scholarly journals The exposome – a new approach for risk assessment

ALTEX ◽  
2020 ◽  
pp. 3-23 ◽  
Author(s):  
Fenna Sillé
Keyword(s):  
1994 ◽  
Vol 57 (3) ◽  
pp. 95-98 ◽  
Author(s):  
Chris Iveson

A new approach to counselling, solution focused brief therapy, is based on assumptions of client well-being which are very close to those underlying the work of occupational therapists. Two cases, one of memory loss and one of suicide risk assessment, are used to illustrate the principles of brief therapy translated into everyday practice.


Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project’s research data shows that this new approach is capable of improving the existing COCOMO estimation performance.


2018 ◽  
pp. 771-797
Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project's research data shows that this new approach is capable of improving the existing COCOMO estimation performance.


2019 ◽  
Author(s):  
F. Silva ◽  
S. Fernandes ◽  
J. Casacão ◽  
C. Libório ◽  
J. Almeida ◽  
...  

Author(s):  
Cansu Dagsuyu ◽  
Murat Oturakci ◽  
Esra Sarac Essiz

In this study, a new approach to Fine-Kinney risk assessment method is developed in order to overcome the limitations of the conventional method with clustering algorithms. New risk level of classes are attempted to determine with K-Means and Hierarchical clustering algorithms with using two different distance functions which are Euclidean and Manhattan distances. According to the results, K-Means algorithms have provided accurate and sensitive cluster of classes. Classes from conventional and K-Means algorithms are applied and compared to the identified risks of a workshop of a medium sized textile company. Results of the study indicate that clustering techniques are new, original and applicable way to define new classes in order to prioritize risks by overcoming the drawbacks of conventional Fine-Kinney method.


Sign in / Sign up

Export Citation Format

Share Document