• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5B
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• pp.794-800
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• 2010

It is necessary to accurate and efficient management for measured digital data from various sensors in digital marine vessel. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. In this paper, We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose that we arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using SVM algorithm. We automatically delete that it isn't necessary to the data from the database and we used to ship diagnosis system for available data. As a result, we obtained to efficient result about 18.3% reduction rate of database using 35,912 data sets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.95-98
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• 2006

Data collected by sensors in field are transmitted to the base station gathering all of data. Because sensors have to gather data in surroundings and periodically transmit data to the base station, it makes energy consumed much. In this paper, we propose the scheme that is to avoid traffic congestion with achievement of energy efficiency, so collected data is transmitted efficiently. This is to adjust transmission rate differently in case of increasing or decreasing traffic and minimize the energy consumption with setting ideal options up basic CSMA(Carrier Sense Multiple Access) protocol in each sensor. Through the simulation, we find the ideal CSMA options and apply the proposed scheme of traffic control mechanism to them, then show energy efficiency and effective traffic control mechanism.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.11-18
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• 2014

Most of the energy efficient MAC protocols for wireless sensor networks (WSNs) are based on duty cycling in a single channel and show competitive performances in a small number of traffic flows; however, under concurrent multiple flows, they result in significant performance degradation due to contention and collision. We propose a multi-channel pipelining (MCP) method for convergecast WSN in order to address these problems. In MCP, a staggered dynamic phase shift (SDPS) algorithms devised to minimize end-to-end latency by dynamically staggering wake-up schedule of nodes on a multi-hop path. Also, a phase-locking identification (PLI) algorithm is proposed to optimize energy efficiency. Based on these algorithms, multiple flows can be dynamically pipelined in one of multiple channels and successively handled by sink switched to each channel. We present an analytical model to compute the duty cycle and the latency of MCP and validate the model by simulation. Simulation evaluation shows that our proposal is superior to existing protocols: X-MAC and DPS-MAC in terms of duty cycle, end-to-end latency, delivery ratio, and aggregate throughput.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.660-665
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• 1993

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD ( an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very fast training and processing implementation required for real time control.

• Current Optics and Photonics
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• v.4 no.3
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• pp.186-192
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• 2020

This paper describes a real-time monitoring system in Ethernet passive optical networks (EPON) that uses burst-mode fiber Bragg grating (FBG) optical sensors. The FBG interrogation unit in the optical line terminal (OLT) transmits the monitoring wavelength to optical network units (ONUs). The FBG sensor unit in each ONU returns a burst-mode monitoring signal to the OLT. As the system applies time division multiple access (TDMA), a uniform Bragg wavelength can be used to monitor the EPON system. The FBG interrogation unit analyzes the received burst-mode monitoring signals and outputs fault information on the ONU branches in EPON. The simulation results show the effectiveness of the proposed monitoring system based on TDMA. In addition, we compared the proposed TDMA-based monitoring system with a WDMA-based monitoring system.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.1
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• pp.5-9
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• 2003

The waveforms of partial discharges (PDs) imply physical and structural properties of PD sources, so analyzing them give us information on the kind of PD sources and the location. Waveforms of PD as a time series function have variable amplitudes but sustain a certain uniform shape, which shows well the characteristics of the waveforms and frequency region. They can also be used as parameters having time and frequency information of PD signals and applied to classification of multiple PDs sources via Artificial Neural Network with back propagation (BP) learning.

• The KIPS Transactions:PartC
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• v.12C no.7 s.103
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• pp.1031-1038
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• 2005

As the research on home network technologies, sensor network technologies, and ubiquitous network technologies makes rapid progresses, wireless ad-hoc network have attracted a lot of attention. A wireless ad-hoc network is a temporary network formed by a collection of wireless mobile nodes without the aid of my existing network infrastructure or centralized administration, and it is suitable for ubiquitous computing environments. In this paper, we suggest an interconnection scheme between the wireless ad-hoc network environment based on multiple path source routing protocol and a Mobile-IP based network environment. This scheme reduces the overhead of route re-establishment and re-registration by maintaining multiple paths between the mobile host in wireless ad-hoc network and the base station in mobile-IP network. Also it puts the base station in charge of function that performs translation between wireless ad-hoc network packets and Mobile-IP packets, reducing the load of mobile hosts. In this paper, our simulations show that our scheme outperforms existing interconnecting schemes with regards to throughput and end-to-end delay Also we show that our scheme outperforms multi-paths approach using disjoint routes with regards to routing overhead.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9A
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• pp.874-881
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• 2010

Acoustic signal, which is a main carrier of underwater communication, attenuates along the traveled path heavily depending on the frequency as well as inter-node distance. In addition, since it has a long propagation delay, the conventional medium access control (MAC) schemes requiring complex signaling procedures and accordingly heavy overhead messages would not be appropriate in underwater communications. In this paper, we propose a code division multiple access (CDMA) scheme as a solution for MAC of underwater communication and evaluate the performance. A hierarchical data-gathering tree topology is considered and a staggered wake-up pattern is employed for the purpose of energy saving. As a performance measure, the data rate at each level of hierarchical topology is derived.