• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.34-42
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• 2019

Receiving great attention of IoT and 4th industrial revolution, the necessity comes to the fore of the plant system which aims making it smart and effective. Smart Factory is the key realm of IoT to apply with the concept to optimize the entire process and it presents a new and flexible production paradigm based on the collected data from numerous sensors installed in a plant. Especially, the wireless sensor network technology is receiving attention as the key technology of Smart Factory, researches to interface those technology is actively in progress. In addition, IoT devices for plant industry security and high reliable network protocols are under development to cope with high-risk plant facilities. In the meanwhile, Blockchain can support high security and reliability because of the hash and hash algorithm in its core structure and transaction as well as the shared ledger among all nodes and immutability of data. With the reason, this research presents Blockchain as a method to preserve security and reliability of the wireless communication technology. In regard to that, it establishes some of key concepts of the possibility on the blockchain based IoT Edge devices for Plant O&M (Operations and Maintenance), and fulfills performance verification with test devices to present key indicator data such as transaction elapsed time and CPU consumption rate.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.15-21
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• 2019

X-rays with shorter wavelengths than ultraviolet light have very good penetration power. It is convergence in industrial and medical fields has been used a lot. n particular, in the industrial field, various researches have been conducted on the detection of foregin body inside metal that can occur in the production process of products such as metal using x-ray, a non-destructive inspection device. Detectors are becoming increasingly popular for the popularization of DR (Digital Radiography) photography methods that digitally acquire X-ray video images. However, there are cases where foreign body detection is impossible depending on the sensor noise and sensitivity inside the detector. When producing a metal product, since the defective rate of the produced product may increase due to contamination of the foreign body, accurate detection is necessary. In this paper, we provide a correction model for X-ray images acquired in order to improve the efficiency of defect detection such as foreign body inside metal. When applied to defect detection in the production process of metal products through the proposed model, it is expected that the detection of product defects can be processed accurately and quickly.

• Smart Media Journal
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• v.8 no.1
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• pp.43-50
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• 2019

As numerous devices are connected through a wireless network, there exist many studies conducted to efficiently connect the devices. While earlier studies often use clustering for efficient device management, there is a load-intensive cluster node which may lead the entire network to be unstable. In order to solve this problem, we propose a scheduling model for centralized unequal chain clustering for efficient management of sensor nodes. For the cluster configuration, this study is based on the cluster head range and the distance to the base station(BS). The main vector projection technique is used to construct clustering with concentricity where the positions of the base stations are not the same. We utilize a multiple radio access interface, multiple-input multiple-output (MIMO), for data transmission. Experiments show that cluster head energy consumption is reduced and network lifetime is improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.149-155
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• 2019

In this paper, we propose an emergency call system which makes a call to an institution or a guardian when an urgent case occurs to a user based on the indoor location service. In addition, it establishes indoor location service infrastructure assuming welfare institutions and hospitals. The proposed system receives the sensor value from the device that is in the form of a clock on the wrist and determines the emergency situation and delivers emergency information to the terminal. The location terminal transmits location and emergency information to the server, and the server accesses the database and stores the data. This enables the caregiver to communicate with the server through the application, monitor the user's status, receive notifications, and respond to emergency situations by using the emergency call function. If the proposed system is applied to the fields requiring urgent action such as medical field and welfare field, it will provide more stable and prompt emergency service to users and carers.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.145-152
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• 2019

Unlike a single value from a sensor device, a massive data set has characteristics for various processing aspects; input data may be formed in a different format, the size of input data varies, and the processing time of analyzing input data is not predictable. Therefore, context aware systems may contain complex modules, and these modules can be implemented and used in different ways. In order to solve these problems, we propose a method to handle context information from the result of analyzing massive data. The proposed method considers analysis work as a different type of abstracting context and suggests the way of representing context information. In experiment, we demonstrate how the context processing engine works properly in a couple of steps with healthcare services.

