• 통합자연과학논문집
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• 제9권2호
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• pp.155-160
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• 2016

Applying image processing techniques to education, the face of the learner is photographed, and expression and movement are detected from video, and the system which estimates degree of concentration of the learner is developed. For one learner, the measuring system is designed in terms of estimating a degree of concentration from direction of line of learner's sight and condition of the eye. In case of multiple learners, it must need to measure each concentration level of all learners in the classroom. But it is inefficient because one camera per each learner is required. In this paper, position in the face region is estimated from video which photographs the learner in the class by the difference between frames within the motion direction. And the system which detects the face direction by the face part detection by template matching is proposed. From the result of the difference between frames in the first image of the video, frontal face detection by Viola-Jones method is performed. Also the direction of the motion which arose in the face region is estimated with the migration length and the face region is tracked. Then the face parts are detected to tracking. Finally, the direction of the face is estimated from the result of face tracking and face parts detection.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.313-315
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• 1997

We developed a new analysis technique for the assessment of irregular vibratory movement of vocal folds. Successive frames of pre-recorded video images from videostroboscopy were transferred to computer memory and a vibratory tract of one selected point was described as a waveform by displaying the same lines of all frames along the y-direction. By applying this technique, irregular vibratory patterns of multiple regions, such as asynchronized registration of glottal cycles, could be easily visualized. It would be possible to monitor and analyze the pathologic changes of vocal fold movement by means of this newly developed system.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2008년도 추계 학술발표회 제20권2호
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• pp.221-224
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• 2008

할선강성을 이용하여 모멘트저항골조의 모멘트재분배를 수행하는 선형해석법을 연구하였다. 제안된 방법에서는 모멘트재분배가 요구되는 부재의 소성힌지에 회전스프링을 모델링한 후, 이 스프링의 할선 강성을 조정하여 비탄성변형으로 인해 저감된 부재의 휨강성을 반영한다. 회전스프링의 할선강성을 조정하여 선형해석한 결과, 해당 부재와 전체 구조물에서 힘의 평형이 만족될 때까지 계산을 반복한다. 할선강성해석을 통해, 소성힌지의 비탄성변형에 의한 하중의 재분배가 고려될 수 있으며, 해당 소성힌지에서의 요구회전변형이 변형능력을 초과하지 않는지 비교함으로써 안전성을 평가할 수 있다. 검증을 위해, 제안된 방법은 기존의 연속보에 대한 실험연구와 비교되었으며, 기존건물의 평가에 적용되었다.

• Journal of Communications and Networks
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• 제13권2호
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• pp.132-141
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• 2011

IEEE 802.15.4 networks are a feasible platform candidate for connecting all health-care-related equipment dispersed across a hospital room to collect critical time-sensitive data about patient health state, such as the heart rate and blood pressure. To meet the quality of service requirements of health-care systems, this paper proposes a multi-priority queue system that differentiates between various types of frames. The effect of the proposed system on the average delay and throughput is explored herein. By employing different contention window parameters, as in IEEE 802.11e, this multi-queue system prioritizes frames on the basis of priority classes. Performance under both saturated and unsaturated traffic conditions was evaluated using a novel analytical model that comprehensively integrates two legacy models for 802.15.4 and 802.11e. To improve the accuracy, our model also accommodates the transmission retries and deferment algorithms that significantly affect the performance of IEEE 802.15.4. The multi-queue scheme is predicted to separate the average delay and throughput of two different classes by up to 48.4% and 46%, respectively, without wasting bandwidth. These outcomes imply that the multi-queue system should be employed in health-care systems for prompt allocation of synchronous channels and faster delivery of urgent information. The simulation results validate these model's predictions with a maximum deviation of 7.6%.

• Earthquakes and Structures
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• 제17권1호
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• pp.63-73
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• 2019

This paper studies damage detection as an optimization problem. A new objective function based on changes in natural frequencies, and Natural Frequency Vector Assurance Criterion (NFVAC) was developed. Due to their easy and fast acquisition, natural frequencies were utilized to detect structural damages. Moreover, they are sensitive to stiffness reduction. The method presented here consists of two stages. Firstly, Finite Element Model (FEM) is updated. Secondly, damage severities and locations are determined. To minimize the proposed objective function, a new bio-inspired optimization algorithm called salp swarm was employed. Efficiency of the method presented here is validated by three experimental examples. The first example relates to three-story shear frame with two single damage cases in the first story. The second relates to a five-story shear frame with single and multiple damage cases in the first and third stories. The last one relates to a large-scale eight-story shear frame with minor damage case in the first and third stories. Moreover, the performance of Salp Swarm Algorithm (SSA) was compared with Particle Swarm Optimization (PSO). The results show that better accuracy is obtained using SSA than using PSO. The obtained results clearly indicate that the proposed method can be used to determine accurately and efficiently both damage location and severity in multi-story shear frames.

