• Steel and Composite Structures
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• v.22 no.2
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• pp.235-255
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• 2016

This paper experimentally investigated the behavior of steel frame structures of traditional-style buildings subjected to combined constant axial load and reversed lateral cyclic loading conditions. The low cyclic reversed loading test was carried out on a 1/2 model of a traditional-style steel frame. The failure process and failure mode of the structure were observed. The mechanical behaviors of the steel frame, including hysteretic behaviors, order of plastic hinges, load-displacement curve, characteristic loads and corresponding displacements, ductility, energy dissipation capacity, and stiffness degradation were analyzed. Test results showed that the Dou-Gong component (a special construct in traditional-style buildings) in steel frame structures acted as the first seismic line under the action of horizontal loads, the plastic hinges at the beam end developed sufficiently and satisfied the Chinese Seismic Design Principle of "strong columns-weak beams, strong joints-weak members". The pinching phenomenon of hysteretic loops occurred and it changed into Z-shape, indicating shear-slip property. The stiffness degradation of the structure was significant at the early stage of the loading. When failure, the ultimate elastic-plastic interlayer displacement angle was 1/20, which indicated high collapse resistance capacity of the steel frame. Furthermore, the finite element analysis was conducted to simulate the behavior of traditional-style frame structure. Test results agreed well with the results of the finite element analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.418-427
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• 2020

The measurement of meat freshness at meat markets is important for the health of consumers. Currently a variety of sensors have been studied for the measurement of the meat freshness. Therefore, the analysis of sensor data is needed for the reduction of measurement errors. In this paper, we analyze the freshness measurement data of ten sensors based on deep learning. The measured data are composed of beef, pork and chicken, whose reliability and noise-robustness are examined by a deep neural network. Further, to search for multiple sensors better than a torrymeter, PCA (principle component analysis) is carried. Then, we validated that the performance of the three sensors outperforms the torrymeter in the experiment.

• Journal of the Korean Society of Food Culture
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• v.29 no.6
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• pp.637-647
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• 2014

This study was conducted to examine the physicochemical properties and consumer acceptability of commercial Gang-jeong. The samples used in this study were nine different Gang-jeong as commercial products. To accomplish this research, the physicochemical properties of nine samples, including moisture, crude lipid, sugar contents, acid value, color values, and texture, were measured. In addition, consumer panels evaluated the overall acceptability, appearance, flavor, sweetness, and texture of samples using a 9-point Likert type scale as well as the perceived intensities of sweetness and rancid odor by a 9-point Just-About-Right (JAR) scale. All data were statistically analyzed using One-way ANOVA, Principle Component Analysis, Hierarchical Cluster Analysis, and Pearson's Correlation Analysis. All physicochemical properties were significantly different among the samples (p<0.001). Analyses of consumer acceptability and JAR ratings of the nine samples showed significant differences (p<0.001).

• Smart Structures and Systems
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• v.33 no.6
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• pp.385-398
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• 2024

To improve the accuracy of time-frequency analysis (TFA) and instantaneous frequency (IF) extraction of structural dynamic response signals, this paper improves the spline-kernelled chirplet transform, and a new form of modified spline-kernelled chirplet transform (MSCT) based on revised Gaussian window function and energy concentration principle is put forward. The effectiveness of the proposed method is verified by numerical examples of single-component signal, multicomponent signal, single-degree-of-freedom Duffing nonlinear system and two-layer shear frame structure model. Then, a time-varying cable test is designed to collect the acceleration response signals under linear changing tension, and the IF extraction of these signals is performed by using MSCT, which further verifies the effectiveness and accuracy of this method. Through numerical simulation and experimental verification, it is proved that the proposed method can effectively extract the IF of nonlinear structure and time-varying structure.

• Korean Journal of Food Science and Technology
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• v.47 no.1
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• pp.20-26
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• 2015

This study aimed to establish a rapid system for discriminating the cultivation origins and cultivars of dry persimmons, using metabolite fingerprinting by Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis. Whole-cell extracts from the sepals of four Korean cultivars and two different Chinese dry persimmons were subjected to FT-IR spectroscopy. Principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of the FT-IR spectral data successfully discriminated six dry persimmons into two groups depending on their cultivation origins. Principal component loading values showed that the 1750-1420 and $1190-950cm^{-1}$ regions of the FT-IR spectra were significantly important for the discrimination of cultivation origins. The accuracy of prediction of the cultivation origins and cultivars by PLS regression was 100% (p<0.01) and 85.9% (p<0.05), respectively. These results clearly show that metabolic fingerprinting of FT-IR spectra can be applied for rapid discrimination of the cultivation origins and cultivars of commercial dry persimmons.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.55-62
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• 2005

In this paper, we propose the face recognition system using HNMA(Hippocampal Neuron Modeling Algorithm) which can remodel the cerebral cortex and hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature-vector of the face images very fast and construct the optimized feature each image. The system is composed of two parts. One is feature-extraction and the other is teaming and recognition. In the feature extraction part, it can construct good-classified features applying PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis) in order. In the learning part, it cm table the features of the image data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in the dentate gyrus region and remove the noise through the associate memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are face changes, pose changes and low quality image. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.

