• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.175-186
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• 2021

The roles and functions of domestic public libraries are diversifying, but various problems have emerged due to internally biased book lending. In addition, due to the 4th Industrial Revolution, public libraries have introduced a book recommendation system focusing on popular books, but the variety of books that users can access is limited. Therefore, in this study, the public library unborrowed book recommendation system was implemented limiting its spatial scope to Duryu Library in Daegu City to enhance the satisfaction of public library users, by using the loan records data (213,093 cases), user information (35,561 people), etc. and utilizing methods like cluster analysis, topic modeling, content-based filtering recommendation algorithm, and conducted a survey on actual users' satisfaction to present the possibility and implications of the unborrowed book recommendation system. As a result of the analysis, the majority of users responded with high satisfaction, and was able to find the satisfaction was relatively high in the class classified by specific gender, age, occupation, and usual reading. Through the results of this study, it is expected that some problems such as biased book lending and reduced operational efficiency of public libraries can be improved, and limitations of the study was also presented.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.321-326
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• 2019

Image denoising methods based on block matching are founded on the experimental observations that neighboring patches or blocks in images retain similar features with each other, and have been proved to show superior performance in denoising different kinds of noise. The methods, however, take into account only neighboring blocks in searching for similar blocks, and ignore the characteristic features of the reference block itself. Consequently, denoising performance is negatively affected when outliers of the Gaussian distribution are included in the reference block which is to be denoised. In this paper, we propose an expanded block matching method in which noisy images are first decomposed into a number of bit-planes, then the range of true signals are estimated based on the distribution of pixels on the bit-planes, and finally outliers are replaced by the neighboring pixels belonging to the estimated range. In this way, the advantages of the conventional Gaussian filter can be added to the blocking matching method. We tested the proposed method through extensive experiments with well known test-bed images, and observed that performance gain can be achieved by the proposed method.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.339-344
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• 2022

It is about how much fine dust can be efficiently removed with respect to the electric dust collector used in factories and large facilities. The results of evaluating the fine dust removal efficiency are as follows. At 10,000 V, Efficiency method I showed 68.1 %, and Efficiency method II was 58.6 %, which was lower than that of Efficiency method I. At 5,000 V, Efficiency method I showed 57.6%, and Efficiency method II showed 51.6%, which was lower than Efficiency method I. At 2,500 V, Efficiency method I showed 50.3%, and Efficiency method II showed 24.4%, which was lower than Efficiency method I. In case of Efficiency method I, it is the efficiency calculated by using the dust concentration before and after passing through the filter. Efficiency method II calculated Efficiency method II to measure the efficiency a little more accurately in the environment where the air after the filter and the polluted air are mixed. Efficiency method II showed lower efficiency than Efficiency method I. As a result of the electrostatic precipitator test, the dust collecting performance was highest at 10,000 V, followed by 5,000 V and 2,500 V in that order.

• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.315-323
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• 2023

Marine accidents due to loss of stability of small ships have continued to increase over the past decade. In particular, since sudden winds have been pointed out as main causes of most small ship accidents, safety measures have been established to prevent them. In this regard, to prevent accidents caused by sudden winds, a systematic analysis technique is required. The aim of the present study was to develop a probabilistic approach to estimate extreme value and evaluate effects of wind on motion characteristics of ships. The present study included studies of motion analysis, extraction of extreme values, and motion characteristics. A series analysis was conducted for three conditions: wave only, wave with uniform wind speed, and wave with the NPD wind model. Hysteresis filtering and Peak-Valley filtering techniques were applied to time-domain motion analysis results for extreme value extraction. Using extracted extreme values, the goodness of fit test was performed on four distribution functions to select the optimal distribution-function that best expressed extreme values. Motion characteristics of a fishing boat were evaluated for three periodic motion conditions (Heave, Roll, and Pitch) and results were compared. Numerical analysis was performed using a commercial solver, ANSYS-AQWA.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.19-23
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• 2024

