• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.449-468
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• 2023

This paper deals in the study of the estimation of the parameters of Erlang distribution based on rank set sampling and some of its modifications. Here we considered Maximum Likelihood (ML) and the Bayesian technique to estimate the shape and scale parameter of Erlang distribution based on RSS and its some modifications such as ERSS, MRSS, and MRSSu. The derivation for unknown parameters of Erlang distribution is well presented using normal approximation to the asymptotic distribution of ML estimators. But due to the complexity involves in the integral, the Bayes estimator of unknown parameters is obtained using MCMC method. Further, we compared the MSE of estimation in different sampling schemes with different set sizes and cycle size. A real-life data application is also given to illustrate the efficiency of the proposed scheme.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.718-727
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• 2022

The Korean domestic cartoon industry has grown explosively by 65% compared to the previous year. Then the market size is expected to exceed KRW 1 trillion. However, excessive work results in health deterioration. Moreover, this working environment makes the production of human resources insufficient, repeating a vicious cycle. Although some tasks require creation activity during cartoon production, there are still a lot of simple repetitive tasks. Therefore, this study aimed to develop a method for creating a character pose through human pose estimation (HPE). The HPE is to detect key points for each joint of a user. The primary role of the proposed method was to make each joint of the character match that of the human. The proposed method enabled us to create the pose of the two-dimensional cartoon character through the results. Furthermore, it was possible to save the static image for one character pose and the video for continuous character pose.

• Korea journal of population studies
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• v.29 no.1
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• pp.269-292
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• 2006

The current environmental problem is global, and threatens the very existence of human beings. Many factors have been argued as the causes of environmental problem. The examples include anthroponcentric human perspective on nature, increase in the knowledge on nature, development of technology, economic growth and unequal distribution, and population increase, etc. The scholars who argues population increase have focused on over-population. However, the estimation of optimum population size has not been attempted in terms of environmental carrying capacity. In such a context, this paper aims at estimating optimum population size in South Korea in terms of environmental carrying capacity. The estimation was done from two approaches. One was based on the state of environment, the other was based on 'the desirable state of environment' Koreans expect. The former is termed an objective approach, while the latter is termed an approach based on social consensus. About 47.5 millions were estimated from the former approach, and 48.5 millions from the latter approach. However, optimum population size increase by 50.5 millions if government increase environmental budget to 2.00% among total budget. As such, different optimum population size is estimated according to the values of variables. The most significant variable determining optimum population size is environmental budget, and followed by supply of clean energy. The estimated optimum population size was based on the time-series data from 1993 to 2002. Therefore, time-series data collected from other years will result in different estimation model, and then different optimum population size will be estimated.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.1
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• pp.32-36
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• 2011

In this study, authors have proposed the autonomous state estimation which has been composed with IEC61850, GPS time synchronization and objective model design concept. The proposed method is able to supervise/correct measurement and communication error from SCADA. The major advantages of the proposed autonomous state estimation are that it is possible to evaluate integrity of data measured and transferred from SCADA, to reduce human intervention and to expense national-size applications such as EMS (Energy Management System), WAMS (Wide Area Monitoring System) or WAPS (Wide Area Protection System). This study addresses the issues related to the operation of the smart grid and proposes a new automated approach to achieve this goal. Through applying the proposed system to IEEE 14-bus test electric system, we prove the possibility of the proposed idea.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.373-376
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• 2021

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavior of deep learning. The deep ensemble provides increased accuracy and estimated uncertainty; however, linearly increasing the size makes the deep ensemble unfeasible for memory-intensive tasks. To address this problem, we used model pruning and quantization with a deep ensemble and analyzed the effect in the context of uncertainty metrics. We empirically showed that the ensemble members' disagreement increases with pruning, making models sparser by zeroing irrelevant parameters. Increased disagreement implies increased uncertainty, which helps in making more robust predictions. Accordingly, an energy-efficient compressed deep ensemble is appropriate for memory-intensive and uncertainty-aware tasks.

