• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.867-870
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• 2014

Currently a number of universities and other educational institutions in the e-learning education system being implemented. Also that there is a demand. However, existing e-learning system has many problems. First, the theory of how the university -centered education and training institutions to adopt e-learning system has become the biggest obstacle. In addition, students can not engage the problem of a one-way lecture. In this paper, the theory -oriented and practice to overcome the one-way river systems programming language will develop e-learning content. Using socket communication and multi-threaded server-side Web browser on the client side through the compiler without installing a separate application installation and environmental learning environment can be unrestricted. Hands- content programming language allows the learner to direct the client-side source code in a web browser by entering the lecture is leading the way. For learners to enter the source code compiled to run on the server side, the compiler provides the learner results. Hands- because the future e-learning content development in e-learning systems will be a major contribution to.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.31-39
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• 2019

This research examined the changes that fast-growing voice-based devices would bring in the media multitasking environment. Based on the theoretical background that information processing efficiency improves when performing multiple tasks requiring different resource structures at the same time, we conducted an experiment where participants searched for information with voice-based or screen-based devices while performing an additional visual task. Results showed that both task performance environment and interface modality had significant main effects on cognitive load. The overall cognitive load level was higher in the voice interface group, but the difference in cognitive load between the two groups decreased in a multitasking environment where the additional visual resources was required. The visual task performance was significantly higher when using the voice interface than the screen interface. Our findings suggest that voice interfaces offered advantages in the cognitive load and task performance by distributing two tasks to the auditory and visual channels. The results of this study imply that voice-based devices have the potential to facilitate efficient information processing in the screen-centric environment where visual resources collide. We provided theoretical evidence of resource distribution using multiple resource theory and tried to identify the advantages of the voice interface more specifically based on the threaded cognition model.

• Journal of Science Education
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• v.46 no.1
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• pp.17-29
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• 2022

The purpose of this study is to look qualitatively into how efficiently and reasonably a computer can learn themes related to the Nature of Science (NOS). In this regard, a corpus has been constructed focusing on literature (920 abstracts) related to NOS, and factors of the optimized Word2Vec (CBOW, Skip-gram) were confirmed. According to the four dimensions (Inquiry, Thinking, Knowledge and STS) of NOS, the comparative evaluation on the word-level word embedding was conducted. As a result of the study, according to the previous studies and the pre-evaluation on performance, the CBOW model was determined to be 200 for the dimension, five for the number of threads, ten for the minimum frequency, 100 for the number of repetition and one for the context range. And the Skip-gram model was determined to be 200 for the number of dimension, five for the number of threads, ten for the minimum frequency, 200 for the number of repetition and three for the context range. The Skip-gram had better performance in the dimension of Inquiry in terms of types of words with high similarity by model, which was checked by applying it to the four dimensions of NOS. In the dimensions of Thinking and Knowledge, there was no difference in the embedding performance of both models, but in case of words with high similarity for each model, they are sharing the name of a reciprocal domain so it seems that it is required to apply other models additionally in order to learn properly. It was evaluated that the dimension of STS also had the embedding performance that was not sufficient to look into comprehensive STS elements, while listing words related to solution of problems excessively. It is expected that overall implications on models available for science education and utilization of artificial intelligence could be given by making a computer learn themes related to NOS through this study.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.83-88
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• 2013

Many studies adopting brain functions to the engineering systems have been made for recent years as the brain Science has developed. If we investigate the parts which take part in memorizing and emotional process, we can know that Hippocampus of memorizing center and Amygdala of Emotional center closely cooperate each other. Actually Knowledge effects on Emotion and Emotion effects on Knowledge. During the human decision making, emotional factor has much important effects on Decision making process. For implementing more delicate intelligent system, the knowledge base coupled to emotional factor should be designed. Accordingly in this paper starting from the idea of cooperating system between Hippocampus and Amygdala,, we design Knowledge Emotion Binding System and propose Emotional changing mechanism by Memory retrieval and knowledge reasoning process.

• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.171-175
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• 2017

Recently, Training of the convolutional neural network (CNN) entails many iterative computations. Therefore, a method of accelerating the training speed through parallel processing using the hardware specifications of GPGPU is actively researched. In this paper, the operations of the feature extraction unit and the classification unit are divided into blocks and threads of GPGPU and processed in parallel. Convolution and Pooling operations of the feature extraction unit are processed in parallel at once without sequentially processing. As a result, proposed method improved the training time about 314%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.719-726
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• 2015

As big-data and cloud security technologies become popular, many researchers have recently been conducted on faster and lighter encryption. As a result, National Security Research Institute developed LEA which is lightweight and fast block cipher. To date, there have been various studies on lightweight encryption algorithm (LEA) for speeding up using GPU rather than conventional CPU. However, it is rather difficult to explore any guideline how to manipulate the GPU for the efficient usage of the LEA. Therefore, we introduce a guideline which explains how to implement and design the optimal LEA using GPU.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.795-798
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• 2017

