• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.7-14
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• 2019

Users who use smartphone can using knowledge-based authentication, possession-based authentication, biometric-based authentication, and token-based authentication in order to access rights to systems requiring authentication. However, desktop computer users use method only ID and password, which are knowledge-based authentication factors, due to limitations of authentication devices, despite various authentication methods. In this paper, we designed and implemented a raspberry pi based authentication system that provides multiple authentication method of a user's desired type. The implementation system uses knowledge-based authentication, possessive-based authentication, biometric-based authentication, and token-based authentication. The proposed system can provide a security function that can be used by SMEs, which is difficult to hire a security officer due to the economic burden. The implemented system can be used not only for personal use but also for enterprise, and it can be applied to various fields such as finance and game.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.845-847
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• 2014

In recent years, the mobile OS market, enlargement and, at the same time, Android has mounted various smart phones and feature air conditioning, smart TV, cleaning robot, camera, etc. that the number is being spread at a rapid pace. But a lot of devices to control the modules and applications at once, this is not a device for controlling the dissemination of applications all in one place, and in charge of the devices that allow you to manage applications are lacking. Accordingly, in this paper, use the Web Server registered in the appliance can be controlled by management, Web access, is proposing and designing the system. This is the current research is actively in progress in the field of IoT (Internet of Things) would be utilized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.606-608
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• 2014

The Study on the technique of applying the method USB redirection on Linux-based SPICE-GTK VDI solution for in (Virtual Desktop Infrastructure) VDI solution for Android-based USB redirection in this paper. VDI solutions are developed according to the development of many of the latest Android-based devices, but a VDI solution that supports USB redirection is limited. Also does not support USB redirection of Android to use the SPICE VDI solution. Therefore, the text presents the techniques applied to the Android-based VDI solutions applied to analyze the way USB redirection of SPICE-GTK VDI solution based on Linux. G PRO smartphone devices to install and use Linux-based VDI server to a test of the method applied in this paper, and the USB redirection applied VDI clients using a USB storage device, USB redirection is done playing files results you can check

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.169-174
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• 2019

This paper propose a system to notify the user that detects failure of malfunction of smart farm ICT devices. As the fourth industrial revolution approaches, agriculture is also fused with ICT technology to improve competitiveness. Smart farming market is rapidly growing every year, but there is still a lack of standardization and certification systems. Especially, smart farm devices that are widely used in Korea are different in product specifications, software and hardware are developed separately, and quality and compatibility are poor. Therefore, a system that can recognize the abnormality of the equipment due to the frequent damage of farmers using low cost smart farm equipment is needed. In this paper, we review smart farm domestic and overseas policy trends and domestic smart agriculture trends, analyze smart farm failure or malfunctions and proactively prevent them, and propose a system to inform users when problems occur.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.1
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• pp.67-80
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• 2012

Recently as the number of smartphone user is growing rapidly, android is also getting more interest in digital forensic. However, there is not enough research on digital data acquisition and analysis based on android platform's unique characteristics so far. Android system stores all the related recent systemwide logs from the system components to applications in volatile memory, and therefore, the logs can potentially serve as important evidences. In this paper, we propose a digital data acquisition and analysis system for android which extracts meaningful information based on the correlation of android logs and user activities from a device at runtime. We also present an efficient search scheme to facilitate realtime analysis on site. Finally, we demonstrate how the proposed system can be used to reconstruct the sequence of user activities in a more intuitive manner, and show that the proposed search scheme can reduce overall search and analysis time approximately 10 times shorter than the normal regular search method.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.1-9
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• 2021

Artificial intelligence (AI) devices are rapidly emerging as a core platform of next-generation information and communication technology (ICT), this study investigated consumer usage behavior and user experience through AI devices that are widely applied to consumers' daily lives. To this end, data was collected from 600 consumers with experience in using AI devices were derived to recognize the attributes and behavior of AI devices. The analysis results are as follows. First, music listening was the most used among various attributes and it was found that simple functions such as providing weather information were usefully recognized. Second, the main devices used by AI device users were identified as AI speakers, smartphone, PC and laptops. Third, associative images of AI devices appeared in the order of fun, useful, novel, smart, innovative, and friendly. Therefore, practical implications are suggested to contribute to provision of user services using AI devices in the future by analyzing usage behaviors that reflect the characteristics of AI devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1325-1330
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• 2020

