• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.91-96
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• 2017

In this paper, we aim to respond efficiently to crime by using Arduino and smartphone apps in response to increasing number of house-breaking crimes. It receives the signal of the sensor installed in the house and connects it with the app of the smartphone. To use the app, you can download the app from the user's smartphone, launch the app, and operate the operation outside the home, not only inside the house, by linking the executed app. Among the sensors installed in the house, the movement detection sensor is used to enhance the security, and the gas leakage sensor and the flame detection sensor can be used to easily detect the risk of fire and to prevent the fire early. Security is further enhanced by the ability to remotely control the front door with a smartphone. After that, various sensors can be added and it can be developed as a WiFi module in addition to the Bluetooth module.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.941-949
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• 2014

Demands for cloud computing service rapidly increased along with the expansion of supplying smart devices. Interest in cloud system has led to the question whether it is really safe. Due to the nature of cloud system, cloud service provider can get a user's private information and disclose it. There is a large range of opinion on this issue and recently many researchers are looking into fully homomorphic encryption as a solution for this problem. Fully homomorphic encryption can permit arbitrary computation on encrypted data. Many security threats will disappear by using fully homomorphic encryption, because fully homomorphic encryption keeps the confidentiality. In this paper, we research possible security threats in cloud computing service and study on the application method of fully homomorphic encryption for cloud computing system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.483-486
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• 2011

Recently, large and small vehicle accidents due to human life and property due to loss of function similar to that used on the plane with a black box mounted on the vehicle by the driver of the vehicle in order to analyze the cause of the accident vehicle you are using a black box. The black box used in the existing operating system, unlike the Android OS portability is good compared to other OS support an open platform for the development of additional costs or proven, which includes many libraries need to use any external libraries there are no advantages. In addition, the existing black box on the incident can not be sent automatically to report an accident notification has a problem. In this paper, another advantage of the OS used in a black box with an Android-based acceleration sensor on the test board GPS module and smart phones using the information, and incident detection capability to send a message to the specified number of black boxes with was implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.499-508
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• 2004

The Smart Home or intelligent home network control system has the need for home devices to cooperate for the purpose of providing the automated services to residents. The cooperation of home devices can be defined as the service for residents that it controls simultaneously two or more home devices with the same purpose about user's control request of specific home device. A object of home device cooperation are the function object of home device, it is well defined in each device model in AHAM(Association of Home Appliance Manufactures) nth(Connected Home Appliances). AMAM CHA is to promote new appliance services and features enabled through networking by describing generic appliance models, objects, and high-level messages, but does not consider the description and process of cooperation between objects of each device model. This paper defines the cooperation relationship that could be discovered in among home devices, and proposes the cooperation model that AHAM objects could process the cooperation relationship.

• Journal of KIISE
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• v.43 no.7
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• pp.781-785
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• 2016

Learning from human behaviors in the real world is essential for human-aware intelligent systems such as smart assistants and autonomous robots. Most of research focuses on correlations between sensory patterns and a label for each activity. However, human activity is a combination of several event contexts and is a narrative story in and of itself. We propose a novel approach of human activity prediction based on event cognition. Egocentric multi-sensor data are collected from an individual's daily life by using a wearable device and smartphone. Event contexts about location, scene and activities are then recognized, and finally the users" daily activities are predicted from a decision rule based on the event contexts. The proposed method has been evaluated on a wearable sensor data collected from the real world over 2 weeks by 2 people. Experimental results showed improved recognition accuracies when using the proposed method comparing to results directly using sensory features.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.1-17
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• 2021

Identifying the exact train and the type of train boarded by passengers is practically cumbersome. Previous studies identified the trains boarded by each passenger by matching the Automated Fare Collection (AFC) data and the train schedule diagram. However, this approach has been shown to be inefficient as the exact train boarded by a considerable number of passengers cannot be accurately determined. In this study, we demonstrate that the AFC data - diagram matching technique could not estimate 28% of the train type selected by passengers using the Seoul Metro line no.9. To obtain more accurate results, this paper developed a two-step method for estimating the train type boarded by passengers by applying the AFC data - diagram matching method followed by a mixture distribution analysis. As a result of the analysis, we derived reasonable express train use/non-use passenger classification points based on 298 origin-destination pairs that satisfied the verification criteria of this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.740-747
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• 2019

In this paper, an antenna applicable to WLAN and WiMAX frequency bands is designed, fabricated, and measured. The proposed antenna is designed to have two branch strip line in the patch plane and a rectangular slit in the ground plane based on microstrip feeding for triple band characteristics and added a vertical strip in the ground plane to enhance impedance bandwidth characteristics. The proposed antenna is designed on a substrate with a relative permittivity of 4.4, a thickness of 1.0 mm, and has a size of $18.0mm(W1){\times}37.3mm$ (L4+L5+L7). From the fabricated and measured results, impedance bandwidths of 480 MHz (2.32 to 2.80 GHz) for 2.4/2.5 GHz band, 810 MHz (3.22 to 4.03 GHz) for 3.5 GHz band, and 1,820 MHz (5.05 to 6.87 GHz) for 5.0 GHz band were obtained based on the impedance bandwidth. Measured 3D pattern and gains are displayed.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.217-226
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• 2018

According to the Korea Coast Guard's maritime disaster statistics (Korea Coast Guard 2017, Korean Statistical information Service 2018), an average of 2,140 marine accidents occurred every year for the past 6 years and the number of accidents is increasing every year. Among them, maritime accidents of fishing vessels are the most frequent, and recently accidents involving fishing boat and leisure vessels are rapidly increasing as well. In particular, the number of accidents involving leisure vessels increased to about one-third of the accidents of fishing vessels, and emergency rescue requests are increasing every year accordingly. However, the number of crash accidents involving users of small vessels and marine leisure activities are increasing because of the difficulties of installing navigation equipment and electronic navigation charts. Recently, the demand for precise positioning using mobile devices is increasing in the fields of maritime safety, piloting support, and coastal survey. Although various applications of smart devices provide location-based services for users, the measurement results are discontinuous when using the position coordinates of the National Marine Electronics Association (NMEA) calculated by smartphone. Recently, Google announced that they will provide GPS raw data to developers from Android 7.0 Nougat. As a result, developers have an opportunity to receive precise carrier phase and code measurements to make more accurate positioning according to the performance of Android devices. This study analyzed GPS positioning performance using Android devices, and compared and analyzed the positioning performance at sea with high-performance GPS receivers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.117-126
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• 2019

The data generated in the IoT environment is very diverse. Especially, the development of the fourth industrial revolution has made it possible to increase the number of fixed and unstructured data generated in manufacturing facilities such as Smart Factory. With Big Data related solutions, it is possible to collect, store, process, analyze and visualize various large volumes of data quickly and accurately. Therefore, in this paper, we will directly generate data using Raspberry Pi used in IoT environment, and analyze using various Big Data solutions. Collected by using an Sqoop solution collected and stored in the database to the HDFS, and the process is to process the data by using the solutions available Hive parallel processing is associated with Hadoop. Finally, the analysis and visualization of the processed data via the R programming will be used universally to end verification.