Atherosclerosis Risk Assessment using Rule-Based Approach

Author(s):  
Petr Berka ◽  
Marie Tomeckova
Author(s):  
A. A. Flippen ◽  
R. J. Navarro ◽  
A. M. Larsen ◽  
M. Stamatelatos

The safety of the public, the astronaut crew, Agency assets, other payloads, and the environment are NASA’s priorities when assessing the adequacy of space flight designs. While Probabilistic Risk Assessment (PRA) has been successfully applied to Space Shuttle and Space Station vehicle risk decision-making, the mandated use of a non-probabilistic rule-based approach is unique to the safety certification of NASA’s habitable payloads. A 1997 survey of historical safety policies with NASA’s Payload Safety Review Panel (PSRP) revealed that the non-probabilistic approach for habitable payloads was not arbitrary but founded on informed risk decisions from 20 years ago by then NASA Headquarters policy makers. Based on a sound payload safety track record, there has been no compelling reason, until recently, to consider expanding from the present NSTS 1700.7B rule-based approach to include risk-based PRA as a viable alternative. However, with the Agency’s increased focus on structured risk management, the establishment of a Risk Assessment Program at NASA Headquarters, and refined PRA guidelines and techniques, PRA is now formally recognized as an essential method for evaluating complex and high risk systems. The PSRP recognizes a growing need and an opportunity for evaluating the efficacy of risk-based PRA methods for application to increasingly complex next generation payload technologies. Therefore, it is timely to revisit the potential application of PRA to habitable payloads. This paper discusses PRA as a risk-based method that, when properly implemented, will result in equivalent or improed safety compared with the rule-based failure tolerance requirements for achieving the Agency’s “Safety First” core value. The benefits and cautions associated with infusing PRA methodology into the PSRP safety certification process are also discussed, as well as a proposed deployment strategy of how PRA might be prudently tailored and applied to habitable payloads. The use of PRA for assessing payload reliability is unrestricted at NASA but this is beyond the scope of the present discussion of payload safety applications.


Author(s):  
Padmavathi .S ◽  
M. Chidambaram

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.


2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK

2010 ◽  
Vol 12 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Xueying ZHNAG ◽  
Guonian LV ◽  
Boqiu LI ◽  
Wenjun CHEN

Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.


Author(s):  
Supriya Raheja ◽  
Geetika Munjal ◽  
Jyoti Jangra ◽  
Rakesh Garg

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