dtControl: Decision Tree Learning Algorithms for Controller Representation

Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent provably-correct controllers concisely. Compared to representations using lookup tables or binary decision diagrams, decision trees are smaller and more explainable. We present dtControl, an easily extensible tool for representing memoryless controllers as decision trees. We give a comprehensive evaluation of various decision tree learning algorithms applied to 10 case studies arising out of correct-by-construction controller synthesis. These algorithms include two new techniques, one for using arbitrary linear binary classifiers in the decision tree learning, and one novel approach for determinizing controllers during the decision tree construction. In particular the latter turns out to be extremely efficient, yielding decision trees with a single-digit number of decision nodes on 5 of the case studies

Синтез оптимального варіанта інтегрованого рішення з конкурентоспроможності машинобудівної продукції

Для вибору оптимального варіанта інтегрованого рішення щодо забезпечення відповідного рівня конкурентоспроможності продукції запропоновано використання морфологічного аналізу та синтезу. Виконано побудову морфологічної множини рішень у вигляді морфологічних таблиць та розроблено метод синтезу оптимального варіанта інтегрованого рішення щодо забезпечення та підвищення конкурентоспроможності машинобудівної продукції.Для выбора оптимального варианта интегрированного решения по обеспечению соответствующего уровня конкурентоспособности продукции предлагается использование морфологического анализа и синтеза. Выполнено построение морфологического множества решений в виде морфологических таблиц и разработан метод синтеза оптимального варианта интегрированного решения по обеспечению и повышению конкурентоспособности машиностроительной продукции.There is offered the use of morphological analysis and synthesis for the choice of optimum variant of integrated decision on providing of the proper level of products competitiveness. In the article there is executed the construction of morphological multitude of decisions as morphological tables and developed the method of synthesis of optimum variant of integrated decision on providing and increase of competitiveness of machine-building products

Вибір оптимального варіанта управлінського рішення по забезпеченню конкурентоспроможності продукції машинобудування

Для упорядкування множини управлінських рішень запропоновано формування морфологічних таблиць. Розроблено методику вибору управлінського рішення на підставі морфологічного аналізу і синтезу з використанням кластерного аналізу.Для упорядочения множества управленческих решений предложено формирование морфологических таблиц. Разработана методика выбора управленческого решения на основании морфологического анализа и синтеза с использованием кластерного анализа.For organization of great number of administrative decisions forming of morphological tables is offered. The method of choice of administrative decision on the basis of morphological analysis and synthesis with the use of cluster analysis is developed

The use of ‘PICO for synthesis’ and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions

INTRODUCTION: Systematic reviews involve synthesis of research to inform decision making by clinicians, consumers, policy makers and researchers. While guidance for synthesis often focuses on meta-analysis, synthesis begins with specifying the ’PICO for each synthesis’ (i.e. the criteria for deciding which populations, interventions, comparators and outcomes are eligible for each analysis). Synthesis may also involve the use of statistical methods other than meta-analysis (e.g. vote counting based on the direction of effect, presenting the range of effects, combining P values) augmented by visual display, tables and text-based summaries. This study examines these two aspects of synthesis. OBJECTIVES: To identify and describe current practice in systematic reviews of health interventions in relation to: (i) approaches to grouping and definition of PICO characteristics for synthesis; and (ii) methods of summary and synthesis when meta-analysis is not used. METHODS: We will randomly sample 100 systematic reviews of the quantitative effects of public health and health systems interventions published in 2018 and indexed in the Health Evidence and Health Systems Evidence databases. Two authors will independently screen citations for eligibility. Two authors will confirm eligibility based on full text, then extract data for 20% of reviews on the specification and use of PICO for synthesis, and the presentation and synthesis methods used (e.g. statistical synthesis methods, tabulation, visual displays, structured summary). The remaining reviews will be confirmed as eligible and data extracted by a single author. We will use descriptive statistics to summarise the specification of methods and their use in practice. We will compare how clearly the PICO for synthesis is specified in reviews that primarily use meta-analysis and those that do not. CONCLUSION: This study will provide an understanding of current practice in two important aspects of the synthesis process, enabling future research to test the feasibility and impact of different approaches

Development of an algorithm for automated cause-consequence diagram construction.

Cause-consequence analysis is one of the best tools available for a comprehensive reliability study. The cause-consequence diagram (CCD) method, like fault tree analysis, represents the failure logic of the system, but in addition the CCD also identifies the complete set of consequences following a given initiating event. While there are well-developed commercialized software packages for fault tree evaluation and construction, no satisfactory methodology has been published for automated cause-consequence chart synthesis. Hence this paper outlines the development of an algorithm for automated causeconsequence diagram construction. The algorithm builds on methods developed previously for fault tree construction, such as topology diagrams, describing how components are linked together in a system, and component decision tables which model component behaviour. Using this information rules have been developed which enable the construction of the CCD. Once constructed the diagram can be quantified to give exact system reliability. To demonstrate the construction the algorithm is applied to a simple example

An Eye-Opening Approach to Developing and Communicating Integrated Environmental Assessments

Communication among managers, the public, and scientists is the key to successful ecosystem management; however, the varied perspectives and interests of these groups can make such communication difficult. One way to achieve effective communication is to develop a common knowledge base by combining syntheses of key scientific results with information-rich visual elements. Within a management landscape, integrated environmental assessments provide a useful framework for evaluating resources and directing management efforts. The integrated assessment process involves (1) initial investigation, (2) development of a conceptual framework, (3) data navigation, (4) environmental report cards, and (5) science communication. Each step requires the synthesis and visualization of information on the status and trends connected with multiple natural resources. We provide a case study, using examples from selected National Park Service sites in the mid-Atlantic region of the United States. Visual elements (conceptual diagrams, maps, graphs, tables, and photographs) were used to facilitate comparative assessments and to provide a more visual, or eye-opening , approach to effective environmental decision making

What guidance are researchers given on how to present network meta-analyses to end-users such as policymakers and clinicians? A systematic review

© 2014 Sullivan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: Network meta-analyses (NMAs) are complex methodological approaches that may be challenging for non-technical end-users, such as policymakers and clinicians, to understand. Consideration should be given to identifying optimal approaches to presenting NMAs that help clarify analyses. It is unclear what guidance researchers currently have on how to present and tailor NMAs to different end-users. Methods: A systematic review of NMA guidelines was conducted to identify guidance on how to present NMAs. Electronic databases and supplementary sources were searched for NMA guidelines. Presentation format details related to sample formats, target audiences, data sources, analysis methods and results were extracted and frequencies tabulated. Guideline quality was assessed following criteria developed for clinical practice guidelines. Results: Seven guidelines were included. Current guidelines focus on how to conduct NMAs but provide limited guidance to researchers on how to best present analyses to different end-users. None of the guidelines provided reporting templates. Few guidelines provided advice on tailoring presentations to different end-users, such as policymakers. Available guidance on presentation formats focused on evidence networks, characteristics of individual trials, comparisons between direct and indirect estimates and assumptions of heterogeneity and/or inconsistency. Some guidelines also provided examples of figures and tables that could be used to present information. Conclusions: Limited guidance exists for researchers on how best to present NMAs in an accessible format, especially for non-technical end-users such as policymakers and clinicians. NMA guidelines may require further integration with end-users' needs, when NMAs are used to support healthcare policy and practice decisions. Developing presentation formats that enhance understanding and accessibility of NMAs could also enhance the transparency and legitimacy of decisions informed by NMAs.The Canadian Institute of Health Research (CIHR) Drug Safety and Effectiveness Network (Funding reference number – 116573)