• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.836-841
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• 2016

An indoor positioning system using Wi-Fi is essential to produce a radio map that combines the indoor space of two or more dimensions, the information of node positions, and etc. in processing for constructing the radio map, the measurement of the received signal strength indicator(RSSI) and the confirmation of node placement information counsume substantial time. Especially, when the installed wireless environment is changed or a new space is created, easy installation of the node and fast indoor radio mapping are needed to provide indoor location-based services. In this paper, to reduce the time consumption, we propose an algorithm to distinguish the straight and curve lines of a corridor section by RSSI visualization and Sobel filter-based edge detection that enable accurate node deployment and space analysis using cable-type Wi-Fi node installed at a 3 m interval. Because the cable type Wi-Fi is connected by a same power line, it has an advantage that the installation order of nodes at regular intervals could be confirmed accurately. To be able to analyze specific sections in space based on this advantage, the distribution of the signal was confirmed and analyzed by Sobel filter based edge detection and total RSSI distribution(TRD) computation through a visualization process based on the measured RSSI. As a result to compare the raw data with the performance of the proposed algorithm, the signal intensity of proposed algorithm is improved by 13.73 % in the curve section. Besides, the characteristics of the straight and the curve line were enhanced as the signal intensity of the straight line decreased by an average of 34.16 %.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.102-109
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• 2008

In this paper, the robust hybrid modulation type classifier which use both HOS and WT key features and can recognize 10 digitally modulated signals without a priori information in multipath fading channel conditions is proposed. The proposed classifier developed using data taken field measurements in various propagation model (i,e., rural area, small town and urban area) for real world scenarios. The 9 channel data are used for supervised training and the 6 channel data are used for testing among total 15 channel data(i.e., holdout-like method). The Proposed classifier is based on HOS key features because they are relatively robust to signal distortion in AWGN and multipath environments, and combined WT key features for classifying MQAM(M=16, 64, 256) signals which are difficult to classify without equalization scheme such as AMA(Alphabet Matched Algorithm) or MMA(Multi-modulus Algorithm. To investigate the performance of proposed classifier, these selected key features are applied in SVM(Support Vector Machine) which is known to having good capability of classifying because of mapping input space to hyperspace for margin maximization. The Pcc(Probability of correct classification) of the proposed classifier shows higher than those of classifiers using only HOS or WT key features in both training channels and testing channels. Especially, the Pccs of MQAM 3re almost perfect in various SNR levels.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.22-30
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• 2009

Due to high levels of integration and complexity, the Network-on-Chip (NoC) approach has emerged as a new design paradigm to overcome on-chip communication issues and data bandwidth limits in conventional SoC(System-on-Chip) design. In particular, exponentially growing of energy consumption caused by high frequency, synchronization and distributing a single global clock signal throughout the chip have become major design bottlenecks. To deal with these issues, a globally asynchronous, locally synchronous (GALS) design combined with low power techniques is considered. Such a design style fits nicely with the concept of voltage-frequency-islands (VFI) which has been recently introduced for achieving fine-grain system-level power management. In this paper, we propose an efficient design methodology that minimizes energy consumption by VFI partitioning on an NoC architecture as well as assigning supply and threshold voltage levels to each VFI. The proposed algorithm which find VFI and appropriate core (or processing element) supply voltage consists of traffic-aware core graph partitioning, communication contention delay-aware tile mapping, power variation-aware core dynamic voltage scaling (DVS), power efficient VFI merging and voltage update on the VFIs Simulation results show that average 10.3% improvement in energy consumption compared to other existing works.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.1
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• pp.30-43
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• 2008

Memory reference instructions such as loads or stores are critical factors that limit the processing power of processor. The prefetching technique is an effective way to reduce the latency caused from memory access. However, excessively aggressive prefetch leads to cache pollution so as to cancel out the advantage of prefetch. In this study, four filtering schemes have been compared and evaluated which dynamically decide whether to begin prefetch after referring a filtering table to decrease cache pollution. First, A bi-states scheme has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete state scheme has been introduced to be used as a reference for the comparative study. A block address lookup scheme has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the bi-states scheme, the contents of each entry have the fields the same as the complete state scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. Experimental results from commonly used general benchmarks and multimedia programs show that average cache miss ratio have been decreased by 10.5% for the block address lookup scheme(BAL) compare to conventional dynamic filter scheme(2-bitSC).

