• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.17-23
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• 2005

In this paper we consider the well-known semiparametric proportional hazards models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions(covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enables us to estimate the survival curve when n ${\ll}$p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA (cDNA) data and Breast Carcinomas data.

• Journal of Hospice and Palliative Care
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• 제23권2호
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• pp.44-54
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• 2020

Purpose: The purpose of this study was to analyze the experiences of acute care hospital nurses' on spiritual care with focus group interviews. Methods: Data were collected from 24 nurses recruited from one acute-care hospital in a southern province of Korea. Six focus groups were assembled considering age and religion. All interviews were recorded and transcribed. Data were analyzed using qualitative content analysis. Results: Five categories with 14 sub-categories emerged: 1) ambiguous concept: confusing terms, an additional job; 2) assessment of spiritual care needs: looking for spiritual care needs, not recognizing spiritual care needs; 3) spiritual care practices: active spiritual care, passive spiritual care ; 4) outcomes of spiritual care: comfort of the recipient, comfort of the provider; and 5) barriers to spiritual care: fear of criticism from others, lack of education, lack of time, space constraints, and absence of a recording system. Conclusion: Participants perceived spiritual care as an uncertain concept. Some participants recognized it as a form of nursing care, and others did not. They practiced spiritual care in acute-care settings according to their personal perceptions of spiritual care. Therefore, in order to perform spiritual nursing in acute-care hospitals, it is a priority for nurses to recognize the concept of spiritual nursing accurately. It is also necessary to prepare a hospital environment suitable for the provision of spiritual care.

• 대한안전경영과학회지
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• 제6권3호
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• pp.141-152
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• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where JIT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying JIT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 춘계학술대회
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• pp.191-201
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• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where ]IT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying ]IT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• ETRI Journal
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• 제38권6호
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• Earthquakes and Structures
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• 제9권5호
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• pp.1069-1089
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• 2015

This paper investigates the limits and efficacies of the Fiber Reinforced Polymer (FRP) material for strengthening mid-rise RC buildings against seismic actions. Turkey, the region of the highest seismic risk in Europe, is chosen as the case-study country, the building stock of which consists in its vast majority of mid-rise RC residential and/or commercial buildings. Strengthening with traditional methods is usually applied in most projects, as ordinary construction materials and no specialized workmanship are required. However, in cases of tight time constraints, architectural limitations, durability issues or higher demand for ductile performance, FRP material is often opted for since the most recent Turkish Earthquake Code allows engineers to employ this advanced-technology product to overcome issues of inadequate ductility or shear capacity of existing RC buildings. The paper compares strengthening of a characteristically typical mid-rise Turkish RC building by two methods, i.e., traditional column jacketing and FRP strengthening, evaluating their effectiveness with respect to the requirements of the Turkish Earthquake Code. The effect of FRP confinement is explicitly taken into account in the numerical model, unlike the common procedure followed according to which the demand on un-strengthened members is established and then mere section analyses are employed to meet the additional demands.

• Journal of Power Electronics
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• 제16권1호
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• pp.111-120
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• 2016

Generally, a single phase H-bridge converter feeding a single primary track is employed in conventional inductive power transfer systems. However, these systems may not be suitable for some high power applications due to the constraints of the semiconductor switches and the cost. To resolve this problem, a novel dual coupled primary tracks IPT system consisting of two high frequency resonant inverters feeding the tracks is presented in this paper. The primary tracks are wound around an E-shape ferrite core in parallel which enhances the magnetic flux around the tracks. The mutual inductance of the coupled tracks is utilized to achieve adjustable power sharing between the inverters by configuring the additional resonant capacitors. The total transfer power can be continuously regulated by altering the pulse width of the inverters' output voltage with the phase shift control approach. In addition, the system's efficiency and the control strategy are provided to analyze the characteristic of the proposed IPT system. An experimental setup with total power of 1.4kW is employed to verify the proposed system under power ratios of 1:1 and 1:2 with a transfer efficiency up to 88.7%. The results verify the performance of the proposed system.

• 융합신호처리학회논문지
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• 제3권4호
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• pp.17-22
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• 2002

본 논문은 연속적으로 움직이는 심장의 모습을 추적하기 위해 레벨 세트 알고리즘과 양방향 곡선 전개 이론을 적용한 활성 모델을 사용하였다. 대부분의 활성 모델이 영상 그라디언의 에지 갭이 존재하는 영역에서 움직임이 안정적이지 않아 추출에 실패할 확률이 많다. 본 연구에서는 영상 자체의 밝기 값과 안정적 추출을 위한 추가 제약만 이용한 새로운 활성 모델을 제안한다. 제안된 모델은 초기 곡선의 위치 설정에 제약이 없어 특히 연속적 영상의 특정한 대상 영역을 추출하거나 추적하기에 효율적이었다. 또한 에지 정보가 심하게 변화거나 모호한 부분에서도 안정적인 곡선의 움직임과 추출 결과를 보였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2012년도 제38회 춘계학술대회논문집
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• pp.46-51
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• 2012

본 연구에서는 액체로켓엔진 단계식 연소 사이클의 기본 설계 사양을 도출하기 위한 시스템 해석을 수행하였다. 액체산소를 산화제로 하고 액체수소와 RP-1을 각각 연료로 사용하는 엔진에 대해 사이클 해석을 적용하였다. 엔진의 성능지표인 비추력을 기준으로 하여 실제 개발되어있는 엔진과 1% 이내의 차이를 보였다. 사이클 해석을 위해 개발된 프로그램은 압력과 유량 균형, 터보펌프-터빈의 에너지 균형 조건을 만족하며 주어진 추력에 대한 연료 소모와 비추력 및 각 부품의 기본적인 사양을 도출할 수 있다. 추가적인 제한조건들의 조사가 이루어지면 통합 최적화 프로그램으로 발전시킬 수 있을 것으로 판단된다.

• 스마트미디어저널
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• 제8권2호
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• pp.46-57
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• 2019

In recent research, deep learning-based methods have achieved state-of-the-art performance in various computer vision tasks. However, these methods are commonly supervised, and require huge amounts of annotated data to train. Acquisition of data demands an additional costly effort, particularly for the tasks where it becomes challenging to obtain large amounts of data considering the time constraints and the requirement of professional human diligence. In this paper, we present a data level synthetic sampling solution to learn from small and imbalanced data sets using Generative Adversarial Networks (GANs). The reason for using GANs are the challenges posed in various fields to manage with the small datasets and fluctuating amounts of samples per class. As a result, we present an approach that can improve learning with respect to data distributions, reducing the partiality introduced by class imbalance and hence shifting the classification decision boundary towards more accurate results. Our novel method is demonstrated on a small dataset of 2789 tomato plant disease images, highly corrupted with class imbalance in 9 disease categories. Moreover, we evaluate our results in terms of different metrics and compare the quality of these results for distinct classes.