• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.82-90
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• 2013

An Optical Network-on-Chip(ONoC) based on silicon photonics is one of promising technology for next generation exascale computing architectures. Recent active researches on ONoC focus on improving bandwidth further and avoiding path collisions by using wavelength division multiplexing (WDM). However, the number of wavelengths used for the WDM increases linearly as the number of Processing Element (PE) increases in existing ONoCs which adopt centralized routing architecture. The problem will also arises growing cost of optical devices such as light switches and light sources and limits the scalability of ONoC due to the sinal loss caused by interference of distinct light sources. In this paper, we proposes a distributed routing architecture for ONoC which is based on 2D-mesh structure using WDM technique and present a method that minimize the required number of wavelengths exploiting the connectivity of communication. In comparison with existing centralized routing architectures, results show reduction by 56% of the number of wavelengths and 21% of the number of optical switches in $8{\times}8$ networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1B
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• pp.1-7
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• 2004

Increase of internet users and new type of applied traffic such as game, news, distributed computing, online image conference, and real time audio and video have leaded to demand for more bandwidth for each application. This algorithm represents a complex optical exchanger having typical wavelength switching function and time-slotted transmission function. Performance assessment of the proposed OXC (Optical Cross connect) sttucture defines LFS (Limit Frame Size) and VFS (Variable Frame Size) for classification by packet type and calculates the channel effect and loss probability depending the demanded bandwidth by access node increase. Optical exchanger in this type of structure can guarantee future network expansion as well as decrease of frame collision resulted from node increase.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.256-263
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• 2002

Optical Multistage Interconnection Networks(OMINs) comprising photonic switches have been studied extensively as important interconnecting building blocks for communication networks and parallel computing systems. A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of cross-talk-faults in OMINs. As the size of today's network becomes very large, the conventional diagnosis methods based on tests and simulation have become inefficient, or even more, impractical. In this paper, we propose a simple and easily implementable algorithm for detection and isolation of the single crosstalk-fault in OMINs. Specifically, we develope an algorithm fur the isolation of the source fault in switching elements whenever the single crosstalk-fault is detected in OMINS. The proposed algorithm is illustrated by an example of 16$\times$16 banyan network.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.394-401
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• 2007

High speed all optical network is a viable option to satisfy the exponential growth of internet usage in the recent years. Optical networks offer very high bit rates and, by employing technologies like internet protocol over wavelength division multiplexing(IP-over-WDM), these high bit rates can be effectively utilized. However, failure of a network component, carrying such high speed data traffic can result in enormous loss of data in a few seconds and persistence of a failure can severely degrade the performance of the entire network. Designing IP-over-WDM networks, which can withstand failures, has been subject of considerable interest in the research community recently. Most of the research is focused on the failure of optical links in the network. This paper addresses the problem of designing IP-over-WDM networks that do not suffer service degradation in case of a single link failure. The paper proposes an approach based on the framework provided by a recent paper by M. Kurant and P. Thiran. The proposed approach can be used to design large survivable IP-over-WDM networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5978-5999
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• 2018

Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.99-104
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• 2022

Convolutional neural network (CNN) generally uses two-stream architecture RGB and optical flow stream for its action recognition function. RGB frames stream display appearance and optical flow stream interprets its action. However, the standard method of using optical flow is costly in its computational time and latency associated with increased action recognition. The purpose of the study was to evaluate a novel way to create a two sub-networks in neural networks. The optical flow sub-network was assigned as a teacher and the RGB frames as a student. In the training stage, the optical flow sub-network extracts features through the teacher sub-network and transmits the information to student sub-network for baseline training. In the test stage, only student sub-network was operational with decreased in latency without computing optical flow. Experimental results shows that our network fed only by RGB stream gets a competitive accuracy of 54.5% on HMDB51, which is 1.5 times better than that on R3D-18.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.267-270
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• 1997

Oxygen saturation is an important parameter in clinical fields; fetal monitoring, apnea, emergency medicine etc. Because of monitoring patients continuously, pulse oximeter that measures oxigen saturation non-invasively is regarded attentively. But, though research about accuracy of signal extraction has been developed, it actually plays a supplementary part in hospital for not trusting the principle of measurement by clinicians. In this paper focusing on these things, first we suggested simple mathematical modelling on separating do components, ac components andnoise components in optical signal transmitted from fingertip or earlobe, and then we considered oxygen saturation computing algorithm using integral ratio of pulsating components. Last, we analyzed its effect by comparing received data.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of The Korean Astronomical Society
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• v.48 no.1
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• pp.57-66
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• 2015

Monte-Carlo radiative models of the diffuse Galactic light (DGL) in our Galaxy are calculated using the dust radiative transfer code MoCafe, which is three-dimensional and takes full account of multiple scattering. The code is recently updated to use a fast voxel traversal algorithm, which has dramatically increased the computing speed. The radiative transfer models are calculated with the generally accepted dust scale-height of 0.1 kpc. The stellar scale-heights are assumed to be 0.1 or 0.35 kpc, appropriate for far-ultraviolet (FUV) and optical wavelengths, respectively. The face-on optical depth, measured perpendicular to the Galactic plane, is also varied from 0.2 to 0.6, suitable to the optical to FUV wavelengths, respectively. We find that the DGL at high Galactic latitudes is mostly due to backward or large-angle scattering of starlight originating from the local stars within a radial distance of r < 0.5 kpc from the Earth. On the other hand, the DGL measured in the Galactic plane is mostly due to stars at a distance range that corresponds to an optical depth of $${\sim_\sim}$$ 1 measured from the Earth. Therefore, the low-latitude DGL at the FUV wavelength band would be mostly caused by the stars located at a distance of $r{\leq}0.5$ kpc and the optical DGL near the Galactic plane mainly originates from stars within a distance range of $1{\leq}r{\leq}2kpc$. We also calculate the radiative transfer models in a clumpy two-phase medium. The clumpy two-phase models provide lower intensities at high Galactic latitudes compared to the uniform density models, because of the lower effective optical depth in clumpy media. However, no significant difference in the intensity at the Galactic plane is found.