• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.49-56
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• 2007

The IEEE 802.15.4 low rate wireless personal area network is a protocol suitable for wireless sensor networks. Thus there has been growing interest in the IEEE 802.15.4 protocol in the home automation networks. This paper proposes a scheduling scheme obtaining optimal parameters regarding the IEEE 802.15.4 frame and subframes in the home automation networks. Guaranteed time slots (GTS) are exploited for the delivery of real-time traffic. Given a set of the requirements for bandwidths and periods assigned to nodes in the network, the beacon interval and the active/inactive subframe duration satisfying the requirements are selected considering the low duty cycle by the proposed scheme. Based on these parameters, analytic results provide the way to efficient use of network resources including energy.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.71-80
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• 2012

In this paper, applications that require low-speed data rate on personal area network to operate the Land Warrior system is proposed. These applications can refer to WSN(wireless sensor network) technology. However, this technology is not suitable to support various data transmission rate. A suitable CSMA/CA algorithm for Land Warrior System in order to solve these existing system problems is proposed. The proposed algorithm is designed to be variable CSMA/CA algorithm parameter, depending on data rate. For the evaluation of Land Warrior system model and CSMA/CA algorithm, we used Castalia. As a result of the simulation, it is found that the proposed system model can not only relieve loads of data processing, but also probability of collision was decreased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4883-4901
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• 2016

Energy efficiency in Wireless Sensor Networks (WSNs) is very appealing research area due to serious constrains on resources like storage, processing, and communication power of the sensor nodes. Due to limited capabilities of sensing nodes, such networks are composed of a large number of nodes. The higher number of nodes increases the overall performance in data collection from environment and transmission of packets among nodes. In such networks the nodes sense data and ultimately forward the information to a Base Station (BS). The main issues in WSNs revolve around energy consumption and delay in relaying of data. A lot of research work has been published in this area of achieving energy efficiency in the network. Various techniques have been proposed to divide such networks; like grid division of network, group based division, clustering, making logical layers of network, variable size clusters or groups and so on. In this paper a new technique of group based WSNs is proposed by using some features from recent published protocols i.e. "Energy-Efficient Multi-level and Distance Aware Clustering (EEMDC)" and "Energy-Efficient Multi-level and Distance Aware Clustering (EEUC)". The proposed work is not only energy-efficient but also minimizes the delay in relaying of data from the sensor nodes to BS. Simulation results show, that it outperforms LEACH protocol by 38%, EEMDC by 10% and EEUC by 13%.

• Journal of IKEEE
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• v.23 no.4
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• pp.1440-1447
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• 2019

Currently, the prevalence of autism spectrum disorders in children is reported to be higher and shows various types of disorders. In particular, they are having difficulty in communication due to communication impairment in the area of social communication and need to be improved through training. Thus, this study proposes a method of acquiring voice information through a microphone mounted on a robot designed through preliminary research and using this information to make intelligent motions. An ANN(Artificial Neural Network) was used to classify the speech data into robot motions, and we tried to improve the accuracy by combining the Recurrent Neural Network based on Convolutional Neural Network. The preprocessing of input speech data was analyzed using MFCC(Mel-Frequency Cepstral Coefficient), and the motion of the robot was estimated using various data normalization and neural network optimization techniques. In addition, the designed ANN showed a high accuracy by conducting an experiment comparing the accuracy with the existing architecture and the method of human intervention. In order to design robot motions with higher accuracy in the future and to apply them in the treatment and education environment of children with autism.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.321-326
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• 2005

근거리 통신망 LAN(Local Area Network)는 일반적으로 회사, 학교, PC방에서 널리 사용하는 통신 방식으로 Serial, USB 통신방식과 더불어 반드시 습득해야 할 프로토콜 중의 하나로서 앞으로는 이러한 LAN 통신방식을 이용하여 모든 가전기기, 회사 내의 보안장치 등이 모두 유무선 복합적으로 연결되어 휴대폰 또는 PDA로 상태변화를 실시간으로 확인이 가능한 시대가 올 것이다. 본 논문에서는 LAN LSI인 W3100A를 분석해 보고, MCU(Atmega128)과 Phycei ver인 RTL8201과 Interface하여 회로를 구성한 다음, TCP Client 역할을 위한 MCU Programming을 하여 .NET으로 Server 프로그램을 만들어 Server에 데이터를 전송한다. 이와 같이 MCU(Atmega128)을 사용하여 들어온 데이터를 Ethernet Network상으로 데이터의 전송을 가능하게 하는 Ethernet 통신 시스템을 연구하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4781-4803
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• 2017

