• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.6
• /
• pp.243-250
• /
• 2021

With the increased development of 3D VR applications augmented by recent VR/AR/MR technologies and by the advance of 3D devices, interchangeability and portability of 3D data have become essential. 3D files should be processed in a standard data format for common usage between applications. Providing standardized libraries and data structures along with the standard file format means that a more efficient system organization is possible and unnecessary processing due to the usage of different file formats and data structures depending on the applications can be omitted. In order to provide the function of using a common data file and data structure, this research is intended to provide a programming binding tool for generating and storing standardized data so that various services can be developed by accessing the common 3D files. To achieve this, this paper defines a common data structure including classes and functions to access X3D files with a standardized scheme using the Python programming language. It describes the implementation of a Python language binding viewer, which is an X3D VR viewer for rendering standard X3D data files based on the language binding interface. The VR viewer includes Python based 3D scene libraries and a data structure for creation, modification, exchange, and transfer of X3D objects. In addition, the viewer displays X3D objects and processes events using the libraries and data structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.6
• /
• pp.515-523
• /
• 2021

An integrated underground spatial map consists of underground facilities, underground structures, and ground information, and is periodically updated. In this paper, we design and implement a system for detecting and extracting only changed ground objects to shorten the map update speed. To find the changed objects, all the objects are compared, which are included in the newly input map and the reference map in the integrated map. Since the entire process of comparing objects and generating results is classified by function, the implemented system is composed of several modules such as object comparer, changed object detector, history data manager, changed object extractor, changed type classifier, and changed object saver. We use two metrics: detection rate and extraction rate, to evaluate the performance of the system. As a result of applying the system to boreholes, ground wells, soil layers, and rock floors in Pyeongtaek, 100% of inserted, deleted, and updated objects in each layer are detected. In addition, it provides the advantage of ensuring the up-to-dateness of the reference map by downloading it whenever maps are compared. In the future, additional research is needed to confirm the stability and effectiveness of the developed system using various data to apply it to the field.

• Smart Media Journal
• /
• v.11 no.10
• /
• pp.65-75
• /
• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Journal of the Society of Disaster Information
• /
• v.18 no.4
• /
• pp.806-816
• /
• 2022

Purpose: In this study, the luminance measurement analysis results of the smoke generation state are considered for visual signal display light color for real-time escape guidance in the underground common area. Method: We will analyze the scattering characteristics of light in the atmosphere and optical technology based on the visibility theory, and try to classify the elemental technology as a guidance function through a prototype of a visual signal display device for evacuation guidance. Result: In the experiment conducted under the smoke-generating condition, the results were derived with low luminance ratio and good visibility in the order of red, green, and yellow. However, this result is different from general lighting in which color rendering is considered, and is limited to signals for signals and detection. Conclusion: A conclusions were drawn by reflecting both the luminance measurement results in the smoke generation situation and the preference survey results conducted in previous studies for the light color of the visual signal for signal and detection. When events such as smoke occur, it is better to use the escape guidance visual signal in red or green.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.4
• /
• pp.221-232
• /
• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.

• Journal of Korean Elementary Science Education
• /
• v.42 no.3
• /
• pp.434-454
• /
• 2023

This study explored the composition and attributes of modeling instructions and factors of teacher competence in elementary science classes. The study also examined educational research papers regarding modeling instruction cases in elementary schools and elementary teachers' perceptions of modeling instructions using qualitative meta-analysis, which can integrate findings from qualitative research. This investigation led to creating a small group to compose modeling instructions. Furthermore, the modeling approach was demonstrated to go through the process of generating, evaluating, and modifying the model. The attributes of modeling instructions can be divided into factors that affect modeling instructions and competence factors necessary for students participating in modeling instructions. The factors affecting modeling instructions included "small group interactions" and "time limitation in classes." The competence factors necessary for students participating in modeling instructions included "scientific knowledge," "meta-modeling knowledge," and the "ability to control emotions." The teacher competence factors in modeling instructions regarding knowledge, function, and attitude were explored. The teacher competence factors in elementary modeling instructions included "meta-modeling knowledge," "knowledge of modeling assessment," "emotional support for students," and the "awareness of modeling value." Accordingly, this study offered some recommendations for effective modeling instructions.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.10
• /
• pp.97-107
• /
• 2007

Accurate evaluation of the slope stability by assuming failure block as the entire slope is considered to be apposite for the small scale slope, whereas it is not the case for the large scale slope. Hence, appropriate estimation of a failure block size is required since the safety factor and the joint strength parameters are the function of the failure block size. In this paper, the size of failure block was investigated by generating 3-dimensional rock joint system based on statistical data of joints obtained from research slope, such as joint orientation, spacing and 3-dimensional joint intensity. The result indicates that 33 potential failure blocks exist in research slope, as large as 1.4 meters at least and 38.7 meters at most, and average block height is 15.2 meters. In addition, the data obtained from 3 dimensional joint system were directly applicable to the probability analysis and 2 and 3 dimensional discontinuity analysis.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.325-331
• /
• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.51 no.5
• /
• pp.70-83
• /
• 2023

