• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.111-118
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• 2014

In mobile sensor networks, a large number of sensor nodes with battery powered are deployed randomly in a region. They monitor the environmental states and transmit data to its neighboring nodes. For mobile sensor networks, It is needed to maintain the connectivity autonomously among nodes as the sensor node moves. However, the existing works have focused on the energy savings in the fixed sensor networks. A specific algorithm considering node mobility is required in the mobile sensor networks. Along with energy efficiency, the transmission delay should be considered. In this paper, we propose an autonomous configuration scheme and a node scheduling algorithm when a moving node joins into the existing network. Through simulations, we show a superior performance of the proposed algorithm to the existing protocol.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.98-106
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• 2013

The duty-cycle synchronization among mobile sensor nodes with energy-harvesting is very important. The nodes should keep their duty-cycle same to others as much as possible because they have to cooperate each other and to consume energy efficiently. The distribution of node position in network affects not only node connectivity but also the active time of synchronized nodes, and it relates to network life-time finally. In this paper, we introduce a network topology change algorithm (TCA) for energy-harvesting mobile sensor networks based on self-synchronized duty-cycling. The algorithm tries to change a network topology into a balanced topology where the mobile sensor nodes are unified according to the density of the number of nodes. For TCA, both fluid flow algorithm and flock dispersion algorithm are proposed and they are evaluated through the simulation in agent based modeling language. TCA is applied to the energy-harvesting mobile sensor networks to improve the synchronization of duty-cycle and to reduce the variation of energy consumption among nodes.

• Broadcasting and Media Magazine
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• v.25 no.2
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• pp.17-26
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• 2020

최근 스마트폰에서의 증강현실, 미적 효과의 증대(예, 라이브 포커싱) 등의 어플리케이션을 제공하기 위해 모바일 기기에서의 3차원 공간 복원 기술에 대한 관심이 증가하고 있다. 소비자들의 요구에 발 맞춰 최근 스마트폰 제조사는 모든 플래그십 모델에 다중 카메라 및 뎁스 센서(거리 측정 센서)를 탑재하는 추세이다. 본 고에서는 모바일 폰에 탑재되고 있는 대표적인 세 축의 뎁스 추정(공간 복원) 방식에 대해 간단히 살펴보고, 최근 심층학습(Deep learning)의 등장으로 기술 발전의 새로운 국면에 접어 든 다중 시점 매칭(Multi-view stereo) 방법에 대해 소개하고자 한다. 심층 신경망이 재조명 받은 2012년 전까지 주류 연구 방향이었던 전통 기하학 기반의 방법에 대한 소개를 시작으로 심층 신경망기반의 방법론으로의 발전된 형태를 살펴본다. 또한, 신경망기반의 방법론은 크게 3 세대로 나누어 각 세대별 특징에 대해 자세히 살펴보고, 다양한 데이터에 대한 실험 결과를 통해 세대별 공간 복원 결과를 비교 분석한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.321-323
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• 2012

스마트폰 사용의 보편화와 센서기술의 발달로 이를 응용하는 다양한 연구가 진행되고 있다. 특히 가속도, GPS, 조도, 방향센서 등의 센서들이 스마트폰에 부착되어 출시되고 있어서, 이를 이용한 상황인지, 행동인식 등의 관련 연구들이 활발하다. 하지만 다양한 클래스를 분류하면서 높은 인식률을 유지하는 것은 어려운 문제이다. 본 논문에서는 인식률 향상을 위해 계층적 구조의 순환 신경망을 이용하여 제스처를 인식한다. 스마트폰의 가속도 센서를 이용하여 사용자의 제스처 데이터를 수집하고 BLSTM(Bidirectional Long Short-Term Memory) 구조의 순환신경망을 계층적으로 사용하여, 20가지 사용자의 제스처와 비제스처를 분류한다. 약 24,850개의 시퀀스 데이터를 사용하여 실험한 결과, 기존 BLSTM은 평균 89.17%의 인식률을 기록한 반면 계층적 BLSTM은 평균 91.11%의 인식률을 나타내었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.243-248
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• 2013

