Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

Disease 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

The study focused on the identification of the natural relation between the organizational components, and the most important is the organizational structure, which not hid its effect on each function and operation of the organizational structure through commanding the individual craters and its forms according to the requirement of these function, also it has relation with an organic synthesis that between the dimensions of the organic synthesis and the practice side in the commission of Integrity.

The problem of the research pensioned in some questions about hypothesis and theoretical parts, in which they go a mention about the hypothesis questions is to use all the knowledge's in this atmosphere and th

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

This paper examines the mechanical properties of a composite material made of modified Iraqi gypsum (juss) reinforced with polypropylene fibers. The modified juss was prepared by adding two percentages of cement (5, 10) %. Two percentages of polypropylene fibers were used, to reinforce the modified juss (1, 2) %. The water/dry compound ratio used was equal to 0.53%. The composite was evaluated based on compressive strength, flexural strengths, absorption percentage, density, acoustic impedance, ultra - pulse velocity, longitudinal shrinkage and setting time tests. The results indicated that the inclusion of cement on to juss increases the compressive strength, absorption percentage, density, acoustic impedance, ultra - pulse velocit

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

Energy Loss Function (ELF) of 2 5 Ta O derived from optical limit
and extended to the total part of momentum and their energy
excitation region ELF plays an important function in calculating
energy loss of electron in materials. The parameter Inelastic Mean
Free Path (IMFP) is most important in quantitative surface sensitive
electron spectroscopies, defined as the average distance that an
electron with a given energy travels between successive inelastic
collisions. The stopping cross section and single differential crosssection
SDCS are also calculated and gives good agreement with
previous work.

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o