• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.361-367
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• 2008

When constructing a synthetic seismogram in the earthquake study or in seismic data interpretation by using a ray-tracing technique, the most troublesome and error-prone task is to define a suite of ray codes for the corresponding rays to trace in advance. An infinite number of rays exist for any arbitrarily located source and receiver in a medium. Missing certain important rays or an inappropriate selection of ray codes in tracing rays may result in wrong interpretation of the earthquake record or seismogram. Automatic ray code generation could be able to eliminate those problems. In this study we have developed an efficient algorithm with which one can generate systematically all the ray codes for the source(s) and receiver(s) arbitrarily located in a model. The result of this work could be used not only in analysing multiples in seismic data processing and interpretation, but also in coda wave study, study on the amplification effects in a basin and phase identification of the waves multiply reflected/refracted in earthquake study.

• The Korean Journal of Rheology
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• v.11 no.1
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• pp.1-8
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• 1999

This paper experimentally investigates the steady shear behaviors of electro-rheological(ER) fluids under flow mode at high pressure level. As for the ER fluid to be tested, two types of ER fluids are employed; water-based ER fluids (ERF 1, ERF 2) and water-free ER fluid(ERF 3). The water-based ER fluids are composed inhousingly, and the concentrations of dispersed particles are 20 wt% and 30 wt% for ERF 1 and ERF 2, respectively. To generate the flow mode at high pressure, an experimental apparatus operated by two-way hydraulic cylinder is constructed and utilized. The pressure difference is measured by the pressure sensor, while the flow rate is calculated using the measured data of the displacement sensor(LVDT). Consequently, the shear stress and shear rate are distilled by incorporating the measured data; the pressure difference and the flow rate.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1052-1061
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• 2006

This paper presents a method of using virtual examples to improve the classification accuracy for data with nominal attributes. Most of the previous researches on virtual examples focused on data with numeric attributes, and they used domain-specific knowledge to generate useful virtual examples for a particularly targeted learning algorithm. Instead of using domain-specific knowledge, our method samples virtual examples from a naive Bayesian network constructed from the given training set. A sampled example is considered useful if it contributes to the increment of the network's conditional likelihood when added to the training set. A set of useful virtual examples can be collected by repeating this process of sampling followed by evaluation. Experiments have shown that the virtual examples collected this way.can help various learning algorithms to derive classifiers of improved accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.24-36
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• 2003

This study integrates the revised universal soil loss equation(RUSLE) with a grid-based GIS method to assess the potential risk of soil erosion at the watershed scale. Data used in this study to generate the RUSLE factors include several thematic maps such as land use, topographic and soil maps, together with tabular precipitation data. Based on the RUSLE estimation for all the grids(10m cells) in the corresponding watershed, a cumulative histogram for the annual soil loss can be constructed. As the results, it shows that the 83.5% value of the annual soil loss for the watershed is less than 1ton/ha. However, the above 30% of agricultural land is defined as a medium or very high-risk area(more than 10ton/ha/yr). So it is necessary to establish soil conservation practices to reduce soil erosion based on the field observations.

• Wind and Structures
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• v.12 no.4
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• pp.383-400
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• 2009

Low rise building roofs can be subjected to large fluctuating pressures during a tropical cyclone resulting in fatigue failure of cladding. Following the damage to housing in Tropical Cyclone Tracy in Darwin, Australia, the Darwin Area Building Manual (DABM) cyclic loading test criteria, that loaded the cladding for 10000 cycles oscillating from zero to a permissible stress design pressure, and the Experimental Building Station TR440 test of 10200 load cycles which increased in steps to the permissible stress design pressure, were developed for assessing building elements susceptible to low cycle fatigue failure. Recently the 'Low-High-Low' (L-H-L) cyclic test for metal roofing was introduced into the Building Code of Australia (2007). Following advances in wind tunnel data acquisition and full-scale wind loading simulators, this paper presents a comparison of wind-induced cladding damage, from a "design" cyclone proposed by Jancauskas, et al. (1994), with current test criteria developed by Mahendran (1995). Wind tunnel data were used to generate the external and net pressure time histories on the roof of a low-rise building during the passage of the "design" cyclone. The peak pressures generated at the windward roof corner for a tributary area representative of a cladding fastener are underestimated by the Australian/New Zealand Wind Actions Standard. The "design" cyclone, with increasing and decreasing wind speeds combined with changes in wind direction, generated increasing then decreasing pressures in a manner similar to that specified in the L-H-L test. However, the L-H-L test underestimated the magnitude and number of large load cycles, but overestimated the number of cycles in the mid ranges. Cladding elements subjected to the L-H-L test showed greater fatigue damage than when experiencing a five hour "design" cyclone containing higher peak pressures. It is evident that the increased fatigue damage was due to the L-H-L test having a large number of load cycles cycling from zero load (R=0) in contrast to that produced during the cyclone.

