• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.167-173
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• 2016

Compressed Sensing(CS) is the theory that can recover signals which are sampled below the Nyquist sampling rate to original analog signals. In this paper, we propose the estimation algorithm of ultrasonic attenuation coefficients in the frequency domain using CS. While most estimation algorithms transform the time-domain signals into the frequency-domain using the Fourier transform, the proposed method directly utilize the spectral information in the recovery process by the basis matrix without the completely recovered signals in the time domain. We apply three transform bases for sparsifying and estimate the attenuation coefficients using the Centroid Downshift method with Dual-reference diffraction compensation technique. The estimation accuracy and execution time are compared for each basis matrix. Computer simulation results show that the DCT basis matrix exhibits less than 0.35% estimation error for the compressive ratio of 50% and about 6% average error for the compressive ratio of 70%. The proposed method which directly extracts frequency information from the CS signals can be extended to estimating for other ultrasonic parameters in the Quantitative Ultrasound (QUS) Analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.375-383
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• 2004

As wireless mobile networks have been widely adopted due to their convenience for deployment, the research for improving their performance has been actively conducted. Since their throughput is restrained by the packet corruption rate not by congestion as in wired networks, however, network simulations for performance evaluation need to select the appropriate wireless channel model representing the behavior of propagation errors for the evaluated channel. The selection of the right model should depend on various factors such as the adopted frequency band, the level of signal power, the existence of obstacles against signal propagation, the sensitivity of protocols to bit errors, and etc. This paper analyzes 10-day bit traces collected from real sensor channels exhibiting the high bit error rate to determine a suitable sensor channel model. For selection, it also evaluates the performance of two error recovery algorithms such as a link layer FEC algorithm and three TCPs (Tahoe, Reno, and Vegas) over several channel models. The comparison analysis shows that CM(Chaotic Map) model predicts 3-time less BER variance and 10-time larger PER(Packet Error Rate) than traces while these differences between the other models and traces are larger than 10-time. The simulation experiments, furthermore, prove that CM model evaluates the performance of these algorithms over sensor channels with the precision at least 10-time more accurate than any other models.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1639-1645
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• 1991

Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation

• Journal of Korea Soil Environment Society
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• v.2 no.1
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• pp.51-61
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• 1997

The objective of this study is to evaluate the feasibility of Pumping-and-Treatment system (PTS) for remediation of the saturated zones contaminated with NAPLs. A simulation is carried out for the removal of DNAPLs (denser-than-water non-aqueous phase liquids) and LNAPLS (lighter-than-water non-aqueous phase liquids) distributing at and below the water table. In the study, LNAPL and DNAPL are assumed to be n-hexane and 1,1-dichloroacetone, respectively. The model system studied consists of four heterogeneous soil layers with different permeabilities. Groundwater flows through the bottom layer and a pumping well is located under the initial water table. The time-driven deformation of the water table and removal efficiency of contaminants are estimated after vacuum application to the inlet of the well. In the calculation, FVM (Finite Volumetric Method) with SIMPLEC algorithm is applied. Results show that removal efficiencies of both DNAPL and LNAPL are negligible for the first 5 days after the PTS operation. However, when the cone-shape water table is formed around the inlet of the pumping well, the rapid removal rate is obtained since NAPLs migrate rapidly through the curvature of the water table. The removal efficiency of DNAPL is estimated to be higher than that of LNAPL due to the gravity. The results also show that the fluctuation or cone-shaped depression of the water table enhances the removal efficiency of NAPLs in saturated zones. The simulation results could provide a basis of the PTS design for the removal of NAPLs in saturated zones.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.57-65
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• 2010

