• Korean Journal of Applied Biomechanics
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• v.33 no.2
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• pp.73-83
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• 2023

Objective: Adolescent idiopathic scoliosis patients make up 40% of all scoliosis patients, and it is likely to increase even more because of the increase in sitting times due to the pandemic. Method: The subject of this study was a 16-year-old female student. The Cobb's Angle at initial value was 42° at the thoracic and 33° at the lumbar. The subject's height was 161.6 cm, and the type of scoliosis was 3CL. The brace was built with fabric materials with the size information from the X-ray information and actual measurements. The brace was made for the adolescents to wear for a longer time by making them put pressure on the same pressure points of the existing braces. The subjects were required to wear the device for 16 hours every day for three months. Additional features to check the pressure and time were synchronized through an app for easier communication and management with the responsible investigator. Results: After wearing the 3D Fabric brace, Cobb's angle changed from 42° to 33° at the thoracic and 33° to 23° at the lumbar. The ATR changed from 9° to 8° at the thoracic and 11° to 6° at the lumbar. As a result, the changes in the ATR angle do relate to the decrease of Cobb's angle, which made the angle of scoliosis that is bent in a three-dimensional way improve, making the height of the subject increase from 161.6 cm to 163.5 cm. Conclusion: Through this study, developing a brace that is made in the form of the 3CL to align the strap direction and putting pressure on the proper pressure points makes Cobb's angle and the ATR smaller. This means that there is a positive effect on the changes in height. A brace made of light fabric material is a good brace to help treat adolescent idiopathic scoliosis. There was an opinion that it is more comfortable to wear than existing braces, but it seems necessary to conduct a quantitative study about the before and after of wearing the brace and a survey for Korean specific cases.

• Implantology
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• v.18 no.2
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• pp.120-138
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• 2014

Purpose: The purpose of this study was to review the outcomes of a series of studies on tissue regeneration conducted in multiple institutions including the Department of Periodontology, College of Dentistry, Yonsei University. Materials and Methods: Studies were performed divided into the following three subjects; 1) Development of three-dimensional nano-hydroxyapatite (n-HA) scaffold for facilitating drug release and cell adhesion. 2) Synergistic effects of bone marrow-derived mesenchymal stem cells (BMMSC) application simultaneously with platelet-rich plasma (PRP) on HA scaffolds. 3) The efficacy of silk scaffolds coated with n-HA. Also, all results were analyzed by subjects. Results: Hollow hydroxyapatite spherical granules were found to be a useful tool for the drug release and avidin-biotin binding system for cell attachment. Also, BMMSC simultaneously with PRP applied in an animal bone defect model was seen to be more synergistic than in the control group. But, the efficacy of periodontal ligament cells and dental pulp cells with silk scaffolds could not be confirmed in the initial phase of bone healing. Conclusion: The ideal combination of three elements of tissue engineering-scaffolds, cells and signaling molecules could be substantiated due to further investigations with the potentials and limitations of the suggested list of studies.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.635-652
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• 2023

This study conducts a comprehensive analysis of the curricular progression of the concepts and learning sequences of 'lines', specifically, 'line segments', 'straight lines', and 'rays', at the elementary school level. By examining mathematics curricula and textbooks, spanning from 2nd to 7th and 2007, 2009, 2015, and up to 2022 revised version, the study investigates the timing and methods of introducing these essential geometric concepts. It also explores the sequential delivery of instruction and the key focal points of pedagogy. Through the analysis of shifts in the timing and definitions, it becomes evident that these concepts of lines have predominantly been integrated as integral components of two-dimensional plane figures. This includes their role in defining the sides of polygons and the angles formed by lines. This perspective underscores the importance of providing ample opportunities for students to explore these basic geometric entities. Furthermore, the definitions of line segments, straight lines, and rays, their interrelations with points, and the relationships established between different types of lines significantly influence the development of these core concepts. Lastly, the study emphasizes the significance of introducing fundamental mathematical concepts, such as the notion of straight lines as the shortest distance in line segments and the concept of lines extending infinitely (infiniteness) in straight lines and rays. These ideas serve as foundational elements of mathematical thinking, emphasizing the necessity for students to grasp concretely these concepts through visualization and experiences in their daily surroundings. This progression aligns with a shift towards the comprehension of Euclidean geometry. This research suggests a comprehensive reassessment of how line concepts are introduced and taught, with a particular focus on connecting real-life exploratory experiences to the foundational principles of geometry, thereby enhancing the quality of mathematics education.

