• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.193-209
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• 2006

Multiple regression is used to examine the relationship between a set of two or more independent variables and one dependent variable. It provides the information necessary to make predictions of the dependent variables based on several independent variables. To do so, the multiple regression equation is extended to: y=$a+{\beta}_1x_1+{\beta}_2x_2+{\ldots}+{\beta}_kx_k$ y=attractiveness a=the value of the intercept ${\beta}_1$=the slope(weighting) of the first variable ${\beta}_1$= the slope(weighting) of the second variable ${\beta}_k$=the slope of the $\kappa$th variable The resulting regression equation of this research is y=$a+{\beta}_1site's\;system+{\beta}_2customer\;satisfaction+{\beta}_3products+{\beta}_4delivery$ y=3.233+0.374(site's system)+0.268(customer satisfaction)+0.17(products)+0.077(delivery)

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.9-17
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• 2022

As the COVID-19 pandemic situation worsens, the time spent indoors increases, and the exposure to indoor environmental pollution such as indoor air pollution and noise also increases, causing problems such as deterioration of human health, stress, and discord between neighbors. This paper designs and implements a system that measures and monitors indoor air quality and noise, which are representative evaluation criteria of the indoor environment. The system proposed in this paper consists of a particulate matter measurement subsystem that measures and corrects the concentration of particulate matters to monitor indoor air quality, and a noise measurement subsystem that detects changes in sound and converts it to a sound pressure level. The concentration of indoor particulate matters is measured using a laser-based light scattering method, and an error caused by temperature and humidity is compensated in this paper. For indoor noise measurement, the voltage measured through a microphone is basically measured, Fourier transform is performed to classify it by frequency, and then A-weighting is performed to correct loudness equality. Then, the RMS value is obtained, high-frequency noise is removed by performing time-weighting, and then SPL is obtained. Finally, the equivalent noise level for 1 minute and 5 minutes are calculated to show the indoor noise level. In order to classify noise into direct impact sound and air transmission noise, a piezo vibration sensors is mounted to determine the presence or absence of direct impact transmitted through the wall. For performance evaluation, the error of particulate matter measurement is analyzed through TSI's AM510 instrument. and compare the noise error with CEM's noise measurement system.

• Industry Promotion Research
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• v.8 no.4
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• pp.29-36
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• 2023

In order to prevent industrial accidents, this study presented a methodology to ensure that risk aggravating factors are reflected in risk assessments at manufacturing sites and demonstrated it by applying it to actual manufacturing sites. As a result of a statistical analysis of all 242,906 accidents that occurred in the manufacturing industry over the past 10 years, new workers less than 6 months old, foreign workers, older workers over 55 years old, and jobs where hands and arms are exposed to risk areas, Non-routine work performed from 9 o'clock to 12 o'clock showed a significantly high accident rate. In addition, a weighted value was applied to estimate the possibility of an accident at the risk determination stage through focus group interviews. Through the results of this study, risk weighting factors can be quantitatively reflected in risk assessment, which is meaningful in preventing accidents by evaluating the size of the identified risk closer.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.129-144
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• 2013

Recognizing a limits on quantitative evaluation of cultural contents' and for its betterment, study aims developing a qualitative evaluation model. For this study, Reception Theory, Semiotics and Psychology were derived for epistemological dimension to contemplate culture contents' essential attribute. To be concrete, cultural contents was examined as experiential products, emotional products, rememberable products and texts. Also, codes of fun, emotion and culture were discussed as intrinsic attributes for cultural contents and how those attributes were expressed or composed in cultural contents was discussed as well. Evaluation items were extracted based on final discussion at the epistemic level, set up the final evaluation model by taking experts' advices on each items. With all those outcomes, qualitative evaluation model for cultural contents was developed. For the importance of each index in the model, priority was granted by weighting on each index. Lastly, evaluation scale was developed for each index. The culture contents' evaluation model developed in study is meaningful not only in drawing qualitative evaluation items of video(image) contents and developing the index and model for the first time, but also its possibility of wide use for other genres.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.109-124
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• 2000

For rational human value judgement and evaluation, provision of clear evaluation data, objective value judgement criteria, and properly generalized methods are required. For instance, this is true for software quality evaluation, and the measure of software quality and the weighting method of evaluation target directly affect final decisions. However it is not easy to find a generalized method for the software quality evaluation or product selection, because of its complex characteristics. In this paper, we apply the qualitative preference method based on quantitative belief functions to find a general weighing method for the software quality evaluation. In particular, the qualitative preference method, in which the differentiated preference expression is possible, is conceptually expanded for general applications in future. For this purpose, we hierarchically differentiate the strong preference relation from the weak preference relation, and show an example of quantification of software quality evaluation on different applications, by comparing the qualitative preference method with AHP. We believe that the application domain of this method is not limited to the software quality evaluation and it is very useful to apply this results to other SE areas, e.g., metric selection with different views and riority determination of practices to be assessed in the SPICE.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1788-1792
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• 2006

The ordered weighted averaging (OWA) operator by Yager has received more and more attention since its appearance. One key point in the OWA operator is to determine its associated weights. Among numerous methods that have appeared in the literature, we notice the maximum entropy OWA (MEOWA) weights that are determined by taking into account two appealing measures characterizing the OWA weights. Instead of maximizing the entropy in the formulation for determining the MEOWA weights, the new method in the article tries to obtain the OWA weights which are evenly spread out around equal weights as much as possible while strictly satisfying the orness value provided in the program. This consideration leads to the least squared OWA (LSOWA) weighting method in which the program tries to obtain the weights that minimize the sum of deviations from the equal weights since entropy is maximized when the weights are equal. Above all, the LSOWA weights display symmetric allocations of weights on the basis of equal weights. The positive or negative allocations of weights from the median as a basis depend on the magnitude of orness specified. Further interval LSOWA weights are constructed when a decision-maker specifies his or her value of orness in uncertain numerical bounds.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.11
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• pp.1195-1202
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• 2004

The international competition in refrigerator markets has continuously required the research for sound quality of a refrigerator to improve the quality of a life. In this paper, A new method for evaluation of the sound quality of a refrigerator is developed based on human sensibility engineering by using ANN(artificial neural network). In this paper, the loudness and the sharpness of the refrigerator's signals was used for the input value in ANN's training process because the loudness and the sharpness has a good correlation between the output of the ANN and the target of the individual evaluation In the training process. Two input factor was used repeatedly in the training process to get more optimum weighting value. And then finally we developed the sound quality index of a refrigerator. The developed sound quality index was confirmed by the 96.5 % of correlation between the output of the ANN and the real evaluation. It will be applied to evaluate the sound quality of a refrigerator in the industry.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.41-50
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• 1994

Consider a canning process where cans are filled with an expensive ingredient. Cans weighting above the specified limit are sold in a regular market for a fixed price, and underfilled cans are emptied and refilled at the expense of a reprocessing cost. In this paper, the effect of measurement error on the determination of the optimal process mean for a canning process is examined. It is assumed that the quantity X of ingredient in a can is normally distributed with unknown mean and known variance, and the observed value Y of X is also normally distributed with known mean and variance. A profit model is constructed which involves selling price. cost of ingredients, reprocessing cost. and cost from an accepted nonconforming can, and methods of finding the optimal process mean and the cutoff value on Y are presented. It is shown that the optimal process mean increases. and the expected profit decreases when the measurement error is relatively large in comparison to the process variance.