• Industrial Engineering and Management Systems
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• 제15권3호
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• pp.259-267
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• 2016

In Wireless Sensor Network, various routing protocols were employed by our Research and Development community to improve the energy efficiency of a network as well as to control the traffic by considering the terms, i.e. Packet delivery rate, the average end-to-end delay, network routing load, average throughput, and total energy consumption. While maintaining network connectivity for a long-term duration, it's necessary that routing protocol must perform in an efficient way. As we discussed Optimized Link State Routing protocol between all of them, we find out that this protocol performs well in the large and dense networks, but with the decrease in network size then scalability of the network decreases. Whenever a link breakage is encountered, OLSR is not able to periodically update its routing table which may create a redundancy problem. To resolve this issue in the OLSR problem of redundancy and predict link breakage, an enhanced protocol, i.e. S-OLSR (More Scalable OLSR) protocol has been proposed. At the end, a comparison among different existing protocols, i.e. DSR, AODV, OLSR with the proposed protocol, i.e. S-OLSR is drawn by using the NS-2 simulator.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.361-365
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• 2006

High ionospheric spatial gradient during ionospheric storm is most concern for the landing approach with GNSS (Global Navigation Satellite System) augmentation systems. In case of the GBAS (Ground-Based Augmentation System), the ionospheric storm causes sudden increase of the ionospheric delay difference between a ground facility and a user (aircraft), and the aircraft position error increases significantly. Since the ionosphere behavior and the storm effect depend on geographic location, understanding the ionospheric storm behavior at specific regional area is crucial for the GNSS augmentation system development and implementation. Korea Aerospace Research Institute and collaborating universities have been developing an integrity monitoring test bed for GBAS research and for future regional augmentation system development. By using the dense GPS (Global Positioning System) networks in Korea, a regional ionosphere map is constructed for finding detailed aspect of the ionosphere variation. Preliminary analysis on the ionospheric gradient variation during a recent storm period is performed and the results are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4787-4807
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• 2016

Although the dense interconnection datacenter networks (DCNs) (e.g. FatTree) provide multiple paths and high bisection bandwidth for each server pair, the single-path TCP (SPT) and ECMP which are widely used currently neither achieve high bandwidth utilization nor have good load balancing. Due to only one available transmission path, SPT cannot make full use of all available bandwidth, while ECMP's random hashing results in many collisions. In this paper, we present OFPT, an OpenFlow based Parallel Transport framework, which integrates precise routing and scheduling for better load balancing and higher network throughput. By adopting OpenFlow based centralized control mechanism, OFPT computes the optimal path and bandwidth provision for each flow according to the global network view. To guarantee high throughput, OFPT dynamically schedules flows with Seamless Flow Migration Mechanism (SFMM), which can avoid packet loss in flow rerouting. Finally, we test OFPT on Mininet and implement it in a real testbed. The experimental results show that the average network throughput in OFPT is up to 97.5% of bisection bandwidth, which is higher than ECMP by 36%. Besides, OFPT decreases the average flow completion time (AFCT) and achieves better scalability.

• 한국멀티미디어학회논문지
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• 제22권9호
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• pp.1000-1010
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• 2019

Image semantic segmentation and dehazing are key tasks in the computer vision. In recent years, researches in both tasks have achieved substantial improvements in performance with the development of Convolutional Neural Network (CNN). However, most of the previous works for semantic segmentation assume the images are captured in clear weather and show degraded performance under hazy images with low contrast and faded color. Meanwhile, dehazing aims to recover clear image given observed hazy image, which is an ill-posed problem and can be alleviated with additional information about the image. In this work, we propose a deep multi-task network for simultaneous semantic segmentation and dehazing. The proposed network takes single haze image as input and predicts dense semantic segmentation map and clear image. The visual information getting refined during the dehazing process can help the recognition task of semantic segmentation. On the other hand, semantic features obtained during the semantic segmentation process can provide cues for color priors for objects, which can help dehazing process. Experimental results demonstrate the effectiveness of the proposed multi-task approach, showing improved performance compared to the separate networks.

• 국제초고층학회논문집
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• 제8권2호
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• pp.137-154
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• 2019

Singapore has seen a phenomenal and an unprecedented transformation from a swampland to a high density urban environment since its independence in 1965, made possible largely and single-handedly by the sustained efforts of its government. Indeed, urban space is a key vehicle for achieving urban social, environmental, economic, and cultural sustainability. The dense urban context in Singapore has seen an emergence and increase in elevated spaces in the form of sky-gardens, sky-bridges and sky-courts in a range of building types, seemingly seeking to tie together the different horizontal and vertical components of the city. This paper, therefore, examines the effectiveness of elevated urban spaces and pedestrian networks in Singapore and their ability to contribute to the horizontal to vertical transitions, and consequently to the urban vitality and accessibility. It does this through the analysis of two key developments: Marina Bay Sands and the Jurong Gateway. In particular, it considers the implications of certain constraints placed on urban spaces by their inherent location at height, in addition to the familiar privatization of public spaces, over-management of spaces, and their somewhat utilitarian characteristics. The paper argues that some of these issues may pose detrimental effects on the publicness of these spaces that in turn may lead to such spaces being underused and therefore adding redundancies and further stress to Singapore's urban land. Finally, the paper outlines key strategies that may help overcome the aforementioned issues, including the disjuncture associated with elevated spaces such that they may become a seamless extension of the urban spaces on ground.