• Korean Journal of Materials Research
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• v.29 no.5
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• pp.336-341
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• 2019

The gas adsorption isotherm requires accurate measurement for the analysis of porous materials and is used as an index of surface area, pore distribution, and adsorption amount of gas. Basically, adsorption isotherms of porous materials are measured conventionally at 77K and 87K using liquid nitrogen and liquid argon. The cold volume calibration in this conventional method is done simply by splitting a sample cell into two zones (cold and warm volumes) by controlling the level sensor in a Dewar filled with liquid nitrogen or argon. As a result, BET measurement for textural properties is mainly limited to liquefied gases (i.e. $N_2$ or Ar) at atmospheric pressure. In order to independently investigate other gases (e.g. hydrogen isotopes) at cryogenic temperature, a novel temperature control system in the sample cell is required, and consequently cold volume calibration at various temperatures becomes more important. In this study, a cryocooler system is installed in a commercially available BET device to control the sample cell temperature, and the automated cold volume calibration method of temperature variation is introduced. This developed calibration method presents a reliable and reproducible method of cryogenic measurement for hydrogen isotope separation in porous materials, and also provides large flexibility for evaluating various other gases at various temperature.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.67-73
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• 2018

There are many types of power facilities such as transformers, switches, and energy storage devices in the micro grid environment. However, with the development of IoT technology, opportunities to acquire sensor information such as temperature, pressure, and humidity are provided. In the existing micro grid environment, the communication protocols such as MMS transport protocol in IEC 61850 standard is applied in accordance with the integrated operation between the power facilities and the platform. Therefore, to accommodate IoT data, a gateway technology that can link IoT data to a data collection device (FEP) based on IEC 61850 is required. In this paper, we propose IEC 61850 based IoT gateway platform prototype for microgrid operating system linkage. The gateway platform consists of an IoT protocol interface module (MQTT, CoAP, AMQP) and database, IEC 61850 server. For databases, We used open source based NoSQL databases, Hbase and MongoDB, to store JSON data. We verified the interoperability between the IoT protocol and the IEC 61850 protocol using Sisco's MMS EASY Lite.

• Journal of Fashion Business
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• v.23 no.2
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• pp.156-169
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• 2019

The objective of this study was to develop lightweight, stretchable, tight-fit smart sportswear using the conductive yarns into the garment and demonstrating its usefulness. Sportswears with the ability to control LEDs with respect to lighting of the surrounding were developed by applying embroidery with conductive yarns to 2 types of men's T-shirts and 2 types of women's leggings pants for outdoor activities and exercise purposes. LEDs were applied to the front and back of men's T-shirts and to the rear of the waist of women's leggings. Men's T-shirts were printed where the LEDs were to be applied, and inside, they were embroidered with conductive threads on the hot-melt fabric to be attached, and then connected with LED. Women's pants were embroidered on the elastic band, in the form of a sine wave that gives it ability to stretch, and finally the elastic band was hidden inside the waistband. The operation of the light sensor in the dark provided the ability to protect joggers from night drivers or cyclists. LEDs were activated when the wearer turns on the fashionable device on his/her shoulder by pressing it. It was able to reduce the risk of accidents by giving recognizability to vehicles, bicycles, and athletes approaching or passing by at night, and securing safe distance from vehicles, etc. Internal embroidery technology had the same flexible and lightweight functions as ordinary clothing products, making it possible to apply to tight-fit smart T-shirts or leggings pants designs.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.223-232
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• 2019

With the development of the information communication industry, the size of the communication device has been reduced to a system that generates a large amount of heat. Therefore, since the amount of heat generated by the wireless equipment is large in the wireless base station, the energy consumption is continuously consumed and the failure of the wireless base station may occur. Therefore, in this study, The study was analyzed. As a research method, we performed base station with a lot of calorific value and electric charge. We selected 25 base stations and obtained data for two weeks. To ensure reliability, the room temperature was kept constant at $27^{\circ}C$, and the control system was installed and equiped for two weeks to obtain the date analysis. In order to calculate the test results in the study method, the instrument was used with a computer, a digital thermometer, and dust measurement. For the date analysis, we conducted a research study on 25 wireless basestations before and after the installation of Control Sysetm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.