• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.76-90
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• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.239-246
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• 2017

There are various transversal structures (small dams or drop structures) in median and small streams in Korea. Most of them are concrete structures and it is so hard to exclude low-level water. Unless drainage valves and/or gates would not be installed near bottom of bed, sediment from upstream should be deposited and also contaminants attached to the sediments would devastatingly threaten the water quality and ecosystem. One of countermeasures for such problem is the bypass pipe installed underneath the transversal structure. However, there is still issued whether it would be workable if the gravels and/or stones would roll into and be not excluded. Therefore, in this study, the conditions to exclude the rip stone which enter into the bypass pipe was reviewed. Based on sediment transport phenomenon, the behavior of stones was investigated with the concepts from the critical shear stress of sediment and d'Alembert principle. As final results, the basis condition (${\tau}_c{^*}$) was derived using the Lagrangian description since the stones are in the moving state, not in the stationary state. From hydraulic experiments the relative velocity could be obtained. In order to minimize the scale effect, the extra wide channel of 5.0 m wide and 1.0 m high was constructed and the experimental stones were fully spherical ones. Experimental results showed that the ratio of flow velocity to spherical particle velocity was measured between 0.5 and 0.7, and this result was substituted into the suggested equation to identify the critical condition wether the stones were excluded. Regimes about the exclusion of stone in bypass pipe were divided into three types according to particle Reynolds number ($Re_p$) and dimensionless critical shear force (${\tau}_c{^*}$) - exclusion section, probabilistic exclusion section, no exclusion section. Results from this study would be useful and essential information for bypass pipe design in transveral structures.