• Journal of Fashion Business
• /
• v.21 no.4
• /
• pp.144-158
• /
• 2017

Fur garment has long been the conventional symbol for luxury, or conspicuous consumption. However, as fashion items began to diversify as part of overall fashion trend, fur items are now more about individual taste and style than just lavishness. Synthetic fur is especially emerging as a new promising fashion material, with a touch almost like natural fur at an affordable price. Along with the emergence of 'Vegan Fashion' trend, synthetic fur is establishing itself as a popular fashion textile. This study is an attempt to investigate subjective evaluation and physical properties of natural and synthetic furs, whose results will further serve as basic data in developing synthetic fur materials. Sensory and emotional evaluations are carried out on natural and artificial furs. For analysis, factors such as weight, thickness, air permeability, gloss and compressibility were surveyed to observe how they influence the physical properties. According to the subjective evaluation, natural and artificial fur samples do not differ in conspicuous ways in appearance. Experiments on physical properties, specifically warm/cool touch experiment, show that natural fur has a slightly higher warm sensation than artificial fur. Luster analysis by using a microscope revealed that there are subtle qualitative differences between natural and artificial fur. During the subjective evaluation, subjects found it hard to state distinct quantitative differences in luster. A survey as a means of assessing qualitative differences in gloss seems to be necessary to complement the evaluation. Results from this study will potentially serve as resources for diversification of fashion product designs using synthetic fur.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.9
• /
• pp.85-94
• /
• 2004

As over 70% of the total life cycle cost (LCC) of a product is committed at the early design stage, designers are in an important position to substantially reduce the LCC of the products they design by giving due to life cycle implications of their design decisions. During early design stages, there may be competing concepts with dramatic differences. In addition, the detailed information is scarce and decisions must be made quickly. Thus, both the overhead in developing parametric LCC models fur a wide range of concepts, and the lack of detailed information make the application of traditional LCC models impractical. A different approach is needed, because a traditional LCC method is to be incorporated in the very early design stages. This paper explores an approximate method for providing the preliminary LCC, Learning algorithms trained to use the known characteristics of existing products might allow the LCC of new products to be approximated quickly during the conceptual design phase without the overhead of defining new LCC models. Artificial neural networks are trained to generalize product attributes and LCC data from pre-existing LCC studies. Then the product designers query the trained artificial model with new high-level product attribute data to quickly obtain an LCC for a new product concept. Foundations fur the learning LCC approach are established, and then an application is provided.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2001.09a
• /
• pp.28-35
• /
• 2001

Liquefaction potential on the specific site of nuclear power plant is analyzed and reviewed. The layered site fur this study consists of silt and sand. Based on the limited available soil data, maximum shear strength at critical locations using Seed & Idriss method and computer program SHAKE is calculated, and liquefaction potential is reviewed. Seismic input motion used fur the assessment of liquefaction is the artificial time history compatible with the US NRC regulatory Guider .60. Assessment results of the liquefaction are validated by analyzing to the other typical soil fecundations which can show the effects of foundation depth and soil data.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.5 s.248
• /
• pp.520-527
• /
• 2006

The design of major industrial facilities for the prevention of fatigue failure is customarily done by defining a set of transients and performing a calculation of cumulative usage factor. However, sometimes, the inherent conservatism or lack of details as well as unanticipated transients in old plant may cause maintenance problems. Even though several famous on-line monitoring and diagnosis systems have been developed world-widely, in this paper, a new system fur fatigue monitoring and life evaluation of crane is proposed to reduce customizing effort and purchasing cost. With regard to the system, at first, comprehensive operating transient data has been acquired at critical locations of crane. The real-time data were classified, by using adaptive resonance theory that is one of typical artificial neural network, into representative stress groups. Then the each classified stress pattern was mapped to calculated cumulative usage factor in accordance with ASME procedure. Thereby, promising results were obtained fur the crane and it is believed that the developed system can be applicable to other major facilities extensively.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.4
• /
• pp.563-573
• /
• 2009

This study analyzed the trends and aesthetic characteristics of fur design found in the contemporary fashion to examine the status of fur material in the contemporary fashion design, and through an analysis of the meaning it attempted to come up with a new viewpoint and form on material for the future fashion design. A literature review was used to explore the kinds and properties of furs. In addition, an empirical analysis of works that have appeared in fashion collections since the year 2000 was conducted with local and foreign fashion magazines such as Gap, Vogue, and Mode & Mode and other publications related to fashion collections. In the contemporary fashion, the trends of fur design are represented by use of various items, material combinations, application to decorative purposes(like trimmings, details, or accessories), and a wide range of colors and textures available by advanced dyeing and finishing techniques. The aesthetic values intrinsic to fur design are that the expression of conspicuous luxury covers even the qualitative aspect of luxury and adds fashionable images to casual items, contributing to the popularization of fur fashion, by using a variety of artificial furs; the expression of sensual feminine beauty allows the animal and primitive feel characteristic of furs to convert a feminine body into a sensual image of more than a simple biological impulse; and the expression of hybridity presents a new viewpoint through distortions, exaggerations, deviations from the existing constituent forms, or futuristic sensibilities in all elements of fashion design.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.8
• /
• pp.83-88
• /
• 2004

The Classification of defected oil-seals using a vision system with the artificial neural network is presented. The artificial neural network fur classification consists of 27 input nodes, 10 hidden nodes, and one output node. The selection of the number of the input nodes is based on an observation that the difference among the defected, non-defected, and smeared oil-seals is greatly pronounced in the 26 step gray-scale level thresholding. The number of the hidden nodes is chosen as a result of a trade-off between accuracy and computing time. The back-propagation algorithm is used for teaching the network. The proposed network is capable of successfully classifying the defected from the smeared oil-seals which tend to be classified as the defected ones using the binary thresholding. It is envisaged that the proposed method improves the reliability and productivity of the automotive vision inspection system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.273-276
• /
• 2000

This paper describes on-going research, applying an artificial immune system to the problem of network intrusion detection. The paper starts by introducing the motivation and rationale of this research. After describing the overall architecture of the proposed artificial immune system fur network intrusion detection, the real network traffic data and its profile features used in this research are explained. As the first step of this effort, the negative selection algorithm, which is one of three significant evolutionary stages comprising an overall artificial immune system, is investigated and initial results are briefly discussed. Finally, the direction of future work is discussed based on this initial result and the contribution of this research is addressed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.869-874
• /
• 2005

This paper proposes the Pareto artificial life algorithm for a multi-objective function optimization problem. The artificial life algorithm for a single objective function optimization problem is improved through incorporating the new method to estimate the fitness value fur a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm is applied to the optimum design of a Journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application are reported to present the possible solutions to a decision maker or a designer.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.297-300
• /
• 2001

Artificial neural networks have become important tools in many fields. This paper describes a new algorithm fur training an RBF network. This algorithm has two main advantages: higher accuracy and a too stable learning process. In addition, it can be used as a good classifier in pattern recognition.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.405-405
• /
• 2000

We designed the artificial olfactory sensing system (Electronic Nose) using MOS type sensor array fur recognizing and analyzing odour. The response of individual sensors of sensor array, each processing a slightly different response towards the sample volatiles, can provide enough information to discriminate between sample odours. In this paper, we applied clustering algorithm for dimension reduction, such as linear projection mapping (PCA method), nonlinear mapping (Sammon mapping method) and the combination of PCA and Sammon mapping having a better discriminating ability. The odours used are VOC (Volatile chemical compound) and Toxic gases.