• Journal of Distribution Science
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• v.19 no.9
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• pp.41-52
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• 2021

Purpose: Virtual reality is a unique technology to distribute data and demonstrates user's understanding towards complex products. The objective of this research is to investigate the impact of virtual reality on real world purchase intention of automotive cutting tools in Thailand's exhibitions. Hence, the research framework was constructed by telepresence, perception narrative, authenticity, trustworthiness, functional value, aesthetics, and purchase intention. Research design, data and methodology: Samples were collected from 500 visitors who participated in the selected top two metalworking exhibitions. Mix sampling approach is applied by using non-probability sampling methods of purposive or judgmental sampling, quota sampling, and convenience sampling method, respectively to reach target samples. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) were used to analyze and confirm goodness-of-fit of the model and hypothesis testing. Results: The results indicate that authenticity, functional value, and trustworthiness induced higher experiential value towards purchase intention. Those variables are stimulated by telepresence and perception narrative towards VR experience. Conclusions: Consumer's purchase intention towards VR experience on engineering cutting tools rely on consumer's sense of authenticity, trustworthiness, and functional value. Hence, marketing practitioners in automotive companies are encouraged to develop VR which focusing on significant factors to enhance consumers purchase intention.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.209-240
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• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.803-815
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• 2016

In this paper, we design a direct radio frequency (RF) sampling receiver for multiband GNSS signals and demonstrate its performance. The direct RF sampling is a technique that does not use an analog mixer, but samples the passband signal directly, and all receiver processes are done in digital domain, whereas the conventional intermediate frequency (IF) receiver samples the IF band signals. In contrast to the IF sampling receiver, the RF sampling receiver is less complex in hardware, reconfigurable, and simultaneously converts multiband signals to digital signals with an analog-to-digital (AD) converter. The reconfigurability and simultaneous reception are very important in military applications where rapid change to other system is needed when a system is jammed by an enemy. For simultaneous reception of multiband signals, the sampling frequency should be selected with caution by considering the carrier frequencies, bandwidths, desired intermediate frequencies, and guard bands. In this paper, we select a sampling frequency and design a direct RF sampling receiver to receive multiband global navigation satellite system (GNSS) signals such as GPS L1, GLONASS G1 and G2 signals. The receiver is implemented with a commercial AD converter and software. The receiver performance is demonstrated by receiving the real signals.

• Survey Research
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• v.11 no.1
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• pp.123-144
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• 2010

In new sample design for Korea Housing Survey to research about housing policy, total strata are forty five because individual results of sixteen regions are estimated. The sample size is determined by sample errors of several variables which are the living area, family income, householder income, and living expenses. The sample size of each region is determined by relative standard error of existing result, and the strata sample size is to use the square root proportion allocation. Enumeration districts are sampled by the probability proportion to size systematic sampling in proportion to the enumeration district size, and the systemic sampling to use assortment characteristics. We considered a new apartment complex because of variation reflections which are rebuilder and redevelopment of houses. To get estimators of mean and variance, we used the design weighting, non-response adjusting, and post-stratification. In order to consider estimation efficiency, we calculate the design effect using estimators of variance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.3
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• pp.33-38
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• 2011

A cubic spline trajectory planner with arc-length parameter is formulated with estimation by summing up to the 3rd order in Taylor's expansion. The PVAJT motion planning is presented to reduce trajectory calculation time at every cycle time of servo control loop so that it is able to generate cubic spline trajectory in real time. This method can be used to more complex spline trajectory. Several case studies are executed with different values of cycle time and sampling time, and showed the advantages of the PVAJT motion planner. A DSP-based motion controller is designed to implement the PVAJT motion planning.

• ETRI Journal
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• v.24 no.5
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• pp.341-348
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• 2002

We propose an asymmetric sampled grating laser and a multi-wavelength laser array associated with it. Asymmetric sampling periods combined with an index shifter make it possible to use first order reflection for lasing operations. With the structure of our design, we achieved a simple fabrication procedure as well as a high yield without using complex and time-consuming e-beam lithography for multi-period gratings. We analyzed the effect of mirror coating by numerical analysis to improve single mode and power extraction performance. By using high reflection-antireflection coatings, we obtained high power extraction efficiency without degradation of the single mode property. For the multi-wavelength laser array, to gain wavelength control, we varied the sampling periods from one laser to an adjacent laser across the array. With this approach, we showed the feasibility of an array of up to 30 channels with 100 GHz wavelength spacing.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.4
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• pp.19-27
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• 2023

PURPOSE: This investigation in the study aimed to assess to determine proportion and susceptibility makers of sarcopenia in Korean younger female aged 30 to 39 years. METHODS: To address the complex sampling design of Korea National Health and Nutrition Examination Surveys, appropriate individual weights were incorporated into the analysis. The data employed a stratified, clustered, multistage probability sampling design. A total of 2,098 participants were enrolled and categorized into two groups based on their skeletal muscle mass index scores. One hundred and twenty-four individuals were placed in the sarcopenia group, while 2,024 were allocated to a normal group. The study examined various markers as variables, including age, height, weight, body mass index waist circumference, skeletal muscle mass index, systolic and diastolic blood pressure, fasting glucose, triglyceride, and total cholesterol levels, and smoking and drinking habits. RESULTS: The study found that proportion of sarcopenia in this population was 3.78% (CI: 2.89-4.94) in sarcopenia group and 96.22% (CI: 95.06-97.11) in normal with weighed values. Several susceptibilities including height, weight, BMI, waist circumference, diastolic blood pressure, and total cholesterol levels were risk factor for sarcopenia (p < .05), exhibited significant differences between the sarcopenia and normal groups. CONCLUSION: This investigation provides the proportion of sarcopenia and identifies relevant susceptibility markers among community dwelling younger women in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.