• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.225-232
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• 2013

In this paper, we introduce a method that can be used to select the position of head node for context-awareness information. The validity of the head node optimal location is saving the energy in the path according to the clustering. It is important how to elect one of the relay node for energy efficiency routing. Existing LEACH algorithm to elect the head node when the node's energy probability distribution function based on the management of the head node is optional cycle. However, in this case, the distance of the relay node status information including context-awareness parameters does not reflect. These factors are not suitable for the relay node or nodes are included in the probability distribution during the head node selects occurs. In particular, to solve the problems from the LEACH-based hierarchical clustering algorithms, this study defines location with the status context information and the residual energy factor in choosing topology of the structure adjacent nodes. The proposed ECOPS (Energy Conserving Optimal path Schedule) algorithm that contextual information is contributed for head node selection in topology protocols. This proposed algorithm has the head node replacement situations from the candidate head node in the optimal path and efficient energy conservation that is the path of the member nodes. The new head node election technique show improving the entire node lifetime and network in management the network from simulation results.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.249-264
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• 2019

In this study, the precise orbit determination (POD) software is developed for optical observation. To improve the performance of the estimation algorithm, a nonlinear batch filter, based on the unscented transform (UT) that overcomes the disadvantages of the least-squares (LS) batch filter, is utilized. The LS and UT batch filter algorithms are verified through numerical simulation analysis using artificial optical measurements. We use the real optical observation data of a low Earth orbit (LEO) satellite, Cryosat-2, observed from optical wide-field patrol network (OWL-Net), to verify the performance of the POD software developed. The effects of light travel time, annual aberration, and diurnal aberration are considered as error models to correct OWL-Net data. As a result of POD, measurement residual and estimated state vector of the LS batch filter converge to the local minimum when the initial orbit error is large or the initial covariance matrix is smaller than the initial error level. However, UT batch filter converges to the global minimum, irrespective of the initial orbit error and the initial covariance matrix.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.4
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• pp.459-468
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• 2015

Deposits discharged through the cleaning mainly were cement mortar, bitumen paintings and rust pieces, and fragments of perforation, stones and gravels. Deposits were more removed through swabbing pig cleaning rather than air scouring cleaning on the whole. However, air scouring cleaning were not influenced by the constraint conditions such as a change in the diameter or the presence of the valve in water mains compare to swabbing pig cleaning. So, it was thought that air scouring cleaning might be more favorable to water distribution network cleaning in the future. After the cleaning, water quality including residual chlorine and turbidity also was improved because of the removal of a significant amount of the deposits. Therefore, if the cleaning is continuously and regularly implemented in water mains, it is expected that it will help to recover the reliability and to preserve the health of water quality.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.167-183
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• 2013

Methods for estimating structural reliability using probability ideas are well established. When the residual ultimate strength of a buried pipeline is exceeded the limit, breakage becomes imminent and the overall reliability of the pipe distribution network is reduced. This paper is concerned with estimating structural failure of underground flexible pipes due to corrosion induced excessive deflection, buckling, wall thrust and bending stress subject to externally applied loading. With changes of pipe wall thickness due to corrosion, the moment of inertia and the cross-sectional area of pipe wall are directly changed with time. Consequently, the chance of survival or the reliability of the pipe material is decreased over time. One numerical example has been presented for a buried steel pipe to predict the probability of failure using Hasofer-Lind and Rackwitz-Fiessler algorithm and Monte Carlo simulation. Then the parametric study and sensitivity analysis have been conducted on the reliability of pipeline with different influencing factors, e.g. pipe thickness, diameter, backfill height etc.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2654-2663
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• 2000

Steam turbine rotors are the most critical and highly stressed components of a steam power plant; therefore, the life expectancy of the turbine rotor is an important consideration for the safety of a steam power plant. The objective of this paper is to develop a life estimation program for turbine rotors for all possible operating conditions. For this purpose, finite element analysis was carried out for four normal operating modes (cold, warm, hot and very hot starts) using ABAQUS codes. The results are made into databases to evaluate the life expenditure for an actual operating condition. For any other possible abnormal operating condition, the operating data are transmitted to the server (workstation) through a network to carry out finite element analysis. Damage estimation is carried out by transmitting the finite element analysis results to the personal computer, and then the life expectancy is calculated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5729-5744
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• 2017

Vehicular Ad Hoc Networks (VANET) in the large-scale road section usually have typical characteristics of large number of vehicles and unevenly distribution over geographic spaces. These two inherent characteristics lead to the unsatisfactory performance of VANETs. This poor performance is mainly due to fragile communication link and low dissemination efficiency. We propose a novel routing mechanism to address the issue in the paper, which includes a competition-based routing discovery with priority metrics and a local routing repair strategy. In the routing discovery stage, the algorithm uses adaptive scheme to select a stable route by the priorities of routing metrics, which are the length of each hop, as well as the residual lifetime of each link. Comparisons of different ratios over link length and link stability further show outstanding improvements. In the routing repair process, upstream and downstream nodes also compete for the right to establish repair process and to remain as a member of the active route after repair. Our simulation results confirm the improved performance of the proposed algorithm.

• Journal of Contemporary Eastern Asia
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• v.13 no.2
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• pp.41-56
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• 2014

This research paper advances our understanding of complex interdependence among countries. Existing research has found that total factor productivity (TFP), the residual from the economic growth function, is hindered in the absence of a country's strong political and legal institutions or if a country does not already have a sufficiently high level of TFP. We also know that regional efforts to eliminate pollution are complex. Bridging these two areas while focusing on a high polluting yet high innovating region, the following research questions are posed: Are Northeast Asian countries key collaborators in pursuit of green R&D? Are Northeast Asian countries collaborating extensively with each other? What are the implications for other regions' attempts to establish these kinds of relations? To answer the above questions, biofuels-related technology as defined in the International Patent Classification's "green inventory" of environmentally sound technologies is examined. Patent data is drawn from the USPTO and inventors' country origin as the unit of analysis. For the 1990-2013 period, the Northeast Asian countries are in the core of a small set of collaborating countries. There is evidence that their centrality has increased in recent years. Most importantly, East Asia is becoming a singular research hub in terms of biofuels-related R&D, offering a counter in the foreseeable future to the dominance of the American and European research network hubs.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.8-13
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• 2012

In this paper, we investigate cooperative spectrum sensing scheme for sensor network-aided cognitive radio systems with energy harvesting capability. In the proposed model, each sensor node harvests ambient energy from environment such as solar, wind, mechanical vibration, or thermoelectric effect. We propose adaptive cooperative spectrum sensing scheme in which each sensor node adaptively carries out energy detection depending on the residual energy in its energy storage and then conveys the sensing result to the fusion center. From simulation results, we show that the proposed scheme minimizes the false alarm probability for given target detection probability by adjusting the number of samples for energy detector.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.4
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• pp.243-249
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• 2016

Energy-harvesting nodes in wireless sensor networks(WSNs) can be exhausted due to a heavy workload even though they can harvest energy from their environment. On contrast, they can sometimes fully charged, thus waste the harvested energy due to the limited battery-capacity. In order to utilize the harvested energy efficiently, we introduce a selective data compression and transmission range control scheme for energy-harvesting nodes. In this scheme, if the residual energy of a node is expected to run over the battery capacity, the node spends the surplus energy to exploit the data compression or the transmission range expansion; these operations can reduce the burden of intermediate nodes at the expanse of its own energy. Otherwise, the node performs only basic operations such as sensing or transmitting so as to avoid its blackout time. Simulation result verifies that the proposed scheme gathers more data with fewer number of blackout nodes than other schemes by consuming energy efficiently.