• International Journal of Costume and Fashion
• /
• v.13 no.2
• /
• pp.65-77
• /
• 2013

The purposes of this study were to document the fashions adopted by young women in the United States in the 1980s and to explore if and how the dynamic shifts toward postmodernist values influenced those fashion trends. Fifteen U.S. women who were college students in the 1980s were interviewed for the study. In analysis of the data, we focused on social changes during the 1980s and the cultural impact of postmodernism vs. modernism as influential factors. Both postmodern and feminist ideas challenged the mainstream cultural framework of capitalism. U.S. women's styles and behaviors concerning dress reflected characteristics of postmodern consumption patterns, which include nostalgia, ethnic dress, androgyny, eclectic and novel clothing combinations, surprising or humorous appearance, and nonconformity. Despite the critique of conformity and conservatism in dress that had emerged in the 1960s and remained in at least minority or subversive trends, the importance of brand names and designer labels increased in mainstream fashion. This study helps us better understand the dynamics of fashion as it reflects societal and value changes in a transitional time in history.

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.616-621
• /
• 2003

Fluid-elastic instability is believed to be a cause of the large-amplitude vibration and resulting rapid wear of heat exchanger tubes when the flow velocity exceeds a critical value. For sub-critical flow velocities, the random turbulence excitation is the main mechanism to be considered in predicting the long-term wear of steam generator tubes. Since flow-induced interactions of the tubes with tube supports in the sub-critical flow velocity can cause a localized tube wear, tube movement in the clearance between the tube and tube support as well as the normal contact force on the tubes by fluid should be maintained as low as possible. A simplified method is used for predicting fretting-wear damage of the double $90^{\circ}$U-bend tubes. The approach employed is based on the straight single-span tube analytical model proposed by Connors, the linear structural dynamic theory of Appendix N-1300 to ASME Section III and the Archard's equation for adhesive wear. Results from the presented method show a similar trend compared with the field data. This method can be utilized to predict the fretting-wear of the double $90^{\circ}$U-bend tubes in steam generators.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.2
• /
• pp.16-28
• /
• 2000

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion"method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion"method is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we peformed simulations in PC as well as real experiments with ZIRO. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.9C
• /
• pp.1258-1268
• /
• 2004

We propose a new fast, algorithm which is used for detecting frontal face in the frequency domain based on human skin-color using OCT coefficient of dynamic image compression and skin color information. The region where each pixel has a value of skin-color were extracted from U and V value based on DCT coefficient obtained in the process of Image compression using skin-color map in the Y, U, V color space A morphological filter and labeling method are used to eliminate noise in the resulting image We propose the algorithm to detect fastly human face that estimate the directional feature and variance of luminance block of human skin-color Then Extraction of face was completed adaptively on both background have the object analogous to skin-color and background is simple in the proposed algorithm The performance of face detection algorithm is illustrated by some simulation results earned out on various races We confined that a success rate of 94 % was achieved from the experimental results.

• Advances in nano research
• /
• v.16 no.4
• /
• pp.413-426
• /
• 2024

This paper investigates the dynamic behavior of a simply supported viscoelastic plate made of functionally graded carbon nanotube reinforced composite under dynamic loading. Carbon nanotubes are distributed in 5 different shapes: U, V, A, O and X, depending on the shape they form through the thickness of the plate. The displacement fields are derived in the Laplace domain using a higher-order shear deformation theory. Equations of motion are obtained through the application of the energy method and Hamilton's principle. The resulting equations of motion are solved using Navier's method. Transforming the Laplace domain displacements into the time domain involves Durbin's modified inverse Laplace transform. To validate the accuracy of the developed algorithm, a free vibration analysis is conducted for simply supported plate made of functionally graded carbon nanotube reinforced composite and compared against existing literature. Subsequently, a parametric forced vibration analysis considers the influence of various parameters: volume fractions of carbon nanotubes, their distributions, and ratios of instantaneous value to retardation time in the relaxation function, using a linear standard viscoelastic model. In the forced vibration analysis, the dynamic distributed load applied to functionally graded carbon nanotube reinforced composite viscoelastic plate is obtained in terms of double trigonometric series. The study culminates in an examination of maximum displacement, exploring the effects of different carbon nanotube distributions, volume fractions, and ratios of instantaneous value to retardation times in the relaxation function on the amplitudes of maximum displacements.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.14 no.6
• /
• pp.17-23
• /
• 2006

Rubber materials have the nonlinear, large deformation and viscoelastic behavior. W.D. Kim et al. studied these characteristics through the static, fatigue, dynamic, aging and viscoelastic test. This paper discussed that the properties of engine mounting rubber, such as static stiffness, fatigue life and damping factor, are predicted based on CAE by using material properties acquired by the report of Kim et al. In result, the static stiffness of engine mounting rubber is predicted approximately in comparison with test value. Also, it was confirmed that the relationship of fatigue life and Green-Lagrange strain in specimen was the valid tool to predict the fatigue life of engine mounting rubber. From the results of transient viscoelastic analysis the damping factor changed rapidly at the range less than 8hz.

