Robust GNSS Point Positioning in the Presence of Cycle Slips and Observation Gaps

Among the various factors limiting accurate positioning with a Global Navigation Satellite System (GNSS) is the inherent code error level on a code observation, cycle slip occurrence on a phase observation, inadequate accuracy in the broadcast ionospheric model for single-frequency receivers; and the occurrence of observation gaps, which are short duration satellite outages (temporal loss of an observed satellite). The existing Cycle Slip Detection and Correction (CSDC) techniques are usually multi-satellite based; quite computationally intensive; and are often marred by the inherent code errors from the included code observations. Also, existing code-carrier smoothing techniques employed to mitigate code errors are limited by cycle slip occurrences on phase observations. In this research, algorithms are proposed in order to facilitate simple, efficient and real-time cycle slip detection, determination and correction, on a standalone single- or dual-frequency receiver; to enable cycle-slip-resilient code errors mitigation; and to improve the broadcast ionospheric model for single-frequency receivers. The proposed single-satellite and phase-only-derived CSDC algorithms are based on adaptive time differencing of short time series phase observables. To further provide robustness to the impact of an observation gap occurrence for an observed satellite, post-gap ionospheric delay is predicted assuming a linearly varying ionospheric delay over a short interval, which consequently enables the dual-frequency post-gap cycle slip determination and code error mitigation. The proposed CSDC algorithms showed good performance, with or without simulated cycle slips on actual data obtained with static and kinematic GNSS receivers. Over different simulated cycle slip conditions, a minimum of 97.3% correct detection and 79.8% correctly fixed cycle slips were achieved with single-frequency data; while a minimum of 99.9% correct detection and 95.1% correctly fixed cycle slips were achieved with dual-frequency data. The point positioning results obtained with the proposed methods that integrates the new code error mitigation and cycle slip detection and correction algorithms, showed significant improvement over the conventional code-carrier smoothing technique (i.e. a standalone Hatch filter, without inclusion of any cycle slip fixing method). Under different simulated cycle slip scenarios, the new methods achieved 25-42% single-frequency positioning accuracy improvement over the standalone Hatch filter, and achieved 18-55% dual-frequency positioning accuracy improvement over the standalone Hatch filter

Cigarette Smoking and Adolescent Health: A Survey of Selected Senior Secondary Schools in Ekpoma

The objective of this study was to investigate the knowledge and practice of cigarette smoking among in-school adolescents in Ekpoma. A sample of 353 senior secondary students drawn from selected schools in the area was studied in a cross-sectional design using self-administered questionnaires. Respondents’ knowledge was  assessed with questions that bother on aspects of smoking with public health implications. Mean age of respondents was 16.6   years and a near-equal gender distribution. The results showed a smoking prevalence of 11.6% while the percentage attempts to quit was 26.8%. Percentage awareness about the harmful effects of smoking was 86.1% while comprehensive knowledge of important aspects of smoking was good in 60.3% of respondents. There was a  significant relationship between smoking and self-reported academic performance (X2 = 5.002; p=0.025; OR = 0.47; CI (95%) = 0.22 – 0.96). Conclusively, the prevalence of smoking was high among in-school adolescents in the study area. We recommend special programmes and services aimed at reducing smoking among adolescents in a learning environment.Keywords: Cigarette, Smoking, Adolescents, Secondary schools, Ekpoma

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Hypercalcemia in patients with newly diagnosed tuberculosis in Abuja, Nigeria

BACKGROUND: The prevalence of hypercalcemia has not previously been determined in newly diagnosed tuberculosis (TB) patients in Nigeria

Optimal Power Flow Analysis in Power Dispatch for Distribution Networks

This paper presents two applications of Optimal Power Flow analysis for active and reactive power redispatch in medium-voltage distribution networks and shows how this tool can be used to efficiently manage the selection and operation of network resources as well as the definition of a market interface with the transmission network. The description of the frameworks is complemented by the analysis of a case study for the optimal selection and operation of available devices

Genetic algorithm-based spinning reserve dispatching in a competitive electricity market

Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses haw been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market