• Journal of KIISE:Databases
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• v.33 no.4
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• pp.372-383
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• 2006

Among the approaches to image database management, content-based image retrieval (CBIR) is viewed as having the best support for effective searching and browsing of large digital image libraries. Typical CBIR systems allow a user to provide a query image, from which low-level features are extracted and used to find 'similar' images in a database. However, there exists the semantic gap between human visual perception and low-level representations. An effective methodology for overcoming this semantic gap involves relevance feedback to perform feature re-weighting. Current approaches to feature re-weighting require the number of components for a feature representation to be the same for every image in consideration. Following this assumption, they map each component to an axis in the n-dimensional space, which we call the metric space; likewise the feature representation is stored in a fixed-length vector. However, with the emergence of features that do not have a fixed number of components in their representation, existing feature re-weighting approaches are invalidated. In this paper we propose a feature re-weighting technique that supports features regardless of whether or not they can be mapped into a metric space. Our approach analyses the feature distances calculated between the query image and the images in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting. There is no restriction on how the distances are calculated for each feature. This provides freedom for how feature representations are structured, i.e. there is no requirement for features to be represented in fixed-length vectors or metric space. Our experimental results show the effectiveness of our approach and in a comparison with other work, we can see how it outperforms previous work.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of KIISE
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• v.42 no.3
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• pp.390-398
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• 2015

Spatial web objects refer to web documents that contain geographic information. Recently, services that create spatial web objects have increased greatly because of the advancements in devices such as smartphones. For services such as Twitter or Facebook, simple texts posted by users is stored along with information about the post's location. To search for such spatial web objects, a method that uses spatial information and text information simultaneously is required. Conventional spatial web object search methods mostly use R-tree and inverted file methods. However, these methods have a disadvantage of requiring a large volume of space when building indices. Furthermore, such methods are efficient for searching with many keywords but are inefficient for searching with a few keywords.. In this paper, we propose a spatial web object search method that uses a quad-tree and a patricia-trie. We show that the proposed technique is more effective than existing ones in searching with a small number of keywords. Furthermore, we show through an experiment that the space required by the proposed technique is much smaller than that required by existing ones.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.613-620
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• 2008

Noun extraction plays an important part in the fields of information retrieval, text summarization, and so on. In this paper, we present a Korean base-noun extraction system and apply it to text summarization to deal with a huge amount of text effectively. The base-noun is an atomic noun but not a compound noun and we use tow techniques, filtering and segmenting. The filtering technique is used for removing non-nominal words from text before extracting base-nouns and the segmenting technique is employed for separating a particle from a nominal and for dividing a compound noun into base-nouns. We have shown that both of the recall and the precision of the proposed system are about 89% on the average under experimental conditions of ETRI corpus. The proposed system has applied to Korean text summarization system and is shown satisfactory results.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.169-175
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• 2021

Recently, an ultrasound hologram and its applications have gained attention in the ultrasound research field. However, the determination technique of transmit signal phases, which generate a hologram, has not been significantly advanced from the previous algorithms which are time-consuming iterative methods. Thus, we applied the deep learning technique, which has been previously adopted to generate an optical hologram, to generate an ultrasound hologram. We further examined the Deep learning-based Holographic Ultrasound Generation algorithm (Deep-HUG). We implement the U-Net-based algorithm and examine its generalizability by training on a dataset, which consists of randomly distributed disks, and testing on the alphabets (A-Z). Furthermore, we compare the Deep-HUG with the previous algorithm in terms of computation time, accuracy, and uniformity. It was found that the accuracy and uniformity of the Deep-HUG are somewhat lower than those of the previous algorithm whereas the computation time is 190 times faster than that of the previous algorithm, demonstrating that Deep-HUG has potential as a useful technique to rapidly generate an ultrasound hologram for various applications.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.1-7
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• 2021

In this paper, optimized media data retrieval and transmission based on the Hybrid CDN/P2P architecture and selective storage through user's prediction of requestability enable seamless data transfer to users and reduction of unnecessary traffic. We also propose a new media management method to minimize the possibility of transmission delay and packet loss so that media can be utilized in real time. To this end, we construct each media into logical segments, continuously compute weights for each segment, and determine whether to store segment data based on the calculated weights. We also designate scattered computing nodes on the network as local groups by distance and ensure that storage space is efficiently shared and utilized within those groups. Experiments conducted to verify the efficiency of the proposed technique have shown that the proposed method yields a relatively good performance evaluation compared to the existing methods, which can enable both initial latency reduction and seamless transmission.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.249-274
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• 1998

It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

• Clinical and Experimental Reproductive Medicine
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• v.30 no.2
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• pp.119-126
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• 2003

Objective: This study was carried out to compare the clinical outcomes of intracytoplasmic sperm injection (ICSI) in patients with obstructive azoospermia according to sperm retrieval site and technique; microsurgical epididymal sperm aspiration (MESA), percutaneous epididymal sperm aspiration (PESA), testicular sperm extraction by open biopsy (TESE). Methods: The outcomes of ICSI and IVF-ET were evaluated and compared among 3 groups. Seventy three men suffering from infertility due to obstructive azoospermia had 107 ICSI cycles using MESA (21 cycles in 15 patients), PESA (26 cycles in 17 patients) and TESE (60 cycles in 41 patients). Results: In the clinical outcomes in patients undergoing ICSI with epididymal or testicular sperm, there were no significant differences in fertilization rate (66.1% vs. 60.5%), cleavage rate (94.9% vs. 97.6%), cumulative embryo score (CES) (51.3 vs. 58.8), implantation rate (7.9% vs. 6.1), and clinical pregnancy rate per ET (30.4% (14/46) vs. 25.4% (15/59)) between both groups. Also, in the clinical outcomes in ICSI patients using MESA, PESA, TESE, there were no significant differences in fertilization rate (61.8%, 69.4%, 60.5%), cleavage rate (92.1%, 97.3%, 97.6%), CES (38.1, 52.0, 58.8), implantation rate (9.5%, 6.6%, 6.1%), and clinical pregnancy rate per ET (35% (7/20), 26.9% (7/26), 25.4% (15/59)) among 3 groups. Conclusion: When compared with MESA or TESE, PESA, the clinical outcomes were similar in ICSI patients with obstructive azoospermia whatever the origin or the technique of sperm retrieval. However, we considered PESA is more time-saving and cost effective for ICSI in patients with obstructive azoospermia.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.21-28
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• 2010

This paper reports an experimental result on optimizing dissimilarity-based classification(DBC) by simultaneously using a dynamic time warping(DTW) and a multiple fusion strategy(MFS). DBC is a way of defining classifiers among classes; they are not based on the feature measurements of individual samples, but rather on a suitable dissimilarity measure among the samples. In DTW, the dissimilarity is measured in two steps: first, we adjust the object samples by finding the best warping path with a correlation coefficient-based DTW technique. We then compute the dissimilarity distance between the adjusted objects with conventional measures. In MFS, fusion strategies are repeatedly used in generating dissimilarity matrices as well as in designing classifiers: we first combine the dissimilarity matrices obtained with the DTW technique to a new matrix. After training some base classifiers in the new matrix, we again combine the results of the base classifiers. Our experimental results for well-known benchmark databases demonstrate that the proposed mechanism achieves further improved results in terms of classification accuracy compared with the previous approaches. From this consideration, the method could also be applied to other high-dimensional tasks, such as multimedia information retrieval.