• Journal of Magnetics
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• v.21 no.2
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• pp.286-292
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• 2016

This study evaluates the change of computer tomography (CT) number in the case of the metal artifact reduction (MAR) algorithm, using the phantom. The images were obtained from dual CT using a gammex 467 tissue characterization phantom, which is similar to human tissues. The test method was performed by dividing pre and post MAR algorithm and measured CT values of nonmagnetic materials within the phantom. In addition, the changes of CT values for each material were compared and analyzed after measuring CT values up to 140 keV, using the spectral HU curve followed by CT scan. As a result, in the cases of N rod (trabecular bone) and E rod (trabecular bone), the CT numbers decreased as keV increasing but were constant above 90 keV. In the cases of I rod (dense bone) and K rod (dense bone), the CT numbers also decreased as keV increased but were uniform above 90 keV. The CT numbers from 40 keV to 140 keV were consistent in the cases of J rod (liver), D rod (liver), L rod (muscle), and F rod (muscle). For A rod (adipose), G rod (adipose), B rod (breast) and O rod (breast), the CT numbers increased as keV increased but were constant after 90 keV. The CT numbers from 40 keV to 140 keV were consistent in the cases of C rod (lung (exhale)), P rod (lung (exhale)), M rod (lung (inhale)) and H rod (lung (exhale)). Conclusively, because dual CT exhibits no changes in image quality and is able to analyze nonmagnetic materials by measuring the CT values of various materials, it will be used in the future as a useful tool for the diagnosis of lesions.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.239-254
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• 2006

Location-based advertising or application has been one of the drivers of third-generation mobile operators' marketing efforts in the past few years. As a result, many studies on location-based marketing or advertising have been proposed for recent several years. However, these approaches have two common shortcomings. First. most of them just suggested the theoretical architectures, which were too abstract to apply it to the real-world cases. Second, many of these approaches only consider service provider (seller) rather than customers (buyers). Thus, the prior approaches fit to the automated sales or advertising rather than the implementation of CRM. To mitigate these limitations, this study presents a novel advertisement recommendation model for mobile users. We call our model MAR-CF (Mobile Advertisement Recommender using Collaborative Filtering). Our proposed model is based on traditional CF algorithm, but we adopt the multi-dimensional personalization model to conventional CF for enabling location-based advertising for mobile users. Thus, MAR-CF is designed to make recommendation results for mobile users by considering location, time, and needs type. To validate the usefulness of our recommendation model. we collect the real-world data for mobile advertisements, and perform an empirical validation. Experimental results show that MAR-CF generates more accurate prediction results than other comparative models.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.497-503
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• 2018

The purpose of this study was to investigate the degree of image degradation and the improvement of image quality caused by the density difference between the orthodontic filling material and the surrounding anatomical structure during the examination of the facial CT by quantitative and qualitative analysis. The teeth were scanned using 64-MDCT (Discovery 750 HD, GE HEALTH CARE, Milwaukee, USA). The teeth were scanned and compared according to tube voltage, silicone application, and MAR application. As a result, 10.36% CT value decreased at 140 kVp and 5.81% decrease at the application of silicon material. As a result of the qualitative evaluation, it was evaluated that 7 of the 10 observers and 3 of the acceptors were applied to the MAR algorithm. Therefore, it is possible to reduce the unnecessary burden on the radiation exposure dose as well as to reduce the loss of image data by reducing the high density artifacts, as well as the inspection parameters used in the current clinical application and various algorithms that can reduce the high density artifacts. It can be expected to provide a lot of image information.

