Evaluation of flight parameters during approach and landing phases by applying principal component analysis

This paper adopts an unsupervised learning technique, Principal Component Analysis (PCA) to analyze flight data. While the flight parameters for a stable approach have been established for a while, the paper reevaluates these flight parameters using PCA for a set of airports across the United States of America. Some flight parameters were found to be more sensitive to some airports. The parameters have been cross-checked with experts in the industry to better interpret their significance.peer-reviewe

Literature review of machine learning techniques to analyse flight data

This paper analyses the increasing trend of using modern machine learning technologies to analyze flight data efficiently. Flight data offers an important insight into the operations of an aircraft. This paper reviews the research undertaken so far on the use of Machine Learning techniques for the analyses of flight data by evaluating various anomaly detection algorithms and the significance of feature selection in Flight Data Monitoring. These algorithms are compared to determine the best class of algorithms for highlighting significant flight anomalies. Furthermore, these algorithms are analyzed for various flight data parameters to determine which class of algorithms is sensitive to continuous parameters and which is sensitive to discrete parameters of flight data. The paper also addresses the ability of each anomaly detection algorithm to be easily adaptable to different datasets and different phases of flight, including take-off and landing.peer-reviewe

Hybrid machine learning–statistical method for anomaly detection in flight data

This paper investigates the use of an unsupervised hybrid statistical–local outlier factor algorithm to detect anomalies in time-series flight data. Flight data analysis is an activity carried out by airlines primarily as a means of improving the safety and operation of their fleet. Traditionally, this is performed by checking exceedances in pre-set limits to the flight data parameters. However, this method highlights single events during a flight, making this analysis laborious. The process also fails to establish trends or reflect potential unknown hazards. This research took advantage of machine learning techniques to recognize patterns in large datasets by implementing the local outlier factor (LOF). In order to minimize human input, a statistical approach was adopted to establish the threshold value above which the flights are considered to be anomalous and interpret the scores. This paper shows that LOF quantifies the degree of outlier-ness of an outlier rather than binary categorizing a point into inlier or outlier, as in the case of clustering algorithms. Thus, with LOF, for the first time, we demonstrated that in the aviation industry, anomalous flights could not only be identified but also be given an anomaly score to compare two anomalous flights in an unsupervised manner. Furthermore, LOF helps to track anomalous behavior in time during the flight. This is insightful when a flight is abnormal, only for some seconds or short duration. For the first time, we attempted to detect flight parameters responsible for anomalous behavior or at least give direction to human experts looking for the cause of abnormal behavior. This was all analyzed with real-life flight data in an unsupervised manner in contrast to simulated data.peer-reviewe

A quasi-real-time ground-based trajectory optimization tool for greener operations

This paper describes the methodology adopted in designing a quasi-real-time ground-based trajectory optimization tool for use by air traffic control officers. The tool is primarily intended for the optimization of aircraft trajectories during the climb and descent phases in which the user can define the trajectory in four dimensions. The optimized trajectories would then contribute to a reduction in fuel burn and emissions. The designed tool takes into account different aircraft types and sub-types through BADA performance and engine coefficients. A simple case study for an approach in Malta International Airport has also been presented to illustrate the use of the tool.peer-reviewe

A proposal for revised approaches and procedures to Malta International Airport

Malta International Airport (ICAO code LMML) has four runways organized in T-format. The longer two are usually used by commercial aircraft since they are equipped with an Intrument Landing System and are facing local prevailing winds. The shorter two are mainly used for general aviation and for commercial airport adopting visual flight rules. Conventional procedures to and from the airfield are published in the Aeronautical Information Package, and include Standard Instrument Departures, instrument T-bar approach charts and other visual charts. However, no Standard Terminal Arrival Routes to connect inbound fixes to initial approach fixes or equivalent waypoints are available. This paper describes in detail the methodologies adopted in designing revised SIDs, STARs and associated procedures aimed at introducing optimal approaches and departures from LMML for the reduction of greenhouse gases in Maltese airspace. The resulting procedures for runway 13, which is the most heavily used runway by commercial aircraft, are presented, analyzed and discussed.peer-reviewe

Concept of operations of an ATC tool for trajectory optimisation

In this paper, a detailed Concept of Operations (Con-Ops) associated with a trajectory optimisation tool is presented. Operational scenarios are included for both climb and descent phases. The paper also includes a description of the tests used to assess the Con-Ops and the ATC tool. Finally, an overview of the safety assessment procedure to be carried out for the Con-Ops is provided.peer-reviewe

