Lessons Learned from Automated Analysis of Industrial UML Class Models (An Experience Report)  

2005 ◽  
pp. 324-338 ◽  
Author(s):  
Betty H. C. Cheng ◽  
Ryan Stephenson ◽  
Brian Berenbach
Keyword(s):  
Automated Analysis ◽  
Lessons Learned ◽  
Experience Report ◽  
Class Models

scholarly journals Lessons learned from ten investigations of waterborne gastroenteritis outbreaks, France, 1998–2006

2008 ◽  
Vol 6 (4) ◽  
pp. 491-503 ◽  
Author(s):  
Pascal Beaudeau ◽  
Henriette de Valk ◽  
Véronique Vaillant ◽  
Christian Mannschott ◽  
Claude Tillier ◽  
...  
Keyword(s):  
Waste Water ◽  
Public Health Surveillance ◽  
Automated Analysis ◽  
Lessons Learned ◽  
Water Network ◽  
Health Insurance Data ◽  
Point Of Entry ◽  
Health Authorities ◽  
Maintenance Work ◽  
Insurance Data

Ten outbreaks of waterborne acute gastroenteritis (AGE) have been investigated in France since 1998. These outbreaks have affected populations of over 1,000 people, with generally high attack rates. The causal agents have been identified in six of these events. Aetiologies involved mainly noroviruses and Cryptosporidium sp. The point of entry of the contamination was located in the distribution network in five outbreaks (waste water backflows in four cases and one case of contamination induced by maintenance work) and at the water collection facilities in five other cases. Once the outbreak was detected, epidemiological and environmental investigations and crisis management followed well-established procedures. Further progress in public health surveillance will depend on more complete and rapid detection and reporting. Automated analysis of health insurance data on the reimbursement of drugs for AGE should help make detection more complete. Improved reactivity depends primarily on the operator immediately reporting incidents that indicate a possible massive contamination of the water network to health authorities – in particular complaints from the population, which are the only early-warning alerts in the case of waste water backflows.

scholarly journals Screening for Cervical Cancer Using Automated Analysis of PAP-Smears

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ewert Bengtsson ◽  
Patrik Malm
Keyword(s):  
Cervical Cancer ◽  
Pap Smear ◽  
Cost Effective ◽  
Automated Analysis ◽  
Lessons Learned ◽  
Pap Smears ◽  
Turn Of The Millennium ◽  
Prevention Measure ◽  
Key Issues ◽  
Analysis System

Cervical cancer is one of the most deadly and common forms of cancer among women if no action is taken to prevent it, yet it is preventable through a simple screening test, the so-called PAP-smear. This is the most effective cancer prevention measure developed so far. But the visual examination of the smears is time consuming and expensive and there have been numerous attempts at automating the analysis ever since the test was introduced more than 60 years ago. The first commercial systems for automated analysis of the cell samples appeared around the turn of the millennium but they have had limited impact on the screening costs. In this paper we examine the key issues that need to be addressed when an automated analysis system is developed and discuss how these challenges have been met over the years. The lessons learned may be useful in the efforts to create a cost-effective screening system that could make affordable screening for cervical cancer available for all women globally, thus preventing most of the quarter million annual unnecessary deaths still caused by this disease.

scholarly journals A Problem-based Approach to teach physical database design: an experience report

2020 ◽  
Author(s):  
João Marcelo Borovina Josko
Keyword(s):  
Learning Process ◽  
Problem Based Learning ◽  
Database Design ◽  
Lessons Learned ◽  
Experience Report ◽  
Learning Approach ◽  
Database Performance ◽  
Physical Database Design ◽  
Performance Problems

This work presents our first experience in applying a Problem-Based Learning approach to improving students’ abilities on how to analyze and evaluate database performance problems. The preliminary qualitative results reveal our approach contribution to students learning process. Additionally, we also discuss key lessons learned and indicate some future areas of improvement.

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