• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.2812-2817
• /
• 2013

In this paper, an outage probability for the best relay selection in decode-and-forward relaying systems in the presence of interference is analyzed over Rayleigh fading channels. Based on the outage performance results, we propose a method to determine effective relay candidates for the best relay selection, where the effective relay candidates represent the relays except for relays that make no contribution to improving the performance. in all possible relays given in the system. By determining the effective relay candidates, the feedback overhead of channel state information and the energy consumption of relays can be significantly reduced while minimizing the performance degradation. In this paper, we provide important parameters that affect the determination of the effective relay candidates.

• Communications for Statistical Applications and Methods
• /
• v.26 no.2
• /
• pp.149-161
• /
• 2019

In this article, we suggest the following approaches to simultaneous variable selection and outlier detection. First, we determine possible candidates for outliers using properties of an intercept estimator in a difference-based regression model, and the information of outliers is reflected in the multiple regression model adding mean shift parameters. Second, we select the best model from the model including the outlier candidates as predictors using stochastic search variable selection. Finally, we evaluate our method using simulations and real data analysis to yield promising results. In addition, we need to develop our method to make robust estimates. We will also to the nonparametric regression model for simultaneous outlier detection and variable selection.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.80.2-80.2
• /
• 2021

Galactic young massive clusters are the ideal laboratories to study massive stellar evolution. Unfortunately, such objects are rare. Of particular interest are so-called Red Supergiant Clusters (RSGCs) that are currently only found toward the Scutum-Crux Galactic arm. Confirming their nature as RSGC is often not straight-fortward as distinguishing RSGs from AGB stars is still difficult even with high spectral resolution spectra. Here we report that broad band colors using 2MASS JHK and GAIA G band data can be useful in reducing the AGB contamination, thus providing selection criteria that effectively reveal the known RSGCs with negligible false positives. On the other hand, we suggest that RSGC4, one of the proposed RSGC candidates, may not be a cluster of RSGs as their colors are not compatible with our selection criteria. We discuss the nature of these stars together with our IGRINS spectroscopic observations. We also employ the same selection criteria to search for RSGC candidates in other parts of the plane, resulting in no prominent candidates.

• The Journal of the Acoustical Society of Korea
• /
• v.30 no.8
• /
• pp.428-435
• /
• 2011

Many isolated word recognition systems may generate irrelevant words for recognition results because they use only acoustic information or small amount of language information. In this paper, I propose word similarity that is used for selecting (or removing) less common words from candidates by applying Levenshtein distance. Word similarity is obtained by using positional accuracy that reflects the frequency information along to character's alignment information. This paper also discusses various improving techniques of selection of disparate words. The methods include different loss values, phone accuracy based on confusion information, weights of candidates by ranking order and partial comparisons. Through experiments, I found that the proposed methods are effective for removing heterogeneous words without loss of performance.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.18 no.1
• /
• pp.83-88
• /
• 2010

The study is intended to help to select the pilot candidates with exceptional flight aptitude ability and to investigate the relationship between the results of the scholastic aptitude test and the flight aptitude. It is intended that the research will help to draw recommendations on the relevant fields of the scholastic aptitude test that is to be used to select the high caliber candidates with exceptional flight aptitude ability, to gauge the resulting effectiveness of its application and helping to revise the university's syllabus accordingly. From the study, korean, mathematics, english grade and the flight aptitude test results have all shown to hold mutual relationship and through simple correlation analysis, it was discovered that mathematics and English are the two factors that affect the results of the flight aptitude test, with the extent of its impact graded in descending order of English, mathematics and Korean. Lastly, the logistic regression analysis have discovered that the mathematics grade has significant effect on the classification of the flight aptitude and non aptitude category groups, and English also has significant influence close to the 0.05 p-values. It is believed that should the findings of this study be considered as part of the selection process of the university applicants of the department of aeronautical science, making discovery of candidates of higher quality is expected.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.32 no.3
• /
• pp.253-267
• /
• 2022

