• 한국군사과학기술학회지
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• 제20권3호
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• pp.315-327
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• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).

• Radiation Oncology Journal
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• 제35권1호
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• pp.39-47
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• 2017

Purpose: The purpose of this study was to analyze clinical outcomes from cervical cancer and stratify patients into risk groups for prognostic factors for early-stage disease. Materials and Methods: We retrospectively reviewed patients with stage IB or IIA cervical cancer treated with adjuvant radiotherapy (RT) or concurrent chemoradiotherapy (CCRT) following primary surgery at Samsung Medical Center from 2001 to 2011. Adjuvant RT was added for patients with intermediate-risk factors, and adjuvant CCRT was performed on high-risk patients after surgery. Results: We reviewed 247 patients-149 in the high-risk group and 98 in intermediate-risk group. The median follow-up was 62 months. Loco-regional failure (LRF) alone occurred in 7 patients (2.8%), distant metastasis alone in 37 patients (15.0%) and LRF with DM in 4 patients (1.6%). The 5-year disease-free survival (DFS) and overall survival (OS) rates for both groups were 79.7% and 87.6%, respectively. In the high-risk group, the 5-year DFS and OS probabilities were 72.5% and 81.9%, respectively. Histologic type, pathologic tumor size, and the number of pelvic lymph node (PLN) metastasis were significant prognostic factors for DFS and OS. We suggest a scoring system (0-3) using these prognostic factors to predict poor prognosis in high-risk patients. Using this system, patients with higher scores have higher recurrence and lower survival rates. Conclusion: In the high-risk cervical-cancer group who received primary surgery and adjuvant CCRT, non-squamous type, large tumor size and the number of PLN metastasis were significant prognostic factors, and the number of these factors was associated with survival rates.

• BMB Reports
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• 제29권6호
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• pp.569-573
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• 1996

Clinical strains of Mycobacterium tuberculosis, M. terrae complex, M. gordonae, M. avium-intracellulae complex, and M. fortuitum from Korean patients were isolated and analyzed by comparing large restriction fragment (LRF) patterns produced by digestion of genomic DNA with infrequent-cutting endonucleases like AsnI and XbaI. and pulsed-field gel electrophoresis (PFGE). Three M. tuberculosis, two M. terrae complex, two M. gordonae, two M. avium-intracellulae complex, and two M. fortuitum strains were compared by using AsnI and XbaI. and this allowed easy visual separation of all epidemiologically unrelated strains. PFGE exhibits different DNA restriction patterns which are easy to compare. Genome size of the strains roughly ranged from 3020 to 3335 kb. The LRF patterns are useful for epidemiologic studies of tuberculosis with regard to drug resistance.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.745-754
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• 2013

An efficient urban outdoor localization and navigation system is proposed for car-like robots. First an accurate outdoor localization method is suggested using line/arc features and 2.5D map matching with LRFs (Laser Range Finders), which can reduce the number of singular cases and increase accuracy. Also, path generation, path tracking, and path modification algorithms are proposed for navigation. All these algorithms are implemented on an electric scooter to construct an autonomous urban outdoor localization and navigation system. Experiments reveal the practicality of the proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.960-973
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• 2018

This paper presents design for error correcting algorithm of the time of flight (ToF) detection value in the light detection and ranging (LIDAR) system sensor. The walk error of ToF value is generated by change of the received signal power depending on distance between the LIDAR sensor and object. The proposed method efficiently compensates the ToF value error by the independent ToF value calculation from the received signal using both rising point and falling point. A constant error of ~0.05 m is obtained after the walk error correction while an increasing error up to ~1 m is obtained with conventional method.

• 한국군사과학기술학회지
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• 제5권3호
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• pp.62-76
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• 2002

This paper describes the design of a Coordinates Tracking algorithm for EOTS and its error analysis. EOTS stabilizes the image sensors such as FLIR, CCD TV camera, LRF/LD, and so on, tracks targets automatically, and provides navigation capability for vehicles. The Coordinates Tracking algorithm calculates the azimuth and the elevation angle of EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which is generated by a Radar or an operator. In the error analysis in this paper, the unexpected behaviors of EOTS that is due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. This algorithm is verified and the error analysis is confirmed through simulations. The application of this algorithm to EOTS will improve the operational capability by reducing the time which is required to find the target and support especially the flight in a night time flight and the poor weather condition.

• Journal of Advanced Marine Engineering and Technology
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• 제37권7호
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• pp.737-742
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• 2013

Recently, unmanned aircrafts for safe measurement in hazardous locations have been developed. In a method of operation of unmanned aircraft vehicles (UAV), there are two methods of manual control and automatic control. Small UAVs are used for low altitude surveillance flights where unknown obstacles can be encountered. Obstacle avoidance is one of the most challenging tasks which the UAV has to perform with high level of accuracy. In this study, we used a laser range finder as an obstacle detector in automatic navigation of unmanned aircraft to patrol the destination automatically. We proposed a system to avoid obstacles automatically by measuring the angle and distance of the obstacle using the laser range finder.

• 전기학회논문지
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• 제56권7호
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• pp.1302-1308
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• 2007

In this paper, a real-time collision avoidance algorithm is proposed for experimental Autonomous Vehicle(XAV). To ensure real-time implementation, a virtual potential field is calculated in one dimensional space. The attractive force is generated by the steering command either transmitted in the remote control station or calculated in the Autonomous Navigation System(ANS) of the XAV. The repulsive force is generated by obstacle information obtained from Laser Range Finder(LRF) mounted on the XAV. Using these attractive and repulsive forces, modified steering, velocity and emergency stop commands are created to avoid obstacles and follow a planned path. The suggested algorithm is inserted as one component in the XAV system. Through various real experiments and technical demonstration using the XAV, the usefulness and practicality of the proposed algorithm are verified.

• Advances in Computational Design
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• 제1권1호
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• pp.79-86
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• 2016

In this study, the three different meta-heuristics namely the Grey Wolf Optimizer (GWO), Stochastic Fractal Search (SFS), and Adaptive Differential Evolution with Optional External Archive (JADE) algorithms are examined. This study considers optimization of the planer frame to minimize its weight subjected to the strength and displacement constraints as per the American Institute of Steel and Construction - Load and Resistance Factor Design (AISC-LRFD). The GWO algorithm is associated with grey wolves' activities in the social hierarchy. The SFS algorithm works on the natural phenomenon of growth. JADE on the other hand is a powerful self-adaptive version of a differential evolution algorithm. A one-bay ten-story planar steel frame problem is examined in the present work to investigate the design ability of the proposed algorithms. The frame design is produced by optimizing the W-shaped cross sections of beam and column members as per AISC-LRFD standard steel sections. The results of the algorithms are compared. In addition, these results are also mapped with other state-of-art algorithms.