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Optimal crew allocation and scheduling is an important issue in the management of a large fleet of taxis. Presents a modelling study of a taxi service operation in a Singapore public transport company, with the results adaptable for other similar operations. Proposes two quantitative techniques: the queueing analysis approach and the integer programming approach: These can be used to allocate and schedule the taxi fleet to cover the demand for services at various time periods and geographical zones for the entire country. Presents a routeing and scheduling management information system to support the scheduler in making routeing and scheduling decisions.

In recent years, a wide range of psychosocial health interventions have been implemented among military service members and their families. However, there are questions over the evaluative rigor of these interventions. We conducted a systematic review of this literature, rating each relevant study (k = 111) on five evaluative rigor scales (type of control group, approach to participant assignment, outcome quality, number of measurement time points, and follow-up distality). The most frequently coded values on three of the five scales (control group type, participant assignment, and follow-up distality) were those indicating the lowest level of operationally defined rigor. Logistic regression results indicate that the evaluative rigor of intervention studies has largely remained consistent over time, with exceptions indicating that rigor has decreased. Analyses among seven military sub-populations indicate that interventions conducted among soldiers completing basic training, soldiers returning from combat deployment, and combat veterans have had, on average, the greatest evaluative rigor. However, variability in mean scores across evaluative rigor scales within sub-populations highlights the unique methodological hurdles common to different military settings. Recommendations for better standardizing the intervention evaluation process are discussed.

In Senegal, the government has encouraged private investment in agriculture and biofuel production since the 2000s, generating several attempted or effective large-scale land acquisitions by domestic and international investors. In reaction to these projects, local groups of opponents have joined forces with national peasant organizations, civil society associations, and think tanks to resist perceived land grabs. This article examines the emergence of this social movement and explains why anti-land grabs campaigns were successful in halting some projects, but not successful in others. I argue that four main factors are at play: a strong mobilization of local populations measured by group cohesion and level of determination; the assistance of national and international NGOs in scaling up protests beyond the local level; the capacity of opponents to harness the support of influential elites and decision-makers; and the legal status of the land under contention. This paper draws on an analysis of secondary data, qualitative interviews, and field observations carried out in Senegal for several months from 2013 to 2018.

Studying Chinese higher education internationalization policy-making requires paying attention to the political ontology of China's top-designed policy-making system before proceeding to methodological approaches. The ontology is two-fold: a fixed reality grounded in the structure and agency of the one-party state, and an emergent reality that derives from the pervasive practice of using policy documents to govern. A two-pronged epistemology is proposed to uncover these realities: interpretative and poststructural problematization. Interpretative problematization helps discern how policy-makers frame a problem–solution discourse in policy documents to achieve predetermined strategic objectives. Contrastingly, poststructural problematization views policy documents as prescriptive texts that offer rules on how to behave. The potential methodologies drawn from the tradition of critical policy sociology can be employed to study these two problematizations, thereby unpacking the fixed and emergent realities.

The purpose of this paper is to present the methodology and the results on the design and development of an autonomous, golf ball picking robot, for driving ranges.

The strategy followed to develop a commercial product is presented, based on prior identification requirements, which consist of picking up golf balls on a driving range in a safe and efficient way.

A fully working prototype robot has been developed. It uses two driving wheels and a third cast wheel, and pushes a standard gang which collects the balls from the ground. A hybrid information system was implemented in order to provide a statistically relevant prediction of golf balls location, to optimize the path the robot has to follow in order to reduce time and cost. Autonomous navigation was developed and tested on a simulation environment.

Preliminary results showed that the new path planning algorithm Twin‐RRT* is able to form closed loop trajectories and improve the result over time. Kinematic constraints were already taken into account on the algorithm. This sampling based algorithm has potential usage in solving other TPP (Travelling Purchaser Problem) related problems.

The prototype feasibility is being tested in real driving ranges. It has autonomy of up to 8 h per day. It is capable of collecting up to 1,200 balls in one single journey. It weighs 130 kg and is capable of climbing slopes of up to 22°. The maximum speed is 8 km/h and the robot takes 140 min to completely sweep a 25,000 m² field at 7.2 km/h (2 m/s) average speed.

