The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost.
Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreDisease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
... Show MoreAdvertisement on smart phone shopping apps are a new way of driving users to satisfy their needs and influence their purchasing decisions, In this way, the research could be aimed to know The role of the relationship between the motivations for audience exposure to shopping apps advertisement and purchasing decisions, In order to achieve the objectives of the research, the researcher adopted the survey method and used the questionnaire and the scale to collect data and information, The researcher chose the "random sample multi stages", The sample size was (475) respondents from Baghdad city center (18 years and above) women and men.
Zinc sulfide(ZnS) thin films of different thickness were deposited on corning glass with the substrate kept at room temperature and high vacuum using thermal evaporation technique.the film properties investigated include their absorbance/transmittance/reflectance spectra,band gap,refractive index,extinction coefficient,complex dielectric constant and thickness.The films were found to exhibt high transmittance(59-98%) ,low absorbance and low reflectance in the visible/near infrared region up to 900 nm..However, the absorbance of the films were found to be high in the ultra violet region with peak around 360 nm.The thickness(using optical interference fringes method) of various films thichness(100,200,300,and 400) nm.The band gap meas
... Show MoreIn this work the structural, electrical and optical Properties of CuO semiconductor films had been studied, which prepared at three thickness (100, 200 and 500 nm) by spray pyrolysis method at 573K substrate temperatures on glass substrates from 0.2M CuCl2•2H2O dissolved in alcohol. Structural Properties shows that the films have only a polycrystalline CuO phase with preferential orientation in the (111) direction, the dc conductivity shows that all films have two activation energies, Ea1 (0.45-0.66 eV) and Ea2 (0.055-.0185 eV), CuO films have CBH (Correlated Barrier Hopping) mechanism for ac-conductivity. The energy gap between (1.5-1.85 eV).
Theatrical techniques took upon themselves the responsibility of building and organizing the theatrical form for the various forms of performances, and it was the important tool that the show makers could rely on in carrying out the various works at the audio-visual level, and lighting is one of the most important elements of the visual formation of the image in the show, as it is related to the visual process and what it can achieve in operations The contrast that constitutes the aesthetic and intellectual values of the theatrical show, especially since the process of adjusting the element of time and the timings for receiving or delivering, moving, and the movement of the actor is what can determine the rhythm of the scene, which in it
... Show MoreAbstract: This paper presents the results of the structural and optical analysis of CdS thin films prepared by Spray of Pyrolysis (SP) technique. The deposited CdS films were characterized using spectrophotometer and the effect of Sulfide on the structural properties of the films was investigated through the analysis of X-ray diffraction pattern (XRD). The growth of crystal became stronger and more oriented as seen in the X-ray diffraction pattern. The studying of X-ray diffraction showed that; all the films have the hexagonal structure with lattice constants a=b=4.1358 and c=6.7156A°, the crystallite size of the CdS thin films increases and strain (ε) as well as the dislocation density (δ) decreases. Also, the optical properties of the
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