This paper focuses on applying a neural network model to predict pseudorange corrections (PRC) for differential Global Positioning System (DGPS). The class of nonlinear autoregressive recurrent neural networks is chosen as the basic architecture. The neural networks are trained by an unscented Kalman filter due to its powerful capabilities for online parameters estimation. The paper first brief...

Cell-to-cell variability (noise) is an important feature of gene expression that impacts cell fitness and development. The regulatory mechanism of this variability is not fully understood. Here we investigate the effect on gene expression noise in divergent gene pairs (DGPs). We generated reporters driven by divergent promoters, rearranged their gene order, and probed their expressions using ti...

Automatic image measuring is to identify and to measure conjugate points in two or more overlapping photographs automatically. In digital photogrammetry, this process is done by image matching. A straightforward way to make image matching well-posed is to restrict the space of possible solutions and provide good initial parallax. Initial parallax is related to the searching space. The better th...

Position information obtained from standard GPS receivers is known to be corrupted with noise. To make effective use of GPS information in a navigation system it is essential to model this noise and to eliminate its effect. This paper present Parallel Structure Wavelet Based Neural Network (PSWNN) for predicting the Differential GPS (DGPS) corrections. The PSWNN consists of multiple numbers of ...

For many years, real-time DGPS and RTK correction data distribution have been providing GPS users a means to accomplish their tasks with high accuracy positioning in real-time. Dial-up systems over phone line or local area network (LAN) enable users to download data from base stations at remote locations. Radio modems provides wireless communication links between a base station and a rover to e...

Back-Propagation (BP), Extended Kalman Filter (EKF) and Particle Swarm Optimization (PSO) are three of the most widely used algorithms for training feed forward Neural Networks (NNs). This paper presents an accurate DGPS land vehicle navigation system using multi-layered NNs based on the BP, EKF and PSO learning algorithms. The network setup is developed based on mathematical models to avoid ex...

In our study, we analyzed the combined standard uncertainty of water table slope assessment done using differential global positioning system (DGPS)-based measurements of water table elevation and distances between measurement locations. We compared and discussed uncertainties in water table slope assessments done in various hypothetical environments of lowland floodplains (water table slopes t...

Maria Christina Binz-Scharf Harvard University [email protected] Abstract This paper examines knowledge sharing processes in digital government projects (DGPs). Although knowledge sharing processes are a central feature of the functioning of government, they have received little attention in the literature. The importance of knowledge sharing has become even more evident with the rise of...