• 한국전자거래학회지
• /
• 제1권2호
• /
• pp.93-116
• /
• 1996

Nowadays, there are many efforts to integrate CAD/CAM and other systems. The key of integration is engineering database implementation through the product data definition. In this paper, we suggest the product data definition and their properties for electronic consumer product throughout the requirement analysis for engineering database. Electronic consumer products include electric/electronic parts. as well as mechanical part which mainly compose of machinery. The paper is composed of three parts: the first is analysis about engineering data base. the second is understanding of product data structure and properties. and the last is modeling of product data including static and dynamic characteristics.

• Design & Manufacturing
• /
• 제16권3호
• /
• pp.1-8
• /
• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
• /
• pp.397-400
• /
• 2011

In this paper, we propose an approach to detect the product label for mobile phone images based on saliency map and the local structure tensor. The object boundary information can be better described by the local structure tensor than other edge detectors, and the saliency map methods can find out the most salient area and shorten the computational time by reducing the size of the orignal image. Therefore, these two methods are considered for our product label detection. The experimental results show an acceptable performance based on our proposed approach.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2001년도 춘계학술대회논문집A
• /
• pp.471-476
• /
• 2001

Milli-structure components ate classified as a component group whose size is between macro and micro scales, that is, about less than 20mm and larger than 1mm. The forming of these components has a typical phenomenon of bulk deformation with thin sheets because of the forming size. In this study, milli-structure rectangular cup drawing is analyzed and measured using the finite element method and experiment. Generally, milli-structure containers or cases like cellular phone vibrator consist of rectangular-shaped drawing to save installation space. A systematic approach is established for the design and the experiment of the forming processes for rectangular milli-structure cases. To verify the simulation results, the experimental investigations were also carried out on a real industrial product. The numerical analysis by FEM shows good agreement with the experimental results in view of the deformation shape of the product.

• Journal of applied mathematics & informatics
• /
• 제9권2호
• /
• pp.705-716
• /
• 2002

In this paper we shall introduce the algebraic structure of a tensor product for arbitrarily given automata, giving a defintion of the tensor product for automata. We introduce and study that for any set X there always exists a free automaton on X. The existence of a tensor product for automata will be investigated in the same way like modules do.

• 대한수학회지
• /
• 제33권2호
• /
• pp.319-332
• /
• 1996

Many authors have studied multiple stochastic integrals in pursuit of the existence of product processes in terms of multiple integrals. But there has not been much research into the structure of the product processes themselves. In this direction, a study which gives emphasis on sample path continuity and boundedness properties was initiated in Pyke[9]. For details of problem set-ups and necessary notations, see [9]. Recently the weak limits of U-processes are shown to be chaos processes, which is product of the same Brownian measures, see [2] and [7].

• 호남수학학술지
• /
• 제44권1호
• /
• pp.62-77
• /
• 2022

This study presents an 𝛼-Sasakian structure on the product manifold M₁ × 𝛽(I), where M₁ is a Kähler manifold with an exact 1-form, and 𝛽(I) is an open curve. It then defines a new type warped product metric to study the warped product of almost Hermitian manifolds with almost contact metric manifolds, contact metric manifolds, and K-contact manifolds.

• 대한안전경영과학회지
• /
• 제6권1호
• /
• pp.201-217
• /
• 2004

In this research, OIL (Ontology Inference Layer), one of the ontology language, is applied for classifying product data systematically, defining concepts, and establishing relationship between concepts. By transforming steel product data into XML documentation and managing them, knowledge management based on the logical structure of documents is possible.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2007년도 춘계학술대회 논문집
• /
• pp.429-430
• /
• 2007

• Korean Journal of Mathematics
• /
• 제28권4호
• /
• pp.973-984
• /
• 2020

This paper is devoted to study the reproducing property on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi variable computing, this structures play the key role in probability, mathematical finance and machine learning.