Countering the Attention Deficit Hyperactivity Disorder epidemic: a question of ethics?

Recently in Australia, another media skirmish has erupted over the problem we currently call “Attention Deficit Hyperactivity Disorder”. This particular event was precipitated by the comments of a respected District Court judge. His claim that doctors are creating a generation of violent juvenile offenders by prescribing Ritalin to young children created a great deal of excitement, attracting the attention of election-conscious politicians who appear blissfully unaware of the role played by educational policy in creating and maintaining the problem. Given the short (election-driven) attention span of government policymakers, I bypass government to question what those at the front line can do to circumvent the questionable practice of diagnosing and medicating young children for difficulties they experience in schools and with learning.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Ethics, Law and Health Care : a Guide for Nurses and Midwives

Understanding ethics and law in health care is an essential part of nurses’ and midwives’ professional standards. Ethics, Law and Health Care focuses on teaching applied ethics and law in a manner that illustrates the real world applications of these core components of the nursing and midwifery curriculum and practice. It equips readers with the ability to recognise and address legal and ethical issues that will arise in their professional practice. The book uses the four principles of biomedical ethics (autonomy, non-maleficence, beneficence and justice) together with the use of both the Nursing and Midwifery Codes of Ethics and Codes of Professional Conduct, issued by the Nursing and Midwifery Board of Australia, as a central means through which to analyse and approach ethical and legal issues. Ethics, Law and Health Care is scaffolded to assist readers in understanding legal and ethical principles, to integrate them in the context of a particular issue within professional practice, and provide them with a decision-making framework to take action in a professional context by utilising the Codes as well as state and federal law. Aided by pedagogical features such as case studies, review questions, further reading and a glossary of common terms, this book is an essential resource for students, academics and practitioners.

Sexualities and sensitivities: Queer(y)ing the ethics of youth research in the field

In contemporary Western societies, the years between childhood and young adulthood are commonly understood to be (trans)formative in the reflexive project of sexual self-making (Russell et al. 2012). As sexual subjects in the making, youthful bodies, desires and sexual activities are often perceived as both volatile and vulnerable, thus subjected to instruction and discipline, protection and surveillance. Accordingly, young people’s sexual proximities are closely monitored by social institutions and ‘(hetero)normalising regimes’ (Warner 1999) for any signs that may compromise the end goal of development—a ‘normal’ reproductive heterosexual monogamous adult...

Design and ethics in digital mental health promotion

This chapter presents a case study of Participatory Design as a design framework for developing interactive digital tools for promoting children’s resilience. The author argues for a participatory methodology as an ethical approach that involves children as co-designers in the process from which they are traditionally excluded, namely the creative design process and the process of mental health promotion.

A little learning is a dangerous thing? The ethics of teaching accidental tourists in higher education

This paper raises questions about the ethical issues that arise for academics and universities when under-graduate students enrol in classes outside of their discipline - classes that are not designed to be multi-disciplinary or introductory. We term these students ‘accidental tourists'. Differences between disciplines in terms of pedagogy, norms, language and understanding may pose challenges for accidental tourists in achieving desired learning outcomes. This paper begins a discussion about whether lecturers and universities have any ethical obligations towards supporting the learning of these students. Recognising that engaging with only one ethical theory leads to a fragmented moral vision, this paper employs a variety of ethical theories to examine any possible moral obligations that may fall upon lecturers and/or universities. In regards to lecturers, the paper critically engages with the ethical theories of utilitarianism, Kantianism and virtue ethics (Aristotle) to determine the extent of any academic duty to accidental tourists. In relation to universities, this paper employs the emerging ethical theory of organisational ethics as a lens through which to critically examine any possible obligations. Organisational ethics stems from the recognition that moral demands also exist for organisations so organisations must be reconceptualised as ethical actors and their policies and practices subject to ethical scrutiny. The analysis in this paper illustrates the challenges faced by lecturers some of whom, we theorise, may experience a form of moral distress facing a conflict between personal beliefs and organisational requirements. It also critically examines the role and responsibilities of universities towards students and towards their staff and the inherent moral tensions between a market model and demands for ‘good' learning experiences. This paper highlights the tensions for academics, between academics and universities and within university policy and indicates the need for greater reflection about this issue, especially given the many constraints facing lecturers and universities.

