• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.90-104
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• 2008

Laser scanning technology with high positional accuracy and high density will be widely applied to vast range of fields including geomatics. Especially, the development of laser scanning technology enabling long range information extraction is increasing its full use in civil engineering. This study taps into the strengths of a terrestrial laser scanning technique to develop a tunnel cross section management system that can be practically employed for determining the cross section of tunnels more promptly and accurately. Three dimensional data with high density were obtained in a prompt and accurate manner using a terrestrial laser scanner. Data processing was then conducted to promptly determine arbitrary cross sections at 0.1meter, 0.5meter and 1.0meter intervals. A laser scanning technique was also used to quickly and accurately calculate the overbreak and underbreak of both each cross section and the entire tunnel section. As the developed system utilizes vast amounts of data, it was possible to promptly determine the shape of arbitrary cross section and to calculate the overbreak and underbreak more accurately with higher area precision. It is expected, therefore, that the system will not only enable more efficient and cost effective tunnel drilling management and monitoring but also will provide a basis for future construction and management of tunnel cross section.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.205-213
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• 2018

Development and validation of crop models often require measurements of biomass for the crop of interest. Considerable efforts would be needed to obtain a reasonable amount of biomass data because the destructive sampling of a given crop is usually used. The Kinect sensor, which has a combination of image and depth sensors, can be used for estimating crop biomass without using destructive sampling approach. This approach could provide more data sets for model development and validation. The objective of this study was to examine the applicability of the Kinect sensor for estimation of chinese cabbage fresh weight. The fresh weight of five chinese cabbage was measured and compared with estimates using the Kinect sensor. The estimates were obtained by scanning individual chinese cabbage to create point cloud, removing noise, and building a three dimensional model with a set of free software. It was found that the 3D model created using the Kinect sensor explained about 98.7% of variation in fresh weight of chinese cabbage. Furthermore, the correlation coefficient between estimates and measurements were highly significant, which suggested that the Kinect sensor would be applicable to estimation of fresh weight for chinese cabbage. Our results demonstrated that a depth sensor allows for a non-destructive sampling approach, which enables to collect observation data for crop fresh weight over time. This would help development and validation of a crop model using a large number of reliable data sets, which merits further studies on application of various depth sensors to crop dry weight measurements.

• Advances in Energy Research
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• v.1 no.2
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• pp.147-163
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• 2013

The world faces several issues of energy crisis and environmental deterioration due to over-dependence on single source of which is fossil fuel. Though, fuel is needed as ingredients for industrial development and growth of any country, however the fossil fuel which is a major source of energy for this purpose has always been terrifying thus the need for alternative and renewable energy sources. The search for alternative energy sources resulted into the acceptance of a biofuel as a reliable alternative energy source. This work presents the study of optimization of process of transesterification of vegetable oil to biodiesel using NaOH as catalyst. A $2^4$ factorial design method was employed to investigate the influence of ratio of oil to methanol, temperature, NaOH concentration, and transesterification time on the yield of biodiesel from vegetable oil. Low and high levels of the key factors considered were 4:1 and 6:1 mole ratio, 30 and $60^{\circ}C$ temperatures, 0.5 and 1.0 wt% catalyst concentration, and 30 and 60 min reaction time. Results obtained revealed that oil to methanol molar ratio of 6:1, tranesetrification temperature of $60^{\circ}C$, catalyst concentration of 1.0wt % and reaction time of 30 min are the best operating conditions for the optimum yield of biofuel from vegetable oil, with optimum yield of 95.8%. Results obtained on the characterizzation of the produced biodiesel indicate that the specific gravity, cloud point, flash point, sulphur content, viscosity, diesel index, centane number, acid value, free glycerine, total glycerine and total recovery are 0.8899, 4, 13, 0.0087%, 4.83, 25, 54.6. 0.228mgKOH/g, 0.018, 0.23% and 96% respectively. Results also indicate that the qualities of the biodiesel tested for are in conformity with the set standard. A model equation was developed based on the results obtained using a statistical tool. Analysis of variance (ANOVA) of data shows that mole ratio of ground nut oil to methanol and transesterification time have the most pronounced effect on the biodiesel yield with contributions of 55.06% and 9.22% respectively. It can be inferred from the results various conducted that vegetable oil locally produced from groundnut oil can be utilized as a feedstock for biodiesel production.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.849-858
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• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.155-168
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• 2020

