Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

Study the effect of additives polymer polyvinyl alcohol (PVA) after solving in water by concentration 10% since represent a standard of PVA solution with added to cement – silica composite of ratio (1:2) with 5%, 10%, 15%, 20%, and 25% respectively to the standard quantity of water which using as a mortar of building. The results are demonstrate increasing on compression resistance with increase of PVA solution until 20%, and decreasing of thermal conductivity which represent a composite are increasing in thermal insulating. The results were recommended decreasing of water absorption with increase of PVA solution ratio as illustrated in this study.

The scarcity of irrigation water requires procedures of specific. One of these procedures is the implementation of the rationing system (a period of the irrigation followed by a period of the dry). This system can have an impact on the properties of irrigation channels. Therefore, the study of rationing system for irrigation channels is important in both water resources and civil engineering, especially if they are constructed with gypseous soil. In order to assess the rationing system on gypseous canals stabilized with a specific ratio of cement, practical experiments were conducted to detect the effect of wetting and drying cycles on the physical and hydraulic behavior of this soil and calculation of some properties of soil such a

The need for Dewatering is very important in construction workshops field and sometimes it needs to pay more attention as a result of its impacts on causing additional settlement of nearby pile foundations. Dewatering construction may become a costly topic if ignored during project planning and designing .In this paper a simplified procedure maybe adopted to calculate the foundation settlement induced by using dewatering system which is required to lower the water table level to reach a dry condition during construction. Synthesized case study adopted at a specified location in Baghdad city and analysis are computed for two types of piles both of them are submerged with water. Results shows the effect of dewatering on pile foundatio

Foundations supporting reciprocating engines, radar towers, turbines, large electric motors, and generators, etc. are subject to vibrations caused by unbalanced machine forces as well as the static weight of the machine. If these vibrations are excessive, they may damage the machine or cause it not to function properly. In the case of block foundation, if changes in size and mass of the foundation do not lead to a satisfactory design, a pile foundation may be used. In this study, the dynamic response of piles and pile Groups in dry sand is investigated experimentally. The analysis involves the displacement response under harmonic excitation. In addition, a numerical modeling by using finite element method with a three-dimensional formula

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia