• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.761-773
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• 2023

This paper proposes a method to increase the power-analysis resistance of the neural network model's feedforward process by replacing the exponential-based activation function, used in the deep-learning field, with an approximated function especially at the multi-layer perceptron model. Due to its nature, the feedforward process of neural networks calculates secret weight and bias, which already trained, so it has risk of exposure of internal information by side-channel attacks. However, various functions are used as the activation function in neural network, so it's difficult to apply conventional side-channel countermeasure techniques, such as masking, to activation function(especially, to exponential-based activation functions). Therefore, this paper shows that even if an exponential-based activation function is replaced with approximated function of simple form, there is no fatal performance degradation of the model, and than suggests a power-analysis resistant feedforward neural network with exponential-based activation function, by masking approximated function and whole network.

• Journal of the Korean Wood Science and Technology
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• v.20 no.4
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• pp.21-30
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• 1992

An activation energy equation for moisture diffusion in wood was developed with an assumption that activation energy is directly proportional to wood specific gravity. Theoretical activation energies obtained from the activation energy equation were revealed to be always lower than actual activation energies, which implies that activation energy isn't affected only by wood specific gravity. The other affecting factors are possibly anatomical structures of wood which determine a ratio of vapor diffusion to bound water diffusion in wood. For the convenience of estimating actual activation energy by using the activation energy equation, thirteen kinds of species were categorized into three groups according to their anatomical structures.

• Fire Science and Engineering
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• v.10 no.4
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• pp.13-18
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• 1996

A general description of sprinkler activation time in compartment-fire-generated smoke layers is made. For calculation of the time hot layer temperature is obtained from two-layer zonal model and time constant of sprinkler is measured. Upper-layer thickness at the instant of sprinkler activation is also presented with changes of opening area. The output of the present study provide inputs for the interaction modeling of sprinkler spray and compartment fire environment, which simulates fire suppression phenomena. Futhermore, experiments are performed in mock-up with gasoline pool fire in order to evaluate the reliability of the model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1476-1478
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• 1999

A musculotendon model is proposed to predict muscle force during muscle fatigue due to the continuous functional electrical stimulation(FES). Muscle fatigue dynamics can be modeled as the electrical admittance of muscle fibers and included in activation dynamics based on the{{{{ { Ca}^{2+ } }}}} kinetics. The admittance depends on the fatigue variable that monotonically increase or decrease if electrical pulse exists or not, and on the stimulation parameters and the number of applied pulses. In the response of the change in activation the normalized Hill-type contraction dynamics connected with activation dynamics decline the muscle shortening velocity and thus its force under muscle fatigue. The computer simulation shows that the proposed model can express the muscle fatigue and its recovery without changing any stimulation parameters.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.1-10
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• 2016

OBJECTIVES : Currently, the market for carbon emissions trading has been increasing. In Korea, it is known that traffic mode rate in bike transportation is low. However, if bike transportation system is encouraged and the traffic mode rate is increased, it would be possible to reduce carbon emissions through the trading market. In this study, a practical policy to activate the bike transportation system in Korea will be proposed and verified. METHODS : Past studies regarding bike transportation system in international and domestic metropolitan cities were analyzed. Moreover, detailed reviews on recent carbon emissions trading market were performed. In particular, SWOT analysis on the bike transportation system in Korea and policy topology analysis were conducted. RESULTS : Based on the literature reviews and SWOT analysis, a new bike transportation policy was proposed. Several actual plans to adopt in Korea were proposed. In addition, a new bike transportation policy was analyzed using policy typology model, and a business model related to the cost of implementing the system and CERs were also proposed. CONCLUSIONS : It is concluded that the proposed bike transportation activation policy and several practical plans to connect CERs and a business model including bus, subway, T-money and bike riders to give some incentive were effective and reasonable. It is desired that this study will help Korea to get CERs through bike transportation activation in the future.

• Korean Journal of Cognitive Science
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• v.2 no.2
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• pp.487-513
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• 1990

The present paper reviews experimental finding such as kanji stroop effect, kana superiority effect in naming task, kanji superiority effect in lexical devision task, and the different pattern of facilitatory priming effect in repetition priming task. Most of the experimental findings indicate that kana script and kanji script are processed independently and modularly. These indications are also consistent with the basic observations on Japanese dyslexics. A connectionist model named JIA(Japanese Interactive Activation)is proposed which is a revision of interactive activation model proposed by McClelland & Rumelhart(1981). The differences between the two models are as follows. Firstly, JIA has a kana module and kanji module at letter level. Secondly, JIA adopts script-specific interconnections between letter-level nodes and word-level nodes:word nodes receive larger activation from the script consistent letter-level nodes. JIA successfully explains all the experimental findings and many cases of Japanese dyslexia. A computer program which simulates JIA model was written and run.

