In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as  (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.

Background: the aim of this study was to assess the value of serum thyroid–stimulating hormone (TSH) levels in predicting malignancy in patients with nodular thyroid disease (NTD). Objective: The aim was to examine the relationship between preoperative TSH and differentiated thyroid cancer (DTC).
Patients and Method: all patients with NTD who were admitted in the first surgical unit of Baghdad teaching hospital and assessed for preoperative TSH level before subjecting them for thyroidectomy from first of April 2014 to 31 of January 2016, were included in the study. A preoperative database sheets including Age, gender, nodule size, and pathology were evaluated. Logistic regression analysis was used t

Several methods have been developed for routing problem in MANETs wireless network, because it considered very important problem in this network ,we suggested proposed method based on modified radial basis function networks RBFN and Kmean++ algorithm. The modification in RBFN for routing operation in order to find the optimal path between source and destination in MANETs clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. The re

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

The presented work shows a preliminary analytic method for estimation of load and pressure distributions on low speed wings with flow separation and wake rollup phenomena’s. A higher order vortex panel method is coupled with the numerical lifting line theory by means of iterative procedure including models of separation and wake rollup. The computer programs are written in FORTRAN which are stable and efficient.

      The capability of the present method is investigated through a number of test cases with different types of wing sections (NACA 0012 and GA(W)-1) for different aspect ratios and angles of attack, the results include the lift and drag curves, lift and pressure distributions along the wing s

Lung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr