• Journal of Information Technology Applications and Management
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• v.23 no.1
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• pp.33-43
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• 2016

Along with the spread of digital music and recent growth in the digital music industry, the demands for music recommender are increasing. These days, listeners have increasingly preferred to digital real-time streamlining and downloading to listen to music because it is convenient and affordable for the listeners to do that. We use Bayesian learning through weight of listener's prefered music site such as Melon, Billboard, Bugs Music, Soribada, and Gini. We reflect most popular current songs across all genres and styles for music recommender system using user profile. It is necessary for us to make the task of preprocessing of clustering the preference with weight of listener's preferred music site with popular music charts. We evaluated the proposed system on the data set of music sites to measure its performance. We reported some of the experimental result, which is better performance than the previous system.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.490-492
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• 1997

This paper describes a digital sensorless drive of permanent magnet brushless DC (PM BLDC) motors. The sensorless drive adopts a digital filter - moving average finite impulse response filter for accurate estimation of commutation time. Experimental results show that the performance of the proposed sensorless drive is superior to that of the sensorless drive without filtering.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.18-21
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• 2007

Digital image watermarking is a technology used in copyrighting of digital images by embedding unremovable informations. In this paper, a pixel-domain look-up-table-based watermarking algorithm is presented. With this methodology, the watermark was embedded in the host image, but we did not observe any distortion at certain specific region of interest. This means the proposed method is preferred in case of satellite images. Then, the image manipulation tool which is called 'StirMark' will be used to perform many kinds of attacks such as rotation, scaling, filtering and compression on the watermarked image. Finally, the effectiveness of a watermarking technique in terms of 'robustness' and 'data integrity' criteria will be measured by calculating PSNR of watermark and watermarked image.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.415-416
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• 2006

In this paper, we proposed a new coding technique of digital hologram video using 3D scanning method and video compression technique. The proposed coding consists of capturing a digital hologram to separate into RGB color space components, localization by segmenting the fringe pattern, frequency transform using $M{\tiems}N$ (segment size) 2D DCT (2 Dimensional Discrete Cosine Transform) for extracting redundancy, 3D scan of segment to form a video sequence, motion compensated temporal filtering (MCTF) and modified video coding which uses H.264/AVC.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.239-240
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• 2023

Construction site management involves overseeing tasks from the construction phase to the maintenance stage, and digitalization of construction sites is necessary for digital construction site management. In this study, we aim to conduct research on object recognition at construction sites using drones. Images of construction sites captured by drones are reconstructed into BIM (Building Information Modeling) models, and objects are recognized after partially rendering the models using artificial intelligence. For the photorealistic rendering of the BIM models, both traditional filtering techniques and the generative adversarial network (GAN) model were used, while the YOLO (You Only Look Once) model was employed for object recognition. This study is expected to provide insights into the research direction of digital construction site management and help assess the potential and future value of introducing artificial intelligence in the construction industry.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.67-73
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• 2015

In a distribution of digital image, there is a serious problem that is the image alteration by a forger. For the problem solution, this paper proposes the forensic decision algorithm of a median filtering (MF) image using the feature vector based on a coefficient of variation (c.v.) of Fourier transform. In the proposed algorithm, we compute Fourier transform (FT) coefficients of row and column line respectively of an image first, then c.v. between neighboring lines is computed. Subsquently, 10 Dim. feature vector is defined for the MF detection. On the experiment of MF detection, the proposed scheme is compared to MFR (Median Filter Residual) and Rhee's MF detection schemes that have the same 10 Dim. feature vector both. As a result, the performance is excellent at Unaltered, JPEG (QF=90), Down scaling (0.9) and Up scaling (1.1) images, and it showed good performance at Gaussian filtering ($3{\times}3$) image. However, in the performance evaluation of all measured items of the proposed scheme, AUC (Area Under ROC (Receiver Operating Characteristic) Curve) by the sensitivity and 1-specificity approached to 1 thus, it is confirmed that the grade of the performance evaluation is rated as 'Excellent (A)'.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.157-177
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• 2008

