• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.365-371
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• 2022

In order to obtain excellent spatial resolution in the PET detector, when the detector module is designed using very small scintillation pixels, overlap occurs at the edges and corners of the scintillation pixel array in the flood image. By using a light guide, the occurrence of overlap can be reduced. In this study, after using a scintillator of 0.8 mm × 0.8 mm × 20 mm to form a 14 × 14 array, 3 mm × 3 mm SiPM pixels are combined with 4 × 4 photosensor to reduce the occurrence of overlap. The optimal thickness of the light guide used for this purpose was derived. Quantitative evaluation was performed based on scintillation pixel images of edges and corners where overlap occurs mainly in the acquired flood image. Quantitative evaluation was calculated through the interval and full width at half maximum between scintillation pixel images, and when a light guide with a thickness of 2 mm was used, the best image was obtained with a k value of 2.60. In addition, as a result of measuring the energy resolution through the energy spectrum, the light guide with a thickness of 2 mm showed the best result at 28.5%. If a 2 mm light guide is used, it is considered that the best flood image and energy resolution with minimal overlap can be obtained.

• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.87-97
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• 2022

Although the use of BIM in architectural projects has increased, repetitive modeling tasks and frequent design errors remain as obstacles to the practical application of BIM. In particular, interior finishing elements include the most varied and detailed requirements, and thus requires improving its modelling efficiency and resolving potential design errors. Recently, visual programming-based modules has gained traction as a way to automate a series of repetitive modeling tasks. However, existing approaches do not adequately reflect the practical modeling needs and focus only on replacing siimple, repetitive tasks. This study developed and evaluated the performance of three modules for automatic detailing of walls, floors and ceilings. The three elements were selected by analyzing the man-hours and the number of errors that typically occur when detailing BIM models. The modules were then applied to automatically detail a sample commercial facility BIM model. Results showed that the implementations met the practical modeling requirements identified by actual modelers of an construction management firm.

• Journal of the Korea Institute of Building Construction
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• v.22 no.4
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• pp.347-358
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• 2022

In order to satisfy the extraction and use of information such as estimates and processes required in the design and construction stages of BIM, which is an expectation of overall construction operation for the design and construction stage of domestic buildings, it is insufficient to supply and apply mobile technologies or terminals. In this paper, standardization of BIM-based processes from the design stage to the construction stage is proposed as an efficient construction system method through mobile-based simulation and test-bed case analysis review. The current status and potential of BIM application were identified through theoretical review of BIM and case studies at home and abroad. In addition, the overall flow of the project and the direction of effective process construction were investigated through each process by 3D, 4D, and 5D execution stage and the role of each collaborator. 4D building process BIM simulation system using mobile was implemented by applying a visualization engine that simulates process information, object information connection module, and related object information. Therefore, it was possible to minimize the possibility of re-construction of the BIM design and construction process model through the visualization of 2D drawings based on the 3D model of the building and the review of errors and interferences in the drawings. In addition, in the implementation of simulation for each process of the construction process through mobile devices, it was possible to support construction progress and process management according to the optimal option selected by the user.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.274-286
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• 2022

Multi-object tracking has been studied for a long time under computer vision and plays a critical role in applications such as autonomous driving and driving assistance. Multi-object tracking techniques generally consist of a detector that detects objects and a tracker that tracks the detected objects. Various publicly available datasets allow us to train a detector model without much effort. However, there are relatively few publicly available datasets for training a tracker model, and configuring own tracker datasets takes a long time compared to configuring detector datasets. Hence, the detector is often developed separately with a tracker module. However, the separated tracker should be adjusted whenever the former detector model is changed. This study proposes a system that can train a model that performs detection and tracking simultaneously using only the detector training datasets. In particular, a Siam network with augmentation is used to compose the detector and tracker. Experiments are conducted on public datasets to verify that the proposed algorithm can formulate a real-time multi-object tracker comparable to the state-of-the-art tracker models.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1513-1513
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• 2001

