• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.19-26
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• 2021

The lattice structure is attracting attention from industry because of its excellent strength and stiffness, ultra-lightweight, and energy absorption capability. Despite these advantages, widespread commercialization is limited by the difficult manufacturing processes for complex shapes. Additive manufacturing is attracting attention as an optimal technology for manufacturing lattice structures as a technology capable of fabricating complex geometric shapes. In this study, a unit cell was formed using a three-dimensional coordinate method. The relative density relational equation according to the boundary box size and strut radius of the unit cell was derived. Simple cubic (SC), body-centered cubic (BCC), and face-centered cubic (FCC) with a controlled relative density were designed using modeling software. The accuracy of the equations for calculating the relative density proposed in this study secured 98.3%, 98.6%, and 96.2% reliability in SC, BCC, and FCC, respectively. A simulation of the lattice structure revealed an increase in compressive yield load with increasing relative density under the same cell arrangement condition. The compressive yield load decreased in the order of SC, BCC, and FCC under the same arrangement conditions. Finally, structural optimization for the compressive load of a 20 mm × 20 mm × 20 mm structure was possible by configuring the SC unit cells in a 3 × 3 × 3 array.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.203-209
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• 2021

In this study, a prototype design model was proposed for developing an online recruitment system through multi-dimensional data crawling and social media analysis, and validates text information and video interview in job application process. This study includes a comparative analysis process through text mining to verify the authenticity of job application paperwork and to effectively hire and allocate workers based on the potential job capability. Based on the prototype system, we conducted performance tests and analyzed the result for key performance indicators such as text mining accuracy and interview STT(speech to text) function recognition rate. If commercialized based on design specifications and prototype development results derived from this study, it may be expected to be utilized as the intelligent online recruitment system technology required in the public and private recruitment markets in the future.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.305-312
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• 2021

Even though various types of sensors are being used for security applications, radar sensors are being suggested as an alternative due to the privacy issues. Among those radar sensors, PD radar has high-complexity receiver, but, FMCW radar requires fewer resources. However, FMCW has disadvantage from the use of 2D-FFT which increases the complexity, and it is difficult to distinguish people from objects those are stationary. In this paper, we present the design and the implementation results of the radar signal processor (RSP) that can distinguish between people and object by respiration measurement using phase estimation without 2D-FFT. The proposed RSP is designed with Verilog-HDL and is implemented on FPGA device. It was confirmed that the proposed RSP includes 6,425 LUT, 4,243 register, and 12,288 memory bits with 92.1% accuracy for target's breathing status.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.145-166
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• 2021

The study was aimed at verifying the effectiveness of Book-Coding reading education as a reader activity of older elementary school children at a time when high-dimensional thinking abilities were formed. To this end, 30 fifth-grade children of N Elementary School in N-si, Gyeonggi-do, comprised of 15 students from a reading education program using Book-Coding, and 15 students from a reading comprehension program, and applied the reading education program over a total of 12 sessions. The main results of the study are summarized as follows. First, when the effects of the convergence reading education program using Book-Coding on the logical thinking ability of the students in the upper grades in the elementary school were analyzed, all the six sub-factors of logical thinking ability, that is, conservation logic, proportional logic, variable controlling logic, probabilistic logic, correlational inference logic, and combinational logic, were proved to have statistically more meaningful difference than the group writing a book report. Second, the analysis result of the influence of the convergence reading education program using Book-Coding on the creativity of the students in the upper grades of the elementary school showed that all the 13 elements of curiosity, persistence, effectiveness, independence, adventurousness, openness, knowledge, imagination, originality, sensitivity, fluency, flexibility, and accuracy were statistically meaningfully different compared to the book report group. Third, when it was analyzed how the convergence reading education program using Book-Coding affected the creative personality of the elementary school students, all the six factors of curiosity, task commitment, independence, awareness of risk, and openness of thinking, and aesthetics were found out to have a statistically more meaningful difference than the group that wrote a book report.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.2
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• pp.222-230
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• 2022