Objectives: This study was performed to check whether the CRS (Chemical Ranking and Scoring) system is appropriate as a method to determine substances as candidates for substances subject to permission and to apply this system to the selection of candidates for substances subject to permission. Methods: A risk score was obtained by multiplying the hazard score and the exposure score and then ranking them. The hazard sub-indicators are carcinogenicity, germ cell mutagenicity, reproductive toxicity, specific target organ toxicity-repeated exposure, respiratory sensitization and endocrine disrupting chemicals. Exposure sub-indicators are persistence, bioaccumulation and emission volume. Sensitivity analysis was performed for missing values. Correlation analysis and multivariable linear regression analysis were performed among hazard, exposure and risk in order to confirm that CRS was an appropriate method. Results: As a result of the sensitivity analysis on missing values, it was confirmed that the effect on the risk ranking was not sensitive. Correlation and regression analysis confirmed that exposure had a greater effect on risk than hazard. Conclusions: The CRS system, which derives a risk score using a hazard and exposure score, is judged to be appropriate as a method for the selection of preliminary of candidates for substances subject to permission. Benzene, cadmium, nickel, and cobalt were selected as priority candidates for substances subject to permission.

• Journal of KIISE:Software and Applications
• /
• v.29 no.8
• /
• pp.595-603
• /
• 2002

Only a few studies have been conducted on how to select multiple classifiers from the pool of available classifiers for showing the good classification performance. Thus, the selection problem if classifiers on how to select or how many to select still remains an important research issue. In this paper, provided that the number of selected classifiers is constrained in advance, a variety of selection criteria are proposed and applied to tile construction of multiple classifier systems, and then these selection criteria will be evaluated by the performance of the constructed multiple classifier systems. All the possible sets of classifiers are trammed by the selection criteria, and some of these sets are selected as the candidates of multiple classifier systems. The multiple classifier system candidates were evaluated by the experiments recognizing unconstrained handwritten numerals obtained both from Concordia university and UCI machine learning repository. Among the selection criteria, particularly the multiple classifier system candidates by the information-theoretic selection criteria based on conditional entropy showed more promising results than those by the other selection criteria.

• Journal of information and communication convergence engineering
• /
• v.13 no.2
• /
• pp.97-104
• /
• 2015

In this paper, we propose a data envelopment analysis (DEA) and analytic hierarchy process (AHP) integrated model to improve the selection process in the acquisition of a weapon system which is the key component to the success of the project. In particular, we applied DEA in the first stage to choose a frontier group among the candidates in the selection process of the next-generation fighter system (the 3rd FX) in Korea. Then, by using the Delphi technique, we surveyed military experts and applied AHP to determine the best choice among the candidates. The results of the study match the actual decision made by the Korean government in the weapon system acquisition. The results of the proposed DEA-AHP integrated method in the selection of the next-generation fighter systems in Korea demonstrate the usefulness of the method. In this paper, we also discuss the future implications of the proposed model.

• Journal of the Korea Convergence Society
• /
• v.9 no.5
• /
• pp.191-202
• /
• 2018

Artificial intelligence (AI) is already being utilized in certain personnel selection processes in organizations; AI will eventually make even final decisions for personnel selection. The present study investigated potential job candidates' perceptions of an AI recruiter by comparing the selection procedures carried out by an AI recruiter to those carried out by a human recruiter. For this study college students in South Korea were recruited. They were each shown one of two recruitment scenarios (human recruiter vs. AI recruiter; between-subject design) followed by questionnaires measuring their satisfaction with the selection procedures and procedural justice, their trust in the recruiter, and their belief in a just world. Results show that potential job candidates were more satisfied with the selection procedures used by the AI recruiter than the human recruiter; they perceived the procedures as fairer than those used by the human recruiter. In addition, potential job candidates' trust in the AI recruiter was significantly higher than their trust in the human recruiter. This study also explored whether potential job candidates' perceptions of the AI and human recruiter were contingent upon their beliefs in a just world. The present study suggests a direction for future research.

• The Bulletin of The Korean Astronomical Society
• /
• v.36 no.2
• /
• pp.64-64
• /
• 2011

We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ~80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million lightcurves, and found 1620 QSO candidates. During the selection, none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.