• Geomechanics and Engineering
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• 제37권5호
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• 한국과학교육학회지
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• 제35권2호
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• pp.267-275
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• 2015

본 연구의 목적은 우리나라 학생들의 인지적 속성의 특징을 인지진단이론에 근거하여 국제적인 수준에서 비교 분석하고 우리나라 교육에 주는 시사점을 찾는 것이다. TIMSS 2011의 평가틀에 근거하여 9개의 인지 속성을 추출하였고 TIMSS 2011의 과학 문항 216개에 대해 각 문항이 어떠한 인지 속성들을 요구하는지 판단하여 Q행렬을 작성하였다. 총 5차례의 검토와 수정을 반복하여 타당도를 점검하고 최종적인 Q행렬을 작성한 후, 다층 IRT 분석을 실시하여 인지 속성에 따른 국가별 특성을 파악하였다. 분석을 통해 나타난 우리나라의 인지적 속성을 TIMSS 2011의 과학성취도 상위 15개국과 비교한 결과 우리나라 학생들에게 모형사용하기, 자료분석하기, 결론도출하기, 평가 및 정당화하기는 쉬운 속성에 해당하였고 회상/인식하기, 설명하기, 분류하기, 통합하기, 가설설정 및 실험설계하기는 어려운 속성에 해당하였다. 우리나라 학생들이 가장 쉬워하는 인지 속성은 자료해석하기였고 가장 어려워하는 인지 속성은 설명하기였다. 우리나라의 경우 쉬운 인지 속성의 대부분은 비교국 중에서 가장 쉽게 여기고 어려운 인지 속성은 가장 어렵게 여기는 것으로 나타나 극단적인 특성을 보였다. 따라서 특정한 인지 속성이 많이 활용되도록 하기 보다는 여러가지 인지 속성이 골고루 활용되도록 과학 교육과정과 과학 교과서를 구성할 필요가 있겠다.

• 한국콘텐츠학회논문지
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• 제17권9호
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• pp.192-202
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• 2017

본 연구는 NCS를 기반으로 한 음식 조리분야 교육과정의 주관적 인식을 파악하고자 호텔조리학과 졸업생을 대상으로 Q방법론을 적용하였다. 연구의 목적은 NCS를 기반으로 한 음식 조리분야 교육과정에 관한 주관적 구조를 유형화 하며, NCS를 기반으로 한 음식 조리분야 교육과정에 관한 유형들 간의 특성을 기술하고 분석하여 향후 시사점을 제시하고자 한다. 유형분석 결과, 총 4가지로 도출되었다. 제 1유형(N=7) : 기초실무 수업 추구형 (Seeking Basic Practical Classes type), 제 2유형(N=5) : 국내 취업 선호형(Prefer domestic employment type), 제 3유형(N=5) : 유명 셰프초청 수업 추구형(Pursuit of famous chef inviting class type), 제 4유형(N=3) : 현장실무 맞춤수업 추구형 (Seeking tailor-made lessons typ) 으로, 각각의 유형마다 다양한 특징이 있는 것으로 분석되었다. 향후 NCS기반 음식 조리분야 교육과정에 관한 연구에서는 많은 문헌과 실증연구를 바탕으로 보다 세밀한 Q방법론적인 질문과 분석기법으로 수정 보완하여, 응답자들의 다양한 의견을 보다 구체적이며 객관적으로 분석하고자 한다.

• Membrane and Water Treatment
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• 제9권6호
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• pp.455-462
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• 2018

The measurement and monitoring of the biochemical oxygen demand (BOD) play an important role in the planning and operation of wastewater treatment plants. The most basic method for determining biochemical oxygen demand is direct measurement. However, this method is both expensive and takes a long time. A five-day period is required to determine the biochemical oxygen demand. This study has been carried out in a wastewater treatment plant in Turkey (Hurma WWTP) in order to estimate the biochemical oxygen demand a shorter time and with a lower cost. Estimation was performed using artificial neural network (ANN) method. There are three different methods in the training of artificial neural networks, respectively, multi-layered (ML-ANN), teaching learning based algorithm (TLBO-ANN) and artificial bee colony algorithm (ABC-ANN). The input flow (Q), wastewater temperature (t), pH, chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (tP), total nitrogen (tN), and electrical conductivity of wastewater (EC) are used as the input parameters to estimate the BOD. The root mean squared error (RMSE) and the mean absolute error (MAE) values were used in evaluating performance criteria for each model. As a result of the general evaluation, the ML-ANN method provided the best estimation results both training and test series with 0.8924 and 0.8442 determination coefficient, respectively.

