• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.594-597
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• 2022

Recommendation systems are a prominent approach for users to make informed automated judgments. In terms of movie recommendation systems, there are two methods used; Collaborative filtering, which is based on user similarities; and Content-based filtering which takes into account specific user's activity. However, there are still issues with these two existing methods, and to address those, a combination of collaborative and content-based filtering is employed to produce a more effective system. In addition, various similarity methodologies are used to identify parallels among users. This paper focuses on a survey of the various tactics and methods to find solutions based on the problems of the current recommendation system.

• Convergence Security Journal
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• v.22 no.4
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• pp.179-188
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• 2022

Password authentication schemes (PAS) are the most common mechanisms used to ensure secure communication in open networks. Mathematical-based cryptographic authentication schemes such as factorization and discrete logarithms have been proposed and provided strong security features, but they have the disadvantage of high computational and message transmission costs required to construct passwords. Fairuz et al. therefore argued for an improved cryptographic authentication scheme based on two difficult fixed issues related to session key consent using the smart card scheme. However, in this paper, we have made clear through security analysis that Fairuz et al.'s protocol has security holes for Privileged Insider Attack, Lack of Perfect Forward Secrecy, Lack of User Anonymity, DoS Attack, Off-line Password Guessing Attack.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.311-322
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• 2024

In this study, we conduct an exploratory analysis of the MovieLens data, which is frequently used in many recommender system researches, to examine the detailed characteristics of the data. Also, we seek alternatives to improve the well-known neural collaborative filtering (NCF) method. NCF improved matrix factorization method by using deep neural networks in recommender systems. We devise, generalized NCF (G-NCF), a variant of NCF and test the performances. The G-NCF we propose shows superior characteristics on average performance across key evaluation metrics, compared to the NCF, but it also has a slightly larger variance in the evaluation metrics. Evaluation metrics such as MAP and nDCG were considered for comparison.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.2
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• pp.108-121
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• 2009

The suspended particulate matters have been collected on membrane filters and glass fiber filters by an 8-stage cascade impactor for 2 years (Sep. 2005${\sim}$Sep. 2007) in Kyung Hee University-Global Campus located on the border of Yongin and Suwon. The 20 chemical species (Al, Mn, Si, Fe, Cu, Pb, Cr, Ni, V, Cd, Ba, $Na^+$, ${NH_4}^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, ${NO_3}^-$, and ${SO_4}^{2-}$) were analyzed by an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on these chemical information, the PMF receptor model was applied to identify the source of ambient size-by-size particulate matters. The receptor modeling is the one of the statistical methods to achieve resonable air pollution management strategies. A total of 10 sources was identified in 9 size-ranges such as long-range transport, secondary aerosol, $NH_{4}NO_{3}$ related source, coal combustion, sea-salt, soil, oil combustion, auto emission, incineration, and biomass burning. Especially, the secondary aerosol source assorted in fine and coarse modes was intensively studied.

• Journal of Environmental Science International
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• v.17 no.10
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• pp.1155-1167
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• 2008

Chlorophyll a (chl a) has been used as an indicator for phytoplankton biomass in pelagic ecosystems due to the relative ease of measurement and selectivity for autotrophs in mixed plankton assemblages. However, the use of chi a as an indicator for phytoplankton biomass is restricted due to its inability to resolve taxonomic differences of phytoplankton and the highly variable relationship of chi a with phytoplankton. Here, we describe the analysis of High-Performance Liquid Chromatography (HPLC) photosynthetic pigment data using CHEMTAX, which is a matrix factorization program that uses chemical taxonomic indices (phytoplankton carotenoids) to quantify the abundance of phytoplankton groups. Compared to direct microscopic counting that can distinguish species within broad groups, the resolution of taxonomic groups by CHEMTAX is generally coarse. It can only distinguish between diatoms, dinoflagellates, cryptophytes, cyanobacteria, chlorophytes, prasinophytes, and haptophytes. However, CHEMTAX analysis is much faster and less expensive than microscopic counting methods. HPLC pigment observations were taken in the spring, summer, fall, and winter in$ 2005\sim2006$ within Gamak Bay, South Korea. CHEMTAX results revealed that diatoms were the dominant taxonomic group in Gamak Bay. In inner Gamak Bay, the ratio between diatoms and cryptophytes was $75\sim80%$, and the ratio between dinoflagellates and cryptophytes was $10\sim15%$. In outer Gamak Bay, the ratio between diatoms and cryptophytes was $85\sim90%$, and the ratio between dinflagellates and cryptophytes was only $1\sim5%$. The population structure was seasonal. Relative diatom populations were less in the summer than the winter season.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.404-409
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• 2001

