Search results

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

Research has shown that Indigenous people suffer significant health inequalities in comparison to dominant colonising cultures. Evidence shows that these inequalities can be addressed by gaining a deeper understanding of the social and cultural determinants of health, applying Indigenous views of health and developing better definitions of the term wellbeing. The following chapter draws on research exploring the relationship between Indigenous culture, the landscape and the connection with health and wellbeing. In Aotearoa/New Zealand, consideration of Indigenous Māori is a national imperative, enshrined in the Te Tiriti o Waitangi (Treaty of Waitangi) which establishes it as a bicultural country. Exploring three Māori health models, the chapter examines the factors that play a significant role in shaping Māori people's health. It relates how landscape is a foundational therapeutic aspect of Māori wellbeing using the models to express the forces that impact both positively and negatively on this relationship. The chapter concludes that all three concepts, culture, health and landscape, are interconnected and must be balanced to reduce Māori health inequalities and to provide a more sustainable model for health and wellbeing for all New Zealanders.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

This chapter seeks to understand the emergence of new institutions of business regulation, standard-setting and governance commonly referred to as multistakeholder initiatives (MSIs), and to consider their implications both from the perspective of regulatory effectiveness and sustainable development.

The analysis synthesizes the findings of a review of 20 such initiatives. It draws on a wide body of literatures and conceptual insights to understand the emergence of these new approaches to international business regulation. The assessment of their emergence, performance, and impacts highlights the complex dynamics of regulatory change.

The findings caution against simple generalizations about the positive or negative outcomes of these new forms of collaborative governance. Their somewhat mixed record can be partly explained by the diverse set of interests, preferences, and agendas of the actors involved; variations in institutional learning, capacities, and power relations; as well as how such initiatives are nested in broader institutions and structures. This points to the need, raised in the conclusion, for intellectual pluralism in advancing knowledge of the effectiveness of new regulatory institutions.

The analysis aims to go beyond studies that (i) tend to focus on just one or a few cases; (ii) that ignore the implications of such initiatives for development in the Global South; and (iii) draw on narrow bodies of theory and literature to understand complex issues.

The purpose of this paper is to calculate the probability of collision of flying aircraft crossing on straight paths in any direction.

The probability of deviations from the intended flight paths is used to calculate the probability of collision that is integrated over time to cover whole events.

The probabilities of collision are calculated in terms of the r.m.s. position errors and encounter geometry, that is aircraft velocities and flight path angles and crossing angles.

The method does not apply to aircraft flying in parallel tracks at the same velocity in air corridors: that case has been covered elsewhere, as well as the case of climbing or descending aircraft.

International Civil Aviation Organization (ICAO) specifies as target level of safety (TLS) a probability of collision not exceeding 5×10⁻⁹ per hour. To meet the ICAO TLS standard, it is necessary to calculate collision probabilities for all stages of flight.

A low collision probability is a safety metric; the value does depend on a realist choice of probability distribution.

Calculates the probability of collision for crossing flights, corresponding to a common scenario on air traffic management.

The purpose of this chapter is to solve multi-objective formulation for traveling salesman and transportation problems. Computations are based on real data for the road freight transportation of a Spanish company. The company was selected because of its importance in Spanish economy and market. This company is important in the whole country; however, it has its higher importance in the northern part of Spain. The requirements for these models are the minimization of total distance and the CO₂ emissions. To achieve this, it is required to know and carry out the minimization of the total distance traveled by the trucks during the deliveries. The deliveries are going to be executed between the different locations, nodes, in the region, and Elorrio, where the depot is situated. The data have been used to decide the best route in order to obtain a minimization of cost for the company. As it was mentioned earlier, the problems are focused on the reduction of the amount of CO₂ emissions and minimization of total distance; by studying different parameters, the best solutions of route transportation have been obtained. The software used to solve these models is CPLEX solver with AMPL programming language.

The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.

It has been well known that the quantum zero‐point energy (ZPE) cannot be conserved in simulations of atoms and molecules dynamics based on classical mechanics. The purpose of this paper is to examine fundamental issues related to the treatment of quantum ZPE constraint in simulations of atoms and molecules dynamics.

The ZPE is well known to be a quantum mechanical expectation value that is equivalent to an ensemble average when this value is interpreted to classical mechanics. An important point is that the ensemble‐averaged energies on simulations are expected to obey the ZPE criteria rather than those of individual simulation. The point is elucidated using quasiclassical trajectory calculations with a popular hydrogen atom‐diatom direct collision process incorporating a potential energy surface of a triatomic hydrogen system.

The results obtained by using standard classical trajectory calculations agree well with the quantum calculations. Using them, the author found that the classical results remain valid even if some trajectory calculations have vibrational energies that are less than the ZPE.

It is found that the ensemble‐average of each trajectory calculation can provide results that are consistent with quantum mechanical ones that obey the ZPE criteria, without the introduction of any additional constraint conditions for atoms and simulation algorithms.