• Journal of Oral Medicine and Pain
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• v.39 no.4
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• pp.119-126
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• 2014

This review provides an overview of the most commonly used dental age estimation techniques which focus on radiological methods in Korean adults. The literature from 1995 through July 31, 2014, was searched, using PubMed, for publications in English language. In PubMed, the keywords 'tooth' OR 'dental' AND 'pulp' AND 'age estimation' were searched. Inclusion criteria was comprised of the following: the subjects were living adults and dental radiography (excluded computed tomography [CT] and cone-beam CT) was used to measure the pulpal size. Twenty articles that met the criteria were selected. The method of age estimation using dental radiographs for measuring pulp and tooth size was represented in all studies. The methods were assorted into three categories generally; Kvaal's, Ikeda's and Cameriere's methods. Those methods had certain limitations such as large error range and low correlation coefficient depending on populations, type of employed teeth and particular method. Various techniques and many studies have been published for age estimation from human teeth using dental radiographs, but those techniques showed various predictability and reliability. Therefore, future studies on larger samples with well-distributed age group using not only existing techniques but new techniques are necessary for deriving convincing results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.761-764
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• 1993

In this paper we consider techniques for reducing the generated number of rules in learning fuzzy controllers of the state-space action-reinforcement type that can be simply implemented and that behave well in the presence of process noise. Fewer rules lead to better performance, less contradiction in controller action estimation, smaller required execution-time and make it easier for a human to comprehend the generated rules and possibly intervene.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.113-119
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• 2023

In this paper, we propose an optimization of a pose estimation deep learning model for recognition of abnormal behavior in unmanned stores using radio frequencies. The radio frequency use millimeter wave in the 30 GHz to 300 GHz band. Due to the short wavelength and strong straightness, it is a frequency with less grayness and less interference due to radio absorption on the object. A millimeter wave radar is used to solve the problem of personal information infringement that may occur in conventional CCTV image-based pose estimation. Deep learning-based pose estimation models generally use convolution neural networks. The convolution neural network is a combination of convolution layers and pooling layers of different types, and there are many cases of convolution filter size, number, and convolution operations, and more cases of combining components. Therefore, it is difficult to find the structure and components of the optimal posture estimation model for input data. Compared with conventional millimeter wave-based posture estimation studies, it is possible to explore the structure and components of the optimal posture estimation model for input data using genetic algorithms, and the performance of optimizing the proposed posture estimation model is excellent. Data are collected for actual unmanned stores, and point cloud data and three-dimensional keypoint information of Kinect Azure are collected using millimeter wave radar for collapse and property damage occurring in unmanned stores. As a result of the experiment, it was confirmed that the error was moored compared to the conventional posture estimation model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4160-4173
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• 2019

Borescopes facilitate the inspection of areas inside machines and systems that are not directly accessible for visual inspection. They offer real-time, up-close access to confined and hard-to-access spaces without having to dismantle or destructure the object under inspection. Borescopes are ideal instruments for routine maintenance, quality inspection and monitoring of systems and structures. The main application being fault or defect detection, it is useful to have measuring capability to quantify object dimensions in a target area. High-end borescopes use multi-optic solutions to provide measurement information of viewed objects. Multi-optic solutions can provide accurate measurements at the expense of structural complexity and cost increase. Measuring functionality is often unavailable in low-end, single camera borescopes. In this paper, a single camera measurement solution that enables the size estimation of viewed objects is proposed. The proposed solution computes and overlays a scaled grid of known spacing value over the screen view, enabling the human inspector to estimate the size of the objects in view. The proposed method provides a simple means of measurement that is applicable to low-end borescopes with no built-in measurement capability.

• Korean Management Science Review
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• v.29 no.1
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• pp.131-141
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• 2012

The automated material handling systems today are playing ever more important roles in semiconductor/LCD fabrication facilities. Recently they became more flexible, intelligent, and speedy than in the past. The facilities have been fully automated because the size and weight of the unit loads used in the facilities were being increased beyond the limits that a human operator can handle. This research develops an efficient procedure to streamline the delivery of unit loads by the automated material handling system (AMHS). For this task, the research employs the event scheduling theory that has been successfully used in the both academia and industry. The developed procedure was applied to an actual LCD fabrication facility and improved the performance of an existing material handling system.