• Structural Engineering and Mechanics
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• 제47권3호
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• pp.361-381
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• 2013

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

• 센서학회지
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• 제19권3호
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• pp.169-175
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• 2010

Urinalysis is an important clinical test to diagnose urinary diseases, and dipstick method with visual inspection is widely applied in practice. Automated optical devices recently developed have disadvantages of long measurement time, big size and heavy weight, accuracy degradation with time, etc. The present study proposed a new computer scanning technique, in which the test strip and the standard chart were simultaneously scanned to remove any environmental artifacts, followed by automated differentiation with the minimum distance algorithm, leading to significant enhancement of accuracy. Experiments demonstrated an accuracy of 100 % in that all test results were identical with the human visual inspection. The present technique only uses a personal computer with scanner and shortens the test time to a great degree. The results are also stored and accumulated for later use which can be transmitted to remote locations through a network, thus could be easily integrated to any ubiquitous health care systems.

• ETRI Journal
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• 제39권5호
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• pp.662-671
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• 2017

Coronary artery disease (CAD) is a major cause of death in the world. As a non-invasive imaging modality, computed tomography angiography (CTA) is now usually used in clinical practice for CAD diagnosis. Precise quantification of coronary stenosis is of great interest for diagnosis and treatment planning. In this paper, a novel cluster method based on a Modified Student's t-Mixture Model is applied to separate the region of vessel lumen from other tissues. Then, the area of the vessel lumen in each slice is computed and the estimated value of it is fitted with a curve. Finally, the location and the level of the most stenoses are captured by comparing the calculated and fitted areas of the vessel. The proposed method has been applied to 17 clinical CTA datasets and the results have been compared with reference standard degrees of stenosis defined by an expert. The results of the experiment indicate that the proposed method can accurately quantify the stenosis of the coronary artery in CTA.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1905-1910
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• 2003

It is well known that parameter uncertainties and time-delays cannot be avoided in practice and result in poor performance and even instability. Nevertheless, to the authors' best knowledge, there exist few results on model predictive control (MPC) handling explicitly uncertain time-delayed systems. In this paper, we present an MPC algorithm for uncertain time-varying systems with input constraints and state-delay. An optimization problem is suggested to find a memoryless state-feedback MPC law and the closed-loop stability is established under feasibility and certain conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2191-2208
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• 2022

Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.

• 한국전자파학회논문지
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• 제11권3호
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• pp.474-483
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• 2000

본 논문에서는 LMDS용 평변형 안테나로 28 GHz에서 동작하는 LTS 안테나와 Vivaldi 안테나를 시간영역 유한차분법(Finite Difference Time Domain Method)를 이용하여 최적화한 후 제작 및 측정하였다. 부엽의 크기 를 줄이기 위하여 corrugation 구조를 설계한 평변형 안테나에 적용하여 FDTD 방법으로 최적화 한 후, 제작 및 측정하였다. 측정결과, corrugation 구조를 갖는 LTS 안테나와 Vivaldi 안테나의 부엽의 크기가 약 4 dB 감소됨을 확인하였다.

• 한국토양비료학회지
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• 제46권6호
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• pp.458-462
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• 2013

A drainage ditch is normally a component of drainage networks in farming systems to remove surplus water, but at the same time, it may act as a major conduit of agricultural nonpoint source pollutions such as sediment, nitrogen, phosphorus, and so on. The hybrid turbidity reduction system using biodegradable check dam and synthetic polymer was developed in this study to manage pollutant discharge from agricultural farmlands during rainfall events and/or irrigation periods. The performance of this hybrid system was assessed using a laboratory open channel sized in 10m-length and 0.2m-width. Various check dams using agricultural byproducts (e.g., rice straw, rice husks, coconut fiber and a mixture of rice husks and coconut fiber) were tested and additional physical factors (e.g., channel slope, flowrate, PAM dosage, turbidity level, etc.) affecting on turbidity reduction were applied to assess their performance. A series of lab experiments clearly showed that the hybrid turbidity reduction system could play a significant role as a supplementary of Best Management Practice (BMP). Moreover, the findings of this study could facilitate to develop an advanced BMP for minimizing nonpoint source pollution from agricultural farmlands and ultimately to achieve the sustainable agriculture.

• Structural Engineering and Mechanics
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• 제78권4호
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• pp.425-437
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• 2021

Under foundation shock mats have been used in the current practice in order to reduce/damp vibrations received by buildings through the surrounding environment. Although some investigations have been made on under foundation shock mats performance, their effectiveness in the reduction of railway induced-vibrations has not been fully studied, particularly with the consideration of underneath soil media. In this regard, this research is aimed at investigating performance of shock mat used beneath building foundation for reduction of railway induced-vibrations, taking into account soil-structure interaction. For this purpose, a 2D finite/infinite element model of a building and its surrounding soil media was developed. It includes an elastic soil media, a railway embankment, a shock mat, and the building. The model results were validated using an analytical solution reported in the literature. The performance of shock mats was examined by an extensive parametric analysis on the soil type, bedding modulus of shock mat and dominant excitation frequency. The results obtained indicated that although the shock mat can substantially reduce the building vibrations, its performance is significantly influenced by its underneath soil media. The softer the soil, the lower the shock mat efficiency. Also, as the train excitation frequency increases, a better performance of shock-mats is observed. A simplified model/method was developed for prediction of shock mat effectiveness in reduction of railway-induced vibrations, making use of the results obtained.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.559-570
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• 2008

This paper proposes an improved particle swarm optimization named PSO with Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation diagram. Hence a stochastic velocity independent on cognitive and social components of PSO can be added to the updating principle, so that particles have strong exploration ability than those of conventional PSO. The conditions and main behaviors of PSO-CREV are described. Two properties in terms of "divergence before convergence" and "controllable exploration behavior" are presented, which promote the performance of PSO-CREV. An experimental method based on a complex test function is proposed by which the proper parameters of PSO-CREV used in practice are figured out, which guarantees the high exploration ability, as well as the convergence rate is concerned. The benchmarks and applications on FCRNN training verify the improvements brought by PSO-CREV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.597-618
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• 2019

Categorical range aggregation, which is conceptually equivalent to running a range aggregation query separately on multiple datasets, returns the query result on each dataset. The challenge is when the number of dataset is as large as hundreds or thousands, it takes a lot of computation time and I/O. In previous work, only a single dimension of the range restriction has been solved, and in practice, more applications are being used to calculate multiple range restriction statistics. We proposed MCRI-Tree, an index structure designed to solve multi-dimensional categorical range aggregation queries, which can utilize main memory to maximize the efficiency of CRA queries. Specifically, the MCRI-Tree answers any query in $O(nk^{n-1})$ I/Os (where n is the number of dimensions, and k denotes the maximum number of pages covered in one dimension among all the n dimensions during a query). The practical efficiency of our technique is demonstrated with extensive experiments.