• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.23-28
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• 2023

In a wireless smart utility network communication system, an asynchronous low power MAC is standardized and used according to IEEE 802.15.4e. An asynchronous MAC called RIT (Receiver Initiated Transmission) has a characteristic in which delay time and power consumption are greatly affected by a check-in interval (RIT period). By waking up from sleep every check-in interval and checking whether there is data to be received, power consumption in the receiving end can be drastically reduced, but power consumption in the transmitting end occurs due to an excessive wakeup sequence. If an excessive wake-up sequence is reduced by shortening the check interval, power consumption of the receiving end increases due to too frequent wake-up. In the RIT asynchronous MAC technique, power consumption performance according to traffic load and operation of check-in interval is analyzed and applied to Wi-SUN construction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.787-790
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• 2015

Recently, M2M (Machine to Machine) communication is possible the development of MTC (Machine Type Communication) devices becomes active. MCT devices in the form of home appliances have a low power consumption, low cost, short-range wireless communication in wireless home network. For purpose, MTC devices based on IEEE 802.15.4/Zigbee are composed in the form of cluster-tree topology, which consists of one PAN (Personal Area Network), one or other router and end of nodes. It happens that transmission delay, packet drop, and lacking data resulted from collision originated by a competition for allocating channels among MTC devices that greatly increased. At last performance of entire network can be degradated. This paper proposes that the beacon frame-based grouping algorithm using multiple channels in a MTC devices in the presence of wireless home network interference. The proposed algorithm decreases the transmission delay, dropped packet and throughput is more increase, so the proposal algorithm is more efficient than the IEEE 802.15.4/ Zigbee standard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1575-1583
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• 2008

Wireless sensor network has merit of low-power, low-cost and self-organization network, so there are many researches substituted for existing wire network. As structure reinforcement work need a high accuracy, many sensors are installed in structure and connected with data logger for monitoring. However this wire data logger method takes a long time to install wires and installed wires obstruct to work. Additionally, wire data logger method represent sensor data by only numeric and graph, it is not able to support a rapid decision-making for working. To resolve wiring problem and support decision-making, we designed and implemented the monitoring system based in wireless sensor network. For verifying performance, accuracy and availability, we simulated and tested our system in real field. Consequently, wireless sensor network method is easier to install and deploy than wire data logger method, user is able to monitor instinctively and overall by 3D representation of structure and sensors, and it show not only accuracy but also performance for many sensors.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.378-390
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• 2022

With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

• Smart Media Journal
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• v.12 no.11
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• pp.185-197
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• 2023

This study was conducted using text mining and network theory to extract useful information for application for occupancy and performance of permit tasks contained in the permit contents from the permit register, which is used only for the simple purpose of recording occupancy permit information. Based on text mining, we analyzed and compared the frequency of vocabulary occurrence and topic modeling in five regions, including Seoul, Gyeonggi, Gyeongsang, Jeolla, Chungcheong, and Gangwon, as well as normalization processes such as stopword removal and morpheme analysis. By applying four types of centrality algorithms, including stage, proximity, mediation, and eigenvector, which are widely used in network theory, we looked at keywords that are in a central position or act as an intermediary in the network. Through a comprehensive analysis of vocabulary appearance frequency, topic modeling, and network centrality, it was found that the 'installation' keyword was the most influential in all regions. This is believed to be the result of the Ministry of Environment's permit management office issuing many permits for constructing facilities or installing structures. In addition, it was found that keywords related to road facilities, flood control facilities, underground facilities, power/communication facilities, sports/park facilities, etc. were at a central position or played a role as an intermediary in topic modeling and networks. Most of the keywords appeared to have a Zipf's law statistical distribution with low frequency of occurrence and low distribution ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.578-585
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• 2012

Location tracking system through GPS and Wi-Fi is available at no additional cost in an environment of IEEE 802.11-based wireless network. It is useful for many applications in outdoor environment. However, a previous systems used for general device to tag. It is unsuitable for power aware location tracking system because general devices is more expensive and non-optimized for tracking. The hand-off method of IEEE 802.11 standard is not enough considering power consumption. This thesis analyzes the previous location tracking systems and proposes power aware system. First, we designed and implemented tag to optimize location tracking. Next, we propose low-power hand-off method and low-power behavior model in implemented tag. The proposed hand-off method resolve power problem by using the location information and behavior model minimize power consumption of tag through power-saving mode and the concept of duty cycle. To evaluating proposed methods and system performance, we perform simulations and experiments in real environment. And then, we calculate tag's power consumption based on the actual measured current consumption of each operation. In a simulation result, the proposed behavior model and hand-off method reduced about 98%, 59% than the standard's hand-off and default behavior model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.900-905
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• 2016

