• Journal of Advanced Marine Engineering and Technology
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• 제22권4호
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• pp.551-559
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• 1998

Evaporation and ignition characteristics of fuel droplet have major influences on the efficiency and performance of engine. In the present study the experiment of evaporation and self-ignition of single fuel was performed under the various ambient conditions. An individually suspended droplet of n-heptane n-hexadecane ethyl-alcohol and light oil were employed as a liquid droplet. Evaporation and ignition characteristics were measured by using the video-camera and image processing technique under the various ambient temperatures (up to 1000310 OC)and partial pressure of oxigen(up to 60%) The evaporation curve shows that the droplet life time ignition delay time decreases as the ambient temperature and partial pressure of oxigen increase, The temperature variations of droplet were also reported for various fuel and ambient temperatures. The numerical simulations were carried out to predict droplet diameter and temperature with favorable agreement.

• Journal of Advanced Marine Engineering and Technology
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• 제24권4호
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• pp.515-525
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• 2000

A new acoustic field visualization technique is introduced in this study. Small particles of which density is small enough to follow up the air used for the noise field visualization. In order to quantify the noise, PIV(Particle Imaging Velocimetry) has been constructed. When the driving frequency is in the vicinity of the resonance frequency of the simplified 2-dimensional muffler system, an acoustic streaming is shown and of which velocity distribution is obtained through PIV technique. It is experimentally proved that the present technique is able to visualize and quantify the acoustic fields.

• 한국항행학회논문지
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• 제14권6호
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• pp.928-934
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• 2010

본 논문에서는 적외선 빛을 이용하여 터치를 인식하고 어플리케이션을 구동할 수 있는 방법에 대하여 소개한다. 화면에 터치하면 그 곳의 빛을 적외선 카메라가 촬영을 하고, 촬영된 영상은 영상처리를 통해 ID, 좌표 등을 구한 후 TUIO Protocol로 Application에 통신 한다. 전달된 정보를 통해 Application에서 이벤트를 발생하여 구동하게 되는 원리이다. 본 논문에서는 터치를 이용한 Application은 Android Phone과 사진을 주고받을 수 있는 모바일 사진 관리 Application, 여러 사용자가 동시에 합주를 할 수 있는 음악연주 Application에 대해 설명한다.

• 한국멀티미디어학회논문지
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• 제24권10호
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• pp.1391-1402
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• 2021

This paper focuses use context-sensitive spelling error correction using generative adversarial network. Generative adversarial network[1] are attracting attention as they solve data generation problems that have been a challenge in the field of deep learning. In this paper, sentences are generated using word embedding information and reflected in word distribution representation. We experiment with DCGAN[2] used for the stability of learning in the existing image processing and D2GAN[3] with double discriminator. In this paper, we experimented with how the composition of generative adversarial networks and the change of learning corpus influence the context-sensitive spelling error correction In the experiment, we correction the generated word embedding information and compare the performance with the actual word embedding information.

• 한국가시화정보학회지
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• 제19권1호
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• pp.57-61
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• 2021

In order to determine erythrocyte sedimentation rate (ESR) indicating acute phase inflammation, a Westergren method has been widely used because it is cheap and easy to be implemented. However, the Westergren method requires quite a long time for 1 hour. In this study, a gated recurrent unit (GRU) neural network was used to reduce measurement time of ESR evaluation. The sedimentation sequences of the erythrocytes were acquired by the camera and data processed through image processing were used as an input data into the neural network models. The performance of a proposed models was evaluated based on mean absolute error. The results show that GRU model provides best accurate prediction than others within 30 minutes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• International journal of advanced smart convergence
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• 제10권2호
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• pp.45-52
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• 2021

The surveillance camera market has developed and plays an important role in the field of video surveillance. However, in recent years, the identification of areas requiring surveillance has been limited by reflective light in the surveillance camera market. Cameras using polarization filters are being developed to reduce reflective light and facilitate identification. Programs are required to automatically adjust polarization filters. In this paper, we proposed an optimal angle extraction method from surveillance cameras using polarization filters through histogram analysis. First of all, transformed to grayscale to analyze the specifications of frames in multiple polarized angle images, reducing computational throughput. Then we generated and analyzed a histogram of the corresponding frame to extract the angle when the highlights are the fewest. Experiments with 0˚ and 90˚ showed high performance in extracting optimal angles. At this point, it is hoped this technology would be used for surveillance cameras in place like beach with a lot of reflective light.

• Journal of information and communication convergence engineering
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• 제20권3호
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.187-192
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• 2023

With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.438-440
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• 2021

기계학습의 발전에 따라 다양한 분야에 인공지능 기법이 적용되고 있다. 이 분야 중 이미지에 있는 문자를 텍스트로 변환하는 OCR 기법이 있다. HP에서 개발된 tesseract는 그 기법의 하나다. 그러나 이미지의 문자를 인식하는 인식률이 아직은 낮다. 이를 위해 본 연구에서는 온톨로지를 이용하여 문맥을 인지시키는 후처리 과정을 통해서 이미지의 문자 변환율에 향상을 기하고자 한다.