Open source is a key growth engine of the 4th industrial revolution, and the continuous development and use of various algorithms for image processing is expected. The purpose of this study is to examine the effectiveness of the UAS image processing open source based algorithm by comparing and analyzing the water reproduction and moving object filtering function and the time required for data processing in 3D reproduction. Five matching algorithms were compared based on recall and processing speed through the 'ANN-Benchmarks' program, and HNSW (Hierarchical Navigable Small World) matching algorithm was judged to be the best. Based on this, 108 algorithms for image processing were constructed by combining each methods of triangulation, point cloud data densification, and surface generation. In addition, the 3D reproduction and data processing time of 108 algorithms for image processing were studied for UAS (Unmanned Aerial System) images of a park adjacent to the sea, and compared and analyzed with the commercial image processing software 'Pix4D Mapper'. As a result of the study, the algorithms that are good in terms of reproducing water and filtering functions of moving objects during 3D reproduction were specified, respectively, and the algorithm with the lowest required time was selected, and the effectiveness of the algorithm was verified by comparing it with the result of 'Pix4D Mapper'.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.121-130
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• 2007

in a software development, the design or architecture prior to implementing the software is essential for the success. This paper presents a case that we successfully designed a software architecture of radiation monitoring system (RMS) for HANARO research reactor currently operating in KAERI by applying the quality attribute-driven design method which is modified from the attribute-driven design (ADD) introduced by Bass[1]. The quality attribute-driven design method consists of following procedures: eliciting functionality and quality requirements of system as architecture drivers, selecting tactics to satisfy the drivers, determining architectures based on the tactics, and implementing and validating the architectures. The availability, maintainability, and interchangeability were elicited as duality requirements, hot-standby dual servers and weak-coupled modulization were selected as tactics, and client-server structure and object-oriented data processing structure were determined at architectures for the RMS. The architecture was implemented using Adroit which is a commercial off-the-shelf software tool and was validated based on performing the function-oriented testing. We found that the design method in this paper is an efficient method for a project which has constraints such as low budget and short period of development time. The architecture will be reused for the development of other RMS in KAERI. Further works are necessary to quantitatively evaluate the architecture.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.525-531
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• 2015

According to the increasing demand for 3D indoor spatial information, the utilization of a terrestrial laser scanner comes to the fore. However, the research for the comparison between a terrestrial laser scanning method and a traditional surveying method is insufficient. The paper evaluated the time-efficiency and the locational accuracy of an AMCW type and a direct TOF type of terrestrial laser scanning methods in comparison with the observation using a total station. As a result, an AMCW type showed higher time-efficiency than a direct TOF type and the RMSE between the two types of data was ${\pm}1mm$. Moreover, the terrestrial laser scanning method showed twice higher time-efficiency than the observation using a total station and the RMSE between the two data was ${\pm}3.4cm$. The results indicate that the terrestrial laser scanning method has better profitability and performance for 3D indoor modeling than the traditional survey using a total station. In the future, a terrestrial laser scanner can be efficiently utilized in the construction of 3D indoor spatial information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.587-598
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• 2021

This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.314-328
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• 2023

In this paper, we propose a texture map compression method based on the hierarchical coding method of SHVC to support the scalability function of dynamic mesh compression. The proposed method effectively eliminates the redundancy of multiple-resolution texture maps by downsampling a high-resolution texture map to generate multiple-resolution texture maps and encoding them with SHVC. The dynamic mesh decoder supports the scalability of mesh data by decoding a texture map having an appropriate resolution according to receiver performance and network environment. To evaluate the performance of the proposed method, the proposed method is applied to V-DMC (Video-based Dynamic Mesh Coding) reference software, TMMv1.0, and the performance of the scalable encoder/decoder proposed in this paper and TMMv1.0-based simulcast method is compared. As a result of experiments, the proposed method effectively improves in performance the average of -7.7% and -5.7% in terms of point cloud-based BD-rate (Luma PSNR) in AI and LD conditions compared to the simulcast method, confirming that it is possible to effectively support the texture map scalability of dynamic mesh data through the proposed method.

• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.149-161
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• 2019

At present, we are at the point of change of the 4th industrial revolution era due to the development of artificial intelligence(AI) and rapid technological innovation that no one can predict until now. This study started from the question of 'What role should home economics education play in the era of the Fourth Industrial Revolution?'. The Fourth Industrial Revolution is characterized by AI, cloud computing, Internet of Things(IoT), big data, and Online to Offline(O2O). It will drastically change the social system, science and technology and the structure of the profession. Since the dehumanization of robots and artificial intelligence may occur, the 4th Industrial Revolution Education should be sought to foster future human resources with humanity and citizenship for the future community. In addition, the implication of education in the fourth industrial revolution, which will bring about a change to a super-intelligent and hyper-connected society, is that the role of education should be emphasized so that humans internalize their values as human beings. Character education should be established as a generalized and internalized consciousness with a concept established in the integration of the curriculum, and concrete practical strategies should be prepared. In conclusion, home economics education in the 4th industrial revolution era should play a leading role in the central role of character education, and intrinsic improvement of various human lives. The fourth industrial revolution will change not only what we do, or human mental and physical activities, but also who we are, or human identity. In the information society and digital society, it is important how quickly and accurately it is possible to acquire scattered knowledge. In the information society, it is required to learn how to use knowledge for human beings in rapid change. As such, the fourth industrial revolution seeks to lead the family, organization, and community positively by influencing the systems that shape our lives. Home economics education should take the lead in this role.