• 컴퓨터교육학회논문지
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• 제10권2호
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• pp.77-87
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• 2007

본 연구는 오프라인 수업을 온라인 토론이 보조하는 블렌디드 러닝 형태의 대학교 수업 상황에서 학습자의 적에 미치는 사회 연결망의 효과를 분석하기 위해 수행되었다. '사이버 학습 세미나' 과목을 수강하는 36명의 교육대학교 학생들을 대상으로 교우 연결망 중심도, 조언 연결망 중심도, 그리고 적대 연결망 중심도 등 세 가지 사회 연결망 변수들을 측정한 후, 이를 기말 과제 및 시험 점수 등 학습자 성과 변수들과의 상관관계를 분석하였다. 그 결과, 조언 연결망 중심도와 교우 연결망 중심도는 학습 성과와 정적 상관관계를 보이고 있었던 반면, 적대 연결망 중심도는 대부분분의 성과 변수들과 부적 상관관계를 보였다. 온라인 토론의 양과 질은 교우 연결망 중심도 및 조언 연결망 중심도와 높은 상관을 보였으며, 특히 그 질은 조언 연결망과 매우 높은 정적 상관관계를 나타내었다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.361-364
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• 2005

As increasing the Internet traffic, many researches on access network are reported for end-to-end high-speed broadband network, where E-PON(Ethernet-Passive Active Network) is one of reasonable candidate fur the network with respect to cost and bandwidth utilization. For the high-speed access network, E-PON need an efficient bandwidth allocation method. This paper suggests a WFA(Water-Filling Allocation) algorithm for the efficient bandwidth allocation with various simulation test.

• International journal of advanced smart convergence
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• 제6권4호
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• pp.73-79
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• 2017

The Convolutional Neural Network (CNN) has shown an excellent performance in computer vision task. Applications of CNN include image classification, object detection in images, autonomous driving, etc. This paper will evaluate the performance of CNN model with ReLU and SELU as activation function. The evaluation will be performed on four different choices of hyperparameter which are initialization method, network configuration, optimization technique, and regularization. We did experiment on each choice of hyperparameter and show how it influences the network convergence and test accuracy. In this experiment, we also discover performance improvement when using SELU as activation function over ReLU.

• 동력기계공학회지
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• 제11권1호
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• pp.28-32
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• 2007

This research proposed that development of wireless condition monitoring system using WLAN network. It offers the prospect of improved performance that removed a current a coaxial cable and reduced overall cost of condition monitoring. Recently, there is an interesting concern for wireless system as an infrastructure technology construct ubiquitous computing environment in the future. High performance computing board makes minimization with integrate of a various functions which support wireless LAN network. Instead of wired coaxial cable using measurement system in industry, wireless LAN network assists industry automation and engineer's convenience. Developed system adapted wireless LAN network on shipboard with engine room and deck house, it also executes wireless measurement test on 8500TEU containership.

• KIEAE Journal
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• 제14권3호
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• pp.97-103
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• 2014

This study aimed at developing integrated logic for controlling heating device and openings of the double skin facade buildings. Two major logics were developed-rule-based control logic and artificial neural network based control logic. The rule based logic represented the widely applied conventional method while the artificial neural network based logic meant the optimal method. Applying the optimal method, the predictive and adaptive controls were feasible for supplying the advanced thermal indoor environment. Comparative performance tests were conducted using the numerical computer simulation tools such as MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation). Analysis on the test results in the test module revealed that the artificial neural network-based control logics provided more comfortable and stable temperature conditions based on the optimal control of the heating device and opening conditions of the double skin facades. However, the amount of heat supply to the indoor space by the optimal method was increased for the better thermal conditioning. The number of on/off moments of the heating device, on the other hand, was significantly reduced. Therefore, the optimal logic is expected to beneficial to create more comfortable thermal environment and to potentially prevent system degradation.

• Asia pacific journal of information systems
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• 제10권2호
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• pp.97-123
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• 2000

This paper proposes a model for assessing enterprise network maturity. We define maturity in terms of the institutional and member support for the network(organizational maturity) and its technical sophistication(technological maturity), and examine their relationships. We build several hypotheses about the relationships between the maturity types and between the maturity of the network and various organizational factors including industry, size, and performance of the enterprise. We test the hypotheses using data collected from a questionnaire survey with Korean firms. The results show that there is a positive correlation between organizational and technological maturity. It is also found that investment in the network infrastructure has a positive influence on the organizational efficiency. However, it is found that industry type does not affect network utilization, but size does, suggesting that large firms utilize network infrastructure more than small ones do. We also identify various relationships among performance, satisfaction level and the maturity of the enterprise networks. Finally, we provide an overview on the current technological state of the Korean enterprise networks.

