• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.37-37
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• 2010

Silicate-silsesquioxane or siloxane-silsesquioxane hybrid thin films are strong candidates as matrix materials for ultra low dielectric constant (low-k) thin films. We synthesized the silicate-silsesquioxane hybrid resins from tetraethoxyorthosilicate (TEOS) and methyltrimethoxysilane (MTMS) through hydrolysis and condensation polymerization by changing their molar ratios ([TEOS]:[MTMS] = 7:3, 5:5, and 3:7), spin-coating on Si(100) wafers. In the case of [TEOS]:[MTMS] 7:3, the dielectric permittivity value of the resultant thin film was measured at 4.30, exceeding that of the thermal oxide (3.9). This high value was thought to be due to Si-OH groups inside the film and more extensive studies were performed in terms of electronic, ionic, and orientational polarizations using Debye equation. The relationship between the mechanical properties and the synthetic conditions of the silicate-silsesquioxane precursors was also investigated. The synthetic conditions of the low-k films have to be chosen to meet both the low orientational polarization and high mechanical properties requirements. In addition, we have investigated a new solution-based approach to the synthesis of semiconducting chalcogenide films for use in thin-film transistor (TFT) devices, in an attempt to develop a simple and robust solution process for the synthesis of inorganic semiconductors. Our material design strategy is to use a sol-gel reaction to carry out the deposition of a spin-coated CdS film, which can then be converted to a xerogel material. These devices were found to exhibit n-channel TFT characteristics with an excellent field-effect mobility (a saturation mobility of ${\sim}\;48\;cm^2V^{-1}s^{-1}$) and low voltage operation (< 5 V). These results show that these semiconducting thin film materials can be used in low-cost and high-performance printable electronics.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.3
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• pp.211-216
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• 2016

In several industrial fields, epoxy resin is widely used as an adhesive for co-curing and manufacturing various structures. Controlling the manufacturing process is required for ensuring robust bonding performance and the stability of the structures. A fiber optic sensor is suitable for the cure monitoring of epoxy resin owing to the thready shape of the sensor. In this paper, a fiber Bragg grating (FBG) sensor was applied for the cure monitoring of epoxy resin. Based on the experimental results, it was demonstrated that the FBG sensor can monitor the status of epoxy resin curing by measuring the strain caused by volume shrinkage and considering the compensation of temperature. In addition, two types of epoxy resin were used for the cure-monitoring; moreover, when compared to each other, it was found that the two types of epoxy had different cure-processes in terms of the change of strain during the curing. Therefore, the study proved that the FBG sensor is very profitable for the cure-monitoring of epoxy resin.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.9-18
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• 2014

The sensors attached on/in a person are moved since human body frequency changes their activity, therefore in wireless body area networks, nodal mobility and non-line-of-sight condition will impact on performance of networks such as energy efficiency and reliable communication. We then proposed schemes which study on forwarding decisions against frequent change of topology and channel conditions to increase reliable connections and improve energy efficiency. In this work, we control the size of packets, forwarding rate based on ratio of input links and output links at each node. We also robust the network topology by extending the peer to peer IEEE 802.15.4-based. The adaptive topology from chain-based to grid-based can optimal our schemes. The simulation shows that these approaches are not only extending network lifetime to 48.2 percent but also increase around 6.08 percent the packet delivery ratio. The "hot spots" problem is also resolved with this approach.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.446-454
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• 2009

Among various region detector and shape feature extraction method, MSER(Maximally Stable Extremal Region) and SIFT and its variant methods are popularly used in computer vision application. However, since SIFT is sensitive to the illumination change and MSER is sensitive to the scale change, it is not easy to apply the image similarity retrieval. In this paper, we present a Scale and Rotation Invariant Region Feature(SRIRF) descriptor using scale pyramid, MSER and affine normalization. The proposed SRIRF method is robust to scale, rotation, illumination change of image since it uses the affine normalization and the scale pyramid. We have tested the SRIRF method on various images. Experimental results demonstrate that the retrieval performance of the SRIRF method is about 20%, 38%, 11%, 24% better than those of traditional SIFT, PCA-SIFT, CE-SIFT and SURF, respectively.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.136-144
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• 2004

In this paper, we present an improved channel estimation method for orthogonal frequency division multiplexing systems using pilot-symbol-aided parameter estimation. Conventional linear minimum mean square error(LMMSE) channel estimation method uses only pilot symbols for channel estimation. So, as the fading channel varies rapidly, a performance is decreased. We proposed a channel estimation method, which estimates channel attenuation in the middle of pilots using pilot symbols and then estimates the whole channel attenuation with pilots and estimated channel attenuation. Compared with conventional LMMSE channel estimation method, the proposed method is significantly robust in a rapid fading channel with high Doppler frequency and delay spread.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.851-856
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• 2008

Construction of large-scale container ports with the productivity improvements in container cranes shortened time of staying port to increase the level of service it harbors efforts accelerated. About container crane system exerted on the input, which is designed to look good performance considering the states feedback control system. The states observer designed of container cranes state variables that are expected to measurement noise or particular measurement signal. In the status of existing research, the feedback gain matrix and the state observer gain matrix are searched by being separated solving. But the feedback gain matrix and the state observer gain matrix are searched by RCGAs at once that be used robust search method in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.632-639
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• 2007

This paper presents a wavelet-based watermarking algorithm to securely hide biometric features such as face and fingerprint and effectively extract them with less distortion of the concealed data. To hide the biometric features, we proposed a determination method of insert location based on wavelet transform and adaptive weight method according to the image characteristics. The hidden features are effectively extracted by applying the inverse wavelet transform to the watermarked image. To show the effectiveness, we analyze the various performance such as PSNR and correlation of watermark features before and after applying watermarking. Also, we evaluate the effect of watermaking algorithm with respect to biometric system such as recognition rate. Recognition rate shows 98.67% for multimodal biometric systems consisted of face and fingerprint. From these, we confirm that the proposed method makes it possible to effectively hide and extract the biometric features without lowering recognition rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.667-673
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• 2009

This paper presents an efficient facial expression recognition method by measuring the histogram distance based on preprocessing. The preprocessing that uses both centroid shift and histogram equalization is applied to improve the recognition performance, The distance measurement is also applied to estimate the similarity between the facial expressions. The centroid shift based on the first moment balance technique is applied not only to obtain the robust recognition with respect to position or size variations but also to reduce the distance measurement load by excluding the background in the recognition. Histogram equalization is used for robustly recognizing the poor contrast of the images due to light intensity. The proposed method has been applied for recognizing 72 facial expression images(4 persons * 18 scenes) of 320*243 pixels. Three distances such as city-block, Euclidean, and ordinal are used as a similarity measure between histograms. The experimental results show that the proposed method has superior recognition performances compared with the method without preprocessing. The ordinal distance shows superior recognition performances over city-block and Euclidean distances, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.629-634
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• 2009

In real-time system application, the feature extraction and scoring algorithm for classification of the passive sonar target has the following problems: it requires an accurate and efficient feature extraction method because it is very difficult to distinguish the features of the propeller shaft rate (PSR) and the blade rate (BR) from the frequency spectrum in real-time, it requires a robust and effective feature scoring method because the classification database (DB) composed of extracted features is noised and incomplete, and further, it requires an easy design procedure in terms of structures and parameters. To solve these problems, an intelligent feature extraction and scoring algorithm using the evolution strategy (ES) and the fuzzy theory is proposed here. To verify the performance of the proposed algorithm, a passive sonar target classification is performed in real-time. Simulation results show that the proposed algorithm effectively solves sonar classification problems in real-time.