최근 멀티코어 프로세서가 개발됨에 따라 병렬 프로그래밍은 멀티코어를 효과적으로 활용하기 위한 기법으로 그 중요성이 높아지고 있다. 트랜잭셔널 메모리는 처리 방식에 따라 HTM, STM, HyTM으로 구분되며, 최근 HTM 및 STM 결합한 HyTM 이 활발히 연구되고 있다. 그러나 기존의 HyTM 는 HTM과 STM의 동시성 제어를 위해 블룸필터를 사용하는 반면, 블룸필터의 자체적인 긍정 오류를 해결하지 못한다. 아울러, 트랜잭션 처리를 위한 메모리 할당/해제를 기존의 락 메커니즘을 사용하여 관리한다. 따라서 멀티코어 환경에서 스레드 수가 증가할수록 트랜잭션 처리 효율이 떨어진다. 본 논문에서는 멀티코어 환경에서 효율적인 트랜잭션 처리를 위한 메모리 관리 기반 하이브리드 트랜잭셔널 메모리 기법을 제안한다. 제안하는 기법은 트랜잭션 처리에 최적화된 블룸필터를 제공함으로써, 병렬적으로 동시에 수행되는 서로 다른 환경의 트랜잭션에 대해 일관성 있는 처리를 지원한다. 아울러, CPU 캐시라인에 최적화된 메모리 기법을 통해, 메모리 할당량이 적은 트랜잭션은 로컬 캐시에 할당함으로써 트랜잭션의 빠른 처리를 지원한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.36-39
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• 2017

길이가 같은 두 문자열의 같은 위치에 있는 문자의 순위가 모두 일치할 때, 두 문자열은 순위동형이라 한다. 순위다중패턴매칭문제는 텍스트 T와 k개의 패턴들의 집합 $P^{\prime}=\{P_1,P_2{\ldots},P_k\}$이 주어졌을 때, P'의 패턴들과 순위동형인 T의 모든 부분문자열의 위치를 찾는 문제이다. 최근 전처리단계에서 P'에 대한 이동테이블을 O(kmqlogq) 시간에 계산하여 순위다중패턴매칭문제를 해결하는 해싱기반 알고리즘이 제시되었다. 이때 P'에서 가장 짧은 패턴의 길이를 m, q-그램의 길이를 q라고 한다. 본 논문에서는 P'이 주어졌을 때, 이동테이블을 O(mqlogq) 시간에 계산하는 병렬알고리즘을 제시한다. 실험결과, 본 논문에서 제시하는 병렬알고리즘은 k개의 스레드를 이용하여 m=100, q=5에 대해 k=100일때와 k=1,000일 때 순차알고리즘보다 각각 약 12.9배, 약 215배 빠른 수행시간을 보였다.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.163-169
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• 2016

Lustre is a scalable, distributed file system, which is popular in the field of high-performance computing. Recently, the advent of SSD has enabled high-performance storage hardware, but software development requires further improvement. In this paper, we analyzed performance of the Lustre system using SSD via extensive experimentation. We compared performance of Lustre on SSDs and HDDs in terms of file read/write throughputs and metadata access latencies. Our experimental results showed that 1) SSDs improve metadata access performance due to fast random read/write access of SSD characteristics, and 2) SSD are benefited to a greater extent under multiple threads and large numbers of small sized files.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.568-570
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• 2001

최근에 들어와 그 응용분야가 확대되어 가고 있는 에이전트 소프트웨어는 점점 그 크기와 복잡성이 커져 감에 따라 소프트웨어 개발치 효율성을 필요로 하는 추세이다. 이에 따라 네트워크에 분산되고 이질적인 시스템에 존재하는 에이전트들은 자신의 정보를 효율적으로 교환할 수 있도록 하기 위해 통신 프레임웍을 필요로 하게 되었다. 본 논문에서는 네트워크에 존재하고 동일한 환경 또는 서로 다른 환경에 존재하는 에이전트들 간의 의사 소통을 위한 통신 프레임웍의 설계 및 구현을 제시한다. 기본적으로 에이전트 소프트웨어 아키텍처는 KRIL(KQML- Router Interface Labrary), Router, Facilitator로 구성되어 진다. 같은 호스트에 존재하는 에이전트들은 같은 주소를 가지기 때문에 각기 다른 Router를 가질 필요 없이 하나의 Router를 공유한다. Router는 로컬 호스트에 존재하는 에이전트들의 리스트를 유지 관리하며, 로컬 에이전트가 보낸 메시지의 수신자가 자신의 리스트에 없을 경우 Facilitator를 통해 다른 호스트에 존재하는 에이전트에 메시지를 전달한다. 서로 다른 환경에 존재하는 에이전트들 간의 통신과 스레드 관리, 병행처리와 동기화 등을 위해 KRIL은 ACE(The Adaptive Communication Environment) 라이브러리를 사용하였으며, Router와 Facilitator는 Java로 구현하였다.