• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.535-544
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• 2018

Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. This study was conducted to segment and classify road objects using 3D point cloud data acquired by terrestrial mobile mapping system provided by National Geographic Information Institute. For this study, the original 3D point cloud data were pre-processed and a filtering technique was selected to separate the ground and non-ground points. In addition, the road objects corresponding to the lanes, the street lights, the safety fences were initially segmented, and then the objects were classified using the support vector machine which is a kind of machine learning. For the training data for supervised classification, only the geometric elements and the height information using the eigenvalues extracted from the road objects were used. The overall accuracy of the classification results was 87% and the kappa coefficient was 0.795. It is expected that classification accuracy will be increased if various classification items are added not only geometric elements for classifying road objects in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.141-148
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• 2022

Global climate change caused by greenhouse gases(GHG) is getting serious. To prevent this, countries around the world are regulating GHG emissions. Korea has decided to reduce GHG emissions by 37% compared to BAU (Business As Usual) by 2030. The transportation sector accounted for 18.58% of the domestic GHG emission, and roads accounted for 93.75% of the total. Public transportation is also included in the target of GHG reduction, and this study was conducted to reduce GHG emissions of bus public transportation, which can reduce GHG emissions while reducing the cost of road transportation. In this study, a simulation was conducted to predict the optimal GHG emission compared to the waiting time of passengers by adjusting the bus dispatch interval by implementing a greenhouse gas simulation model using Any Logic. If a more precise model is implemented in the future, it is expected that it will be used to reduce bus GHG emissions.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.55-65
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• 2022

As Internet and mobile technology is developing, the educational environment is changing from the traditional passive way into an active one driven by learners. It is important to construct the proper learner's profile for personalized education where learners are able to study according to their learning levels. The existing studies on ICT-based personalized education have mostly focused on vocabulary and learning contents. In this paper, learning profile is constructed with not only vocabulary but grammar to define a learner's learning status in more detailed way. A proficiency metric is defined which shows how a learner is accustomed to the learning contents. The simulational results present the suggested approach is effective to the evaluation essay data with each learner's proficiency that is determined after pre-learning process. Additionally, the proposed analysis technique enables to provide statistics or graphs of the learner's status and necessary data for the learner's learning contents.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.124-133
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• 2022

With the development of hardware technology and the advancement of numerical model methods, more precise weather forecasts can be carried out. In this paper, we propose a Unicon Optimization scheme combining Loop Vectorization, Dependency Vectorization, and Code Modernization to optimize and increase Maintainability the Unicon source contained in SCAM, a simplified version of CESM, and present an overall SCAM structure. This paper tested the unicorn optimization scheme in the SCAM structure, and compared to the existing source code, the loop vectorization resulted in a performance improvement of 3.086% and the dependency vectorization of 0.4572%. And in the case of Unicorn Optimization, which applied all of these, the performance improvement was 3.457% compared to the existing source code. This proves that the Unicorn Optimization technique proposed in this paper provides excellent performance.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.312-318
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• 2022

Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

• Journal of Korea Foundry Society
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• v.42 no.6
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• pp.369-376
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• 2022

The die-casting process is an important process for various industries, but there are limitations in the profitability and productivity of related companies due to the high defect rate. In order to overcome this, this study has developed die-casting fault detection modules based on industrial AI technologies. The developed module is constructed from three-stage models depending on the characteristics of the dataset. The first-stage model conducts fault detection based on supervised learning from the dataset without labels. The second-stage model realizes one-class classification based on semi-supervised learning, where the dataset only has production success labels. The third-stage model corresponds to fault detection based on supervised learning, where the dataset includes a small amount of production failure cases. The developed fault detection module exhibited outstanding performance with roughly 96% accuracy for actual process data.

• Journal of IKEEE
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• v.28 no.3
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• pp.382-389
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• 2024

In this paper, a design of dynamic braking resistor for stationary mode of azimuth driving equipment (ADE) for multi-function radar (MFR) is presented. The ADE carries out missions which is the rotation mode for all directions and the stationary mode for tracing a subject with standstill. The ADE has to transfer the operation mode in demand time from rotation mode to stationary mode for precise target tracing. During the transition with deceleration, it may cause the fault of input power device due to back-electromotive force (back-EMF) of PMSM with generator mode. To protect the power device, a design of dynamic braking resistor is essential for consuming back-EMF. This paper presents the development of dynamic braking resistor for consuming back-EMF of ADE with deceleration mode. The validity and effect of the design is verified using simulation results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.6
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• pp.1601-1609
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• 2024

This paper proposes an automated system for detecting and managing security threats by incorporating SOAR technology for intelligent cybersecurity. The objective of the study is to analyze external STIX/TAXII-based data to build Cyber Threat Intelligence (CTI), thereby accurately assessing the risk levels of internal assets and establishing effective response strategies. The proposed system consists of four main components: CTI collection and normalization, CTI-based TTP mapping, internal asset CPE identification, and risk assessment and response strategy formulation. The information collection method involves gathering publicly available external threat intelligence and normalizing it for storage in a CTI integrated database. Additionally, a rule-based mapping algorithm is utilized to derive risk levels and response strategies based on key information such as CVE, CPE, CVSS, and TTP. As a result, the automated system proposed in this paper demonstrates the capability to analyze approximately 2,300 reports within one hour and achieve a high detection accuracy of 99.74%.

• Current Research on Agriculture and Life Sciences
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• v.24
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• pp.43-47
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• 2006

The soils of plastic film houses in which intensive cultivation takes place suffer from the serious problems such as severe salinity and accumulation of heavy metals etc. The objective of this research was to examine the change in soil properties with repeated cucumber cultivation under plastic film house at Gunwi-Gun area. The soils were classified mainly to Danbuk and SinJung series. Clay content is lower in the soils of plastic film house than in the field soil. Available $P_2O_5$ and exchangeable cations were accumulated at the level higher than the optimum range. The content of extractable heavy metals were higher in the soils of plastic film house than in those of the field. For optimum yield, much attention should be paied to the management of soils by the pre-soil survey.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.383-394
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• 2006

This study is for the inundation damage analysis caused by levee break, and for the applicability of GIS tool to make inundation map in the Jungrang stream basin which is one of the representative urbanized area in Korea. The FLDWAV was applied to the actual flood in 1998 to calibrate the parameters, and was used under the flood conditions of 100, 200 years and PMF for the analysis of inundation caused by the levee breach. As the conditions of the levee break, the duration of break(10, 30, 60 min), the width of break(10, 20, 30m) and the location of the break are considered. We found out that the range and the volume of the inundation are strongly influenced by the location of the levee break, the break width in order. And, we compared the two processes of making the inundation map using WMS and ArcView model. The Process 1 which use only WMS has the benefit by its simplicity but there could be considerable errors in making the inundation map, while Process 2 where the ArcView model is introduced to WMS has the capability of making detailed topography map but needs more process time. This study could contribute to levee breach flood analysis and making flood map to establish the EAP(Emergency Action Plan) in the urban basin.