• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.565-570
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• 2012

This paper has proposed a multi-channel low pass filter (LPF) for LTE-Advanced systems. The proposed LPF is an active-RC 5th chebyshev topology with three cut-off frequencies of 5 MHz, 10 MHz, and 40 MHz. A 3-bit tuning circuit has been adopted to prevent variations of each cut-off frequency from process, voltage, and temperature (PVT). To achieve a high cut-off frequency of 40 MHz, an operational amplifier used in the proposed filter has employed a PMOS cross-connection load with a negative impedance. A proposed filter has been implemented in a 0.13-${\mu}m$ CMOS technology and consumes 20.2 mW with a 1.2 V supply voltage.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.423-431
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• 2000

This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• Korean Journal of Optics and Photonics
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• v.4 no.3
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• pp.301-308
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• 1993

Phenomenological nonlinear gain saturation effect on the modulation characteristics in a multi-electrode DBR laser, when the lasing wavelength changes, continuously is analized theoretically. FM efficiency, 3 dB bandwidth, and resonance frequency decrease with increasing bias current to the passive section, except increasing the flat FM response. It is found that the nonlinear gain saturation effect severely affects the modulation characteristics such as FM/IM response, 3 dB bandwidth, resonance frequency and CPR, but hardly affects the behavior of continuous frequency tuning.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.719-720
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• 2006

In the mechanical system, optimization of motion control is very essential in the aspect of automation technique progress. In the servo system, the function of controller is very important but most of the controllers have played only the role of pulse generator because the controller with main function is very expensive. In this thesis, the system was composed of PC, commonly used driver AC servo motor and a produced control board. The PC transmit a gain, a locus data to a driver and controller. At the same time, it converts imformation from the controller and convert them into data and offer an output with graph. The role of a controller is to trasmit a locus data to a driver and counting the pulse on the phase of an encoder to the PC. We have performed the experiment in order to confirm with variable PID parameter capable of the optimization of gain tuning with the counting of feedback control sensor signal with regard to the external interface into the system, such as torque. Based on the experiment result, we have confirmed as follows: First, it was confirmed that we could easily input control factors P.I Gain, constant $K_P,\;K_I$ into PC. Second, not only pulse generator function was possible, but with this pulse it was also possible to count using software with PIC chip. And third, using the multi-purpose PIC micro chip, simple operation and the formation of small size AC Servo Controller was possible.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.231-236
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• 2002

The classification of the speech-sound block comes from the multi-resolution analysis property of the discrete wavelet transform, which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract vapid speech-sounds in terms of position and frequency range. It performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising signal-to-noise ratio and a useful system tuning for the system implementation.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.56-61
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• 2013

Modern integrated circuits (ICs) are becoming an integrated parts of analog, digital, and radio frequency (RF) circuits. Testing these RF circuits on a chip is an important task, not only for fabrication quality control but also for tuning RF circuit elements to fit multi-standard wireless systems. In this paper, RF test circuits suitable for embedded testing are introduced: RF power detectors, power control circuits, directional couplers, and six-port reflectometers. Various types of embedded RF power detectors are reviewed. The conventional approach and our approach for the RF power control circuits are compared. Also, embedded tunable active directional couplers are presented. Then, six-port reflectometers for embedded RF testing are introduced including a 77-GHz six-port reflectometer circuit in a 130 nm process. This circuit demonstrates successful calibrated reflection coefficient simulation results for 37 well distributed samples in a Smith chart. The details including the theory, calibration, circuit design techniques, and simulations of the 77-GHz six-port reflectometer are presented in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1795-1811
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• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• Smart Structures and Systems
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• v.29 no.3
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• pp.457-473
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• 2022

A high-frequency vibration control method is proposed in this paper for Pumped Storage Power Plants (PSPPs) using Eddy Current Tuned Mass Damper (EC-TMD), based on which a new type of EC-TMD device is designed. The eddy current damper parameters are optimized by numerical simulation. On this basis, physical simulation model tests are conducted to compare and study the effect of structural performance with and without damping, different control strategies, and different arrangement positions of TMD. The test results show that EC-TMD can effectively reduce the control effect under high-frequency vibration of the plant structure, and after the additional damping device forms EC-TMD, the energy dissipation is further realized due to the intervention of eddy current damping, and the control effect is subsequently improved. The Multi-Tuned Mass Damper (MTMD) control strategy broadens the tuning band to improve the robustness of the system, and the vibration advantage is more obvious. Also, some suggestions are made for the placement of the dampers to promote their application.