• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.214-220
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• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.22-29
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• 2021

COVID-19, which has spread around the world, is also affecting local economic industries such as the domestic tourism industry and the service industry. In particular, the quality of life is threatened as safety prevention rules related to infectious diseases such as social distancing have been regularized. The purpose of this study is to analyze the impact on safety quarantine on users of the summer festival at Songho Beach in Haenam, a summer resort. In addition, it protrudes through big data surveys, demographic analysis, and technology analysis on the management of users who have changed in the COVID-19 era. It is expected to be a reference material by utilizing practical data on users in the future. In addition, this study is significant that it has been reviewed for safety and satisfaction for tourists using the summer beach festival through quarantine management using ICT technology in the COVID-19 situation, and needs to be used as good guidelines and examples for this study in the future.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.20-26
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• 2021

In this paper, we studied the rotation angle estimation methods required for image alignment in an image recognition environment. In particular, a rotation angle estimation method applicable to a low specification embedded-based environment was proposed and compared with the existing method using complex moment. The proposed method estimates the rotation angle through similarity mathcing of the 1D projection profile along the radial axis after converting an image into polar coordinates. In addition, it is also possible to select a method of using vector sum of the projection profile, which more simplifies the calculation. Through experiments conducted on binary pattern images and gray-scale images, it was shown that the estimation error of the proposed method is not significantly different from that of complex moment-based method and requires less computation and system resources. For future expansion, a study on how to match the rotation center in gray-scale images will be needed.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.138-144
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• 2021

In the electronic component assembly business, when product defects occur, it is important to track incoming raw material defects or work defects, and it is important to improve suppliers or work sites according to the results. The core task of the smart factory is to build an integrated data hub to process storage, management, and analysis in real time, and to manage cluster processes, energy, environment, and safety. In order to improve reliability through accurate analysis and collection of production data by real-time monitoring of production site management for electronic parts-related small and medium-sized enterprises (SMEs), the establishment of a smart factory is essential. This paper was developed to be utilized in the construction by defining the system configuration method, smart factory-related technology and application cases, considering the characteristics of SMEs related to electronic components that want to introduce a smart factory.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.131-137
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• 2021

The aim of the study was to observe the influence and related mechanism of histamine and its analogues used for hypersensitivity tests and used as an indicator of impurities in drugs on the tissue-specific intestinal contraction. Intestinal contraction includes the activation of thick or thin filament regulation. However, there are few reports addressing the question whether this regulation is involved in histamine-induced regulation. We hypothesized that histamine plays a role in tissue-dependent regulation of intestinal contractility. Denuded ileal/colonic longitudinal and circular muscles of male rats were used and isometric contractions were recorded using a data acquisition system. Interestingly, histamine alone didn't increase the contraction of the circular muscle but increased the contraction of the longitudinal muscle. Histamine together with atropine (M3 receptor antagonist) didn't inhibit the contraction of the longitudinal and circular muscle. Therefore, histamine alone and together with atropine increases the ileal longitudinal muscle contraction suggesting that additional mechanisms (decreased receptor density, postreceptor signaling or distribution of agonists) might be involved in the regulation of ileal muscle contractility. In conclusion, histamine and/or atropine has some effect on the regulation of the longitudinal contractility regardless of M3 receptor and the simpler test would be preferred as the drug impurity test compared to more complicated tests.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.10-19
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• 2021

In this paper, we tried to derive characteristic parameters that reflect mental fatigue through EEG measurement and analysis. For this purpose, mental fatigue was induced through a resting state with eyes closed and performing subtraction operations in mental arithmetic for 30 minutes. Five subjects participated in the experiment, and all subjects were right-handed male students in university, with an average age of 25.5 years. Spectral analysis was performed on the EEG collected at the beginning and the end of the experiment to derive feature parameters reflecting mental fatigue. As a result of the analysis, the absolute power of the alpha band in the occipital lobe and the temporal lobe increased as the mental fatigue increased, while the relative power decreased. Also, the difference in power between resting state and task state showed that the relative power was larger than the absolute power. These results indicate that alpha relative power in the occipital lobe and temporal lobe is a feature parameter reflecting mental fatigue. The results of this study can be utilized as feature parameters for the development of an automated system for mental fatigue determination such as fatigue and drowsiness while driving.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.44-50
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• 2021

Recently, enterprise storage systems that require large-capacity storage devices to accommodate big data have used large-capacity flash memory-based storage devices with high density compared to cost and size. This paper proposes a high-efficiency life prediction method with slope descent to maximize the life of flash memory media that directly affects the reliability and usability of large enterprise storage devices. To this end, this paper proposes the structure of a matrix for storing metadata for learning the frequency of defects and proposes a cost model using metadata. It also proposes a life expectancy prediction policy in exceptional situations when defects outside the learned range occur. Lastly, it was verified through simulation that a method proposed by this paper can maximize its life compared to a life prediction method based on the fixed number of times and the life prediction method based on the remaining ratio of spare blocks, which has been used to predict the life of flash memory.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.168-175
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• 2021

Goal of this study is to perform the correlation about Gross motor function, eating-drinking function, and oral motor function, to identify necessity for invervention of feeding disorders on severity of the function of children with cerebral palsy. Subjects were 61 children diagnosed with cerebral palsy. The subject were evaluated for oral motor function, feeding function by GMFCS, EDACS, OMAS. The results of this study showed a significant correlation between gross motor function, eating and drinking functions, and oral motor functions. That is, the more severe the deterioration of the motor function, the lower the functional level of eating and drinking and oral motor function deterioration. In evaluating and treating the eating activity of children with cerebral palsy through this study, it seems necessary to check the eating and drinking function and oral motor function according to the gross motor function.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.94-103
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• 2021

This study aims to propose technical trading rules for Bitcoin futures and empirically analyze investment performance. Investment strategies include standard trading rules such as VMA, TRB, FR, MACD, RSI, BB, using Bitcoin futures daily data from December 18, 2017 to March 31, 2021. The trend-following rules showed higher investment performance than the comparative strategy B&H. Compared to KOSPI200 index futures, Bitcoin futures investment performance was higher. In particular, the investment performance has increased significantly in Sortino Ratio, which reflects downside risk. This study can find academic significance in that it is the first attempt to systematically analyze the investment performance of standard technical trading rules of Bitcoin futures. In future research, it is necessary to improve investment performance through the use of deep learning models or machine learning models to predict the price of Bitcoin futures.