An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.
According to the advancement of the GNSS satellite positioning system, the module of hardware and operation software reflecting accuracy and economical efficiency is implemented in the user sector including the multi-channel GNSS receiver, the multi-frequency external antenna and the mobile app (App) base public positioning analysis software etc., and the multichannel GNSS RTK positioning of the active configuration method (DIY, Do it yourself) is possible according to the purpose of user. Especially, as the infrastructure of multi-GNSS satellite is expanded and the potential of expansion of utilization according to various modules is highlighted, interest in the utilization of multi-channel low-cost GNSS receiver module is gradually increasing. The purpose of this study is to review the multi-channel low-cost GNSS receivers that are appearing in the mass market in various forms and to analyze the utilization plan of the "address information facility investigation project" of the Ministry of Public Administration and Security by constructing the multi-channel low-cost GNSS positioning module based RTK survey system (hereinafter referred to as "multi-channel GNSS RTK module positioning system"). For this purpose, we constructed a low-cost "multi-channel GNSS RTK module positioning system" by combining related modules such as U-blox's F9P chipset, antenna, Ntrip transmission of GNSS observation data and RTK positioning analysis app through smartphone. Kinematic positioning was performed for circular trajectories, and static positioning was performed for address information facilities. The results of comparative analysis with the Static positioning performance of the geodetic receivers were obtained with 5 fixed points in the experimental site, and the good static surveying performance was obtained with the standard deviation of average ±1.2cm. In addition, the results of the test point for the outline of the circular structure in the orthogonal image composed of the drone image analysis and the Kinematic positioning trajectory of the low cost RTK GNSS receiver showed that the trajectory was very close to the standard deviation of average ±2.5cm. Especially, as a result of applying it to address information facilities, it was possible to verify the utility of spatial information construction at low cost compared to expensive commercial geodetic receivers, so it is expected that various utilization of "multi-channel GNSS RTK module positioning system"
The Journal of Korean Institute of Communications and Information Sciences
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v.29
no.6C
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pp.801-814
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2004
In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.
Purpose : To evaluate accuracy and reliability of program to measure facial soft tissue thickness using 3D computed tomographic images by comparing with direct measurement. Materials and Methods : One cadaver was scanned with a Helical CT with 3 mm slice thickness and 3 mm/sec table speed. The acquired data was reconstructed with 1.5 mm reconstruction interval and the images were transferred to a personal computer. The facial soft tissue thickness were measured using a program developed newly in 3D image. For direct measurement, the cadaver was cut with a bone cutter and then a ruler was placed above the cut side. The procedure was followed by taking pictures of the facial soft tissues with a high-resolution digital camera. Then the measurements were done in the photographic images and repeated for ten times. A repeated measure analysis of variance was adopted to compare and analyze the measurements resulting from the two different methods. Comparison according to the areas was analyzed by Mann-Whitney test. Results : There were no statistically significant differences between the direct measurements and those using the 3D images (p>0.05). There were statistical differences in the measurements on 17 points but all the points except 2 points showed a mean difference of 0.5 mm or less. Conclusion : The developed software program to measure the facial soft tissue thickness using 3D images was so accurate that it allows to measure facial soft tissues thickness more easily in forensic science and anthropology.
In relation to the extraction of opinion words, it may be difficult to directly apply most of the methods suggested in existing English studies to the Korean language. Additionally, the manual method suggested by studies in Korea poses a problem with the extraction of opinion words in that it takes a long time. In addition, English thesaurus-based extraction of Korean opinion words leaves a challenge to reconsider the deterioration of precision attributed to the one to one mismatching between Korean and English words. Studies based on Korean phrase analyzers may potentially fail due to the fact that they select opinion words with a low level of frequency. Therefore, this study will suggest the k-Structure (k=5 or 8) method, which may possibly improve the precision while mutually complementing existing studies in Korea, in automatically extracting opinion words from a simple sentence in a given Korean product review. A simple sentence is defined to be composed of at least 3 words, i.e., a sentence including an opinion word in ${\pm}2$ distance from the attribute name (e.g., the 'battery' of a camera) of a evaluated product (e.g., a 'camera'). In the performance experiment, the precision of those opinion words for 8 previously given attribute names were automatically extracted and estimated for 1,868 product reviews collected from major domestic shopping malls, by using k-Structure. The results showed that k=5 led to a recall of 79.0% and a precision of 87.0%; while k=8 led to a recall of 92.35% and a precision of 89.3%. Also, a test was conducted using PMI-IR (Pointwise Mutual Information - Information Retrieval) out of those methods suggested in English studies, which resulted in a recall of 55% and a precision of 57%.
