• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.106-117
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• 2022

In 2021, AI basics were introduced in the high school curriculum. There are many worries that the problem of utilization-oriented education will be repeated with the introduction of artificial intelligence education rather than the principles that occurred when ICT was applied to education in the past. Most of the existing AI education platforms focus only on the use of AI. For artificial intelligence education of middle school students, there are difficulties in learning about the process by which artificial intelligence derives results and learning the principles of artificial intelligence algorithms. Recently, as the educational application of metaverse has become a hot topic, research has been started to improve learning achievement by arousing students' immersion and interest. This research developed educational game contents about decision tree algorithm using metaverse as educational contents that can be used in middle school AI education. By applying games to education, it was intended to increase students' interest and immersion in artificial intelligence, and to increase educational effectiveness. In this paper, the educational effectiveness, difficulty, and level of interest were analyzed for pre-service teachers regarding the developed game content. Based on this, a future principle-oriented artificial intelligence education method was suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.767-778
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• 2007

In this paper, we propose a Intelligent Service Reasoning (ISR) model using data mining in smart home environments. Our model creates a service tree used for service reasoning on the basis of C4.5 algorithm, one of decision tree algorithms, and reasons service that will be offered to users through quantitative weight estimation algorithm that uses quantitative characteristic rule and quantitative discriminant rule. The effectiveness in the performance of the developed model is validated through a smart home-network simulation.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1385-1389
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• 2010

수자원 계획에 있어서 강우 또는 홍수빈도분석시 주로 사용되는 확률의 개념은 상대빈도에 대한 극한으로 확률을 정의하는 빈도학파적 확률관점에 속하며, 확률모델에서 미지의 매개변수들은 고정된 상수로 간주된다. 따라서 확률은 객관적이고 매개변수들은 고정된 값을 가지기 때문에 이러한 매개변수들에 대한 확률론적 설명은 매우 어렵다. 본 연구에서는 강우빈도해석에서 확률분포의 매개변수에 대한 불확실성을 정량화하기 위하여 베이지안 MCMC 및 Metropolis-Hastings 알고리즘을 이용한 불확실성 평가모델을 구축하였다. 그리고 베이지안 MCMC 및 Metropolis-Hastings 알고리즘의 적용을 통하여 확률강우량 산정시 확률분포의 매개변수에 대한 통계학적 특성 및 불확실성 구간을 정량화하였으며, 이를 바탕으로 홍수위험평가 및 의사결정과정에서 불확실성 및 위험도를 충분히 설명할 수 있는 프레임워크 구성을 위한 기초를 마련할 수 있었다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.38-41
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• 2003

There are many kinds of algorithms used for the purpose of data mining. But without the understanding the underlying principles in the algorithm, the result of the data mining cannot be interpreted correctly. In this paper, the principle of ID3 algorithm is explained for that purpose. In addition, the way how to generate good training examples from the relational database is treated, as well as how to convert continuous values into discrete values is considered to use the algorithm for the data mining of real world database.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.1-7
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• 2021

Detect and avoid (DAA) system, which is essential for the operation of UAS, detects intruding aircraft and offers the ranges of turn and climb/descent maneuver that are required to avoid the intruder. This paper uses detect and avoid alerting logic for unmanned systems (DAIDALUS) developed at NASA as a DAA algorithm. Since DAIDALUS offers ranges of avoidance maneuvers, the actual avoidance maneuver must be decided by the UAS pilot as well as the timing and method of returning to the original route. It can be readily used in real-time human-in-the-loop (HiTL) simulations where a human pilot is making the decision, but a pilot decision model is required in fast-time simulations that proceed without human pilot intervention. This paper proposes a pilot decision model that maneuvers the aircraft based on the DAIDALUS avoidance maneuver range. A series of tests were conducted using test vectors from radio technical commission for aeronautics (RTCA) minimum operational performance standards (MOPS). The alert levels differed by the types of encounters, but loss of well clear (LoWC) was avoided. This model will be useful in fast-time simulation of high-volume traffic involving UAS.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.449-459
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• 2015

