• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.9-22
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• 2005

The allowed operation space for the mass damper in an active tuned mass damper (ATMD) system is limited for most civil structures. In this study, a restrained stroke active tuned mass damper (RS-ATMD) system with a end-spring and a holder that reduces the stroke of the mass damper with maintaining the control effect durably is proposed. This new control system functions as a conventional ATMD within the predetermined stroke limitation under small excitation and as an RS-ATMD beyond that limitation under large excitation. A new control algorithm considering such an operation principle of the RS-ATMD are also provided. Parameteric study for the various design factors of the RS-ATMD is conducted and the control effectiveness are investigated in comparison with the ATMD. Exposed to sinusoidal or impact load, the RS-ATMD system shows the considerable reduction of the maximum stroke of the mass damper with the slight diminution in the control effectiveness. Excited by random load, it also shows the considerable reduction of the maximum stroke of the mass damper not allowing the diminution in the control effectiveness.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.348-356
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• 2014

The existing effective path-length model of ITU-R has some drawbacks: The prediction error is quite large compared to domestic measurement data and it is an empirical model in which the physical characteristics of rain cells are not considered. In this paper, a theoretical model for effective path-length using the rain-cell concept was proposed and its validity was verified using the measurement data. To analyze the statistical characteristics of rain cell parameters, the weather-radar data(CAPPI) measured by Korea Meterological Administration were analyzed and the correction factor was properly introduced to fit the Chollian beacon measurement data of ETRI(Electronics and Telecommunications Research Institute). To verify the proposed effective path-length model, it was compared with the Mugunghwa No. 5 beacon data measured in Chungnam National University with the support of ADD(Agency for Defense Development). It was confirmed that the prediction results of the proposed model are in good agreement with the measurement data.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.4
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• pp.496-502
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• 2017

The purpose of this study is to investigate the applicability of surface-wave techniques for the evaluation of the crack-repairing performance of an epoxy injection method in concrete. In this study, box-shaped concrete specimens with four different crack depths were made with identical mix proportions. The specimens with different crack depths were completely repaired using the same epoxy injection method. The spectral energy transmission ratio of surface waves is used as an index to differentiate the effects of crack depth and crack-repairing performance. The decrease of spectral energy transmission ratio in accordance with the increase of crack depth was identified before repairing. Furthermore, the spectral energy transmission ratio increased after the crack-repairing process in all specimens. The spectral energy transmission ratio is considered as a great indicator for estimating the crack-repairing performance of the epoxy injection method; the ratio was recovered up to almost 95% of the uncracked condition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.47-52
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• 2005

Obstructive Sleep Apnea (OSA) is a representative symptom of sleep disorder caused by the obstruction of upper airway. Because OSA causes not only excessive daytime sleepiness and fatigue, hypertension and arrhythmia but also cardiac arrest and sudden death during sleep in the severe case, it is very important to detect the occurrence and the frequency of OSA. OSA is usually diagnosed through the laboratory-based Polysomnography (PSG) which is uncomfortable and expensive. Therefore researches to improve the disadvantages of PSG are needed and studies for the detection of OSA using only one or two parameters are being made as alternatives to PSG. In this paper, we developed an algorithm for the detection of OSA based on Heart Rate Variability (HRV). The proposed method is applied to the ECG data sets provided from PhysioNet which consist of learning set and training set. We extracted features for the detection of OSA such as average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-peak amplitude from data sets. These features are applied to the input of neural network. As a result, we obtained sensitivity of $89.66\%$ and specificity of $95.25\%$. It shows that the features suggested in this study are useful to detect OSA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of Korean Society of Forest Science
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• v.107 no.2
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• pp.140-150
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• 2018