• Membrane Journal
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• v.33 no.6
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• pp.325-343
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• 2023

Direct methanol fuel cells (DMFCs) have been attracting attention as energy conversion devices that can directly supply methanol liquid fuel without a fuel reforming process. The commercial polymer electrolyte membranes (PEMs) currently applied to DMFC are perfluorosulfonic acid ionomer-based PEMs, which exhibit high proton conductivity and physicochemical stability during the operation. However, problems such as high methanol permeability and environmental pollutants generated during decomposition require the development of PEMs for DMFCs using novel ionomers. Recently, studies have been reported to develop PEMs using hydrocarbon-based ionomers that exhibit low fuel permeability and high physicochemical stability. This review introduces the following studies on hydrocarbon-based PEMs for DMFC applications: 1) synthesis of grafting copolymers that exhibit distinct hydrophilic/hydrophobic phase-separated structure to improve both proton conductivity and methanol selectivity, 2) introduction of cross-linked structure during PEM fabrication to reduce the methanol permeability and improve dimensional stability, and 3) incorporation of organic/inorganic composites or reinforcing substrates to develop reinforced composite membranes showing improved PEM performances and durability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.315-324
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• 2023

In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.354-361
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• 2023

Big data analysis systems apply NoSQL databases like MongoDB to store, process, and analyze diverse forms of large-scale data. MongoDB offers scalability and fast data processing speeds through distributed processing and data replication, depending on its configuration. This paper investigates the suitable MongoDB environment configurations for implementing big data analysis systems. For performance evaluation, we configured both single-node and multi-node environments. In the multi-node setup, we expanded the number of data nodes from two to three and measured the performance in each environment. According to the analysis, the processing speeds for complex data structures with three or more dimensions are approximately 5.75% faster in the single-node environment compared to an environment with two data nodes. However, a setting with three data nodes processes data about 25.15% faster than the single-node environment. On the other hand, for simple one-dimensional data structures, the multi-node environment processes data approximately 28.63% faster than the single-node environment. Further research is needed to practically validate these findings with diverse data structures and large volumes of data.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.

• Journal of The Korean Association For Science Education
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• v.27 no.7
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• pp.645-662
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• 2007

The purpose of this study was to explore the manners in which models are used in secondary science classrooms. A total of thirteen video-recordings of science lessons dealing with the domains of atmospheric and oceanic earth sciences and their verbatim transcripts were analysed both quantitatively and qualitatively. Interviews with three inservice science teachers were also conducted. Six interrelated assertions were generated as the result of the study: 1) The most frequently used models in secondary earth science classrooms include two-dimensional pictorial, symbolic, iconic, and diagrammatic ones; 2) Science teachers employ models as a mode of representation to make the subject matter available to students; 3) In earth science classrooms, teachers use typical forms of models in intensive manners; 4) Students themselves deal with models on a few occasions, but they just follow similar procedures with the same models; 5) Teachers talk rarely about the nature of scientific models and provide few opportunities for students to think about it; and, 6) Teachers in practice think that the value of using models should be appraised in consideration of the pedagogical intentions of the teacher. Implications for science education and science education research were discussed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.3
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• pp.252-259
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• 2008

The deep-sea mining system is generally composed of surface vessel, lifting system, buffer, flexible pipe and miner. The mining system can be regarded as a large-scale system in which each subsystem is interconnected to other ones. In order to control a large-scale system, decentralized control approaches have been proposed recently. In this paper, as a basic study on application of decentralized control, firstly, the mining system was modeled in a simplified way. Lifting system and buffer were regarded as a spherical pendulum and the flexible pipe was taken as a two-dimensional linear spring connection. Based on the simplified model dynamics, the mining system can be decentralized two subsystems, the one consisting of surface vessel, lifting system and buffer, and the other, the miner. Next, this paper proposed the design of controller for each decentralized subsystem by regarding the interacting terms as disturbances. The controllers kept the constant distance between two subsystems during the miner was moving on the specified track. Finally, the efficiency of proposed controller was proven through the numerical simulation of the derived model.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.209-224
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• 2024

Speaker verification is becoming popular as a method of non-face-to-face identity authentication. It involves determining whether two voice data belong to the same speaker. In cases where the criminal's voice remains at the crime scene, it is vital to establish a speaker verification system that can accurately compare the two voice evidence. In this study, to achieve this, a new speaker verification system was built using a deep learning model for Korean language. High-dimensional voice data with a high variability like background noise made it necessary to use deep learning-based methods for speaker matching. To construct the matching algorithm, the ECAPA-TDNN model, known as the most famous deep learning system for speaker verification, was selected. A large dataset of the voice data, Voxceleb, collected from people of various nationalities without Korean. To study the appropriate form of datasets necessary for learning the Korean language, experiments were carried out to find out how Korean voice data affects the matching performance. The results showed that when comparing models learned only with Voxceleb and models learned with datasets combining Voxceleb and Korean datasets to maximize language and speaker diversity, the performance of learning data, including Korean, is improved for all test sets.