• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.229-243
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• 2018

The purpose of this study is to develop a personality education program that can enhance the virtues of elementary school students, self-esteem, Consideration communication, self-control, honesty courage by using coaching methodologically, To improve the personality virtue. The subjects of this study were 31 students from 4th grade of U elementary school in S Gu, Seoul. The experimental group was divided into 16 sessions, weekly from March 5, 2018 to June 30, 2018, 1 hour (40 minutes). The program consisted of items such as self-esteem, Consideration communication, self-control, honesty courage among the personality virtues of KEDI personality test, Each activity used a tough coaching model developed by combining the GROW model with the Empowering model and considering the developmental level of elementary school students. As a result, all four virtues of personality were significantly improved, model with the Empowering model and considering the developmental level of elementary school students. We compared pre and post test result with paired t-test. As a results, the experimental group showed improvement in all four virtues of personality at 0.05 significance level, whereas the control group did not. This suggests that the program can be usefully used as a tool to improve four virtues of personality of elementary school students. For further research, we expect that the program would be integrated with state-of-art technology such as online program or CBI(Computer-Based Instruction).

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.1-12
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• 2016

When utilizing a Tunnel Boring Machine (TBM) for tunnelling work, unexpected ground conditions can be encountered that are not predicted in the design stage. These include fractured zones or mixed ground conditions that are likely to reduce the stability of TBM excavation, and result in considerable economic losses such as construction delays or increases in costs. Minimizing these potential risks during tunnel construction is therefore a crucial issue in any mechanized tunneling project. This paper proposed the potential risk events that may occur due to risky ground conditions. A resistivity survey is utilized to predict the risky ground conditions ahead of the tunnel face during construction. The potential risk events are then evaluated based on their occurrence probability and impact. A TBM risk management system that can suggest proper solution methods (measures) for potential risk events is also developed. Multi-Criterion Decision Making (MCDM) is utilized to determine the optimal solution method (optimal measure) to handle risk events. Lastly, an actual construction site, at which there was a risk event during Earth Pressure-Balance (EPB) Shield TBM construction, is analyzed to verify the efficacy of the proposed system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.48-54
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• 2020

DMSMS (Diminishing Manufacturing Sources and Material Shortage) is increased by developing the scientific technique and downsizing the military part market. DMSMS affects the increase in total life cycle costs and serviceability. Therefore, advance control for parts is important to reduce the cost, and a database is needed to share information on the DMSMS. A task needs to be performed continuously by setting the major control item to management more efficiently. The purpose of this study was to deduce the major control item for the DMSMS management system. Thus, the pre-control item basis of the DAPA (Defense Acquisition Program Administration) Manual and the SD-22 Manual were first selected, and the results of the survey were analyzed by AHP (Analytic Hierarchy Process) method. Fifteen of the detailed items were stratified into three criteria (Impact, Probability, and cost of the DMSMS), and each weight for the items was calculated using a nine-point scale survey. The AHP survey was executed with 25 specialists in the DMSMS management field, and the score of consistency ratio over 0.1 was excluded. The model explained the results and suggested future directions for development.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.510-519
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• 2011

Intra mode decision is a useful coding tool in Distributed Video Coding (DVC) for improving DVC coding efficiency for video sequences having fast motion. A major limitation associated with the existing intra mode decision methods, however, is that its efficiency highly depends on user-specified thresholds or modeling parameters. This paper proposes an entropy-based method to address this problem. The probabilities of intra and Wyner?Ziv (WZ) modes are determined firstly by examining correlation of pixels in spatial and temporal directions. Based on these probabilities, entropy of the intra and the WZ modes are computed. A comparison based on the entropy values decides a coding mode between intra coding and WZ coding without relying on any user-specified thresholds or modeling parameters. Experimental results show its superior rate-distortion performance of improvements of PSNR up to 2 dB against a conventional Wyner?Ziv coding without intra mode decision. Furthermore, since the proposed method does not require any thresholds or modeling parameters from users, it is very attractive for real life applications.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.21-29
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• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.303-314
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• 2024

Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.286-289
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• 2005

기존의 물리적 인증도구를 이용한 방식이나 패스워드 인증 방식은 분실, 도난, 해킹 등에 취약점을 가지고 있다. 따라서 지문, 서명, 홍채, 음성, 얼굴 등을 이용한 생체 인식기술을 보안 기술로 적용하려는 연구가 진행중이며 일부는 실용화도 되고 있다. 본 논문에서는 최근 널리 보급되어 있는 임베디드 시스템중의 하나인 PDA에 음성 기술을 이용한 내장형 화자 인증기를 구현하였다. 화자 인증기는 음성기술에서 널리 사용되고 있는 벡터 양자화 기술과 은닉 마코프 모델 기술을 사용하였으며, PDA의 하드웨어적인 제약 사항을 고려하여 사용되는 벡터 코드북을 두 가지로 다르게 하여 각각 구현하였다. 처음은 코드북을 화자 등록시에 발성음만을 이용하여 생성하고 화자인증 시에 이용하는 방법이며, 다른 하나는 대용량의 음성 데이터베이스를 이용하여 코드북을 사전에 생성하여 이를 화자 인증시에 이용하는 방법이다. 화자인증기의 성능평가는 5명의 화자가 10번씩 5개의 단어에 대하여 실험하여, 각각 화자종속 코득북을 이용한 인증기는 88.8%, 99.5%, 화자독립 코드북을 이용한 인증기는 85.6%, 95.5%의 인증율과 거절율을 보였으며, 93.5%와 90.0%의 평균 확률을 보였다.. 실험을 통하여 화자독립 인증기의 경우가 화자종속 인증기의 경우보다 낮은 인식율을 보였지만, 화자종속 인증기에서 나타나는 코드북 훈련시에 발생하는 메모리 문제를 해결 할 수 있었다.

• Journal of Advanced Navigation Technology
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• v.5 no.1
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• pp.1-10
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• 2001

Speech has a good characteristics of which car drivers busy to concern with miscellaneous operation can make use in convenient handling and manipulating of devices. By utilizing this, this works proposes a speaker verification method for protecting cars from being stolen and identifying a person trying to access critical on-line services. In this, continuant phonemes recognition which uses language information of speech and MLP(mult-layer perceptron) which has some advantages against previous stochastic methods are adopted. The recognition method, though, involves huge computation amount for learning, so it is somewhat difficult to adopt this in speaker verification application in which speakers should enroll themselves at real time. To relieve this problem, this works presents a solution that introduces speaker cohort models from speaker verification score normalization technique established before, dividing background speakers into small cohorts in advance. As a result, this enables computation burden to be reduced through classifying the enrolling speaker into one of those cohorts and going through enrollment for only that cohort.