• The Journal of Korean Academy of Prosthodontics
• /
• v.52 no.2
• /
• pp.82-89
• /
• 2014

Purpose: The purpose of this study was to observe the change of viscoelastic properties of dental resin cements during polymerization. Materials and methods: Six commercially available resin cement materials (Clearfil SA luting, Panavia F 2.0, Zirconite, Variolink N, RelyX Unicem clicker, RelyX U200) were investigated in this study. A dynamic oscillation-time sweep test was performed with AR1500 stress controlled rheometer at $32^{\circ}C$. The changes in shear storage modulus (G'), shear loss modulus (G"), loss tangent (tan ${\delta}$) and displacement were measured for twenty minutes and repeated three times for each material. The data were analyzed using one-way ANOVA and Tukey's post hoc test (${\alpha}$=0.05). Results: After mixing, all materials demonstrated an increase in G' with time, reaching the plateau in the end. RelyX U200 demonstrated the highest G' value, while RelyX Unicem (clicker type) and Variolink N demonstrated the lowest G' value at the end of experimental time. Tan ${\delta}$was maintained at some level and reached the zero at the starting point where G' began to increase. The tan ${\delta}$and displacement of the tested materials showed similar pattern in the graph within change of time. The displacement of all 6 materials approached to zero within 6 minutes. Conclusion: Compared to other resin cements used in this study, RelyX U200 maintained plastic property for a longer period of time. When it completed the curing process, RelyX U200 had the highest stiffness. It is convenient for clinicians to cement multiple units of dental prostheses simultaneously.

• The International Journal of Costume Culture
• /
• v.6 no.2
• /
• pp.105-116
• /
• 2003

The purposes of this study were to examine the fashion adopted by young women in the United States in the 1970s and to explore how the dynamic shifts toward feminist values influenced those fashion trends. Fifteen American women who were college students in the 1970s were interviewed for the study. Throughout the decade, casual and comfortable styles became more prevalent; for example, pants became widely accepted for formal occasions as well as informal occasions due to an overall emphasis on practicality. The feminist and civil rights movements along with more liberal attitudes toward religion were among the more dominant cultural values that influenced the respondents' choices in clothing styles. Feminist presentation was diverse extreme or eclectic - and constantly renegotiating itself. This study helped us better understand the dynamics involved between fashion and value changes as well as the influence of feminism on the 1970s fashion in the United States.

• Proceedings of the KSR Conference
• /
• 2001.10a
• /
• pp.534-539
• /
• 2001

This paper presents the critical speed analysis of geogrid-reinforced rail roadbeds on soft soil. A rail roadbed on soft ground must be designed to avoid intolerable stress in the underlying soil and to give sufficient support for the rail system. At high speeds, the deformation of rail systems will gain dynamic amplification, and reach excessive values as a certain speed, here termed critical speed is approached. The elastic Winkler foundation model was used to predict the critical speed of geogrid-reinforced rail roadbeds on soft soil and the model properties were determined by the in-situ cyclic plate load test. Based on the parametric study of elastic beam on Winkler foundation model, the critical speed increase with the increase of the flexural risidity of subgrade EI and the stiffness coefficient of Winkler foundation k. From the in-situ cyclic load tests and analysis of elastic beam on Winkler foundation model, the critical speed increase with increase in number of reinforced layer and non-dimensional value for depth of first geogrid layers and the thickness of reinforced rail roadbed u/d.

• Journal of the Korean Society of Visualization
• /
• v.20 no.2
• /
• pp.78-85
• /
• 2022

In these days, the rapid development in prediction technology using artificial intelligent is being applied in a variety of engineering fields. Especially, dimensionality reduction technologies such as autoencoder and convolutional neural network have enabled the classification and regression of high-dimensional data. In particular, pixel level prediction technology enables semantic segmentation (fine-grained classification), or physical value prediction for each pixel such as depth or surface normal estimation. In this study, the pressure distribution of the ship's surface was estimated at the pixel level based on the artificial neural network. First, a potential flow analysis was performed on the hull form data generated by transforming the baseline hull form data to construct 429 datasets for learning. Thereafter, a neural network with a U-shape structure was configured to learn the pressure value at the node position of the pretreated hull form. As a result, for the hull form included in training set, it was confirmed that the neural network can make a good prediction for pressure distribution. But in case of container ship, which is not included and have different characteristics, the network couldn't give a reasonable result.