• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1651-1656
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• 1995

The adhesively bonded tubular single lap joint shows large nonlinear behavior in the loaddisplacement relation, because structural adhesives for the joint are usually rubber toughened, which endows adhesives with nonlinear shear properties. since the majority of load transfer of the adhesively bonded tubular single lap joint is accomplished by the nonlinear behavior of the adhesive, its torque transmission capability should be calculated incorporating nonlinear shear properties. However, both the analytic and numerical analyses become complicated if the nonlinear shear properties of the adhesive are included during the calculation of torque transmission capabilities. In this paper, in order to obtain the torque transmission capabilities easily, an iterative solution which includes the nonlinear shear properties of the adhesive was derived using the analytic solution with the linear shear properties of the adhesive. Since the iterative solution can be obtained very fast due to its simplicity, it has been found that it can be used in the design of the adhesively bonded tubular single lap joint.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.276-282
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• 2013

Self-encoded spread spectrum (SESS) is a novel modulation technique that acquires its spreading code from a random information source, rather than using the traditional pseudo-random noise (PN) codes. In this paper, we present our study of the SESS system performance under pulsed-noise jamming and show that iterative detection can significantly improve the bit error rate (BER) performance. The jamming performance of the SESS with correlation detection is verified to be similar to that of the conventional direct sequence spread spectrum (DSSS) system. On the other hand, the time diversity detection of the SESS can completely mitigate the effect of jamming by exploiting the inherent temporal diversity of the SESS system. Furthermore, iterative detection with multiple iterations can not only eliminate the jamming completely but also achieve a gain of approximately 1 dB at $10^{-3}$ BER as compared with the binary phase shift keying (BPSK) system under additive white gaussian noise (AWGN) by effectively combining the correlation and time diversity detections.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.3
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• pp.3-6
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• 2008

Electrolytic in-process dressing (ELID) grinding is a new technique for achieving a nanoscale surface finish on hard and brittle materials such as optical glass and ceramics. This process applies an electrochemical dressing on the metal-bonded diamond wheels to ensure constant protrusion of sharp cutting grits throughout the grinding cycle. In conventional ELID grinding, a constant source of pulsed DC power is supplied to the ELID cell, but a feedback mechanism is necessary to control the dressing power and obtain better performance. In this study, we propose a new closed-loop wheel dressing technique for grinding wheel truing that addresses the efficient correction of eccentric wheel rotation and the nonuniformity in the grinding wheel profile. The technique relies on an iterative control algorithm for the ELID power supply. An inductive sensor is used to measure the wheel profile based on the gap between the sensor head and wheel edge, and this is used as the feedback signal to control the pulse width of the power supply. We discuss the detailed mathematical design of the control algorithm and provide simulation results that were confirmed experimentally.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.74-80
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• 2001

Because of ocean waves, swell, steering corrections, etc, the hydrophones of a towed array will not live along a straight line. However the degradation of bearing estimation performance occurs when beamforming is carried out on the hydrophone outputs of an acoustic towed array which is not straight. So it is required to estimate the shape of the array for the improved beamformer output. In this paper, an iterative array shape estimation technique is presented, which is based on the use of the least squares polynomial fitting to the data from heading sensors. The estimation error and the influence of deformations on the performance of the conventional beamformer output are investigated. Finally, the suggested method is applied to the real system in order to investigate the applicability.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.57-60
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• 1999

An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.275-283
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• 2004

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive Approximation, is a competent strategy via MDO framework systems.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1817-1824
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• 1990

This paper describes a shape matching algorithm for occluded or distorted two-dimensional objects. In our approach, the shape matchin is viewed as a segment matching problem. A shape matching algorithm, based on both the stochastic labeling technique and the hypothesis generate-test paradigm, is proposed, and a simple technique which performs the stochastic labeling process in accordance with the definition of consisten labeling assignment without requiring an iterative updating process of probability valiues is also proposed. Several simulation results show that the proposed algorithm is very effective when occlusion, scaling or change of orientation has occurred in the object.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1857-1866
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• 1989

In this paper, an algorithm to update a codebook using a neural network in consecutive images, is proposed. With the Kohonen's self-organizing feature map, we adopt the iterative technique to update a centroid of each cluster instead of the unsupervised learning technique. Because the performance of this neural model is comparable to that of the LBG algorithm, it is possible to update the codebooks of consecutive frames sequentially in TV and to realize the hardwadre on the real-time implementation basis.

• Journal of applied mathematics & informatics
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• v.33 no.3_4
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• pp.401-415
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• 2015

In this paper, we propose a modified proximal point algorithm which consists of a resolvent operator technique step followed by a generalized projection onto a moving half-space for approximating a solution of a variational inclusion involving a maximal monotone mapping and a monotone, bounded and continuous operator in Banach spaces. The weak convergence of the iterative sequence generated by the algorithm is also proved.