Search results

The purpose of this paper is to focus on the development of conflict-resolution algorithms between Remotely Piloted Aircraft System (RPAS) and conventional aircraft. The goal of the conflict-resolution algorithm is to estimate the minimum protection distance (MPD) which is required to avoid a potential conflict.

The conflict-resolution algorithms calculate the last location at which an RPAS must start climbing to avoid a separation minima infringement. The RPAS maneuvers to prevent the conventional aircraft based on the kinematic equations. The approach selects two parameters to model the conflict-geometry: the path-intersection angle and the Rate of Climb (ROCD).

Results confirmed that the aircraft pair flying in opposition was the worst scenario because the MPD reached its maximum value. The best value of the MPD is about 12 Nautical Miles to ensure a safe resolution of a potential conflict. Besides, variations of the ROCD concluded that the relation between the ROCD and the MPD is not proportional.

The primary limitation is that the conflict-resolution algorithms are designed in a theoretical framework without bearing in mind other factors such as communications, navigation capacity, wind and pilot errors among others. Further work should introduce these concepts to determine how the MPD varies and affects air traffic safety. Moreover, the relation between an ROCD requirement and the MPD will have an impact on regulations.

The non-linear relation between the MPD and the ROCD could be the pillar to define a standardized MPD in the future for RPAS systematic integration. To accomplish this standard, RPAS could have to fulfil a requirement of minimum ROCD until a specified flight level.

This paper is the first approach to quantify the Minimum Protection Distance between RPAS and conventional aircraft, and it can serve the aeronautical community to define new navigation requirements for RPAS.

The 2019 coronavirus disease (COVID-19) pandemic has profoundly affected family and school life. Evidence demonstrates how pandemic-induced online learning and home confinement can influence family dynamics and, consequently, students’ mental health and quality of life. This chapter extends the literature by building upon the perspective of family systems theory and focusing the analysis on graduate students who are underrepresented in COVID-19 research. Drawing from an online survey among 337 graduate students enrolled in a state university in the Philippines during the second year of the pandemic, this study examines the three family relationship domains (cohesion, expressiveness, and conflict), their predictive relationships with life satisfaction, and the mediating role of mental well-being on these relationships. Findings indicate favorable levels of cohesion, expressiveness, and conflict in the family. Respondents’ age, sex assigned at birth, and marital status were significantly correlated with at least one domain of family relationship. Cohesion and expressiveness yielded significant positive predictive relationships on mental well-being and life satisfaction. Furthermore, findings indicate the partial mediation of mental well-being on the relationship between cohesion and life satisfaction and full mediation on expressiveness and life satisfaction.

This paper aims to assess the implications in safety levels by the integration of remotely piloted aircraft system (RPAS). The goal is to calculate the number of RPAS that can jointly operate with conventional aircraft regarding conflict risk, without exceeding current safety levels.

This approach benchmarks a calculated level of safety (CLS) with a target level of safety (TLS). Monte Carlo (MC) simulations quantify the TLS based on the current operation of conventional aircraft. Then, different experiments calculate the CLS associated with combinations of conventional aircraft and RPAS. MC simulations are performed based on probabilistic distributions of aircraft performances, entry times and geographical distribution. The safety levels are based on a conflict risk model because the safety metrics are the average number of conflicts and average conflict duration.

The results provide restrictions to the number of RPAS that can jointly operate with conventional aircraft. The TLS is quantified for four conventional aircraft. MC simulations confirm that the integration of RPAS demands a reduction in the total number of aircraft. The same number of RPAS than conventional aircraft shows an increase over 90% average number of conflicts and 300% average conflict time.

The methodology is applied to one flight level of en-route airspace without considering climbing or descending aircraft.

This paper is one of the most advanced investigations performed to quantify the number of RPAS that can be safely integrated into non-segregated airspace, which is one of the challenges for the forthcoming integration of RPAS. Particularly, Europe draws to allow operating RPAS and conventional aircraft in non-segregated airspace by 2025, but this demanding perspective entails a thorough analysis of operational and safety aspects involved.

