• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.39-56
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• 2021

Many researches have been done on portfolio optimization since Markowitz (1952) published a diversified investment model. Markowitz's mean-variance portfolio optimization problem is established under the assumption that the distribution of returns follows a normal distribution. However, in real life, the distribution of returns does not follow a normal distribution, and variance is not a robust statistic as it is heavily influenced by outliers. To overcome these potential issues, mean-shortfall portfolio model was proposed that utilized downside risk, shortfall, as a risk index. In this paper, we propose a perturbation method that uses the shortfall as a risk index of the portfolio. The proposed portfolio utilizes an adaptive Lasso to obtain a sparse and stable asset selection because it can reduce management and transaction costs. The proposed optimization is easily applicable as it can be computed using an efficient linear programming. In our real data analysis, we show the validity of the proposed perturbation method.

• Journal of Korean Medicine for Obesity Research
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• v.21 no.2
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• pp.80-94
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• 2021

Objectives: The purpose of this study is to re-evaluate the importance of questions of obesity syndrome differentiation (OSD) questionnaire based on real-world survey and to explore the possibility of simplifying OSD types. Methods: The OSD frequency was identified, and variance threshold feature selection was performed to filter the questions. Filtered questions were clustered by K-means clustering and hierarchical clustering. After principal component analysis (PCA), the distribution patterns of the subjects were identified and the differences in the syndrome distribution were compared. Results: The frequency of OSD in spleen deficiency, phlegm (PH), and blood stasis (BS) was lower than in food retention (FR), liver qi stagnation (LS), and yang deficiency. We excluded 13 questions with low variance, 7 of which were related to BS. Filtered questions were clustered into 3 groups by K-means clustering; Cluster 1 (17 questions) mainly related to PH, BS syndromes; Cluster 2 (11 questions) related to swelling, and indigestion; Cluster 3 (11 questions) related to overeating or emotional symptoms. After PCA, significant different patterns of subjects were observed in the FR, LS, and other obesity syndromes. The questions that mainly affect the FR distribution were digestive symptoms. And emotional symptoms mainly affect the distribution of LS subjects. And other obesity syndrome was partially affected by both digestive and emotional symptoms, and also affected by symptoms related to poor circulation. Conclusions: In-depth data mining analysis identified relatively low importance questions and the potential to simplify OSD types.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.22-29
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• 2006

In this paper, we propose a block-based real-time people counting system that can be used in various environments including showing mall entrances, elevators and escalators. The main contributions of this paper are robust background subtraction, the block-based decision method and real-time processing. For robust background subtraction obtained from a number of image sequences, we used a mixture of K Gaussian. The block-based decision method was used to determine the size of the given objects (moving people) in each block. We divided the images into $6{\times}12$ blocks and trained the mean and variance values of the specific objects in each block. This was done in order to provide real-time processing for up to 4 channels. Finally, we analyzed various actions that can occur with moving people in real world environments.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.39-49
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• 1999

This paper describes the development of a vision-aided position and orientation recognition system for automatically adjusting electronic tuners which control the waveform by rotating variable resisters. The position and orientation recognition system estimates the center and the angle of the tuner grooves so that the main controller may correct the difference from the ideal position and thereby manipulate the variable resisters automatically. In this paper a robust algorithm is suggested which estimates the center and the angle of the tuner grooves fast and precisly from the source image with lighting variance and video noise. In the algorithm morphological filtering, 8-chain coding, and invariant moments are sequentially used to figure out image segments concerned. The performance of the proposed system was evaluated using a set of real specimens. The results indicate the system works well enough to be used practically in real manufacturing lines. If the system adopts a high speed frame grabber which enables real time image processing, it can also be applied to positioning of robot manipulators as well as automated PCB adjusters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8A
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• pp.1187-1194
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• 1999

In general wireless mobile channel is modeled as complex random processes having a narrowband spectrum. In this paper, a real-time feneration of fading signals using a DSP chip is described. Real-time simulator is designed so that simulation parameters such as mobile terminal speed, carrier frequency, power ratio of line-of-sight component versus multipath, and variance of received power can be chosen in the window. Design algorithms for the generation of ideal fading signals with a minimum DSP computation and trade-offs are investigated. The accuracy of the statistical characteristics is verified through the comparison of measured results with the theoretical prediction.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.4
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• pp.236-241
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• 2023

Objectives: According to the 10th revision of the International Classification of Diseases, the main categories of tic disorders (F95.0, F95.1, and F95.2) follow a diagnostic hierarchy based on the duration and diversity of tic symptoms. The present study investigated the use of this diagnostic hierarchy in real-world clinical practice. Methods: Based on the National Health Insurance Service-National Health Information Database, the diagnosis of transient tic disorder (F95.0) made after a diagnosis of chronic motor or vocal tic disorder (F95.1) or Tourette's syndrome (F95.2) and diagnosis of chronic motor or vocal tic disorder (F95.1) made after a diagnosis of Tourette's syndrome (F95.2) were referred to as type A errors. The diagnosis of transient tic disorder (F95.0) repeated after a period of >12 months was referred to as type B error. Demographic and clinical differences according to the diagnostic error types were analyzed using analysis of variance, Student's t-tests, and chi-squared tests. Results: Most participants (96.5%) were without errors in the diagnosis of tic disorders. Higher proportions of males (p=0.005) and antipsychotic prescriptions (p<0.001) were observed in patients with type A or B diagnostic errors. A higher proportion of health insurance holders was observed among those with type A errors (p=0.027). Conclusion: Errors were absent in majority of the tic diagnoses in real-world clinical practice in terms of the diagnostic hierarchy.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.434-437
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• 1996

Symmetry is one of the important structural properties of shapes both in perceptual psychology and in computer vision. Recently, a number of automatic symmetry finding algorithms have been reported. Among them, the algorithm based on the use of principal axes of objects is the most general and practical. It is, however, of no use when shapes concerned have some asymmetry. Asymmetric shapes which make us associate with certain kinds of symmetry are practically important and they are called shapes with potential symmetry in this paper. The algorithm we have already proposed can cope with those shapes having potential axial symmetry. The algorithm employs a reflected image of the original and a certain evaluation function. In the former paper, areal minimization was employed for the evaluation function and it yielded satisfactory experimental results. However, it could not cope with those shapes which have larger asymmetry. In this paper, we propose the employment of variance as an alternative evaluation index with respect to the difference image between the reflected and the original shape. The technique is examined its performance by real video images as well as synthetic data. Experimental results are shown and discussion is given.

• Journal of ILASS-Korea
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• v.25 no.3
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• pp.132-138
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• 2020

N₂O is hazardous atmosphere pollution matter which can damage the ozone layer and cause green house effect. There are many other nitrogen oxide emission control but N₂O has no its particular method. Preventing further environmental pollution and global warming, it is essential to control N₂O emission from industrial machines. In this study, the thermal decomposition experiment of N₂O gas mixture is conducted by using cylindrical reactor to figure out N₂O reduction and NO formation. And CHEMKIN calculation is conducted to figure out reaction rate and mechanism. Residence time of the N₂O gas in the reactor is set as experimental variable to imitate real SNCR system. As a result, most of the nitrogen components are converted into N2. Reaction rate of the N₂O gas decreases with N₂O emitted concentration. At 800℃ and 900℃, N₂O reduction variance and NO concentration are increased with residence time and temperature. However, at 1000℃, N₂O reduction variance and NO concentration are deceased in 40s due to forward reaction rate diminished and reverse reaction rate appeared.

• Korean Management Science Review
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• v.29 no.3
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• pp.81-89
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• 2012

Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.