The purpose of this study was to examine demographic, human capital and service factors affecting employment outcomes of people with hearing impairments. The total of 422 individuals (age from 20 years to 65 years) with hearing impairments were collected from the Panel Survey of Employment for the Disabled from Korea Employment Agency for the Disabled. The dependent variable is employment outcomes. The predictor variables include a set of personal history, human capital and rehabilitation service variables. The chi-squared automatic interaction detector (CHAID) analysis revealed that the status of the national basic livelihood security played a determining role in predicting the employment of people with hearing impairments. Also, it was found that the three factors of the status on the national basic livelihood security, needed help about activities of dailey living, licenses & employment service factors created bigger synergy effect when they inter-complemented one another.

• Korean Journal of Construction Engineering and Management
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• v.21 no.1
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• pp.50-60
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• 2020

Estimates of project costs in the early stages of a construction project have a significant impact on the operator's decision-making in important matters, such as the site's decision or the construction period. However, it is difficult to carry out the initial stage with confidence because information such as design books and specifications is not available. In previous studies, case-based reasoning was used to predict initial construction costs, and genetic algorithms were used to calculate the weight of the inquiry phase among them. However, some say that it is difficult to perform better than the current year because existing genetic algorithms are calculated in random numbers. To overcome these limitations, correlation numbers using correlation analysis rather than random numbers are reflected in the genetic algorithm by method of local search, and weights are calculated using a hybrid genetic algorithm that combines local search and genetic algorithms. A case-based reasoning model was developed using the weights calculated and validated with the data. As a result, it was found that the hybrid GA-CBR applied with local search performed better than the existing GA-CBR.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.154-156
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• 2002

정보화시대에 들어서면서 나날이 급증하는 데이터에 대한 재가용성을 위한 많은 연구가 이루어지고 있다 이러한 연구들은 의사결정지원, 예측, 추정 등의 분야에서 적용되고 있으나, 실생활에 활발히 적용되기까지 앞으로 많은 연구 및 개발이 요구된다. 이 논문에서는 수집된 데이터로부터 패턴을 추출하여 예측결과를 제공할 수 있는 시스템 모델과 모델에 적합한 점진적 규칙갱신 알고리즘을 제안하였다. 제안하는 예측 모델의 특징은 새로 입력되는 정보에 대한 반복 학습시 수치데이터에 대한 평균근사치 할당방법을 적용하여 규칙갱신을 용이하게 하였으며 각 클래스의 수치데이터에 대한 분류를 용이하도록 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1177-1180
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• 2000

본 논문은 영상처리의 전처리 과정에서 많이 쓰이는 윤곽선 추출 알고리즘을 이용하여 각종 공격에 강인한 디지털 워터마킹 기법을 제안한다. 윤곽선은 영상의 특징을 결정하는 중요한 요소이기 때문에 이를 워터마크 시퀀스로 이용함으로써 기존 가우시안 랜덤 시퀀스나 의사 랜덤 시퀀스 보다 더 효과적인 시퀀스를 생성할 수 있다. 이를 증명하기 위해 다양한 공격 형태를 가지고 실험해 봄으로써 제안한 방법의 타당성을 검증한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.69-72
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• 2004

기업간의 경쟁이 심화되고 정보의 중요성에 대한 인식이 확대되어 가는 상황에서 다량의 데이터로부터 가치 있는 데이터를 추출하는 CRM 데이터 마이닝은 중대한 관심사가 아닐 수 없다. 본 연구는 데이터마이닝의 여러 활용 분야 중 고객세분화를 위해 최근 많이 사용되고 있는 데이터마이닝 기법인 로지스틱 회귀분석, 의사결정나무, 신경망 알고리즘 기법들을 비교하며, 이를 실제 아파트 고객의 데이터를 이용하여 검증하고자 한다. 따라서, 아파트 고객 세분화를 위한 데이터마이닝 수행시 기법 선택의 기준과 비교 평가의 기준을 제시하는 데 연구목적 있다.