• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.169-180
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• 2020

The purpose of this study was to find the characteristics of the foreign and domestic travels and to seek out the significance of the study, by grouping the geotweets users who moved abroad, according to the average and the standard deviation of moving distances. Geotweets which caused foreign and domestic travels occurred divided, after building a data mart and the moving distances of users were measured by using the Haversine formula. It has moved more often among groups of foreign travelers in countries that use the same language and have similar lifestyles. There has been a lot of movement in developed countries with well-established infrastructure in a group of domestic travelers. This study tried to draw common features, by calculating the travel distances by each user and grouped users according to the characteristics of user's moving distances. There are significant differences in national economic power, age, jobs, etc. among users from a total of 21 countries analyzed by this study, so a more precise analysis would be able to be conducted, only if the whole conditions are considered. A future study should additionally consider real factors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.443-452
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• 2021

One of the key technologies in edge computing is that it always provides services close to the user by moving data between edge servers according to the user's movements. As such, the movement of data between edge servers is frequent. As IoT technology advances and usage areas expand, the data generated also increases, requiring technology to accurately track and process each data to properly manage the data present in the edge computing environment. Currently, cloud systems do not have data disposal technology based on tracking technology for data movement and distribution in their environment, so users cannot see where it is now, whether it is properly removed or not left in the cloud system if users request it to be deleted. In this paper, we propose a tracking data server to create and manage the movement and distribution of data for each edge server and data stored in the central cloud in an edge computing environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.38-46
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• 2024

In general, EEG signal analysis has been the subject of several studies due to its ability to provide an objective mode of recording brain stimulation, which is widely used in brain-computer interface research with applications in medical diagnosis and rehabilitation engineering. In this study, we developed EEG reception hardware to measure electroencephalograms and implemented a processing system, classifying it into server and data processing. It was conducted as an intermediate-stage research on the implementation of a brain-computer interface using electroencephalograms, and was implemented in the form of predicting the user's arm movements according to measured electroencephalogram data. Electroencephalogram measurements were performed using input from four electrodes through an analog-to-digital converter. After sending this to the server through a communication process, we designed and implemented a system flow in which the server classifies the electroencephalogram input using a convolutional neural network model and displays the results on the user terminal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.23-28
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• 2010

Recently, as the number of people using Smartphones increased, several researches has been launched basing it's subject on this issue. In this circumstance, the fusion of sensor technologies and Smartphone offers a variety of functions. The system introduced in the current paper uses a controller which extracts information about accelerating movements of an user. This information is then sent to the Smartphone through Bluetooth communication. The input method proposed in this paper differs from the existing methods such as touch typing or button input in Smartphones. It rather uses the 3-D acceleration sensor which enables users to control their Smartphone anywhere and anytime without directly touching the device. Furthermore, because it is developed for various applications, it can be applied in many different fields.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1027-1030
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• 2005

The article introduces developing trends of an adaptive mobile terminal as an interface for use of various network resources, such as public wireless networks and un-licensed wireless networks in ubiquitous sensor network environments, without troublesome settings or operations by users. These adaptive mobile terminals able to provide seamless services that adapt autonomously to the user's movements and changes in the state of wireless resources. Consequently, adaptive mobile terminals should be had respective independent hardware structure of usable wireless networks.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.61-69
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• 2009

In this paper, to propose a new approach to real-time eye tracking. Existing methods of tracking the user's attention to the little I move my head was not going to get bad results for each of the users needed to perform the calibration process. Infrared eye tracking methods proposed lighting and Generalized Regression Neural Networks (GRNN) By using the calibration process, the movement of the head is large, even without the reliable and accurate eye tracking, mapping function was to enable each of the calibration process by the generalization can be omitted, did not participate in the study eye other users tracking was possible. Experimental results of facial movements that an average 90% of cases, other users on average 85% of the eye tracking results were shown.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.313-323
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• 2023

The wearable robot system is designed to assist human skeletal and muscular systems for enhancing user's abilities in various fields, including medical, industrial, and military. The military has an expanding need for wearable robots with the integration of surveillance/control systems and advanced equipment in unstructured battlefield environments. However, there is a lack of research on the design and mechanism of wearable robots, especially for power assist systems. This study proposes a lightweight wearable robot system that provides comfortable wear and muscle support effects in various movements for soldiers performing high-strength and endurance missions. The Power assist mechanism is described and verified, and the tasks that require power assist are analyzed. This study explain the system including its driving mechanism, control system, and mechanical design. Finally, the performance of the robot is verified through experiments and evaluations, demonstrating its effectiveness in muscle support.