Issues in the definition of a project support environment reference model

1993 ◽  
Vol 15 (5) ◽  
pp. 431-443
Author(s):  
A.W Brown ◽  
D.J Carney ◽  
P.H Feiler ◽  
P.A Oberndorf ◽  
M.V Zelkowitz
Keyword(s):  
Reference Model ◽  
Definition Of

Development and Evaluation of Fuzzy Criteria for the Diagnosis of Rheumatoid Arthritis

1996 ◽  
Vol 35 (04/05) ◽  
pp. 334-342 ◽  
Author(s):  
K.-P. Adlassnig ◽  
G. Kolarz ◽  
H. Leitich
Keyword(s):  
Rheumatoid Arthritis ◽  
Reference Model ◽  
American Rheumatism Association ◽  
Uniform Definition ◽  
Sensitivity Rate ◽  
Fuzzy Techniques ◽  
Definition Of ◽  
Different Levels ◽  
Specificity Rate

Abstract:In 1987, the American Rheumatism Association issued a set of criteria for the classification of rheumatoid arthritis (RA) to provide a uniform definition of RA patients. Fuzzy set theory and fuzzy logic were used to transform this set of criteria into a diagnostic tool that offers diagnoses at different levels of confidence: a definite level, which was consistent with the original criteria definition, as well as several possible and superdefinite levels. Two fuzzy models and a reference model which provided results at a definite level only were applied to 292 clinical cases from a hospital for rheumatic diseases. At the definite level, all models yielded a sensitivity rate of 72.6% and a specificity rate of 87.0%. Sensitivity and specificity rates at the possible levels ranged from 73.3% to 85.6% and from 83.6% to 87.0%. At the superdefinite levels, sensitivity rates ranged from 39.0% to 63.7% and specificity rates from 90.4% to 95.2%. Fuzzy techniques were helpful to add flexibility to preexisting diagnostic criteria in order to obtain diagnoses at the desired level of confidence.

Semantics Enhancing Knowledge Discovery and Ontology Engineering Using Mining Techniques

2011 ◽  
pp. 163-188
Author(s):  
Elena Irina Neaga
Keyword(s):  
Knowledge Discovery ◽  
Knowledge Engineering ◽  
Reference Model ◽  
Distributed Processing ◽  
Ontology Engineering ◽  
Software Architectures ◽  
Model Driven ◽  
Architectural Models ◽  
Definition Of ◽  
Comprehensive Framework

This chapter deals with a roadmap on the bidirectional interaction and support between knowledge discovery (Kd) processes and ontology engineering (Onto) mainly directed to provide refined models using common methodologies. This approach provides a holistic literature review required for the further definition of a comprehensive framework and an associated meta-methodology (Kd4onto4dm) based on the existing theories, paradigms, and practices regarding knowledge discovery and ontology engineering as well as closely related areas such as knowledge engineering, machine/ontology learning, standardization issues and architectural models. The suggested framework may adhere to the Iso-reference model for open distributed processing and Omg-model-driven architecture, and associated dedicated software architectures should be defined.

Designing a M-Health Framework for Conceptualizing Mobile Health Systems

2011 ◽  
pp. 1-24 ◽  
Author(s):  
Phillip Olla ◽  
Joseph Tan
Keyword(s):  
Health System ◽  
Health Systems ◽  
Mobile Networks ◽  
High Speed ◽  
Reference Model ◽  
Mobile Telecommunication ◽  
Technological Infrastructure ◽  
Key Dimensions ◽  
Definition Of ◽  
Health Field

The reference model presented in this chapter encourages the breakdown of m-health systems into the following five key dimensions: communication infrastructure: this is a description of the mobile telecommunication technologies and networks; device type: this relates to the type of device being used such as PDA, sensor, or tablet PC; data display: describes how the data will be displayed to the user and transmitted such as images, e-mail and textual data; application purpose: identification of the objective for the m-health system; application domain: definition of the area that the system will be implemented. Healthcare stakeholders and system implementer can use the reference model presented in this chapter to understand the security implications of the proposed system, identify the technological infrastructure, business requirements and operational needs of the m-health systems being implemented. A reference model to encapsulate the emerging m-health field is needed for cumulative progress in this field. Currently, the m-health field is disjointed and it is often unclear what constitutes an m-health system. In the future, m-health applications will take advantage of technological advances such as device miniaturizations, device convergence, high-speed mobile networks, and improved medical sensors. This will lead to the increased diffusion of clinical m-health systems requiring better understanding of the components, which constitute the m-health system.