Digital technology is gradually expanding its field and has a great influence on various fields of dentistry. Recently in digital dentistry, the importance of superimposing various 3-dimensional (3D) image data is emerging, in order to utilize gathered data effectively for diagnosis and prosthesis fabrication. Integrating data from facial scans, intraoral scans, and mandibular movement recordings can create a virtual patient. A virtual patient is formed by integrating digital 3D diagnostic data such as intraoral and extraoral soft tissues, residual dentition, and dynamic occlusion, and the results of prosthetic treatment can be evaluated virtually. The patients in this case report were a 37-year-old female whose chief complaint is that the appearance of the existing prosthesis was distorted and a 55-year-old female patient whose anterior prosthesis needed to be refabricated after the endodontic treatment. 3D facial scans were obtained from each patient, and the patient's mandibular movements were recorded using ARCUS Digma 2 (KaVo Dental GmbH, Biberach an der Riss, Germany). The collected data were integrated on computer-aided design (CAD) software (Exocad dental CAD; exocad GmbH, Darmstadt, Germany) and transferred to a virtual articulator to create a digital virtual patient. The temporary fixed prostheses were designed, restored, and evaluated, and it was reflected into the final restorations. With the aid of the virtual dental patient, accuracy and predictability could be increased throughout treatment, simplifying the occlusal adjustment and clinical evaluation with improved esthetic outcomes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.621-628
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• 2021

This paper proposes a method to calibrate a thermal camera with three different perspectives. In particular, the intrinsic parameters of the camera and re-projection errors were provided to quantify the accuracy of the calibration result. Three lenses of the camera capture the same image, but they are not overlapped, and the image resolution is worse than the one captured by the RGB camera. In computer vision, camera calibration is one of the most important and fundamental tasks to calculate the distance between camera (s) and a target object or the three-dimensional (3D) coordinates of a point in a 3D object. Once calibration is complete, the intrinsic and the extrinsic parameters of the camera(s) are provided. The intrinsic parameters are composed of the focal length, skewness factor, and principal points, and the extrinsic parameters are composed of the relative rotation and translation of the camera(s). This study estimated the intrinsic parameters of thermal cameras that have three lenses of different perspectives. In particular, image enhancement based on a deep learning algorithm was carried out to improve the quality of the calibration results. Experimental results are provided to substantiate the proposed method.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.933-942
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• 2021

The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in the surface image velocimetry. Among them the spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity for a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analyzing time so much. It, however, has a little drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it may cause singnificant error in velocity. The present study aims to propose a new method to find out the main flow direction by using a fast Fourier transform(FFT) to a spatio-temporal (image) volume, which were constructed by accumulating the river surface images along the time direction. The method consists of two steps; the first step for finding main flow direction in space image and the second step for calculating the velocity magnitude in main flow direction in spatio-temporal image. In the first step a time-accumulated image was made from the spatio-temporal volume along the time direction. We analyzed this time-accumulated image by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image in main flow direction was extracted from the spatio-temporal volume. Once again, the spatio-temporal image was analyzed by FFT and velocity magnitudes were calculated from the transformed image. The proposed method was applied to a series of artificial images for error analysis. It was shown that the proposed method could analyze two-dimensional flow field with fairly good accuracy.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.30 no.2
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• pp.71-90
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• 2021

The virtual patient dataset is a collection of diagnostic data from various sources acquired from a single patient into a coordinate system of three-dimensional visualization. Virtual patient dataset makes it possible to establish a treatment plan, simulate various treatment procedures, and create a treatment planning delivery device. Clinicians can design and simulate a patient's smile on the virtual patient dataset and select the optimal result from the diagnostic process. The selected treatment plan can be delivered identically to the patient using manufacturing techniques such as 3D printing, milling, and injection molding. The delivery of this treatment plan can be linked to the final prosthesis through mockup confirmation through provisional restoration fabrication and delivery in the patient's mouth. In this way, if the diagnostic data superimposition and processing accuracy during the manufacturing process are guaranteed, 3D digital smile design simulated in 3D visualization can be accurately delivered to the real patient. As a clinical application method of the virtual patient dataset, we suggest a decision-making method that can exclude occlusal adjustment treatment from the treatment plan through the digital occlusal pressure analysis. A comparative analysis of whole-body scans before and after temporomandibular joint treatment was suggested for adolescent idiopathic scoliosis patients with temporomandibular joint disease. Occlusal plane and smile aesthetic analysis based on the virtual patient dataset was presented when treating patients with complete dentures.