The global positioning system (GPS) allows properly equipped users to determine their position based on the measured pseudoranges to at least four satellites. Differential GPS operation (DGPS) uses a reference station at a known location to calculate and broadcast pseudorange corrections to local users, resulting in improved user position accuracy. DGPS accuracy is limited by the ability of the...

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 digital government initiatives, as these have a networking effect on bureaucraci...

if both reference station (rs) and navigational device in differential global positioning system (dgps) receive signals from the same satellite, rs position components error (rpce) can be used to compensate for navigational device error. this research used hybrid method for rpce prediction which was collected by a low-cost gps receiver. it is a combination of genetic algorithm (ga) computing an...

Neural Networks (NNs) are capable of learning high complex, nonlinear input-output mappings. This characteristic of NNs enables them to be used in nonlinear system modeling and prediction applications. On the other hand, the wavelet decomposition provides a powerful tool for functional approximation. In this paper, a kind of Wavelet Neural Networks (WNNs) is proposed for Differential GPS (DGPS)...

Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Fun...

Recent developments in differential GPS (DGPS) services have concentrated mainly on the reduction of the number of permanent reference stations required to cover a certain area and the extension of the possible ranges between reference and rover stations. Starting from networked DGPS stations where all stations are linked to a central control station for data correction and modeling, the most a...

This paper presents an industrial application concerning the real time trajectory tracking of an autonomous heavy vehicle (up to 7000 kg) for material handling in industrial environment. Material handling in indoor environment has been successfully developed with navigation based on LIDAR system. In outdoor environment this solution is not reliable due to fog and rain disturbances. In this work...

Divergent gene pairs (DGPs) are abundant in eukaryotic genomes. Since two genes in a DGP potentially share the same regulatory sequence, one might expect that they should be co-regulated. However, an inspection of yeast DGPs containing cell-cycle or stress response genes revealed that most DGPs are differentially-regulated. The mechanism underlying DGP differential regulation is not understood....

This paper proposes the minimization of α-divergences for approximate inference in context deep Gaussian processes (DGPs). The proposed method can be considered as a generalization variational (VI) and expectation propagation (EP), two previously used methods DGPs. Both VI EP are based on Kullback-Leibler divergence. is scalable version power propagation, that introduces an extra parameter α sp...