Assessing health service needs:tools for health planning.

As fiscal pressures mount, health-planning and decision-making at smaller geographics scales must be more effective. Involving local constituents in needs assessments, it is believed, would lead to better identification and serving of regional demands and needs for health services. This article examines needs assessment as a tool to determine a community's service needs and establish priorities for the creation of programs. Various approaches used in needs assessments are described, including survey methods, structured groups and geographic information systems.

An intelligent configuration-sampling based local motion planner for robotic manipulators

Manipulator motion planning is a task which relies heavily on the construction of a configuration space prior to path planning. However when fast real-time motion is needed, the full construction of the manipulator's high-dimensional configu-ration space can be too slow and expensive. Alternative planning methods, which avoid this full construction of the manipulator's configuration space are needed to solve this problem. Here, one such existing local planning method for manipulators based on configuration-sampling and subgoal-selection has been extended. Using a modified Artificial Potential Fields (APF) function, goal-configuration sampling and a novel subgoal selection method, it provides faster, more optimal paths than the previously proposed work. Simulation results show a decrease in both runtime and path lengths, along with a decrease in unexpected local minimum and crashing issues.

Analysis of electric vehicle charging using the traditional generation expansion planning analysis tool WASP-IV

Electric vehicles (EV) are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems. Optimal benefits can only be achieved, if EVs are deployed effectively, so that the exhaust emissions are not substituted by additional emissions in the electricity sector, which can be implemented using Smart Grid controls. This research presents the results of an EV roll-out in the all island grid (AIG) in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV (WASP-IV) tool to measure carbon dioxide emissions and changes in total energy. The model incorporates all generators and operational requirements while meeting environmental emissions, fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch. In the study three distinct scenarios are investigated base case, peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.

Optimal Route Search with the Coverage of Users' Preferences

The preferences of users are important in route search and planning. For example, when a user plans a trip within a city, their preferences can be expressed as keywords shopping mall, restaurant, and museum, with weights 0.5, 0.4, and 0.1, respectively. The resulting route should best satisfy their weighted preferences. In this paper, we take into account the weighted user preferences in route search, and present a keyword coverage problem, which finds an optimal route from a source location to a target location such that the keyword coverage is optimized and that the budget score satisfies a specified constraint. We prove that this problem is NP-hard. To solve this complex problem, we pro- pose an optimal route search based on an A* variant for which we have defined an admissible heuristic function. The experiments conducted on real-world datasets demonstrate both the efficiency and accu- racy of our proposed algorithms.

Risk-aware Planning in BDI Agents

The ability of an autonomous agent to select rational actions is vital in enabling it to achieve its goals. To do so effectively in a high-stakes setting, the agent must be capable of considering the risk and potential reward of both immediate and future actions. In this paper we provide a novel method for calculating risk alongside utility in online planning algorithms. We integrate such a risk-aware planner with a BDI agent, allowing us to build agents that can set their risk aversion levels dynamically based on their changing beliefs about the environment. To guide the design of a risk-aware agent we propose a number of principles which such an agent should adhere to and show how our proposed framework satisfies these principles. Finally, we evaluate our approach and demonstrate that a dynamically risk-averse agent is capable of achieving a higher success rate than an agent that ignores risk, while obtaining a higher utility than an agent with a static risk attitude.

Self-perceptions of the role of the planner

The role of the planning practitioner has received considerable attention in a diverse range of theoretical and empirical debates within the broad spectrum of planning scholarship from normative debates surrounding the planner's role in society, to more empirical investigations into the skills, attributes, and evolving nature of planning practitioners. Fundamental questions surrounding the role and purpose of planners have also entered into more mainstream discussions as the democratic nature of the planning system has been consistently undermined by allegations of misconduct, corruption, and incompetence. Despite the broad range of literature and debate which centres on the role of the planner, relatively few studies have explored the views of planning practitioners themselves, making it difficult to judge whether the ideas of planning academics are actually shared by those in the field. In this paper we seek to address this particular gap and argue that such insights are critical in determining the extent to which planning practitioners serve to challenge, maintain, or reinforce existing power imbalances in the planning system. The methodology consists of a series of qualitative interviews with twenty local authority planners working throughout the Greater Dublin Area, Ireland. The results suggest that planners' self-perceptions of their role tend to reflect traditional pluralist and managerialist perspectives. More broadly, the results suggest that the role orientations of contemporary planners are being shaped by dominant discourses in current planning ideology — namely, collaborative and participatory approaches

Morality, Power and the Planning Subject

Ethical issues are at the heart of planning. Thus, planning theory has long displayed an interest in debating both the ethical justification for planning and how the activity of planning can be rendered more ethically sensitive. However, comparatively little attention has been shown to how the very constitution of the planner as a ‘moral subject’ may be ethically problematic for planning practice. This article addresses this lacuna through an engagement with the philosophy of Michel Foucault. In contrast to how his work is normally applied, this article accords with Foucault’s own direction that his later examination of ethics be used as a lens through which to read his earlier analysis of power and knowledge. Accordingly, the article first outlines Foucault’s innovative reinterpretation of how power and knowledge operate in society before setting this within his novel reconception of ethics. This theoretical exposition is then employed to interpret the material drawn from in-depth qualitative interviews with 20 planning officers working in a range of different contexts. The article subsequently employs Foucault’s ethically informed reading of power and knowledge to identify ethical issues arising from the approaches used by practitioners to justify their planning activities. The article concludes by suggesting how such issues can be resolved.

A Two-Stage Online Approach for Collaborative Multi-Agent Planning under Uncertainty

In a team of multiple agents, the pursuance of a common goal is a defining characteristic. Since agents may have different capabilities, and effects of actions may be uncertain, a common goal can generally only be achieved through a careful cooperation between the different agents. In this work, we propose a novel two-stage planner that combines online planning at both team level and individual level through a subgoal delegation scheme. The proposal brings the advantages of online planning approaches to the multi-agent setting. A number of modifications are made to a classical UCT approximate algorithm to (i) adapt it to the application domains considered, (ii) reduce the branching factor in the underlying search process, and (iii) effectively manage uncertain information of action effects by using information fusion mechanisms. The proposed online multi-agent planner reduces the cost of planning and decreases the temporal cost of reaching a goal, while significantly increasing the chance of success of achieving the common goal. 

Extracellular vesicle biogenesis in helminths: more than one route to the surface?

The quite recent discovery that parasites release extracellular vesicles (EVs) that can transfer a range of effector molecules to host cells has made us re-think our understanding of the host-parasite interface. In this opinion article we will consider how recent proteomics and transcriptomics studies, together with ultrastructural observations, suggest that more than one mechanism of EV biogenesis can occur in helminths. We propose that distinct EV sub-types have roles in immune-modulation and repair of drug-induced damage, and put forward the case for targeting EV biogenesis pathways to achieve parasite control. In doing so we raise a number of outstanding research questions that must be addressed before this can happen.

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

A Collaborative Multiagent Framework based on Online Risk-Aware Planning and Decision-Making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions.