• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.83-85
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• 2013

본 연구는 사용자가 센서를 의식하지 않고 편안하게 일상생활을 영위할 수 있는 비침습적 방식의 센서를 활용하여 향후 침대 위에 있는 사람의 움직임을 정량적으로 측정하고자 한다. 이러한 목적으로 필름 형태의 압전센서를 사용하는 센서 시스템을 구축하였으며, 본 논문에서는 구축된 시스템에서 필요한 전처리 과정을 제시한다. 본 연구에서 사용된 압전센서는 침대 매트리스 아래에 설치하였다. 사람의 움직임에 의한 압전센서의 출력 신호를 증폭하고 샘플링하여 PC로 전송하는 컨트롤러, 컨트롤러로부터 센서 데이터를 수신하고, 사용자에게 센서 데이터를 시각적으로 제시하는 모니터링 프로그램을 개발하였다. 본 연구에서는 컨트롤러에서의 노이즈 제거, 증폭, 샘플링 등의 전처리, 모니터링 프로그램에 의해 수집된 센서 데이터에 대한 이동 평균 필터, 불필요한 움직임이 없는 구간을 제거 후 움직임이 있는 구간 추출 등의 전처리 과정을 제시한다. 이러한 전처리 연산은 향후 침대 위 인체의 움직임을 정량적으로 측정하고, 행동유형을 식별하는데 기여하게 될 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.452-460
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• 2008

ALE-complient RFID middleware system receives EPC code data from reader devices and converts the data into URN format data internally. After filtering and grouping, the system sends the resulting URN code to application and(or) users. Meanwhile, not only the types of EPC code are very diverse, but also another new kinds of EPC code can be emerged in the future. Therefore, a method to process all kinds of EPC code effectively is required by RFID middleware. In this paper, a method to process various kinds of EPC code acquired from RFID reader devices in ALE-complient RFID middleware is proposed. Especially, we propose an approach using ontology technology to process not only existing EPC code but also newly defined code in the future. That is, we build an ontology of conversion rules for each EPC data type to effectively convert EPC data into URL format data. In this case, we can easily extend RFID middleware to process a new EPC code data by adding a conversion rule ontology for the code.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.79-98
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• 2011

This paper proposes a semantic recommendation technique for a personalized e-commerce portal. Semantic recommendation is achieved by utilizing the attributes of products. The semantic similarity of the products is merged with the rating information of the products to provide an accurate recommendation. The recommendation technique also analyzes various attitudes of the customer to evaluate the implicit rating of products. Attitudes are classifies into three types such as "purchasing product", "adding product to shopping cart", and "viewing the product information." We implicitly track customer attitude to estimate the rating of products for recommending products. Also we implement a session validation process to identify the valid sessions that are highly important for giving an accurate recommendation. Our recommendation technique shows a high degree of accuracy as we use age groupings of customers with similar preferences. The experimental section shows that our proposed recommendation method outperforms well known collaborative filtering methods not only for the existing customer, but also for the new user with no previous purchase record.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.49-54
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• 2006

Recently, e-mail has become an important way of communications in IT societies, but it creates various social problems due to increase of spam mails. Even though many organizations and cooperation have been trying researches to develop spam mail blocking technologies, a lot of cost and system complexities are required because of varieties of spam blocking technologies. In this paper, we designed of the SMBC(Spam Mail Blocking Center) using the Fit FA(Filtering Algorithm) Finder. Fit-FA Finder that search and applises spam mail filtering algorithm of the most suitable confrontation according to type of spam mail. The system of spam mail filtering is decided performance of the system by procedure that spam filter is used. Go through designed Fit-FA Finder and reduced unnecessary filtering process and processing time and load than appointment order filter application way of existent spam mail interception system.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.169-177
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• 2012

