Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. This paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. The proposed method includes three main modules: the feature extraction module, the classifier module, and the optimization module. In ...

A prototype system has been designed to automate the extraction of bibliographic data (e.g., article title, authors, abstract, affiliation and others) from online biomedical journals to populate the National Library of Medicine’s MEDLINE® database. This paper describes a key module in this system: the labeling module that employs statistics and fuzzy rule-based algorithms to identify segmented ...

We propose a fuzzy-based approach which provides a soft threshold to determine the module size for CMOS circuit partitioning in built-in current testing (BICT). Experimental results show that our design approach indeed provides a feasible way to exploit the design space of BICT partitioning in comparison with other approaches with a fixed threshold, and a better module size can thus be determin...

An automated labeling (AL) module has been developed to automate the extraction of bibliographic data (e.g., article title, authors, affiliation, abstract, and others) from online biomedical journals for the National Library of Medicine’s MEDLINE database. The AL module employs string matching, statistics, and fuzzy rule-based algorithms to identify segmented zones in an article’s HTML pages a...

In this paper, an alternative battery charging control technique based on fuzzy logic for photovoltaic (PV) applications is presented. A PV module is connected to a buck type DC/DC power converter and a microcontroller based unit is used to control the lead acid battery charging voltage. The fuzzy control is used due to the simplicity of implementation, robustness and independence from the comp...

In this paper, the notions of (T, S)-composition matrix and (T, S)interval-valued intuitionistic fuzzy equivalence matrix are introduced where (T, S) is a dual pair of triangular module. They are the generalization of composition matrix and interval-valued intuitionistic fuzzy equivalence matrix. Furthermore, their properties and characterizations are presented. Then a new method based on α̃−mat...

Short-term prediction of traffic flow is central to alleviating congestion and controlling the negative impacts of environmental pollution resulting from vehicle emissions on both inter- and intra-urban highways. The strong need to monitor and control congestion time and costs for metropolis in developing countries has therefore motivated the current study. This paper establishes the applicatio...

This paper gives a description of an adaptative on-line diagnosis system for the detection of slow varying changes in dynamical systems. This fault detection system is based on both a learning and a supervisor module. The learning module acts as an adaptatif fuzzy classiier i.e. its parameters are updated on-line. The supervisor module controls the learning periods of the classiier, it makes th...

In this paper we describ� Category ART, a variation on the adaptive resonance theory (ART) neural network models. Category ART is a predictive ART architecture because it incorporates an ART module to be able to learn to predict a prescribed category given a prescribed n-dimensional input vector a. In contrast to ARTMAP, Category ART contains only one ART module and the map field algorithm has ...

A hybrid knowledge-and-model-based advisory system for intensive care ventilators has been developed. The system consists of two parts: a knowledge-based toplevel module using neural fuzzy technology and a model-based lower-level module consisting of 4 sub-units. The system generates advice on four ventilator settings (the inspired fraction of oxygen (FiO2), positive end-expiratory pressure (PE...