For the estimation of greenhouse gas dynamics in forests, it is useful to use a model which simulates both carbon (C) and nitrogen (N) cycle simultaneously. A forest C model, called FBDC, was developed and validated in Korea. However, studies on development of forest N model are insufficient. This study aimed to suggest a development process of a forest C and N model. We analyzed the general features, structures, ecological processes, input data, output data, and methods of integrating C and N cycles of the VISIT, Biome-BGC, Forest-DNDC, and O-CN. The structure and features of the FBDC were also analyzed. The VISIT was developed by integrating forest C model with a N cycle module, and the new model also could be designed by combining the FBDC with a N cycle module. The VISIT and Forest-DNDC could estimate soil $N_2O$ emissions, and the integrated model should include the processes shared by these models. Especially, the overseas models linked C and N cycles based on N absorption, C absorption, and decomposition of dead organic matter. Therefore, the integration of the FBDC with N cycle module should apply this linkage of structures between C and N cycles. Climate, soil texture, and species distribution data, which are essential for the model development, were available in Korea. However, parameter data associated with N cycle and validation data for soil $N_2O$ emissions need to be obtained by field studies.

• Journal of the Korean Chemical Society
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• v.47 no.3
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• pp.206-212
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• 2003

The reaction rates of substituted quinolines (6-Clqui., qui.) with p-substituted benzoylchlorides $(p-CH_3,\;p-H,\;p-NO_2)$ have been measured by conductometry in acetonitrile, and the rate constants are determined at various temperatures (10, 15, 20, $25^{\circ}C$) and pressures (1, 200, 500, 1000 bar). From the values of rate constants, the activation parameters $(Ea,\;{\Delta}V^{\neq},\;{\Delta}H^{\neq},\;{\Delta}S^{\neq}, \;{\Delta}G^{\neq})$and the pressure dependence of Hammett ρ values were determined. The rate constants increased with increasing temperatures and pressures, and are further increased to introduction to the electron acceptor substituents in substrate $(p-NO_2)$ with quinoline. The activation volume and the activation entropy are all negative. And the Hammett p values are negative for nucleophile ${\rho}_X$ and positive for the substrate ${\rho}_Y$ over the pressure range studied. The results of kinetic studies for pressure and substituent show that these reactions proceed through a typical $S_N2$ reaction mechanism and "associative $S_N2$" favoring bond formation with increasing pressures.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.3
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• pp.265-272
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• 2020

The body odor as well as the skin changes has become an important issue. Humans leave respective specific odors dependent on sex and age; The odor has been known to affect social relationship of human. In this study, we wanted to confirm the possibility as parameters to evaluate body odor into existing odor evaluation methods by experts. The 15 subjects, aged from 50 to 61 years wore cotton t-shirts for 72 hours and collected body odor. The cotton t-shirts containing body odor were used for sensory evaluation and EEG measurement by the odor experts. In order to evaluate body odors of each subject, an odor sensory evaluation and electroencephalogram (EEG) were conducted by odor exports and the correlation in between two assessments was analyzed. Pearson correlation analysis shows negative correlation of the sensory evaluation versus 'Excitement' in EEG parameter (r = - 0.649, p = 0.009) and positive correlation of the sensory evaluation versus 'Stress' in EEG parameter (r = 0.704, p = 0.003). In conclusion, it is considered that the evaluation of body odor through EEG measurement can be used as a method to complement the odor evaluation by experts.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.17-21
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• 2008

Because of the reason that the meningioma is enhanced lately, we started the study to maximally enhance the meningioma. we were to know the relation between meningioma and vessels in the skull and compared 3D CT angiography with the conventional angiography. we got the data from 6 patients performed by both 3D CT angiography and there were 5 cases in sphenoidal ridge and 1 case parasagittal sinus. Injecting the contrast media at 3 ml/sec, 120 ml and then the CT number reached 100, we started the study using the medical system Program(smart prep). The scan parameters were HS-Mode(1.25 mm / 7.5 mm) right after being injected all and reconstructed with 0.5 mm interval. We compared the study with the conventional angiography after reconstructing the images required by using 3D-Med software Program(Rapidia). Seeing the consequences, the maximum enhancing time in the menigioma is about 120~180 seconds after injecting the contrast media and we distinguished the relation between vessels and tumors at the time and 1 case showed us the aneurysm with a tumor clearly at the time too. It was very helpful to the operation that the 3D images required by injecting the contrast media to the patients with meningioma distingushed between tumors and vessels dimensionally.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.629-635
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• 2019

In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.