• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.4
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• pp.175-180
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• 2002

In order to satisfy the requirements of time reduction and cost saving for development of electronic control systems(ECU) in automotive industry, the applications of a standardized real-time operating system(RTOS) and a communication protocol to ECUs are increased. In this study, a body control module(BCM) that employs OSEK/VDX(open system and corresponding interfaces for automotive electronics/vehicle distributed executive) OS tour the RTOS and a controller area network(CAN) fur the communication protocol is designed, and the performances of the system are evaluated. The BCM controls doors, mirrors, and windows of the vehicle through the in-vehicle network. To identify all the transmitted and received control messages, a PC connected with the CAN communication protocol behaves as a CAN bus emulator. The control system based upon in-vehicle network improves the system stability and reduces the number of wiring harness. Furthermore it is easy to maintain and simple to add new features because the system is designed based on the standards of RTOS and communication protocol.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.640-647
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• 2014

The WBAN technology means a short distance wireless network which provides each device's interactive communication by connecting devices inside and outside of body located within 3 meters. It is necessary to develop core technology that the WBAN middleware and application service for WBAN sensor network. A device for gathering patient's biometric information was used zigbex of Hanbaek electronics and we designed the message structure which is collected the biometric information. The gateway design and implementation for the WBAN environment. The embedded system was HBE-empos II of Hanbaek electronics and the WBAN network is implemented to BNC and BN that used for hbe-ubi-zigbex. It was confirmed that the proposed sensor gateway could be used for the interconnection of the proposed system with other networks.

• Smart Media Journal
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• v.4 no.1
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• pp.25-32
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• 2015

Powering wireless sensors with energy harvested from the environment is coming of age due to the increasing power densities of both storage and harvesting devices and the electronics performing energy efficient energy conversion. In order to maximize the functionality of the wireless sensor network, minimize missing packets, minimize latency and prevent the waste of energy, problems like congestion and inefficient energy usage must be addressed. Many sleep-awake protocols and efficient message priority techniques have been developed to properly manage the energy of the nodes and to minimize congestion. For a WSN that is operating in a strictly energy constrained environment, an energy-efficient transmission strategy is necessary. In this paper, we present a novel transmission priority decision scheme for a heterogeneous body sensor network composed of normal nodes and an energy harvesting node that acts as a cluster head. The energy harvesting node's decision whether or not to clear a normal node for sending is based on a set of metrics which includes the energy harvesting node's remaining energy, the total harvested energy, the type of message in a normal node's queue and finally, the implementation context of the wireless sensor network.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.106-114
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• 2015

Wireless Body Area Network(WBAN) is a network standard around a human body which connects various medical sensor and devices It has to satisfy various demands such as data transmission rate, priority, and delay time. In this paper, considering a data priority and transmission delay time, is proposed to improve efficiency of WBAN service depending on congestion status of network. The proposed algorithm operates with adapted data removal probability according to data priority when the hub buffer is congested than before. And in the case of lower congestion within the hub buffer data is served considering data delay time. Through the comparison with other existing scheduling algorithms, it is confirmed that quality of WBAN service is improved due to lower data loss rate of medical data and less delay time in the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1547-1568
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• 2013

Wireless body area network (WBAN) is an emerging short-range wireless communication network with sensor nodes located on, in or around the human body for healthcare, entertainment and ubiquitous computing. In WBANs, energy is severely constrained which is the prime consideration in the medium access control (MAC) protocol design. In this paper, we propose a novel MAC protocol named Energy-efficient Relay MAC with dynamic Power Control (ERPC-MAC) to save energy consumption. Without relying on the additional devices, ERPC-MAC employs relaying nodes to provide relay service for nodes which consume energy fast. Accordingly the superframe adjustment is performed and then the network topology can be smoothly switched from single-hop to multi-hop. Moreover, for further energy saving and reliability improvement, the dynamic power control is introduced to adjust the power level whenever a node transmits its packets to the coordinator or the relaying node. To the best of the authors' knowledge, this is the first effort to integrate relay, topology adjustment and power control to improve the network performance in a WBAN. Comprehensive simulations are conducted to evaluate the performance. The results show that the ERPC-MAC is more superior to the existing standard and significantly prolongs the network lifetime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.294-296
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• 2017

