• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.147-157
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• 2018

Recently, with the advancement of network technologies, and the activation of IoT and social network services, many graph stream data have been generated. As the relationship between objects in the graph streams changes dynamically, studies have been conducting to detect or analyze the change of the graph. In this paper, we propose a scheme to incrementally detect frequent patterns by using frequent patterns information detected in previous sliding windows. The proposed scheme calculates values that represent whether the frequent patterns detected in previous sliding windows will be frequent in how many future silding windows. By using the values, the proposed scheme reduces the overall amount of computation by performing only necessary calculations in the next sliding window. In addition, only the patterns that are connected between the patterns are recognized as one pattern, so that only the more significant patterns are detected. We conduct various performance evaluations in order to show the superiority of the proposed scheme. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.1
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• pp.25-39
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• 1986

In this paper, we analyze the performance, particularly the flow control mechanism, of the CCITT X.25 protocol in a packet-switched network. In this analysis, we consider the link and packet layers separately, and investigate the performance in three measures; normalized channel throughput, mean transmission time, and transmission efficiency. Each of these measures is formulated in terms of given protocol parameters such as windos size, $T_1$ and $T_2$ values, message length, and so forth. We model the service procedure of the inpur traffic based on the flow control mechanism of the X.25 protocol, and investigate the mechanism of the sliding window flow control with the piggybacked acknowlodgment scheme using a discrete-time Markov chain model. With this model, we study the effect of variation of the protoccol parameters on the performance of the X.25 protocol. From the numerical results of this analysis one can select the optimal valuse of the protocol parameters for different channel environments. it has been found that to maintain the trasnmission capacity satisfactorily, the window size must be greater than or equal to 7 in a high-speed channel. The time-out value, $T_1$, must carefully be selected in a noisy channel. In a normal condition, it should be in the order of ls. The value of $T_2$ has some effect on the transmission efficiency, but is not critical.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.44-47
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• 2006

One of the critical issues in a sensor network concerns the detection of changes in data streams. Recently presented change detection schemes primarily use a sliding window model to detect changes. In such a model, a distance function is used to compare two sliding windows. Therefore, the performance of the change detection scheme is greatly influenced by the distance function. With regard to sensor nodes, however, energy consumption constitutes a critical design concern because the change detection scheme is implemented in a sensor node, which is a small battery-powered device. In this paper, we present a comparative study of various distance functions in terms of execution time, energy consumption, and detecting accuracy through simulation of speech signal data. The simulation result demonstrates that the Euclidean distance function has the highest performance while consuming a low amount of power. We believe our work is the first attempt to undertake a comparative study of distance functions in terms of execution time, energy consumption, and accuracy detection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.267-274
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• 2011

Recently, actor-critic methods have drawn significant interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy. In this paper, we consider a new type of actor-critic algorithms employing the kernel methods, which have recently shown to be very effective tools in the various fields of machine learning, and have performed investigations on combining the actor-critic strategy together with kernel methods. More specifically, this paper studies actor-critic algorithms utilizing the kernel-based least-squares estimation and policy gradient, and in its critic's part, the study uses a sliding-window-based kernel least-squares method, which leads to a fast and efficient value-function-estimation in a nonparametric setting. The applicability of the considered algorithms is illustrated via a robot locomotion problem and a tunnel ventilation control problem.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.275-284
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• 2007

For the application to the numerical weather prediction (NWP) in active service, it is necessary to ensure that the GPS precipitable water vapor (PWV) data has less than one hour latency and three millimeter accuracy. The comparison and the verification between the daily products from GPS measurement by using the IGS final ephemeris and the conventional meteorological observation has been done in domestic researches. In case of using IGS final ephemeris, GPS measurements can be only post processed in daily basis in three weeks after the observation. Thus this method cannot be applied to any near real-time data processing. In this paper, a GPS data processing method to produce the PWV output with three mm accuracy and one hour latency for the data assimilation in NWP has been planned. For our new data processing strategy, IGS ultra-rapid ephemeris and the sliding window technique are applied. And the results from the new strategy has been verified. The GPS measurements during the first 10 days of January, April, July and October were processed. The results from the observations at Sokcho, where the GPS and radiosonde were collocated, were compared. As the results, a data processing strategy with 0.8 mm of mean bias and 1.7 mm of standard deviation in three minutes forty-three seconds has been established.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.162-167
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• 2012

This paper describes the design of a high-performance unified SVM classifier circuit. The proposed circuit supports both linear and non-linear SVM classifications. In order to ensure efficient classification, a 48x96 or 64x64 sliding window with 20 window strides is used. We reduced the circuit size by sharing most of the resources required for both types of classification. We described the proposed unified SVM classifier circuit using the Verilog HDL and synthesized the gate-level circuit using 65nm standard cell library. The synthesized circuit consists of 661,261 gates, operates at the maximum operating frequency of 152 MHz and processes up to 33.8 640x480 image frames per second.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.102.3-102
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• 2001

In this paper, we propose a novel method that can detect face region effectively with fuzzy theory and neural network We make fuzzy rules and membership functions to describe the face color. In this algorithm, we use a perceptually uniform color space to increase the accuracy and stableness of the nonlinear color information. We use this model to extract the face candidate, and then scan it with the pre-built sliding window by using a neural network-based pattern-matching method to find eye. A neural network examines small windows of face candidate, and decides whether each window contains eye. We can standardize the face candidate geometrically with detected eyes.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.3 s.18
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• pp.101-109
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• 2004

Image enhancement for Infrared imaging system is mainly based on the global histogram equalization. The global histogram equalization(GHE) is a method in which each pixel is equalized by using a whole histogram of an image. GHE is speedy and effective for real-time imaging system but its method fails to enhance the fine details. On the other hand, the basic local histogram equalization(LHE) method uses sliding a window and. the pixels under the window region are equalized over the whole output dynamic range. The LHE is adequate to enhance the fine details. But this method is computationally slow and noises are over-enhanced. So various local histogram equalization methods have been already presented to overcome these problems of LHE. In this paper, a new regional dynamic range histogram equalization (RDRHE) is presented. RDRHE improves the equalization quality while reducing the computational burden.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.673-682
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• 2009

XML data are widely used for data representation and exchange on the Web and the data type is an continuous stream in ubiquitous environment. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the sliding window. XML stream data are modeled as a tree set, called XFP_tree and we quickly extract the frequent structures over recent XML data in the XFP_tree.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.30 no.4
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• pp.195-203
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• 2018

Mohair is widely used as an airtight material for filling the gap between a window frame and sash. The purpose of this study is to investigate infiltration rate and opening force of sliding windows according to the mohair installation conditions. Infiltration experimental apparatus was set up, and the experimental results were applied to windows to find a correlation between infiltration rates and opening forces. When 4 rows of mohair were installed, the infiltration rate increase became 27.1% per clearance length increase of 1 mm, and the infiltration rate decrease became 5.7% per shortened length increase of 0.1 mm. For 4 rows of mohair, the opening force decreased by 28.2% as the clearance increased by 1 mm, and it increased by 9.3% as the shortened length increased by 0.1 mm.