• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1544-1553
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• 2017

The network coding mechanism has attracted much attention because of its advantage of enhanced network throughput which is a desirable characteristic especially in a multi-hop wireless network with limited link capacity such as the device-to-device (D2D) communication network of 5G. COPE proposes to use the XOR-based network coding in the two-hop wireless network topology. For multi-hop wireless networks, the Distributed Coding-Aware Routing (DCAR) mechanism was proposed, in which the coding conditions for two flows intersecting at an intermediate node are defined and the routing metric to improve the coding opportunity by preferring those routes with longer queues is designed. Because the routes with longer queues may increase the delay, DCAR is inefficient in delivering real-time multimedia traffic flows. In this paper, we propose a network coding-aware routing protocol for multi-hop wireless networks that enhances DCAR by considering traffic load distribution and link quality. From this, we can achieve higher network throughput and lower end-to-end delay at the same time for the proper delivery of time-sensitive data flow. The Qualnet-based simulation results show that our proposed scheme outperforms DCAR in terms of throughput and delay.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.1
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• pp.8-13
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• 2006

In mobile ad hoc networks, most of on demand routing protocols such as DSR and AODV do not deal with traffic load during the route discovery procedure. To achieve load balancing in networks, many protocols have been proposed. However, existing load balancing schemes do not consider the remaining available buffer size of the interface queue, which still results in buffer overflows by congestion in a certain node which has the least available buffer size in the route. To solve this problem, we propose a load balancing protocol called Dynamic Congestion Aware Routing Protocol (DCAR) which monitors the remaining buffer length of all nodes in routes and excludes a certain congested node during the route discovery procedure. We also propose two buffer threshold values to select an optimal route selection metric between the traffic load and the minimum hop count. Through simulation study, we compare DCAR with other on demand routing protocols and show that the proposed protocol is more efficient when a network is heavily loaded.

• Progress in Medical Physics
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• v.16 no.4
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• pp.166-175
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• 2005

The purpose of this study is to develop the optimization method for adjusting the film isocenter shift and to suggest the quantitative acceptable criteria for film dosimetry after optimization In the dynamic conformal arc radiation therapy (DCAR). The DCAR planning was peformed In 7 patients with brain metastasis. Both absolute dosimetry with ion chamber and relative film dosimetry were peformed throughout the DCAR using BrainLab's micro-multileaf collimator. An optimization method for obtaining the global minimum was used to adjust for the error in the film isocenter shift, which is the largest pan of systemic errors. The mean of point dose difference between measured value using ion chamber and calculated value acquired from planning system was $0.51{\pm}0.43\%$ and maximum was $1.14\%$ with absolute dosimetry These results were within the AAPM criteria of below $5\%$. The translation values of film isocenter shift with optimization were within ${\pm}$1 mm in all patients. The mean of average dose difference before and after optimization was $1.70{\pm}0.35\%$ and $1.34{\pm}0.20\%$, respectively, and the mean ratios over $5\%$ dose difference was $4.54{\pm}3.94\%$ and $0.11{\pm}0.12\%$, respectively. After optimization, the dose differences decreased dramatically and a ratio over $5\%$ dose difference and average dose difference was less than $2\%$. This optimization method is effective in adjusting the error of the film isocenter shift, which Is the largest part of systemic errors, and the results of this research suggested the quantitative acceptable criteria could be accurate and useful in clinical application of dosimetric verification using film dosimetry as follows; film isocenter shift with optimization should be within ${\pm}$1 mm, and a ratio over $5\%$ dose difference and average dose difference were less than $2\%$.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.835-847
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• 2016

To analyze lattice or areal data, a conditionally autoregressive (CAR) model has been widely used in the eld of spatial analysis. The spatial neighborhoods within CAR model are generally formed using only inter-distance or boundaries between regions. Kyung and Ghosh (2010) proposed a new class of models to accommodate spatial variations that may depend on directions. The proposed model, a directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Properties of maximum likelihood estimators of a Gaussian DCAR are discussed. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1133-1146
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• 2016

Counts or averages over arbitrary regions are often analyzed using conditionally autoregressive (CAR) models. The spatial neighborhoods within CAR model are generally formed using only the inter-distance or boundaries between the sub-regions. Kyung and Ghosh (2009) proposed a new class of models to accommodate spatial variations that may depend on directions, using different weights given to neighbors in different directions. The proposed model, directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Bayesian inference method is discussed based on efficient Markov chain Monte Carlo (MCMC) sampling of the posterior distributions of the parameters. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.