Performance evaluation of GNSS receiver clock modelling in urban navigation using geodetic and high-sensitivity receivers

In urban areas, the Global Navigation Satellite System (GNSS) can lead to position errors of tens of meters due to signal obstruction and severe multipath effects. In cases of 3D-positioning, the vertical coordinate is estimated less accurately than are the horizontal coordinates. Multisensor systems can enhance navigation performance in terms of accuracy, availability, continuity and integrity. However, the addition of multiple sensors increases the system cost, and thereby the applicability to low-cost applications is limited. By using the concept of receiver clock modelling (RCM), the position estimation can be made more robust; the use of high-sensitivity (HS) GNSS receivers can improve the system availability and continuity. This paper investigates the integration of a low-cost HS GNSS receiver with an external clock in urban conditions; subsequently, the gain in the navigation performance is evaluated. GNSS kinematic data is recorded in an urban environment with multiple geodetic-grade and HS receivers. The external clock stability information is incorporated through the process noise matrix in a Kalman filter when estimating the position, velocity and time states. Results shows that the improvement in the precision of the height component and vertical velocity with both receivers is about 70% with RCM compared with the estimates obtained without applying RCM. Pertaining accuracy, the improvement in height with RCM is found to be about 70% and 50% with geodetic and HS receivers, respectively. In terms of availability, the HS receiver delivers an 100% output compared with a geodetic receiver, which provides an output 99⋅4% of the total experiment duration. Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of The Royal Institute of Navigation.

Improving skills in rounding off the whole number

This study was conducted to address teaching and learning skills in rounding off a whole number. This study consisted of 15 years 4 students from the Kong Nan Chinese Primary School, Parit Raja, Johor, Malaysia. Initial survey to identify this problem was carried out by analyzing the exercise books and exercises in pre-test. Based on these analyses, a large number of students were not proficient in relevant skills. A ‘q’ technique was introduced as an approach in teaching and learning to help students master the skills of rounding whole numbers. In summary, this technique helps students to remember the sequence of processes and process in rounding numbers. A total of four sessions of teaching and learning activities that take less than an hour have been implemented specifically to help students to master this technique. Results of the implementation of these activities have shown very positive results among the students. Two post tests were carried out to see the effectiveness of techniques and the results shows that 100% of students were able to answer correctly at least three questions correctly. The t-test analysis was clearly showed the effectiveness of ‘q’ technique. This technique also indirectly helps to maintain and increase student interest in learning Mathematics. This is shown with the active involvement of students in answering questions given by the teacher

A novel planning approach for the water, sanitation and hygiene (WaSH) sector: the use of object-oriented bayesian networks

Conventional approaches to design and plan water, sanitation, and hygiene (WaSH) interventions are not suitable for capturing the increasing complexity of the context in which these services are delivered. Multidimensional tools are needed to unravel the links between access to basic services and the socio-economic drivers of poverty. This paper applies an object-oriented Bayesian network to reflect the main issues that determine access to WaSH services. A national Program in Kenya has been analyzed as initial case study. The main findings suggest that the proposed approach is able to accommodate local conditions and to represent an accurate reflection of the complexities of WaSH issues, incorporating the uncertainty intrinsic to service delivery processes. Results indicate those areas in which policy makers should prioritize efforts and resources. Similarly, the study shows the effects of sector interventions, as well as the foreseen impact of various scenarios related to the national Program.Preprin

Analysis of resource sharing in transparent networks

Transparent optical networking promises a cost-efficient solution for future core and metro networks because of the efficacy of switching high-granularity trunk traffic without opto-electronic conversion. Network availability is an important performance parameter for network operators, who are incorporating protection and restoration mechanisms in the network to achieve competitive advantages. This paper focuses on the reduction in Capital Expenditures (CapEx) expected from implementing sharing of backup resources in path-protected transparent networks. We dimension a nationwide network topology for different protection mechanisms using transparent and opaque architectures. We investigate the CapEx reductions obtained through protection sharing on a population of 1000 randomly generated biconnected planar topologies with 14 nodes. We show that the gain for transparent networks is heavily dependent on the offered load, with almost no relative gain for low load (no required parallel line systems). We also show that for opaque networks the CapEx reduction through protection sharing is independent of the traffic load and shows only a small dependency on the number of links in the network. The node CapEx reduction for high load (relative to the number of channels in a line system) is comparable to the CapEx reduction in opaque OTN systems. This is rather surprising as in OTN systems the number of transceivers and linecards and the size of the OTN switching matrix all decrease, while in transparent networks only the degree of the ROADM (number and size of WSSs in the node) decreases while the number of transponders remains the same

Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study

Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG(Lab)(2)) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications