• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.523-542
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• 2007

In this paper we consider semiparametric random effect panel models that contain AR(p) disturbances. We derive the efficient score function and the information bound for estimating the slope parameters. We make minimal assumptions on the distribution of the random errors, effects, and the regressors, and provide semiparametric efficient estimates of the slope parameters. The present paper extends the previous work of Park et al.(2003) where AR(1) errors were considered.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.113-123
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• 1996

Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

• Journal of the Korean Statistical Society
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• v.32 no.1
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• pp.1-10
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• 2003

We consider obtaining graphical summaries of uncertainty in estimates of parameters in nonlinear models. A nonlinear constrained optimization algorithm is developed for likelihood based confidence intervals for the functions of parameters in the model The results are applied to the problem of finding significance levels in nonlinear models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.1997-2003
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• 2009

Methods for effective musical score recognition and efficient editing of musical scores are demanded because functions of computers for researches on musical activities become more and more important parts in recent days. In the conventional methods for handling musical scores manually, there are weak points such as incorrect score symbols in input process and requirement of much time to adjust the incorrect symbols. And also there is another weak point that the scores edited by each application program can be remodified by a specific application program only. In this paper, we proposed a method for automatic musical score recognition of printed musical scores in order to make up for the weak points. In the proposed method, staffs in a scanned score image are eliminated by horizontal histogram, noises are removed by 4 directional edge tracking algorithm, and then musical score symbols are extracted by using Grassfire algorithm. The extracted symbols are recognized by hierarchical ART2 algorithm. In order to evaluate the performance of the proposed method, we used 100 musical scores for experiment. In the experiment, we verified that the proposed method using hierarchical ART2 algorithm is efficient.

• The Journal of the Korea Contents Association
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• v.2 no.1
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• pp.113-119
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• 2002

E-Biz. system must provide convenient and easy interface, efficient functions, and provides information and contents satisfying customers. To do this, many kinds of studies are being advanced actively about E-Biz. system using intelligent agent technology and efficient E-Biz. strategy. Also E-Biz. system score a lot of information and contents to get a efficient business activities and relationships between a company arid customers. To effectively adopt individual customer's preference and actively adapt change of business situation, we may consider individual user characteristics and emotion. This paper suggests E-Biz. system using intelligent agent technology based on user characteristics and emotion. This system can provide convenient user interface and improve customer royalty. In the results, it is found that proposed system is more efficient than existing systems about customer's preference.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.911-921
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• 2009

Receiver Operating Characteristic(ROC) and Cumulative Accuracy Profile(CAP) curves are two methods used to assess the discriminatory power of different credit-rating approaches. The points of optimal classification accuracy on an ROC curve and of maximal profit on a CAP curve can be found by using iso-performance tangent lines, which are based on the standard notion of accuracy. In this paper, we offer an alternative accuracy measure called the true rate. Using this rate, one can obtain alternative optimal threshold points on both ROC and CAP curves. For most real populations of borrowers, the number of the defaults is much less than that of the non-defaults, and in such cases the true rate may be more efficient than the accuracy rate in terms of cost functions. Moreover, it is shown that both alternative scores of optimal classification accuracy and maximal profit are the identical, and this single score coincides with the score corresponding to Kolmogorov-Smirnov statistic used to test the homogeneous distribution functions of the defaults and non-defaults.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.91-97
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• 2021

User interface for cancer classification system is a software application with clinician's friendly tools and functions to diagnose cancer from pathology images. Pathology evolved from manual diagnosis to computer-aided diagnosis with the help of Artificial Intelligence tools and algorithms. In this paper, we explained each block of the project life cycle for the implementation of automated breast cancer classification software using AI and machine learning algorithms to classify normal and invasive breast histology images. The system was designed to help the pathologists in an automatic and efficient diagnosis of breast cancer. To design the classification model, Hematoxylin and Eosin (H&E) stained breast histology images were obtained from the ICIAR Breast Cancer challenge. These images are stain normalized to minimize the error that can occur during model training due to pathological stains. The normalized dataset was fed into the ResNet-34 for the classification of normal and invasive breast cancer images. ResNet-34 gave 94% accuracy, 93% F Score, 95% of model Recall, and 91% precision.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.241-253
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• 2023

Purpose: The purpose of this study is to introduce the structure and functions of an application developed for enhancing risk knowledge/perception, called KNOWRISK, and to identify and determine problems and requirements based on the usability evaluation results of the application. Method: The evaluation was conducted using the Mobile App Rating Scale (MARS) with a sample of 43 application users and related experts. Result: The application received a satisfactory evaluation score with an overall average of 4.074 points, and there was no significant difference in evaluation scores between experts and users. The highest score was for ease of use at 4.47, while the lowest score was for cost payment usage at 2.88. Conclusion: The results of this study suggest that efforts to increase risk knowledge and promote safe behavior using a mobile application can be an effective and efficient strategy for preventing industrial accidents and enhancing safety management.

• The Korean Nurse
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• v.35 no.4
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• pp.37-50
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• 1996

Nursing Diagnosis has evolved in the guest to define nursing and its functions. But for the application to clinical practice an unified system of terminology that helps nurses to assess selected data and identify potential or actual client problems is required. Consistent terminology that captures the real meanings of the nursing diagnosis makes oral and written communication more accurate and efficient. Therefore,' this study was performed to deliver a Korean-translated version of the nursing diagnoses through the process of content validity tests and translations. Data collection for the first content validity test was done from June 27, 1996 to August 1. 1996. Among 20 questionnaires only 16 were used for analysis. With the results of content validity, the list of 109 nursing diagnoses were reviewed by two linguists, one specialized in Korean and the other in English. To clear confusion on a diagnostic label "Incontinence" a urology specialist was invited for consultation. From this analysis and discussions a total of 98 nursing diagnoses was delivered and quesitons containing 98. 98 diagnoses were mailed to 741 subjects to test content validity from August 13, 1996 to October 7, 1996. Among 741 questionnaires, 343 were used for analysis. Total mean score of the diagnoses was 4.30 on the 5 point likert scale. The diagnoses that acquired less than 3.50 were "High risk for altered body temperature"(3.34), "Ineffective thermoregulation" (3.34), "Perceived cosntipation"(3.24). "Stress incontinence"(3.42), "Ineffective airway clearance"(3. 48), "Altered sexuality patterns"(3.35).

• Bulletin of the Korean Chemical Society
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• v.34 no.4
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• pp.1051-1054
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• 2013

Closo-carborane has been considered as an efficient boron-carrier for boron neutron capture therapy (BNCT) and an attractive surrogate of lipophilic phenyl or cyclohexyl ring in drug design. Despite a great number of carborane-containing ligands have been synthesized and evaluated, molecular modeling studies of carborane ligands with macromolecules have been rarely reported. We herein describe a facile docking and scoring-function strategy of 16 carborane ligands with an estrogen receptor by using the commercial Gaussian, Chem3D Pro and Discovery Studio (DS) computational programs. Docked poses of the carborane ligands in silico exhibited similar binding modes to that of the crystal ligand in the active site of estrogen receptor. Score analysis of the best docked pose for each ligand indicated that the Ligscore1 and the Dockscore have a moderate correlation with in vitro biological activity. This is the first report on the scoring-correlation studies of carborane ligands with macromolecules. The integrated Gaussian-DS approach has a potential application for virtual screening, De novo design, and optimization of carborane ligands in medicinal chemistry.