New-born babies who require special attention medically are admitted often to incubator. Incubators are well equipped to fulfill take care of infants, but they have to hospital and so expensive. This paper proposes a smart incubator that can solve the problem of convenience and cost aspect of these incubators. Developed incubator enables near-field monitoring using Arduino Uno as the main control device and Bluetooth communication. The environment in the incubator measures temperature and humidity using a DHT22 sensor and the sound using a P5510 microphone. If the temperature and humidity data set by the user are lower or higher than the reference value, it is designed to operate the heating pad using the controller or turn on the fan to allow air circulation. The measured values in the incubator are displayed in real time on the user's smartphone monitoring screen and are programmed using app inventor. Developed incubators can help take care of infants at low cost in the home.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.146-152
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• 2022

Information collected from temperature, humidity, inclination, and pressure sensors using Raspberry Pi or Arduino is used in automatic constant temperature and constant humidity systems. In addition, by using it in the agricultural and livestock industry to remotely control the system with only a smartphone, workers in the agricultural and livestock industry can use it conveniently. In general, temperature and humidity are expressed in a line graph, etc., and the change is monitored in real time. The technology to visually express the temperature has recently been used intuitively by using an infrared device to test the fever of Corona 19. In this paper, the information collected from the Raspberry Pi and the DHT11 sensor is used to predict the temperature change in space through intuitive visualization and to make a immediate response. To this end, an algorithm was created to effectively visualize temperature and humidity, and data representation is possible even if some sensors are defective.

• Journal of Korean Biological Nursing Science
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• v.23 no.4
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• pp.287-297
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• 2021

Purpose: This study aimed to evaluate the correlation and agreement of physical activity (PA) between data obtained from wearable Actigraph devices and self-reporting questionnaires, and to investigate the relationship between psychological state (depression, anxiety, and fatigue) and PA. Methods: A descriptive study was conducted using physical measurements and surveys. PA was measured through both the International Physical Activity Questionnaire (IPAQ) and the Actigraph GT3X+ device. The demographic characteristics of the subjects, as well as their depression, anxiety, and fatigue scores, were collected with structured questionnaires. The Spearman's rank correlation coefficient and the Bland-Altman plot method were employed. Results: Data from 36 healthy adults were analyzed. The overall levels of PA measured using the IPAQ and the Actigraph were 1,891.69 MET min/week and 669.96 MET/day, respectively. Total levels of PA did not show a significant correlation between the two measurement methodologies. However, the moderate-intensity PA resulting from the IPAQ scores showed a significant positive correlation with the light-intensity PA recorded by the Actigraph. The Bland-Altman plot analysis demonstrated that the levels of PA as measured by the two different methods did not match. In addition, PA measured using the Actigraph showed a significant negative correlation with depression and anxiety whereas PA measured using the IPAQ showed a significant positive correlation with fatigue. Conclusion: The conclusion of this study is that the data obtained from the subjective self-reporting questionnaire and the wearable Actigraph do not correlate or match in healthy adults. Future research should investigate the relationship between depression and PA intensity through the Actigraph, or other wearable devices equipped with smartphone apps.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.70-75
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• 2022

Accurately measuring location is necessary to provide a variety of services. The data for indoor positioning measures the RSSI values from the WiFi device through an application of a smartphone. The measured data becomes the raw data of machine learning. The feature data is the measured RSSI value, and the label is the name of the space for the measured position. For this purpose, the machine learning technique is to study a technique that predicts the exact location only with the WiFi signal by applying an efficient technique to classification. Ensemble is a technique for obtaining more accurate predictions through various models than one model, including backing and boosting. Among them, Boosting is a technique for adjusting the weight of a model through a modeling result based on sampled data, and there are various algorithms. This study uses Xgboost among the above techniques and evaluates performance with other ensemble techniques.