• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.259-266
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• 2011

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.47-55
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• 2018

Purpose - To meet the needs of various customers in an uncertain market environment, many companies use product modularization strategies. Modularization of a product means that one product consists of several components and that the type of product can be changed according to the combination of components. The greatest feature of modularity is that changes in one component do not significantly affect the physical changes in the other component to which they are connected. Modularization of products is recognized as a very important strategy to reflect increasingly complicated customer requirements to products and respond to the needs of various markets. Many studies have been made in connection with the concept of mass customer satisfaction. There are many prior studies that modularization of such products positively affects the operational performance (manufacturing cost, fast delivery, etc.) and innovation of the product. However, excessive modularization has been found to have a negative effect on this performance. However, there are very few studies on the nonlinear relationship between product modularization and customer satisfaction. Supplementing these academically insufficient parts is very necessary when considering the current market environment. Research design, data, and methodology - In order to make up for the shortcomings of academic research in Korea, this study collects data through questionnaires in electronic, auto, and defense industry. This is because these industries are using modularity of products. based on lots of previous studies and information overload theory, we made two hypothesis and verify with empirical analysis. All 108 data were used. We used the R program and SPSS program for statistical verification. Results - As a result of the study, modularization of products showed positive relationship with customer satisfaction to a certain level. However, it has been found that when the modularization is over and beyond a certain level, there is a negative relationship with customer satisfaction. Conclusions - Excessive modularization of products can have a negative impact on customer satisfaction. This result can be understood as a result of human limited rationality due to information overload. Therefore, it is important for companies to apply appropriate modularity to product design.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.83-90
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• 2000

A simple low-cost and small size 1.88-198 GHz Band RF power amplifier module is developed for IMT2000 repeater. The power amplifier consists of two stage amplifiers that the first stage amplifier is drive amplifier using discrete type P-HEMT (ATF-34143, 800 micron gate width, Agilent Technologies) and the second is power amplifier with 300Bm 1dB gain compression point using GaAs FET(EFA240D-SOT89, 2400 micron gate width, Excelics Semiconductor). this power amplifier module feature a 29.5dBm 1dB gain compression point, 29.5dB gain, 42dBm 3rd order intercept point(OIP3) and -10dB/-l2dB input/output return loss over the 1880-1980 MHz. This PA module is fully integrated using MIC technology into a small size and design by full nonlinear design technologies. The dimensions of this PA module are 42(L) $\times$ 34(W) mm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.333-342
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• 2012

This paper presents a vowel onset point (VOP) detection method based on the human auditory system. This method maps the "perceptual" frequency scale, i.e. Mel scale onto a linear acoustic frequency, and then establishes a series of Triangular Mel-weighted Filter Bank simulate the function of band pass filtering in human ear. This nonlinear critical-band filter bank helps greatly reduce the data dimensionality, and eliminate the effect of harmonic waves to make the formants more prominent in the nonlinear spaced Mel spectrum. The sum of mel spectrum peaks energy is extracted as feature for each frame, and the instinct at which the energy amplitude starts rising sharply is detected as VOP, by convolving with Gabor window. For the single-word database which contains 12 vowels articulated with different kinds of consonants, the experimental results showed a good average detection rate of 72.73%, higher than other vowel detection methods based on short-time energy and zero-crossing rate.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.467-476
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• 1997

This paper presents a designing of a digital hearing aid processor (DHAP) chip being operated by a dedicated DSP core. The DHAP for hearing aid devices must be feasible within a size and power consumption required. Furthermore, it should be able to compensate for wide range of hearing losses and allow sufficient flexibility for the algorithm development. In this paper, a programmable 16-bit fixed-point DSP core is employed thor the designing of the DHAP. The designed DHAP performs a nonlinear loudness correction of 8 frequency bands based on audiometric measurements of impaired subjects. By employing a programmable DSP, the DHAP provides all the flexibility needed to implement audiological algorithms. In addition, the chip has low-power feature and $5, 500\times5000$$\mu$$m^2$ dimensions that fit for wearable hearing aids.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.1-12
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• 2021

In this paper, a new algorithm is proposed to estimate the damage location in the composite panel by extracting the elastic wave signal reflected from the damaged area. The guided elastic wave is generated by a piezoelectric actuator and sensed by a piezoelectric sensor. The proposed algorithm adopts a diagnostic approach. It compares the non-damaged signal with the damaged signal, and extract damage information along with sensor network and lamb wave group velocity estimated by signal correlation. However, it is difficult to clearly distinguish the damage location due to the nonlinear properties of lamb wave and complex information composed of various signals. To overcome this difficulty, the cumulative summation feature vector algorithm(CSFV) and a visualization technique are newly proposed in this paper. CSFV algorithm finds the center position of the damage by converting the signals reflected from the damage to the area of distance at which signals reach, and visualization technique is applied that expresses feature vectors by multiplying damage indexes. Experiments are performed for a composite panel and comparative study with the existing algorithms is carried out. From the results, it is confirmed that the damage location can be detected by the proposed algorithm with more reliable accuracy.

• Magazine of the Korea Concrete Institute
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• v.10 no.6
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• pp.269-280
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• 1998

Recently, application of composite materials such as fiber reinforced concretes(FRCs) and fiber reinforced plastics(FRPs) in conjunction with conventional structural components has become one of the main research areas. A proper use of advanced composite materials requires understanding their resistance mechanism and failure mode when they are applied to structures or their components. Particular considerations are given in this research to develop an analytical model which can predict the nonlinear flexural responses of bonded and unbonded prestressed concrete beams possibly having layers of different cementitious composite matrices in a section and/or FRP tendons. The block concept is used, which can be regarded as an intermediate modeling method between the couple method with one block and the layered method with multiply sliced layers in a section. In order to find a particular deflection point of a beam under load, solutions to the 2N-variables are found numerically by using approximate N-force equilibrium equations and N-moment equilibirum equations. The model is shown to successfully predict the flexual behavior of variously reinforced bonded and unbonded prestressed concrete beams. The model is also successful in simulating a gradually increasing load after sudden drop inload resistance due to fracture of one or more FRP tendons. This feature is useful in tracing the overall load-deflection response of a beam prestressed with brittle FRP tendons.

• Journal of Korea Soil Environment Society
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• v.1 no.1
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• pp.89-102
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• 1996

An integrated model is presented to describe underground flow and mass transport, using a multicomponent multiphase approach. The comprehensive governing equation is derived considering mass and force balances of chemical species over four phases(water, oil, air, and soil) in a schematic elementary volume. Compact and systemati notations of relevant variables and equations are introduced to facilitate the inclusion of complex migration and transformation processes, and variable spatial dimensions. The resulting nonlinear system is solved by a multidimensional finite element code. The developed code with dynamic array allocation, is sufficiently flexible to work across a wide spectrum of computers, including an IBM ES 9000/900 vector facility, SP2 cluster machine, Unix workstations and PCs, for one-, two and three-dimensional problems. To reduce the computation time and storage requirements, the system equations are decoupled and solved using a banded global matrix solver, with the vector and parallel processing on the IBM 9000. To avoide the numerical oscillations of the nonlinear problems in the case of convective dominant transport, the techniques of upstream weighting, mass lumping, and elementary-wise parameter evaluation are applied. The instability and convergence criteria of the nonlinear problems are studied for the one-dimensional analogue of FEM and FDM. Modeling capacity is presented in the simulation of three dimensional composite multiphase TCE migration. Comprehesive simulation feature of the code is presented in a companion paper of this issue for the specific groundwater or flow and contamination problems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.