ABSTRACT
Scientific Workflows (SWfs) have revolutionized how scientists in various domains of science conduct their experiments. The management of SWfs is performed by complex tools that provide support for workflow composition, monitoring, execution, capturing, and storage of the data generated during execution. In some cases, they also provide components to ease the visualization and analysis of the generated data. During the workflow's composition phase, programs must be selected to perform the activities defined in the workflow specification. These programs often require additional parameters that serve to adjust the program's behavior according to the experiment's goals. Consequently, workflows commonly have many parameters to be manually configured, encompassing even more than one hundred in many cases. Wrongly parameters' values choosing can lead to crash workflows executions or provide undesired results. As the execution of data- and compute-intensive workflows is commonly performed in a high-performance computing environment e.g., (a cluster, a supercomputer, or a public cloud), an unsuccessful execution configures a waste of time and resources. In this article, we present FReeP-Feature Recommender from Preferences, a parameter value recommendation method that is designed to suggest values for workflow parameters, taking into account past user preferences. FReeP is based on Machine Learning techniques, particularly in Preference Learning. FReeP is composed of three algorithms, where two of them aim at recommending the value for one parameter at a time, and the third makes recommendations for n parameters at once. The experimental results obtained with provenance data from two broadly used workflows showed FReeP usefulness in the recommendation of values for one parameter. Furthermore, the results indicate the potential of FReeP to recommend values for n parameters in scientific workflows.
ABSTRACT
Os autores fazem revisäo dos mecanismos fisiopatológicos propostos para a neuralgia essencial do trigêmio considerando aspectos anatômicos básicos para o entendimento dos mesmos
Subject(s)
Humans , Trigeminal Neuralgia/physiopathologyABSTRACT
Os autores tecem consideraçöes sobre o tratamento clínico e cirúrgico da neuralgia essencial do trigênio e apontam o efeito benéfico da indicaçäo do propranolol em pacientes com resistência ao tratamento com a carbamazepina isoladamente ou em associaçäo
Subject(s)
Trigeminal Neuralgia/drug therapy , Propranolol/therapeutic use , Carbamazepine/therapeutic use , Drug Therapy, Combination , Trigeminal Neuralgia/surgeryABSTRACT
Os autores tecem consideracoes sobre o tratamento clinico e cirurgico da neuralgia essencial do trigemio e apontam o efeito benefico da indicacao do propranolol em pacientes com resistencia ao tratamento com a carbamazepina isoladamente ou em associacao.
Subject(s)
Trigeminal Neuralgia , Propranolol , Carbamazepine , Drug Therapy, Combination , Trigeminal Neuralgia , Propranolol , Carbamazepine , Drug Therapy, CombinationABSTRACT
Os autores fazem revisao dos mecanismos fisiopatologicos propostos para a neuralgia essencial do trigemeo considerando aspectos anatomicos basicos para o entendimento dos mesmos.