In this study, disaster damage investigation system was developed using high resolution satellite images and GIS technique to afford effective damage investigation system for widely disaster damaged area. Study area was selected in Bonghwa, Gyungsangbukdo where high magnitude of damages from torrential rain has occurred at July in 2008. GIS DB was built using 1:5,000 topographic map, cadastral map, satellite image and aerial photo to apply for investigation algorithm. Disaster damage investigation system was developed using VB NET languages, ArcObject component and MS-SQL DBMS for effective management of damage informations. The system can finding damaged area comparing pre- and post-disaster images and drawing damaged area according to the damage item unit. Extracted object was saved in Shape file format and overlayed with background GIS DB for obtaining detail information of damaged area. Disaster damage investigation system using high resolution spatial images can extract damage information rapidly and highly reliably for widely disaster areas. This system can be expected to highly contributing to enhance the disaster prevention capabilities in national level field investigation supporting and establishing recovery plan etc. This system can be utilized at the plan of disaster prevention through digital damage information and linked in national disaster information management system. Further studies are needed to better improvement in system and cover for the linkage of damage information with digital disaster registry.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.803-812
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• 2006

This paper analytically evaluates the FEC(Forward Error Correction) symbol size's effect on the performance and energy consumption of 802.11 protocol with the block FEC algorithm over WSN(Wireless Sensor Network). Since the basic recovery unit of block FEC algorithms is symbols not bits, the FEC symbol size affects the packet correction rate even with the same amount of FEC check bits over a given WSN channel. Precisely, when the same amount of FEC check bits are allocated, the small-size symbols are effective over channels with frequent short bursts of propagation errors while the large ones are good at remedying the long rare bursts. To estimate the effect of the FEC symbol site, the paper at first models the WSN channel with Gilbert model based on real packet traces collected over TIP50CM sensor nodes and measures the energy consumed for encoding and decoding the RS (Reed-Solomon) code with various symbol sizes. Based on the WSN channel model and each RS code's energy expenditure, it analytically calculates the transmission efficiency and power consumption of 802.11 equipped with RS code. The computational analysis combined with real experimental data shows that the RS symbol size makes a difference of up to 4.2% in the transmission efficiency and 35% in energy consumption even with the same amount of FEC check bits.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Journal of KIISE:Information Networking
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• v.30 no.5
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• pp.656-667
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• 2003

Congestion control is a key task in reliable multicast along with error control. However, existing tree-based congestion control schemes such as MTCP and TRAMCC are designed for one-to-many reliable multicast and have some drawbacks when they are used for many-to-many reliable multicast. We propose an efficient congestion control mechanism, TMRCC, for tree-based many-to-many reliable multicast protocols. The proposed scheme is based on the congestion windowing mechanism and a rate controller is used in addition. The feedback for error recovery is exploited for congestion control as well to minimize the overhead at the receivers. The ACK timer and the NACK timers are set dynamically reflecting the network condition changes. The rate regulation algorithm in the proposed scheme is designed to help the flows sharing the same link to achieve the fair share quickly The performance of the proposed scheme is evaluated using ns-2. The simulation results show that the proposed scheme outperforms TRAMCC in terms of intra- session fairness and shows good level of responsiveness, TCP-friendliness, and scalability. In addition, we implemented the proposed scheme by integrating with GAM that is one of many-to-many reliable multicast protocols and evaluated the performance in a laboratory-wide testbed.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.513-521
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• 2015

In the processing of ocean color remote sensing data, spatio-temporal binning is crucial for securing effective observation area. The validity determination for given source data refers to the information in Level-2 flag. For minimizing the stray light contamination, NASA OBPG's standard algorithm suggests the use of large filtering window but it results in the loss of effective observation area. This study is aimed for quality improvement of ocean color remote sensing data by recovering/extending the portion of effective observation area. We analyzed the difference between MODIS/Aqua standard and modified product in terms of chlorophyll-a concentration, spatial and temporal coverage. The recovery fractions in Level-2 swath product, Level-3 daily composite product, 8-day composite product, and monthly composite product were $13.2({\pm}5.2)%$, $30.8({\pm}16.3)%$, $15.8({\pm}9.2)%$, and $6.0({\pm}5.6)%$, respectively. The mean difference between chlorophyll-a concentrations of two products was only 0.012%, which is smaller than the nominal precision of the geophysical parameter estimation. Increase in areal coverage also results in the increase in temporal density of multi-temporal dataset, and this processing gain was most effective in 8-day composite data. The proposed method can contribute for the quality enhancement of ocean color remote sensing data by improving not only the data productivity but also statistical stability from increased number of samples.