Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Community Development Evaluation Storymap and Legend

Community based organizations, funders, and intermediary organizations working in the community development field have a shared interest in building stronger organizations and stronger communities. Through evaluation these organizations can learn how their programs and activities contribute to the achievement of these goals, and how to improve their effectiveness and the well-being of their communities. Yet, evaluation is rarely seen as part of a non-judgemental organizational learning process. Instead, the term "evaluation" has often generated anxiety and confusion. The Community Development Storymap project is a response to those concerns.Illustrations found in this document were produced by Grove Consultants

A hydrogen framework for the East Midlands

Profiles capabilities in midlands-based organisations in hydrogen and fuel cell technologies as a rationale for support of a Midlands hydrogen cluster

Funding Media, Strengthening Democracy: Grantmaking for the 21st Century

Despite the pervasiveness of media, the amount of philanthropic dollars in support of public interest media remains minuscule and, therefore largely ineffective. The report, based on a survey of the the funding sector, calls on philanthropists to embrace a practice of transparency and information sharing via technology, to determine how existing funds are being used and how they can best be leveraged to increase philanthropic impact within the media field

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Intelligent policy making? Key actors' perspectives on the development and implementation of a national early years' initiative

Increased political enthusiasm for evidence-based policy and action has re-ignited interest in the use of evidence within political and practitioner networks. Theories of evidence-based policy making and practice are being re-considered in an attempt to better understand the processes through which knowledge translation occurs. Understanding how policy develops, and practice results, has the potential to facilitate effective evidence use. Further knowledge of the factors which shape healthcare delivery and their influence in different contexts is needed.<p></p> This paper explores the processes involved in the development of a complex intervention in Scotland's National Health Service (NHS). It uses a national oral health programme for children (Childsmile) as a case study, drawing upon key actors' perceptions of the influence of different drivers (research evidence, practitioner knowledge and values, policy, and political and local context) to programme development. Framework analysis is used to analyse stakeholder accounts from in-depth interviews. Documentary review is also undertaken.<p></p> Findings suggest that Childsmile can be described as an ‘evidence-informed’ intervention, blending available research evidence with knowledge from practitioner experience and continual learning through evaluation, to plan delivery. The importance of context was underscored, in terms of the need to align with prevailing political ideology and in the facilitative strength of networks within the relatively small public health community in Scotland. Respondents' perceptions support several existing theoretical models of translation, however no single theory offered a comprehensive framework covering all aspects of the complex processes reported. Childsmile's use of best available evidence and on-going contribution to knowledge suggest that the programme is an example of intelligent policy making with international relevance.<p></p&gt

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Supporting decision making process with "Ideal" software agents: what do business executives want?

According to Simon’s (1977) decision making theory, intelligence is the first and most important phase in the decision making process. With the escalation of information resources available to business executives, it is becoming imperative to explore the potential and challenges of using agent-based systems to support the intelligence phase of decision-making. This research examines UK executives’ perceptions of using agent-based support systems and the criteria for design and development of their “ideal” intelligent software agents. The study adopted an inductive approach using focus groups to generate a preliminary set of design criteria of “ideal” agents. It then followed a deductive approach using semi-structured interviews to validate and enhance the criteria. This qualitative research has generated unique insights into executives’ perceptions of the design and use of agent-based support systems. The systematic content analysis of qualitative data led to the proposal and validation of design criteria at three levels. The findings revealed the most desirable criteria for agent based support systems from the end users’ point view. The design criteria can be used not only to guide intelligent agent system design but also system evaluation