• Journal of Pharmaceutical Investigation
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• v.36 no.1
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• pp.31-38
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• 2006

Using a Rheometries Dynamic Analyzer (RDA II), the dynamic viscoelastic properties of a semi-solid ointment base (vaseline) in large amplitude oscillatory shear flow fields were measured over a temperature range of $25{\sim}45^{\circ}C$ and the linear viscoelastic behavior in small amplitude oscillatory shear flow fields was investigated over a wide range of angular frequencies. In this article, the nonlinear viscoelastic behavior was reported from the experimentally obtained data and the effect of temperature on this behavior was discussed in detail. In addition, the angular frequency and temperature dependencies of a linear viscoelastic behavior were explained. Finally, the applicability of a time-temperature superposition principle originally developed for polymeric materials was examined using a shift factor. Main results obtained from this study can be summarized as follows : (1) At very small strain amplitude region, vaseline shows a linear viscoelastic behavior independent of the imposed deformation magnitudes. Above a critical strain amplitude $({\gamma}_{0}=0.1{\sim}0.2%)$, however, vaseline exhibits a nonlinear viscoelastic behavior ; indicating that both the storage modulus and dynamic viscosity are sharply decreased with increasing deformation magnitude. (2) In large amplitude oscillatory shear flow fields, an elastic behavior (storage modulus) has a stronger strain amplitude dependence and begins to show a nonlinear behavior at a smaller strain amplitude region than does a viscous behavior (dynamic viscosity). (3) In small amplitude oscillatory shear flow fields, the storage modulus as well as the loss modulus are continuously increased as an increase in angular frequency and an elastic nature is always superior to a viscous behavior over a wide range of angular frequencies. (4) A time-temperature superposition principle can successfully be applicable to vaseline. This finding allows us to estimate the dynamic viscoelastic behavior of vaseline over an extraordinarily extended range (11 decades) of angular frequencies inaccessible from the experimentally measured range (4 decades).

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.5
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• pp.86-94
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• 2013

Research on dynamic characteristics of injectors gives us insight for preventing combustion instability in a rocket engine. While lots of studies have been done about swirl injectors' dynamic characteristics, little is known about impinging jet injectors' dynamic characteristics. For this reason, this study was aimed to reveal the dynamic characteristics of an impinging jet injector based on experiment using a hydraulic mechanical pulsator. Gain, which is the relationship between input pressure and output value(pressure or velocity) was analyzed with the frequency and manifold pressure change. Pulsating frequency was chosen in the low range: 5, 10, 15 Hz. As a background work, Methods to determine the jet velocity were discussed. Klystron effect was also considered as a factor of this experiment.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.294-299
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• 2007

For efficient and accurate diagnosis of ultrasound images, appropriate time gain compensation(TGC) and dynamic range(DR) control of ultrasound echo signals are important. TGC is used for compensating the attenuation of ultrasound echo signals along the depth, and DR controls the image contrast. In recent ultrasound systems, these two factors are automatically set by a system and/or manually adjusted by an operator to obtain the desired image quality on the screen. In this paper, we propose an algorithm to find the optimized parameter values far TGC and DR automatically. In TGC optimization, we determine the degree of attenuation compensation along the depth by dividing an image into vertical strips and reliably estimating the attenuation characteristic of ultrasound signals. For DR optimization, we define a novel cost function by properly using the characteristics of ultrasound images. We obtain experimental results by applying the proposed algorithm to a real ultrasound(US) imaging system. The results verify that the proposed algorithm automatically sets values of TGC and DR in real-time such that the subjective quality of the enhanced ultrasound images may be sufficiently high for efficient and accurate diagnosis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.3
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• pp.56-61
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• 2010

Recently, UV pulse laser is widely used in micro machining of the research, development and industry field of IT, NT and BT products because the laser short wavelength provides not only micro drilling, micro cutting and micro grooving which has a very fine line width, but also high absorption coefficient which allows a lot of type of materials to be machined more easily. To analyze the dynamic deformation during a very short processing time, which is nearly about several tens nanoseconds, the commercial Finite Element Analysis (FEA) code, LS-DYNA 3D, was employed for the computitional simulation of the UV laser micro machining behavior for thin copper material in this paper. A finite element model considering high strain rate effect is especially suggested to investigate the micro phenomena which are only dominated by mechanically pressure impact in disregard of thermally heat transfer. From these computational results, some of dynamic deformation behaviors such as dent deformation shapes, strains and stresses distributions were observed and compared with previous experimental works. These will help us to understand micro interaction between UV laser beam and material.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.204-210
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• 2002

The self-organizing feature map of Kohonen has disadvantage that needs too much input patterns in order to converge into the equilibrium state when it trains. In this paper we proposed the method of improving the convergence speed and rate of self-organizing feature map converting the interaction set into Dynamic Gaussian function. The proposed method Provides us with dynamic Properties that the deviation and width of Gaussian function used as an interaction function are narrowed in proportion to learning times and learning rates that varies according to topological position from the winner neuron. In this Paper. we proposed the method of improving the convergence rate and the degree of self-organizing feature map.