An account of second-order fractional-step methods and boundary conditions for the incompressible Navier-Stokes equations is presented. The present work has aimed at (i) identification and analysis of all possible splitting methods of second-order splitting accuracy; and (ii) determination of consistent boundary conditions that yield second-order accurate solutions. It has been found that only three types (D, P and M) of splitting methods called the canonical methods are non-degenerate so that all other second-order splitting schemes are either degenerate or equivalent to them. Investigation of the properties of the canonical methods indicates that a method of type D is recommended for computations in which the zero divergence is preferred, while a method of type P is better suited to the cases when highly-accurate pressure is more desirable. The consistent boundary conditions on the tentative velocity and pressure have been determined by a procedure that consists of approximation of the split equations and the boundary limit of the result. The pressure boundary condition is independent of the type of fractional-step methods. The consistent boundary conditions on the tentative velocity were determined in terms of the natural boundary condition and derivatives of quantities available at the current timestep (to be evaluated by extrapolation). Second-order fractional-step methods that admit the zero pressure-gradient boundary condition have been derived. The boundary condition on the new tentative velocity becomes greatly simplified due to improved accuracy built in the transformation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.25-44
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• 2010

With the increasing popularity of mobile devices, it has become necessary to protect private information and content in these devices. Face recognition has been favored over conventional passwords or security keys, because it can be easily implemented using a built-in camera, while providing user convenience. However, because mobile devices can be used both indoors and outdoors, there can be many illumination changes, which can reduce the accuracy of face recognition. Therefore, we propose a new face recognition method on a mobile device robust to illumination variations. This research makes the following four original contributions. First, we compared the performance of face recognition with illumination variations on mobile devices for several illumination normalization procedures suitable for mobile devices with low processing power. These include the Retinex filter, histogram equalization and histogram stretching. Second, we compared the performance for global and local methods of face recognition such as PCA (Principal Component Analysis), LNMF (Local Non-negative Matrix Factorization) and LBP (Local Binary Pattern) using an integer-based kernel suitable for mobile devices having low processing power. Third, the characteristics of each method according to the illumination va iations are analyzed. Fourth, we use two matching scores for several methods of illumination normalization, Retinex and histogram stretching, which show the best and $2^{nd}$ best performances, respectively. These are used as the inputs of an SVM (Support Vector Machine) classifier, which can increase the accuracy of face recognition. Experimental results with two databases (data collected by a mobile device and the AR database) showed that the accuracy of face recognition achieved by the proposed method was superior to that of other methods.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.468-475
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• 2014

The recommend system is getting more difficult real time recommend by lager preference data set, computing power and recommend algorithm. For this reason, recommend system is proceeding actively one's studies toward distribute processing method of large preference data set. This paper studied distribute processing method of large preference data set using hadoop distribute processing platform and mahout machine learning library. The recommend algorithm is used Co-occurrence Matrix similar to item Collaborative Filtering. The Co-occurrence Matrix can do distribute processing by many node of hadoop cluster, and it needs many computation scale but can reduce computation scale by distribute processing. This paper has simplified distribute processing of co-occurrence matrix by changes over from four stage to three stage. As a result, this paper can reduce mapreduce job and can generate recommend file. And it has a fast processing speed, and reduce map output data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2844-2851
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• 2015

How to recover from the multiple 2D images into 3D object has been widely studied in the field of computer vision. In order to improve the accuracy of the recovered 3D shape, it is more important that noise must be minimized and the number of image frames must be guaranteed. However, potential noise is implied when tracking feature points. And the number of image frames which is consisted of an observation matrix usually decrease because of tracking failure, occlusions, or low image resolution, and so on. Therefore, it is obviously essential that the number of image frames must be secured by recovering the missing feature points under noise. Thus, we propose the analytic approach which can control directly the error distance and orientation of missing feature point by the geometrical properties under noise distribution. The superiority of proposed method is demonstrated through experimental results for synthetic and real object.

• The KIPS Transactions:PartA
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• v.12A no.3 s.93
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• pp.215-222
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• 2005

The efficient utilization of cache memories is a key factor in achieving high performance for computing large signal transforms. Nonunit stride access in computation of large DFTs causes cache conflict misses, thereby resulting in poor cache performance. It leads to a severe degradation in overall performance. In this paper, we propose a dynamic data layout approach considering the memory hierarchy system. In our approach, data reorganization is performed between computation stages to reduce the number of cache misses. Also, we develop an efficient search algorithm to determine the optimal tree with the minimum execution time among possible factorization trees considering the size of DFTs and the data access stride. Our approach is applied to compute the fast Fourier Transform (FFT). Experiments were performed on Pentium 4, $Athlon^{TM}$ 64, Alpha 21264, UtraSPARC III. Experiment results show that our FFT achieve performance improvement of up to 3.37 times better than the previous FFT packages.