Patients with amputations of both hands need prosthetic hands that serve both cosmetic and functional purposes, and research on prosthetic hands using electromyography of remaining muscles is active, but there is still the problem of high cost. In this study, an artificial prosthetic hand was manufactured and its performance was evaluated using low-cost parts and software such as a surface electromyography sensor, machine learning software Edge Impulse, Arduino Nano 33 BLE, and 3D printing. Using signals acquired with surface electromyography sensors and subjected to digital signal processing through Edge Impulse, the flexing movement signals of each finger were transmitted to the fingers of the prosthetic hand model through training to determine the type of finger movement using machine learning. When the digital signal processing conditions were set to a notch filter of 60 Hz, a bandpass filter of 10-300 Hz, and a sampling frequency of 1,000 Hz, the accuracy of machine learning was the highest at 82.1%. The possibility of being confused between each finger flexion movement was highest for the ring finger, with a 44.7% chance of being confused with the movement of the index finger. More research is needed to successfully develop a low-cost prosthetic hand.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.243-252
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• 2020

To share an understanding of trajectory measurement in surveys using borehole, this tutorial summarizes the relevant mathematical principles of the borehole deviation survey based on coordinate transform. For uncased or open holes, calculations of the azimuth-deviation-tool face rotation using three-component accelerometer and magnetometer measurements are summarized. For the steel-cased holes, calculations are based on the time-derivative formula of the coordinate transform matrix; yaw-pitch-roll angles through time are mathematically determined by integrating the threecomponent angular velocity measurements from the gyroscope while also removing the Earth's rotation effect. Sensor and data fusion to increase the accuracy of borehole deviation survey is explained with an example of the method. These principles of borehole deviation surveys can be adapted for attitude estimation in air-borne surveys or for positioning in tunnels where global positioning system (GPS) signals cannot be accessed. Information on the optimization filter that must be incorporated in sensor fusion is introduced to help future research.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.31-39
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• 2018

In this paper, we proposed a license plate detection method based on contour extraction that adapts to environmental changes. The proposed method extracts contour lines using DoG (Difference of Gaussian) to remove unnecessary noise parts in the contour extraction process. Binarization was applied in ugly outline images, and erosion and dilation operations were used to emphasize the contour of the character part. Then, only the outline of the ratio of the characters of the plate was extracted through the ratio of the width and height of the characters. And the case where the outline is the longest is estimated by estimating the characters of the license plate. For the experiment, we applied 130 image data to license plate on the front of the vehicle, oblique environment, and environment images with various backgrounds. I also experimented with motorcycle images of different license plate patterns. Experimental results showed that the detection rate of the oblique image was 93% and that of the various background environment was 70% in the motorcycle image but 98% in the front image.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.333-340
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• 2011

KJJVC(Korea-Japan Joint VLBI Correlator) was installed at the KJCC(Korea-Japan Correlation Center) and has been operated by KASI(Korea Astronomy and Space Science Institute) from 2009. KJNC is able to correlate the VLBI observed data through KVN(Korean VLBI Network), VERA(VLBI Exploration of Radio Astrometry), and JVN(Japanese VLBI Network) and its joint network array. And it is used exclusively as computer in order to process the observed data for the scientific purpose KJJVC used the VSI(VLBI Standard Interface) as the VLBI international standard at the data input-output specification between each component. Especially, for correlating the observed data, the data is transmitted with 1024Mbps speed between Mark5B high-speed playback and RVDB(Raw VLBI Data Buffer). The EMI(Electromagnetic lnterference), which is occurred by data transmission with high-speed, cause the data loss and the loss occurrence is frequently often for long transmission cable. Finally it will be caused the data recognition error by decreasing the voltage level of digital data signal. In this paper, in order to minimize the data loss by measuring the EMI noise level in transmission of the VSI specification, the 3 methods such as 1) RC filtering method, 2) lmpedance matching using Microstrip line, and 3) Signal buffering method using Differential line driver, were proposed. To verify the effectiveness of each proposed method, the performance evaluation was conducted by implementing and simulations for each method. Each proposed method was effectively confirmed as the high-speed data transmission of the VSI specification.