Cloud computing is a computing technique that uploads all the data from a cloud node to a cloud server and provides it to users as a service. This is difficult to provide services in real time depending on the network conditions. This is because it is necessary to download information to the remote site through the network, not the local area, and to download additional services to provide services in the cloud. So fog computing has been proposed as an alternative. In this paper, we propose an efficient data exchange technique between cloud, fog and user. The proposed fog provides services to users and collects and processes data. The cloud is responsible for the flow of data exchange and control between the fog. We propose a standard method for data exchange. The application for this is to process and service the information generated by the BAN (Body Area Network) in the fog, and the cloud serves as a mediator. This can resolve data heterogeneity between devices or services and provide efficient data movement.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1119-1130
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• 2019

With the wide spread of Social Network Services (SNS), fake news-which is a way of disguising false information as legitimate media-has become a big social issue. This paper proposes a deep learning architecture for detecting fake news that is written in Korean. Previous works proposed appropriate fake news detection models for English, but Korean has two issues that cannot apply existing models: Korean can be expressed in shorter sentences than English even with the same meaning; therefore, it is difficult to operate a deep neural network because of the feature scarcity for deep learning. Difficulty in semantic analysis due to morpheme ambiguity. We worked to resolve these issues by implementing a system using various convolutional neural network-based deep learning architectures and "Fasttext" which is a word-embedding model learned by syllable unit. After training and testing its implementation, we could achieve meaningful accuracy for classification of the body and context discrepancies, but the accuracy was low for classification of the headline and body discrepancies.

• International Journal of Advanced Culture Technology
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• v.6 no.1
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• pp.42-49
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• 2018

In this study, we tried to reveal the state of stillness of Cho Ji-Hoon's poem "Silent Night 1" as a healing modifier. The language of poem is synaptically linked to the calmness emotion of the human body, seeking a principle that leads to a state of healing. Therefore, this study was carried out for the purpose of applying the principle to literary therapy program. The silent signal embedded in the poem is encoded into the signals of the sound as it is synapsed to the human body. Encoding of auditory nerves by poem lines is like a Morse code that word and word leave in the human body. The action potential of the auditory nerve is further activated by the potential difference between the word and the word represented by the neural network, such as a Morse code, which is accessed to the human body by such a path. There is worked as amplified potential difference between the words perceived by a sound which is synapsed to the human body and by a silence which is synapsed to the human body. The phenomenon of the words approaching the human body and setting the absence of sound and amplifying the sound is because the words amplifies the Morse codes in the human neural network. At this time, the signals overlap each other. Thereby this poem is increasing the amplitude of the sound. This overlapping of auditory signals appears and amplifies the catharsis. If this Cho Ji-Hoon Poem's principle is applied to literary therapy program in the future, more effective treatment will be done.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.39-46
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• 2006

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.110-116
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• 2023

Recently, as various examples of machine learning have been applied in the healthcare field, deep learning technology has been applied to various tasks, such as electrocardiogram examination and body composition analysis using wearable devices such as smart watches. To utilize deep learning, securing data is the most important procedure, where human intervention, such as data classification, is required. In this study, we propose a model that uses a clustering algorithm, namely, the K-means clustering, to label body fat according to gender and age considering body size aspects, such as chest circumference and waist circumference, and classifies body fat into five groups from high risk to low risk using a convolutional neural network (CNN). As a result of model validation, accuracy, precision, and recall results of more than 95% were obtained. Thus, rational decision making can be made in the field of healthcare or obesity analysis using the proposed method.