• The korean journal of orthodontics
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• v.43 no.2
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• pp.54-61
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• 2013

Objective: The purpose of this study was to evaluate the effectiveness of the use of Reference Ear Plug (REP) during cone-beam computed tomography (CBCT) scan for the generation of lateral cephalograms from CBCT scan data. Methods: Two CBCT scans were obtained from 33 adults. One CBCT scan was acquired using conventional methods, and the other scan was acquired with the use of REP. Virtual lateral cephalograms created from each CBCT image were traced and compared with tracings of the real cephalograms obtained from the same subject. Results: CBCT scan with REP resulted in a smaller discrepancy between real and virtual cephalograms. In comparing the real and virtual cephalograms, no measurements significantly differed from real cephalogram values in case of CBCT scan with REP, whereas many measurements significantly differed in the case of CBCT scan without REP. Conclusion: Measurements from CBCT-generated cephalograms are more similar to those from real cephalograms when REP are used during CBCT scan. Thus, the use of REP is suggested during CBCT scan to generate accurate virtual cephalograms from CBCT scan data.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.151-159
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• 2013

The building information should be up-to-date information and propagated rapidly for urban modeling, terrain analysis, life information, navigational system, and location-based services(LBS), hence the most recent and updated data of the building information have been required of researchers. This paper presents the developed system to extract the 3-dimension spatial information from aerial orthoimage and LiDAR data of HSI color model. In particular, this paper presents the image processing algorithm to extract the outline of specific buildings and generate the building polygon from the image using HIS color model, recursive backtracking algorithm and the search maze algorithm. Also, this paper shows the effectivity of the HIS color model in the image segmentation.

• The korean journal of orthodontics
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• v.43 no.6
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• pp.271-278
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• 2013

Objective: The purposes of this study were to determine the accuracy of crown and root length measurements of premolars using cone-beam computed tomography (CBCT) and to generate reference CBCT-based data on incisor, canine, and premolar lengths in patients with malocclusions. Methods: Imaging was performed using a CBCT scanner with a 0.292-mm voxel size and 12-bit grayscale. The CBCT-based length measurements were compared with direct measurements of 94 subsequently extracted premolars without metal restorations using the paired t-test. Furthermore, the crown and root lengths of incisors, canines, and premolars in 62 Korean patients with malocclusions were measured using CBCT, and Pearson's correlation coefficients were calculated to examine the relationship between the crown and root length measurements of each tooth type. Results: The differences between the CBCT-based and direct measurements of the extracted premolars were not significant, with 95% limits of agreement of -0.90 to 0.90 mm for crown length and -1.23 to 1.18 mm for root length. Weak positive correlations between the crown and root length measurements were observed for the mandibular canine and premolars. Conclusions: The CBCT-based measurements showed a wider range of limits of agreements for root length than for crown length. The CBCT-based data can be used as a reference for evaluating root length and resorption of teeth without metal restorations in patients with malocclusions.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.1-13
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• 2020

Machine learning refers to a model generation technique that can solve specific problems from the generalization process for given data. In order to generate a high performance model, high quality training data and learning algorithms for generalization process should be prepared. As one way of improving the performance of model to be learned, the Ensemble technique generates multiple models rather than a single model, which includes bagging, boosting, and stacking learning techniques. This paper proposes a new Ensemble technique with multiple stacking that outperforms the conventional stacking technique. The learning structure of multiple stacking ensemble technique is similar to the structure of deep learning, in which each layer is composed of a combination of stacking models, and the number of layers get increased so as to minimize the misclassification rate of each layer. Through experiments using four types of datasets, we have showed that the proposed method outperforms the exiting ones.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.38-46
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• 2020

LOw Frequency Analysis Recording (LOFAR) and Demodulation of Envelop Modulation On Noise (DEMON) grams are bearing-time-frequency plots of underwater acoustic signals, to visualize features for passive sonar. Those grams are characterized by tonal components, for which conventional data coding methods are not suitable. In this work, a novel LOFAR/DEMON gram compression algorithm based on binary map and prediction methods is proposed. We first generate a binary map, from which prediction for each frequency bin is determined, and then divide a frame into several macro blocks. For each macro block, we apply intra and inter prediction modes and compute residuals. Then, we perform the prediction of available bins in the binary map and quantize residuals for entropy coding. By transmitting the binary map and prediction modes, the decoder can reconstructs grams using the same process. Simulation results show that the proposed algorithm provides significantly better compression performance on LOFAR and DEMON grams than conventional data coding methods.