We discuss adoption as a diverse family structure in America. Adoption has existed in some form throughout the history with the portrayal varying by historical epoch. Adoption has been both disparaged and idealized to perpetuate the interest of elite players. This chapter discusses adoption in terms of the changing demographic which 21st century families face. In this manuscript, we first discuss the history of adoption in the United States including its impact as social control of premarital sex. Then the three players in the adoption triad are discussed and analyzed. Finally, we highlight how demographics of race, class, gender, and sexuality impact the adoption experience by 21st century families. Specifically, we explore the recent National Survey of Adoptive Parents from the United States Center for Disease Control and look at the modern adoption experience

This paper aims to analyse remotely piloted aircraft system (RPAS) integration in non-segregated terminal airspace. This work aims to identify the potential airspace volumes where a free operation of RPAS can be developed by analysing the airspace design of the terminal airspace.

The methodology considers five crucial elements of the airspace design: obstacles, prohibited, restricted and dangerous zones, aerodrome zones, departing and arriving procedures and visual corridors. Free operation of RPAS is performed in those airspace volumes that no interaction with instrumental flight rules (IFR) flights is expected. Free RPAS airspace volumes are separated through current IFR separation minima.

The results show there is a significant amount of available airspace that RPAS can operate without interaction with conventional aircraft. The more significant risks are allocated by the limitations imposed by departing and arriving procedures in the terminal airspace.

The methodology is applied to medium-dense terminal airspace. This work assumes RPAS can perform visual or instrumental flights.

RPAS is a capital issue for the majority of aviation actors. This work underlay the further development of a methodology regarding airspace design for RPAS in a terminal control area.

This article surveys the literature dealing with theory and applications of life cycle costing (LCC). It deals with the literature published in the last 25 years and provides 667 references.

Measures are important to healthcare outcomes. Outcome changes result from deliberate selective intervention introduction on a measure. If measures can be characterized and categorized, then the resulting schema may be generalized and utilized as a framework for uniquely identifying, packaging and comparing different interventions and probing target systems to facilitate selecting the most appropriate intervention for maximum desired outcomes. Measure characterization was accomplished with multi-axial statistical analysis and measure categorization by logical tabulation. The measure of interest is a key provider productivity index: “patient visits per hour,” while the specific intervention is “patient schedule manipulation by overbooking.” The paper aims to discuss these issues.

For statistical analysis, interrupted time series (ITS), robust-ITS and outlier detection models were applied to an 18-month data set that included patient visits per hour and intervention introduction time. A statistically significant change-point was determined, resulting in pre-intervention, transitional and post-effect segmentation. Linear regression modeling was used to analyze pre-intervention and post-effect mean change while a triangle was used to analyze the transitional state. For categorization, an “intervention moments” table was constructed from the analysis results with: time-to-effect, pre- and post-mean change magnitude and velocity; pre- and post-correlation and variance; and effect decay/doubling time. The table included transitional parameters such as transition velocity and transition footprint visualization represented as a triangle.

The intervention produced a significant change. The pre-intervention and post-effect means for patient visits per hour were statistically different (0.38, p=0.0001). The pre- and post-variance change (0.23, p=0.01) was statistically significant (variance was higher post-intervention, which was undesirable). Post-intervention correlation was higher (desirable). Decay time for the effect was calculated as 11 months post-effect. Time-to-effect was four months; mean change velocity was +0.094 visits per h/month. A transition triangular footprint was produced, yielding 0.35 visits per hr/month transition velocity. Using these results, the intervention was fully profiled and thereby categorized as an intervention moments table.

One limitation is sample size for this time series, 18 monthly cycles’ analysis. However, interventions on measures in healthcare demand short time cycles (hence necessarily yielding fewer data points) for practicality, meaningfulness and usefulness. Despite this shortcoming, the statistical processes applied such as outliers detection, t-test for mean difference, F-test for variances and modeling, all consider the small sample sizes. Seasonality, which usually affects time series, was not detected and even if present, was also considered by modeling.

Obtaining an intervention profile, made possible by multidimensional analysis, allows interventions to be uniquely classified and categorized, enabling informed, comparative and appropriate selective deployment against health measures, thus potentially contributing to outcomes optimization.