• 한국철도학회논문집
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• 제12권6호
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• pp.902-908
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• 2009

TETRA는 유럽 전기 통신 표준협회에서 제안한 D-TRS 서비스의 표준이다. 현재 국가전력IT무선 기간망으로 TETRA가 채택되어, 다양한 활용을 위한 국가사업이 진행되고 있는 실정이다. 이와 같은 경우 TETRA 무선망을 이용하기 위해서는 TETRA 모뎀이 필요하게 된다. 따라서 각 제조사별로 존재하는 다양한 TETRA 모뎀의 성능 평가가 절실한 상황이다. 본 논문에서는 D-TRS 무선망 환경에서의 패킷 데이터 성능 평가를 위해 PED(Protocol Evaluation Data)를 제안하였다. 또한 Test Bed 상에서 TG(Traffic Generator)와 TA(Traffic Analyzer)를 이용하여 데이터 길이 및 전송 인터벌에 따른 성능 측정을 실시하여 모뎀의 성능을 알아보았다. 데이터 크기는 최초 10바이트에서 400바이트까지 10바이트씩 증가시키면서 측정하였고, 0.5초, 1초, 1.5초간격으로 각각 1000번 씩 전송하여 전송시간을 측정하였다. 측정한 전송시간을 바탕으로 평균전송속도, MER(Message Error Rate)을 도출하여 TETRA 모뎀 성능을 측정하였다. 본 논문에서 사용한 TETRA 모뎀은 EADS 사의 TMR880i 2대를 사용하였고, 교환기로는 EADS 사의 SwMI (Switching and Management Infrastructure)를 이용하였다.

• 대한원격탐사학회지
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• 제38권1호
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• pp.103-110
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• 2022

Since satellite images generally include clouds in the atmosphere, it is essential to detect or mask clouds before satellite image processing. Clouds were detected using physical characteristics of clouds in previous research. Cloud detection methods using deep learning techniques such as CNN or the modified U-Net in image segmentation field have been studied recently. Since image segmentation is the process of assigning a label to every pixel in an image, precise pixel-based dataset is required for cloud detection. Obtaining accurate training datasets is more important than a network configuration in image segmentation for cloud detection. Existing deep learning techniques used different training datasets. And test datasets were extracted from intra-dataset which were acquired by same sensor and procedure as training dataset. Different datasets make it difficult to determine which network shows a better overall performance. To verify the effectiveness of the cloud detection network such as Cloud-Net, two types of networks were trained using the cloud dataset from KOMPSAT-3 images provided by the AIHUB site and the L8-Cloud dataset from Landsat8 images which was publicly opened by a Cloud-Net author. Test data from intra-dataset of KOMPSAT-3 cloud dataset were used for validating the network. The simulation results show that the network trained with KOMPSAT-3 cloud dataset shows good performance on the network trained with L8-Cloud dataset. Because Landsat8 and KOMPSAT-3 satellite images have different GSDs, making it difficult to achieve good results from cross-sensor validation. The network could be superior for intra-dataset, but it could be inferior for cross-sensor data. It is necessary to study techniques that show good results in cross-senor validation dataset in the future.

• 말소리와 음성과학
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• 제9권2호
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• pp.85-94
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• 2017

Conventional speaker verification systems using time delay neural network, identity vector and probabilistic linear discriminant analysis (TDNN-Ivector-PLDA) are known to be very effective for verifying long-duration speech utterances. However, when test utterances are of short duration, duration mismatch between enrollment and test utterances significantly degrades the performance of TDNN-Ivector-PLDA systems. To compensate for the I-vector mismatch between long and short utterances, this paper proposes to use probabilistic linear discriminant analysis (PLDA) model adaptation with augmented data. A PLDA model is trained on vast amount of speech data, most of which have long duration. Then, the PLDA model is adapted with the I-vectors obtained from short-utterance data which are augmented by using vocal tract length perturbation (VTLP). In computer experiments using the NIST SRE 2008 database, the proposed method is shown to achieve significantly better performance than the conventional TDNN-Ivector-PLDA systems when there exists duration mismatch between enrollment and test utterances.

• 한국통신학회논문지
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• 제35권7A호
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• pp.715-724
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• 2010

한국수자원공사에서는 수문관측용으로 홍수예보망 및 감시제어를 포함한 원격 데이터 취득과 정보제공 등 여러부분에 위성통신망을 12년째 사용하고 있다. 장기간의 시스템 사용에 따른 설비 대체가 필요한 시점으로, VSAT을 이용한 Ku-Band 대역에서 7개의 단말, 3개 2 hop, 1 HUB로 고속 위성망 Pilot 시스템을 구축하였으며, 구축된 시스템에 대한 성능시험을 실시한 결과, 설계한 Link Budget 등 모든 항목에 대하여 규정치를 만족시키는 성능을 확인하였다.