Titlebook: Resource Management in Wireless Networking; Mihaela Cardei,Ionut Cardei,Ding-Zhu Du Book 2005 Springer-Verlag US 2005 Bluetooth.Performanc

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Fang Liu,Kai Xing,Xiuzhen Cheng,Shmuel Rotenstreichctor, and water aquifer draw-down predictions. Feature engineering presents the opportunity to integrate heterogeneity information, but traditional heterogeneity engineered features like Dykstra-Parsons and Lorenz coefficients ignore the spatial context; therefore, are not sufficient to quantify the

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Eylem Ekicictor, and water aquifer draw-down predictions. Feature engineering presents the opportunity to integrate heterogeneity information, but traditional heterogeneity engineered features like Dykstra-Parsons and Lorenz coefficients ignore the spatial context; therefore, are not sufficient to quantify the

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Imad Jawhar,Jie Wue of geologically-derived training images to reproduce the desired heterogeneity. A variety of different training image types are often proposed for use in MPS modelling, including object-based, surface-based and process-based models. The purpose of the training image is to provide a description of

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Mario Gerla,Kaixin Xuior distributions are then updated into posterior distributions using the nearby hard and soft data. The posterior distributions provide models of uncertainty prevailing at unsampled locations..The Markov-Bayes algorithm for such updating can be seen as a cokriging capitalizing on spatial correlatio

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Dmitri D. Perkins,Ramesh Tumati,Hongyi Wu,Ikhlas Ajbar..These two-point statistics consist of second-order moments that are defined by a variogram. The statistics describe the lateral continuity behaviour of the models. It can be shown that the sequential sampling method correctly generates samples from a probability density function (pdf), when this p

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