• 보건교육건강증진학회지
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• 제31권4호
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• pp.93-106
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• 2014

Objectives: The aim of this study was to develop the efficient program protecting shift to cerebrovascular disease as complication for patients with diabetes and hypertension. Methods: Chronic disease self management program(CDSMP), implement manual, action plan, Q&A card and motivation methods were suggested based on Bandura's social learning theory through reviewing various literatures and cases. Results: This program can increase self-efficacy, individual health behavior change and quality of life and it makes to continuous care of chronic disease. Conclusion: In order to operate chronic disease self-management program, standardized education courses training of specialist leaders and expert patients leaders would be required. And the development enlargement of self-management program for various other chronic disease such as arthritis, back pain, atopy, asthma would be required in the future.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.57-60
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• 1999

An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.45-46
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• 2019

본 논문에서는 Upper Confidence Bound (UCB)를 이용한 효율적인 패킷 스케줄링 기법을 제안한다. 기존 e-greedy 등 강화학습의 보상을 극대화 할 수 있는 행동을 선택하는 것과 다르게, 제안된 UCB를 이용한 강화학습 패킷 스케줄링 기법은 각 상태에서 행동을 선택한 횟수를 추가적으로 고려한다. 이는 보다 효율적인 강화학습의 탐구(Exploration)를 가능케 한다. 본 논문에서는 컴퓨터 시뮬레이션을 통하여 제안하는 UCB를 이용한 강화학습 패킷 스케줄링 기법이 기존의 e-greedy 및 softmax를 기반으로 한 패킷 스케줄링 기법에 비해 정확도 측면에서 향상된 정확도를 보인다.

• 패션비즈니스
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• 제24권6호
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• pp.135-147
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• 2020

This study explored students' online fashion studio class experiences, and investigated the factors affecting their class satisfaction. An online survey of college students who were enrolled in online studio classes within apparel and fashion-related departments during the spring of 2020 was conducted in June 2020. Responses from a total of 213 participants were included in the final data. Respondents rated lecture clips as the most useful, followed by teacher demonstration and feedback, PowerPoint (PPT) supplements, and Q&As. Frequently mentioned areas of improvement were online platform stability and video quality. Many respondents also stated that more streamlined teacher-student communication channels, immediate and meticulous teacher feedback, the adoption of course contents developed specifically for an online environment, and provisions for equipment usage would be desirable. Student satisfaction of an online fashion design studio class was significantly affected by teaching presence, social presence, online learning system stability, perceived usefulness of teacher's demonstration, and affective response toward COVID-19. Students satisfaction of an online garment construction studio class was significantly affected by teaching and social presence, online learning system stability, and perceived usefulness of teacher's demonstration. Based on these findings, we recommend developing teaching contents and methods that allow students to feel included in class and establish an online system with various functions to enhance the sense of social connection that can enable two-way communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• 정보교육학회논문지
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• 제11권1호
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• pp.79-89
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• 2007

10대 학생들의 지속적인 인터넷 이용률 상승과 높은 온라인 커뮤니티 참여율을 고려할 때, 그들이 인터넷 이용을 통해 경험할 수 있는 역기능을 최소화하고 긍정적인 경험을 쌓을 수 있도록 지도하는 것이 필요하다. 학생들은 온라인 커뮤니티 활동을 통해서 다양한 사회성을 경험하고, 자아성을 탐색할 수 있다. 그러나 다른 한편으로, 학생들을 대상으로 하는 상당수의 온라인 커뮤니티들이 사회적인 배려와 관심을 제공하지 못하여 학생들의 가치관 혼란이나 잘못된 행동을 유도하기도 한다. 이러한 문제를 고려하여, 본 연구는 10대 학생들의 요구를 수용하면서 동시에 그들의 요구를 학습 활동과 연계할 수 있는 온라인 학습 커뮤니티에 초점을 두고, 활발한 공동체 활동과 학습 활동을 진행할 수 있는 온라인 학습 커뮤니티를 설계하고 개발하였다. 커뮤니티는 운영 취지를 소개하고, 알림방, 요구함 등을 제시하는 'e-Tivity소개', '이벤트홀' '자료파크' 'e-Tivity센터' 등으로 구성된 커뮤니티 활동 공간, '교사연구실' '관리실'로 구성된 교사와 관리자 공간, 'My Room' 아바타 꾸미기 등의 기능을 제공하는 학생 개인 공간 등으로 구성되었다.