• Journal of the Korea Society for Simulation
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• v.26 no.1
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• pp.13-19
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• 2017

6-DOF flight simulation program is most generally used M&S tool in domestic missile development procedure. The 6-DOF M&S method, however, cannot validate the performance of a imaging seeker-adopted missile in various conditions. A M&S tool for the analysis of the integrated-flight simulation is required since the tracking performance of the imaging seeker is highly dependent on the missile maneuvering, which introduces the displacement and rotation of the target in the seeker imagery. Through the development of the $3^{rd}$ generation anti-tank missile, Raybolt, the integrated-flight M&S tool was developed and applied to the missile configuration design. It integrates synthetic image generation S/W, imaging tracker, and flight simulation program and computes the main system performance criteria, hit probability by Monte-Carlo Simulation. In this paper, the issues in the $3^{rd}$ generation anti-tank missile configuration and the integrated-flight M&S method and results are described.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.445-452
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• 2022

Class distribution of unbalanced data is an important part of the digital world and is a significant part of cybersecurity. Abnormal activity of unbalanced data should be found and problems solved. Although a system capable of tracking patterns in all transactions is needed, machine learning with disproportionate data, which typically has abnormal patterns, can ignore and degrade performance for minority layers, and predictive models can be inaccurately biased. In this paper, we predict target variables and improve accuracy by combining estimates using Synthetic Minority Oversampling Technique (SMOTE) and Light GBM algorithms as an approach to address unbalanced datasets. Experimental results were compared with logistic regression, decision tree, KNN, Random Forest, and XGBoost algorithms. The performance was similar in accuracy and reproduction rate, but in precision, two algorithms performed at Random Forest 80.76% and Light GBM 97.16%, and in F1-score, Random Forest 84.67% and Light GBM 91.96%. As a result of this experiment, it was confirmed that Light GBM's performance was similar without deviation or improved by up to 16% compared to five algorithms.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.251-259
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• 2023

In the path traveling of differential-drive robots, the steering controller plays an important role in determining the path-following performance. When a robot with a pure-pursuit algorithm is used to continuously drive a right-angled driving path in an unstructured environment without turning in place, the robot cannot accurately follow the right-angled path and stops driving due to the ground and motor load caused by turning. In the case of pure-pursuit, only the current robot position and the steering angle to the current target path point are generated, and the steering component does not reflect the speed plan, which requires improvement for precise path following. In this study, we propose a driving algorithm for differentially driven robots that enables precise path following by planning the driving speed using the radius of curvature and fusing the planned speed with the steering angle of the existing pure-pursuit controller, similar to the Model Predict Control control that reflects speed planning. When speed planning is applied, the robot slows down before entering a right-angle path and returns to the input speed when leaving the right-angle path. The pure-pursuit controller then fuses the steering angle calculated at each path point with the accelerated and decelerated velocity to achieve more precise following of the orthogonal path.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.401-410
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• 2020

In this study, a real-time Tactical UAS position compensation system based on image information developed to compensate for the weakness of location navigation information during GPS signal interference and jamming / spoofing attack is described. The Tactical UAS (KUS-FT) is capable of automatic flight by switching the mode from GPS/INS integrated navigation to DR/AHRS when GPS signal is lost. However, in the case of location navigation, errors accumulate over time due to dead reckoning (DR) using airspeed and azimuth which causes problems such as UAS positioning and data link antenna tracking. To minimize the accumulation of position error, based on the target data of specific region through image sensor, we developed a system that calculates the position using the UAS attitude, EO/IR (Electric Optic/Infra-Red) azimuth and elevation and numerical map data and corrects the calculated position in real-time. In addition, function and performance of the image information based real-time UAS position compensation system has been verified by ground test using GPS simulator and flight test in DR mode.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.8 s.111
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• pp.773-787
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• 2006

An airborne radar is an essential aviation electronic system for the aircraft to perform various civil and/or military missions in all weather environments. This paper presents the design, development, and test results of the multi-mode X-band pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRUs(Line-Replacement Unit), which include antenna unit, transmitter and receiver unit, radar signal & data processing unit and display Unit. The developed core technologies include the planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, MTI, DSP based Doppler FFT filter, adaptive CFAR, moving clutter compensation, platform motion stabilizer, and tracking capability. The design performance of the developed radar system is verified through various ground fixed and moving vehicle test as well as helicopter-borne field tests including MTD(Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• Journal of The Korean Association For Science Education
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• v.33 no.6
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• pp.1154-1169
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• 2013

The present work was performed to find behavioral characteristics of elementary school students corresponding to the motivation system on science learning (SL-BIS/BAS; Behavioral Inhibition/Activation System about Science Learning) in the observation situation. Eye-tracking was used for this study, which is one of the neurophysiological methods. The findings of present study were as follows: First, students who have sensitive motivation system to SL-BIS (SL-BIS group) showed meaningfully shorter fixation duration the whole time during an observation task than students who have sensitive motivation system to SL-BAS (SL-BAS group) (p<.05). Total fixation counts of SL-BIS group were significantly larger than SL-BAS group and it indicates that SL-BIS group often generated new fixations. Therefore, fixation duration per count of SL-BAS group was longer than that of SLBIS group. Second, we studied fixations in situations with movement corresponding to the motivation system on science learning. SL-BIS group and SL-BAS group exhibited similar fixation duration in the study task segment with movement, which is one of the stimulus attracting students. However, for the study task segment when the movement was finished, total fixation duration and fixation duration per count of SL-BAS group were meaningfully longer than those of SL-BIS group. Third, comparing fixation targets classified by factors of study task, SL-BIS group showed fixation on the target that is not important for the study task. But SL-BAS group concentrated on the target-related factor of the study task. The present work could be helpful in understanding students' characteristics corresponding to the motivation system on science learning in observation situation and for making a learning & teaching plan that is suitable to the feature of students.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.507-517
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• 2019

Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.435-441
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• 2018

In this study, we performed to design an image guiding algorithm to improve the efficiency and safety of treatment of varicose vein by focused ultrasound. The algorithm was suggested by different guiding images according to the location of varicose veins. In the case of deep-seated varicose veins, the target area was marked on the surface of the blood vessel in the obtained cross-sectional blood vessel ultrasound image. In the case of the superficial varicose vein, A guiding system based on image segmentation algorithm of the vascular region was suggested and designed two different algorithms according to varicose veins progression degree. as a results, the algorithm based on ultrasound image show a small error with $830{\mu}m$ at maximum. However, the algorithm based on charge coupled device image has a maximum error of 8.3 mm in some data. Therefore, it is expected that additional study is needed for superficial varicose vein image guiding algorithm, and it is expected that the accuracy of blood vessel tracking should be evaluated by constructing simple system.