• 제어로봇시스템학회논문지
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• 제6권10호
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• pp.845-853
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• 2000

In this paper, we introduce a relationship between the sensitivity and the robustness of a system, and we propose a robust eigenstructure assignment scheme using a novel performance index which can consider the performance and the robustness of the system simultaneously. We also propose an assignment accuracy measure and a robustness measure which are used for the performance examination of the proposed robust eigenstructure assignment scheme. The usefulness of the proposed algorithm and the measures are verified by applying to controller design of a simple numerical example and the EMRAAT missile.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.263-268
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• 2022

Precise Point Positioning-Real Time Kinematic (PPP-RTK) is a high accuracy positioning method that combines RTK and PPP to overcome the limitations on service coverage of RTK and convergence time of PPP. PPP-RTK provides correction data in the form of State Space Representation (SSR), unlike RTK, which provides measurement-based Observation Space Representation (OSR). Due to this, PPP-RTK has an advantage that it can transmit less data than RTK. So, recently, several techniques for PPP-RTK have been proposed. However, in order to utilize PPP-RTK techniques, performance analysis of these in a real environment is essential. In this paper, we implement the local network PPP-RTK and analyze the positioning performance according to the distance within 100 km from the reference station in Korea. As results of experiment, the horizontal and vertical 95% errors of local network PPP-RTK were 6.25 cm and 5.86 cm or less, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1649-1665
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• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

• 대한인간공학회지
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• 제24권2호
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• pp.45-49
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• 2005

The FSA(Force Sensitive Application) system measures hand force by using force resistance sensors. Compared to conventional hand force measurement systems such as Lafayette hand dynamometer and Jamar hydraulic hand dynamometer, the FSA system can be applied to analyze use of hand forces while the hand is manipulating objects for a task, However, the measurement performance of the FSA system has not been objectively evaluated. The present study tested the FSA system in terms of stability, repeatability, accuracy, and linearity. It is shown that the FSA system has good stability (CV$\leq$0.02) and linearity($R^2$=0.82), but has low repeatability(CV=$0.11{\sim}0.19$) and accuracy(22% of underevaluation on average). This performance result indicates that measurements from the FSA system should be used for relative comparison rather than for absolute comparison.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2348-2360
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• 2023

As science and technology evolve, object detection of moving objects has been widely used in the context of machine learning and artificial intelligence. Traditional moving object detection algorithms, however, are characterized by relatively poor real-time performance and low accuracy in detecting moving objects. To tackle this issue, this manuscript proposes a modified Kalman filter algorithm, which aims to expand the equations of the system with the Taylor series first, ignoring the higher order terms of the second order and above, when the nonlinear system is close to the linear form, then it uses standard Kalman filter algorithms to measure the situation of the system. which can not only detect moving objects accurately but also has better real-time performance and can be employed to predict the trajectory of moving objects. Meanwhile, the accuracy and real-time performance of the algorithm were experimentally verified.

• 대한의용생체공학회:의공학회지
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• 제40권6호
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• pp.242-249
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• 2019

Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

• Earthquakes and Structures
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• 제15권6호
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• pp.595-603
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• 2018

Shake table testing has been regarded as one of the most effective experimental approaches to evaluate seismic response of structural systems subjected to earthquakes. However, reproducing a prescribed acceleration time history precisely over the frequency of interest is challenging because shake table test systems are eventually nonlinear by nature. In addition, interaction between the table and specimen could affect the control accuracy of shake table testing significantly. Various novel control algorithms have been proposed to improve the control accuracy of shake table testing; however, reference values for control performance assessment remain rare. In this study, reference values for control performance assessment of shake table testing are specified based on the statistical analyses of 1,209 experimental data provided by the Seismic Simulator Laboratory of National Center for Research on Earthquake Engineering in Taiwan. Three individual reference values are considered for the assessment including the root-mean-square error of the achieved acceleration time history; the percentage of the spectral acceleration that exceeds the determined tolerance range over the frequency of interest; and the error-ratio of the achieved peak ground acceleration. Quartiles of the real experimental data in terms of the three objective variables are obtained, providing users with solid and simple references to evaluate the control performance of shake table testing. Finally, a set of experimental data of a newly developed control framework implementation for uni-axial shake tables are used as an application example to demonstrate the significant improvement of control accuracy according to the reference values provided in this study.

• 한국항공운항학회지
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• 제18권1호
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• pp.39-44
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• 2010

A method is presented of dynamic determination of mode transition probability for IMM in order to improve the accuracy performance of maneuvering target tracking for air traffic control surveillance processing system under multiple radar environment. It is shown that dynamic determination of mode transition probability based on the time intervals between the data input from multiple radars gives the optimized performance in terms of position estimation accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• Journal of Positioning, Navigation, and Timing
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• 제10권3호
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• pp.159-168
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• 2021

Precise Point Positioning-Real Time Kinematic (PPP-RTK) is an improved PPP method that provides the user receiver with satellite code and phase bias correction information in addition to the satellite orbit and clock, thus enabling single-receiver ambiguity resolution. Single station PPP-RTK concept is special case of PPP-RTK in that corrections are computed, instead of a network, by only one single GNSS receiver. This study is performed to experimentally verify the positioning accuracy performance of single baseline RTK level by a user who utilizes correction for a single station PPP-RTK using dual frequencies. As an experimental result, the horizontal and vertical 95% accuracy was 2.2 cm, 4.4 cm, respectively, which verify the same performance as the single baseline RTK.