• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.65-74
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• 2009

Scene change detection is pretreatment to index and search video information in video search system, and it is very important technology for overall performance. Existing scene change detection used single characteristic of pixel value difference, histogram difference, etc or mixed single characteristics that have complementary relationship. However, accuracy of those researches is very poor for special video such as infrared camera, night shooting. Therefore, this paper is proposed the method that is mixed color histogram and at algorithm for scene change detection at the specific movie. To verify the usefulness of a proposed method, we did an experiment which used color histogram only and KLT algorithm with color histogram. In result, evaluation index of proposed method is improved about 11.4% at the specific movie.

• Structural Engineering and Mechanics
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• v.35 no.2
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• pp.257-260
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• 2010

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.627-635
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• 2020

With the increasing severity of climate change, intense torrential rains are occurring more frequently globally. Flooding due to torrential rain not only causes substantial damage directly, but also via secondary events such as landslides. Therefore, accurate and prompt flood detection is required. Because it is difficult to directly access flooded areas, previous studies have largely used satellite images. Traditionally, water indices such asthe normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) which are based on different optical bands acquired by satellites, are used to detect floods. In addition, as flooding likelihood is greatly influenced by the weather, synthetic aperture radar (SAR) images have also been used, because these are less influenced by weather conditions. In this study, we compared flood areas calculated from SAR images and water indices derived from Landsat-8 images, where the images were acquired at similar times. The flooded area was calculated from Landsat-8 and Sentinel-1 images taken between the end of May and August 2019 at Lijiazhou Island, China, which is located in the Changjiang (Yangtze) River basin and experiences annual floods. As a result, the flooded area calculated using the MNDWI was approximately 21% larger on average than that calculated using the NDWI. In a comparison of flood areas calculated using water indices and SAR intensity images, the flood areas calculated using SAR images tended to be smaller, regardless of the order in which the images were acquired. Because the images were acquired by the two satellites on different dates, we could not directly compare the accuracy of the water-index and SAR data. Nevertheless, this study demonstrates that floods can be detected using both optical and SAR satellite data.

• Food Engineering Progress
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• v.13 no.2
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• pp.117-121
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• 2009

Detection of spoilage odors from beef during storage was investigated using sensory evaluation with R-index, and microbial assay for Pseudomonas. Beef samples were tested to measure the flavor changes, which were converted to R-index, and the Pseudomonas levels during storage. There was a steep rise in R-index until 36 hr after storage at 25$^{\circ}C$, and then a gentle rise from 48 hr, whereas, there was a steady rise in R-index in the whole range of storage at 5$^{\circ}C$. Detection time of spoilage odors according to R-index was statistically analyzed at $\alpha$=5% to be at 30.92${\pm}$3.47 hr and 169.80${\pm}$11.27 hr for 25 and 5$^{\circ}C$ storage, respectively, and analyzed at $\alpha$=1% to be 34.80${\pm}$4.01 and 176.41${\pm}$9.89 hr for 25 and 5$^{\circ}C$ storage, respectively. At the detection times of spoilage odors, the Pseudomonas levels were found to be almost the same, but less than 6-7 log CFU/g generally known as a standard level at occurrence of spoilage odors in beef. This indicated that some other factors than the Pseudomonas reactions could be associated with generation of spoilage odors.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.975-988
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• 2020

Change detection is the process of identifying changes by observing the multi-temporal images at different times, and it is an important technique in remote sensing using satellite images. Among the change detection methods, the unsupervised change detection technique has the advantage of extracting rapidly the change area as a binary image. However, it is difficult to understand the changing pattern of land cover in binary images. This study used grid points generated from seamless digital map to evaluate the satellite image change detection results. The land cover change results were extracted using multi-temporal KOMPSAT-3A (K3A) data taken by Gimje Free Trade Zone and change detection algorithm used Spectral Angle Mapper (SAM). Change detection results were presented as binary images using the methods Otsu, Kittler, Kapur, and Tsai among the automated threshold selection algorithms. To consider the seasonal change of vegetation in the change detection process, we used the threshold of Differenced Normalized Difference Vegetation Index (dNDVI) through the probability density function. The experimental results showed the accuracy of the Otsu and Kapur was the highest at 58.16%, and the accuracy improved to 85.47% when the seasonal effects were removed through dNDVI. The algorithm generated based on this research is considered to be an effective method for accuracy assessment and identifying changes pattern when applied to unsupervised change detection.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.2
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• pp.168-174
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• 2008

Diagnosis on setteability based on human operator's experimental knowledge, which could be established by long term operation, is a limit factor to construction of automation control system in wastewater treatment plant. On-line SVI(Sludge Volume Index) analyzer was developed which can measure SV30 automatically by image capture and image analysis method. In this paper, information got by settling process was studied using On-line SVI analyzer for better operation & management of WWTPs. First, SV30 detection algorithm was developed using image capture and image analysis for settling test and it showed that automatic detection is feasible even if deflocculation and bulking was occurred. Second, turbidity assessment model was developed using image analysis.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.223-223
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• 2009

