• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.1-9
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• 2021

3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, due to the nature of the lamination process, there is a problem that the frequency of error occurrence may vary depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of write/erase(P/E) operations of the flash memory increases. Most flash-based storage devices such as SSDs use ECC for error correction. Since this method provides a fixed strength of data protection for all flash memory pages, it has limitations in 3D NAND flash memory, where the error rate varies depending on the physical location. Therefore, in this paper, pages and layers with different error rates are classified into clusters through the K-means machine learning algorithm, and differentiated data protection strength is applied to each cluster. We classify pages and layers based on the number of errors measured after endurance test, where the error rate varies significantly for each page and layer, and add parity data to stripes for areas vulnerable to errors to provides differentiate data protection strength. We show the possibility that this differentiated data protection policy can contribute to the improvement of reliability and lifespan of 3D NAND flash memory compared to the protection techniques using RAID-like or ECC alone.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.61-68
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• 2018

In this paper, we propose a method of character detection by analyzing image enhancement and character type to detect characters in natural images that can be acquired in everyday life. The proposed method emphasizes the boundaries of the object part using the unsharp mask in order to improve the detection rate of the area to be recognized as a character in a natural image. By using the boundary of the enhanced object, the character candidate region of the image is detected using Maximal Stable Extermal Regions (MSER). In order to detect the region to be judged as a real character in the detected character candidate region, the shape of each region is analyzed and the non-character region other than the region having the character characteristic is removed to increase the detection rate of the actual character region. In order to compare the objective test of this paper, we compare the detection rate and the accuracy of the character region with the existing methods. Experimental results show that the proposed method improves the detection rate and accuracy of the character region over the existing character detection method.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.43-59
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• 2019

Today, with the spread of smartphones and the development of social networking services, structured and unstructured big data have stored exponentially. If we analyze them well, we will get useful information to be able to predict data for the future. Large amounts of data need to be collected first in order to analyze big data. The web is repository where these data are most stored. However, because the data size is large, there are also many data that have information that is not needed as much as there are data that have useful information. This has made it important to collect data efficiently, where data with unnecessary information is filtered and only collected data with useful information. Web crawlers cannot download all pages due to some constraints such as network bandwidth, operational time, and data storage. This is why we should avoid visiting many pages that are not relevant to what we want and download only important pages as soon as possible. This paper seeks to help resolve the above issues. First, We introduce basic web-crawling algorithms. For each algorithm, the time-complexity and pros and cons are described, and compared and analyzed. Next, we introduce the state-of-the-art web crawling algorithms that have improved the shortcomings of the basic web crawling algorithms. In addition, recent research trends show that the web crawling algorithms with special purposes such as collecting sentiment words are actively studied. We will one of the introduce Sentiment-aware web crawling techniques that is a proactive web crawling technique as a study of web crawling algorithms with special purpose. The result showed that the larger the data are, the higher the performance is and the more space is saved.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.67-77
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• 2018

Currently, there are many problems due to the decline in school-age population. Moreover, Korea has the largest number of universities compared to the population, and the university enrollment rate is also the highest in the world. As a result, the minimum student retention rate required for the survival of each university is becoming increasingly important. The purpose of this study was to examine the effects of reducing the number of graduates of education and the social climate that prioritizes employment. And to determine what the basic direction is for students to manage the student retention rate, which can be maintained from admission to graduation, to determine the optimal input variables, Based on the input parameters, we will make associative analysis using apriori algorithm to collect training data that is most suitable for maintenance rate management and make base data for development of the most efficient Deep Learning module based on it. The accuracy of Deep Learning was 75%, which is a measure of graduation using decision trees. In decision tree, factors that determine whether to graduate are graduated from general high school and students who are female and high in residence in urban area have high probability of graduation. As a result, the Deep Learning module developed rather than the decision tree was identified as a model for evaluating the graduation of students more efficiently.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.7-13
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• 2019

