• 디지털융복합연구
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• 제13권8호
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• pp.289-294
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• 2015

본 연구는 비교사학습의 대표적인 방법 중 하나인 코호넨의 자기조직화 방법을 기반으로 BCI(Brain-Computer Interface)에 적용 가능한 자율적 기계학습방법을 제안한다. 이를 위해 상호작용 함수를 이용한 학습영역조정방법과 자율적 기계학습규칙을 제안하였다. 학습영역조정과 기계학습은 코호넨의 자기조직화 방법을 기반으로 한 상호작용 함수에 의한 측면제어효과를 이용하였다. 승자 뉴런을 결정하고 난 후 학습 규칙에 따라 뉴런의 연결강도를 조정하고 학습 횟수가 증가함에 따라 학습영역이 점차 감소하여 출력층 뉴런 가중치들의 입력을 향한 유동을 완화시켜 네트워크가 평형 상태(equilibrium state)에 도달하여 학습을 마칠 수 있는 자율적 기계학습을 제안하였다.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.1-7
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• 2021

Reinforcement learning is an area of machine learning that studies how an intelligent agent takes actions in a given environment to maximize the cumulative reward. In this paper, we propose a new MAC protocol based on the Q-learning technique of reinforcement learning to improve the performance of the IEEE 802.11 wireless LAN CSMA/CA MAC protocol. Furthermore, the operation of each access point (AP) and station is proposed. The AP adjusts the value of the contention window (CW), which is the range for determining the backoff number of the station, according to the wireless traffic load. The station improves the performance by selecting an optimal backoff number with the lowest packet collision rate and the highest transmission success rate through Q-learning within the CW value transmitted from the AP. The result of the performance evaluation through computer simulations showed that the proposed scheme has a higher throughput than that of the existing CSMA/CA scheme.

• 컴퓨터교육학회논문지
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• 제22권2호
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• pp.39-50
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• 2019

본 논문에서는 효과적인 컴퓨터 프로그래밍 학습을 위하여 팀 프로젝트 기반 학습을 설계하여 적용하고 학습효과에 미치는 영향을 분석하였다. 이론 강의 및 실습 최소화, 무작위 추첨에 의한 팀 구성, 각 팀원별 책임과 권한의 설정, 주어진 과제에 대한 경쟁 방식 문제 해결 프로젝트 진행, 팀 프로젝트가 끝날 때까지 매주 단계별 진행사항 발표를 통한 자연스러운 정보 공유 및 학습 사이클 반복 등을 통하여 학생들이 능동적으로 학습에 참여하는 모습이 관찰되었다. 과정 종료 후, 학습효과에 대한 분석을 위하여 학습자를 대상으로 설문조사를 실시하였으며, 그 결과 팀 프로젝트 기반 교육이 컴퓨터 프로그래밍 학습에 긍정적인 영향을 미치는 것으로 파악되었다. 본 논문에서는 도출된 요인 간 관계분석을 바탕으로 보다 효과적인 컴퓨터 프로그래밍 학습 방법을 논하고자 한다.

• Current Optics and Photonics
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• 제8권3호
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• 한국콘텐츠학회논문지
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• 제5권1호
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• pp.1-8
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• 2005

e-러닝은 교육과 학습을 위하여 e-비즈니스 기술 및 서비스를 사용하는 응용프로그램이다. 이는 원격지자원과 서비스에 접근을 수월하게 함으로서 교육의 질을 높이기 위한 새로운 멀티미디어 및 인터넷 기술을 사용한다. 본 논문은 신중하게 설계되고 구현된 인터넷기반의 컴퓨터기반 시험 시스템에 대하여 기술한다. 본 시스템은 콘텐츠 전달 기술, 컴퓨터 적응형 시험 알고리즘, 리뷰엔진으로 구성되어 있다. 본 논문에서는 컴퓨터기반 시험 시스템을 설계하고 구현할 때에 고려되어야 할 요소들에 대하여 서술한다. 또한, 실제 데이터를 이용하여 컴퓨터 적응형 알고리즘을 위한 편향 값을 어떻게 조절하는지를 보인다.

• Educational Technology International
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• 제15권1호
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• pp.27-48
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• 2014

The purpose of the present research was to examine the relationship between the using goals of computer and self-regulated learning ability on the gender difference. To accomplish this goal, we have analyzed the data of Korea Children and Youth Panel Survey III which is nationally collected from primary school students, currently on the 6th grade in South Korea. 2,219 samples were used in the study excluding missing samples. The participants were 1167 males (49.5%) and 1052 females (50.5%). The mean age was 13.94 years (SD=.25). As results, female students spent more time on using computer than male students did: (1) the male students' time spent on Playing game was significantly larger than that of female students, but (2) on the rest seven using goals of computer including e-Learning/Information retrieval for learning, the female students spent significantly more time than the male students did. Also, in terms of the self-regulated learning ability, using computer for e-Learning/Information retrieval for learning itself gave significantly positive effects on both male and female students' self-regulated learning ability. On the other hand, Playing game gave significantly negative effects on both. Based on the results, some strategies were suggested on the proper use of computer for learning.

• 영어어문교육
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• 제10권2호
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• pp.133-158
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• 2004

The purpose of the present study was to scrutinize computer games that can motivate elementary school students through their interactive "edutainment" effects. The types of elements in computer games that students find interesting as learning media and their impact were studied. The current status of Korean computer games, issues related to learning English, and methods to stimulate the motivation and interest in learning by elementary school students were explored. A computer game model for efficiently teaching English to elementary school students through a connection between computer games and education was suggested. In this model, overall games were designed with the focus on the integration of curriculum and content subjects related to learning activities. For games not to be biased toward entertainment and to have systemized learning steps, the games are composed of an introduction, presentation, practice, production and evaluation, in that order. The model suggested by this plan and composition make it possible to approach learning efficiently with entertaining games based on a systematic learning curriculum. As shown above, developing the model of educational computer games can be seen as an opportunity, which can provide amusement and interests and a broad learning experience as an additional learning method.

• 한국컴퓨터정보학회논문지
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• 제12권1호
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• pp.83-88
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• 2007

본 연구는 중학교 컴퓨터교과에 있어서 게임기반학습이 학업성취도에 미치는 영향을 살펴보고자 하는데 목적이 있다. 이 목적을 위해 먼저, 1차시 분량의 교과내용이 담긴 교육용 게임을 개발하고, 이것의 교육적 효과성을 확인하고자 중학생 1학년 2개 학급을 각각 실험집단(37명)과 통제집단(37명)으로 나누어 실험을 수행했다. 사전 학업성취도 분석결과 두 집단의 동질성이 확인되었다. 사후 학업성취도 분석결과, 교육용 컴퓨터게임으로 수업을 한 집단의 평균점수(69.86)가 면대면 수업 집단 평균(61.61) 보다 높은 것으로 나타났으며, 두 집단 간의 평균 차이가 유의수준.05에서 통계적으로 유의미한 차이를 보였다(t=2.08, p=.04). 이러한 결과는 게임기반 학습이 전통적 면대면 학습방법보다 학업성취도를 향상시키는데 있어서 더 효과적임을 설명해 준다. 또한 게임이라는 교수전략을 교수설계에 적극적으로 반영할 필요가 있음을 시사해 준다.