• Journal of Korean Biological Nursing Science
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• v.21 no.4
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• pp.249-258
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• 2019

Purpose: The purpose of this study was to assess the psychosocial status of candidates for deceased donor kidney transplantation (DDKT) in South Korea and identify factors associated with high-risk psychosocial status. Methods: The descriptive cross-sectional design included application of a standardized transplantation-specific assessment tool, the Psychosocial Assessment Candidacy Transplantation (PACT) instrument, and review of candidates' medical records. A total of 157 patients awaiting DDKT were recruited from a Korean organ transplantation center. The collected data were analyzed using descriptive statistics and binary logistic regression. Candidates were divided into high- and low-psychosocial risk groups using 3 as the cutoff point of PACT. Results: The mean score for the PACT final rating was 2.10, and the lowest average subscale score was 2.30 for understanding the processes of transplantation and follow up. Poor physical candidacy, especially due to comorbidities, and older age were associated with high psychosocial risk. Conclusion: The results of this study showed that the psychosocial status of Korean DDKT candidates was problematic. Development of systematic management programs for effective clinical strategies in the care of candidates is crucial to maintain their desirable psychosocial status in case of an emergency DDKT operation and improve post-transplantation outcomes. Continuous education is absolutely necessary to enhance understanding of the transplantation process for high-risk psychosocial candidates. Additionally, nurses and transplantation professionals should screen candidates with high-risk psychosocial status early in the process using transplantation-specific assessment tools and provide intensive interventions, particularly for poor physical candidacy patients and older candidates.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.612-628
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• 2001

This paper presents a methodology to extract classes and inheritance relations from procedural software. The methodology is based on the idea of generating all groups of class candidates, based on the combinatorial groups of object candidates, and their inheritance with all possible combinations and selecting a group of object candidates, and their inheritance with all possible combinations and selecting a group with the best or optimal combination of candidates with respect to the degree of relativity and similarity between class candidates in the group and classes in a domain model. The methodology has innovative features in class candidates in the group and classes in a domain model. The methodology has innovative features in class and inheritance extraction: a clustering method based on both static (attribute) and dynamic (method) clustering, the combinatorial cases of grouping class candidate cases based on abstraction, a signature similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement, that is, the horizontal measurement for overall group similarity between n class candidates and m classes, and the vertical measurement for specific similarity between a set of classes in a group of class candidates and a set of classes with the same class hierarchy in a domain model, etc. This methodology provides reengineering experts with a comprehensive and integrated environment to select the best or optimal group of class candidates.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.1-10
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• 2007

In this paper, we focus on churn analysis for the first successful candidates in the entrance examination on 2006 year using Clementine, data mining tool. The goal of this study is to apply decision tree including C5.0 and CART algorithms, neural network and logistic regression techniques to predict a successful candidate churn. And we analyze the churning and nochurning successful candidates and why the successful candidates churn and which successful candidates are most likely to churn in the future using data from entrance examination data of K university on 2006 year.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.109-115
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• 2009

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. In this paper, we investigate several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. At first, word distance method based on phone and syllable distances are considered. These methods use just Levenstein distance on phones or double Levenstein distance algorithm on syllables of candidates. Next, word similarity approaches are presented that they use characters' position information of word candidates. Each character's position is labeled to inserted, deleted, and correct position after alignment between source and target string. The word similarities are obtained from characters' positional probabilities which mean the frequency ratio of the same characters' observations on the position. From experimental results, we can find that the proposed methods are effective for removing non-similar words without loss of system performance from the N-best recognition candidates of the systems.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.93-98
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• 2002

It is important to evaluate the performance of candidates mathematically from various aspects, and reflect it on decision making. In decision making, we judge the candidates through two steps, classification of objects and comparison of objects or candidates with plural elements. In the former step, Analytic Hierarchy Process (AHP) is useful method to evaluate candidates from plural viewpoints, and in the later step, Data Envelopment Analysis (DEA) is also useful method to evaluate candidates with plural categorized data. In fact, each candidate has plural elements, nevertheless it has been more important to evaluate from various aspects in IT society. So, we propose a new procedure complementing AHP with DEA.

