The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256) in our research, compressed them by using MLP for each compression process the number of neurons in the hidden layer was changing and calculating the compression ratio, mean square error and peak signal-to-noise ratio to compare the results to get the value of original image. The findings of the research was the desired results as the compression ratio was less than five and a few mean square error thus a large value of peak signal-to-noise ratio had been recorded.
This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio
... Show MoreThe aim of this paper is introducing the concept of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal. Some properties of (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal have been studied and another characterizations have been given. The relationship of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal that states, a B- -module Ӽ is (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal , if and only if for any two ɱ-element sub-sets and of Ӽɳ, if , for each j = 1, …, ɱ, i = 1,…, ɳ and implies Ạɳ( ) Ạɳ( have been proved..
People may believe that tissue of normal brain and brain with benign tumor
have the same statistical descriptive measurements that are significantly different
from the of brain with malignant tumor. Thirty brain tumor images were collected
from thirty patients with different complains (10 normal brain images, 10 images
with benign brain tumor and 10 images with malignant brain tumor). Pixel
intensities are significantly different for all three types of images and the F-test was
measured and found equal to 25.55 with p-value less than 0.0001. The means of
standard deviations and coefficients of variation showed that pixel intensities from
normal and benign tumors images are almost have the same behavior whereas the
New class A^* (a,c,k,β,α,γ,μ) is introduced of meromorphic univalent functions with positive coefficient f(z)=□(1/z)+∑_(n=1)^∞▒〖a_n z^n 〗,(a_n≥0,z∈U^*,∀ n∈ N={1,2,3,…}) defined by the integral operator in the punctured unit disc U^*={z∈C∶0<|z|<1}, satisfying |(z^2 (I^k (L^* (a,c)f(z)))^''+2z(I^k (L^* (a,c)f(z)))^')/(βz(I^k (L^* (a,c)f(z)))^''-α(1+γ)z(I^k (L^* (a,c)f(z)))^' )|<μ,(0<μ≤1,0≤α,γ<1,0<β≤1/2 ,k=1,2,3,… ) . Several properties were studied like coefficient estimates, convex set and weighted mean.
Risk factors can be considered unique in construction projects, especially in tendering phase. This research is directed to recognize and evaluate the importance of critical risk factors in the tendering phase related to Iraq’s construction project. As a rule, construction projects are impacted by risk factors throughout the project life cycle; without identifying and allocating these risk factors, the project cannot succeed. In this paper, the open and closed questionnaires are used to categorize the critical risk factors in tendering phase. Research aims to recognize the factors that influence the success of tendering phase, to determine the correct response to the risk’s factors in this research article, (IBM, SPSS, V23) package has
... Show MoreThe general objective of surface shape descriptors techniques is to categorize several surface shapes from collection data. Gaussian (K) and Mean (H) curvatures are the most broadly utilized indicators for surface shape characterization in collection image analysis. This paper explains the details of some descriptions (K and H), The discriminating power of 3D descriptors taken away from 3D surfaces (faces) is analyzed and present the experiment results of applying these descriptions on 3D face (with polygon mesh and point cloud representations). The results shows that Gaussian and Mean curvatures are important to discover unique points on the 3d surface (face) and the experiment result shows that these curvatures are very useful for some
... Show MoreRisk factors can be considered unique in construction projects, especially in tendering phase. This research is directed to recognize and evaluate the importance of critical risk factors in the tendering phase related to Iraq’s construction project. As a rule, construction projects are impacted by risk factors throughout the project life cycle; without identifying and allocating these risk factors, the project cannot succeed. In this paper, the open and closed questionnaires are used to categorize the critical risk factors in tendering phase. Research aims to recognize the factors that influence the success of tendering phase, to determine the correct response to the risk’s factors in this research article, (IBM, SPSS, V23) package has
... Show MoreVideo steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the
... Show MoreIn this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.
the Current research aims to identify the psychological stressors coping strategies and their relationship to the cognitive motivation among Al-Anbar University students through the following hypotheses: 1) no statistically significant differences at a level (0.05) among the sample according to the instrumental support strategy depending on the variable type and specialization, 2) No statistically significant differences at a level (0.05) among the sample in regard of coping avoiding strategy depending on the variable type and specialization, 3) There is no statistically significant difference at a level (0.05) in cognitive motivation level among Al-Anbar University students, 4) No statistically significant differences at a level (0.05)
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