By Kevin Dooley, Ian Brown
Everyone who has labored with Cisco routers for any size of time has needed to ask their associates and associates for instance router configuration documents that express find out how to resolve a typical challenge. a great operating configuration instance can frequently keep large quantities of time and frustration whilst imposing a function that you've by no means used prior to. The Cisco Cookbook gathers hundreds of thousands of instance router configurations multi functional position. because the identify indicates, Cisco Cookbook is prepared as a sequence of recipes. every one recipe starts off with an issue assertion that describes a standard scenario that you simply may well face. After every one challenge assertion is a quick resolution that exhibits a pattern router configuration or script for you to use to solve this actual challenge. A dialogue part then describes the answer, the way it works, and in case you may still or are not use it. The chapters are prepared through the function or protocol mentioned. when you are trying to find info on a specific characteristic comparable to NAT, NTP or SNMP, you could flip to that bankruptcy and discover a number of similar recipes. so much chapters checklist uncomplicated difficulties first, and any strange or advanced events final. The Cisco Cookbook will speedy turn into your "go to" source for gaining knowledge of and fixing advanced router configuration matters, saving you time and making your community extra effective.
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They were able to categorize the subjects based on how their muscle responses were classified. The ANN classifier found distinct clusters of two groups of response patterns, whereby the muscle activity of subjects categorized as majority-type responders were in better correspondence with optimization-based predicted forces. An ANN for the simulation of lumbar muscle response to static-moment loads was created by Nussbaum et al. (1997). Based on an abstract representation of a motor control system in which muscle activity is driven primarily to maintain equilibrium, a 4-layered feed forward and fully interconnected MLP was employed.
1996) Breast cancer benign/malignant Weak when evidence on the image is considered weak by the expert Breast nodules Ultrasonic images 24-dimensional image feature vector benign/malignant 2 MLPs: one for malignant, one for benign (27/4/1) (27/14/2/1) compared with experts MLP (25/10/1) Chen et al. (1999) Delen et al. (2004) Comparison methods Breast cancer survivability Survived Not survived 1) Decision tree 2) MLP(17/15/2) 3) Log reg Downs et al. (1996) 1) Coronary care 2) Breast cancer 3) Myocardial infarction ?
Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 24 Schöllhorn & Jäger The results of contrasting the PLANN model with the clinically accepted proportional hazards model were that the two are consistent, but the neural network may be more specific in the allocation of patients into prognostic groups using a default procedure. The probability of relapse after surgery is objective to the MLP model of GomezRuiz et al. (2004). The model is based only on six attributes including tumor size, patient age, or menarchy age and is able to make an appropriate prediction about the relapse probability at different times of follow up.