Recently, the Korea Forest Service has implemented a planning project about wind corridor forests as a response measure to climate change. Based on this, research on wind corridors has been underway. For the creation of wind corridor forests, a preliminary evaluation of the wind corridor function is necessary. However, currently, there is no evaluation index to directly evaluate and spatially distinguish the types of wind corridors, and analysis is being performed based on indirect indicators. Therefore, this study proposed a method to evaluate and classify wind corridors by utilizing heat deficit analysis as an evaluation index for cold air generation. Heat deficit was analyzed using a cold air analysis model called Kaltluftabflussmodell_21 (KLAM_21). According to the results of the simulation analysis, the wind path was functionally classified. The top 5% were classified as cold-air generating Areas (CGA), and the bottom 5% as cold-air vulnerable Areas (CVA). In addition, the cold-air flowing Areas (CFA) were classified by identifying the flow of cold air moving from the cold air generation area. It is expected that the methodology of this study can be utilized as an evaluation method for the effectiveness of wind corridors. It is also anticipated to be used as an evaluation index to be presented in the selection of wind corridor forest sites.

• Proceedings of the KSAR Conference
• /
• 2000.10a
• /
• pp.10-12
• /
• 2000

Members of the glycoprotein family, which includes CG, LH, FSH and TSH, comprise two noncovalently linked $\alpha$- and $\beta$-subunits. Equine chorionic gonadotropin (eCG), known as PMSG, has a number of interesting and unique characteristics since it appears to be a single molecule that possesses both LH- and FSH-like activities in other species than the horse. This dual activity of eCG in heterologous species is of fundamental interest to the study of the structure-function relationships of gonadotropins and their receptors. CG and LH $\beta$ genes are different in primates. In horse, however, a single gene encodes both eCG and eLH $\beta$-subunits. The subunit mRNA levels seem to be independently regulated and their imbalance may account for differences in the quantities of $\alpha$ - and $\beta$ -subunits in the placenta and pituitary. The dual activities of eCG could be separated by removal of the N-linked oligosaccharide on the $\alpha$-subunit Asn 56 or CTP-associated O-linked oligosaccharides. The tethered-eCG was. efficiently secreted and showed similar LH-like activity to the dimeric eCG. Interestingly, the FSH-like activity of the tethered-eCG was increased markedly in comparison with the native and wild type eCG. These results also suggest that this molecular can implay particular models of FSH-like activity not LH-like activity in the eCG/indicate that the constructs of tethered molecule will be useful in the study of mutants that affect subunit association and/or secretion. A single-chain analog can also be constructed to include additional hormone-specific bioactive generating potentially efficacious compounds that have only FSH-like activity. The LH/CG receptor (LH/CGR), a membrane glycoprotein that is present on testicular Leydig cells and ovarian theca, granulosa, luteal, and interstitial cells, plays a pivotal role in the regulation of gonadal development and function in males as well as in nonpregnant and pregnant females. The LH/CGR is a member of the family of G protein-coupled receptors and its structure is predicted to consist of a large extracellular domain connected to a bundle of seven membrane-spanning a-helices. The LH/CGR phosphorylation can be induced with a phorbol ester, but not with a calcium ionophore. The truncated form of LHR also was down-regulated normally in response to hCG stimulation. In contrast, the cell lines expressing LHR-t63I or LHR-628, the two phosphorylation-negative receptor mutant, showed a delay in the early phase of hCG-induced desensitization, a complete loss of PMA-induced desensitization, and an increase in the rate of hCG-induced receptor down-regulation. These results clearly show that residues 632-653 in the C-terminal tail of the LHR are involved in PMA-induced desensitization, hCG-induced desensitization, and hCG-induced down-regulation. Recently, constitutively activating mutations of the receptor have been identified that are associated with familial male-precocious puberty. Cells expressing LHR-D556Y bind hCG with normal affinity, exhibit a 25-fold increase in basal cAMP and respond to hCG with a normal increase in cAMP accumulation. This mutation enhances the internalization of the free and agonist-occupied receptors ~2- and ~17-fold, respectively. We conclude that the state of activation of the LHR can modulate its basal and/or agonist-stimulated internalization. Since the internalization of hCG is involved in the termination of hCG actions, we suggest that the lack of responsiveness detected in cells expressing LHR-L435R is due to the fast rate of internalization of the bound hCG. This statement is supported by the finding that hCG responsiveness is restored when the cells are lysed and signal transduction is measured in a subcellular fraction (membranes) that cannot internalize the bound hormone.