• International Journal of Computer Science & Network Security
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• 제22권9호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권3호
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• pp.1058-1070
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• 2014

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

• 산업공학
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• 제25권2호
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• pp.264-275
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• 2012

The process of semiconductor(IC Package) manufacturing usually includes lots of complex and sequential processes. Many kinds of equipments are installed with the mixed concept of serial and parallel manufacturing system. The business environments of the semiconductor industry have been changed frequently, because new technologies are developed continuously. It is the main reason of new investment plan and layout consideration. However, it is difficult to change the layout after installation, because the major equipments are expensive and difficult to move. Furthermore, it is usually a multiple-objective problem. Thus, new investment or layout change should be carefully considered when the production environments likewise product mix and production quantity are changed. This paper introduces a simulation case study of a Korean company that produces packaging substrates(especially lead frames) and requires multi-objective decision support. $QUEST^{(R)}$ is used for simulation modelling and AHP(Analytic Hierarchy Process) and DEA(Data Envelopment Analysis) are used for weighting of qualitative performance measures and solving multiple-objective layout problem, respectively.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.167-177
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• 2019

Even though so much progresses have been achieved in Multiple Object Tracking (MOT), most of reported MOT methods are not still satisfactory for commercial embedded products like Pan-Tilt-Zoom (PTZ) camera. In this paper, we propose a real-time multiple pedestrians tracking method for embedded environments. First, we design a new light weight convolutional neural network(CNN)-based pedestrian detector, which is constructed to detect even small size pedestrians, as well. For further saving of processing time, the designed detector is applied for every other frame, and Kalman filter is employed to predict pedestrians' positions in frames where the designed CNN-based detector is not applied. The pose orientation information is incorporated to enhance object association for tracking pedestrians without further computational cost. Through experiments on Nvidia's embedded computing board, Jetson TX2, it is verified that the designed pedestrian detector detects even small size pedestrians fast and well, compared to many state-of-the-art detectors, and that the proposed tracking method can track pedestrians in real-time and show accuracy performance comparably to performances of many state-of-the-art tracking methods, which do not target for operation in embedded systems.

• 전자공학회논문지
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• 제54권2호
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• pp.123-129
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• 2017

본 논문에서는 이중 마이크로폰 배열을 이용하여 비음수 행렬분해(nonnegative matrix factorization, NMF) 기반으로 다중음원의 도래각을 추정하는 새로운 방법을 제안한다. 우선 이중 마이크로폰 배열에 들어온 음향 신호들을 연속된 분석프레임으로 분할한 후, 각 프레임에 대해 조향응답파워 위상변환(steered-response power phase transform, SRP-PHAT) 빔형성기를 적용하여 스테레오 신호들을 시간-방향 영역으로 표현한다. 이러한 SRP-PHAT의 시간-방향 출력값들은 사전에 정의된 프레임 수만큼 누적하여 시간-방향 블록으로 정의한다. 다음으로, 잡음에 강건한 도래각 추정을 위하여, 각 시간-방향 블록을 블록차감 기법을 사용하여 매 프레임에 대해 정규화한다. 이후, 다중음원 환경에서 각 음원의 방향을 클러스터링하기 위해 정규화된 시간-방향 블록에 비지도(unsupervised) NMF를 적용한다. 구체적으로, 음원의 개수와 이들의 도래각을 추정하는데 각각 활성 및 기저 행렬들을 사용한다. 제안된 방법의 도래각 추정 성능을 평가하기 위해 이중 마이크로폰 배열로부터 입력된 [$-35{\circ}$, 5m], [$12{\circ}$, 4m], 그리고 [$38{\circ}$, 4.m]에 각각 위치한 세 가지 음원들에 대한 추정 오차의 절대 평균(mean absolute error, MAE) 및 오차의 표준편차를 측정하였다. 실험 결과. 제안된 방법은 기존의 SRP-PHAT 기반 도래각 추정방법에 비해 상대적으로 MAE를 56.83% 줄일 수 있었다.