• Rapid Communication in Photoscience
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• v.3 no.1
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• pp.16-19
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• 2014

Anodic self-organized titania nanotube (TNT) arrays have a great potential as efficient electron-transport materials for dye-sensitized solar cells (DSSC). Herewith we report the photovoltaic and kinetic investigations for a series of heteroleptic ruthenium complexes (RD16-RD18) sensitized on TNT films for DSSC applications. We found that the RD16 device had an enhanced short-circuit current density ($J_{SC}/mAcm^{-2}=15.0$) and an efficiency of power conversion (${\eta}=7.2%$) greater than that of a N719 device (${\eta}=7.1%$) due to the increasing light-harvesting and the broadened spectral features with thiophene-based ligands. However, the device made of RD17 (adding one more hexyl chain) showed smaller $J_{SC}(14.1mAcm^{-2})$ and poorer ${\eta}(6.8%)$ compare to those of RD16 due to smaller amount of dye-loading and less efficient electron injection for the RD17 device than for the RD16 device. For the RD18 dye (adding one more thiophene unit and one more hexyl chain), we found that the device showed even lower $J_{SC}(13.2mAcm^{-2}) $ that led to a poorest device performance (${\eta}=6.2%$) for the RD18 device. These results are against to those obtained from the same dyes sensitized on $TiO_2$ nanoparticle films and they can be rationalized according to the electron transport kinetics measured using the methods of charge extraction and transient photovoltage decays.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.859-872
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• 2016

Land cover classification is an important tool for preventing natural disasters, collecting environmental information, and monitoring natural resources. Hyperspectral imaging is widely used for this task thanks to sufficient spectral information. However, the curse of dimensionality, spatiotemporal variability, and lack of labeled data make it difficult to classify the land cover correctly. We propose a novel classification framework for land cover classification of hyperspectral data based on convolutional neural networks. The proposed framework naturally incorporates full spectral features with the information from neighboring pixels and has advantages over existing methods that require additional feature extraction or pre-processing steps. Empirical evaluation results show that the proposed framework provides good generalization power with classification accuracies better than (or comparable to) the most advanced existing classifiers.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.557-561
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• 2014

In this work, Altair Engineering's vibroacoustic modeling approach is used to simulate the acoustic signature of a simplified automobile in a wind tunnel. The modeling approach relies on a two step procedure involving simulation and extraction of acoustic sources using a high fidelity Computational Fluid Dynamics (CFD) simulation followed by propagation of the acoustic energy within the structure and passenger compartment using a structural dynamics solver. The tools necessary to complete this process are contained within Altair's HyperWorks CAE software suite. The CFD simulations are performed using AcuSolve and the structural simulations are performed using OptiStruct. This vibroacoustics simulation methodology relies on calculation of the acoustic sources from the flow solution computed by AcuSolve. The sources are based on Lighthill's analogy and are sampled directly on the acoustic mesh. Once the acoustic sources have been computed, they are transformed into the frequency domain using a Fast Fourier Transform (FFT) with advanced sampling and are subsequently used in the structural acoustics model. Although this approach does require the CFD solver to have knowledge of the acoustic simulation domain a priori, it avoids modeling errors introduced by evaluation of the acoustic source terms using dissimilar meshes and numerical methods. The aforementioned modeling approach is demonstrated on the Hyundai Simplified Model (HSM) geometry in this work. This geometry contains flow features that are representative of the dominant noise sources in a typical automobile design; namely vortex shedding from the passenger compartment A-pillar and bluff body shedding from the side view mirrors. The geometry also contains a thick poroelastic material on the interior that acts to reduce the acoustic noise. This material is modeled using a Biot material formulation during the structural acoustic simulation. Successful prediction of the acoustic noise within the HSM geometry serves to validate the vibroacoustic modeling approach for automotive applications.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.3-10
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• 2014

Digital maps are made by experts who digitize the data from aerial image and field survey. And the digital maps are updated every 2 years in National Geographic Information Institute. Conventional Digitizing methods take a lot of time and cost. And geographic information needs to be modified and updated appropriately as geographical features are changing rapidly. Therefore in this paper, we modify the digital map updates the road information for rapid high-resolution aerial orthophoto taken at different times were performed HSI color conversion. Road area of the cassification was performed the region growing methods. In addition, changes in the target area for analysis by applying the CVA technique to compare the changed road area by analyzing the accuracy of the proposed extraction.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.125-137
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• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.139-149
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• 2006

Earlier research works focused on the seasonal patterns and bio-geochemical processes in sand dunes, and the satellite data and aerial photographs have been used only as a backdrop or for the multi-temporal delineation of sand dune area. In order to find the optimal way to extract features' characteristics, Gimnyeong sand dune area was selected as a study site. Field works have been carried out three times to collect ground control points and sand samples for laboratory analyses. The texture of sand dune is classified as fine sand, which has been derived from shell fragments. The sand dune penetrated into the island from northwest to southeast direction. An aerial photograph was re-sampled into one-meter resolution and rectified with software including Erdas Imagine and ENVI. Sub-scenes were chosen as samples for sand dune, urban area and rural area. K-group non-parametric analysis had been done for the geometric and spectral values of enclosed texture patches. Urban areas proved to have significant smaller patches than the others.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.57-66
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• 2011

In this paper, it is proposed for algorithm to detect human efficiently using a edge symmetry and gradient directional characteristics in realtime by the feature extraction in a single input image. Proposed algorithm is composed of three stages, preprocessing, region partition of human candidates, verification of candidate regions. Here, preprocessing stage is strong the image regardless of the intensity and brightness of surrounding environment, also detects a contour with characteristics of human as considering the shape features size and the condition of human for characteristic of human. And stage for region partition of human candidates has separated the region with edge symmetry for human and size in the detected contour, also divided 1st candidates region with applying the adaboost algorithm. Finally, the candidate region verification stage makes excellent the performance for the false detection by verifying the candidate region using feature vector of a gradient for divided local area and classifier. The results of the simulations, which is applying the proposed algorithm, the processing speed of the proposed algorithms is improved approximately 1.7 times, also, the FNR(False Negative Rate) is confirmed to be better 3% than the conventional algorithm which is a single structure algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.79-86
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• 2008

As the rapid development of the Internet, the embedded images in HTML web pages nowadays become predominant. For its amazing function in describing the content and attracting attention, images become substantially important in web pages. All these images consist a considerable database. What's more, the semantic meanings of images are well presented by the surrounding text and links. But only a small minority of these images have precise assigned keyphrases. and manually assigning keyphrases to existing images is very laborious. Therefore it is highly desirable to automate the keyphrases extraction process. In this paper, we first introduce WWW image annotation methods, based on low level features, page tags, overall word frequency and local word frequency. Then we put forward our method of multi-cues integration image annotation. Also, show multi-cue image annotation method is more superior than other method through an experiment.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.675-682
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• 2014

Prostate is only an organ of men. To diagnose the disease of the prostate, generally transrectal ultrasound(TRUS) images are used. Detecting its boundary is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Support Vector Machine(SVM) is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing. Gabor filter bank for extraction of rotation-invariant texture features has been implemented. SVM for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted. A number of experiments are conducted to validate this method and results shows that the proposed algorithm extracted the prostate boundary with less than 10% relative to boundary provided manually by doctors.