Present Food Legislation compels dairy industry to carry out analyses in order to guarantee the food safety and quality of products. Furthermore, in many cases industry pays milk according to bacteriological or/and nutritional quality. In order to do these analyses, several expensive instruments are needed (Milkoscan, Fossomatic, Bactoscan). NIRS technology Provides a unique instrument to deal with all analytical requirements. It offers as main advantages its speed and, specially, its versatility, since not only allows determine all the parameters required in milk analysis, but also allows analyse other dairy products, like cheese or whey. The objective of this study is to develop NIRS calibration equations to predict several quality parameters in goat milk, cheese and whey. Three sets of 123 milk samples, 190 cheese samples and 109 whey samples, have been analysed in a FOSS NIR Systems 6500 I spectrophotometer equipped with a spinning module. Milk and whey were analysed by folded transmission, using circular cells with gold surface and pathlength of 0.1 m, while intact cheese was analysed by reflectance using standard circular cells. NIRS calibrations were obtained for the prediction of chemical composition in goat milk, for fat (r$^2$=0.92; SECV=0.20%), total solids (r$^2$=0.95: SECV=0.22%), protein (r$^2$=0.94; SECV=0.07%), casein (r$^2$=0.93; SECV=0.07%) and lactose (r$^2$=0.89; SECV=0.05%). Moreover, equations have been performed to determine somatic cells (r$^2$=0.81; SECV=276.89%) and total bacteria (r$^2$=0.58; SECV=499.32%) counts in goat milk. In the case of cheese, calibrations were obtained for the prediction of fat (r$^2$=0.92; SECV=0.57), total solids (r$^2$=0.80; SECV=0.92%) and protein (r$^2$=0.70; SECV=0.63%). In whey, fat (r$^2$=0.66; SECV=0.08%), total solids (r$^2$=0.67; SECV=0.19%) and protein (r$^2$=0.76; SECV=0.07%) NIRS equations were obtained. These results proved the viability of NIRS technology to predict chemical and microbiological parameters and somatic cells count in goat milk, as well as chemical composition of goat cheese and whey.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.10-17
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• 2023

This paper describes the research and development of a 3.0 m Solar-Powered UAV system for mission flight that is based on the 4.2 m Solar-powered UAV. Both the Solar-Powered UAVs were lightened in weight by applying a composite fuselage and solar charging system. Also, a deep stall landing application and airbag module were installed for usability in mission performance. The flight performance of the Solar-Powered UAV system was verified through flight test. In particular, the 3.0 m Solar-Powered UAV performed continuous flight along the coastline of Jeju Island for 147 km in 3 hours and 50 minutes, and its performance as a mission flight was also confirmed.

• Membrane Journal
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• v.33 no.4
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• pp.222-232
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• 2023

In this study, a hollow fiber support membrane was prepared by a non-solvent induced phase separation (NIPS) method using a polysulfone (PSf). The prepared hollow fiber support membrane was coated with PDMS and Pebax to prepare a hollow fiber composite membrane. The prepared composite membrane was measured for permeance and selectivity for pure CO₂, H₂, O₂ and N₂. Gas separation performance of the module having the highest selectivity (CO₂/H₂) among the prepared composite membrane modules was measured according to the change in stage cut using simulated gas. The composition of the simulated gas used at this time was 70% CO₂ and 30% H₂. In the 1 stage experiment, it was possible to obtain values of about 60% of H₂ concentration and 12% of H₂ recovery. In order to overcome the low H₂ concentration and recovery, 2 stage serial test was performed, and through this, it was possible to achieve 70% H₂ concentration and 70% recovery. Through this, it was possible to derive a separation process configuration for CO₂/H₂ separation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.113-120
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• 2023

This paper introduces a simulation method for the collision between roadblocks and vehicles using LS-DYNA. The need to evaluate the performance of anti-ram barriers to prepare for vehicle impact has increased since vehicle impact threats have been included as a design criterion for nuclear power plants. Anti-ram barriers are typically certified for their performance through collision experiments. However, because Koreas has no performance testing facilities for anti-ram barriers, their performance can only be verified through simulations. LS-DYNA is a specialized program for collision simulation. Various organizations, including NCAC, distributes numerical models that have been validated for their accuracy with collision tests. In this study, we constructed a finite element model of the most critical vehicle barrier module and simulated collision between roadblocks and vehicles. The calculated results were verified by applying the validation criteria for vehicle safety facility collision simulations of NCHRP 179.