A non-decimation second-order spatial moving average (SMA) discrete-time (DT) filter is proposed with reconfigurable null frequencies. The filter coefficients are changeable, and it can be controlled by switching sampling capacitors. So, interferers can be rejected effectively by flexible nulls. Since it operates without decimation, it does not change the sample rate and aliasing problem can be avoided. The filter is designed with variable weight of coefficients as $1:{\alpha}:1$ where ${\alpha}$ varies from 1 to 2. This corresponds to the change of null frequencies within the range of fs/3~fs/2 and fs/2~2fs/3. The proposed filter is implemented in the TSMC 0.18-${\mu}m$ CMOS process. Simulation shows that null frequencies are changeable in the range of 0.38~0.49fs and 0.51~0.62fs.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.2
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• pp.47-55
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• 2012

A discrete-time(DT) filter with high-order temporal moving average(TMA) using actively-weighted charge sampling is proposed in this paper. To obtain different weight of sampled charge, the variable transconductance OTA is used prior to charge sampler, and the ratio of charge can be effectively weighted by switching the control transistors in the OTA. As a result, high-order TMA operation can be possible by actively-weighted charge sampling. In addition, the transconductance generated by the OTA is relatively accurate and stable by using the size ratio of the control transistors. The high-order TMA filter has small size, increased voltage gain, and low parasitic effects due to the small amount of switches and sampling capacitors. It is implemented in the TSMC $0.18-{\mu}m$ CMOS process by TMA-$2^2$. The simulated voltage gain is about 16.7 dB, and P1dB and IIP3 are -32.5 dBm and -23.7 dBm, respectively. DC current consumption is about 9.7 mA.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.9-16
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• 2023

In the IoT environment, various objects mutually interactive, and various services can be composed based on this environment. In the previous study, we have developed a resource collaboration system to provide services by substituting limited resources in the user's personal device using resource collaboration. However, in the preceding system, when the number of resources and situations increases, the inference time increases exponentially. To solve this problem, this study proposes a method of classifying users and resources by applying the BIG5 user type classification model. In this paper, we propose a method to reduce the inference time by filtering the user's preferred resources through BIG5 type-based preprocessing and using the filtered resources as an input to the recommendation system. We implement the proposed method as a prototype system and show the validation of our approach through performance and user satisfaction evaluation.

• Convergence Security Journal
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• v.20 no.3
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• pp.61-69
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• 2020

Since spear-phishing mail attacks focus on a particular target persistently to collect and take advantage of information, it can incur severe damage to the target as a part of the intelligent and new attacks such as APT attacks and social engineering attacks. The usual spam filtering services can have limits in countering spear-phishing mail attacks because of different targets, goals, and methods. In this paper, we analyze mail security services of several enterprises hosted by midium and small-sized enterprises with relatively security vulnerabilities in order to see whether their services can effectively respond spear-phishing mail attacks. According to the analysis result, we can say that most of mail security hosting services lack in responding spear-phishing mail attacks by providing functions for mainly managing mails including spam mail. The analysis result can be used as basic data to extract the effective and systematic countermeasure.

• Journal of KIISE
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• v.42 no.3
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• pp.367-378
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• 2015

This study was directed at the design of a hybrid algorithm for competition relation extraction. Previous works on relation extraction have relied on various lexical and deep parsing indicators and mostly utilize only the machine learning method. We present a new algorithm integrating machine learning with various filtering methods. Some simple but useful features for competition relation extraction are also introduced, and an optimum feature set is proposed. The goal of this paper was to increase the precision of competition relation extraction by combining supervised learning with various filtering methods. Filtering methods were employed for classifying compete relation occurrence, using distance restriction for the filtering of feature pairs, and classifying whether or not the candidate entity pair is spam. For evaluation, a test set consisting of 2,565 sentences was examined. The proposed method was compared with the rule-based method and general relation extraction method. As a result, the rule-based method achieved positive precision of 0.812 and accuracy of 0.568, while the general relation extraction method achieved 0.612 and 0.563, respectively. The proposed system obtained positive precision of 0.922 and accuracy of 0.713. These results demonstrate that the developed method is effective for competition relation extraction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.755-759
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• 2012

In this paper, it is about random number generator, which is based on hardware is utilized in medical science and game area. The Intel presents guideline of security level about hardware based true random number generator. At hardware based random number generator, the various test items, that are included in test suits as NIST statistical test, FIPS140-1, is applied. In this paper, it experiments about degree extent of randomness variation from filter scheme effects, which is applied in output stream of hardware noise source.