• 전기학회논문지
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• 제58권1호
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• pp.173-180
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• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

• 대한의용생체공학회:의공학회지
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• 제26권4호
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• pp.231-241
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• 2005

New methods to register multiple hemispheric slices of the postmortem brain to anatomically corresponding in-vivo MRI slices within a 3D volumetric MRI are presented. Gel-embedding and fiducial markers are used to reduce geometrical distortions in the postmortem brain volume. The registration algorithm relies on a recursive extraction of warped MRI slices from the reference MRI volume using a modified non-linear polynomial transformation until matching slices are found. Eight different voxel similarity measures are tested to get the best co-registration cost and the results show that combination of two different similarity measures shows the best performance. After validating the implementation and approach through simulation studies, the presented methods are applied to real data. The results demonstrate the feasibility and practicability of the presented co­registration methods, thus providing a means of MR signal analysis and histological examination of tissue lesions via co­registered images of postmortem brain slices and their corresponding MRI sections. With this approach, it is possible to investigate the pathology of a disease through both routinely acquired MRls and postmortem brain slices, thus improving the understanding of the pathological substrates and their progression.

• 한국소음진동공학회논문집
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• 제18권2호
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• pp.224-230
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• 2008

This paper is concerned with the active vibration control of building structure by means of the active tuned mass damper and the modified positive position feedback controller. To this end, one-degree-of-freedom spring-mass-damper system equipped with ATMD is considered. The stability condition for the addressed system when applying the proposed PPF controller is derived by Routh-Hurwitz stability criterion. The stability condition shows that the modified PPF controller is absolutely stable if the controller gain is positive. so that the modified PPF controller can be used without difficulty. Theoretical study shows that the modified PPF controller can effectively suppress vibrations as the original PPF controller does in smart structure applications. To investigate the validity of the modified PPF controller, a simple experimental structure with an ATMD system driven by DC motor was built. The modified PPF control algorithm was implemented on Atmel 128 microcontroller. The experimental result shows that the modified PPF controller can also suppress vibrations for the real structure.

• 정보관리연구
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• 제42권3호
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• pp.167-186
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• 2011

동시인용은 서로 다른 두 연구가 이후의 새로운 연구에서 동시 인용되는 것이다. 이 연구는 동시인용과 저자식별의 관계를 다룬다. 저자식별은 문헌에 출현한 동명의 저자명들을 실 세계 저자로 식별하는 것이다. 동시인용은, 한 사람의 관련된 연구들이 이후 또 다른 연구들에서 타인 혹은 자신에 의해 동시 인용되는 증거를 수집함으로써, 저자식별의 절차와 성능에 영향을 미칠 수 있다. 이 연구는 구글 스칼라로부터 동시인용을 자동 수집하는 절차를 제시하고 동시인용 정보를 저자식별의 기존 자질들과 효율적으로 결합하는 새로운 군집알고리즘을 제안한다. 실험을 통해 동시인용이 저자식별에 미치는 긍정적 효과를 확인하였다.

• 한국인터넷방송통신학회논문지
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• 제13권4호
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• pp.61-66
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• 2013

교통관리 시스템에서 돌발상황 관리시스템은 매우 중요한 역할을 차지하고 있다. 여러 종류의 알고리즘이 사용되고 있는데 이 중에서 APID, DELOS가 가장 많이 사용되고 있다. 검지알고리즘의 경우는 localization이 중요하며 교통상황에 적합한 파라미터의 검증과, 검지기 자료의 유효성 문제가 지적되고 있다. 본 논문에서는 APID, DELOS 돌발상황 검지알고리즘의 평가를 위해 방법론 및 시나리오를 구성하여 교통여건별, 시나리오별로 평가하였다. 특히, 알제리의 실제 도로망을 이용하여 평가를 진행하였다. 모든 조건을 만족하는 하나의 돌발상황 검지알고리즘을 개발한다는 것은 어려우며 각 도로 및 교통조건에 맞추어 최적의 알고리즘을 적용하는 것이 바람직할 것으로 판단된다.

• 산업기술연구
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• 제30권A호
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• pp.111-117
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• 2010

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1891-1908
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• 2021

Cyber deception defense mitigates Advanced Persistent Threats (APTs) with deploying deceptive entities, such as the Honeyfile. The Honeyfile distracts attackers from valuable digital documents and attracts unauthorized access by deliberately exposing fake content. The effectiveness of distraction and trap lies in the enticement of fake content. However, existing studies on the Honeyfile focus less on this perspective. In this work, we seek to improve the enticement of fake text content through enhancing its readability, indistinguishability, and believability. Hence, an enticing deceptive-content generator, EDGE, is presented. The EDGE is constructed with three steps: extracting key concepts with a semantics-aware K-means clustering algorithm, searching for candidate deceptive concepts within the Word2Vec model, and generating deceptive text content under the Integrated Readability Index (IR). Furthermore, the readability and believability performance analyses are undertaken. The experimental results show that EDGE generates indistinguishable deceptive text content without decreasing readability. In all, EDGE proves effective to generate enticing deceptive text content as deception defense against APTs.

• International journal of advanced smart convergence
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• 제10권1호
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• pp.105-116
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• 2021

In order to preserve the seeds of excellent Hanwoo(Korean traditional cattle) and secure quality competitiveness in the infinite competition with foreign imported beef, production of high-quality Hanwoo beef is absolutely necessary. %IMF (Intramuscular Fat Percentage) is one of the most important factors in evaluating the value of high-quality meat, although standards vary according to food culture and industrial conditions by country. Therefore, it is required to develop a %IMF estimation algorithm suitable for Hanwoo. In this study, we proposed a method of estimating %IMF of Hanwoo using CNN in ultrasound images. First, the proposed method classified the chemically measured %IMF into 10 classes using k-means clustering method to apply CNN. Next, ROI images were obtained at regular intervals from each ultrasound image and used for CNN training and estimation. The proposed CNN model is composed of three stages of convolution layer and fully connected layer. As a result of the experiment, it was confirmed that the %IMF of Hanwoo was estimated with an accuracy of 98.2%. The correlation coefficient between the estimated %IMF and the real %IMF by the proposed method is 0.97, which is about 10% better than the 0.88 of the previous method.

• Tribology and Lubricants
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• 제38권4호
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• pp.128-135
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• 2022

In the product development process, the reliability of the product can be secured through durability tests. However, since the durability test method is expensive and time consuming, a method to save time and money by utilizing virtual product development (VPD) is required. However, research on the accuracy of the results of virtual product development is required. In this paper, an accelerated durability test was designed and conducted using a planetary gear decelerator. And an analysis model under the same conditions was created and simulated. To correlate the results of the experiment with the results of the analytical model, created a model that can discriminate the wear region using one of the data mining methods, the k-means algorithm method and HSV (Hue, Saturation, Value). The wear area is compared by counting the number of pixels defined as wear through a discrimination model. A similar ratio was calculated by comparing the pixel ratio of the area determined as wear in the entire area. It showed a similar ratio of about 70%, and it is necessary to improve the discrimination method.