<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver operating characteristic ROC). Dataset was downloaded from UCI ml repository; it is composed of 9 attributes and 699 samples. The findings are clearly showing that the RBF NN classifier is the best in prediction of the type of breast tumors since it had recorded the highest performance in terms of correct classification rate (accuracy), sensitivity, specificity, and AUC (area under Receiver Operating Characteristic ROC) among all other models.</p>
Background: Squamous cell carcinoma (SCC) is the most prevalent malignant neoplasm of the oral cavity that exhibits certain histological variations. Verrucous carcinoma (VC) is an uncommon exophytic low-grade well-differentiated variant of SCC. Cellular differentiation and morphology play important roles in cell functions and maintenance of structural integrity .As the cancer is a malignant process in which disorder of the cell growth and behavior occurs, such changes may differ in different tumor types and within different grades of the same tumor. Materials and Methods:Forty two formalin – fixed, paraffin – embedded tissue blocks were included in this study (30 blocks were diagnosed as OSCC and 12 blocks were diagnosed as OV
... Show MoreThe grain hardness, wet and dry gluten contents, protein and ash contents are determined in grains from different cultivars of wheat which are important in food products, either which are present in raw materials or in final products. Wheat is also a very important food raw material, and flour as the final product of milling. The importance of knowing the physical and chemical properties of wheat and flour is due to the determination of quality and kind of flour which is produced after the milling process. In this work, some physical and chemical properties of different wheat cultivars are determined and the comparisons of these characteristics are performed in both wheat and flour. Uruq Wheat sample (W5) has the highest results when compar
... Show MoreAmino acids were analyzed in stomach regions of males & females of Felis catus (Domestic Cat) & Sciurus carolinesis (Eastern Gray Squirrel ), where it was stated that there are (18) amino acids as following : Aspartic acid (Asp), Glutamic acid (Gla), Serine (Ser), Arginine (Arg), Aspargine ( Asn), Cysteine (Cys), Alanine (Ala), Proline (Pro), Glyscine (Gly), Threonine (Thr), Tyrosine (Tyr), Valine (Val), Methionine (Met), Histidine ( His), Isoleucine (ile), Leucine (leu), Phenylalanine (Phe ) and Lysine (lys). Results have shown there are significant differences in concentration of amino acids between different region of stomach between males & females of Felis catus in part and between males & females of Sciurus carolinesis (Eastern Gray S
... Show MoreA comparative study was carried out on ecological and genetical adaptation of three Iraqi
freshwater snails, Physa acuta, Melanopsis buccinoidea and Melanoides tuberculata, in
respect to acute toxicity of heavy metals (Zn, Cd and Hg). Longevity are used as poisoning
tolerance criterion. LT 50 and LT 100 were determined for the studied snails at (0.5, 1, 5, and
10 ppm), for the three metals. Results indicated that Physa acuta had a higher tolerance than
Melanopsis buccinoidea and Melanoides tuberculata, which was the lower one. Previous
exposure to heavy metals in the original habitat was affecting on experimental tolerance and
no relationships of physical and chemical factors (total hardness, temperature, D. O. and
In this research, the Williamson-Hall method and of size-strain plot method was employed to analyze X- ray lines for evaluating the crystallite size and lattice strain and of cadmium oxide nanoparticles. the crystallite size value is (15.2 nm) and (93.1 nm) and lattice strain (4.2 x10−4 ) and (21x10−4) respectively. Also, other methods have been employed to evaluate the crystallite size. The current methods are (Sherrer and modified Sherrer methods ) and their results are (14.8 nm) and (13.9nm) respectively. Each method of analysis has a different result because the alteration in the crystallite size and lattice strain calculated according to the Williamson-Hall and size-strain plot methods shows that the non-uniform strain in nan
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MorePath planning in autonomous robotic systems (ARS) is challenging, especially in dynamic or uncertain environments. Many classical methods are computationally expensive and lack adaptability to real-world scenarios. In order to improve the overall path-planning capabilities of robots; this paper introduces a new smart robotic navigation system which uses Software Defined Network (SDN) and Multi-Spike Elman Neural Network (MS-ENN). The introduced system includes an innovative way to encode temporal information using multiple spikes which can capture much greater amounts of detail about changing environmental characteristics than conventional artificial neural networks. Additionally, it includes a spiking wave-front planner (SWP) to pr
... Show MoreThe estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t
... Show MoreVariable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.