This study aims to develop a FE Model to simulate dissimilar friction stir welding and to address its potential for fundamental analysis and practical applications. The FE model is based on Coupled Eulerian-Lagrangian approach. Multiphysics systems are calculated using explicit time integration algorithm, and heat generations by friction and inelastic heat conversion as well as heat transfer through the bottom surface are included. Using the developed model, friction stir welding between an Al6061T6 plate and an AZ61 plate were simulated. Three simulations are carried out varying the welding parameters. The model is capable of predicting the temperature and plastic strain fields and the distribution of void. The simulation results showed that temperature was generally greater in Mg plates and that, as a rotation speed increase, not the maximum temperature of Mg plate increased, but did the temperature of Al plate. In addition, the model could predict flash defects, however, the prediction of void near the welding tool was not satisfactory. Since the model includes the complex physics closely occurring during FSW, the model possibly analyze a lot of phenomena hard to discovered by experiments. However, practical applications may be limited due to huge simulation time.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1301-1308
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• 2018

90/150 CA which are used as key generators of the cipher system have more randomness than LFSRs, but synthesis methods of 90/150 CA are difficult. Therefore, 90/150 CA synthesis methods have been studied by many researchers. In order to synthesize a suitable CA, the analysis of the characteristic polynomial of 90/150 CA should be preceded. In general, the characteristic of polynomial ${\Delta}_n$ of n cell 90/150 CA is obtained by using ${\Delta}_{n-1}$ and ${\Delta}_{n-2}$. Choi et al. analyzed $H_{2^n}(x)$ and $H_{2^n-1}(x)$, where $H_k(x)$ is the characteristic polynomial of k cell 90/150 CA with state transition rule <$10{\cdots}0$>. In this paper, we propose an efficient method to obtain $H_n(x)$ from $H_{n-1}(x)$ and an efficient algorithm to obtain $H_{2^n+i}(x)$ and $H_{2^n-i}(x)$ ($1{\leq}i{\leq}2^{n-1}$) from $H_{2^n}(x)$ by using this method.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1143-1153
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• 2018

For TOPS InSAR processing, high-precision image co-registration is required. We propose an image co-registration method suitable for the TOPS mode by comparing the performance of cross correlation method, the geometric co-registration and the enhanced spectral diversity (ESD) matching algorithm based on the spectral diversity (SD) on the Sentinel-1 TOPS mode image. Using 23 pairs of interferometric pairs generated from 25 Sentinel-1 TOPS images, we applied the cross correlation (CC), geometric correction with only orbit information (GC1), geometric correction combined with iterative cross-correlation (GC2, GC3, GC4), and ESD iteration (ESD_GC, ESD_1, ESD_2). The mean of co-registration errors in azimuth direction by cross correlation and geometric matching are 0.0041 pixels and 0.0016 pixels, respectively. Although the ESD method shows the most accurate result with the error of less than 0.0005 pixels, the error of geometric co-registration is reduced to 0.001 pixels by repetition through additional cross correlation matching between the reference and resampled slave image. The ESD method is not applicable when the coherence of the burst overlap areas is low. Therefore, the geometric co-registration method through iterative processing is a suitable alternative for time series analysis using multiple SAR data or generating interferogram with long time intervals.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.11-20
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• 2019

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.918-925
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• 2017

Multiple reflections on exterior equipment with complex shape on naval ships cause unexpectedly high Radar Cross Section (RCS) distributions, and the directions of reradiated electromagnetic waves are hard to predict. Therefore, the optimum arrangement of exterior equipments should be considered according to the Radar Absorbing Structure (RAS) method. In this paper, the optimum arrangement for exterior equipments was determined to reduce multiple reflections and RCS even with complex shapes. The sequential descending arrangement method was used to establish an optimum arrangement algorithm. An LCS-2 type model was selected for optimum exterior equipment arrangements. In order to reduce computational cost, RCS distributions and multiple reflection path analysis of exterior equipments was carried out to select exterior equipments for optimum arrangement, and an optimum arrangement was determined to find positions with minimum RCS values. Also, the RCS reduction effect was analyzed using detectable radar range.