detection of bot group activities could help network administrators isolate an activity or access a bot group attacks and determine the relations between bots that can measure the correlation. This paper proposed a new model to measure the similarity between bot activities using the intersections-probability concept to define bot group activities called as B-Corr Model. The B-Corr model consisted of several stages, such as extraction feature from bot activity flows, measurement of intersections between bots, and similarity value production. B-Corr model categorizes similar bots with a similar target to specify bot group activities. To achieve a more comprehensive view, the B-Corr model visualizes the similarity values between bots in the form of a similar bot graph. Furthermore, extensive experiments have been conducted using real botnet datasets with high detection accuracy in various scenarios.

• 한국음향학회지
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• 제26권5호
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• pp.194-198
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• 2007

본 논문에서는 음성의 통계적 모델에 기반한 음성검출기의 성능향상을 위해 변별적 가중치 학습(discriminative weight training) 기반의 최적화된 우도비 테스트(Likelihood Ratio Test, LRT)를 제안한다. 먼저, 기존의 통계모델기반의 음성검출기를 분석하고, 이를 기반으로 MCE(minimum classification error)방법을 도입하여, 각 주파수 채널별로 다른 가중치를 가지는 우도비 기반의 음성검출 결정법(decision rule)을 제시한다. 제안된 알고리즘은 비정상(non-stationary)잡음환경에서 기존의 동일 가중치를 가지는 기하 평균 기반의 음성검출기와 비교하였으며, 우수한 성능을 보인다.

• Journal of Construction Engineering and Project Management
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• 제3권2호
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• pp.21-34
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• 2013

Various risk factors affect construction projects. Due to the uncertainties created by risk factors, actual activity durations frequently deviate from the estimated durations in either favorable or adverse direction. For this reason, evaluation of schedule uncertainty is required to make decisions accurately when managing construction projects. In this regard, this paper presents a new computer simulation model - the Repetitive Schedule Risk Analysis Model (RSRAM) - to evaluate unit-based repetitive building project schedules under uncertainty when activity durations and risk factors are correlated. The proposed model utilizes Monte Carlo Simulation and a Critical Path Method based repetitive scheduling procedure. This new procedure concurrently provides the utilization of resources without interruption and the maintenance of network logic through successive units. Furthermore, it enables assigning variable production rates to the activities from one unit to another and any kind of relationship type with or without lag time. Details of the model are described and an example application is presented. The findings show that the model produces realistic results regarding the extent of uncertainty inherent in the schedule.