Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

    The problem statement discussed in this paper is a new technique for the presentation of painterly rendering that uses a K-mean segmentation to divide the input image into a set of regions (depending on the grayscale of the regions). Segmenting the input image helps users use different brush strokes and easily change the strokes' shape, size, or orientation for different regions. Every region is painted using different brush kinds. The properties of the brush strokes are chosen depending on the region's details. The brush stroke properties, such as size, color, shape, location, and orientation, are extracted from the source image using statistical tools. The number of regions is set up manually and depends on the input image. This

We have studied some types of ideals in a KU-semigroup by using the concept of a bipolar fuzzy set. Bipolar fuzzy S-ideals and bipolar fuzzy k-ideals are introduced, and some properties are investigated. Also, some relations between a bipolar fuzzy k-ideal and k-ideal are discussed. Moreover, a bipolar fuzzy k-ideal under homomorphism and the product of two bipolar fuzzy k-ideals are studied.

Some structures such as tall buildings, offshore platforms, and bridge bents are subjected to lateral loads of considerable magnitude due to wind and wave actions, ship impacts, or high-speed vehicles. Significant torsional forces can be transferred to the foundation piles by virtue of eccentric lateral loading. The testing program of this study includes one group consists of 3 piles, four percentages of allowable vertical load were used (0%, 25%, 50%, and 100%) with two L/D ratios 20 and 30, vertical allowable load 110 N for L/D = 20 and 156 N for L/D = 30. The results obtained indicate that the torsional capacity for pile group increases with increasing the percentage of allowable vertical load, when the percentage of allowable vertica

Background: A role for vitamin D deficiency in Parkinson disease (PD) has recently been suggested.

Objective:: To estimate the state of vitamin D in PD with an age-matched healthy control.

Type of the study: A case control study.

Method: The study randomly comparison of plasma 25-hydroxyvitamin D (25[OH] D) concentrations of collected samples in a clinical neurology department ward / Baghdad teaching hospital / Medical City and Parkinson disease movement disorder clinic. Participants were registered into the study from October 2015 to October 2016. We was study   serum vitamin D level in 40 consecutive patients with

Background: Osteoporosis is a systemic skeletal disorder that has an impact on general health, dental health and salivary composition. The mineralization of teeth happens simultaneously with that of the skeleton, but if mineral metabolism is disrupted, tooth failures will resemble those that affect bone tissue. Vitamin D plays a key role in bone and tooth mineralization.

Objective: to evaluate the impact of osteoporosis on teeth decay in relation to salivary vitamin D among menopause in Baghdad city.

Subjects and Methods: This study was cross sectional study. The study group consists of

  M D simulation of Imidazole aqueous solution at 298.15, 303.15 and 308.15 K was carried out by using OPLS force field from this simulation we calculate RDF of N-H… OH2 and N…HOH type of interactions, the results show that the hydration shell around N-H site at 5A0 decade with the increase of temperature and reformed at 10A0, so N site has two conserved hydration shells at approximate 4 and 6A0 respectively these are stable in this temperature range but the order and number of water molecules are varying with temperature specially the hydration shell at 4A0

Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th