• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.12-20
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• 2007

The aiming ability is a key to improve the accuracy performance of the gun pointing system in the ground military vehicle. This paper describes the new detection method of chatter vibration using disturbance acceleration in the pointing structure. In order to analysis the vibration trends of the pointing system occurred while the vehicle driving, acceleration data obtained from vehicle was processed by using data processing algorithm with moving average and Hilbert transform. The specific mode constants of acceleration were obtained from various disturbances. Vehicle velocity, road condition and property of pointing structure were considered as factors which make the change of vibration trend in vehicle dynamics. Finally, back propagation neural networks have been applied to the pattern recognition of the classification of vibration signal in various driving conditions. Results of signal processing were compared with other condition result and analysed.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.251-257
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• 2012

Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

• Journal of electromagnetic engineering and science
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• v.15 no.1
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• pp.37-43
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• 2015

We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.272-273
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• 2007

This paper presents the characteristic of rectangular and octagonal spiral inductor using PGS(Patterned Ground Shield). We investigated variation of inductance and Q-factor with changing of turn number at fixed width, spacing and inner diameter. We confirmed that characteristic of inductance and Q-factor be appled PGS in rectangular and octagonal types spiral inductor by EM simulation tool. Inductance decreased irrespective of structure but Q-factor increased. When PGS not exist, Q-factor of Inductor is analogous at classification frequency but, rectangular is a few larger then octagonal in small turn number. The other side, When PGS is inserted, we confirmed that octagonal lager then rectangular in many turn number. Q-factor is improved in case of octagonal structure and small turn number by PGS effect.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1064-1066
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• 2003

In this paper, ground penetrating radar (GPR), which has the capability to detect non metal and plastic mines, is proposed to detect and discriminate antipersonnel (AP) landmines. The time domain GPR - Impulse radar and frequency domain GPR - SFCW (Stepped Frequency Continuous Wave) radar is utilized for metal and non-metal landmine detection and its performance is investigated. Since signal processing is vital for target reorganization and clutter rejection, we implemented the MUSIC (Multiple Signal Classification) algorithm for the signal processing of SFCW radar data and SAR (Synthetic Aperture Radar) processing method for the signal processing of Impulse radar data.

• Journal of KIBIM
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• v.13 no.1
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• pp.22-32
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• 2023

Due to the increased use of digital maps in the construction industry, there is a growing demand for high-quality digital map analysis. With the large amounts of data found in digital maps at earthwork sites, there is a particular need to enhance the accuracy and speed of digital map analysis. To address this issue, our study aims to develop new technology and verify its performance to address non-ground and range mismatch issues that commonly arise. Additionally, our study presents a new digital map analysis framework for earthwork sites that utilizes three newly developed technologies to improve the performance of digital map analysis. Through this, it achieved about 95% improvement in analysis performance compared to the existing framework. This study is expected to contribute to the improvement of the quality of digital map analysis data of earthworks.

• Earthquakes and Structures
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• v.23 no.3
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• pp.315-328
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• 2022

Structures designed for wind have an opposite design approach to those designed for earthquakes. These structures are usually reliable if they are constructed in an area where there is almost no or less severe earthquake. However, as seismic activity is unpredictable and it can occur anytime and anywhere, the seismic safety of structures designed for wind must be assessed. Moreover, the design approaches of wind and earthquake systems are opposite where wind design considers higher stiffness but earthquake designs demand a more flexible structure. For this reason, a novel Machine learning framework is proposed that is used to assess and classify the seismic safety of the structures designed for wind load. Moreover, suitable criteria is defined for the design of wind resistance structures considering seismic behavior. Furthermore, the structural behavior as a result of dynamic interaction between superstructure and substructure during seismic events is also studied. The proposed framework achieved an accuracy of more than 90% for classification and prediction as well, when applied to new structures and unknown ground motions.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1063-1071
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• 2023

Unmanned aerial vehicles (UAVs, drones) are becoming increasingly useful in a variety of fields. Advances in UAV and camera technology have made it possible to equip them with ultra-high resolution sensors and capture images at low altitudes, which has improved the reliability and classification accuracy of object identification on the ground. The distinctive contribution of this study is the derivation of sensor-specific performance metrics (GRD/GSD), which shows that as the GSD increases with altitude, the GRD value also increases. In this study, we identified the characteristics of various onboard sensors and analysed the image quality (discrimination resolution) of aerial photography results using UAVs, and calculated the shooting conditions to obtain the discrimination resolution required for reading ground objects.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.1
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• pp.56-63
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• 2020

The usage of OPC-free alkali activated ground granulated blast furnace slag(GGBS) mortar has been widely studied on the previous years, due to its advantages on sustainability, durability and workability. This paper brings a new view, aiming to classify the best application in situ for each mortar, according to the type and activator content. By this practical implication, more efficiency is achieved on the construction site and consequently less waste of materials. In order to compare the different activators, the following experiments were performed: analysis of compressive strength at 28 days, setting time measured by needles penetration resistance, analysis of total pore volume performed by MIP and permeability assessment by RCPT test. In general, activated GGBS had acceptable performance in all cases compared to OPC, and remarkable improved durability. Following the experimental results, it was confirmed that each activator and different concentrations impose distinct outcome performance to the mortar which allows the classification. It was observed that the activator Ca(OH)2 is the most versatile among the others, even though it has limited compressive strength, being suitable for laying mortar, coating/plaster, adhesive and grouting mortar. Samples activated with NaOH, in turn, presented in general the most similar results compared to OPC.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.386-389
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• 1999

In this study, visible and near infrared channels of NOAA/AVHRR data were used to classify land use and vegetation types over Korean peninsula. Analyzing forest stand structures and prediction of forest productivity using satellite data were also reviewed. Land use and land cover classification was made by unsupervised clustering methods. After monthly Normalized Difference Vegetation Index (NDVI) composite images were derived from April to November 1998, the derived composite images were used as temporal feature vector's in this clustering analysis. Visually interpreted, the classification result was satisfactory in overall for it matched well with the general land cover patterns. But subclassification of forests into coniferous, deciduous, and mixed forests were much confused due to the effects of low ground resolution of AVHRR data and without defined classification scheme. To investigate into the forest stand structures, digital forest type maps were used as an ancillary data. Forest type maps, which were compiled and digitalized by Forestry Research Institute, were registered to AVHRR image coordinates. Two data sets were compared and percent forest cover over whole region was estimated by multiple regression analysis. Using this method, other forest stand structure characteristics within the primary data pixels are expected to be extracted and estimated.