<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>
Algorithms using the second order of B -splines [B (x)] and the third order of B -splines [B,3(x)] are derived to solve 1' , 2nd and 3rd linear Fredholm integro-differential equations (F1DEs). These new procedures have all the useful properties of B -spline function and can be used comparatively greater computational ease and efficiency.The results of these algorithms are compared with the cubic spline function.Two numerical examples are given for conciliated the results of this method.
In this Paper, we proposed two new predictor corrector methods for solving Kepler's equation in hyperbolic case using quadrature formula which plays an important and significant rule in the evaluation of the integrals. The two procedures are developed that, in two or three iterations, solve the hyperbolic orbit equation in a very efficient manner, and to an accuracy that proves to be always better than 10-15. The solution is examined with and with grid size , using the first guesses hyperbolic eccentric anomaly is and , where is the eccentricity and is the hyperbolic mean anomaly.
In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.
Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras
... Show MoreWith the revolutionized expansion of the Internet, worldwide information increases the application of communication technology, and the rapid growth of significant data volume boosts the requirement to accomplish secure, robust, and confident techniques using various effective algorithms. Lots of algorithms and techniques are available for data security. This paper presents a cryptosystem that combines several Substitution Cipher Algorithms along with the Circular queue data structure. The two different substitution techniques are; Homophonic Substitution Cipher and Polyalphabetic Substitution Cipher in which they merged in a single circular queue with four different keys for each of them, which produces eight different outputs for
... Show MoreReal life scheduling problems require the decision maker to consider a number of criteria before arriving at any decision. In this paper, we consider the multi-criteria scheduling problem of n jobs on single machine to minimize a function of five criteria denoted by total completion times (∑), total tardiness (∑), total earliness (∑), maximum tardiness () and maximum earliness (). The single machine total tardiness problem and total earliness problem are already NP-hard, so the considered problem is strongly NP-hard.
We apply two local search algorithms (LSAs) descent method (DM) and simulated annealing method (SM) for the 1// (∑∑∑
... Show More<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi
... Show MoreUncompressed form of the digital images are needed a very large storage capacity amount, as a consequence requires large communication bandwidth for data transmission over the network. Image compression techniques not only minimize the image storage space but also preserve the quality of image. This paper reveal image compression technique which uses distinct image coding scheme based on wavelet transform that combined effective types of compression algorithms for further compression. EZW and SPIHT algorithms are types of significant compression techniques that obtainable for lossy image compression algorithms. The EZW coding is a worthwhile and simple efficient algorithm. SPIHT is an most powerful technique that utilize for image
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