• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.261-272
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• 2005

3D models in urban areas are essential for a variety of applications, such as virtual visualization, GIS, and mobile communications. LIDAR (Light Detection and Ranging) is a relatively new technology for obtaining Digital Terrain Models (DTM) of the earth's surface since manual 3D data reconstruction is very costly and time consuming. In this paper an approach to extract ground and non-ground points data from LIDAR data by using filtering is presented and the accuracy for generating DTM from ground points data is evaluated. Numerous filter algorithms have been developed to date. To determine the performance of filtering, we selected three filters which are based on the concepts for height difference, slope, and morphology, and also were applied two different data acquired from high raised apartments areas and low house areas. From the results it has been found that the accuracy for generating DTM from LIDAR data are 0.16 m and 0.59 m in high raised apartments areas and low house areas respectively. We expect that LIDAR data is used to generate the accurate DTM in urban areas.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.123-131
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• 2020

After observing that most tourists plan to complete their visits to multiple cultural heritage sites within one day, we surmised that for many museum visitors, the foremost thought is with regard to the amount of time is to be spent at each location and how they can maximize their enjoyment at a site while still balancing their travel itinerary? Recommendation systems in e-commerce are built on knowledge about the users' previous purchasing history; recommendation systems for museums, on the other hand, do not have an equivalent data source available. Recent solutions have incorporated advanced technologies such as algorithms that rely on social filtering, which builds recommendations from the nearest identified similar user. Our paper proposes a different approach, and involves providing dynamic recommendations that deploy social filtering as well as content-based filtering using term frequency-inverse document frequency. The main challenge is to overcome a cold start, whereby no information is available on new users entering the system, and thus there is no strong background information for generating the recommendation. In these cases, our solution deploys statistical methods to create a recommendation, which can then be used to gather data for future iterations. We are currently running a pilot test at Chao Samphraya national museum and have received positive feedback to date on the implementation.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.36-51
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• 2008

As the global warming has influenced on various sectors including agriculture, forestry, fisheries and health, it is essential to project more accurate future climate for an assessment of climate change impact and adaptation strategy. This study examines spatial distribution of onset dates and durations of season decomposed by applying a lowpass filtering using observed 30-year (1971-2000) data and projected 2090s data based on the IPCC SRES A1B emission scenario in South Korea. In general, the distributions of spring and winter onset date are affected by latitudes, topography and proximity to oceans. However, onset dates of summer and autumn are a little affected by proximity to oceans and topography than by latitudes. In the 2090s (2091-2100), the onset dates of spring begin about 40 days earlier and the onset dates of summer begin 25-30 days earlier as compare with present time. On the other hand, the onset dates of winter begin about 50 days later in the southern and eastern coastal area and in the southern inland. The onset dates of autumn begin about 20 days later. In the 2090s, summer duration is longer and winter duration is shorter as compare with present time at southern and eastern coastal area.

• Journal of the Korean Geographical Society
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• v.42 no.6
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• pp.835-850
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• 2007

This study examines long-term trends of onset dates and durations of season decomposed by applying a lowpass filtering using observed 80-year(1921-2000) data and projected 2040s and 2090s data based on the IPCC SRES A1B emission scenario in South Korea. As recent climate changes on seasonal cycles in South Korea, the onset dates of spring and summer began earlier after 1970s. But onset dates of autumn and winter were delayed. Winter duration was more shortened during the post-1990 period. Summer duration is longer and winter duration is shorter at southern and eastern coastal area. The different of summer duration and winter duration in coastal area was longer than over the inland. The reduction in winter duration in South Korea agrees with results in overall global warming trends as a climate change signal. Future model output data predict that winter will disappear in Gangneung, Busan and Mokpo in the 2090s

• Convergence Security Journal
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• v.19 no.4
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• pp.133-142
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• 2019