With rapid growth and fast diffusion of smartphone technologies, many users are deeply concerned about the smart applications and many mobile applications converged with various related technologies are rapidly disseminated. Especially, the convergence technologies like mobile apps that can establish the wireless ad hoc network between smartphone and other peripherals and exchange data are appear and progressed continuously. In this paper, we design and implement the smart app using bluetooth based wireless ad hoc sensor network that can connect smartphone with sensors and exchange data for various smart applications. The proposed smart application in this paper collects data obtained from more than 2 multi-sensors in real time and fulfills the decision making function by storing data at the database and analysing it. The smart application designed and implemented in this paper is the healthcare application that can analyze and evaluate the patient's health condition with sensing data from multi-sensors in real time through bluetooth module.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.1
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• pp.11-14
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• 2015

WSN (Wireless Sensor Network) based on low-power is one of the core technologies in the ubiquitous society. In this paper, we present a border surveillance and control system in WSN environment. The system consists of static sensor node, mobile sensor node, static gateway, mobile gateway, server and mobile application. Mobile applications are divided into user mode and manager mode. So users monitor border surveillance through mobile phone and get information of border network environment without time and space constraints. In manager mode, for the flexible operation of nodes, manager can update to the software remotely and adjust the position of the mobile node. And also we implement a suitable multi-hop routing protocol for scalable low-power sensor nodes and confirm that the system operates well in WSN environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.141-147
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• 2014

With the rapid development of major functions in a smartphone, many applications interacting with a smartphone are introduced and mobile applications converged with various related technologies are announced and rapidly disseminated recently. In this paper, we propose the design of a smart mobile application operated with devices like sensors in order to utilize various functions of the smartphone effectively. The mobile application proposed in this paper uses the bluetooth module of the smartphone, composes the wireless ad hoc network with various sensors around us, and collects bionic context information of the user in real time. The smart application designed and implemented in this paper is the sensor based healthy diet application that can fulfill healthy diet program by reflecting the user's sensed bionic context data in real time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.309-312
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• 2005

본 논문에서는 비젼 시스템과 후각 센서를 이용하여 모바일 로봇의 냄새 발생지 탐색 기능을 구현 하였다. 모바일 로봇에서의 비젼 시스템은 많은 연구가 진행되어진 센싱 방식이지만, 후각 기능은 새롭게 지능 시스템의 센싱 방식으로 주목 받고 있는 추세이다. 이에 본 논문은 이전까지의 연구에서 보여준 임베디드 시스템에서의 가스 센싱 기능 구현을 벗어나 신경망 알고리즘을 이용하여 냄새를 구별 할 수 있는 후각 기능을 구현 하였으며, 비젼 시스템과 후각 센서의 복합적인 알고리즘을 통하여 냄새 발생지를 탐색하는 방법을 제시하였다. 또한 이를 실험하기 위해 AMOR(Autonomous Mobile Olfactory Robot)을 구현하여 남새 발생지 탐색 알고리즘의 효용성을 입증 하였다.

• The KIPS Transactions:PartC
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• v.15C no.5
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• pp.383-390
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• 2008

The mobile sink is most suitable to guarantee the real time processing to events in ubiquitous environment. However it brings many challenges to wireless sensor networks. In particular, the question of how to transfer the collected data to the mobile sink is an important topic in the aspect of effective management of wireless sensor nodes. In this paper, a new data dissemination model is proposed. Since this method uses the home agent and the access node concepts, it provides reliable and efficient data delivery to mobile sink with minimum overhead. In this proposed method, the information of the mobile sink which is constantly moving is informed only to the home agent node and the access node, instead of all sensor nodes. Thus, the collected data from sensor nodes are transferred to the fixed home agent and it sends these data to the mobile sink. Since the confliction phenomenon between data packets in wireless networks could be reduced, the success ratio of data arriving in the mobile sink is highly enhanced. In our experiments, the proposed method reduces the number of broadcast packets so that it saves the amount of energy consumed for transmitting and receiving the data packets. This effect contributes to prolong the lifetime of the wireless sensor networks operated by batteries.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.175-181
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• 2014

With rapid growth of the wireless mobile computing network technologies, various mobile ad hoc network applications converged with other related technologies are rapidly disseminated nowadays. Vehicular Ad Hoc Networks are self-organizing mobile ad hoc networks that typically have moving vehicle nodes with high speeds and maintaining its topology very short with unstable communication links. Therefore, VANETs are very vulnerable for the malicious noise of sensors and anomalies of the nodes in the network system. In this paper, we propose an anomaly detection method by using big data techniques that efficiently identify malicious behaviors or noises of sensors and anomalies of vehicle node activities in these VANETs, and the performance of the proposed scheme is evaluated by a simulation study in terms of anomaly detection rate and false alarm rate for the threshold ${\epsilon}$.