scholarly journals CloudWoT - A Reference Model for Knowledge-based IoT Solutions

2018 ◽  
Author(s):  
Abdelkader Magdy Shaaban ◽  
Christoph Schmittner ◽  
Thomas Gruber ◽  
A. Baith Mohamed ◽  
Gerald Quirchmayr ◽  
...  
Keyword(s):  
Reference Model ◽  
Knowledge Based

scholarly journals Augmenting the educational curriculum with the Visual Analytics Science and Technology Challenge: Opportunities and pitfalls

2013 ◽  
Vol 13 (4) ◽  
pp. 313-325 ◽  
Author(s):  
Christian Rohrdantz ◽  
Florian Mansmann ◽  
Chris North ◽  
Daniel A Keim
Keyword(s):  
Visual Analytics ◽  
Science And Technology ◽  
The United States ◽  
Virginia Tech ◽  
Learning Objectives ◽  
Classroom Setting ◽  
Educational Curriculum ◽  
The Core ◽  
Knowledge Based ◽  
The University

With its mission to move science into practice, the Visual Analytics Science and Technology Challenge has become an integrated part of the annual Visual Analytics Science and Technology Conference since its inception in 2006. In this article, we discuss how we can transfer this objective into a classroom setting by using the Visual Analytics Science and Technology Challenge datasets and by encouraging student submissions to the challenge. By means of Bloom’s Taxonomy of Educational Objectives for Knowledge-Based Goals, we show how the Visual Analytics Science and Technology Challenge enables the integration of additional learning objectives into two types of courses: a dedicated course that focuses on the contest participation and an integrated course that uses the contest data to emphasize practical course elements. The core contribution of this article is that we assess the opportunities and pitfalls that we experienced at the University of Konstanz in Germany and Virginia Tech in the United States when augmenting the educational curriculum with the Visual Analytics Science and Technology Challenge.

An Analytics Framework for Physician Adherence to Clinical Practice Guidelines: Knowledge-Based Approach (Preprint)

2018 ◽  
Author(s):  
Jaehoon Lee ◽  
Nathan C Hulse
Keyword(s):  
Clinical Practice ◽  
Knowledge Base ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Visual Analytics ◽  
Process Models ◽  
Care Process ◽  
Knowledge Based ◽  
Clinical Databases ◽  
Knowledge Content

BACKGROUND One of the problems in evaluating clinical practice guidelines (CPGs) is the occurrence of knowledge gaps. These gaps may occur when evaluation logics and definitions in analytics pipelines are translated differently. OBJECTIVE The objective of this paper is to develop a systematic method that will fill in the cognitive and computational gaps of CPG knowledge components in analytics pipelines. METHODS We used locally developed CPGs that resulted in care process models (CPMs). We derived adherence definitions from the CPMs, transformed them into computationally executable queries, and deployed them into an enterprise knowledge base that specializes in managing clinical knowledge content. We developed a visual analytics framework, whose data pipelines are connected to queries in the knowledge base, to automate the extraction of data from clinical databases and calculation of evaluation metrics. RESULTS In this pilot study, we implemented 21 CPMs within the proposed framework, which is connected to an enterprise data warehouse (EDW) as a data source. We built a Web–based dashboard for monitoring and evaluating adherence to the CPMs. The dashboard ran for 18 months during which CPM adherence definitions were updated a number of times. CONCLUSIONS The proposed framework was demonstrated to accommodate complicated knowledge management for CPM adherence evaluation in analytics pipelines using a knowledge base. At the same time, knowledge consistency and computational efficiency were maintained.

The Science of Interaction

2009 ◽  
Vol 8 (4) ◽  
pp. 263-274 ◽  
Author(s):  
William A. Pike ◽  
John Stasko ◽  
Remco Chang ◽  
Theresa A. O'Connell
Keyword(s):  
Best Practices ◽  
Visual Analytics ◽  
Embodied Interaction ◽  
Knowledge Based ◽  
Development Agenda ◽  
Information Interaction ◽  
Principles Of Design ◽  
Interactive Manipulation ◽  
The Relationship ◽  
Visual Interface

There is a growing recognition within the visual analytics community that interaction and inquiry are inextricable. It is through the interactive manipulation of a visual interface–the analytic discourse–that knowledge is constructed, tested, refined and shared. This article reflects on the interaction challenges raised in the visual analytics research and development agenda and further explores the relationship between interaction and cognition. It identifies recent exemplars of visual analytics research that have made substantive progress toward the goals of a true science of interaction, which must include theories and testable premises about the most appropriate mechanisms for human–information interaction. Seven areas for further work are highlighted as those among the highest priorities for the next 5 years of visual analytics research: ubiquitous, embodied interaction; capturing user intentionality; knowledge-based interfaces; collaboration; principles of design and perception; interoperability; and interaction evaluation. Ultimately, the goal of a science of interaction is to support the visual analytics and human–computer interaction communities through the recognition and implementation of best practices in the representation and manipulation of visual displays.