Searching biomedical databases on complementary medicine: the use of controlled vocabulary among authors, indexers and investigators

BACKGROUND: The optimal retrieval of a literature search in biomedicine depends on the appropriate use of Medical Subject Headings (MeSH), descriptors and keywords among authors and indexers. We hypothesized that authors, investigators and indexers in four biomedical databases are not consistent in their use of terminology in Complementary and Alternative Medicine (CAM). METHODS: Based on a research question addressing the validity of spinal palpation for the diagnosis of neuromuscular dysfunction, we developed four search concepts with their respective controlled vocabulary and key terms. We calculated the frequency of MeSH, descriptors, and keywords used by authors in titles and abstracts in comparison to standard practices in semantic and analytic indexing in MEDLINE, MANTIS, CINAHL, and Web of Science. RESULTS: Multiple searches resulted in the final selection of 38 relevant studies that were indexed at least in one of the four selected databases. Of the four search concepts, validity showed the greatest inconsistency in terminology among authors, indexers and investigators. The use of spinal terms showed the greatest consistency. Of the 22 neuromuscular dysfunction terms provided by the investigators, 11 were not contained in the controlled vocabulary and six were never used by authors or indexers. Most authors did not seem familiar with the controlled vocabulary for validity in the area of neuromuscular dysfunction. Recently, standard glossaries have been developed to assist in the research development of manual medicine. CONCLUSIONS: Searching biomedical databases for CAM is challenging due to inconsistent use of controlled vocabulary and indexing procedures in different databases. A standard terminology should be used by investigators in conducting their search strategies and authors when writing titles, abstracts and submitting keywords for publications

The seventh national communication of Malta under the United Nations framework convention on climate change

This is the fourth time that Malta is submitting a National Communication under the United Nations Framework Convention on Climate Change (UNFCCC), following the submission of a First National Communication in 2004 and a Second National Communication in 2010. This is also the second time that Malta is submitting such a Communication since its accession to Annex I status under the Convention, the first two submissions having been made as a non-Annex I Party. Emission reduction or limitation commitments applicable to Malta Malta’s status under the Convention up to the time it applied for accession to Annex I, and with that accession being conditional to not taking on quantified emission limitation or reduction targets for the first commitment period of the Kyoto Protocol, meant that until 2012 Malta was not subject to an economy-wide greenhouse gas related obligation under the Protocol. This however did not mean that Malta had no obligations to limit or reduce emissions from anthropogenic activities taking place in the country. In line with, Malta will be contributing its fair share of the EU’s unconditional commitment under the Convention to reduce emissions by 20% below 1990 levels by 2020. This is in line with the target inscribed in the amendments to the Kyoto Protocol (the Doha Amendments), that will be jointly fulfilling the second commitment period with the other Union member states; therefore, emissions from the aforementioned power plants remain subject to compliance with EU Emissions Trading Scheme provisions, while the Effort-Sharing Decision target is the principal emissions mitigation obligation that the country has until 2020, for all other greenhouse gas emissions. The major point sources of greenhouse gas emissions in Malta, namely the electricity generation plants have been, since of 2005, subject to the EU Emissions Trading Scheme, whereby they are required to surrender allowances in respect of emissions of carbon dioxide. Emissions of greenhouse gases not covered by the EU Emissions Trading Scheme, are subject to an overall limit under the so-called Effort-Sharing Decision. Under this decision, Malta must limit such greenhouse gases to not more than 5% over emission levels in 2005, by 2020. The EU is already looking towards the longer-term future, with the 2030 climate and energy framework providing for a 40% domestic reduction target for 2030. Legislative implementation of this goal is currently under discussion at EU level.peer-reviewe

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016

Background: A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97\ub71 (95% UI 95\ub78-98\ub71) in Iceland, followed by 96\ub76 (94\ub79-97\ub79) in Norway and 96\ub71 (94\ub75-97\ub73) in the Netherlands, to values as low as 18\ub76 (13\ub71-24\ub74) in the Central African Republic, 19\ub70 (14\ub73-23\ub77) in Somalia, and 23\ub74 (20\ub72-26\ub78) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91\ub75 (89\ub71-93\ub76) in Beijing to 48\ub70 (43\ub74-53\ub72) in Tibet (a 43\ub75-point difference), while India saw a 30\ub78-point disparity, from 64\ub78 (59\ub76-68\ub78) in Goa to 34\ub70 (30\ub73-38\ub71) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4\ub78-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20\ub79-point to 17\ub70-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17\ub72-point to 20\ub74-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle- SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations