• The korean journal of orthodontics
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• v.44 no.1
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• pp.13-19
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• 2014

Objective: The aim of this study was to evaluate long-term changes in the pharyngeal airway dimensions after functional appliance treatment in adolescents with skeletal Class II malocclusions. Methods: Pharyngeal airway dimensions were compared between subjects with skeletal Class II malocclusions (n = 24; mean age: $11.6{\pm}1.29$ years) treated with a Class II bionator and age-matched control subjects with skeletal Class I occlusions (n = 24; mean age: $11.0{\pm}1.21$ years) using a series of lateral cephalograms obtained at the initial visit (T0), after treatment (T1), and at the completion of growth (T2). Results: The length of the nasopharyngeal region was similar between adolescents with skeletal Class I and Class II malocclusions at all time points, while the lengths of the upper and lower oropharyngeal regions and the pharyngeal airway areas were significantly smaller in the skeletal Class II adolescents before treatment when compared to the control adolescents (p < 0.05). However, following treatment with a functional appliance, the skeletal Class II adolescents had increased pharyngeal airway dimensions, which became similar to those of the control subjects. Conclusions: Functional appliance therapy can increase the pharyngeal airway dimensions in growing adolescents with skeletal Class II malocclusions, and this effect is maintained until the completion of growth.

• Journal of Technologic Dentistry
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• v.43 no.4
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• pp.186-193
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• 2021

Purpose: The purpose of the study was to determine the general characteristics of students in dental technology departments; the correlations among their immersion in learning, class satisfaction, and academic achievement; factors influencing online learning experience; ways to improve students' class satisfaction; and basic data for designing effective online courses. Methods: A total of 300 questionnaires were produced and distributed to dental technology students from September 29 through October 8, 2020. The outcome was analyzed using IBM SPSS Statistics ver. 25.0. A significance level of α=0.05 was used for reliable verification. Results: Immersion in learning, class satisfaction, and academic achievement were relatively high among students who studied on a regular basis, and class satisfaction and academic achievement were relatively high among students who studied with almost no interruption. Concerning the correlations between academic achievement, immersion in learning, and class satisfaction in online learning, the correlation between academic achievement and class satisfaction was the highest at r=0.862. Class satisfaction was the largest factor that influenced academic achievement, and the higher students' immersion in learning and class satisfaction were, the higher their academic achievement was. Conclusion: The research is a case study that investigated the general characteristics of dental technology department students and the correlations among their immersion in learning, class satisfaction, and academic achievement. The study outcome could be used in determining factors that influence online learning and designing effective online courses that improve learner satisfaction.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.85-89
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• 2011

In this paper, a novel Class-E power amplifier using metamaterials has been realized with one RF LDMOS diffusion metal-oxide-semiconductor field effect transistor. The CRLH structure can lead to metamaterial transmission line with the Class-E power amplifier tuning capability. The CRLH TL is achieved by the frequency offset and the nonlinear phase slope of the CRLH TL for the matching network of the power amplifier. Also, the proposed power amplifier has been realized by using the CRLH structure in the output matching network for better efficiency. Operating frequencies are chosen at 13.56 MHz in this work. The measured results show that the output power of 39.83 dBm and the gain of 11.83dB was obtained. At this point, we have obtained the power-added efficiency (PAE) of 73 % at operation frequency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1A
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• pp.30-37
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• 2006

In this paper, we propose a QoS-aware efficient bandwidth re-provisioning scheme in a next generation wireless packet transport network. At the transport network layer, it classifies the traffic of the radio network layer into a real time class and a non-real time class. Using an auto-regressive time-series model and a given packet loss probability, our scheme predicts the needed bandwidth of the non-real time class at every re-provisioning interval. Our scheme increases the system capacity by releasing the unutilized bandwidth of the non-real time traffic class for the real-time traffic class while insuring a controllable upper bound on the packet loss probability of a non-real time traffic class. Through empirical evaluations using the real Internet traffic traces, our scheme is validated that it can increase the bandwidth efficiency while guaranteeing the quality of service requirements of the non-real time traffic class.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.309-320
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• 2007