• Steel and Composite Structures
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• v.49 no.1
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• pp.81-89
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• 2023

A simplified calculation method of natural vibration characteristics of high-speed railway multi-span bridge-longitudinal ballastless track system is proposed. The rail, track slab, base slab, main beam, bearing, pier, cap and pile foundation are taken into account, and the multi-span longitudinal ballastless track-beam-bearing-pier-cap-pile foundation integrated model (MBTIM) is established. The energy equation of each component of the MBTIM based on Timoshenko beam theory is constructed. Using the improved Fourier series, and the Rayleigh-Ritz method and Hamilton principle are combined to obtain the extremum of the total energy function. The simplified calculation formula of the natural vibration frequency of the MBTIM under the influence of vertical and longitudinal vibration is derived and verified by numerical methods. The influence law of the natural vibration frequency of the MBTIM is analyzed considering and not considering the participation of each component of the MBTIM, the damage of the track interlayer component and the stiffness change of each layer component. The results show that the error between the calculation results of the formula and the numerical method in this paper is less than 3%, which verifies the correctness of the method in this paper. The high-order frequency of the MBTIM is significantly affected considering the track, bridge pier, pile soil and pile cap, while considering the influence of pile cap on the low-order and high-order frequency of the MBTIM is large. The influence of component damage such as void beneath slab, mortar debonding and fastener failure on each order frequency of the MBTIM is basically the same, and the influence of component damage less than 10m on the first fourteen order frequency of the MBTIM is small. The bending stiffness of track slab and rail has no obvious influence on the natural frequency of the MBTIM, and the bending stiffness of main beam has influence on the natural frequency of the MBTIM. The bending stiffness of pier and base slab only has obvious influence on the high-order frequency of the MBTIM. The natural vibration characteristics of the MBTIM play an important guiding role in the safety analysis of high-speed train running, the damage detection of track-bridge structure and the seismic design of railway bridge.

• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.209-216
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• 2004

This study was aimed to assess the effects of microclimate factors on lettuce chlorophyll fluorescent responses and to develop an environment control system for plant growth by adopting a simple genetic algorithm. The photosynthetic responses measurements were repeated by changing one factor among six climatic factors at a time. The maximum Fv'/Fm' resulted when the ambient temperature was $21^{\circ}C,\;CO_2$ concentration range of 1,200 to 1,400 ppm, relative humidity of $68\%$, air current speed of $1.4m{\cdot}s^{-1}$, and the temperature of nutrient solution of $20^{\circ}C$. In PPF greater than $140{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, Fv'/Fm' values were decreased. To estimate the effects of combined microclimate factors on plant growth, a photosynthesis efficiency model was developed using principle component analysis for six microclimate factors. Predicted Fv'/Fm' values showed a good agreement to measured ones with an average error of $2.5\%$. In this study, a simple genetic algorithm was applied to the photosynthesis efficiency model for optimal environmental condition for lettuce growth. Air emperature of $22^{\circ}C$, root zone temperature of $19^{\circ}C,\;CO_2$ concentration of 1,400 ppm, air current speed of $1.0m{\cdot}s^{-1}$, PPF of $430{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, and relative humidity of $65\%$ were obtained. It is feasible to control plant environment optimally in response to microclimate changes by using photosynthesis efficiency model combined with genetic algorithm.

• Computers and Concrete
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• v.26 no.2
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• pp.185-201
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• 2020

This research is devoted to investigate the bending and free vibration behaviour of laminated composite/sandwich plates and shells, by applying an analytical model based on a generalized and simple refined higher-order shear deformation theory (RHSDT) with four independent unknown variables. The kinematics of the proposed theoretical model is defined by an undetermined integral component and uses the hyperbolic shape function to include the effects of the transverse shear stresses through the plate/shell thickness; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by employing the principle of virtual work and solved via Navier-type analytical procedure. To verify the validity and applicability of the present refined theory, some numerical results related to displacements, stresses and fundamental frequencies of simply supported laminated composite/sandwich plates and shells are presented and compared with those obtained by other shear deformation models considered in this paper. From the analysis, it can be concluded that the kinematics based on the undetermined integral component is very efficient, and its use leads to reach higher accuracy than conventional models in the study of laminated plates and shells.