• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.201-209
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• 2012

The point-based complex event processing handled an instantaneous event by using one time stamp in each event. However, the activity period of the event plays the important role in the field which is the same as the finance, multimedia, medicine, and meteorology. The point-based event is insufficient for expressing the complex temporal relationship in this field. In the application field of the real-time world, the event has the period. The events more than two kinds can be temporally overlapped. In addition, one event can include the other event. The relation about the events of kind of these can not be successive like the point-based event. This thesis designs and implements the method detecting the patterns of the complex event by using the interval-based events. The interval-based events can express the overlapping relation between events. Furthermore, it can include the others. By using the end point of beginning and end point of the termination, the operator of interval-based events shows the interval-based events. It expresses the sequence of the interval-based events and can detect the complex event patterns. This thesis proposes the algorithm using the active instance stack in order to raise efficiency of detection of the complex event patterns. When comprising the event sequence, this thesis applies the window push down technique in order to reduce the number of intermediate results. It raises the utility factor of the running time and memory.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.95-102
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• 2005

In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.33-38
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• 2014

The FCM based hybrid RBF network is a heterogeneous learning network model that applies FCM algorithm between input and middle layer and applies Max_Min algorithm between middle layer and output. The Max-Min neural network uses winner nodes of the middle layer as input but shows inefficient learning in performance when the input vector consists of too many patterns. To overcome this problem, we propose a dynamic learning rate control based on fuzzy logic. The proposed method first classifies accurate/inaccurate class with respect to the difference between target value and output value with threshold and then fuzzy membership function and fuzzy decision logic is designed to control the learning rate dynamically. We apply this proposed RBF network to the character recognition problem and the efficacy of the proposed method is verified in the experiment.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.247-256
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• 2001

Digital watermarking is a copyright protection technique for digital images which embed a code into the digital data so the data is marked. Watermarking techniques previously deal with on-line digital data and have been developed to withstand digital attacks such image processing, compression and geometric transformation. In this paper we propose a novel method of embedding watermarks in printed images. In the proposed algorithm, watermark is embedded in a dithered binary image by comparing the $2\times{2}$ blocks of the counting array is the number of 1 (WHITE) in the $16\times{16}$ blocks of the dithered binary image with predefined reference block pattern, which is generated by watermark values. The proposed algorithm is able to provide more information at a watermark because the proposed algorithm use both '1'and '0' as watermark values. The watermark information is detected by comparing the watermark which is reconstructed from the image which is embedded watermark with the original watermark which is embedded in a binary image. The performance of the proposed algorithm is compared with that of the conventional watermark embedding algorithm for printed images by detecting watermark for scan images.

• Journal of KIISE
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• v.45 no.2
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• pp.157-164
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• 2018

Due to the revolutionary advances in deep learning, performance of pattern recognition has increased significantly in many applications like speech recognition and image recognition, and some systems outperform human-level intelligence in specific domains. Unlike pattern recognition, in this paper, we focus on generating Korean sentences based on a few Korean sentences. We apply variational recurrent auto-encoder (VRAE) and modify the model considering some characteristics of Korean sentences. To reduce the number of words in the model, we apply a word spacing model. Also, there are many Korean sentences which have the same meaning but different word order, even without subjects or objects; therefore we change the unidirectional encoder of VRAE into a bidirectional encoder. In addition, we apply an interpolation method on the encoded vectors from the given sentences, so that we can generate new sentences which are similar to the given sentences. In experiments, we confirm that our proposed method generates better sentences which are semantically more similar to the given sentences.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1345-1352
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• 2010

The structural approach in the signature verification, representing a signature as a structural form of local primitives, shows an excellent performance since it counts in the local characteristics such as local variation, stroke complexity, and etc. However, this method has a problem of template data sizing which can not fix the number of subpatterns comprising a signature. In this paper, we proposed a new algorithm to reduce the signature data into a fixed size by selecting a fixed number of subpatterns which is considered as important parts. As a result, it shows more excellent performance when the fixed sized sub-patterns is applied with local weights extracted from variational characteristics and complexities in local part. And the number of subpatterns representing a signature reference model can be fixed under a certain number of segments determined appropriately.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.3
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• pp.388-402
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• 2000

The radiation characteristics of leaky antenna from the dielectric-coated conducting cylinder with periodic corrugation are investigated theoretically for the infinite and finite periodic structures. For the infinite periodic structure, mode-matching method is applied. The integral equation is derived for the finite periodic structure by use of the Fourier transform and mode expansion and a simultaneous linear equation is obtained. The influences of the corrugation slot width, corrugation depth, dielectric thickness, cylinder radius, and finite corrugation number on the radiation characteristics (leakage constant, phase constant, and radiation pattern) are investigated. The results of the finite periodic corrugations are compared with those of the infinite extent structure and good agreement is found. To reduce high side lobe levels of the uniform finite periodic structure, tapering process on the beginning and end section of antenna and nonuniform quasi-period slot arrays are considered. Especially, for the corrugation period, width and depth used for a corrugated surface wave antenna, through the proper tapering process, end-fire radiation pattern with reduced side lobe levels is given.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.53-59
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• 2018

In this study, a new design method is developed to optimize the structure of an underwater sparse array sensor. The purpose of this research is to design the structure of a sparse array that has the performance equivalent to a fully sampled array. The directional factor of a sparse planar array is derived as a function of the structural parameters of the array. With the derived equation, the structure of the sparse array sensor is designed to have the performance equivalent to that of the fully array sensor through structural optimization of the number and location of transmitting and receiving elements in the array. The designed sparse array sensor shows beam patterns very close to those of the fully array sensor in terms of PSLL (Peak Side Lobe Level) and MLBW (Main Lobe Beam Width), which confirms the effectiveness of the present optimal design method. Further, the validity of the analytic beam patterns is verified by comparing them with those from the FEA (Finite Element Analysis) of the optimized sparse array structure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1942-1950
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• 2013

This paper suggests a new method of detecting attacks of network traffic by visualizing original traffic data and applying multi-class SVM (support vector machine). The proposed method first generates 2D images from IP and ports of transmitters and receivers, and extracts linear patterns and high intensity values from the images, representing traffic attacks. It then obtains variance of ports of transmitters and receivers and extracts the number of clusters and entropy features using ISODATA algorithm. Finally, it determines through multi-class SVM if the traffic data contain DDoS, DoS, Internet worm, or port scans. Experimental results show that the suggested multi-class SVM-based algorithm can more effectively detect network traffic attacks.