• International Journal of Contents
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• v.15 no.4
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• pp.113-119
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• 2019

It has been reported that large amounts of information on agri-foods were delivered to consumers through television and social networks, and the information may influence consumers' behavior. The purpose of this paper was first to analyze relations of social network service and broadcasting program on paprika consumption in the aspect of amounts to purchase and identify potential factors that can promote paprika consumption; second, to develop prediction models of paprika consumption by using structured and unstructured big data. By using data 2010-2017, cross-correlation and time-series prediction algorithms (autoregressive exogenous model and vector error correction model), statistically significant correlations between paprika consumption and television programs/shows and blogs mentioning paprika and diet were identified with lagged times. When paprika and diet related data were added for prediction, these data improved the model predictability. This is the first report to predict paprika consumption by using structured and unstructured data.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.15-21
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• 2021

This paper conducted a feasibility study by applying an Internet of Things and Artificial intelligence-based management system for the elderly living alone in an aging society. The number of single-person families over the age of 50 is expected to increase, and problems such as health, safety, and loneliness may occur due to aging. Therefore, by establishing an IoT-based care system for the elderly living alone, a stable service was developed through securing a rapid response system for the elderly living alone and automatically reporting 119. The participants of the demonstration test were subjects under the jurisdiction of the "Seongnam Senior Complex," and the data collection rate between the IoT sensor and the emergency safety gateway was high. During the demonstration period, as a result of evaluating the satisfaction of the IoT-based care system for the elderly living alone, 90 points were achieved. We are currently in the COVID-19 situation. Therefore, the number of elderly living alone is continuously increasing, and the number of people who cannot benefit from care services will continue to occur. Also, even if the COVID-19 situation is over, the epidemic will happen again. So the care system is essential. The elderly care system developed in this way will provide safety management services based on artificial intelligence-based activity pattern analysis, improving the quality of in-house safety services.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.125-131
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• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.781-786
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• 2019

We should give a realistic value on the large amounts of relevant data obtained from these studies to achieve effective objectives of the disease study which is dealing with various vital phenomenon today. In this paper, the proposed MKSV algorithm is estimated by optimal probability distribution, and the input pattern is determined. After classifying it into data mining, it is possible to obtain efficient computational quantity and recognition rate. MKSV algorithm is useful for studying the relationship between disease and gene in the present society by simulating the probabilistic flow of gene data and showing fast and effective performance improvement to classify data through the data mining process of big data.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1108-1121
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• 2019

As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.1-6
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• 2022

In this paper, the research and development aim to strengthen the digital accessibility of the elderly by developing a kiosk incorporating AI voice recognition technology that can replace the promotional signage currently being installed and spread in the elderly and social welfare centers most frequently used by the digital underprivileged. It was intended to develop a converged system for the use of bulletin board functions, educational functions, and welfare center facilities, and to seek ways to increase the user's digital device experience through direct experience and education. Through interviews and surveys of senior citizens and social welfare centers, it was intended to collect problems and pain Points that the elderly currently experience in the process of using kiosks and apply them to the development process, and improve problems through pilot services. Through this study, it was confirmed that voice recognition technology is 2 to 6 times faster than keyboard input, so it is helpful for the elderly who are not familiar with device operation. However, it is necessary to improve the problem that there is a difference in the accuracy of the recognition rate according to the surrounding environment with noise. Through small efforts such as this study, we hope that the elderly will be a little free from digital alienation.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.5
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• pp.91-97
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• 2022

The Directed Energy Deposition (DED) is a representative metal additive manufacturing method. Owing to its strong point of repairment, its application is gradually spreading in aerospace applications, power generation, military components, and mold making. 5-axis cladding is needed to repair damage, such as wear and scratches on cylindrical surfaces to circular-shaped parts, including sleeves and liners. Furthermore, the condition of cladding on inclined parts must also be considered to prevent interference between the nozzle and the part. In this study, the effects of changes in scanning speed due to the 5-axis control system and differences from the height of laser beam irradiation due to inclination are evaluated among the items that should be additionally considered in 5-axis cladding compared to 3-axis cladding. Moreover, the trends of the width and height of the clad are identified by different tilting angles via single line cladding. Lastly, cladding methods on cylindrical surfaces at various angles are proposed to enhance the clad quality and post-processing efficacy. These results can be applied with 5-axis cladding on inclined surfaces, including cylindrical surfaces.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.601-608
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• 2023

Homomorphic encryption is a promising technology that has been extensively researched in recent years. It allows computations to be performed on encrypted data, without the need to decrypt it. In this paper, we perform bibliometric analysis to objectively and quantitatively analyze the research trends of homomorphic encryption technology using 6,047 homomorphic encryption papers from the Scopus database. Specifically, we analyze the number of papers by year, keyword co-occurrence, topic clustering, changes in related keywords over time, and country of homomorphic encryption research institutions. Our analysis results provide strategic directions for research and application of homomorphic encryption and can be a great help for subsequent research and industrial applications.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.15-20
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• 2023

The purpose of this study is to analyze the changes and importance of welfare policies in Chungcheong Province using big data analysis technology in the era of the Fourth Industrial Revolution, and to propose stable welfare policies for all generations, including the socially underprivileged. Chungcheong-do policy-related big data is coded in Python, and stable government policies are proposed based on the results of visualization analysis. As a result of the study, the keywords of Chungcheong-do government policy were confirmed in the order of region, society, government and support, education, and women, and welfare policy should be strengthened with a focus on improving local health policy and social welfare. For future research direction, it will be necessary to compare overseas cases and make policy proposals on the stable impact of national welfare policies.