• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.6
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• pp.894-902
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• 2003

Prebiotics (peptides, N-acetyglucoamine, fructo-oligosaccharides, isomalto-oligosaccharides and galactooligosaccharides) were added to skim milk in order to improve the growth rate of contained Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium longum and Bifidobacterium bifidum. The purpose of this research was to study the potential synergy between probiotics and prebiotics when present in milk, and to apply modern optimization techniques to obtain optimal design and performance for the growth rate of the probiotics using a response surface-modeling technique. To carry out response surface modeling, the regression method was performed on experimental results to build mathematical models. The models were then formulated as an objective function in an optimization problem that was consequently optimized using a genetic algorithm and sequential quadratic programming approach to obtain the maximum growth rate of the probiotics. The results showed that the quadratic models appeared to have the most accurate response surface fit. Both SQP and GA were able to identify the optimal combination of prebiotics to stimulate the growth of probiotics in milk. Comparing both methods, SQP appeared to be more efficient than GA at such a task.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.195-214
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• 2016

Monitoring of impact loads is a very important technique in the field of structural health monitoring (SHM). However, in most cases it is not possible to measure impact events directly, so they need to be reconstructed. Impact load reconstruction refers to the problem of estimating an input to a dynamic system when the system output and the impulse response function are usually known. Generally this leads to a so called ill-posed inverse problem. It is reasonable to use prior knowledge of the force in order to develop more suitable reconstruction strategies and to increase accuracy. An impact event is characterized by a short time duration and a spatial concentration. Moreover the force time history of an impact has a specific shape, which also can be taken into account. In this contribution these properties of the external force are employed to create a sample-force-dictionary and thus to transform the ill-posed problem into a sparse recovery task. The sparse solution is acquired by solving a minimization problem known as basis pursuit denoising (BPDN). The reconstruction approach shown here is capable to estimate simultaneously the magnitude of the impact and the impact location, with a minimum number of accelerometers. The possibility of reconstructing the impact based on a noisy output signal is first demonstrated with simulated measurements of a simple beam structure. Then an experimental investigation of a real beam is performed.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.7 s.172
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• pp.164-169
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• 2005

The micro-gripper system is one of the systems that should be improved in the respect of performance for practical usage. In the previous works, the important issues are considered and presented using axiomatic design approach. In this paper, the functional requirements and design parameters are evaluated in order to improve the performance and efficiency of the system. The evaluation is a very difficult task since many variables are related to the outcomes. To provide a basis for correct design decisions, axiomatic design principles have been advanced. Since the framework of axiomatic design makes design issues easier to understand when they are analyzed, we used those as an evaluation tool. The object of the system is to handle micro-size parts. Main device is a micro-gripper using two bender-typed and one stack-typed PZTs as actuators. And it has three tips made of tungsten wires fur holding function. Also the system must satisfy other functional requirements for appropriate handling performance. The results of this study show design improvements of micro-gripper system such as structural change of gripper, additional element, and integration of physical parts. Axiomatic design guides presented suitable design parameters corresponding to functional requirements and made the design elements improve through diagrams of whole system.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.247-249
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• 2003

Currently there are a variety of different tools may be used to analyze, model, describe and document a business process. However, it is difficult to exchange the information of a business process created in different tools because of the distinct information formats used in different tools. The XML Process Definition Language (XPDL) of the Workflow Management Coalition (WfMC) forms a common interchange standard that enables products to continue to support arbitrary internal representations of process definitions with an import/export function to map to/from the standard at the product boundary. Generally a business process model can be represented by the UML activity diagram, but there is a difficult task to directly generate an XPDL document from a business process model represented by the standard activity diagram. In the paper we will propose an approach to generate an XPDL document from a business process model represented by the extended UML activity diagram.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.987-997
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• 2012

The sales volume of men's cosmetics has drastically increased in Korea. In recent years, men's needs for cosmetics have been diversified and the consumer demand for functional cosmetics has greatly risen. In particular, male consumers have become more interested in essence product that is a light and concentrated treatment to correct skin problems. This research analyzes consumer preferences for essence-for-men through the use of choice-based conjoint analysis. This approach is adopted since the task of respondents to choose the most preferred option from several alternatives closely mimics actual marketplace purchasing behavior by consumers. New technique for the construction of choice sets is suggested based on the balanced incomplete block design, to accommodate a larger number of product profiles. The proposed design for choice sets is balanced and provides a tool to filter the contradictory choices. Conjoint analyses are performed to assess the relative importance of attributes and identify the most preferred profile of essence-for-men with respect to attributes such as emphasized function, price, type of content, and design of container. Some differences are indicated in the analysis results between age brackets as well as between groups classified by the amount of fashion item expenditures.

• Wind and Structures
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• v.31 no.6
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• pp.561-573
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• 2020

Unsteady self-excited forces are commonly represented by parametric models such as rational functions. However, this requires complex multiparametric nonlinear fitting, which can be a challenging task that requires know-how. This paper explores the alternative nonparametric modeling of unsteady self-excited forces based on relations between flutter derivatives. By exploiting the properties of the transfer function of linear causal systems, we show that damping and stiffness aerodynamic derivatives are related by the Hilbert transform. This property is utilized to develop exact simplified expressions, where it is only necessary to consider the frequency dependency of either the aeroelastic damping or stiffness terms but not both simultaneously. This approach is useful if the experimental data on aerodynamic derivatives that are related to the damping are deemed more accurate than the data that are related to the stiffness or vice versa. The proposed numerical models are evaluated with numerical examples and with data from wind tunnel experiments. The presented method can evaluate any continuous fitted table of interpolation functions of various types, which are independently fitted to aeroelastic damping and stiffness terms. The results demonstrate that the proposed methodology performs well. The relations between the flutter derivatives can be used to enhance the understanding of experimental modeling of aerodynamic self-excited forces for bridge decks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.670-684
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• 2024

3D Cross-Modal Retrieval (3DCMR) is a task that retrieves 3D objects regardless of modalities, such as images, meshes, and point clouds. One of the most prominent methods used for 3DCMR is the Cross-Modal Center Loss Function (CLF) which applies the conventional center loss strategy for 3D cross-modal search and retrieval. Since CLF is based on center loss, the center features in CLF are also susceptible to subtle changes in hyperparameters and external inferences. For instance, performance degradation is observed when the batch size is too small. Furthermore, the Mean Squared Error (MSE) used in CLF is unable to adapt to changes in batch size and is vulnerable to data variations that occur during actual inference due to the use of simple Euclidean distance between multi-modal features. To address the problems that arise from small batch training, we propose a Noisy Center Loss (NCL) method to estimate the optimal center features. In addition, we apply the simple Siamese representation learning method (SimSiam) during optimal center feature estimation to compare projected features, making the proposed method robust to changes in batch size and variations in data. As a result, the proposed approach demonstrates improved performance in ModelNet40 dataset compared to the conventional methods.

• Advances in Computational Design
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• v.2 no.3
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• pp.225-240
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• 2017

This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days' curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.7
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• pp.647-654
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• 2007

A Discrete continuation Method/homotopy approaches are studied for energy/fuel optimal low thrust Earth escape trajectory by solving a two point boundary value problem(TPBVP). Recently, maneuvers using low thrust propulsion system have been identified as emerging technologies. The low thruster is considered as the main actuator for orbit maneuvers. The cost function consists of a energy/fuel consumption function, and constraints are position and velocity vectors at the terminal escape point. Solving the minimum energy/fuel problem directly is not an easy task, so we adopt the homotopy analysis. Using a solution of the minimum energy, which is solved by discrete continuation method, we obtain the solution of the minimum fuel problem.