Environmental monitoring systems using Wireless Sensor Networks (WSNs) face the challenge of high power consumption, due to the high levels of multi-hop data communication involved. In order to overcome the issue of fast energy depletion, a proof-of-concept implementation proves that adopting a clustering algorithm in environmental monitoring applications will significantly reduce the total power consumption for environment sensor nodes. In this paper, an energy-efficient WSN-based environmental monitoring system is proposed and implemented, using eight sensor nodes deployed over an area of $1km^2$, which took place in the city of Tabuk in Saudi Arabia. The effectiveness of the proposed environmental monitoring system has been demonstrated through adopting a number of real experimental studies.

• ETRI Journal
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• v.36 no.3
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• pp.374-384
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• 2014

To achieve high-speed (giga-bit) connectivity for short-range wireless multimedia applications, the millimeter-wave (mmWave) wireless personal area networks with directional antennas are gaining increased interest. Due to the use of directional antennas and mmWave communications, the probability of non-interfering transmissions increases in a localized region. Network throughput can be increased immensely by the concurrent time allocation of non-interfering transmissions. The problem of finding optimum time allocation for concurrent transmissions is an NP-hard problem. In this paper, we propose two enhanced versions of previously proposed multi-hop concurrent transmission (MHCT) schemes. To increase network capacity, the proposed schemes efficiently make use of the free holes in the time-allocation map of the MHCT scheme; thus, making it more compact.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.27-33
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• 2020

Backward compatibility is one of the key issues for radio equipment supporting IEEE 802.11, the typical wireless local area networks (WLANs) communication protocol. For a successful packet decoding with the backward compatibility, the frame format detection is a core precondition. This paper presents a novel frame format detection method based on a deep learning procedure for WLANs affiliated with IEEE 802.11. Considering that the detection performance of conventional methods is degraded mainly due to the poor performances in the symbol synchronization and/or channel estimation in low signal-to-noise-ratio environments, we propose a novel detection method based on convolutional neural network (CNN) that replaces the entire conventional detection procedures. The proposed deep learning network provides a robust detection directly from the receive data. Through extensive computer simulations performed in the multipath fading channel environments (modeled by Project IEEE 802.11 Task Group ac), the proposed method exhibits superb improvement in the frame format detection compared to the conventional method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.358-361
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• 2003

As the information and communication technology has been developed, demand for internet and multimedia is increased and customer's needs becomes diverse. Therefore, the convergence of fixed and mobile networks has emerged. Fixed - Mobile Convergence (FMC) service means that it provides users with one type of services from network access to billing regardless of networks and terminal. FMC service is expected to provide an advanced value with both networks providers and users. Wireless local area network (WLAN) and 2.3㎓ HPi are promising services that will generate enormous demands among FMC services. For that reason, this paper investigates the trend of WLAN and HPi in Korea and abroad and suggests future deployment based on reviewing the literature.

• Knowledge Management Research
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• v.16 no.3
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• pp.81-102
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• 2015

With the rapid development of digital media, there has been a huge change in a way of communication, a process of information diffusion and a role of traditional media. Not like mass media, social media enables users to generate and tap into the opinions of a larger world. From that reason, social media is impacting marketing strategies. However, still social media marketing researches just focus on case study, analysis of users motivation or analysis of power user's usage pattern. Word-of-mouth has always been important especially in marketing area. In social media, word-of-mouth depends on each user that's why this research focuses on individual user's activity in SNS. I defined 4 factors (produce, diffusion, network size, activity of network size enlarge) that are effect on activity and verified hypothesis by multiple regression analysis, hierarchical regression analysis and moderated multiple regression.