• Journal of Astronomy and Space Sciences
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• v.39 no.4
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• pp.141-144
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• 2022

By providing an environment where energetic particles and micrometeorites can not penetrate, caves on Mars may serve as a human shelter in future Mars explorations. More than 1,000 cave entrance candidates have been detected; however, their physical characteristics that can be utilized in detecting more candidates have not been explored in detail. In this paper, we explore the nighttime temperature of 100 cave entrance candidates and their surrounding areas to investigate 1) the nighttime temperature tendencies relative to their surrounding areas and 2) the extent of these temperature differences. We find that 79% of the cave entrance candidates exhibit higher temperatures than the surrounding areas, and 59% show a temperature difference over 20K, suggesting that the cave entrances may generally show higher temperatures than the surrounding areas during the nighttime.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.141-144
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• 2014

Recently, cave candidates have been discovered on other planets besides the Earth, such as the Moon and Mars. When we go to other planets, caves could be possible human habitats providing natural protection from cosmic threats. In this study, seven cave candidates have been found on Pavonis Mons and Ascraeus Mons in Tharsis Montes on Mars. The cave candidates were selected using the images of the Context Camera (CTX) on the Mars Reconnaissance Orbiter (MRO). The Context Camera could provide images with the high resolution of 6 meter per pixel. The diameter of the candidates ranges from 50 to 100m. Cushing et al. (2007) have analyzed the temperature change at daytime and nighttime using the Thermal Emission Imaging System (THEMIS) for the sites of potential cave candidates. Similarly, we have examined the temperature change at daytime and at nighttime for seven cave candidates using the method of Cushing et al. (2007). Among those, only one candidate showed a distinct temperature change. However, we cannot verify a cave based on the temperature change only and further study is required for the improvement of this method to identify caves more clearly.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.57.1-57.1
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• 2014

We present the preliminary results of CO outflow survey toward the 56 Very Low Luminosity Object (VeLLO) candidates at CO J=2-1 and J=3-2 transitions with two radio telescopes of the Caltech Submillimeter Observatory (CSO) and the Atacama Submillimeter Telescope Experiment (ASTE). The survey is aimed to understand the origin of the formation of low-mass stars or substellar objects. The VeLLO is a very faint (${\leq}0.1$ $L_{\odot}$) object deeply embedded in dense molecular clouds and believed to be a proto-brown dwarf which will be a brown dwarf or a faint protostar which has just formed with little mass accretion or which is in quiescent stage of episodic accretion. The candidates were searched for over all nearby ($d{\leq}450$ pc) Gould belt clouds and listed in a new catalogue of the VeLLO candidates by Kim et al. (2014 submitted). To diagnose present status and future fate of the VeLLOs, we conducted a systematic observation for the CO molecular outflows of the 56 VeLLOs to infer how accretion is being made around the VeLLOs. We found 17 VeLLO candidates either having a prominent wing in line profiles or showing bipolar intensity distribution of high velocity components. We will discuss the physical properties of these CO outflows and the identity of the VeLLO candidates.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.11
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• pp.82-88
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• 2007

In this paper, we present a pattern comparison algorithm for reducing fault candidate lists. The number of fault candidates determines the total fault simulation time. To decrease the total fault diagnosis time, the reduction of the number of fault candidates is essential. Critical path tracing determines fault candidate lists detected by a set of tests using a backtracing algorithm starting at the primary outputs of a circuit. The proposed algorithm reduces fault candidates comparing failing patterns with good patterns during critical path tracing process. As we reduce all fault candidates of the circuit to more accurately suspected fault candidates, we can greatly reduce fault simulation time. The proposed algorithm greatly increases simulation speed than that of a conventional backtracing method. The proposed algorithm is applicable to both combinational and sequential circuits. Experimental results on ISCAS#85 and ISCAS#89 benchmark circuits showed fault candidates are pruned and fault diagnosis time is also decreased in proportion to fault candidate decrease.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.47-54
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• 2021

Given a document, keyphrase extraction is to automatically extract words or phrases which topically represent the content of the document. In unsupervised keyphrase extraction approaches, candidate words or phrases are first extracted from the input document, and scores are calculated for keyphrase candidates, and final keyphrases are selected based on the scores. Regarding the computation of the scores of candidates in unsupervised keyphrase extraction, this study proposes a method of adjusting the scores of keyphrase candidates according to the types of keyphrase candidates: word-type or phrase-type. For this, type-token ratios of word-type and phrase-type candidates as well as information content of high-frequency word-type and phrase-type candidates are collected from the input document, and those values are employed in adjusting the scores of keyphrase candidates. In experiments using four keyphrase extraction evaluation datasets which were constructed for full-text articles in English, the proposed method performed better than a baseline method and comparison methods in three datasets.