• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.417-421
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• 2007

Recently, many studies have focused on extracting transliteration pairs from bilingual texts. Most of these studies are based on the statistical transliteration model. The paper discusses the limitations of previous approaches and proposes novel approaches called dynamic window and tokenizer to overcome these limitations. Experimental results show that the average rates of word and character precision are 99.0% and 99.78%, respectively.

• KIEAE Journal
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• v.12 no.5
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• pp.77-84
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• 2012

Daylighting is the controlled admission of natural light into a space, reducing electric lighting and saving energy. By providing a direct link to the dynamic and perpetually evolving patterns of outdoor illumination, daylighting helps create a visually stimulating and comfort environment for building occupants, while reducing energy costs. Especially, however, glare is the most important factor in daylighting, which is issued by incoming direct sunlight into windows. This study analyzed the discomfort glare on a daylighting window by using Image processing methodology and found a solution to problems with glare source of occupants. There are several ways to evaluate discomfort glare such as UGR (Unified Glare Rating) of CIE, DGI (Daylight Glare Index, Hopkinson, 1972) and VCP (Visual Comfort Probability) of IES. These are used to apply to the relatively little artificial light source and they cannot cover discomfort glare from a real daylighting window. In this regarding, this paper aimed to calculate DGI index of the real daylighting window in a experimental space by using image processing methodology. The variables and outcomes are luminance distribution of non-shading window, effect of venetian blind installed on the window and locations related to position index of DGI.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.87-104
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• 2024

Most functional magnetic resonance imaging (fMRI) studies in resting state have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant. However, increased interest has recently been in quantifying possible dynamic changes in FC during fMRI experiments. FC study may provide insight into the fundamental workings of brain networks to brain activity. In this work, we focus on the specific problem of estimating the dynamic behavior of pairwise correlations between time courses extracted from two different brain regions. We compare the sliding-window techniques such as moving average (MA) and exponentially weighted moving average (EWMA), dynamic causality with vector autoregressive (VAR) model, dynamic conditional correlation (DCC) based on volatility, and the proposed alternative methods to use differencing and recursive residuals. We investigate the properties of those techniques in a series of simulation studies. We also provide an application with major depressive disorder (MDD) patient fMRI data to demonstrate studying dynamic correlations.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.223-230
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• 2006

A window-based image processing is an elementary part of image processing area. Because window-based image processing is computationally intensive and data intensive, it is hard to perform ail of the operations of a window-based image processing in real-time by using a software program on general-purpose computers. This paper proposes a parallel hardware architecture that can perform a window-based image processing in real-time using FPGA(Field Programmable Gate Array). A dynamic threshold circuit and a local histogram equalization circuit of the proposed architecture are designed using VHDL(VHSIC Hardware Description Language) and implemented with an FPGA. The performances of both implementations are measured.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.10
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• pp.515-529
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• 2017

EnergyPlus, which is widely used in various fields, provides Simple Window Model, a window model that can be used practically. However, the results of building load using the model are different from those of the standard model. The main cause of the deviation by Simple Window Model was analyzed to be due to the assumption that all windows were considered as single layer. The purpose of this study is to propose a window model that improves the cause of deviation by Simple Window Model and can be easily calculated from the algebraic relations. The proposed window model solved the heat balance equation algebraically by using seven window characteristic coefficients. The coefficient relationships consisted of the heat transmission coefficient and solar heat gain coefficient as input parameters make practical use and calculation possible. As a result of comparing the deviation between each window model by implementing the dynamic analysis method, the proposed window model showed that the deviation of the total heating/cooling energy consumption was reduced to 1/3 compared to Simple Window Model for one year. Although the maximum energy consumption did not show any significant improvement, the indoor temperature evaluation showed significantly reduced deviation.

• The Journal of Fisheries Business Administration
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• v.43 no.1
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• pp.11-18
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• 2012

This study is aimed to estimate a dynamic productive efficiency by vessel of large purse seine fishery and analyze changes of them over times using a window/DEA method. In addition, based on estimation results, it aims to suggest production management implications for an viable development of fisheries. Results indicated that an annual efficiency change of large purse seine fishery was estimated at 0.77 for 2007~2008, 0.83 for 2008~2009, and 0.77 for 2009~2010, showing a decreasing trend. As returns on sales of vessels of large purse seine fishery showed a decreasing trend, the degree of efficiency of a vessel might be closely related to the fishing profitability. The Window/DEA method was used in this study to estimate the efficiencies of vessels for large purse seine fishery. This method is well known and widely used to analyze the dynamic efficiency and it can provide useful implications for management of input factors. As a limitation of this study, it was not able to provide detailed management ways to reduce inefficiencies. However, they can be investigated with data on managerial factor, human factor, distribution factors as a future study.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.737-740
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• 1999

This paper deals with a real time optimization algorithm within real time for DRGS(Dynamic Route Guidance System) and evaluate the algorithm. A pre-developed system offers the optimal route in using only static traffic information. In using real-time traffic information, Dynamic route guidance algorithm is needed. The serious problem in implementing it is processing time increase as nodes increase and then the real time processing is impossible. Thus, in this paper we propose the optimal route algorithm with window mechanism for the real-time processing and then evaluate the algorithms.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.295-301
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• 2017

Recently, autonomous navigation technology, obstacle recognition, and obstacle collision avoidance technology are actively being developed for an unmanned surface vehicle (USV). The path to move from the current location to the destination should be planned, in order for an USV to autonomously operate safely to its destination. The dynamic window approach (DWA) is a well-known navigation scheme as a local path planning. The DWA algorithm derives the linear velocity and angular velocity by evaluating the destination direction, velocity, and distance from the obstacle. However, because DWA algorithm does not consider tracking the path, when using only the DWA algorithm, the ship may navigate away from the path line after avoiding obstacles. In this paper, we propose an improved DWA algorithm that can follow path line. And we implemented the simulation and compared the existing DWA algorithm with the improved DWA algorithm proposed in this paper. As a result, it is confirmed that the proposed DWA algorithm follows the path line better.

• The KIPS Transactions:PartC
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• v.16C no.4
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• pp.477-486
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• 2009

This paper proposes a dynamic bandwidth allocation (DBA) algorithm with adaptive maximum transmission window (DBA-AMTW) to increase channel utilization in Ethernet passive optical networks (EPONs). A polling mechanism in EPON determines channel utilization and puts constraints on DBA algorithm and scheduling. DBA algorithms based on interleaved polling with stop (IPS) allocate transmission windows to optical network units (ONU) considering requests of all ONUs. However channel idle time when any ONU does not transmit packets decreases channel utilization. Proposed DBA-AMTW improves efficiency of a network and allocates transmission windows effectively by appropriate DBA computation from REPORT messages of all ONUs. An adaptive maximum transmission window for each ONU determined by a DBA computation in the previous scheduling cycle. Simulation results show that the proposed DBA algorithm improves performance of throughput and average delay time.