• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1165-1171
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• 2022

Human behavior recognition using an accelerometer has been applied to various fields. As smartphones have become used commonly, a method for human behavior recognition using the acceleration sensor built into the smartphone is being studied. In the case of the elderly, falling often leads to serious injuries, and falls are one of the major causes of accidents at construction fields. In this article, we proposed recognition method for human falling direction using built-in acceleration sensor and orientation sensor in the smartphone. In the past, it was a common method to use the magnitude of the acceleration vector to recognize human behavior. These days, deep learning has been actively studied and applied to various areas. In this article, we propose a method for recognizing the direction of human falling by applying the deep learning multilayer technique, which has been widely used recently.

• Computational Structural Engineering
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• v.8 no.4
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• pp.181-187
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• 1995

Recent researches in dynamics are focused on finding effective methods to analyze the dynamic behavior of structures by fewer mode shapes their number of dgrees of freedom. Ritz algorithm and mode acceleration method were developed to improved the mode superposition. Ritz algorithm can include distribution of external loads but be apt to lose the orthogonality condition, which is useful properties in the analysis. Also mode acceleration method should consider a large number of mode shapes to get a satisfactory results. Another method, combining previous two method, was developed but too much computational efforts and times were required. The purpose of this study is to develop and evaluate the Ritz algorithm modified with the lanczos algorithm to improve the efficiency and accuracy. As a result of !this study, dynamic analysis using modified Ritz algorithm was proved to be the rational analysis method.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.144-151
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• 2005

We evaluate the performance of emotion recognition via speech signals when a plain speaker talks to an entertainment robot. For each frame of a speech utterance, we extract the frame-based features: pitch, energy, formant, band energies, mel frequency cepstral coefficients (MFCCs), and velocity/acceleration of pitch and MFCCs. For discriminative classifiers, a fixed-length utterance-based feature vector is computed from the statistics of the frame-based features. Using a speaker-independent database, we evaluate the performance of two promising classifiers: support vector machine (SVM) and hidden Markov model (HMM). For angry/bored/happy/neutral/sad emotion classification, the SVM and HMM classifiers yield $42.3\%\;and\;40.8\%$ accuracy, respectively. We show that the accuracy is significant compared to the performance by foreign human listeners.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1276-1286
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• 2002

The numerical techniques are presented to solve the static and dynamic contact problems of deformable bodies having large rotations of the contact surfaces. The contact conditions on the possible contact surfaces are enforced by using the contact error vector, and an iterative scheme similar to augmented Lagrange multiplier method is employed to reduce the contact error vector monotonically. For dynamic contact problems using implicit time integration, a contact error vector is also defined by combining the displacement, velocity, and acceleration on the contact surface. The suggested iterative technique is implemented to ABAQUS by using the UEL subroutine UEL. In this work, after the computing procedures to solve the frictional contact problems are explained, the numerical examples are presented to compare the present solutions with those obtained by ABAQUS.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.287-292
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• 1998

This paper presents some results of performance evaluation test via actual machines of a new hybrid vector control utilizing a new indirect orientation scheme and stable filter embedded direct orientation scheme for induction motors without speed or position sensor. It is shown through the test by 0.3(kW) and 3.7(kW) motors that the proposed sensorless vector control has the following high potentialities: 1) speed range is 0 to 600(rad/s) or more, 2) zero-speed command is accepted and settles the machines at a stable standstill with no vibration 3) it can make machines to track variable command of acceleration and deceleration $\pm$6,000(rad/s2), 4) it can make machines to drive directly load of at least 26 times larger inertia than that of the machine, 5) it can make machines to produce much larger torque than the rating in torque control mode even at standstill. The performance confirmed by the test is far away for previous schemes or sensorless drive apparatuses.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.574-578
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• 2008

In order to achieve thrust vector control and discharge stabilization in Hall thrusters, the azimuthal nonuniformity of propellant flow rate in an acceleration channel was created. A plenum chamber was divided into two rooms by two walls and propellant flow rate supplied to each section was independently controlled. In a magnetic layer type Hall thruster, steering angle of up to ${\pm}2.3$ degree was achieved. In an anode layer type Hall thruster, discharge current oscillation amplitude was decreased with the normalized differential mass flow rate.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.160-165
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• 2014

In this study, an efficiency test was performed by fabricating MEMS (Micro Electro Mechanical Systems) based 3-axis acceleration sensor modules and an earthquake monitoring system was composed. Data acquisition device (NI-9239) with a 24bit ADC (Analog to Digital Converter) was used for improving the performance of 3-axis acceleration sensor modules and filtered data (100Hz Low Pass Filter) was used for reducing noises. Also this paper focused on detecting meaningful vibration in the building by developing the earthquake monitoring software. If vector sum of 3-axis acceleration is greater than the preset value, the value will be recorded and saved to the file.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.956-962
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• 2020

Recently, as the size of data used in an embedded system increases, the need for an ECC decoding operation to robustly receive a massive data is emphasized. In this paper, we propose a method to accelerate the execution of computations that derive syndrome vectors when ECC decoding is performed using Hamming code in an embedded system with a built-in GPU. The proposed acceleration method uses the matrix-vector multiplication of the decoding operation using the CSR format, one of the data structures representing sparse matrix, and is performed in parallel in the CUDA kernel of the GPU. We evaluated the proposed method using a target embedded board with a GPU, and the result shows that the execution time is reduced when ECC decoding operation accelerated based on the GPU than used only CPU.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.49-60
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• 2022

Motivated by the high-resolution properties of high-order Weighted Essentially Non-Oscillatory (WENO) and flux limiter (FL) for steep-gradient problems and the robust convergence of Jacobian-free Newton-Krylov (JFNK) methods for nonlinear systems, the preconditioned JFNK fully implicit high-order WENO and FL schemes are proposed to solve the transient two-phase two-fluid models. Specially, the second-order fully-implicit BDF2 is used for the temporal operator and then the third-order WENO schemes and various flux limiters can be adopted to discrete the spatial operator. For the sake of the generalization of the finite-difference-based preconditioning acceleration methods and the excellent convergence to solve the complicated and various operational conditions, the random vector instead of the initial condition is skillfully chosen as the solving variables to obtain better sparsity pattern or more positions of non-zero elements in this paper. Finally, the WENO_JFNK and FL_JFNK codes are developed and then the two-phase steep-gradient problem, phase appearance/disappearance problem, U-tube problem and linear advection problem are tested to analyze the convergence, computational cost and efficiency in detailed. Numerical results show that WENO_JFNK and FL_JFNK can significantly reduce numerical diffusion and obtain better solutions than traditional methods. WENO_JFNK gives more stable and accurate solutions than FL_JFNK for the test problems and the proposed finite-difference-based preconditioning acceleration methods based on the random vector can significantly improve the convergence speed and efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1664-1670
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• 1991

For kinematically redundant manipulators, conventional dynamic control methods of local torque optimization showed the instability which resulted in physically unachievable torque requirements. In order to guarantee stability of the null space vector method which resolves redundancy at the acceleration level, Maciejewski[1] analyzed the kinetic behavior of homogeneous solution component and proposed the condition to identify regions of stability and instability for this method. 'In this paper, a modified null space vector method is first presented based on the Maciejewski's condition which is a function of a manipulator's configuration. Secondly, a new control method which is based on the concept of aspects is proposed. It was shown by computer simulations that the modified null space vector method and the proposed method have a common property that a preferred aspect is preserved during the execution of a task. It was also illustrated that both methods demonstrate a drastic reduction of torque loadings at the joints in the tracking motion of a long trajectory when compared with the null space vector method, and thus guarantee the stability of joint torque.