This paper deals with the nonlinear large-angle bending dynamic analysis of curved beams which investigated by modeling wave’s transmission along curved members. The approach depends on the wave propagation in one-dimensional structural element using the method of characteristics. The method of characteristics (MOC) is found to be a suitable method for idealizing the wave propagation inside structural systems. Timoshenko’s beam theory, which includes transverse shear deformation and rotary inertia effects, is adopted in the analysis. Only geometrical non-linearity is considered in this study and the material is assumed to be linearly elastic. Different boundary conditions and loading cases are examined.

From the results obtai

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation technique .. It was obse

Decision making is vital and important activity in field operations research ,engineering ,administration science and economic science with any industrial or service company or organization because the core of management process as well as improve him performance . The research includes decision making process when the objective function is fraction function and solve models fraction programming by using some fraction programming methods and using goal programming method aid programming ( win QSB )and the results explain the effect use the goal programming method in decision making process when the objective function is
fraction .

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

The Assignment model is a mathematical model that aims to express a real problem facing factories and companies which is characterized by the guarantee of its activity in order to make the appropriate decision to get the best allocation of machines or jobs or workers on machines in order to increase efficiency or profits to the highest possible level or reduce costs or time To the extent possible, and in this research has been using the method of labeling to solve the problem of the fuzzy assignment of real data has been approved by the tire factory Diwaniya, where the data included two factors are the factors of efficiency and cost, and was solved manually by a number of iterations until reaching the optimization solution,