• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1163-1176
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• 2005

The Web is the largest distributed information space but, the individual's capacity to read and digest contents is essentially fixed. In these Web environments, mining traversal patterns is an important problem in Web mining with a host of application domains including system design and information services. Conventional traversal pattern mining systems use the inter-pages association in sessions with only a very restricted mechanism (based on vector or matrix) for generating frequent K-Pagesets. We extend a family of novel algorithms (termed WebPR - Web Page Recommend) for mining frequent traversal patterns and then pageset to recommend. We add a WebPR(A) algorithm into a family of WebPR algorithms, and propose a new winWebPR(T) algorithm introducing a window concept on WebPR(T). Including two extended algorithms, our experimentation with two real data sets, including LadyAsiana and KBS media server site, clearly validates that our method outperforms conventional methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.129-135
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• 2014

In the paper, we propose a design method for the logistics transportation system using magnetic levitation that has a good characteristics without mechanical friction, noise and dust. The proposed transportation system consists of a levitation control system and a propulsion control system. Magnetic levitation system is an electromagnetic suspension system in which electromagnet generates magnetic attractive force and the attractive force pulls the rail. We design a PID controller for the current control of electromagnets. We use linear induction motors for propulsion of the proposed logistics transportation system and adapt the space vector PWM method for the propulsion control system. The proposed transportation system using magnetic levitation is verified performances through levitation and propulsion experiments.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.870-878
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• 2013

In this paper, we propose a novel fingerprint classification method to enhance the accuracy and efficiency of the fingerprint identification system, one of biometrics systems. According to the previous researches, fingerprints can be categorized into the several patterns based on their pattern of ridges and valleys. After construction of fingerprint database based on their patters, fingerprint classification approach can help to accelerate the fingerprint recognition. The reason is that classification methods reduce the size of the search space to the fingerprints of the same category before matching. First, we suggest a method to extract region of interest (ROI) which have real information about fingerprint from the image. And then we propose a feature extraction method which combines gray level co-occurrence matrix (GLCM) and wavelet features. Finally, we compare the performance of our proposed method with the existing method which use only GLCM as the feature of fingerprint by using the multi-layer perceptron and support vector machine.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.287-297
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• 1998

RPWM(Random Pulse Width Modulation) is a switching technique to spread the voltage and current harmonics on wide frequency area. Using randomly changed switching frequency of the inverter, the power spectrum of the electromagnetic acoustic noise can be spread into the wide-band area. And the wide-band noise is much more comfortable and less annoying than the narrow-band one. So RPWM have been attracting an interest as an excellent reduction method of acoustic noise on the inverter drive system. In this paper a new RPPWM(Random Position PWM) is proposed and implemented. Each of three pulses is located randomly in each switching intervals. Along with the randomization of PWM pulses, the space vector modulation is processed on the C167 microcontroller also. The experimental results show that the voltage and current harmonics were spread into wide band area and that the audible switching noise was reduced by proposed RPPWM method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4561-4568
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• 2011

In this paper, carrier comparison PWM method for voltage control of Vienna rectifier is discussed. In general, in industrial and communications applications, the two-level rectifier is used. However, this two-level rectifier has the limit of high THD and low efficiency. So, the studies of three-level rectifier has been carried out so far, and the Vienna rectifier circuit is the representative. The space vector pulse width modulation(SVPWM) method is generally used for Vienna rectifier, in which voltage vectors and duration time are calculated from the voltage reference. However, this method require very sophisticated and complex calculations, so realizing this method by software is very difficult. To overcome this disadvantage, simple carrier comparison PWM method for Vienna rectifier is proposed which is modified from the carrier comparison method for 3 level inverter. Furthermore, to verify the usefulness of the Vienna rectifier carrier comparison PWM the simulation and experiment are carried out.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.279-286
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• 2006

One of the widely used methods for product recommendation in Internet storefronts is matching product features against target customer profiles. When using this method, it's very important to choose a suitable subset of features for recommendation efficiency and performance, which, however, has not been rigorously researched so far. In this paper, we utilize a dataset collected from a virtual shopping experiment in a Korean Internet book shopping mall to compare several popular methods from other disciplines for selecting features for product recommendation: the vector-space model, TFIDF(Term Frequency-Inverse Document Frequency), the mutual information method, and the singular value decomposition(SVD). The application of SVD showed the best performance in the analysis results.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.1-6
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• 2007

In order to operate a secure network, it is very important for the network to raise positive detection as well as lower negative detection for reducing the damage from network intrusion. By using SVM on the intrusion detection field, we expect to improve real-time detection of intrusion data. However, due to classification based on calculating values after having expressed input data in vector space by SVM, continuous data type can not be used as any input data. Therefore, we present the hybrid model between SVM and decision tree method to make up for the weak point. Accordingly, we see that intrusion detection rate, F-P error rate, F-N error rate are improved as 5.6%, 0.16%, 0.82%, respectively.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.29-40
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• 2003

Cross-Language Information Retrieval (CLIR) deals with the documents in various languages by one language query. A user who uses one language can retrieve the documents in another language through CLIR system. In CLIR, query translation method is known to be more efficient. For the better performance of query translation, we need more resources like dictionary, ontology, and parallel/comparable corpus but usually not available. This paper proposes a new concept called the Common Base Axis which is adapted to Korean-English Query translation ann a new weighting method in dictionary based query translation. The essential idea is that we can express Korean and English word in one vector space by Common Base Axis and use it in calculating sense distance for query weighting. The experiments show that Common Base Axis gives us good performance without ontology and is especially good for one word query translation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.532-537
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• 2009

The necessity of intelligent surveillance system is gradually considered seriously from the space where the security is important. In this paper, we embodied unmanned intelligent system by developing embedded mobile robot based on images and sounds tracking. For objects tracking, we used block-matching algorithm and for sound source tracking, we calculated time differences and magnitude dissimilarities of sound. And we demonstrated the superiority of intruder tracking algorithm through the embodiment of Pan-Tilt camera and sound source tracking module using system, Network camera and mobile robot using system and mobile robot using system. By linking security system, the suggested system can provide some interfacing functions for the security service of the public facilities as well as that of home.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.