• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.441-447
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• 2007

The conjoint analysis is widely accepted in the field of marketing as a way to understand and incorporate the structure of customer preferences into the new product design process. We apply the conjoint analysis for understanding preferences about after school computer courses in elementary schools. We show that the artificial neural network analysis in addition to the conjoint analysis is very useful to understand the needs of elementary school students about after school computer courses.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.198-204
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• 2019

In this study, the author introduces a supply-chain management (SCM) solution that connects suppliers, manufacturers, customers, and other companies within a transactional relationship to enable efficient inventory management and timely product supply, which ultimately maximizes corporate profits. This proposed solution exploits Fourth Industrial Revolution technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), which provide solutions to complex management issues generated by the broader market. The goal of the current study was to develop an advanced and intelligent smart SCM solution that complies with logistics standards, to enhance the visibility, safety, and efficiency of a supply chain made up of manufacturers and suppliers. This smart SCM solution aims at maximizing corporate profits through efficient inventory management and timely supply of products, and solves the complex management problems caused by operating within a wide range of markets.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.153-154
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• 2019

In this study, the fluidity and compressive strength of lightweight mortar using recycling water for pre-wetting of artificial lightweight aggregate were compared and analyzed to maximize the utilization of the recycling water, which is a by-product of the Ready-Mixed Concrete industry. For this purpose, the pre-wetting water was replaced with recycling water at the ratio of 0, 2.5, 5, 7.5 and 10%.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1367-1374
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• 2022

In this paper, we propose an automatic cosmetic foundation recommendation system that suggests a good foundation product based on the user's skin color. The proposed system receives and preprocesses user images and detects skin color with OpenCV and machine learning algorithms. The system then compares the performance of the training model using XGBoost, Gradient Boost, Random Forest, and Adaptive Boost (AdaBoost), based on 550 datasets collected as essential bestsellers in the United States. Based on the comparison results, this paper implements a recommendation system using the highest performing machine learning model. As a result of the experiment, our system can effectively recommend a suitable skin color foundation. Thus, our system model is 98% accurate. Furthermore, our system can reduce the selection trials of foundations against the user's skin color. It can also save time in selecting foundations.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.40-44
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• 2023

The defect detection based on deep learning requires minimal loss and high accuracy to pinpoint product defects. In this paper, we confirm the loss rate of deep learning training based on disc-shaped artificial scaffold images. It is intended to compare the performance of Cross-Entropy functions used in object detection algorithms. The model was constructed using normal, defective artificial scaffold images and category cross entropy and sparse category cross entropy. The data was repeatedly learned five times using each loss function. The average loss rate, average accuracy, final loss rate, and final accuracy according to the loss function were confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.842-848
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• 2018

The Smart plug is a device that connects between the outlet and the product at home, and it is an IoT type device that can drive energy saving and transmit information to the outside by power on / off control function and power measurement function. In this case, a smart plug that incorporates deep learning of intelligence technology that allows people to learn how to think about a computer, automatically classifies a product as it operates, and automatically tests the operating status of the washing machine by using input AC current pattern. Through this study, even if the product does not function as IoT, it can classify product type and operation state by smart plug connection alone, so we can draw a new paradigm of life pattern and energy saving in one family.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1156-1166
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• 2022

In this study, we examined voice shopping interaction in which consumers can be involved in the decision-making process. Sixteen kinds of voice shopping interaction were designed with differences in the existence of screen/product involvement/conversation style. Their effects on trust, cognitive load, satisfaction, and continuous intention to use were evaluated through a survey experiment. The main effect of conversation style was significant, and it was found that the more deeply involved users have higher trust. The interaction effect between conversation style and product involvement was also significant. Low involvement product buyers had the most positive user experience from the conversation style that included 'Ask for preference,' while high involvement product buyers had the most positive user experience from the conversation style that included both 'Ask for preference' and 'Question and Answer.' The main effect and interaction effect of the existence of screen was not significant. The results indicate that a positive user experience can be obtained when users are deeply involved in consumer decision-making, especially in purchasing high-involvement products.

• Korean journal of applied entomology
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• v.46 no.1 s.145
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• pp.123-129
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• 2007

An artificial insemination instrument of bumblebee queens was firstly developed. This instrument consists of location tube, transfer tube, holding tube, head product, and probe apparatus for reproductive tract etc. This instrument was designed to minimize stress and damage of reproductive tract of bumblebee queens. The regulator handle apparatus in artificial insemination instrument was used the principle of lever, that manipulates easy, accurate and rapid insemination of bumblebee queens. By using this instrument, the insemination rate was over 90%. This instrument will be useful for the breeding and conservation of excellent character of bumblebees.

• Water Engineering Research
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• v.4 no.2
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• pp.59-68
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• 2003

The applicabilities and validities of two methodologies fur the prediction of THM (trihalomethane) formation in a water pipeline system were proposed and discussed. One is the multiple regression technique and the other is an artificial neural network technique. There are many factors which influence water quality, especially THMs formations in water pipeline systems. In this study, the prediction models of THM formation in water pipeline systems are developed based on the independent variables proposed by American Water Works Association(AWWA). Multiple linear/nonlinear regression models are estimated and three layer feed-forward artificial neural networks have been used to predict the THM formation in a water pipeline system. Input parameters of the models consist of organic compounds measured in water pipeline systems such as TOC, DOC and UV254. Also, the reaction time to each measuring site along pipeline is used as input parameter calculated by a hydraulic analysis. Using these variables as model parameters, four models are developed. And the predicted results from the four developed models are compared statistically to the measured THMs data set. It is shown that the artificial neural network approaches are much superior to the conventional regression approaches and that the developed models by neural network can be used more efficiently and reproduce more accurately the THMs formation in water pipeline systems, than the conventional regression methods proposed by AWWA.

• Journal of Microbiology and Biotechnology
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• v.24 no.5
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• pp.614-618
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• 2014

Resveratrol, which is a polyphenolic antioxidant, is dose-dependent when used to provide health benefits, to enhance stress resistance, and to extend lifespans. However, even though resveratrol has therapeutic benefits, its clinical therapeutic effect is limited owing to its low oral bioavailability. An Escherichia coli system was developed that contains an artificial biosynthetic pathway that produces resveratrol glucoside derivatives, such as resveratrol-3-Oglucoside (piceid) and resveratrol-4'-O-glucoside (resveratroloside), from simple carbon sources. This artificial biosynthetic pathway contains a glycosyltransferase addition (YjiC from Bacillus) with resveratrol biosynthetic genes. The produced glucoside compounds were verified through the presence of a product peak(s) and also through LC/MS analyses. The strategy used in this research demonstrates the first harnessing of E. coli for de novo synthesis of resveratrol glucoside derivatives from a simple sugar medium.