Even in a single day, an enormous amount of content including digital videos, posts, photographs, and wikis are generated on the web. It's getting more difficult to recommend to a user what he/she prefers among these contents because of the difficulty of automatically grasping of content's meanings. CF (Collaborative Filtering) is one of useful methods to recommend proper content to a user under these situations because the filtering process is only based on historical information about whether or not a target user has preferred an item before. Collaborative Tagging is the process that allows many users to annotate content with descriptive tags. Recommendation using tags can partially improve, such as the limitations of CF, the sparsity and cold-start problem. In this research, a CF method with user-created tags is proposed. Collaborative tagging is employed to grasp and filter users' preferences for items. Empirical demonstrations using real dataset from del.icio.us show that our algorithm obtains improved performance, compared with existing works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.752-758
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• 2012

SNS(Social Networking Services) is oneline service that enable users to construct human network through their relation on web, such as following relation, friend relation, and etc. Recently, owing to the advent of digital devices (smart phone, tablet PC) which embedded GPS some applications which provide services with spatial relevance and social relevance have been released. Such an online service is called LBSNS. It is required to use spatial filtering so as to build the LBSNS system that enable users to subscribe information of interesting area. For spatial filtering, user and tweet attaches location information which divide into static property presenting fixed area and dynamic property presenting user's area changed along the moving user. In the case of using a location information including dynamic property, Continuous query occurred from the moving user causes the problem in server. In this paper, we propose spatial filtering algorithm using Virtual Grid for reducing frequency of query, and conclude that frequency of query on using Virtual Grid is 93% decreased than frequency of query on not using Virtual Grid.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.61-68
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• 2015

In recent times, the median filtering (MF) detector as a forensic tool for the recovery of forgery images' processing history has concerned broad interest. For the classification of MF image, MF detector should be designed with smaller feature set and higher detection ratio. This paper presents a novel method for the detection of MF in altered images. It is transformed from BMP to several kinds of MF image by the median window size. The difference distribution values are computed according to the window sizes and then the values construct the feature set same as the MF window size. For the MF detector, the feature set transformed to the model specification which is computed using latent growth modeling (LGM). Through experiments, the test image is classified by the discriminant into two classes: the true positive (TP) and the false negative (FN). It confirms that the proposed algorithm is to be outstanding performance when the minimum distance average is 0.119 in the confusion of TP and FN for the effectivity of classification.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.166-171
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• 2010

In this paper, the front-end of a digital receiver with a 25 kHz carrier frequency, 5 kHz symbol rate, and any excess-bandwidth is designed using two basic facts. The first is known as the uniform sampling theorem, which states that the sampled sequence might not suffer from aliasing even if its sampling rate is lower than the Nyquist sampling rate if the analog signal is a bandpass one. The other fact is that if the sampling rate is 4 times the center frequency of the sampled sequence, the front-end processing complexity can be dramatically reduced due to the half of the sampled sequence to be multiplied by zero in the demixing process. Furthermore, the designed front-end is simplified by introducing sub-filters and sub-sampling sequences. The designed front-end is composed of an A/D converter, which takes samples of a bandpass filtered signal at a 20 kHz rate; a serial-to-parallel converter, which converts a sampled bandpass sequence to 4 parallel sub-sample sequences; 4 sub-filter blocks, which act as a frequency shifter and lowpass filter for a complex sequence; 4 synchronized switches; and 2 adders. The designed front-end dramatically reduces the computational complexity by more than 50% for frequency shifting and lowpass filtering operations since a conventional front-end requires a frequency shifting and two lowpass filtering operations to get one lowpass complex sample, while the proposed front-end requires only four filtering operation to get four lowpass complex samples, which is equivalent to one filtering operation for one sample.