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This open access book presents a new generation multi-criteria, multi-stake holder, decision aide, called an "institutional compass". Based on hard data, the compass tells us what quality-direction we are heading in as an institution, region, system or organisation. The quality is not chosen from the usual scalar qualities of: good, neutral and bad. Instead, it is a quality chosen between: harmony, discipline and excitement. None is good in and of itself. We need some of each. The compass marks a new generation in four respects. 1. The representation of the data is intuitive and simple to understand, and therefore can be used to communicate and justify policy decisions. 2. Any data can be included, i.e., none is excluded. This makes the compass tailored to particular situations, voices and contexts. 3. The data includes different time horizons and different types of value: monetary, use, social, sentimental, religious, intrinsic, existential... 4. The process of compass construction can be made inclusive at several junctions. An institutional compass can be extended to evaluate products, add normativity to a systems analysis, reflect world-views such as that of ecological economists or function as an accounting system to manage scarce resources. There are four parts to the book. The first part introduces the general ideas behind the compass. In the second part, the author presents the method for constructing the compass. This includes data collection, data analysis and a mathematical formula to aggregate the data into a single holistic reading. In the third part, the author extends the methodology: to incorporate it into systems science, adding a normative and quality-direction dimension, to use it as a non-linear accounting method and more thoroughly to reflect the philosophy of ecological economists to give a real measure of sustainability. In the fourth part, we see three case studies: one for the World Health Organisation, a second is the use of the compass to label products in a shop and the third is as a regional compass for Hauts-de-France. The book ends with philosophical conclusions. Throughout the book, we see tight arguments, refreshing ideas and a thorough treatment of objectivity in decision making.

Sociology: work & labour --- Operational research --- Databases --- Social & political philosophy --- Data Representation --- Ecological Economics --- Institutional Analysis --- Multi-Criteria Decision Aides --- Non-Linear Accounting --- Policy Analysis/Justification --- Policy Decisions --- Qualitative Data Analysis --- Qualitative Objectivity --- tool for the assessment of an institution --- quantitative and qualitative assessment --- comparative institutional analysis --- qualitative indicators for institution --- measuring institutions --- policy analysis reader --- Adaptation of the institutional compass to ecological economics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book presents a new generation multi-criteria, multi-stake holder, decision aide, called an "institutional compass". Based on hard data, the compass tells us what quality-direction we are heading in as an institution, region, system or organisation. The quality is not chosen from the usual scalar qualities of: good, neutral and bad. Instead, it is a quality chosen between: harmony, discipline and excitement. None is good in and of itself. We need some of each. The compass marks a new generation in four respects. 1. The representation of the data is intuitive and simple to understand, and therefore can be used to communicate and justify policy decisions. 2. Any data can be included, i.e., none is excluded. This makes the compass tailored to particular situations, voices and contexts. 3. The data includes different time horizons and different types of value: monetary, use, social, sentimental, religious, intrinsic, existential... 4. The process of compass construction can be made inclusive at several junctions. An institutional compass can be extended to evaluate products, add normativity to a systems analysis, reflect world-views such as that of ecological economists or function as an accounting system to manage scarce resources. There are four parts to the book. The first part introduces the general ideas behind the compass. In the second part, the author presents the method for constructing the compass. This includes data collection, data analysis and a mathematical formula to aggregate the data into a single holistic reading. In the third part, the author extends the methodology: to incorporate it into systems science, adding a normative and quality-direction dimension, to use it as a non-linear accounting method and more thoroughly to reflect the philosophy of ecological economists to give a real measure of sustainability. In the fourth part, we see three case studies: one for the World Health Organisation, a second is the use of the compass to label products in a shop and the third is as a regional compass for Hauts-de-France. The book ends with philosophical conclusions. Throughout the book, we see tight arguments, refreshing ideas and a thorough treatment of objectivity in decision making.

Political philosophy. Social philosophy --- Theory of knowledge --- Sociology: work and labour --- Operations research. --- Databases. --- Social and political philosophy --- Data Representation --- Ecological Economics --- Institutional Analysis --- Multi-Criteria Decision Aides --- Non-Linear Accounting --- Policy Analysis/Justification --- Policy Decisions --- Qualitative Data Analysis --- Qualitative Objectivity --- tool for the assessment of an institution --- quantitative and qualitative assessment --- comparative institutional analysis --- qualitative indicators for institution --- measuring institutions --- policy analysis reader --- Adaptation of the institutional compass to ecological economics

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This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.

History of engineering & technology --- semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources --- semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.

semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources