• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.4
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• pp.55-66
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• 1993

Upon freezing a soil swells due to phase change and its compression stress increase a lot. As the soil undergo thawing, however, it becomes a soft soil layer because the 'soil changes from a solid state to a plastic state. These changes are largely dependent on freezing temperature and repeated freezing-thawing cycle as well as the density of the soil and applied loading condition. This study was initiated to describe the effect of the freezing temperature and repeated freezing-thawing cycle on the unconfined compressive strength. Soil samples were collected at about 20 sites where soil structures were installed in Kangwon provincial area and necessary laboratory tests were conducted. The results could be used to help manage effectively the field structures and can be used as a basic data for designing and constructing new projects in the future. The results were as follows ; 1. Unconfined compressive strength decreased as the number of freezing and thawing cycle went up. But the strength increased as compression speed, water content and temperature decreased. The largest effect on the strength was observed at the first freezing and thawing cycle. 2. Compression strain went up with the increase of deformation speed, and was largely influenced by the number of the freezing-thawing cycle. 3. Secant modulus was responded sensitivefy to the material of the loading plates, increased with decrease of temperature down to - -10$^{\circ}$C, but was nearly constant below the temperature. Thixotropic ratio characteristic became large as compression strain got smaller and was significantly larger in the controlled soil than in the soil treated with freezing and thawing processes 4. Vertical compression strength of ice crystal(development direction) was 3 to 4 times larger than that of perpendicular to the crystal. The vertical compression strength was agreed well with Clausius-Clapeyrons equation when temperature were between 0 to 5C$^{\circ}$, but the strength below - 5$^{\circ}$C were different from the equation and showed a strong dependency on temperature and deformation speed. When the skew was less then 20 degrees, the vertical compression strength was gradually decreased but when the skew was higher than that, the strength became nearly constant. Almost all samples showed ductile failure. As considered above, strength reduction of the soil due to cyclic freezing-thawing prosses must be considered when trenching and cutting the soil to construct soil structures if the soil is likely subject to the processes. Especially, if a soil no freezing-thawing history, cares for the strength reduction must be given before any design or construction works begin. It is suggested that special design and construction techniques for the strength reduction be developed.

• Parasites, Hosts and Diseases
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• v.35 no.3
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• pp.197-202
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• 1997

Diagnosis of early paragonimiasis is difficult because parasitological evidence is not easily obtained. Antibody tests have been proposed as a good substitute for classical diagnostic techniques. Using the crude extracts of Parnsonimus westermnni eggs, metacercariae. 4- and 7-week Juveniles, and 16-week adults as antigens, we observed the early antibody responses. Sera were obtained from 4 experimental cats, fed 50 metacercariae each, at intervals until 13 weeks post-infection. Antibody (IgG) responses were identified by ELISA using extracts of 4-week juveniles, followed by those of 7- and 16-week worms. Antibody responses were minimal against the metacercarial extracts. Antibodies to p. westemoni egg extracts were elevated after 10 weeks post-infection. In immunoblot analysis, more than nine protein bands in 4-week juveniles reacted with the early infection sera. Antigenic proteins in adult worms were different from those of juveniles. After four weeks of infection, 32 and 35 kDa bands in the adult extracts were increasingly reactive. Egg specific proteins at 28, 46 and 94 kDa were reactive only after 10 weeks. Antigenic components reactin료 to the early infection sera changed during the maturation stages of P. westermani; almost all juvenile antigens were replaced by adult antigen components.

• Parasites, Hosts and Diseases
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• v.42 no.1
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• pp.41-44
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• 2004

The pond smelt Hypomesus olidus and minnow Zacco platypus were collected from the Soyang and Daechung Lakes in January 2003, and their metacercarial infections was examined by the muscle compression and artificial digestion techniques. In the Soyang Lake, 161 metacercariae of Clonorchis sinensis (0.35 per fish) were harvested from 459 pond smelts examined. Also, 13 metacercariae of C. sinensis (0.43 per fish), 1 of Metagonimus sp., 4 of Echinostoma sp., 148 of Centrocestus armatus and 44 unidentified species were collected from 30 minnows. In the Daechung Lake, 369 metacercariae of C. sinensis (3.69 per fish) and 51 unidentified species were recovered from 100 pond smelts. The metacercariae of C. sinensis were fed to experimental rats, in which the adult flukes were identified. The pond smelts and minnows collected from the Soyang and Daechung Lakes were verified to be the second intermediate hosts and the sources of human C. sinensis infection.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.101-113
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• 2007

The period of military personnel service will be phased down by 2014 according to 'The law of National Defense Reformation' issued by the Ministry of National Defense. For this reason, the ROK army provides discrimination education to 'newly recruited privates' for more effective individual performance in the on-the-job training. For the training to be more effective, it would be essential to predict the degree of achievements by new privates in the training. Thus, we used data mining techniques to develop a classification model which classifies the new privates into one of two achievements groups, so that different skills of education are applied to each group. The target variable for this model is a binary variable, whose value can be either 'a group of general control' or 'a group of special control'. We developed four pure classification models using Neural Network, Decision Tree, Support Vector Machine and Naive Bayesian. We also built four hybrid models, each of which combines k-means clustering algorithm with one of these four mining technique. Experimental results demonstrated that the highest performance model was the hybrid model of k-means and Neural Network. We expect that various military education programs could be supported by these classification models for better educational performance.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.10
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• pp.520-529
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• 2005

A feature-based 3D modeling algorithm is presented in this paper. Since conventional methods use depth-based techniques, they need much time for the image matching to extract depth information. Even feature-based methods have less computation load than that of depth-based ones, the calculation of modeling error about whole pixels within a triangle is needed in feature-based algorithms. It also increase the computation time. Therefore, the proposed algorithm consists of three phases, which are an initial 3D model generation, model evaluation, and model refinement phases, in order to acquire an efficient 3D model. Intensity gradients and incremental Delaunay triangulation are used in the Initial model generation. In this phase, a morphological edge operator is adopted for a fast edge filtering, and the incremental Delaunay triangulation is modified to decrease the computation time by avoiding the calculation errors of whole pixels and selecting a vertex at the near of the centroid within the previous triangle. After the model generation, sparse vertices are matched, then the faces are evaluated with the size, approximation error, and disparity fluctuation of the face in evaluation stage. Thereafter, the faces which have a large error are selectively refined into smaller faces. Experimental results showed that the proposed algorithm could acquire an adaptive model with less modeling errors for both smooth and abrupt areas and could remarkably reduce the model acquisition time.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.116-124
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• 2011

In this study, a new method to estimate the bridge deflection is developed by using Wireless Tilt Sensor. Most of evaluations of structural integrity, it is very important to measure the geometric profile, which is a major factor representing the global behavior of civil structure, especially bridges. In the past, Because of the lack of appropriate methods to measure the deflection curve of bridges on site, the measurement of deflection had been done restrictly within just a few discrete points along the bridge. Also the measurement point could be limited to locations installed with displacement transducers. So, in this study, the deflection of the structure was measured by wireless tilt sensor instead of LVDT(Linear Variable Differential Transformer). Angle change of tilt sensor shows structural behavior by the change of the resistor values which is presented to voltage. Moreover, the maximum deflection was calculated by changing the deflection angle which was calculated as V(measured voltage) ${\times}$F(factor) to deflection. The experimental tests were carried out to verify the developed deflection estimation techniques. Because the base of tilt measuring is the gravity, uniform measurement is possible independent of a measuring point. Also, measuring values were showed very high accuracy.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.350-365
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• 2017

Steganography is a technique for secret data communication, which is not perceived by third person between a receiver and a transmitter. It has been developed for thousands of years for the transmission of military, diplomatic or business information. The development of digital media and communication has led to the development of steganography techniques in modern times. Technic of image steganography include the LSB, which fixes the number of embedded bits into a pixel, and PVD, which exploits the difference value in the neighboring pixel pairs. In the case of PVD image steganography, a large amount of information is embedded fluidly by difference value in neighboring pixel pairs and the designed range table. However, since the secret information in order is embedded, if an error of the number of embedded bits occurs in a certain pixel pair, all subsequent information will be destroyed. In this paper, we proposes the method, which improve the vulnerability of PVD property about external attack or various noise and extract secret information. Experimental process is comparison analysis about stego-image, which embedded various noise. PVD shows that it is not possible to preserve secret information at all about noise, but it was possible to robustly extract secret information for partial noise of stego-image in case of the proposed PVD image steganography with locally-fixed number of embedding bits.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.137-142
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• 2010

Although multi-model speech recognizer has been shown to be quite successful in noisy speech recognition, the results were based on general speech front-ends which do not take into account noise adaptation techniques. In this paper, for the accurate evaluation of the multi-model based speech recognizer, we adopted a quite noise-robust speech front-end, AFE, which was proposed by the ETSI for the noisy DSR environment. For the performance comparison, the MTR which is known to give good results in the DSR environment has been used. Also, we modified the structure of the multi-model based speech recognizer to improve the recognition performance. N reference HMMs which are most similar to the input noisy speech are used as the acoustic models for recognition to cope with the errors in the selection of the reference HMMs and the noise signal variability. In addition, multiple SNR levels are used to train each of the reference HMMs to improve the robustness of the acoustic models. From the experimental results on the Aurora 2 databases, we could see better recognition rates using the modified multi-model based speech recognizer compared with the previous method.

• Journal of the Korean Geographical Society
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• v.31 no.2
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• pp.329-345
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• 1996

The purposes of this study are to review research trends of applied geography field, to retrospect geographical works done by Korean geographers in applied geography, and to prospect the future of applied geography. We are in the period where societal problems such as energy, transportation, pollution, environment, health care, and many others, require careful consideration and need throughout strategies for solution. Most societal problems have some geographical dimensions. Because these problems are geographic in nature, there is an obvious implication that geography as a discipline has something to offer in their solutions. In fact, most geographic problems are best presented and analyzed through the applications of geographic theories, concepts and tools. Applied geography is a branch of general geography. It relies on the scientific methods and uses the principles and methods of pure geography. However applied geography is different in that it analyzes and evaluates real world action and planning and seeks to implement and manipulate environmental and spatial realities. Thus, geographic theories and other social theories that have geographic dimensions are fundamental to applied geography. Applied geography has a short history as theme in Korean geography. During the last two decades. Korea achieved remarkable economic growth. We have also encountered widening regional disparity, housing shortage of larger cities, transportation congestion, environmental pollution and many other problems. Applied geographers have tried to analyze and solve such spatial problems during the last 30 years. The research trend of Korean applied geography can be subdivided into 5 categories: (1) land use analysis and efficient utilization, (2) national physical development and planning. (3) regional development and regional planning, (4) tourism and location-allocation, transportation planning. Still the overconcentration of Seoul metropolitan region and unbalanced regional development are perceived to be the serious spatial problems which may induce more works to solve these problems. In Korea new emphasis has to be given to some professional training and experimental learning, including methodology, field techniques data management, statistical analysis, cartography, GIS, and other tools, as applicable and beneficial to problem solving in real world. The growth of applied geography depends on new insights and purposed solutions of future applied geographers in Korea. Applied geographers will contribute to the creation of future Korean geographies.