In this paper, designed and simulated Power Splitter (PS) integrated Mach-Zehnder interferometer (MZI) based planar type optical waveguide devices (which is called here a PS-MZI). The PS-MZI optical waveguide sensor was preceded by a Y-junction, which splits the input power between the sensor, and a reference branch, to minimize the effect of optical power variations. The PS-MZI optical waveguide sensor induced changing phases of the incident beam, which had fallen upon the waveguide through computer simulation, according to the small changes in the index of refraction, thus beam intensity was changed. The waveguide were optimized at a wavelength of 1550 nm and fabricated according to the design rule of 0.45 delta%, which is the difference of refractive index between the core and clad. The fabrication of PS-MZI optical waveguide sensor was performed by a conventional planar lightwave circuit (PLC) fabrication process. The PS-MZI optical waveguide that was fabricated to be applied as a biosensor revealed a low insertion loss and a low polarization-dependent loss. After having etched the over-clad at the sensor part in the MZI optical waveguide that was fabricated, Ti deposition was made on the adhesion layer, and then Au thin-film deposition was carried out thereon. In addition, its optical properties were measured by having changed the index of refraction oil at the sensing part of the MZI. To apply the planar type PS-MZI optical waveguide as a biosensor, a detection test for Staphylococcus aureus was conducted according to changes in concentration, having adopted Ti-alkoxide as ligand. The detection result of the S. aureus by the PS-MZI optical waveguide sensor was possible to the level of $10^1$ CFU/ml.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1601-1614
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• 2008

The number of web service users has been increased rapidly as existing services are changed into the web-based internet applications. Therefore, it is necessary for us to use web log pre-processing technique to detect attacks on diverse web service transactions and it is also possible to extract web mining information. However, existing mechanisms did not provide efficient pre-processing procedures for a huge volume of web log data. In this paper, we proposed both a field based parsing and a high-speed log indexing mechanism based on the suggested B-tree Index Vector structure for performance enhancement. In experiments, the proposed mechanism provides an efficient web log pre-processing and search functions with a session classification. Therefore it is useful to enhance web attack detection function.

• Smart Structures and Systems
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• v.30 no.6
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• pp.661-671
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• 2022

Stayed cables are the key components for transmitting loads in cable-stayed bridges. Therefore, it is very important to evaluate the cable force condition to ensure bridge safety. An online condition assessment and anomaly localization method is proposed for cables based on the spatiotemporal correlation of grouped cable forces. First, an anomaly sensitive feature index is obtained based on the distribution characteristics of grouped cable forces. Second, an adaptive anomaly detection method based on the k-nearest neighbor rule is used to perform dissimilarity measurements on the extracted feature index, and such a method can effectively remove the interference of environment factors and vehicle loads on online condition assessment of the grouped cable forces. Furthermore, an online anomaly isolation and localization method for stay cables is established, and the complete decomposition contributions method is used to decompose the feature matrix of the grouped cable forces and build an anomaly isolation index. Finally, case studies were carried out to validate the proposed method using an in-service cable-stayed bridge equipped with a structural health monitoring system. The results show that the proposed approach is sensitive to the abnormal distribution of grouped cable forces and is robust to the influence of interference factors. In addition, the proposed approach can also localize the cables with abnormal cable forces online, which can be successfully applied to the field monitoring of cables for cable-stayed bridges.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.425-440
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• 2023

Monitoring water surface has become one of the most prominent areas of research in addressing environmental challenges.Accurate and automated detection of watersurface in remote sensing imagesis crucial for disaster prevention, urban planning, and water resource management, particularly for a country where water plays a vital role in human life. However, achieving precise detection poses challenges. Previous studies have explored different approaches,such as analyzing water indexes, like normalized difference water index (NDWI) derived from satellite imagery's visible or infrared bands and using k-means clustering analysis to identify land cover patterns and segment regions based on similar attributes. Nonetheless, challenges persist, notably distinguishing between waterspectralsignatures and cloud shadow or terrain shadow. In thisstudy, our objective is to enhance the precision of water surface detection by constructing a comprehensive water database (DB) using existing digital and land cover maps. This database serves as an initial assumption for automated water index analysis. We utilized 1:5,000 and 1:25,000 digital maps of Korea to extract water surface, specifically rivers, lakes, and reservoirs. Additionally, the 1:50,000 and 1:5,000 land cover maps of Korea aided in the extraction process. Our research demonstrates the effectiveness of utilizing a water DB product as our first approach for efficient water surface extraction from satellite images, complemented by our second and third approachesinvolving NDWI analysis and k-means analysis. The image segmentation and binary mask methods were employed for image analysis during the water extraction process. To evaluate the accuracy of our approach, we conducted two assessments using reference and ground truth data that we made during this research. Visual interpretation involved comparing our results with the global surface water (GSW) mask 60 m resolution, revealing significant improvements in quality and resolution. Additionally, accuracy assessment measures, including an overall accuracy of 90% and kappa values exceeding 0.8, further support the efficacy of our methodology. In conclusion, thisstudy'sresults demonstrate enhanced extraction quality and resolution. Through comprehensive assessment, our approach proves effective in achieving high accuracy in delineating watersurfaces from satellite images.