• The Research Journal of the Costume Culture
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• v.9 no.1
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• pp.111-126
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• 2001

This study concentrates on the relationship between the early 20th century italian artists and their works in the field of clothing design. They advocated the creation of art for life and introduced a new type of work of art which I will call 'experimental clothing for art'. The experimental clothing for art showed its dynamic characteristics in the field s of line and form, color, pattern, and material. The Italian artists made simple and functionalistic dresses, using asymmetric, geometric cuts. in pattern making. They employed dynamic patterns in textile design and favored brilliant colors which they debunked as storage and traditional. With regard to material, they used unusual materials such as metal, net, wire, and paper and inexpensive materials. To investigations of the visual expression of experimental clothing for art in Italy have led us to the internal expressions which are avant-garde, dynamic & speed, functionality & popularity, ephemeral & transformable, and warlike. As a result of the reflection of the times and the artists's will and roles the experimental clothing for art in Italy implicated contemporary clothing in the early twentieth century and it was only laboratory art that underwent various experiments in canvas but a model of efforts for the at of living, which was anti-traditional. It offered a new future and created a new environment. It is left for future research how the experimental clothing for art developed in countries other than Italian.

• Journal of Information Technology Services
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• v.6 no.2
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• pp.19-33
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• 2007

The current advance of IT and the e-commerce triggers the wide practice of dynamic pricing in all industries although the price discrimination has been very cautiously applied in the limited areas in the past. The price discrimination which offers different prices for each customer depending on their preference and buying behaviors has recently gained attention as it could provide superior benefits to sellers. The wide adoption of price discrimination, on the other hand, is reported to face buyer resistances and complaints. Our limited understanding on the perception of price fairness, which we think is key concept in the price discrimination on the Internet-enabled transactions, motives us to investigate factors that affect the perception of price fairness. This study focuses on illusion of control and lateral customer relationship to investigate their effects on price fairness in online auction and group purchase context. By conducting laboratory experiments, our study demonstrates that customers' perception on illusion of control in price determination and advantageous lateral customer relationship significantly affect price fairness perception in both online auction and group purchase environment. The findings are expected to provide researchers and managers with useful insights to develop better pricing strategies and design effective dynamic pricing mechanisms.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1722-1724
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• 2005

The focus of this paper is to develop a mathematical model for investigating the dynamic performance of a polymer electrolyte membrane fuel cell. The model in this work is based on physical laws having clear significance in replicating the fuel cell system and can easily be used to set up different operational strategies. Simulation results display the transient behavior of the voltage within each single cell, and also within a number of such single cells combined into a fuel cell stack system. A linear as well as a nonlinear analysis of the polymer electrolyte membrane fuel cell system(PEMFC) has been discussed in order to present a complete and comprehensive view of this kind of modeling. Also, a comparison of the two kinds of analysis has been performed. Finally, the various characteristics of the fuel cell system are plotted in order to help us understand its dynamic behavior. Results indicate that there is a considerable amount of error in the modeling process if we use a linear model of the fuel cell. Thus, the nonlinearities present in the fuel cell system should be taken into account in order to obtain a better understanding of the dynamic behavior of the fuel cell system.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.23-34
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• 2020

The paper revisits the author's previous paper to examine short-run and long-run dynamic relationships between macroeconomic variables and stock prices in Korea. The data is updated to the period for which monthly data are available from January 1986 to June 2018 (390 observations) retrieved from the Bank of Korea. The results of Johansen cointegration test indicate that at least one cointegrating equation exists, confirming there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Korea. The results of vector error correction estimates confirm that: 1) the coefficient of the error correction term is significant with a negative sign, which is, a long-run dynamic relationship is observed between macroeconomic variables and stock prices; 2) for short-run dynamics, the nominal exchange rate of the Korean won per the US dollar is positively related to stock prices, while interest rates are negatively related to stock prices in the short-run; 3) the coefficient of global financial crises is insignificant, that is, the changes of stock prices are determined largely by their own dynamics in the model. The results suggest only that the global financial crises neither cause instability in the cointegrating vector, nor affect significant changes in the endogenous variables in the model.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.49-62
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• 2023

There has been a rapid increase in the creation and alteration of new malware samples which is a huge financial risk for many organizations. There is a huge demand for improvement in classification and detection mechanisms available today, as some of the old strategies like classification using mac learning algorithms were proved to be useful but cannot perform well in the scalable auto feature extraction scenario. To overcome this there must be a mechanism to automatically analyze malware based on the automatic feature extraction process. For this purpose, the dynamic analysis of real malware executable files has been done to extract useful features like API call sequence and opcode sequence. The use of different hashing techniques has been analyzed to further generate images and convert them into image representable form which will allow us to use more advanced classification approaches to classify huge amounts of images using deep learning approaches. The use of deep learning algorithms like convolutional neural networks enables the classification of malware by converting it into images. These images when fed into the CNN after being converted into the grayscale image will perform comparatively well in case of dynamic changes in malware code as image samples will be changed by few pixels when classified based on a greyscale image. In this work, we used VGG-16 architecture of CNN for experimentation.