• Progress in Medical Physics
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• v.6 no.2
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• pp.83-92
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• 1995

The T1 mapping of an human anatomy may give a characteristic contrast among the various tissues and the normal/abnormal tissues. Here, the methodology of constructing T1 map out of several images with different TRs, will be described using non-linear curve fitting. The general curve fitting algorithm requires the initial trial values T1t and Mot for the variables to be fitted. Three different methods of suppling the trial T1t and Mot are suggested and compared for the efficiency and the accuracy. The curve-fitting routine was written in ANSI C and excuted on a SUN workstation. Several distilled-water phantoms with various concentrations of Gd-DTPA were prepared to examine the accuracy of the curve-fitting program. An MR image was used as the true proton density image without any random noise, and several images with different TRs were generated with the theoretical T1 relaxation times 250, 500, and 1000msec. The random noise of 1, 5, and 10％ were embedded into the simulated images. These images were used to generate the T1 map, and the resultant T1 maps for each T1 were analyzed to study the effect of the random noise on the T1 map.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.174-182
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• 2002

The object-oriented design methods and their CASE tools are widely used in practice by many real-time software developers. However, object-oriented CASE tools require an additional step of identifying tasks from a given design model. Unfortunately, it is difficult to automate this step for a couple of reasons: (1) there are inherent discrepancies between objects and tasks; and (2) it is hard to derive tasks while maximizing real-time schedulability since this problem makes a non-trivial optimization problem. As a result, in practical object-oriented CASE tools, task identification is usually performed in an ad-hoc manner using hints provided by human designers. In this paper, we present a systematic, schedulability-aware approach that can help mapping real-time object-oriented models to multi-threaded implementations. In our approach, a task contains a group of mutually exclusive transactions that may possess different periods and deadline. For this new task model, we provide a new schedulability analysis algorithm. We also show how the run-time system is implemented and how executable code is generated in our frame work. We have performed a case study. It shows the difficulty of task derivation problem and the utility of the automated synthesis of implementations as well as the Inappropriateness of the single-threaded implementations.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.33-46
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• 2015

In this paper, we predicts the analog and digital circuit performance of FinFETs that are scaled down following the ITRS(International technology roadmap for semiconductors). For accurate prediction of the circuit performance of scaled down devices, accurate parasitic resistance and capacitance analytical models are developed and their accuracies are within 2 % compared to 3D TCAD simulation results. The parasitic capacitance models are developed using conformal mapping, and the parasitic resistance models are enhanced to include the fin extension length($L_{ext}$) with respect to the default parasitic resistance model of BSIM-CMG. A new algorithm is developed to fit the DC characteristics of BSIM-CMG to the reference DC data. The proposed capacitance and resistance models are implemented inside BSIM-CMG to replace the default parasitic model, and SPICE simulations are performed to predict circuit performances such as $f_T$, $f_{MAX}$, ring oscillators and common source amplifier. Using the proposed parasitic capacitance and resistance model, the device and circuit performances are quantitatively predicted down to 5 nm FinFET transistors. As the FinFET technology scales, due to the improvement in both DC characteristics and the parasitic elements, the circuit performance will improve.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.29-36
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• 2011

Evapotranspiration (ET) from the various surfaces needs to be understood because it is a crucial hydrological factor to grasp interaction between the land surface and the atmosphere. A traditional way of estimating it, which is calculating it empirically using lysimeter and pan evaporation observations, has a limitation that the measurements represent only point values. However, these measurements cannot describe ET because it is easily affected by outer circumstances. Thus, remote sensing technology was applied to estimate spatial distribution of ET. In this study, we estimated major components of energy balance method (i.e. net radiation flux, soil heat flux, sensible heat flux, and latent heat flux) and ET as a map using Mapping Evapo-Transpiration with Internalized Calibration (METRIC) satellite-based image processing model. This model was run using Landsat imagery of Gyeongan watershed in Korea on Feb 1, 2003 and Sep 13, 2006. Basic statistical analyses were also conducted. The estimated mean daily ETs had respectively 22% and 11% of errors with pan evaporation data acquired from the Suwon Weather Station. This result represented similar distribution compared with previous studies and confirmed that the METRIC algorithm had high reliability in the watershed. In addition, ET distribution of each land use type was separately examined. As a result, it was identified that vegetation density had dominant impacts on distribution of ET. Seasonally, ET in a growing season represented significantly higher than in a dormant season due to more active transpiration. The ET maps will be useful to analyze how ET behaves along with the circumstantial conditions; land cover classification, vegetation density, elevation, topography.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.143-154
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• 2012

As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.28-35
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• 2007

Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.