• 전자통신동향분석
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• 제37권2호
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• pp.83-95
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• 2022

5G goes beyond people to serve indoor and outdoor companies and industries, as well as campuses such as halls, industrial complexes, educational institutions, stadiums, dense urban areas, rural areas, and government institutions. Therefore, a new approach to small cells is needed. Accordingly, 3GPP and Small Cell Forum are researching 5G small cell architecture; 3GPP, Small Cell Forum, and 5G Alliance for Connected Industries and Automation are also researching private networks tailored to meet the specific requirements of various companies and local governments. In particular, in the UK, a small cell-based technology is required for realizing the Joint Operator Technical Specifications-Neutral Host In-Building specification to cost-effectively secure indoor coverage. Further, the research on the SON(Self-Organizing Network) technology for small cells in 5G, where commercialization has begun, is required. The 5G-based small cell structure, private network, and Neutral Host In-Building and SON reviewed in this study are at the initial research stages; therefore, additional research is needed to secure the competitiveness of the small cell technology in 5G and Beyond 5G.

• Journal of Multimedia Information System
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• 제9권3호
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• pp.177-182
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• 2022

A deep neural network (DNN) includes variables whose values keep on changing with the training process until it reaches the final point of convergence. These variables are the co-efficient of a polynomial expression to relate to the feature extraction process. In general, DNNs work in multiple 'dimensions' depending upon the number of channels and batches accounted for training. However, after the execution of feature extraction and before entering the SoftMax or other classifier, there is a conversion of features from multiple N-dimensions to a single vector form, where 'N' represents the number of activation channels. This usually happens in a Fully connected layer (FCL) or a dense layer. This reduced 2D feature is the subject of study for our analysis. For this, we have used the FCL, so the trained weights of this FCL will be used for the weight-class correlation analysis. The popular DNN models selected for our study are ResNet-101, VGG-19, and GoogleNet. These models' weights are directly used for fine-tuning (with all trained weights initially transferred) and scratch trained (with no weights transferred). Then the comparison is done by plotting the graph of feature distribution and the final FCL weights.

• 인터넷정보학회논문지
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• 제23권5호
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• pp.9-15
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• 2022

본 논문은 매크로 기지국(Macro base station, MBS) 커버리지에 위치한 건물 내부의 밀집된 스몰셀 네트워크 환경에서 매크로 사용자 단말(Macro user equipment, MUE)의 성능향상을 위한 채널 선택 기반 다중점 협력통신(Coordinated multi-point, CoMP) 방법을 제안한다. 제안하는 CoMP 방법에서 건물 내에 위치한 MUE의 성능향상을 위해 스몰셀 기지국(Small-cell base station, SBS)들이 이웃한 MUE에게 간섭을 적게 미치는 방법으로 채널을 선택하고 CoMP가 필요한 MUE에게 적절한 신호를 송신한다. 시뮬레이션 결과에서 제안하는 CoMP 방법이 기존의 랜덤채널할당 기반의 스몰셀 네트워크 방법과 CoMP방법보다 MUE의 성능을 각각 최대 164%와 51%까지 향상시킨다.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.23-30
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• 2022

Glaucoma is a chronic neuropathy that affects the optic nerve which can lead to blindness. The detection and prediction of glaucoma become possible using deep neural networks. However, the detection performance relies on the availability of a large number of data. Therefore, we propose different frameworks, including a hybrid of a generative adversarial network and a convolutional neural network to automate and increase the performance of glaucoma detection. The proposed frameworks are evaluated using five public glaucoma datasets. The framework which uses a Deconvolutional Generative Adversarial Network (DCGAN) and a DenseNet pre-trained model achieves 99.6%, 99.08%, 99.4%, 98.69%, and 92.95% of classification accuracy on RIMONE, Drishti-GS, ACRIMA, ORIGA-light, and HRF datasets respectively. Based on the experimental results and evaluation, the proposed framework closely competes with the state-of-the-art methods using the five public glaucoma datasets without requiring any manually preprocessing step.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.644-647
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• 2004

Optical add/drop multiplexers (OADMs), one of the new network elements, will play a key role enabling greater connectivity and flexibility in the dense wavelength-division multiplexing (DWDM) networks. The importance of OADMs is that they allow the optical network to be local transmitting/extraction on a wavelength-by-wavelength basis to optimize traffic, efficient network utilization, network growth, and to enhance network flexibility. Also, the automatic assembly system of micro optical filters and fibers is a key technology in the development of optical modules with high functionality. Recently, one of remarkable tends in the development of optical communication industry is the miniaturization and integration of products. In this research, we have developed a system capable of automatic alignment of a film filter and a lensed fiber in order to improve the speed and losses in the optical fiber to filter alignment of optical modules. Using the developed automatic alignment system and silicon optical benches, we have fabricated the micro OADM and measured the insertion loss and aging effect.