scholarly journals CP-driven Production Process Planning in Multiproject Environment

2008 ◽  
Vol 2 (2) ◽  
pp. 5-32 ◽  
Author(s):  
Zbigniew Banaszak ◽  
Grzegorz Bocewicz ◽  
Irena Bach
Keyword(s):  
Decision Support ◽  
Production Process ◽  
Process Planning ◽  
Reference Model ◽  
Decision Support Tool ◽  
Context Modeling ◽  
Support Tool ◽  
Knowledge Based ◽  
Formal Framework ◽  
Production Orders

The way enterprise capabilities are used decides about its competitiveness among other ones. In that context modeling aimed at production tasks allocation planning plays a crucial role especially at concurrently executed production orders. The introduced reference model employing constraint programming (CP) paradigm describes both an enterprise and a set of project-like production orders. Moreover, encompassing consumer orders requirements and available production capabilities, the model provides the formal framework allowing one to develop a class of decision support systems aimed at interactive production process planning subject to multiproject environment constraints. In that context our contribution is a knowledge-based and CP-driven approach to resource allocation assuming precise character of decision variables. The conditions sufficient for deadlock avoidance are the main goal. The conditions delivered provide formal framework for developing a task oriented Decision Support Tool for Project Portfolio Prototyping (DST4P, Banaszak 2006). The tool provides a prompt and interactive service to a set of routine queries formulated either in straight or reverse way.

scholarly journals Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution

2012 ◽  
Vol 68 (4) ◽  
pp. 381-390 ◽  
Author(s):  
Jeffrey J. Headd ◽  
Nathaniel Echols ◽  
Pavel V. Afonine ◽  
Ralf W. Grosse-Kunstleve ◽  
Vincent B. Chen ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Reference Model ◽  
Target Function ◽  
Quality Data ◽  
Low Resolution ◽  
Torsion Angles ◽  
Knowledge Based ◽  
Validation Criteria ◽  
Resolution Model ◽  
Use Of Knowledge

Traditional methods for macromolecular refinement often have limited success at low resolution (3.0–3.5 Å or worse), producing models that score poorly on crystallographic and geometric validation criteria. To improve low-resolution refinement, knowledge from macromolecular chemistry and homology was used to add three new coordinate-restraint functions to the refinement program phenix.refine. Firstly, a `reference-model' method uses an identical or homologous higher resolution model to add restraints on torsion angles to the geometric target function. Secondly, automatic restraints for common secondary-structure elements in proteins and nucleic acids were implemented that can help to preserve the secondary-structure geometry, which is often distorted at low resolution. Lastly, we have implemented Ramachandran-based restraints on the backbone torsion angles. In this method, a φ,ψ term is added to the geometric target function to minimize a modified Ramachandran landscape that smoothly combines favorable peaks identified from nonredundant high-quality data with unfavorable peaks calculated using a clash-based pseudo-energy function. All three methods show improved MolProbity validation statistics, typically complemented by a lowered R free and a decreased gap between R work and R free.

Prediction of Business Failure with Fuzzy Models

2018 ◽  
Vol 26 (Suppl. 1) ◽  
pp. 21-38
Author(s):  
Antonio Terceño ◽  
Hernán Vigier ◽  
Valeria Scherger
Keyword(s):  
Decision Making ◽  
Reference Model ◽  
Fuzzy Theory ◽  
Fuzzy Model ◽  
Financial Knowledge ◽  
Business Failure ◽  
Financial Situation ◽  
Owa Operators ◽  
Fuzzy Models ◽  
Knowledge Based

This paper extends the theory of fuzzy diseases predictions in order to detect the causes of business failure. This extension is justified through the advantages of the reference model and its originality. Moreover, the fuzzy model is completed by this proposal and some parts of it have been published in isolated articles. For this purpose, the fuzzy theory is combined with the OWA operators to identify the factors that generate problems in firms. Also, a goodness index to validate its functionality and prediction capacity is introduced. The model estimates a matrix of economic- financial knowledge based on matrices of causes and symptoms. Knowing the symptoms makes it possible to estimate the causes, and managing them properly, allows monitoring and improving the company’s financial situation and forecasting its future. Also with this extension, the model can be useful to develop suitable computer systems for monitoring companies’ problems, warning of failures and facilitating decision-making.

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