Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem

The aim of the research to apply TD-ABC technology to determine the idle capacity of the central oil companies (oil field east of Baghdad), as a modern cost management technology based on time-oriented activities (TD-ABC) is used by industrial companies in general and oil companies on In particular to build a sustainable Calvinist pillar and make future decisions by identifying idle energy to gain it a competitive advantage, the descriptive analytical approach has been adopted in calculating and analyzing the company’s data for 2018, and the most prominent conclusions of this research are managing idle energy and the task of applying cost technology on the basis of time-oriented activities and providing Convenient spatial infor

Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Iraq is highly dependent on international markets to provide food for its residents. As imported food prices are highly dependent on crude oil prices in global markets, any shock in oil prices will have an impact on food consumption in the country. As a result, it is essential to study the demand for imported food at every time period. To the best of our knowledge as researchers, as not even a single study is available in the literature, this paper is considered the first to study the demand for imported food groups in Iraq. Therefore, the main objective of this research is to estimate demand elasticities for several imported food categories in Iraq. This study uses an Almost Ideal Demand System model to analyze the demand for imported f

This study employs a critical discourse analysis approach to investigate the linguistic and discursive mechanisms employed by the prominent Russian online news platform Gazeta.ru in its coverage of social news. Drawing on an interdisciplinary framework integrating critical discourse analysis (CDA), media discourse analysis, and sociolinguistic perspectives, the research examines how language is used to construct and disseminate societal narratives. The analysis focuses on a dataset of Gazeta.ru articles published in March 2024, encompassing topics such as health, travel, and consumer affairs. Through a multi-level analytical approach, the study explores macro-level discursive strategies and microlevel linguistic choices, unveiling the intri

Delays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement

Integrated project delivery is collaboratively applying the skills and knowledge of all participants to optimize the project's results, increase owner value, decrease waste, and maximize efficiency during the design, fabrication, and construction processes. This study aims to determine IPD criteria positively impacting value engineering. To do this, the study has considered 9 main criteria according to PMP classification that already covers all project phases and 183 sub-criteria obtained from theoretical study and expert interviews (fieldwork). In this study, the SPSS (V26) program was used to analyze the main criteria and sub-criteria priorities from top to bottom according to their values of the Relative Importance In

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data