• Korean Management Science Review
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• v.26 no.1
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• pp.65-76
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• 2009

The undirected Steiner tree problem in graphs is known to be NP-hard. The objective of this problem is to find a shortest tree containing a subset of nodes, called terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step. graph reduction rules eliminate useless nodes and edges which do not contribute to make an optimal solution. In the second step, a max-min ant colony optimization combined with Prim's algorithm is developed to solve the reduced problem. The proposed algorithm is tested in the sets of standard test problems. The results show that the algorithm efficiently presents very correct solutions to the benchmark problems.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.245-254
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• 2021

We proposed the research on an analysis and prediction model that allows the identification of outliers or abnormality in the data followed by effective and rapid imputation of missing values was conducted. This model is expected to analyze efficiently the problems in the data based on the calibrated raw data. As a result, a system that can adequately utilize the data was constructed by using the introduced KNN + MLE algorithm. With this algorithm, the problems in some of the existing KNN-based missing data imputation algorithms such as ignoring the missing values in some data sections or discarding normal observations were effectively addressed. A comparative evaluation was performed between the existing imputation approaches such as K-means, KNN, MEI, and MI as well as the data missing mechanisms including MCAR, MAR, and NI to check the effectiveness/efficiency of the proposed algorithm, and its superiority in all aspects was confirmed.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.315-330
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• 2017

Halo coronal mass ejections (CMEs) originating from solar activities give rise to geomagnetic storms when they reach the Earth. Variations in the geomagnetic field during a geomagnetic storm can damage satellites, communication systems, electrical power grids, and power systems, and induce currents. Therefore, automated techniques for detecting and analyzing halo CMEs have been eliciting increasing attention for the monitoring and prediction of the space weather environment. In this study, we developed an algorithm to sense and detect halo CMEs using large angle and spectrometric coronagraph (LASCO) C3 coronagraph images from the solar and heliospheric observatory (SOHO) satellite. In addition, we developed an image processing technique to derive the morphological and dynamical characteristics of halo CMEs, namely, the source location, width, actual CME speed, and arrival time at a 21.5 solar radius. The proposed halo CME automatic analysis model was validated using a model of the past three halo CME events. As a result, a solar event that occurred at 03:38 UT on Mar. 23, 2014 was predicted to arrive at Earth at 23:00 UT on Mar. 25, whereas the actual arrival time was at 04:30 UT on Mar. 26, which is a difference of 5 hr and 30 min. In addition, a solar event that occurred at 12:55 UT on Apr. 18, 2014 was estimated to arrive at Earth at 16:00 UT on Apr. 20, which is 4 hr ahead of the actual arrival time of 20:00 UT on the same day. However, the estimation error was reduced significantly compared to the ENLIL model. As a further study, the model will be applied to many more events for validation and testing, and after such tests are completed, on-line service will be provided at the Korean Space Weather Center to detect halo CMEs and derive the model parameters.

• ETRI Journal
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• v.29 no.4
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• pp.530-532
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• 2007

This paper presents a simple method to implement a complete on-line portable wireless holter including an electrocardiogram (ECG) monitoring, processing, and communication protocol. The proposed algorithm significantly reduces the hardware resources of threshold estimation for ECG compression, using the standard deviation updated with each new input signal sample. The new method achieves superior performance in terms of hardware complexity, channel occupation and memory requirements, while keeping the ECG quality at a clinically acceptable level.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1749-1758
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• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.6
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• pp.498-508
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• 1991

This thesis presents a performance analysis algorithm that estimates erro performance of individual links, at the bit level, in an end-to-end digital connection using the model of 3-statte MarKov chain. The link model proposed the burst error behavior of each individual link. It also presents a method to concateante several individual links and extract a model for end-to-end digital connection. This resulting end-to-end model can be used to calculate performance parameters such as bit error rate(BER) and block error(BLER) for any block size.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.575-584
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• 2021

This study contains the process of developing a Mission Planning System (MPS) of an USV that can be applied in real situations and verifying them through HILS. In this study, we set the scenario of a single USV with limited operating time. Since the USV may not perform some missions due to the limited operating time, an objective function was defined to maximize the Mission Achievement Rate (MAR). We used a genetic algorithm to solve the problem model, and proposed a method using a 3-D population. The simulation showed that the probability of deriving the global optimal solution of the mission planning algorithm was 96.6% and the computation time was 1.6 s. Furthermore, USV showed it performs the mission according to the results of the MPS. We expect that the MPS developed in this study can be applied to the real environment where USV performs missions with limited time conditions.