• The korean journal of orthodontics
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• v.52 no.4
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• pp.258-267
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• 2022

Objective: This study aimed to evaluate the superimposition accuracy of digital modes for measuring tooth movement in patients requiring anterior retraction after premolar extraction based on the proposed reference regions. Methods: Forty patients treated with bilateral maxillary first premolar extraction were divided into two groups: moderate retraction (< 7.0 mm) and maximum retraction (≥ 7.0 mm). Central incisor displacement was measured using cephalometric superimpositions and three-dimensional (3D) digital superimpositions with the 3rd or 4th ruga as the reference point. The Wilcoxon signed-rank test and linear regression analyses were performed to test the significance of the differences and relationships between the two measurement techniques. Results: In the moderate retraction group, the central incisor anteroposterior displacement values did not differ significantly between 3D digital and cephalometric superimpositions. However, in the maximum-retraction group, significant differences were observed between the anteroposterior displacement evaluated by the 3rd ruga superimposition and cephalometric methods (p < 0.05). Conclusions: This study demonstrated that 3D digital superimpositions were clinically as reliable as cephalometric superimpositions in assessing tooth movements in patients requiring moderate retraction. However, the reference point should be carefully examined in patients who require maximum retraction.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.316-326
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• 2022

The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.119-126
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• 2024

Disease caused by the coronavirus (COVID-19) is sweeping the globe. There are numerous methods for identifying this disease using a chest imaging. Computerized Tomography (CT) chest scans are used in this study to detect COVID-19 disease using a pretrain Convolutional Neural Network (CNN) ResNet50. This model is based on image dataset taken from two hospitals and used to identify Covid-19 illnesses. The pre-train CNN (ResNet50) architecture was used for feature extraction, and then fully connected layers were used for classification, yielding 97%, 96%, 96%, 96% for accuracy, precision, recall, and F1-score, respectively. When combining the feature extraction techniques with the Back Propagation Neural Network (BPNN), it produced accuracy, precision, recall, and F1-scores of 92.5%, 83%, 92%, and 87.3%. In our suggested approach, we use a preprocessing phase to improve accuracy. The image was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, which was followed by cropping the image before feature extraction with ResNet50. Finally, a fully connected layer was added for classification, with results of 99.1%, 98.7%, 99%, 98.8% in terms of accuracy, precision, recall, and F1-score.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.531-544
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• 2005

최근 우리는 인접학문 간 그리고 학계와 산업계 간의 연구협조가 점차 증가하고 있음을 보아오고 있다. 이러한 현상은 특히 학술저널 간 지식의존성을 촉진하는 계기를 제공하고 있다고 할 수 있다. 본 논문의 목적은 관련저널 간 지식상호 의존성을 규명하고 저널지식의 구조화를 위하여 association, 군집화, 링크분석 등 데이터마이닝 기법을 적용하는 방법론을 제시하는 것이다. 제시된 방법을 통하여 기대되는 점들은 1) 논문의 기본속성인 키워드, 저자, 그리고 인용데이터를 통합하는 규칙 집합을 통하여 논문지식검색기능의 향상, 2) 키워드를 기반으로 관련 저널 간 그리고 저널내부의 군집분석으로 지식동향 파악, 3) Kleinberg (1999)의 권위와 허브 개념을 인용데이터 분석에 활용하여 기존의 양적 평가 기준인 영향력 지수 (impact factor)의 문제점을 보완하며, 4) 특정 논문이나 저널의 지식파급과 관련한 영향력을 산출하는 잠재적 지식파급 지수를 제안하는 것이다.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.85-90
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• 2005

In this paper, firstly we report experimental results on applying information extraction (IE) methodology to the task of summarizing clinical trial design information in focus on ‘Compared Treatment’, ‘Endpoint’ and ‘Patient Population’ from clinical trial MEDLINE abstracts. From these results, we have come to see this problem as one that can be decomposed into a sentence classification subtask and an IE subtask. By classifying sentences from clinical trial abstracts and only performing IE on sentences that are most likely to contain relevant information, we hypothesize that the accuracy of information extracted from the abstracts can be increased. As preparation for testing this theory in the next stage, we conducted an experiment applying state-of-the-art sentence classification techniques to the clinical trial abstracts and evaluated its potential in the original task of the summarization of clinical trial design information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.316-321
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• 2005

A new HBT current source model and the corresponding direct parameter extraction methods are presented. Exact analytical expressions for the current source model parameters are derived. This method is applied to scalable modeling of HBT, Some techniques to reduce redundancy of the parameters are introduced. The model based on this method can accurately predict the measured data for the change of ambient temperature, size, and bias.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.79-82
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• 2009

In this paper, we propose new image processing method to detect fire image. At captured image from camera, we using OpenCV library to implement various image processing techniques such like differential image, binarization image, contour extraction, remove noise(morphology open, close), pixel calculation, flickering extraction, etc.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2921-2923
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• 2005

This paper presents to generate 3D building model using estimation of rooftop surface after 3D line segment extraction using hybrid stereo matching techniques in terms of the co-operation of area-based stereo and feature-based stereo. we first performed a junction extraction from 3D line segment data which was obtained by stereo images, and finally generated building's reliable rooftop surface model using LSE(Least Square Error) method after creating surfaces by grouped and fixed junction points. we generated synthetic images for experimentation by photo-realistic simulation on Avenches data set of Ascona aerial images.

• Fibers and Polymers
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• v.7 no.1
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• pp.57-61
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• 2006

A study has been made on the quantification and evaluation of fabric pilling using two-dimensional and three-dimensional hybrid imaging methods. Two-dimensional imaging method was good for some samples while three-dimensional measurement method for others, according to the properties of their base fabric. Various image processing techniques as well as three-dimensional data processing algorithms were applied for the extraction of pills from measured data and a series of shape parameters have been defined for the objective evaluation of fabric pilling. An evaluation criterion that is compatible with the conventional evaluation method has been proposed by applying the new evaluation method to the current photographic standards.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1400-1407
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• 2005

There are a number of approaches to in situ remediation that are used at contaminated sites for removing contaminants from the contaminated zone without excavating the soil. These include soil flushing, dual phase extraction, and soil vapor extraction. Of these techniques, soil flushing is the focus of the investigation in this paper. The concept of using prefabricated vertical drains(PVDs) for remediation of contaminated sites with fine-grained soils is examined. The PVD system is used to shorten the drainage path or the groundwater flow and promote subsurface liquid movement expediting the soil flushing process. The use of PVDs in the current state of practice has been limited to soil improvement. The use of PVDs under vacuum conditions is investigated using sample soil consisting of silty sand.