Although torrents and P2P sites or web hard are frequently used by users simply because they can be easily downloaded freely or at low prices, domestic torrent and P2P sites or web hard are very sensitive to copyright. Techniques have been researched and applied. Among these, title and string comparison method filtering techniques that block the number of cases such as file titles or combinations of key words are blocked by changing the title and spacing. Bypass is easy through. In order to detect and block illegal works for copyright protection, a technique for normalizing modified file titles is essential. In this paper, we compared the detection rate by searching before and after normalizing the modified file title of illegal works and normalizing the file title. Before the normalization, the detection rate was 77.72%, which was unfortunate while the detection rate was 90.23% after the normalization. In the future, it is expected that better handling of nonsense terms, such as common date and quality display, will yield better results.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.23-26
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• 2003

디지털로 신호를 표현하는 방법은 기존 아날로그 표현하는 방법에 비해 많은 장점을 가지고 있다. 하지만 디지털로 된 데이터는 언제 어디서든 대단위 복제가 가능하다. 즉, 저작권 침해, 불법 복제 및 배포, 손쉽게 위조할 수 있다는 점이 그것이다. 디지털 영상 정보의 보호를 위해 디지털 영상의 불법적인 내용 조작을 막고, 영상의 소유권을 보장할 수 있는 방법으로 디지털 워터마크(Digital Watermark)가 있다. 디지털 워터마크는 공개키 알고리즘이나 방화벽 등으로 해독된 영상에 대하여 부가적인 보호를 제공한다. 본 논문에서는 디지털 영상 데이터의 정보 보호를 위해 주파수 영역에서의 웨이브릿 변환(Wavelet Transform)을 이용한 이미지 적용 디지털 워터마킹(Image-Adaptive Digital Watermarking) 방법을 제안한다. 이미지 적용 웨이브릿(Image-Adaptive Wavelet)은 영상을 주파수적으로 분해하면서 각 대역들의 공간 영역에서의 정보를 함께 지니고 JND(Just noticeable difference)을 포함한다. 이미지 적응 웨이브릿의 이러한 특성을 이용하여 다해상도 분해하고, 손실 압축(Loss Compression)이나 필터링(Filtering), 잡음(Noise)등에 크게 영향받는 저주파 성분과 인간의 시각적으로 큰 의미를 갖는 고주파 성분의 특성을 이용하여 워터마크를 삽입한다.

• Journal of Yeungnam Medical Science
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• v.21 no.1
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• pp.12-22
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• 2004

The management of coincident glaucoma and cataract is not only a common clinical challenge but also an important research topic in the ophthalmic surgical field. The purpose of this article is to compare the different surgical options on the basis of their achievable postoperative intraocular pressure (IOP) control, success rates, and complication rates reported in the related literature, and to give advice on how to manage typical situations of patients with both glaucoma and cataract. Main topics were focused on indications and rationale of 3 surgical options (only cataract surgery first and later trabeculectomy, only trabeculectomy first and later cataract surgery, or simultaneous combined surgery). Modern clear corneal cataract extraction techniques resulted in a modest intermediate-term reduction of IOP and has considerably improved the success rates of combined glaucoma and cataract surgery. It also enabled future trabeculectomy to be successfully performed at a later date if necessary. Trabeculectomy alone achieved better IOP regulation than phacotrabeculectomy (combined surgery), but subsequent cataract surgery may compromise preexisting filtering bleb. Combined surgery augmented with mitomycin C achieved a lower IOP than combined surgery alone but had a higher complication rate. In conclusion, the choice of the preferred surgical method should be determined according to the target pressure, the amount of glaucomatous damage, and the grade of visual disturbance caused by the cataract. Phacotrabeculectomy with adjunctive mitomycin C offers visual improvement and achieves the best IOP lowering of all types of combined glaucoma and cataract surgery currently used but is associated with potentially sight-threatening complications.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.490-494
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• 2005

Multispectral image is wavelet trans formed and classified into one of three classes considering reference characteristics of the subband with the lowest resolution. Recently, aegis of authentitation and creator's copyright has become a matter of great concern by the diffusion of multimedia technique and the growth of the internet and the easily duplicated property of digital data. Consequently, many active researches have been made to protect copyright and to assure integrity by inserting watermark into the digital data. In this paper, watermark is repeated through the entire image and adapted to the content of the image.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.