The data imbalance problem which can be uncounted in data mining classification problems typically means that there are more or less instances in a class than those in other classes. It causes low prediction accuracy of the minority class because classifiers tend to assign instances to major classes and ignore the minor class to reduce overall misclassification rate. In order to solve the data imbalance problem, there has been proposed a number of techniques based on resampling with replacement, adjusting decision thresholds, and adjusting the cost of the different classes. In this paper, we study the feasibility of the combination usage of the techniques previously proposed to deal with the data imbalance problem, and suggest a combination method using genetic algorithm to find the optimal combination ratio of the techniques. To improve the prediction accuracy of a minority class, we determine the combination ratio based on the F-value of the minority class as the fitness function of genetic algorithm. To compare the performance with those of single techniques and the matrix-style combination of random percentage, we performed experiments using four public datasets which has been generally used to compare the performance of methods for the data imbalance problem. From the results of experiments, we can find the usefulness of the proposed method.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.143-152
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• 2004

Recently, software programming method based on EJB for object oriented software design and implement has been used frequently. Usually, case that use permanent data that use Database in EJB base application is most. Part connected with Database-Access that take charge in Entity Bean class of server side creation program. In this paper using J2EE relationship DAO pattern class each separate. This is no much difference with existent pattern method, but in same pattern common classes are designed so that composition may be possible. And as well as use Entity Bean class that created each DBMS classes are different, is doing Rata Source so that connection work is available without alteration or creation of additional program in several DBMS environments.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.97.2-97.2
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• 2014

In this paper, we study the stability and dynamics of a magnetic field producing the M6.6 class solar flare taking place in NOAA active region (AR) 11158 on 2011 February 13th. Toriumi et. al. (2013) recently suggest that a fine scale magnetic structure on the photosphere gives a major possibility to produce the M6.6 class flare. On the other hand, they don't discuss the torus instability as a plausible mechanism even though Zhao et. al. (2014) and Janvier et. al. (2014) suspect it as the trigger mechanism of X2.2 class flare taking place later in the same AR. We are the first to investigate the stability of a nonlinear force-free field (NLFFF) prior to the M6.6 class flare against the torus instability by using analytical and numerical approaches. Consequently, we found that our NLFFF is quite stable against small perturbation. This result supports that the flare is triggered by the photospheric motion suggested by Toriumi et. al. (2013). We further perform another MHD simulation with an anomalous resistivity using the NLFFF as an initial condition. As a result, we found the eruption of strongly twisted lines. We compare our simulation results with observations and discuss relevant dynamics in detail.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.464-467
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• 1996

This paper aims to exploit inter/intra-speaker phoneme sub-class variations as criteria for adaptation in a phoneme recognition system based on a novel neural network architecture. Using a subcluster neural network design based on the One-Class-in-One-Network (OCON) feed forward subnets, similar to those proposed by Kung (2) and Jou (1), joined by a common front-end layer. the idea is to adapt only the neurons within the common front-end layer of the network. Consequently resulting in an adaptation which can be concentrated primarily on the speakers vocal characteristics. Since the adaptation occurs in an area common to all classes, convergence on a single class will improve the recognition of the remaining classes in the network. Results show that adaptation towards a phoneme, in the vowel sub-class, for speakers MDABO and MWBTO Improve the recognition of remaining vowel sub-class phonemes from the same speaker

• Journal of The Korean Association of Information Education
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• v.18 no.3
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• pp.381-390
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• 2014

It is a general tendency that a traditional class management system is operated by teachers' arbitrary decision. However, at the present day, it is needed that both students and teachers make an autonomy standard manual and manage the class by themselves in order to cultivate the qualified democratic citizen. Therefore existing class management systems do not meet present classes with diversity. In this paper, we design a new web application framework using REDIS(Remote Dictionary System) for class management. REDIS is a kind of data repository to store various key values and also generally provides a solution of developing web applications with shared memories. We designed a web application framework to maximize both convenience of use and accessibility. The scalability of the class management system can be effectively enhanced using diverse template functions which are basically provided by the framework.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.33-38
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• 2018

In this study, we try to detect new attacks for vehicle by learning only one class. We use Car-Hacking dataset, an intrusion detection dataset, which is used to evaluate classification performance. The dataset are created by logging CAN (Controller Area Network) traffic through OBD-II port from a real vehicle. The dataset have four attack types. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve high efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data, which are new attacks. In this study, we use one class classifier to detect new attacks that are difficult to detect using signature-based rules on network intrusion detection system. The proposed method suggests a combination of parameters that detect all new attacks and show efficient classification performance for normal dataset.