• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1287-1300
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• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

• Structural Engineering and Mechanics
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• 제76권1호
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• pp.101-114
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• 2020

In this paper, an improved experience-based learning algorithm (EBL), termed as IEBL, is proposed to solve the nonlinear hysteretic parameter identification problem with Bouc-Wen model. A quasi-opposition-based learning mechanism and new updating equations are introduced to improve both the exploration and exploitation abilities of the algorithm. Numerical studies on a single-degree-of-freedom system without/with viscous damping are conducted to investigate the efficiency and robustness of the proposed algorithm. A laboratory test of seven lead-filled steel tube dampers is presented and their hysteretic parameters are also successfully identified with normalized mean square error values less than 2.97%. Both numerical and laboratory results confirm that, in comparison with EBL, CMFOA, SSA, and Jaya, the IEBL is superior in nonlinear hysteretic parameter identification in terms of convergence and accuracy even under measurement noise.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.415-421
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• 2007

This paper proposes a convolution tree kernel-based approach for relation extraction where the parse tree is expanded with entity features such as entity type, subtype, and mention level etc. Our study indicates that not only can our method effectively capture both syntactic structure and entity information of relation instances, but also can avoid the difficulty with tuning the parameters in composite kernels. We also demonstrate that predicate verb information can be used to further improve the performance, though its enhancement is limited. Evaluation on the ACE2004 benchmark corpus shows that our system slightly outperforms both the previous best-reported feature-based and kernel-based systems.

• ETRI Journal
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• 제29권5호
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• pp.700-702
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• 2007

We present a relevance feedback approach based on multi-class support vector machine (SVM) learning and cluster-merging which can significantly improve the retrieval performance in region-based image retrieval. Semantically relevant images may exhibit various visual characteristics and may be scattered in several classes in the feature space due to the semantic gap between low-level features and high-level semantics in the user's mind. To find the semantic classes through relevance feedback, the proposed method reduces the burden of completely re-clustering the classes at iterations and classifies multiple classes. Experimental results show that the proposed method is more effective and efficient than the two-class SVM and multi-class relevance feedback methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.843-846
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• 2000

An optical flow-based motion estimation algorithm is proposed for video coding. The algorithm uses block-matching motion estimation with an adaptive search region. The search region is computed from motion fields that are estimated based on the optical flow. The algorithm is based on the fact that true block-motion vectors have similar characteristics to optical flow vectors. Thereafter, the search region is computed using these optical flow vectors that include spatial relationships. In conventional block matching, the search region is fixed. In contrast, in the new method, the appropriate size and location of the search region are both decided by the proposed algorithm. The results obtained using test images show that the proposed algorithm can produce a significant improvement compared with previous block-matching algorithms.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.991-1000
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• 2020

We propose a content-based image retrieval system that uses a combination of completed local binary pattern (CLBP) and color autocorrelogram. CLBP features are extracted on a multi-resolution multi-direction filtered domain of value component. Color autocorrelogram features are extracted in two dimensions of hue and saturation components. Experiment results revealed that the proposed method yields a lot of improvement when compared with the methods that use partial features employed in the proposed method. It is also superior to the conventional CLBP, the color autocorrelogram using R, G, and B components, and the multichannel decoded local binary pattern which is one of the latest methods.

• Structural Engineering and Mechanics
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• 제69권5호
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• pp.479-486
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• 2019

Based on the displacement general solution of a pre-twisted Euler-Bernoulli beam, the shape function and stiffness matrix are deduced, and a new finite element model is proposed. Comparison analyses are made between the new proposed numerical model based on displacement general solution and the ANSYS solution by Beam188 element based on infinite approach. The results show that developed numerical model is available for the pre-twisted Euler-Bernoulli beam, and that also provide an accuracy finite element model for the numerical analysis. The effects of pre-twisted angle and flexural stiffness ratio on the mechanical property are also investigated.

• 한국멀티미디어학회논문지
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• 제25권9호
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• pp.1367-1374
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• 2022

In this paper, we propose an automatic cosmetic foundation recommendation system that suggests a good foundation product based on the user's skin color. The proposed system receives and preprocesses user images and detects skin color with OpenCV and machine learning algorithms. The system then compares the performance of the training model using XGBoost, Gradient Boost, Random Forest, and Adaptive Boost (AdaBoost), based on 550 datasets collected as essential bestsellers in the United States. Based on the comparison results, this paper implements a recommendation system using the highest performing machine learning model. As a result of the experiment, our system can effectively recommend a suitable skin color foundation. Thus, our system model is 98% accurate. Furthermore, our system can reduce the selection trials of foundations against the user's skin color. It can also save time in selecting foundations.

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.180-188
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• 2024

This research examined consumption-based carbon emission reduction by nuclear energy consumption and environmental tax while considering the context of trade globalization in the highest five emitter nations from 1990 to 2020. This study used various empirical methodologies, including preliminary analysis to check the stationarity and cointegration, the CS-ARDL for long-run analysis, CCEMG, AMG for robustness, and the D-H causality test for short-term pairwise causation. The results indicated that nuclear energy consumption, environmental tax, and trade globalization help to mitigate consumption-based carbon emissions while economic growth and population density boost carbon emissions. Furthermore, the results also found two-way casual connection exists between nuclear energy consumption, population density, and consumption-based carbon emissions. Thus, the results emphasize the need for government policies that encourage nuclear energy and environmental tax as a strategy to reduce carbon emissions and achieve and maintain environmental development.

• 한국학교보건학회지
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• 제24권2호
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• pp.181-189
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• 2011

Purpose: The purpose of this study was to identify the trend of overseas school health indicators and to investigate indicators comparable internationally. Methods: Using the key words, school, health, indicators and policy through formal literature and web sites, the resources were used after the completeness of resources such as the presence of author, year published and place, and reproducibility was evaluated. Results: In overseas, the interest of school health indicators has increased gradually since 1960. Quality indicators as well as quantitative indicators are important as the good school health indicators. The overseas school health indicators have been very comprehensive, not only including students, but also including the expanded population such as school personnel, parents, family and community, process and outcomes, policies, social and cultural environment. The trend of school health research is from traditional issue-based to indicatorbased which makes comprehensive interpretation including development of school health service and life satisfaction. Among internationally comparable indicators, Health Behaviour in School-aged Children (HBSC) and Global School-based Student Health Survey (GSHS) were chiefly for students' health and behavior level, and the School Health Service Survey (SHS) was for school health service personnel and policy. Conclusion: Characteristics of overseas school health indicators were expanded population, and comprehensive and internationally comparable indicators. Therefore, Korea school health indicators need to be comprehensive using expanded population and qualitative indicators, and consider standardized indicators comparable internationally.