• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1419-1436
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• 2020

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.477-483
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• 2011

In this paper, we propose the design and implementation of the storage-based data sharing system in the separate network environment to improve efficiency of data transmission. The previous system generates files per received packet and transmit files to another network through storage. This system causes inefficiency by reading unnecessary blocks, when it transmits a number of files through storage. Our proposed system deals with this inefficiency by adopting concept of snapshot. Consequently, we create one file with snapshot so that the number of files can be reduced and the file size can be optimized according to the block size. The proposed system improves the response time significantly with the minimized reading of unnecessary blocks, compared to the previous system.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1182-1194
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• 2018

The Dynamic Adaptive Streaming over HTTP(DASH) is envisioned to evolve to meet an increasing demand on providing seamless video streaming services in the near future. The DASH performance heavily depends on the client's adaptive quality selection algorithm that is not included in the standard. The existing conventional algorithms are basically based on a procedural algorithm that is not easy to capture and reflect all variations of dynamic network and traffic conditions in a variety of network environments. To solve this problem, this paper proposes a novel quality selection mechanism based on the Deep Q-Network(DQN) model, the DQN-based DASH Adaptive Bitrate(ABR) mechanism. The proposed mechanism adopts a new reward calculation method based on five major performance metrics to reflect the current conditions of networks and devices in real time. In addition, the size of the consecutive video segment to be downloaded is also considered as a major learning metric to reflect a variety of video encodings. Experimental results show that the proposed mechanism quickly selects a suitable video quality even in high error rate environments, significantly reducing frequency of quality changes compared to the existing algorithm and simultaneously improving average video quality during video playback.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.284-292
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• 2013

A stable procedure is presented to attain most probable and unbiased estimate of principal strain, rotation, and dilatation for 2-dimensional geodetic data on triangular network. The proper network size should be chosen carefully, because the errors of these estimates of strain tensor and other associated observables grow inversely proportional to the area of station triangle. As a case study, the deformation observables for the GPS-monitored co-seismic displacement in Korea due to the 2011 Tohoku-Oki earthquake were attained accordingly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.93-100
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• 2014

IEEE 802.11 Wireless LAN Medium Access Control(MAC) supports two transmission methods, a DCF basic and a RTS/CTS in contention-based access. Even though the RTS/CTS method has been optionally introduced to solve the hidden terminal problem, it is able to produce better performance in some network environments than the basic transmission method. In this paper, the collision probability of wireless channel is mathematically analyzed and applied to measure network throughput using real transmission parameters so that a reference value between throughputs of two methods is obtained. We also confirmed that control signal rates affect overall network throughput and evaluated network throughputs considering collision probability, number of stations, and contention window size of Backoff between two methods respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.2
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• pp.178-183
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• 2001

Welding is essential for the manufacture of a range of engineering components which may vary from very large structures such as ships and bridges to very complex structures such as aircraft engines, or miniature components for microelectronic applications. Especially, a domestic situation of the welding automation is still depend on the arc sensing system in comparison to the vision sensing system. Specially, the gap-detecting of workpiece using conventional arc sensor is proposed in this study. As a same principle, a welding current varies with the size of a welding gap. This study introduce to the fuzzy membership filter to cancel a high frequency noise of welding current, and ART2 which has the competitive learning network classifies the signal patterns the filtered welding signal. A welding current possesses a specific pattern according to the existence or the size of a welding gap. These specific patterns result in different classification in comparison with an occasion for no welding gap. The patterns in each case of 1mm, 2mm, 3mm and no welding gap are identified by the artificial neural network.

• Journal of the Korean Ceramic Society
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• v.43 no.4 s.287
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• pp.199-202
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• 2006

In this study, SiC whiskers were grown on a porous SiC diesel particulate filter for nanoparticle filtering. To grow the whiskers at the inner pore without closing the pores, we used chemical vapor infiltration with a solution source and a dilute. As the deposition time increased, the whiskers grew and formed a network structure. After 180 min of deposition, the mean diameter of the whiskers was 174 nm and the compressive strength was 58.4 MPa. The pores shrank from $10{\mu}m\;to\;0.4{\mu}m$ and, because the whiskers filed the inner pores, the gradient of permeability decreased as the deposition time increased. However, by using the network structure of whiskers deposited for 120 min and 180 min, we obtained a diesel particulate filter with pores of $0.98{\mu}m\;and\;0.4{\mu}m$, respectively. Furthermore, the filter shows better permeability than a porous body with pores of $1{\mu}m$. In short, by filtering the nanoparticulate materials, the network structure of whiskers improves the strength, reduces the pore size and minimizes the permeability drop.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.937-942
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• 2003

In this paper, we measured and examined RTT delays and packet losses according to the changes of stationary loads for two typical stream-type traffics, a DV and a MPGE2 on the R＆D Gigabit Network testbed, JGN. As the result of our actual measurements, we realized that the packet size of stationary load have no effects on a DV and a MPGE2 stream on the very high-speed network(50Mbps, IP over ATM). When its bandwidth and stationary load exceeds 95％ of network bandwidth, packet losses appeared and RTT delay increased rapidly. Also we realized that the number and size of Receive ＆ Transmit buffer on the end systems have no effects on packet losses and RTT delays.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.117-139
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• 1999

This paper is concerned about the hybrid tandem configuration as the design of the automated guided vehicle system(AGVs). The hybrid tandem configuration is that the manufacturing system is divided into several non-overlapping zones, workstations of each zone are linked by network configuration including loop. That is, the manufacturing system is divided into several non-overlapping small size networks, and at most two automated guided vehicles can be available in each network. The transit point is located at proper point between adjacent networks. The parts are transported to workstations in other network through the transit points. One of the objective functions in dividing into the hybrid tandem configuration is to minimize the maximum travel time of the divided networks, and other is to minimize the total travel distance of parts moved to workstations in other networks for the next processing. The model formulation is presented, and a numerical example is shown. Also, the performances of system for the hybrid tandem, tandem and network configuration are compared through the simulation. The results of this research will contribute to the development of material handling systems in the manufacturing system. Also, it will be applied in determining the transportation area of transportation vehicles and the number and size of the transportation fleet in the transportation problem of logistics management.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.527-531
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• 1998

This study introduce to the fuzzy membership filter to cancel a high frequency noise of welding current. And ART2 which has the competitive learning network classifiers the signal patterns for the filtered welding signal. A welding current possesses a specific pattern according to the existence or the size of a welding gap. These specific patterns result in different classification in comparison with an occasion for no welding gap. The patterns In each case of 1mm, 2mm, 3mm, and no welding gap are identified by the artificial neural network. These procedure is an off-line execution. In on-line execution, the identification model of neural network for the classified pattern is located on ahead of the welding plant. And when the welding current patterns pass through the neural network in the direction of feedforward. it is possible to recognize the existence or the size of a welding gap.