• Fisheries and Aquatic Sciences
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• v.14 no.3
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• pp.218-225
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• 2011

Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.100-105
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• 2011

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.6
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• pp.889-899
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• 1999

A technique to obtain an exact frequency characteristics of desired targets in radar measurements is presented. The pulsing network composed of two RF switches was installed between the Network Analyzer and the antenna, and the backscattering from a metal sphere was measured at X-band. It is shown that the pulsing effectively eliminated undesired returns from antenna and other circuitry of the systems. The antenna return was suppressed by more than 60 dB, and the signal-to-noise ratio was improved drastically. The pulsed frequency data were processed to extract the responses of the desired target. The result agrees well with the theoretical backscattering characteristics of the sphere. The methods presented here are applicable to RCS measurements in compact ranges, and also to the backscattering measurements of distributed targets outdoors.

• Proceedings of the Ginseng society Conference
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• 1998.06a
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• pp.216-223
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• 1998

Cyclic nucleotide phosphodiesterases (PDEs) represent the unique enzymatic system degrddinf cAMP and cGMP which play a major role in the regulation of cell physiology. To investigate a possible molecular mechanism of ginsenosides, their activities were evaluated on PDEs which are recently described is new therapeutic targets. PDEs are classified into 7 families according to their genes (PDEI to PDE7) and are differently distributed in tissues. The IC50 values of ginsenosides were determined on PDEI to PDE 5 chromatographically isolatetl from bovine aorta. The results show that total ginseng saponin extract preferentially inhibits PDE 1 and PDE4 at concentrations nearby 200 ug/ml. Protopanaxadiol (PPD) fraction acts preferentially on PDE4 with and IC50 value of 100 nlml and inhibits also PDEI and PDE5 at 14 to 2 fold higher concentrations, respectively. Protopanaxatriol (PPT) fraction preferentially inhibits PDE 1 with and IC50 value of 170 ug/ml. Compound Rgl, originated from PPT fraction, and RC3 (5) represent the most active compounds towards PDE 1 with IC50 values around 80 UM. However Rg3 (R), epimer of Rgl (5) has no effect on the various PDEs tested, excepted on PDE3 rich is sligthly sensitive Compound Rbl, originated from PPD, acts on both PDEI and PDE4. It if two fold less active than Rgl and Rg3 (5) on PDEI. Taken together, these results mainly suggest that PDEI and PDE4 inhibitions could be a molecular mechanism which would participate in ginsenoside mechanisms, especially the effect of PPD on blood vessel and on CNS.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.567-577
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• 2016

SqueeSAR is a new technique to combine Persistent Scatterer (PS) and Distributed Scatterer (DS) for deformation monitoring. Although many PSs are available in urban areas, SqueeSAR analysis can be beneficial to increase the PS density in not only natural targets but also smooth surfaces in urban environment. The height of each targets is generally required to remove topographic phase in interferometric SAR processing. The result of PSInSAR analysis to use PS only is not affected by DEM resolution because the height error of initial input DEM at each PSs is precisely compensated in PS processing chain. On the contrary, SqueeSAR can be affected by DEM resolution and precision since it includes spatial average filtering for DS targets to increase a signal-to-noise ratio (SNR). In this study we observe the effect of DEM resolution on deformation measurement by PSInSAR and SqueeSAR. With ALOS-1 PALSAR L-band data, acquired over Daejeon city, Korea, two different DEM data are used in InSAR processing for comparison: 1 m LIDAR DEM and SRTM 1-arc (~30 m) DEM. As expected the results of PSInSAR analysis show almost same results independently of the kind of DEM, while the results of SqueeSAR analysis show the improvement in quality of the time-series in case of 1-m LIDAR DSM. The density of InSAR measurement points was also improved about five times more than the PSInSAR analysis.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.161-164
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• 2005

As the power of influence of the Internet grows steadily, attacks against the Internet can cause enormous monetary damages nowadays. A worm can not only replicate itself like a virus but also propagate itself across the Internet. So it infects vulnerable hosts in the Internet and then downgrades the overall performance of the Internet or makes the Internet not to work. To response this, worm detection and prevention technologies are developed. The worm detection technologies are classified into two categories, host based detection and network based detection. Host based detection methods are a method which checks the files that worms make, a method which checks the integrity of the file systems and so on. Network based detection methods are a misuse detection method which compares traffic payloads with worm signatures and anomaly detection methods which check inbound/outbound scan rates, ICMP host/port unreachable message rates, and TCP RST packet rates. However, single detection methods like the aforementioned can't response worms' attacks effectively because worms attack the Internet in the distributed fashion. In this paper, we propose a design of distributed worm detection system to overcome the inefficiency. Existing distributed network intrusion detection systems cooperate with each other only with their own information. Unlike this, in our proposed system, a worm detection system on a network in which worms select targets and a worm detection system on a network in which worms propagate themselves cooperate with each other with the direction-aware information in terms of worm's lifecycle. The direction-aware information includes the moving direction of worms and the service port attacked by worms. In this way, we can not only reduce false positive rate of the system but also prevent worms from propagating themselves across the Internet through dispersing the confirmed worm signature.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.988-996
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• 2012

This paper presents a distributed task assignment algorithm for the suppression of enemy air defense (SEAD) mission of heterogeneous UAVs, based on the consensus-based bundle algorithm (CBBA). SEAD mission can be modeled as a task assignment problem of multiple UAVs performing multiple air defense targets, and UAVs performing SEAD mission consist of the weasel for destruction of enemy's air defense system and the striker for the battle damage assessment (BDA) or other tasks. In this paper, a distributed task assignment algorithm considering path-planning in presence of terrain obstacle is developed for heterogeneous UAVs, and then it is applied to SEAD mission. Through numerical simulations the performance and the applicability of the proposed method are tested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.338-344
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• 2021

Elements that threaten domestic security, such as diplomatic changes in the four major powers surrounding the Korean Peninsula and restrictions on supply and demand of parts due to COVID-19, are constantly increasing. The importance of localizing weapon systems has grown to respond proactively to the threat. As localization is not conducted evenly by the field, it is necessary to change the criteria for selecting localization targets. Establishing standards for selecting targets is difficult due to a lack of research to identify targets. This paper emphasized that the smooth supply of parts from overseas should be examined to identify targets for localization. If suppliers are not distributed evenly in the market, there is a risk of potential supply problems. CRk and HHI, representing the market structure, were proposed as indicators for evaluating the degree of smoothness quantitatively. Among them, CRk is used in Korea to check the market concentration, but there is a limit in the subjectivity of the evaluator, so it cannot be applied without a separate study on the market structure. Therefore, HHI should be applied.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1414-1419
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• 2011

In this paper we study the modeling to quantitatively assess the failure rate of USN system designed for fault-tolerant architecture, aiming at applying the world's best domestic USN technology to safety-critical railways. In order to apply the USN system to the safety-critical field like a train control sector that the failures of controllers may cause severe railway accidents such as train collision and derailment, the quantitative reliability and safety evaluation recommended in IEC 62278 must be preceded. We also develop the evaluation model for overall system failure rate for the distributed network structure, which is the characteristics of USN system. Especially, we allocate reliability targets to component units, and present an availability evaluation plan through the plan on the quantitative achievement of failure rate for sensor nodes, gateways, radio-communication network and servers, along with the failure rate model of the overall system considering network operational features.