• 설비공학논문집
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• 제29권12호
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Journal of Information Processing Systems
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• 제16권1호
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• pp.171-183
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• 2020

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

• Journal of Information Science Theory and Practice
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• 제9권4호
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• pp.35-49
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• 2021

In a situation where there are multiple diverse datasets, it is essential to have an efficient method to provide users with the datasets they require. To address this suggestion, necessary datasets should be selected on the basis of the relationships between the datasets. In particular, in order to discover the necessary datasets for disaster resolution, we need to consider the disaster resolution stage. In this paper, in order to provide the necessary datasets for each stage of disaster resolution, we constructed a disaster type and disaster management process ontology and designed a method to determine the necessary datasets for each disaster type and disaster management process step. In addition, we introduce a method to determine relationships between datasets necessary for disaster response. We propose a method for discovering datasets based on minimal relationships such as "isA," "sameAs," and "subclassOf." To discover suitable datasets, we designed a knowledge exploration model and collected 651 disaster-related datasets for improving our method. These datasets were categorized by disaster type from the perspective of disaster management. Categorizing actual datasets into disaster types and disaster management types allows a single dataset to be classified as multiple types in both categories. We built a knowledge exploration model on the basis of disaster examples to ensure the configuration of our model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.147-165
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• 2021

In this work, we empirically evaluated the efficiency of the recent EfficientNetB0 model to identify and diagnose malaria parasite infections in blood smears. The dataset used was collected and classified by relevant experts from the Lister Hill National Centre for Biomedical Communications (LHNCBC). We prepared our samples with minimal image transformations as opposed to others, as we focused more on the feature extraction capability of the EfficientNetB0 baseline model. We applied transfer learning to increase the initial feature sets and reduced the training time to train our model. We then fine-tuned it to work with our proposed layers and re-trained the entire model to learn from our prepared dataset. The highest overall accuracy attained from our evaluated results was 94.70% from fifty epochs and followed by 94.68% within just ten. Additional visualization and analysis using the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm visualized how effectively our fine-tuned EfficientNetB0 detected infections better than other recent state-of-the-art DCNN models. This study, therefore, concludes that when fine-tuned, the recent EfficientNetB0 will generate highly accurate deep learning solutions for the identification of malaria parasites in blood smears without the need for stringent pre-processing, optimization, or data augmentation of images.

• 한국컴퓨터그래픽스학회논문지
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• 제29권1호
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• pp.23-29
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• 2023

본 논문은 강화학습을 통해 이족보행에 대한 모션 캡처를 통해 참조 모션의 데이터들을 기반으로 근골격 캐릭터의 시뮬레이션을 적은 비용으로 높은 품질의 결과를 얻을 방법을 소개한다. 우리는 참조 모션 데이터를 캐릭터 모델이 수행할 수 있게끔 재설정을 한 후, 강화학습을 통해 해당 모션을 학습하도록 훈련시킨다. 참조 모션 모방과 근육에 대한 최소한의 메타볼릭 에너지를 결합하여 원하는 방향으로 근골격 모델이 이족보행을 수행하게끔 학습한다. 이러한 방법으로 근골격 모델은 기존의 수동으로 설계된 컨트롤러보다 적은 비용으로 학습할 수 있으며 높은 품질의 이족보행을 수행할 수 있게 된다.

• 천문학회보
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• 제44권2호
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• pp.73.3-73.3
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• 2019

The AGN unification model suggested the presence of obscuring material, a dusty torus, to explain the various types of AGN. IR SED model fitting is a crucial tool to probe the structure and properties of the dusty torus. We use a sample of 16 local quasi-stellar objects in Martinez-Paredes et al. (2017) with obtained NIR and MIR high-angular resolution (~0.3") imaging data from EMIR, CIRCE and CanariCam on the 10.4-m Gran Telescopio CANARIAS (GTC) while 4 objects have NIR high-angular resolution photometry from NICMOS/HST from the literature. The unresolved NIR emission from the NIR image analysis and low-resolution Spitzer/IRS spectra are used to construct NIR-MIR SEDs covering a larger spectral range. We investigate the sensitivity of the geometrical (e.g. viewing angle) and physical parameters (e.g. optical depth) of the clumpy dusty torus model of Nenkova et al. and the clumpy disk+outflow model of Hoenig et al. We aim to investigate the minimal dataset needed to well constrain the parameters of the models and derive the properties of the dusty torus. These results will allow us to plan future observations for a larger sample of high luminosity AGNs with the James Webb Space Telescope and the Giant Magellan Telescope.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2002년도 춘계 학술발표회 논문집
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• pp.203-210
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• 2002

The past bridge design specifications of Korea didn't include 1imitation on the amount of lap splices in the plastic hinge zone of piers, and so do current specifications. But these specifications include just limitation on the minimal length of lap splices. Thus, a large majority of non-seismically designed bridge piers may have lap splices in plastic hinge zone. In this study, model pier was selected among existent bridge piers whose failure mode is complex shear-flexure mode. Full scaled RC pier models whose aspect ratio is about 2.67 were constructed and quasi static test according to the drift level history was implemented. From the test results, effect of the lap splices on the seismic performance of bridges piers was analyzed, and the seismic capacity of the model bridges was evaluated by capacity spectrum method.

• 한국안전학회지
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• 제30권4호
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• pp.174-180
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• 2015

This study developed a Safety Culture Impact Assessment Model (SCIAM) which consists of a safety culture assessment methodology and a safety culture impact quantification methodology. The SCIAM uses safety culture impact index (SCII) to monitor the status of safety culture of the NPPs periodically and it uses relative core damage frequency (RCDF) to present the impact of safety culture on the safety of the NPPs. As a result of applying SCIAM to the reference plant (Kori 3), the standard for the healthy safety culture of the reference plant is suggested. SCIAM might contribute to improve the safety of the NPPs (Nuclear Power Plants) by monitoring the status of safety culture periodically and presenting the standard of healthy safety culture.

• 한국자동차공학회논문집
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• 제7권9호
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• pp.165-171
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• 1999

An oil layer fuel absorption /desorption modeling was developed. Multi-component fuel model has showed more reasonable condition than single component model. Henry's constant which is related to solubility is the most important variable in the oil layer absorption/desorption mechanism. The oil segments close to the top of the cylinder liner have more significant contribution to the fuel absorption and desorption process than other oil segments. At the warmed-up condition, the effect of the engine speed on the precent fuel absorbed/desorbed is minimal. But at low il film temperature, percent of fuel abosrbed/desorbed is decreased with increasing the engine speed because of low value of molecular diffusion coefficient of fuel. The amount of fuel trapped in the piston crevice is from 2 to 2.3 times larger than that of fuel in the oil fim. However, fuel form oil film slowly desorbs into the combustion chamber compared with fuel from the piston crevices when the engines is cold.

• International Journal of Quality Innovation
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• 제5권1호
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• pp.1-9
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• 2004

The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.