• Transactions of the Korean hydrogen and new energy society
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• 제29권5호
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• pp.523-529
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• 2018

Two liquids which are generally used as fuels of rockets are mixed and their mixing process is quantitatively investigated by the use of particle image velocimetry (PIV). As working fluids for the liquid mixing, Dimethylfuran (DMF) and JetA1 oils have been used. Since the specific gravity of DMF is larger than that of JetA1 oil, the DMF oil has been set at the lower part of the JetA1 oil. For better visualization of the mixing process, Rhodamin B powder has been blended into the DMF oil. An agitator having 3 blades has been used for mixing the two liquids. For quantitative visualization, a LCD monitor has been used as a light source. A color camera, camcoder, has been used for recording the mixing process. The images captured by the camcoder have been digitized into three color components, R, G, and B. The color intensities of R, G, and B have been used as the inputs of the neural network of which hidden layer has 20 neurons. Color-to-concentration calibration has been performed before commencing the main experiments. Once this calibration is completed, the temporal changes of the concentration of the DMF has been quantitatively analyzed by using the constructed measurement system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.1027-1030
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• 2013

For the detection of objects in the videos, there are various ways that use the frequency transformation. In the videos, the images of objects could be changed slightly. Object detection methods using frequency transformation such as ASEF and MOSSE have the ability to renew the detection filter in order to deal with the change of object images. But these approaches are likely to fail the detection because the image changes often occur when they come out again after being hidden by other objects. What is worse, when they show up again, they appear in another place, not the original one. In this paper, a new proposal is present so that the detection can be carried out efficiently even when the images come out in other place, and the failure of the detection can be reduced.

• Geophysics and Geophysical Exploration
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• 제10권4호
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• pp.314-321
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• 2007

Recently, multi-dimensional joint inversion of geophysical data based on fundamentally different physical properties is being actively studied. Joint inversion can provide a way to obtaining much more accurate image of the subsurface structure. Through the joint inversion, furthermore, it is possible to directly estimate non-geophysical material properties from geophysical measurements. In this study, we developed a new algorithm for jointly inverting dc resistivity and seismic traveltime data based on the multiple constraints: (1) structural similarity based on cross-gradient, (2) correlation between two different material properties, and (3) a priori information on the material property distribution. Through the numerical experiments of surface dc resistivity and seismic refraction surveys, the performance of the proposed algorithm was demonstrated and the effects of different regularizations were analyzed. In particular, we showed that the hidden layer problem in the seismic refraction method due to an inter-bedded low velocity layer can be solved by the joint inversion when appropriate constraints are applied.

• Archives of design research
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• 제17권3호
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• pp.157-166
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• 2004

Samguk Yusa is a important historic record about the dynasties of ancient Korea. It consists of information about the hidden, mythical history, old languages and poems. This historical book has been translated many times since the Liberation of Korea in 1945. However, these books are the result of academic research so we are restricted in our usage of them to understand Korean history. There are many historical documentaries and TV series on Samguk Yusa. However, these programs can be viewed only and not be utilized in any way by the audience. Since the computer was introduced to the public, multimedia technology has been a good source to combine text, image, moving picture, sound, animation and graphic. Producing the CD-ROM about historical books not only produce digital images but also a valuable high quality digital information. Digitalization process also keeps the original content of the historical books as well as provide value as a research material as historical, artistic and archaeological item. Furthermore, its information would be provided through a network, like internet, to share and to promote more advanced studies. The purpose of this study is to produce the basic method of multimedia design of Samguk Yusa. This study also researches the problems of multimedia process for more effective usage.

• Korean Institute of Interior Design Journal
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• 제21권5호
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• pp.145-152
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• 2012

Since 1966 when James Turrell completed his studies on Art, he has been working on the consistent theme of Art. For the 46 years of time, site contexts, scales, methods of light have been changed and they made Turrell's unique 'project series'. Each series has different spatial, visual-perceptual forms and characteristics from other series. The differences were caused by the given situations, but also Turrell intentionally pursued it. However, there are essential theme of art that has not changed in most of Turrell's projects. Target of this paper is to study the unchanged theme as well as the differences. The study starts with three questions: first, what is the geometrical space composition?, second, what is the visual-perceptual phenomenon?, third, what is the hidden consistent theme? This research focuses on three case projects: Wedgework, Space Division Constructions, Skyspaces. These project series are in between the early small object-like installations and the late mega-scale outdoor projects. The study found that geometrical space composition has important role to give visual-perceptual dynamism to the viewer. The phenomenological perception is connected to the questions of relationship between human and space, ultimately human and the world. Although the Merleau-Ponty's philosophy has been related to the work of Turrell in various previous studies, Cartesian 3-dimensional geometry has also crucial role to experiment a viewer's perceptual boundaries. Image of infinity is another aspect of three cases, especially Space Division Constructions and Skyspaces. Through these structure, Turrell's work lead to an ultimate question of meaning for human existence in infinite space. It is hoped that this paper is helpful for Architecture and Interior design field in which light and space are essential.

• Journal of Intelligence and Information Systems
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• 제11권2호
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.

• Journal of English Language & Literature
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• 제54권1호
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• pp.129-147
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• 2008

Since the beginning of her dramatic career, Suzan-Lori Parks has considered digging up and restoring African-American history buried under the dominant white Anglo-Saxon history as her mission as a playwright. In Red Letter Plays, she attempts what Deborah Geis called "canon-critique" by taking canonical work by Nathaniel Hawthorne and casting an African-American character as the main character and describing her oppression as an African-American female. This paper argues that Suzan-Lori Parks accuses the oppressive social system by restoring and representing the history of sexual, economic, and racial exploitation that African-American females had to suffer through the dominant image of body and blood. Parks had to rewrite the history of black female characters on their bodies and in the blood because their bodies have been the ultimate object of revulsion and attraction in the perspective of white male. While abhorring and despising Hester La Negrita's abject body, male characters in In the Blood nonetheless not only exploit her sexually and economically but also impregnate her. Hester resorts to her only means of revolting against this oppressive system; she kills her most beloved son and writes "A" on the floor with his blood. Likewise, Hester Smith in Fucking A, who wears "A" on her bosom like Hester Prynne, which in this case means "abortionist," "saves" her son from the hunters by slitting his throat. Abundant graphic and sensational images written on black female body and in the blood are Parks's dramatic strategy to rewrite the forgotten and hidden history of black women's history.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제18권5호
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• pp.112-125
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• 2019

An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s.

• Journal of Digital Convergence
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• 제20권4호
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제20권6호
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• pp.26-36
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• 2021

In this study, a deep learning model for predicting the queue length was developed using the information collected from the image detector. Then, a multiple regression analysis model, a statistical technique, was derived and compared using two indices of mean absolute error(MAE) and root mean square error(RMSE). From the results of multiple regression analysis, time, day of the week, occupancy, and bus traffic were found to be statistically significant variables. Occupancy showed the most strong impact on the queue length among the variables. For the optimal deep learning model, 4 hidden layers and 6 lookback were determined, and MAE and RMSE were 6.34 and 8.99. As a result of evaluating the two models, the MAE of the multiple regression model and the deep learning model were 13.65 and 6.44, respectively, and the RMSE were 19.10 and 9.11, respectively. The deep learning model reduced the MAE by 52.8% and the RMSE by 52.3% compared to the multiple regression model.