• The Korean Journal of Physiology and Pharmacology
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• v.20 no.1
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• pp.111-117
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• 2016

Vagal nerve activity has been known to play a crucial role in the induction and maintenance of atrial fibrillation (AF). However, it is unclear how the distribution and concentration of local acetylcholine (ACh) promotes AF. In this study, we investigated the effect of the spatial distribution and concentration of ACh on fibrillation patterns in an in silico human atrial model. A human atrial action potential model with an ACh-dependent $K^+$ current ($I_{KAch}$) was used to examine the effect of vagal activation. A simulation of cardiac wave dynamics was performed in a realistic 3D model of the atrium. A model of the ganglionated plexus (GP) and nerve was developed based on the "octopus hypothesis". The pattern of cardiac wave dynamics was examined by applying vagal activation to the GP areas or randomly. AF inducibility in the octopus hypothesis-based GP and nerve model was tested. The effect of the ACh concentration level was also examined. In the single cell simulation, an increase in the ACh concentration shortened $APD_{90}$ and increased the maximal slope of the restitution curve. In the 3D simulation, a random distribution of vagal activation promoted wavebreaks while ACh secretion limited to the GP areas did not induce a noticeable change in wave dynamics. The octopus hypothesis-based model of the GP and nerve exhibited AF inducibility at higher ACh concentrations. In conclusion, a 3D in silico model of the GP and parasympathetic nerve based on the octopus model exhibited higher AF inducibility with higher ACh concentrations.

• Journal of Digital Contents Society
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• v.9 no.3
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• pp.379-388
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• 2008

This paper is to redefine the concept of Cyber Career Counseling Activation(=C-C-C-A) and verify the effects of the factors affecting the C-C-C-A at Korean academic high school level in Kyunggi Province. In this research, we hypothesize that the three independent variables increase the effects of Cyber Career Counseling Activation.. To discuss the hypothesis, we analyzed survey data of 322 students who had taken Cyber Career Counseling in December 2007 based on Structural Equation Model. The results are as follows: First, the three crucial factors(Expanding C-C-C Opportunities, Improving C-C-C Service, Establishing C-C-C Service System) increase the C-C-C-A effectiveness. Second, as a result of Confirmatory Factor Analysis(CFA), the goodness of fit indices(GFI, AGFI, CFI, RMSEA) demonstrate statistical significance and fitness of the C-C-C-A Model. Therefore, the outcomes show that the three factors are the significant ones of Cyber Career Counseling Activation Model.

• Applied Chemistry for Engineering
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• v.30 no.2
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• pp.178-185
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• 2019

Three spherical quaternary composites composed of metal/metal oxide/high explosive/oxidizer were prepared by a crystallization/agglomeration process. From the characteristics of composites by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), the shortening of the decomposition zone of high explosives in the quaternary composite was observed, which may be attributed to the autocatalytic reaction caused by $ClO_2$ or HCl which are ammonium perchlorate (AP) degradation products. The activation energy analysis showed that the activation energy abruptly decreases at the end of the decomposition zone of high explosives, and it was considered to be caused by $HNO_2$ which is common in decomposition products of high explosives. The activation energy predicted from complex pyrolysis results by the distributed activation energy model (DAEM) showed much better in accuracy than those by model-fitting methods such as Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa models.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.11-25
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• 2021

The objective of this study was to analyze the impact of activation functions on flood forecasting model based on Artificial neural networks (ANNs). The traditional activation functions, the sigmoid and tanh functions, were compared with the functions which have been recently recommended for deep neural networks; the ReLU, leaky ReLU, and ELU functions. The flood forecasting model based on ANNs was designed to predict real-time runoff for 1 to 6-h lead time using the rainfall and runoff data of the past nine hours. The statistical measures such as R2, Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), the error of peak time (ETp), and the error of peak discharge (EQp) were used to evaluate the model accuracy. The tanh and ELU functions were most accurate with R2=0.97 and RMSE=30.1 (㎥/s) for 1-h lead time and R2=0.56 and RMSE=124.6~124.8 (㎥/s) for 6-h lead time. We also evaluated the learning speed by using the number of epochs that minimizes errors. The sigmoid function had the slowest learning speed due to the 'vanishing gradient problem' and the limited direction of weight update. The learning speed of the ELU function was 1.2 times faster than the tanh function. As a result, the ELU function most effectively improved the accuracy and speed of the ANNs model, so it was determined to be the best activation function for ANNs-based flood forecasting.