• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.218-225
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• 2007

Recommendation system is one way of implementing personalized service. The collaborative filtering is one of the major techniques that have been employed for recommendation systems. It has proven its effectiveness in the recommendation systems for such domain as motion picture or music. However, it has some limitations, i.e., sparsity and scalability. In this research, as one way of overcoming such limitations, we proposed the stepwise collaborative filtering method. To show the practicality of our proposed method, we designed and implemented a movie recommendation system which we shall call Step_CF, and its performance was evaluated using MovieLens data. The performance of Step_CF was better than that of Basic_CF that was implemented using the original collaborative filtering method.

• Convergence Security Journal
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• v.14 no.2
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• pp.65-72
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• 2014

This paper proposes multi-filtering method on the double firewall to prevent DDoS attack. In the first firewall, R-PA filtering algorithm and rigid hop counter filtering method are applied by analyzing packet paths. In the second firewall, packets are examined to be distinguished abnormal from normal packets. Security policy system monitors each user sessions and if the traffic is over the threshold value, the system blocks that session for an assigned time.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.616-631
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• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1767-1774
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• 2016

In this paper, we propose the adaptation filtering for correcting the movement path of the recognized object by the depth information. When we recognize the object by the depth information, the path error should be occurred because of the noises in the depth information. The path error is corrected by appling the lowpass filtering, but the lowpass filtering is not efficient when the changes of the object's movement are rapid. In this paper, we apply the adaptation filtering that it gives weights adaptively as the difference between the predicted location and the measured location. To apply the adaptation filtering, we can see that the proposed method can correct accurately the path error of the radical change from simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.742-745
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• 1994

In this paper we show the performance of neural Chandrasekhar filtering which is a special case for the new method of neural filtering using the artificial neural network systems developed recently for the filtering problems of linear and nonlinear, stationary and nonstationary stochastic signals. The neurofilter developed has either the finite impulse response(FIR) structure or the infinite impulse response(IIR) structure. The neurofilter differs from the conventional linear digital FIR and IIR filters because the artificial neural network system used in the neurofilter has nonlinear structure due to the sigmoid function. Numerical studies for the estimation of a second order Butterworth process are performed by changing the structures of the neurofilter in order to evaluate the performance indices under the changes of the output noises or disturbances. In the numerical studies both Chandrasekhar filtering estimates and true signals are used as the training signals for the neurofilter. The results obtained from the studies verified the capabilities which are essentially necessary for on-line filtering of various stochastic signals.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.258-262
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• 2005

An adaptive beamforming system based on code filtering and differential correlation approaches is proposed. The differential correlation method was originally proposed for time delay estimation of direct sequence code division multiple access (DS-CDMA) systems under near-far ratio conditions and the code filtering correlation algorithm, on the other hand, was proposed for array response estimation in DS-CDMA systems under perfect power control. In this paper, by combining differential correlation concept with the code filtering beamforming technology, an accurate estimate of the beam forming weights and an enhanced performance of DS-CDMA systems under sever near-far ratio conditions is achieved. The system performance in terms of beam pattern and bit-error-rate (HER) shows that the proposed adaptive beamformer outperforms the conventional code filtering correlation technique.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.175-178
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• 2003

Two defects have been pointed out in existing user-based collaborative filtering such as sparsity and scalability, and the research has been also made progress, which tries to improve these defects using item-based collaborative filtering. Actually there were many results, but the problem of sparsity still remains because of being based on an explicit data. In addition, the issue has been pointed out. which attributes of item arenot reflected in the recommendation. This paper suggests a recommendation method using nave Bayesian algorithm in hybrid user and item-based collaborative filtering to improve above-mentioned defects of existing item-based collaborative filtering. This method generates a similarity table for each user and item, then it improves the accuracy of prediction and recommendation item using naive Bayesianalgorithm. It was compared and evaluated with existing item-based collaborative filtering technique to estimate the accuracy.

• Journal of Korea Multimedia Society
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• v.15 no.12
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• pp.1417-1429
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• 2012

In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.04a
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• pp.93-97
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• 2002

This research introduces some preliminary results of bank filtering intake method adopted in Dalseo area, Nakdong River. This intake method has been planned to supply water resources of 41,000 ㎥/day to Goryeong-Gun and Seongju-Gun in 2016. It is believed that the bank filtering intake method can afford to supply 41,000 ㎥/day amount of water resources and that the raw water quality using the method has more advantages in water treatment than direct surface water intake. Even though the safety yield about individual vertical well is roughly estimated to about 2,000 ㎥/day, it is desirable to decrease the safety yield to about 1,000 ㎥/day in the consideration of long term and simultaneous well pumpings and other unknown factors. Ongoing study will give basic data and new techniques to solve the problems appearing in application of bank filtering method as well.

• Korean Management Science Review
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• v.29 no.2
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• pp.79-90
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• 2012

Focusing on the rapid market penetration of smart phones, the importance of LBS (Location Based Service) is drastically increased. However, traditional GPS method has critical weakness caused by limited availability, such as indoor environment. WPS is newly attractive method as a widely applicable positioning method. In WPS, RSSI (Received Signal Strength Indication) data of all Wi-Fi APs (Access Point) are measured and stored into a huge database. The stored RSSI data in database make single radio fingerprint map. By the radio fingerprint map, we can estimate the actual position of target point. The essential factor of radio fingerprint database is data integrity of RSSI. Because of millions of APs in urban area, RSSI measurement data are seriously contaminated. Therefore, we present the unified filtering method for RSSI measurement data. As the results of filtering, we can show the effectiveness of suggested method in practical positioning system of mobile operator.