Ethics in Research with Children

Widespread scholarly interest in ethics in research with children, as an extant field of inquiry and practice, is a relatively new phenomenon. The discipline of ethics can be traced back to the Hippocratic school, but its contemporary applications in the everyday worlds of children and those around them are gaining greater attention from theorists, practitioners, and those involved in policy. Heightened international awareness of the United Nations Convention on the Rights of the Child (1979) gave significant impetus to increasing international awareness of children’s rights to provision, protection, and participation in everyday contexts, including those in which research occurs. Understandings of research ethics and of children’s involvement in research relate to broader understandings of children and childhood drawn from developmental science, sociology, human geography, health sciences, and children’s human rights to participation and protection. Key understandings pertain to children’s competence to participate in research, to operate as reliable informants with respect to their own lives, to provide voluntary informed consent and dissent in research, and to make meaningful decisions about the nature and extent of their participation. The field is international and interdisciplinary, although bounded by legislative, policy, and jurisdictional requirements governing research—its conduct and dissemination. So, too, the burgeoning work of ethics committees, whether in relation to health research or social research, is evidence of a sharpened focus on governance of child research. Oxford Bibliographies offers a suite of perspectives, resources, and strategies to guide the researcher, practitioner, and policymaker and serves to challenge readers to interrogate conceptual understandings, methodologies, and dissemination of research with and about children. Exploration of the suite opens up new possibilities for considering children’s rights to participation in matters that affect their lives and for children to be seen and heard in research.

Representations for evolutionary design modelling

This research looked at using the metaphor of biological evolution as a way of solving architectural design problems. Drawing from fields such as language grammars, algorithms and cellular biology, this thesis looked at ways of encoding design information for processing. The aim of this work is to help in the building of software that support the architectural design process and allow designers to examine more variations.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.

Evolutionary Perspectives

The standard approach to industrial economics starts with the industry’s basic conditions, then runs through the structure–conduct–performance paradigm of industrial organization, and finally considers government regulation and policy. Most creative industries segments have been studied in this way, for example in Albarran (2002) and Caves (2000). These approaches use standard economic analysis to explain the particular properties and characteristics of a specific industrial sector. The overview presented here is different again. It focuses on the creative industries and examines their economic effect, specifically their contribution to economic evolu -tion. This is an evolutionary systems approach to industrial analysis, where we seek to understand how a sector fits into a broader system of production, consumption, technology, trade and institutions. The evolutionary approach focuses on innovation, economic growth and endogenous transformation. So, rather than using economics to explain static or industrial-organization features of the creative industries, we are using an open systems view of the creative industries to explain dynamic ‘Schumpeterian’ features of the broader economy. The creative industries are drivers of economic transformation through their role in the origination of new ideas, in consumer adoption, and in facilitating the institutional embedding of new ideas into the economic order. This is not a novel idea, as economists have long understood that particular activities are drivers of economic growth and development, for example research and development, and also that particular sectors are instrumental to this process, for example high-technology sectors. What is new is the argument that cultural and creative sectors are also a key part of this process of economic evolution. We will review the case for that claim, and outline purported mechanisms. We will also consider why policy settings in the creative industries should be more in line with innovation and growth policy than with industry policy.

Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Law, ethics and pandemic preparedness : the importance of cross-jurisdictional and cross-cultural perspectives

OBJECTIVE To explore social equity, health planning, regulatory and ethical dilemmas in responding to a pandemic influenza (H5N1) outbreak, and the adequacy of protocols and standards such as the International Health Regulations (2005). APPROACH This paper analyses the role of legal and ethical considerations for pandemic preparedness, including an exploration of the relevance of cross-jurisdictional and cross-cultural perspectives in assessing the validity of goals for harmonisation of laws and policies both within and between nations. Australian and international experience is reviewed in various areas, including distribution of vaccines during a pandemic, the distribution of authority between national and local levels of government, and global and regional equity issues for poorer countries. CONCLUSION This paper finds that questions such as those of distributional justice (resource allocation) and regulatory frameworks raise important issues about the cultural and ethical acceptability of planning measures. Serious doubt is cast on a 'one size fits all' approach to international planning for managing a pandemic. It is concluded that a more nuanced approach than that contained in international guidelines may be required if an effective response is to be constructed internationally. IMPLICATIONS The paper commends the wisdom of reliance on 'soft law', international guidance that leaves plenty of room for each nation to construct its response in conformity with its own cultural and value requirements.