The inevitable direction for healthcare is heavy investment in measures outcomes optimization to improve: patient experience; population health; and reduce costs. Interventions are the tools that change outcomes. Creative modeling and applying novel methods for intervention analysis are necessary if healthcare is to achieve this goal. Analytical methods should categorize and rank interventions; probe the measures to improve future selection and adoption; reveal the organic systems’ strengths and shortcomings implementing the interventions for fine-tuning for better performance.

An “intervention moments table” is proposed, created from a multi-axial statistical intervention analysis for organizing, classifying and categorizing interventions. The analysis-set was expanded with additional parameters such as time-to-effect, mean change velocity and effect decay time/doubling time, including transition zone analysis, which produced a unique transitional footprint; and transition velocity. The “intervention moments” should facilitate intervention cross-comparisons, intervention selection and optimal intervention deployment for best outcomes optimization.

This study examined 46 articles in total, which yielded 5 recurring themes: perceived discrimination, language barriers, socioeconomic barriers, cultural barriers and educational/knowledge barriers. The two most dominant themes found were the inability to speak the country's primary language and belonging to a culture with different practices and values from the host country. The review provides vital insights into the numerous challenges that immigrants and refugees encounter as they navigate through the primary care systems of English-speaking (E-S) countries and potential solutions to overcome these barriers.

Access to adequate healthcare plays a central part in ensuring the physical and mental wellbeing of society. However, vulnerable groups such as immigrants and refugees, face numerous challenges when utilizing these healthcare services. To shed further light on the barriers impacting healthcare quality, the authors’ team performed a scoping thematic review of the available literature on immigrant and refugees' experiences in primary healthcare systems across E-S countries. Articles were systematically reviewed while focusing on healthcare perceptions by immigrants, potential barriers and suggestions to improve the quality of primary care.

This work looked at qualitative and quantitative information, attempting to combine both paradigms to give a rich and robust platform with which to devise a further study through focus groups. Qualitative inquiry accounted for 28/46, or 61%, of studies, and quantitative inquiry made up 9/46, or 20%, while 9/46 or 20% combined both qualitative and qualitative. Emerging themes are -perceived ethnic discrimination faced by immigrants accessing primary care, language barriers, socioeconomic barriers, cultural barriers and educational barriers.

Most medical journals rely on quantitative data to relate “results” and cases. The authors set out to change ways in which medical reports can be done. Most of the authors were solely trained in quantitative research; consequently, they had to learn to isolate themes and to use a narrative approach in the article.

Research implications clearly indicated that using a qualitative (phenomenological) approach with quantitative data created a human and reachable discourse around patient comfort and the realities of immigrants and refugees to E-S countries. The use of this research opens medical practitioners (and patients) to a richer understanding within a usually difficult arena.

By understanding the qualitative nature of medical research, practitioners, students and mentors are able to bridge medical quantitivity to the human, widening doors to social science and medical collaboratory research.

As stated above, this work is important as it understands the human/patient element and de-emphasizes the medical obsession with quantifying the lives of patients through hard data. This is a unique collaboration that relies on the qualitative to pinpoint and define the difficulties of newcomers to E-S countries.

The Best Management Practices for Sustainable Urban Drainage System including On-Site Detention have been introduced in the Storm Water Management Manual for Malaysia. Flash floods are becoming frequent in the urbanised areas in this country. Inefficient drainage system has been highlighted as one of the factors. Urban drains were reported incapable of coping with the unexpected heavy rainfall. Concrete drains are favourable in construction industry for economic reasons. An experimental research was conducted out to investigate the effectiveness of infiltration integration with drainage system to reduce flash flood. This laboratory research was conducted in the Universiti Teknologi Malaysia. Experiments were performed for selected drainage bed slopes and focussed on several spacing between precast drain sections along the system. The total and infiltrated flow rates, water surface and velocity profiles were examined. The results showed that drain flow rates were reduced by 60.9%–89.6% when the spacing between drain sections were enlarged. Meanwhile, the flow depths in drain sections were dropped by 48.2%–68.9%, and the water velocity was lowered up to 49% as the spacing between drain sections were increased. The study found that the drainage bed slope also influenced the performance of the infiltrated concrete drainage system.