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

The dynamic thermomechanical properties, sealing ability, and voids formation of an experimental obturation hydroxyapatite-reinforced polyethylene (HA/PE) composite/carrier system were investigated and compared with those of a commercial system [GuttaCore (GC)]. The HA/PE system was specifically designed using a melt-extrusion process. The viscoelastic properties of HA/PE were determined using a dynamic thermomechanical analyser. Human single-rooted teeth were endodontically instrumented and obturated using HA/PE or GC systems, and then sealing ability was assessed using a fluid filtration system. In addition, micro-computed tomography (μCT) was used to quantify apparent voids within the root-canal space. The data were statistically analys

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.

           Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,

In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

An electrolytic process for the removal of Zn(II) from aqueous solution using a parallel amalgamated copper screens cathode operated in the flow through mode is proposed. The current-potential curves recorded at a rotating amalgamated copper disc electrode were used to determine diffusion coefficient of Zn(II). The performance of electrolytic reactor was investigated by using different flow rates at initial zinc ion concentration(48 mg/L). Taking into account the residential Zn(II) concentration, the best results were obtained for cathode potential of (-1.35 V vs. SCE) at flow rate (320 L/h). Zinc ion concentration was found to decrease from 48 mg/L to 1 mg/L during 120 min. of electrolysis. The experimental data are well correlate

The performance grading system (superpave) has provided means to incorporate binder characteristics with
pavement failure types. It’s a comprehensive system that relates climate, traffic conditions and aging with
critical pavement distress. The objective of this paper is to develop an improved asphalt binder grading
system for Iraq based on the principal of superpave. The country was divided into different zones according
to the highest and lowest temperature ranges and traffic loading. The Performance graded binder proposed
for each zone was compared with some States of USA that have same hot weather of Iraq by using Long
Term Pavement Performance (LTPP v3.1) software. Iraqi asphalt samples were tested using the Supe

In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

In this paper, the Active Suspension System (ASS) of road vehicles was investigated. In addition to the conventional stiffness and damper, the proposed ASS includes a fuzzy controller, a hydraulic actuator, and an LVDT position sensor. Furthermore, this paper presents a nonlinear model describing the operation of the hydraulic actuator as a part of the suspension system. Additionally, the detailed steps of the fuzzy controller design for such a system are introduced. A MATLAB/Simulink model was constructed to study the proposed ASS at different profiles of road irregularities. The results have shown that the proposed ASS has superior performance compared to the conventional Passive Suspension System (PSS), where the body displacemen

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used