Nowadays, one of the main problems encountered in minimally invasive surgery and telesurgery is the detection of arteries in tissue. In this study, for the first time, tactile detection of an artery in tissue and distinguishing it from the tumor has been modeled by finite element method. In this modeling, three 2D models of tissue have been created: tissue, tissue including a tumor, and tissue ...

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the “conventional” SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials...

Peter G. Anderson Roger S. Gaborski Ming Ge Sanjay Raghavendra Mei-Ling Lung Abstract We present a novel training algorithm for a feed forward neural network with a single hidden layer of nodes (i.e., two layers of connection weights). Our algorithm is capable of training networks for hard problems, such as the classic two-spirals problem. The weights in the rst layer are determined using a qua...

We used an advanced computer logic system (NETS 3.0) to decipher electromagnetic (EM) scans in lieu of traditional linear regression for estimation of pork carcass composition. Fifty EM scans of pork carcasses were obtained on-line (prerigor) at a swine slaughter facility. Right sides were cut into wholesale parts and dissected into fat, lean, and bone to obtain total dissected carcass and prim...

in this paper, we present a binary-linear optimization model to prevent the spread of an infectious disease in a community. the model is based on the remotion of some connections in a contact network in order to separate infected nodes from the others. by using this model we nd an exact optimal solution and determine not only the minimum number of deleted links but also their exact positions. ...