The field of power system harmonics has been receiving a great deal of attention recently. This is primarily due to the fact that non-linear (or harmonic-producing) loads comprise an ever-increasing portion of what is handled at a typical industrial plant. The incidence rate of harmonic-related problems is low, but awareness of harmonic issues can still help increase offshore power plant system reliability. On the rare occasion that harmonics become a problem, this is either due to the magnitude of harmonics produced or power system resonance. This harmonic study used an electrical configuration for the offloading scenario of a Floating LNG (FLNG) unit, considering power load. This electrical network configuration is visible in the electrical network load flow study part of the project. This study has been carried out to evaluate the performance of an electric power system, focusing on the harmonic efficiency of an electrically driven motor system to ensure offshore plant safety. In addition, the design part of this study analyzed the electric power system of an FLNG unit to improve the safety of operation and maintenance.

• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.334-339
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• 2015

Terabit-per-second (Tb/s) transmission capacity for the next generation of long-haul communication networks can be achieved using multicarrier optical super-channel technology. In an elastic orthogonal frequency division multiplexing (OFDM) super-channel transmission system, demultiplexing a portion of an entire spectrum in the form of a subband with minimum power is critically required. A major obstacle to achieving this goal is the analog-to-digital converter (ADC), which is power-hungry and extremely expensive. Without a proper ADC that can work with low power, it is unrealistic to design a 100G coherent receiver suitable for a commercially deployable optical network. Discrete Fourier transform (DFT) is often seen as a primary technique for understanding partial demultiplexing, which can be attained either optically or electronically. If fairly comparable performance can be achieved with an all-optical DFT circuit, then a solution independent of data rate and modulation format can be obtained. In this paper, we investigate two distinct OFDM super-channel receiver models, based on electronic and all-optical DFT-technologies, for partial carrier demultiplexing in a multi-Tb/s transmission system. The performance comparison of the receivers is discussed in terms of bit-error-rate (BER) performance.

• Smart Structures and Systems
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• v.22 no.5
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• pp.509-525
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• 2018

Sensors and systems in Civionics technology play an important role for continuously facilitating real-time structure monitoring systems by detecting and locating damage to or degradation of structures. An advanced materials, design processes, long-term sensing ability of sensors, electromagnetic interference, sensor placement techniques, data acquisition and computation, temperature, harsh environments, and energy consumption are important issues related to sensors for structural health monitoring (SHM). This paper provides a comprehensive survey of various sensor technologies, sensor classes and sensor networks in Civionics research for existing SHM systems. The detailed classification of sensor categories, applications, networking features, ranges, sizes and energy consumptions are investigated, summarized, and tabulated along with corresponding key references. The current challenges facing typical sensors in Civionics research are illustrated with a brief discussion on the progress of SHM in future applications. The purpose of this review is to discuss all the types of sensors and systems used in SHM research to provide a sufficient background on the challenges and problems in optimizing design techniques and understanding infrastructure performance, behavior and current condition. It is observed that the most important factors determining the quality of sensors and systems and their reliability are the long-term sensing ability, data rate, types of processors, size, power consumption, operation frequency, etc. This review will hopefully lead to increased efforts toward the development of low-powered, highly efficient, high data rate, reliable sensors and systems for SHM.

• The KSFM Journal of Fluid Machinery
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• v.5 no.4 s.17
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• pp.47-53
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• 2002

The steam generator feedwater flow-rate in a nuclear power plant was estimated by means of artificial neural networks with the wavelet analysis for enhanced information extraction. The fouling of venturi meters, used for steam generator feedwater flow-rate in pressurized water reactors, may result in unnecessary plant power derating. The back-propagation network was used to generate models of signals for a pressurized water reactor Multiple-input, single-output hetero-associative networks were used for evaluating the feedwater flow rate as a function of a set of related variables. The wavelet was used as a low pass filter eliminating the noise from the raw signals. The results have shown that possible fouling of venturi can be detected by neural networks, and the feedwater flow-rate can be predicted as an alternative to existing methods. The research has also indicated that the decomposition of signals by wavelet transform is a powerful approach to signal analysis for denoising.