There are about 30,000 golf practice fields, of which 18,000 are located in the USA and Canada. In some countries the golf industry represents more than 15 per cent of tourism GNP. In a typical practice field, about 10,000 balls have to be picked up every day.

An important contribution of this paper is the algorithm for path planning in order to optimize the ball pick up task, reducing time and cost. There are two patents are pending concerning the technological novelties of this work.

This study aims to explore the risk and protective factors of abuse on older adults by family caregivers, with a special focus on the protective role of caregiver resilience in elder abuse.

This cross-sectional survey was conducted on a purposive sample of 600 family caregivers of community-dwelling older adults in Hong Kong (mean age = 71.04 and female = 67.2%). Caregivers reported in a guided interview about elder abuse behaviours, caregiver burden, care recipients’ agitated behaviours, caregiver resilience, self-efficacy, social support and basic demographic characteristics. Hierarchical linear regression analyses were conducted to examine the predictors of different forms of elder abuse.

Caregiver resilience was predictive of lower levels of verbal abuse, physical abuse, injury and financial exploitation but not potentially harmful behaviour (PHB). Social support was independent with all forms of elder abuse, while self-efficacy predicted greater physical abuse after the adjustment of confounding variables. Caregiver burden and agitated behaviours by care recipients remained as significant risk factors in the final models when protective factors were considered.

This study extends current knowledge on the protecting role of resilience in elder abuse in family caregiving. Mixed findings revealed on social support and self-efficacy also highlight the complexity of the prediction of caregiver abuse. Further research should address this area.

The findings of this study warrant the inclusion of caregiver resilience as a key component in developing interventions to prevent elder abuse. Addressing caregiver burden and agitated behaviours have the potential in preventing elder abuse.

The findings raise awareness of the importance of supporting caregivers in the community to prevent elder abuse.

Research concerning the protective factors of elder abuse is in a preliminary stage. To the best of the authors’ knowledge, this study is among the first which successfully demonstrates the protective role of resilience in caregiver abuse on older adults. The findings shed invaluable light on the design of effective interventions.

AS the result of a considerable amount of investigation over a period of some months prior to the flight to Canada, six alternative routes were selected for the England‐Canada flight. These routes, in order from north to south, were:—

The purpose of this study is to investigate the influence of light intensity and sources of carbon and nitrogen on the cultivation of Spirulina maxima.

Cultures were carried out in a modified Zarrouk medium using urea, sodium acetate and glycerol. A Taguchi experimental design was used to evaluate the effect on the production of biocompounds: productivities in biomass, carbohydrates, phycocyanin and biochar were analyzed.

Statistical data analysis revealed that light intensity and sodium acetate concentration were the most important factors, being significant in three of the four response variables studied. The highest productivities in biomass (46.94 mg.L⁻¹.d⁻¹), carbohydrates (6.11 mg.L⁻¹.d⁻¹), phycocyanin (3.62 mg.L⁻¹.d⁻¹) and biochar (22, 48 mg.L⁻¹.d⁻¹) were achieved in experiment 4 of the Taguchi matrix, highlighting as the ideal condition for the production of biomass, carbohydrates and phycocyanin.

Sodium acetate and urea can be considered, respectively, as potential sources of carbon and nitrogen to increase Spirulina maxima productivity. From the results, an optimized cultivation condition for the sustainable production of bioproducts was obtained.

This work focuses on the study of the influence of light intensity and the use of alternative sources of nitrogen and carbon on the growth of Spirulina maxima, as well as on the influence on the productivity of biomass and biocompounds. There are few studies in the literature focused on the phycocyanin production from microalgae, justifying the need to deepen the subject.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation under the natural intelligence mechanism.

The brightness and luminosity are the decision variables in proposed study. The paper achieves the two major goals of robot navigation; first, the optimum path generation and, second, as an obstacle avoidance by co-in-centric sphere-based geometrical technique. This technique comprises the optimum path decision to objective function and constraints to paths and obstacles as the function of algebraic-geometry co-relation. Co-in-centric sphere is the proposed technique to correlate the constraints.

It is found that the present FA based on concentric sphere is suitable for efficient navigation of mobile robots at the level of optimum significance when compared with other approaches.

The paper introduces a novel approach to implement the FA for unknown and uncertain environment.