The M-Health Reference Model

2011 ◽  
pp. 455-473
Author(s):  
Phillip Olla ◽  
Joseph Tan
Keyword(s):  
Health System ◽  
Health Systems ◽  
Mobile Networks ◽  
High Speed ◽  
Reference Model ◽  
Mobile Telecommunication ◽  
Technological Infrastructure ◽  
Key Dimensions ◽  
Definition Of ◽  
Health Field

The reference model presented in this article encourages the breakdown of M-Health systems into the following five key dimensions: (1) Communication Infrastructure: a description of mobile telecommunication technologies and networks; (2) Device Type: the type of device being used, such as PDA, sensor, or tablet PC; (3) Data Display: describes how the data will be displayed to the user and transmitted, such as images, email, and textual data; (4) Application Purpose: identification of the objective for the M-Health system; (5) Application Domain: definition of the area in which the system will be implemented. Healthcare stakeholders and system implementer can use the reference model presented in this article to understand the security implications of the proposed system and to identify the technological infrastructure, business requirements, and operational needs of the M-Health systems being implemented. A reference model that encapsulates the emerging M-Health field is needed for cumulative progress in this field. Currently, the M-Health field is disjointed, and it is often unclear what constitutes an M-Health system. In the future, M-Health applications will take advantage of technological advances such as device miniaturizations, device convergence, high-speed mobile networks, and improved medical sensors. This will lead to the increased diffusion of clinical M-Health systems, which will require better understanding of the components that constitute the M-Health system.

How much drinking water can be saved by using rainwater harvesting on a large urban area? Application to Paris agglomeration

2014 ◽  
Vol 70 (11) ◽  
pp. 1782-1788 ◽  
Author(s):  
Ali Belmeziti ◽  
Olivier Coutard ◽  
Bernard de Gouvello
Keyword(s):  
Drinking Water ◽  
Urban Area ◽  
Potable Water ◽  
Rainwater Harvesting ◽  
Reference Model ◽  
Total Current ◽  
Large Urban Area ◽  
Residential Sector ◽  
Definition Of ◽  
Building Level

This paper is based on a prospective scenario of development of rainwater harvesting (RWH) on a given large urban area (such as metropolitan area or region). In such a perspective, a new method is proposed to quantify the related potential of potable water savings (PPWS) indicator on this type of area by adapting the reference model usually used on the building level. The method is based on four setting-up principles: gathering (definition of buildings-types and municipalities-types), progressing (use of an intermediate level), increasing (choice of an upper estimation) and prioritizing (ranking the stakes of RWH). Its application to the Paris agglomeration shows that is possible to save up to 11% of the total current potable water through the use of RWH. It also shows that the residential sector offers the most important part because it holds two-thirds of the agglomeration PPWS.

A SCORM Compliant Courseware Authoring Tool for Supporting Pervasive Learning

2010 ◽  
pp. 557-580
Author(s):  
Te-Hua Wang ◽  
Flora Chia-I Chang
Keyword(s):  
Learning Environment ◽  
Reference Model ◽  
Authoring Tool ◽  
Multimodal Learning ◽  
Web Technologies ◽  
Digital World ◽  
Compliant Systems ◽  
Definition Of ◽  
Content Object ◽  
Pervasive Learning

The sharable content object reference model (SCORM) includes a representation of distance learning contents and a behavior definition of how users should interact with the contents. Generally, SCORM-compliant systems were based on multimedia and Web technologies on PCs. We further build a pervasive learning environment, which allows users to read SCORM-compliant textbooks with multimodal learning devices. Respecting the learning contents for supporting such learning environment, an efficient authoring tool was developed for serving this goal. Some specific tags were defined to specify the corresponding information or interactions that cannot be performed in the hardcopy books. These tags can be printed in SCORM-compliant textbooks and recognized by Hyper Pen to facilitate the affinity between the physical textbooks and digital world. Therefore, users can read the SCORM-compliant hardcopy textbooks in a traditional manner. The authored course contents will be the same while applying to the multimodal learning devices with different layouts.

The M-Health Reference Model

2009 ◽  
pp. 432-450
Author(s):  
Phillip Olla ◽  
Joseph Tan
Keyword(s):  
Health System ◽  
Health Systems ◽  
Mobile Networks ◽  
High Speed ◽  
Reference Model ◽  
Mobile Telecommunication ◽  
Technological Infrastructure ◽  
Key Dimensions ◽  
Definition Of ◽  
Health Field

The reference model presented in this article encourages the breakdown of M-Health systems into the following five key dimensions: (1) Communication Infrastructure: a description of mobile telecommunication technologies and networks; (2) Device Type: the type of device being used, such as PDA, sensor, or tablet PC; (3) Data Display: describes how the data will be displayed to the user and transmitted, such as images, email, and textual data; (4) Application Purpose: identification of the objective for the M-Health system; (5) Application Domain: definition of the area in which the system will be implemented. Healthcare stakeholders and system implementer can use the reference model presented in this article to understand the security implications of the proposed system and to identify the technological infrastructure, business requirements, and operational needs of the M-Health systems being implemented. A reference model that encapsulates the emerging M-Health field is needed for cumulative progress in this field. Currently, the M-Health field is disjointed, and it is often unclear what constitutes an M-Health system. In the future, M-Health applications will take advantage of technological advances such as device miniaturizations, device convergence, high-speed mobile networks, and improved medical sensors. This will lead to the increased diffusion of clinical M-Health systems, which will require better understanding of the components that constitute the M-Health system.

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