• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.113-122
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• 2008

In RFID system, Middleware collects and filters streaming data gathered continuously from readers to process applications requests. The enormous amount of data makes middleware in highly overloaded. Hence, we propose reader level filtering in order to reduce overall middleware load. In this paper, we consider reader filtering capability and define query plan to minimize number of queries for processing into middleware and reader level. We design and implement middleware system based on proposed query plan. We perform several experiments on implemented system. Our experiments show that the proposed query plan considerably improves the performance of middleware by diminishing processing time and network traffic between reader and middleware.

• 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 KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.86-99
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• 2007

Packet filtering is to filter out potentially malicious network packets. In order to test a packet filtering function we should verify whether security policies are performed correctly as intended. However there are few existing tools to test the function. Besides, they need user participation when generating test cases or deciding test results. Many security administrators have a burden to test systematically new security policies when they establish new policies or modify the existing ones. To mitigate the burdens we suggest a new test method with minimal user articipation. Our tool automates generation steps of the test cases and the test oracles, respectively. By using the test oracles generated automatically, deciding test results is possible without user intervention. Our method realizes an automatic testing in three phases; test preparation phase, test execution, and test evaluation. As a result it may enhance confidence of test activities more highly. This paper describes the design and implementation of our test method and tool.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.475-486
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• 2010

Contents Recommender System predicts user's preferences towards contents, and then recommends highly-predicted contents to user. Digital Identifier plays its part in identifying abstract works or digital contents in digital network environment. Digital Identifier could be effectively used in content-based filtering and collaborative filtering that are mainly used in Contents Recommender Systems. Therefore, this paper proposes an improvement of UCI metadata and resolution service for effective use of UCI in massive contents recommender systems. UCI metadata is expanded by adding elements such as abstract, keyword, genre, age, rate and review. Resolution service allows the operation systems to collect user preference for content by including input part of preference in a result page. This paper also designs and implements an improved UCI operation system and shows that the proposed improvement of UCI metadata and resolution service could be used for massive contents recommendation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.434-437
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• 2010

NIPS(Network Intrusion Prevention System) is in line at the end of the external and internal networks which performed two kinds of action: Signature-based filtering and anomaly detection and prevention-based on self-learning. Among them, a signature-based filtering is well known to defend against attacks. By using signature-based filtering, intrusion prevention system passing a payload of packets is compared with attack patterns which are signature. If match, the packet is discard. However, when there is packet delay, it will increase the required pattern matching time as the number of signature is increasing whenever there is delay occur. Therefore, to ensure the performance of IPS, we needed more efficient pattern matching algorithm for high-performance ISP. To improve the performance of pattern matching the most important part is to reduce the number of comparisons signature rules and the packet whenever the packets arrive. In this paper, we propose an improve signature hashing-based pattern matching method. We use tuple pruning algorithm with Bloom filters, which effectively remove unnecessary tuples. Unlike other existing signature hashing-based IPS, our proposed method to improve the performance of IPS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.173-178
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• 2022

Recently, a recommendation system using deep learning in social network services has been actively studied. However, in the case of a recommendation system using deep learning, the cold start problem and the increased learning time due to the complex computation exist as the disadvantage. In this paper, the user-tailored exercise routine recommendation algorithm is proposed using the user's metadata. Metadata (the user's height, weight, sex, etc.) set as the input of the model is applied to the designed model in the proposed algorithms. The exercise recommendation system model proposed in this paper is designed based on the neural collaborative filtering (NCF) algorithm using multi-layer perceptron and matrix factorization algorithm. The learning proceeds with proposed model by receiving user metadata and exercise information. The model where learning is completed provides recommendation score to the user when a specific exercise is set as the input of the model. As a result of the experiment, the proposed exercise recommendation system model showed 10% improvement in recommended performance and 50% reduction in learning time compared to the existing NCF model.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.123-140
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• 2009

Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.4
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• pp.305-313
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• 2013

As an FMT (Filtered Multi-Tone) transmission method of Wideband VHF communication system specified by the ETS (European Telecommunications Standards) EN 300 392-2, this paper introduces three existing realization methods, i.e., the direct filtering method using different band SRRC (Square-Root Raised Cosine) filters for each subcarrier, the PPN-DFT method using the IDFT-PPN (Poly-Phase Network) and PPN-DFT at the transmitter and receiver, respectively, and the Extended DFT method. Then, it proposes the extended IDFT-SDFT (Sliding Discrete Fourier Transform) that computes the DFT values only for interested subcarriers every sample time, and shows that it has an advantage of blind symbol timing (using no training symbol) individually for each user signal (independently of other users' signals) in the multi-user environment where the subcarriers are assigned in contiguous or interleaved blocks to each user and each user signal possibly experiences different channels.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.160-165
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• 1998

Current discriminating technique of rice variety is known to be not objective till this time because of depending on naked eye of well trained inspector. DNA finger print method based on genetic character of rice has been indicated inappropriate for on-site application, because the method need much labor and skilled expert. The purpose of this study was to develops the identification technique of polished rice varieties using CCD camera images. To minimize the noise of the captured image, thresholding and median filtering were carried out, and edge was extracted from the image data. Image data after pretreatment of normalize and FFT(fast fourier transform) were used for library model and feedforward backpropagation neural network model. Image processing technique using CCD camera could discriminate the variety of rice with high accuracy in case of quite different rice of shape, but the accuracy was reached at 85% in the similar shape of rice.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.