• Journal of Sport and Applied Science
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• v.4 no.4
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• pp.27-32
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• 2020

Purpose: This study sought to explore the effects of air pollution on professional sports in South Korea. Research design, data, and methodology: The dependent variable, the number of attendances, was comprised of 2013-2017 K-league, 2015-2017 KBO, 2014-2017 KBL regular season games, resulting in 1,063, 2,121, 810 individual match-level observations, respectively. With the actual data collected from each place across the country, we created a categorical variable which identify the air quality index divided into four categories by K-eco (i.e., good, moderate, unhealthy, hazardous). To analyze data, ANOVA was employed. Results: First, there was a significant group effect on K-league attendance. Second, there was a significant group effect of KBO attendance. Lastly, there was a significant group effect on KBL attendance. Conclusions: Summary of above results showed that each professional sport leagues' attendance was significantly different depending on the levels of air pollution. Implications were also discussed. Keywords: air pollution, sport spectatorship, professional sports.

• KIISE Transactions on Computing Practices
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• v.21 no.4
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• pp.283-289
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• 2015

We propose a low cost attendance checking system using NFC (Near Field Communication) and show a case study of an actual operation of the system in a higher education institute. The system offers a direct attendance check service when a student touches NFC tag on a classroom desk with his/her own smartphone. Our service was first developed and operated in 2012, and then additional functions like massive real time processing were reinforced. In the fall semester, 58 courses use the service and 96% of the class attendance was checked with mobile devices. The only hardware requirement of the system was NFC tag on the classroom desk, which reduced hardware cost dramatically. However, it also minimized attendance checking time into 1 minute regardless of enrolled student number.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.261-267
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• 2021

The mission of the reserve forces unit is to prepare good training for reserve forces during peacetime. For good training, units require proper organization support agents, but they have difficulties due to a lack of unit members. For that reason, the units forecast the monthly attendance rate of reserve forces (using the x-1 year's result) to organize support agents and unit schedule. On the other hand, the existing planning method can have more errors compared to the actual result of the attendance rate. This problem has a negative effect on the training performance. Therefore, it requires more accurate forecast models to reduce attendance rate errors. This paper proposes an attendance rate forecast model using data mining. To verify the proposed data mining based model, the existing planning method was compared with the proposed model using real data. The results showed that the proposed model outperforms the existing planning method.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.131-135
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• 2024

Baseball attracts the largest audience among professional sports in Korea. In particular, attendance is the primary source of income in baseball. Previous studies have limitations in reflecting the characteristics of individual stadium. For instance, the KIA Tigers exhibit the highest away game revenue among domestic teams, but they show lower home game earnings. Therefore, we aim to predict the daily attendance at the Gwangju-KIA Champions Field of the KIA Tigers using deep learning. We collected and preprocessed daily attendance, dates, weather, and team-related variables for Gwangju-KIA Champions Field from 2018 to 2023. We propose a deep learning-based linear regression model to predict the daily attendance. We expect that the proposed deep learning model will be used as basic information to increase the club's revenue.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.890-899
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• 2010

The sport industry has been continuing to grow in the past few decades in the U.S., and it presents significant opportunities for the practitioners to increase the number of patrons. To convert this opportunity to optimum benefits for a sport organization, one of the most significant challenges for the practitioners would be promoting sport attendance and repatronage. So far, many studies have tried to identify variables that affect the level of sports attendance. However, many of these variables are rather uncontrollable due to the nature of the sports and contingencies that are derived from many areas of uncertainties. Thus, to acquire competitive advantage and profit maximization, it would be essential for the managers to focus on understanding controllable elements. This study found that many controllable variables that influence sports attendance coincide with the servicescape elements which have been widely used in the hospitality industry since 1992. In the light of the conceptual framework of servicescape, this study also attempted to isolate the controllable variables that can be utilized to increase the sports attendance. This study presents its significance not only in extending the application of servicescape concept to the sport industry, but also in providing suggestions for future empirical studies that would further identify these variables, gauge the relationship between those variables, and assess its impact on the sports attendance.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.565-572
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• 2017

Traditional method for time series analysis, autoregressive integrated moving average (ARIMA) allows to mine significant patterns from the past observations using autocorrelation and to forecast future sequences. However, Korean baseball games do not have regular intervals to analyze relationship among the past attendance observations. To address this issue, we propose artificial neural network (ANN) based attendance prediction model using various measures including performance, team characteristics and social influences. We optimized ANNs using grid search to construct optimal model for regression problem. The evaluation shows that the optimal and ensemble model outperform the baseline model, linear regression model.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.7-12
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• 2017

In this paper, we proposed an electronic attendance-absence recording system using a smartphone that does not require separate BLE(Bluetooth Low Energy) devices and infrastructure by using BLE advertisement technology of smartphone. The existing BLE-based electronic attendance-absence recording system requires a BEL device to be attached to each classroom for services and a separate technology to identify the devices attached to the classroom. Also, due to the interference with each other, sometimes an error occurred in the electronic connection. In this paper, we propose a system to solve the problems about time, place and cost, which is a disadvantage of the conventional Bluetooth beacon system. BLE advertising function of the smartphone that the user is using without BLE device, it is possible to construct infrastructure for electronic attendance-absence recording system. In order to evaluate the effectiveness of the proposed system, we designed the system structure and operation flow and constructed the system using the smart phone in actual used.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.209-214
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• 2016

In an environment of IoT services, sensors to track things and human activities are included as an essential element and smart phone is actively used as a means of collecting and processing information from sensors. Especially, wireless communication and NFC provided by the smart phone are key technologies for exchanging information between participants of IoT service. In this paper, we propose and implement the smart attendance checking system based on BLE using a beacon for improving the quality of a university lecture by processing attendance information automatically. Proposed system uses the beacon sensor for being aware of attendance information and the smart phone for receiving and processing this information. The implemented system has the benefit to improve the lecture quality because a professor can minimize attendance checking time and spend a lot of time on the lecture.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.72-79
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• 2010

A EAARS(Electronic Attendance-Absence Recording System) is the important LSS(Learning Support System) for blending a on-line learning in the face-to-face classroom. However, the EAARS based on the smart card can not identify a real owner of the checked card. Therefore, we develop the CS(Client-Sever) system that manages the attendance-absence checking automatically, which is used the self-organizing neural network for the face recognition. A client system creates the ID file by extracting the face feature, a server system analyzes the ID file sent from client system, and performs a student identification by using the Recognized weight file saved in Database. As a result, The proposed CS EAARS shows the 92% efficiency in the CS environment that includes the various face image database of the real classroom.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.247-253
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• 2018

This study was designed to analyze the difference in attendance and academic achievement based on spatio-temporal data relate to e-Learning patterns of university e-Learning learners. This study collected e-Learning data from 68 e-Learning classes, 13,611 learners during 3 years. Collected data were analyzed by t-test and two-way ANOVA. Major study findings were as follows. Firstly, e-Learning learners in school received higher than those of learners outside school both in attendance and academic achievement, while that academic achievement showed statistical significance. Secondly, the attendance and academic achievement by the day was in the order of e-Learning learners mainly in the morning, those in the afternoon and those at night, in addition there was statistical significance. Lastly e-Learning learners in the weekdays appeared higher than those of learners in the weekends both in attendance and academic achievement, also both of them showed statistical significance.