Conditional inference plays a central role in logical and Bayesian reasoning, and is used in a wide range of applications. It basically consists of expressing conditional relationship between parent and child propositions, and then to combine those conditionals with evidence about the parent propositions in order to infer conclusions about the child propositions. While conditional reasoning is ...

Background: We designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the Artificial Neural Network (ANN). Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. Each patient’s record consisted of 6 subjec...

Rationale and Objective. To compare logistic regression and artificial neural network for computer-aided diagnosis on breast sonograms. Materials and Methods. Ultrasound images of 24 malignant and 30 benign masses were analyzed quantitatively for margin sharpness, margin echogenicity, and angular variation in margin. These features and age of patients were used with two pattern classifiers, log...

Due to the increased interests in environmental issues along with stringent legislation and regulations, companies start taking a fresh look at impact on their reverse logistic activties environment. This paper is an example of recovery valuable material that can be recycled/recovered or remanufactured end product useful life by designing effective logistics network. In this study, mixed intege...

The logistic network design is an abstract optimization problem that, under the assumption of minimal cost, seeks optimal configuration supply chain’s infrastructures and facilities based on customer demand. Key economic decisions are taken about location, number, size manufacturing warehouses solution. Therefore, improvements in methods to address this question, which known be NP-hard complexi...