Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart.
Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics
Some researchers are interested in using the flexible and applicable properties of quadratic functions as activation functions for FNNs. We study the essential approximation rate of any Lebesgue-integrable monotone function by a neural network of quadratic activation functions. The simultaneous degree of essential approximation is also studied. Both estimates are proved to be within the second order of modulus of smoothness.
Abstract
This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine
... Show Moreتكمن أهمية ألبحث : تأثير تمرينات تأهيلية مصاحبة لجهاز التحفيز الكهربائي للعضلات العاملة في تخفيف الالآم أسفل الظهر للنساء بعمر (25-35) سنة والتعرف على مدى تأثير تلك التمرينات في تخفيف الألأم أسفل الظهر. وتكمن مشكلة البحث نتيجة للتقدم التكنولوجي حيث أصبحت حركة الفرد تقل شيئا فشيئا مما جعله أكثر عرضة للإصابات مما أدى الى ارتفاع نسبة عدد المصابات بالالآم أسفل الظهر وما لتلك الالام من تأثيراتها السلبية على حيا
... Show MoreThe Rate theory of crack growth in PVC pipe has been studied for creep and fatigue crack propagation. Rate theory function parameters, (RTFP), were estimated theoretically from exponential function parameters, (EFP), to experimental data of crack velocity versus stress intensity factor ,(V-K) diagram, to creep crack propagation . Also (RTFP) were estimated theoretically from (EFP) to experimental data of (V-?K) diagram to fatigue crack propagation. Temperature effect with (RTFP) was discussed. Crack velocity function denoted with stress intensity factor and temperature degrees has been determined to fatigue and creep crack propagation theoretically and comparative results this function with experimental data of (V-K or ?K) diagram .
The advertising has emerged as an effective force and an effective instrument upon with all organizations and companies depend on achieving their goals. In additional to the need to use promote sales, The nature and objective of advertising go beyond the scope of specific personal communication to a broader and more effective range for consumers from multiple groups and combination play need to use as well as the need to use means of communication than com convey the message more professional, The coincides with the rapid and remarkable development of all different media technologies and as much as possible social networking sites including mobile phone companies. The advertising has emerged as an effective force and an effective instrum
... Show MoreThe EMERGE application from Hampsson-Russell suite programs was used in the present study. It is an interesting domain for seismic attributes that predict some of reservoir three dimensional or two dimensional properties, as well as their combination. The objective of this study is to differentiate reservoir/non reservoir units with well data in the Yamama Formation by using seismic tools. P-impedance volume (density x velocity of P-wave) was used in this research to perform a three dimensional seismic model on the oilfield of Nasiriya by using post-stack data of 5 wells. The data (training and application) were utilized in the EMERGE analysis for estimating the reservoir properties of P-wave ve
... Show MoreIn this study, He's parallel numerical algorithm by neural network is applied to type of integration of fractional equations is Abel’s integral equations of the 1st and 2nd kinds. Using a Levenberge – Marquaradt training algorithm as a tool to train the network. To show the efficiency of the method, some type of Abel’s integral equations is solved as numerical examples. Numerical results show that the new method is very efficient problems with high accuracy.
Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was
... Show MoreThis paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere
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