• 한국멀티미디어학회논문지
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• 제17권10호
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• pp.1141-1149
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• 2014

Recently, various methods to effectively eliminate the noise are researched in image processing techniques. However, the conventional noise filtering techniques, which remove most of the noise, are less efficient for remained noise detection after filtering due to exploiting no face feature information. In this paper, we proposed a feature vector generation technique in the mouth region by distinguishing and revising the remained noise through gradient correction, when the outline is extracted after performing noise filtering.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2006년도 공동학술대회 논문집
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• pp.51-59
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• 2006

서해안 조간대에서 24 channel 탐사기로 획득한 표면파 자료의 위상속도와 군속도를 구한다음, 이를 역산하여 그 결과를 비교하였다. 위상속도의 분산곡선은 tau-p stacking 방법에 의하여, 군속도의 분산곡선은 wavelet analysis와 Multiple Filtering Technique의 두가지 방법을 사용하여 구하였다. 위상속도의 오차가 군속도의 오차보다 더 큰 것을 확인하였다. 군속도의 경우, wavelet analysis가 Multiple Filtering Technique 보다 fundamental mode와 higher mode를 구분하는데 더 효과적이었다. 역산결과, 군속도의 fundamental mode와 1st higher mode 를 동시에 사용했을 때, 공간적 해상도가 가장 좋았다. 이연구는 천부 지반의 S파 속도 구조를 구하는데, 군속도의 higher mode를 포함한 군속도 분산곡선을 사용하는 것이 효과적임을 시사한다.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.432-434
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• 2008

본 논문은 필터링 수행율을 향상시키기 위해, DTW 알고리즘을 제시한다. 여기에서 말하는 컨텐츠 필터링은 음성의 특징을 사용해서 컨텐츠를 구분하는 것을 확인하는 기술이다. 즉, 이 방법이 일반 컨텐츠와 성인 컨텐츠를 구분한다. 음성에 대한 정보를 추출하는 방법이 컨텐츠를 필터링하는데 있어서 기여를 할 수 있다. 즉, DTW 알고리즘을 사용하여 필터링 인식률을 향상하는 방법이라고 제안을 한다. 마지막으로, 본 논문에서 제안한 방법의 적용 가능성과 일반성을 평가하기위하여 수치적인 예를 적용한다. 제안하는 성질의 정확도를 시험하기 위해서 실험을 제공하였다. 결과적으로 일반 컨텐츠와 성인 컨텐츠 특성의 차이를 알았다. 추후에 이 성질을 필터링 성능 향상에 응용할 수 있다.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2001년도 종합학술발표회논문집
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• pp.464-468
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• 2001

In this paper, we propose a robust watermarking technique that accepts time scaling, pitch shift, add noise and a lot of lossy compression such as MP3, AAC, WMA. The technique is developed based on digital filtering. Being designed according to critical band of HAS (human auditory system), the digital filters nearly affect audio quality. Furthermore, before implementing digital filtering, wavelet transform decomposes the audio signal into several signals that is composed of specific frequencies. Designed digital filters scan the decomposed signal. The designed digital filter, band-stop filter, distorts and eliminates specific frequencies of audio signals. Watermarking detection can be accomplished by FFT (Fast Fourier Transform). Firstly, segments of audio signal are transformed by FFT. Then, the obtained amplitude spectrum by FFT is summed repeatedly. Finally the watermark detector can find filters used to watermark encoding based on eliminating frequencies. The suggested technique can embed 4bits/s in a robust manner.

• Journal of Mechanical Science and Technology
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• 제18권2호
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• pp.253-261
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• 2004

A simple and effective filtering method to control the member size of an optimized structure is proposed for topology optimization. In the present approach, the original objective sensitivities are replaced with their relative values evaluated within a filtering area. By adjusting the size of the filtering area, the member size of an optimized structure or the level of its topological complexity can be controlled even within a given finite element mesh. In contrast to the checkerboard-free filter, the present filter focuses on high-frequency components of the sensitivities. Since the present filtering method does not add a penalty term to the objective function nor require additional constraints, it is not only efficient but also simple to implement. Mean compliance minimization and eigenfrequency maximization problems are considered to verify the effectiveness of the present approach.

• Management Science and Financial Engineering
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• 제12권2호
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

• KIEE International Transaction on Systems and Control
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• 제2D권2호
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• pp.115-119
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• 2002

In this paper we present a generalized directional morphological filtering algorithm for the removal of impulse noise, which is based on a combination of impulse noise detection and a weighted rank-order morphological filtering technique. For salt (or pepper) noise suppression, the generalized directional opening (or closing) filtering of the input signal is selectively used. The detection of impulse noise can be done by the geometrical difference of opening and closing filtering. Simulations show that this new filter has better detail feature preservation with effective noise reduction compared to other nonlinear filtering techniques.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.602-609
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• 2007

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system

• 한국통신학회논문지
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• 제34권6B호
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• pp.585-594
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• 2009

RFID 리더에서의 효율적인 필터링은 RFID 시스템의 성능에 있어 중요한 요소이다. RFID 기술 사용이 보편화되면 태그 및 리더의 수가 크게 늘고 리더가 필터링 없이 수집한 태그 정보 모두를 그대로 RFID 응용 시스템으로 전달할 경우 통신망 및 응용 시스템에 부하를 증가시켜 성능에 악영향을 미치기 때문이다. 본 논문은 RFID 무선 프로토콜 구간 필터링과 무선 인식 후 필터링이라는 단계적인 필터링 기능 조합으로 효과적으로 필터링을 수행하는 방법을 제안한다. 특히 계산 기하학을 활용하여 무선 프로토콜 구간의 필터링을 효율적으로 수행할 수 있는 구체적 방법론을 제시하였다. 시뮬레이션을 통해 제안한 방법의 성능을 검증하였는데 무선 프로토콜 구간의 필터링 없이 수행한 순차적인 필터링에 비해 성능이 50% 정도 개선됨을 확인하였다.