• 한국학교보건학회지
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• 제36권3호
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• pp.113-125
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• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.169-173
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• 2007

Nowadays the aerial photos is using to get the information around our spatial environment and it increases by geometric progression in many fields. The aerial photos need in a simple object such as cartography and ground covey classification and also in a social objects such as the city plan, environment, disaster, transportation etc. However, the shadow, which includes when taking the aerial photos, makes a trouble to interpret the ground information, and also users, who need the photos in their field tasks, have restriction. This study, for removing the shadow, uses the single image and the image without the source of image and taking situation. Also, this study present clustering algorism based on HIS color model that use Hue, Saturation and Intensity, especially this study used I(intensity) to extract shadow area from image. And finally by filtering in Fourier frequency domain creates the intrinsic image which recovers the 3-D color information and removes the shadow.

• 한국정보통신학회논문지
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• 제16권10호
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• pp.2108-2112
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• 2012

본 논문에서는 정변형을 이용하여 파노라마 영상으로 변환하고 파노라마 영상으로 변환하는 과정에서 손실되는 영상 정보를 복원하기 위하여 양선형 보간법을 적용하여 개선된 파노라마 영상을 획득할 수 있는 방법을 제안한다. 본 논문에서 제안한 어안 렌즈 영상 재구성 방법의 성능을 평가하기 위하여 다양한 어안 렌즈 영상을 대상으로 실험한 결과, 기존의 방법보다 영상을 재구성하는데 효과적인 것을 확인하였다.

• 통상정보연구
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• 제9권3호
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• pp.343-362
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• 2007

Inter-Korean Economic Cooperation needs to a different strategy for developing synergy effects, suggesting they should be selected for role to the unification Korea. In the this paper, Three policy-strategies is suggested as follows. Firstly, Economic Cooperation Driving Committee of Inter-Korean Digital Cultural Content is necessary the recovering of cultual consubstantiality and the operating of business partnership in the divided peninsular. Secondly, To cultural contents cooperation between South-North Korea. the exchange of learning and information must be activated constantly. as the cultural contents is creative industrial, it needs for imagination and creative of human and understanding of a fine arts, a traditional arts. Thirdly, A policy and system is inevitable to construction of Inter Korean Cooperation Digital Contents. South-North Korea, including a North Korea having a excellent cultural heritage, must jointly recovery for cultural contents. Under social-economic system, a consumers of digital contents pay to the format creator many royalty. Therefore, We must prepare to roll out a series of new creative contents, and have competitive advantages in the global market.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.81-84
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• 2000

Digital Halftoning convert a continuous-tone images to a binary images. Inverse halftoning addresses the problem of recovering a continuous image from a halftoned binary image. Simple low pass filtering can remove the high frequency noise but it also removes the edge information. Thus the edge information should be separated from the halftoning noise. As a result, the edge of result image is blurring. This paper present that we obtain continuous-tone-image which using Anisotropic diffusion filter. To reduce noise without blurring the edges of reconstructed image use edge map. The experimental results show that proposed method gives a higher PSNR and better subjective quality than conventional methods. As a result, the edge information of reconstructed image reduce blurring.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.646-654
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• 2019

Image denoising is considered as a key factor for capturing high-quality photos in digital cameras. Thus far, several image denoising methods have been proposed in the past decade. In addition, previous studies either relied on deep learning-based approaches or used the hand-crafted filters. Unfortunately, the previous method mostly emphasized on image denoising regardless of preserving or recovering the detail information in result images. This study proposes an detail extraction network to estimate detail information from a noisy input image. Moreover, the extracted detail information is utilized to enhance the final denoised image. Experimental results demonstrate that the proposed method can outperform the existing works by a subjective measurement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4355-4371
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• 2020

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a stochastic gradient iteration algorithm, which runs in two stages: First, we use a truncated sample stochastic variance reduction algorithm to initialize the objective function. The second stage is the gradient refinement stage, which uses continuous updating of the amplitude-based stochastic weighted gradient algorithm to improve the initial estimate. Because of the stochastic method, each iteration of the two stages of SRPR involves only one equation. Therefore, SRPR is simple, scalable, and fast. Compared with the state-of-the-art phase retrieval algorithm, simulation results show that SRPR has a faster convergence speed and fewer magnitude-only measurements required to reconstruct the signal, under the real- or complex- cases.

• Journal of Information Processing Systems
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• 제18권1호
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• pp.12-25
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• 2022

In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

• 한국정보통신학회논문지
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• 제13권9호
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• pp.1913-1920
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• 2009

본 논문에서는 오류센서 보정 기능을 갖춘 태양광 조명용 정밀 태양 추적제어기 개발에 대하여 기술하였다. 태양 위치에 대한 광역범위 추적과 미소범위에서의 정밀추적 제어를 위하여 대범위 센서군과 소범위 센서군으로 나뉜 센서모듈을 개발하였다. 태양위치의 정밀 추적을 위하여 소범위 센서군의 응답특성을 분석하여 퍼지 제어엔진을 개발하였으며, 주축성분 분석법(Principal Component Analysis)을 적용하여 오류센서의 감별 및 복원을 하였다. 개발된 시스템의 실외 태양추적 실험을 통하여 본 연구의 유용성을 입증하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.269-272
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• 1998

The disks containing all the system software-OS(Operating System), application program, and DB(Data Base)-happen to be broken. This happens not only to general computer systems but also to electronic switching system. In the electronic switching system, this causes the essential data and software needed for operating the system to be damaged and is fatal to services, so that they should be recovered as soon as possible. Especially the data, having the information of subscriber, trunk, prefix, and system configuration should be receovered preferentially. To manage this situation, the system should let the operator know that the data are damaged and recover the damaged data. This paper shows a way of recovering this damaged data, the object data of audit, the structure of DBMS and the implementation of audit in the case of the domestic high capacity electronic switching system, TDX-10A.