• Korean Journal of Artificial Intelligence
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• v.7 no.1
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• pp.23-59
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• 2019

The purpose of this study is to develop a measure of service quality in the traditional market by examining previous research on the service quality of the traditional market studied so far. After defining basic concepts through definition of traditional market and existing studies, 5 categories of configuration items for SERVQUAL measurement in traditional market were made up based on existing researches related to definition of service quality and service quality of traditional market. A survey was conducted on the items that fit the intention of this study and various statistical analyzes were conducted. Statistical analysis was performed using SPSS 22.0 and AMOS 22.0. The reliability of the items was measured by the reliability test, and the predictability and accuracy of the items were examined. The validity of the measured variables was verified through confirmatory factor analysis. Reliability, empathy, responsiveness, certainty, and tangibility were the most important factors in this study. Responsiveness factors include communication, time reduction, real time, promptness. Assurance factors include the assurance of delivery, prompt answers, product knowledge items. Tangibility factors include, convenient device systems, location information, presence as a fact, and as a result, the latest modern items are adopted. The quality of service in the traditional market developed in this study was found to be good in reliability and validity test. Confirmatory factor analysis result using structural equation model also met the conformity index standard. If service satisfaction is measured based on this research, basic data can be presented to policy makers who implement policies on traditional markets to make the right decisions. In addition, it will be able to provide traditional market operators with operational strategy and marketing data. In the future, based on the traditional market service quality scale developed in this study, it is necessary to grasp the factors to be continuously managed to improve the service quality of the traditional market, user satisfaction, and intention to use.

• Food Science of Animal Resources
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• v.41 no.4
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• pp.563-588
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• 2021

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1335-1343
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• 1999

This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, zero-crossing(ZCR), mean frequency(MEANF), median frequency(MEDF) and autoregressive model coefficient(ARC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern recognition.

• Korean Journal of Artificial Intelligence
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• v.3 no.1
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• pp.1-4
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• 2015

These days, men live better lives owing to economic growth. They are interested in basic desire such as clothing, food and dwelling. This study investigated food and/or eating. Men like to take better quality food to be healthy. They can hear food problems easily by news to satisfy desire. On October 13, 2014, Dongsuh Food Company was prohibited to distribute a serial product named 'Post Almond Flake' (Statistics Korea). Dongsuh Food was found to produce finished product by mixing contaminants without inspection of colon bacillus, and Crown Confectionery was found to produce 'Organic farming wafer' and 'Organic farming choco wafer' from March 2009 to early August, 2016 cognizing rejection at inspection not to inform Ministry of Health and to sell product amounting to 3.1 billion KRW .

• Electronics and Telecommunications Trends
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• v.32 no.6
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• pp.66-72
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• 2017

The frequency range of a radio wave is from 3kHz to 300GHz, and radio technologies use this range to improve the quality of human lives. Radio technologies have entered a new phase of communication. The core infrastructure used as the basis for technologies leading the fourth industrial evolution, such as artificial intelligence, the Internet of Things, autonomous cars/drones, augmented reality, robots, and remote medical diagnoses, is the 5G network. The 5G network enables transmitting and receiving large amounts of data at very high speed. In particular, application technologies with artificial intelligence have been studied, including radar, wireless charging, electromagnetic devices and their effects on humans, EMI/EMC, and microwave imaging. In this study, we present a future radio technology that is needed to prepare for the upcoming industrial revolution and digital transformation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.671-678
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• 2003

This paper proposes an expert system to generate automatically the test table of test system which can highly enhance the quality and productivity of product by inspecting quickly and accurately the defect device on the electronic circuit board tested. The expert system identifies accurately the tested components and the circuit patterns by tracing automatically the connectivity of circuit from electronic circuit database. And it generates automatically the test table to detect accurately the missing components, the misplaced components, and the wrong components for analog components such as resistance, coil, condenser, diode, and transistor, based on the experience knowledge of veteran expert. It is implemented in C computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique, the interface with the electronic circuit database and the hardware direct control. And, the validity of the builded expert system is proved by simulating for a typical electronic board model.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.129-131
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• 2004

The advanced technology called Telematics appeared with the development of automobile industries and IT technologies. In Telematics it is important to offer good quality information to the car which loads the terminal, so in this paper, for this, we propose the intelligent information service method using artificial intelligence(A. I.). In this paper, through the concept of multi-agent, we represent Telematics system and show the interaction between information service center and a terminal for smooth information service. Finally, we mention the way that Telematics should persue for the enhancement of information service.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.34-42
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• 2019

This study introduces artificial intelligence (AI) techniques for video generation. For an effective illustration, techniques for video generation are classified as either semi-automatic or automatic. First, we discuss some recent achievements in semi-automatic video generation, and explain which types of AI techniques can be applied to produce films and improve film quality. Additionally, we provide an example of video content that has been generated by using AI techniques. Then, two automatic video-generation techniques are introduced with technical details. As there is currently no feasible automatic video-generation technique that can generate commercial videos, in this study, we explain their technical details, and suggest the future direction for researchers. Finally, we discuss several considerations for more practical automatic video-generation techniques.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.190-195
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• 2021

Currently, one of the fields leading the 4th industrial revolution is the image recognition field of artificial intelligence, which is showing good results in many fields. In this paper, using is a YOLO V2 model, which is one of the image recognition models, we intend to classify and select into three types according to the characteristics of fruits. To this end, it was designed to proceed the number of iterations of learning 9000 counts based on 640 mandarin image data of 3 classes. For model evaluation, normal, rotten, and unripe mandarin oranges were used based on images. We as a result of the experiment, the accuracy of the learning model was different depending on the number of learning. Normal mandarin oranges showed the highest at 60.5% in 9000 repetition learning, and unripe mandarin oranges also showed the highest at 61.8% in 9000 repetition learning. Lastly, rotten tangerines showed the highest accuracy at 86.0% in 7000 iterations. It will be very helpful if the results of this study are used for fruit farms in rural areas where labor is scarce.

• Smart Media Journal
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• v.12 no.4
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• pp.9-18
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• 2023

Steganography is a technology capable of protecting data by hiding the existence of data. Recently, with the development of deep learning technology, deep learning-based steganography are being developed. Deep learning can learn by analyzing high-dimensional features of data, so it can improve the performance and quality of steganography. In this paper, we investigated the research trend of image steganography based on deep learning.