• Structural Engineering and Mechanics
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• v.45 no.1
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• pp.95-110
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• 2013

In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

• Journal of Microbiology and Biotechnology
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• v.9 no.2
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• pp.179-183
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• 1999

A recombinant form of hirudin, a potent thrombin-specific inhibitor derived from the bloodsucking leech, was expressed as a secretory product in Saccharomyces cerevisiae under the control of GALl0 promoter and the mating factor $\alpha$pre-pro leader sequence. In an attempt to produce recombinant hirudin (r-Hir) of therapeutic purity in large quantities, the fed-batch fermentation was carried out by using this recombinant yeast, and subsequently downstream processing was developed with the preparative-scale column chromatography systems. About 234 mg/l of biologically active r-Hir was produced as a secretory product by the fed-batch fermentation strategy developed for an efficient downstream processing. Using a two-step chromatography process (an anion exchange chromatography followed by the reverse phase HPLC), the r-Hir was purified to>98% with an overall recovery yield of 84%. According to the N-terminal amino acid sequencing, the purified r-Hir was found to have the predicted N-terminal amino acid sequence. The biological activity of the purified r-Hir to inhibit thrombin was also identical to that of the commercial hirudin.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.134-139
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• 2013

This paper describes design of a RF frequency synthesizer for the MBOA UWB systems with $0.13{\mu}m$ silicon CMOS technology. To generate effective clock signal of the MBOA novel technique which uses large scale multiplication in band of low frequency and small scale multiplication in band of high frequency has been used to reduce oscillation bandwidth of VCO. To get good performance of high speed and wide band operation characteristics a VCO using PMOS core structure and a frequency divider using super dynamic structure used in design of PLL circuit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.454-475
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• 2018

This paper presents a novel Android malware classification model planned to classify and categorize Android malicious code at Drebin dataset. The amount of malicious mobile application targeting Android based smartphones has increased rapidly. In this paper, Restricted Boltzmann Machine and Deep Belief Network are used to classify malware into families of Android application. A texture-fingerprint based approach is proposed to extract or detect the feature of malware content. A malware has a unique "image texture" in feature spatial relations. The method uses information on texture image extracted from malicious or benign code, which are mapped to uncompressed gray-scale according to the texture image-based approach. By studying and extracting the implicit features of the API call from a large number of training samples, we get the original dynamic activity features sets. In order to improve the accuracy of classification algorithm on the features selection, on the basis of which, it combines the implicit features of the texture image and API call in malicious code, to train Restricted Boltzmann Machine and Back Propagation. In an evaluation with different malware and benign samples, the experimental results suggest that the usability of this method---using Deep Belief Network to classify Android malware by their texture images and API calls, it detects more than 94% of the malware with few false alarms. Which is higher than shallow machine learning algorithm clearly.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.494-494
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• 2000

This paper demonstrates that the largest Lyapunov exponent $\lambda$ of recurrent neural networks can be controlled by a gradient method. The method minimizes a square error $e_{\lambda}=(\lambda-\lambda^{obj})^2$ where $\lambda^{obj}$ is desired exponent. The $\lambda$ can be given as a function of the network parameters P such as connection weights and thresholds of neurons' activation. Then changes of parameters to minimize the error are given by calculating their gradients $\partial\lambda/\partialP$. In a previous paper, we derived a control method of $\lambda$via a direct calculation of $\partial\lambda/\partialP$ with a gradient collection through time. This method however is computationally expensive for large-scale recurrent networks and the control is unstable for recurrent networks with chaotic dynamics. Our new method proposed in this paper is based on a stochastic relation between the complexity $\lambda$ and parameters P of the networks configuration under a restriction. Then the new method allows us to approximate the gradient collection in a fashion without time evolution. This approximation requires only $O(N^2)$ run time while our previous method needs $O(N^{5}T)$ run time for networks with N neurons and T evolution. Simulation results show that the new method can realize a "stable" control for larege-scale networks with chaotic dynamics.

• Journal of Energy Engineering
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• v.6 no.1
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• pp.87-95
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• 1997

A chemical heat pump based on the reversible reactions between metal chlorides and ammonia gas is attractive alternative to compression system and liquid absorption systems in cooling and refrigerating fields. The advantages of chemical heat pump are no regulatory constants due to CFC refrigerants, utilization of gas, industrial waste heat, electricity, fuel oil etc. as heat sources and wide applications to energy storage system, large-scale energy managements for industrial process. The scale-up of chemical heat pump from laboratory prototype to pilot plants necessitates the interpretation of system performance and evaluation of dynamic behavior in the chemical reactor. This study contains the prediction of performance of chemical refrigerator according to operating condition, the dynamic simulations through reactor modelling, which is used for the calculation of reactive medium temperature and the conversion variation with reactor cooling temperature, and the effect survey of block parameters on the power of refrigerator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.282-285
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• 2001

In general, the PSS/E program based on RMS mathematical models is used for analyzing the steady state and transient stability phenomena of full-scale large power system. Whereas, the EMTDC program unlike PSS/E, studies the specific reduced small-scale power systems as a basis of instantaneous value mathematical models and used to analyze the Electro-Magnetic transient characteristics. The PSS/E provides various control models such as exciter, governor, PSS models and TGOV5 model but there are few control models in EMTDC. In this paper, we developed EMTDC model for TGOV5 of a steam turbine and boiler which represents governor action, main, reheat and low-pressure effects, including boiler effects. The EMTDC model is developed by examining PSS/E control block and using User Define Model(UDM) in addition to default.lib provided by EMTDC. We verify the correctness of developed TGOV5 model with PSS/E and EMTDC simulation results using Governor Step(GSTEP) method.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.71-74
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• 2001

In general, the PSS/E program based on RMS mathematical models is used for analyzing the steady state and transient stability phenomena of full-scale large power system. Whereas, the EMTDC program unlike PSS/E, studies the specific reduced small-scale power systems as a basis of instantaneous value mathematical models and used to analyze the Electro-Magnetic transient characteristics. The PSS/E provides various control models such as exciter, governor and PSS models, But there are few control models in EMTDC. In this paper, we developed EMTDC models for governor which have been applied in KEPCO system. The EMTDC models are developed by examining PSS/E control block and using User Define Model in addition to default.lib provided by EMTDC. we verify the correctness of developed governor models with PSS/E and EMTDC simulation results using Governor Step(GSTEP) method.

• Coupled systems mechanics
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• v.7 no.2
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• pp.233-254
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• 2018

In order to reduce the dependency on fossil fuels, a policy to increase the production capacity of wind turbine is set up. This can be achieved with increasing the dimensions of offshore wind turbine blades. However, this increase in size implies serious problems of stability and durability. Considering the cost of large turbines and financial consequences of their premature failure, it is imperative to carry out numerical simulations over long periods. Here, an energy-conserving time-stepping scheme is proposed in order to ensure the satisfying computation of long-term response. The proposed scheme is implemented for three-dimensional solid based on Biot strain measures, which is used for modeling flexible blades. The simulations are performed at full spatial scale. For reliable design process, the wind loads should be represented as realistically as possible, including the fluid-structure interaction (FSI) dynamic effects on wind turbine blades. However, full-scale 3D FSI simulations for long-term wind loading remain of prohibitive computation cost. Thus, the model to quantify the wind loads proposed here is a simple, but not too simple to be representative for preliminary design studies.