In this paper, we present an approach to sentence boundary detection for web documents that builds on statistical-based methods and uses rule-based correction. The proposed system uses the classification model learned offline using a training set of human-labeled web documents. The web documents have many word-spacing errors and frequently no punctuation mark that indicates the end of sentence boundary. As sentence boundary candidates, the proposed method considers every Ending Eomis as well as punctuation marks. We optimize engine performance by selecting the best feature, the best training data, and the best classification algorithm. For evaluation, we made two test sets; Set1 consisting of articles and blog documents and Set2 of web community documents. We use F-measure to compare results on a large variety of tasks, Detecting only periods as sentence boundary, our basis engine showed 96.5% in Set1 and 56.7% in Set2. We improved our basis engine by adapting features and the boundary search algorithm. For the final evaluation, we compared our adaptation engine with our basis engine in Set2. As a result, the adaptation engine obtained improvements over the basis engine by 39.6%. We proved the effectiveness of the proposed method in sentence boundary detection.
The goal of Natural Language Processing(NLP) is to make a computer understand a natural language and to deliver the meanings of natural language to humans. Word sense Disambiguation(WSD is a very important technology to achieve the goal of NLP. In this paper, we describe a technology for automatic homonyms disambiguation using both Mutual Information(MI) and a Sense-Tagged Compound Noun Dictionary. Previous research work using word definitions in dictionary suffered from the problem of data sparseness because of the use of exact word matching. Our work overcomes this problem by using MI which is an association measure between words. To reflect language features, the rate of word-pairs with MI values, sense frequency and site of word definitions are used as weights in our system. We constructed a Sense-Tagged Compound Noun Dictionary for high frequency compound nouns and used it to resolve homonym sense disambiguation. Experimental data for testing and evaluating our system is constructed from QA(Question Answering) test data which consisted of about 200 query sentences and answer paragraphs. We performed 4 types of experiments. In case of being used only MI, the result of experiment showed a precision of 65.06%. When we used the weighted values, we achieved a precision of 85.35% and when we used the Sense-Tagged Compound Noun Dictionary, we achieved a precision of 88.82%, respectively.
Akhaveissy, A.H.;Desai, C.S.;Mostofinejad, D.;Vafai, A.
Computers and Concrete
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v.11
no.2
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pp.123-148
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2013
The nonlinear finite element method with eight noded isoparametric quadrilateral element for concrete and two noded element for reinforcement is used for the prediction of the behavior of reinforcement concrete structures. The disturbed state concept (DSC) including the hierarchical single surface (HISS) plasticity model with associated flow rule with modifications is used to characterize the constitutive behavior of concrete both in compression and in tension which is named DSC/HISS-CT. The HISS model is applied to shows the plastic behavior of concrete, and DSC for microcracking, fracture and softening simulations of concrete. It should be noted that the DSC expresses the behavior of a material element as a mixture of two interacting components and can include both softening and stiffening, while the classical damage approach assumes that cracks (damage) induced in a material treated acts as a void, with no strength. The DSC/HISS-CT is a unified model with different mechanism, which expresses the observed behavior in terms of interacting behavior of components; thus the mechanism in the DSC is much different than that of the damage model, which is based on physical cracks which has no strength and interaction with the undamaged part. This is the first time the DSC/HISS-CT model, with the capacity to account for both compression and tension yields, is applied for concrete materials. The DSC model allows also for the characterization of non-associative behavior through the use of disturbance. Elastic perfectly plastic behavior is assumed for modeling of steel reinforcement. The DSC model is validated at two levels: (1) specimen and (2) practical boundary value problem. For the specimen level, the predictions are obtained by the integration of the incremental constitutive relations. The FE procedure with DSC/HISS-CT model is used to obtain predictions for practical boundary value problems. Based on the comparisons between DSC/HISS-CT predictions, test data and ANSYS software predictions, it is found that the model provides highly satisfactory predictions. The model allows computation of microcracking during deformation leading to the fracture and failure; in the model, the critical disturbance, Dc, identifies fracture and failure.
Park, Hyong-Hu;Park, Ji-Koon;Choi, Il-Hong;Kang, Sang-Sik;Noh, Si-Cheol;Jung, Bong-Jae
Journal of the Korean Society of Radiology
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v.10
no.2
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pp.81-87
/
2016
In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some fatty liver patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of fatty liver. As the results of examining over 30 example CT images of fatty liver, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including Average Gray Level, Entropy 96.67%, Skewness 93.33%, and Smoothness while others showed a little low disease recognition rate: 83.33% for Uniformity 86.67% and for Average Contrast 80%. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of fatty liver and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.
In this paper, we developed a MTF (Modulation Transfer Function) measurement system using a knife-edge scanning method for infrared optics. It consists of an objective part to generate the target image, a collimator to make the beam parallel, and a detector to analyze the image. We used a tungsten filament as the light source and MCT (Mercury Cadmium Telluride) to detect the mid-infrared(wavelength $3-5{\mu}m$) image. We measured the MTF of a standard lens (f=5, material ZnSe) to test this instrument and compared the result to the theoretical value calculated using the ZEMAX commercial software. It was found that the difference was within ${\pm}0.035$ at the cut-off frequency (50 1/mm). Also, we calculated the A-type measurement uncertainty to check the reliability of the measurement. The result showed only 0.002 at 20 1/mm in spatial frequency, which means very little variation in the MTF measurement under the same conditions.
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