• Journal of the Korean Society of Safety
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• 제27권4호
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• pp.128-133
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• 2012

This research has analyzed factors affecting customers' satisfaction when they use parking lots of big retailers so that, in case of constructing, operating or managing such retailers, proper measures can be come up with. The analysis has been implemented on the basis of survey, and influence factors including entry/exit lamp, parking cars' traffic flow, parking type, pedestrians' movement after parking and safety. Parking lot users' satisfaction has been analyzed by using the Structural Equation Modelling and, as a result of it, in case of a detached or single building, pedestrians' movement flow after parking contributed the most to the users' satisfaction, while, in case of multipurpose complex, parking cars' traffic flow has the most influential factor. It is interpreted that users of a single building put a bigger emphasis on entry to the shop and their way back to the parked area after their shopping while customers of multipurpose complex might have various purposes of visiting the place and there are relatively more cars so that they put more emphasis on traffic counterflow, other cars and pedestrians.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제13권6호
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• pp.249-254
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• 2013

This paper presented a mobile application program to help eye movement with mobile devices. It helps to strengthen ocular muscles and improve visual acuity. Users can easily access the program of eye movement type of app program in mobile devices. There were some papers which studied on the eye movement and showed efficient eye movement method for improvement of visual acuity. So here presents programming codes to help eye movement with some specific patterns from some papers and it was implemented by HTML, CSS and javascript. To convert web code to app code, appspresso tool was used.

• The Journal of the Korea Contents Association
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• 제14권7호
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• pp.45-57
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• 2014

This study examines subjects' eye movement pattern and surveys their attitudes to the exposed advertisements on the Facebook. Different from the F-shaped pattern of the typical Web pages, users' eye movements on the Facebook have shown a rough H-shape. Even though a large number of users have shown F-shaped pattern on the ordinary Web pages in order to skip the contents of a Web, subjects' eye-movement pattern on the Facebook has H -shaped pattern due to the unique User Interface (UI) of the Facebook. With the right side and vertical arrangement of ads on the Facebook, users skip the page with having a large H-shaped pattern. In addition, this study set four AOIs(Area of Interest) that are advertising sections comprised on the Facebook Web page and measured fixation length within the AOIs then surveyed subjects' attitudes about the exposed ads. Through the experiment and survey, this study offers the optimum advertising position that can attract Facebook users' attention. As the result of experiment and survey, the second ad has the subjects' highest attitude to advertising and fourth ad is the next effectiveness and first and third ad followed. This study highlights the key implications to provide better user experiences(UX) and marketing strategies to users who are the consumers of companies and organizations which have a plan to put their advertising on the Facebook.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4908-4922
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• 2019

The popularization of smartphones in recent years has created a rich ground for online-to-offline (O2O) services based on location information. In the process of finding user locations in O2O services, BLE (Bluetooth Low Energy) beacons are widely used because the beacons are economical in many ways. The current BLE method does not specify the direction of user movement, but adding that information could enrich the user experience for various O2O services. This paper proposes a method that identifies the user movement direction through data analysis on data sets generated by a pair of BLE beacons. Also we demonstrate its implementation with examples of services that need the direction information of users in order to show the feasibility of the method proposed.

• The Journal of the Korea institute of electronic communication sciences
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• 제19권1호
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• pp.217-224
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• 2024

With the rapid growth of K-POP, the dance content industry is spreading. With the recent increase in the spread of SNS, they also shoot and share their dance videos. However, it is not easy for dance beginners who are new to dancing to learn dance moves because it is difficult to receive objective feedback when dancing alone while watching videos. This paper describes a system that uses MediaPipe to compare choreography videos and dance videos of users and detect whether they are following the movement correctly. This study proposes a method of giving feedback based on Color Map to users by calculating the similarity of dance movements between user images taken with webcam or camera and choreography images using cosine similarity and COCO OKS. Through this system, objective feedback on users' dance movements can be visually received, and beginners are expected to be able to learn accurate dance movements.

• Annual Conference of KIPS
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.759-762
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• 2015

Many applications require users to log-in, some applications can allow users to use the same account is active on multiple devices at the same time. On location-based application that serves to record the movement of the position, account is active on multiple devices could not be permitted because it causes a different location data from multiple devices, so the location of the users become ambiguous. This paper describes a simple protocol to prevent users from using their accounts on multiple devices at the same time. This Protocol will turn off one account on a device when the account log-in on new devices.

• Science of Emotion and Sensibility
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• 제19권1호
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• pp.31-38
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• 2016

The brain and muscles both of which are composed of top-down structure occur the connectivity with the change of Electroencephalogram(EEG) and Electromyogram(EMG). In this paper, we studied the difference of functional connectivity between brain and muscles that by applying coherence method to EEG and EMG signals when users exercised upper limb with and without the movement intention. The changes in the EEG and EMG signals were inspected using coherence method. During the upper limb exercise, the mu (8~14 Hz) and beta (15~30 Hz) rhythms of the EEG signal at the motor cortex area are activated. And then the beta and piper (30~60 Hz) rhythms of the EMG signal are activated as well. The result of coherence analysis between EEG and EMG showed the coefficient of active exercise including movement intention is significantly higher than passive exercise. The coherence relations between cognitive response and muscle movement could interpret that the connectivity between the brain and muscle appear during active exercise with movement intention. The feature of coherence between brain and muscles by the status of movement intention will be useful in designing the rehabilitation system requiring feedback depending on the users' movement intention status.

• Journal of Communications and Networks
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• 제17권2호
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• pp.126-132
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• 2015

In mobile computing research area, it is highly desirable to understand the characteristics of user movement so that the user friendly location aware services could be rendered effectively. Location based social networks (LBSNs) have flourished recently and are of great potential for movement behavior exploration and datadriven application design. While there have been some efforts on user check-in movement behavior in LBSNs, they lack comprehensive analysis of social influence on them. To this end, the social-spatial influence and social-temporal influence are analyzed synthetically in this paper based on the related information exposed in LBSNs. The check-in movement behaviors of users are found to be affected by their social friendships both from spatial and temporal dimensions. Furthermore, a probabilistic model of user mobile behavior is proposed, incorporating the comprehensive social influence model with extent personal preference model. The experimental results validate that our proposed model can improve prediction accuracy compared to the state-of-the-art social historical model considering temporal information (SHM+T), which mainly studies the temporal cyclic patterns and uses them to model user mobility, while being with affordable complexity.

• Proceedings of the KSR Conference
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.730-738
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• 2010

In the development of railroad station area, there are many factors about business management, but the interest of railroad users is an important factor as customer satisfaction. It is necessary to have the quality estimation of railroad service, and important factors of service as customer satisfaction aspects can be supply, reliability, convenience, and safety. In this study, primary factors are deduced in the efficiency aspects of railroad station facilities from analyzing relative importance index using AHP(Analytic Hierarchy Process) methods. The most high rank important factor is railroad station user facilities, and the AHP importance index of passenger facilities and elevator facilities for KORAIL personnel and facility users is index. The third of KORAIL personnel is movement facilities, but facility users index is sanitation. And the low important factors of KORAIL personnel and facility users are shown as the platform in passenger facilities, the rest facilities in waiting room, the escalator in going up and coming down facilities, the escalator in movement facilities, the raised letters block in guide facilities, and the parking lot in subsidiary facilities.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.437-444
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• 2012

In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.