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Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination by considering the traffic segment status when choosing the next intersection. RTISAR presents a new formula for assessing segment status based on connectivity, density, load segment, and cumulative distance toward the destination. A verity period mechanism is proposed to denote the projected period when a network failure is likely to occur in a particular segment. This mechanism can be calculated for each collector packet to minimize the frequency of RTISAR execution and to control the generation of collector packets. As a result, this mechanism minimizes the communication overhead generated during the segment status computation process. Simulations are performed to evaluate RTISAR, and the results are compared with those of intersection-based connectivity aware routing and traffic flow oriented routing. The evaluation results provided evidence that RTISAR outperforms in terms of packet delivery ratio, packet delivery delay, and communication overhead.

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
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Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

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Publication Date
Wed Sep 12 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Two Conventional Methods for Identification of Dermatophyte Fungi
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The current study is the identification and isolation dermatophyte species in clinical isolates by both Sabouraud’s Dextrose Agar (SDA) and on Dermatophyte Test Medium (DTM). Clinical specimens of hair, nails and skin scales were collected from patients with dermatophytosis and submitted to direct microscopic examination after immersion in 20% of potassium hydroxide solution. The clinical specimens were cultured on SDA containing chloramphenicol and cycloheximide, and on DTM. Tinea corporis showed the highest prevalent dermatophyte infection among patients (26.7%), followed by Tinea pedis (23.3%), whereas Tinea manuum exhibited the lowest fungal infection (6.7 %). Rural areas revealed the highest prevalence of dermatophyte in

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Publication Date
Thu Nov 01 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Impact of functional disability on lifestyle for patients with arthritis
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A descriptive study, which was using an assessment approach, was conducted for the
determination of the impact of rheumatoid arthritis and osteoarthritis patient’s functional disability
upon their life style. The study was carried out at the Rheumatology and outpatients clinics of ALKarama
Teaching Hospital, Baghdad Teaching Hospital AL-Kindey Teaching Hospital and Specialized
surgeries Teaching Hospital for the period of October 15th 2003 through May 13th 2004 in Baghdad
City. A purposive (non-probability) sample of (245) arthritis patients which was comprised (111)
rheumatoid arthritis patients and (134) osteoarthritis patients, was selected out of the early stated
settings. The questionnaire was comprised of

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Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
The Use of Wavelet, DCT & Quadtree for Images Color Compression
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The need for image compression is always renewed because of its importance in reducing the volume of data; which in turn will be stored in less space and transferred more quickly though the communication channels.
In this paper a low cost color image lossy color image compression is introduced. The RGB image data is transformed to YUV color space, then the chromatic bands U & V are down-sampled using dissemination step. The bi-orthogonal wavelet transform is used to decompose each color sub band, separately. Then, the Discrete Cosine Transform (DCT) is used to encode the Low-Low (LL) sub band. The other wavelet sub bands are coded using scalar Quantization. Also, the quad tree coding process was applied on the outcomes of DCT and

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Sat Feb 26 2022
Journal Name
Iraqi Journal Of Science
Estimating the Reliability Function for Transmuted Pareto Distribution Using Simulation
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     In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates  sample size , and it replicates  for the real value for parameters, for reliability times values  we take .

Results were compared by using mean square error (MSE), the result appears as follows :

The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
Robust Adaptive Sliding Mode Controller for a Nonholonomic Mobile Platform
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In this paper, a robust adaptive sliding mode controller is designed for a mobile platform trajectory tracking.  The mobile platform is an example of a nonholonomic mechanical system. The presence of holonomic constraints reduces the number of degree of freedom that represents the system model, while the nonholonomic constraints reduce the differentiable degree of freedom. The mathematical model was derived here for the mobile platform, considering the existence of one holonomic and two nonholonomic constraints imposed on system dynamics. The partial feedback linearization method was used to get the input-output relation, where the output is the error functions between the position of a certain point on the platform

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Publication Date
Sun May 16 2021
Journal Name
Graphs And Combinatorics
Commuting Involution Graphs for Certain Exceptional Groups of Lie Type
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Abstract<p>Suppose that <italic>G</italic> is a finite group and <italic>X</italic> is a <italic>G</italic>-conjugacy classes of involutions. The commuting involution graph <inline-formula><alternatives><tex-math>$${\mathcal {C}}(G,X)$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>C</mi> <mo>(</mo> <mi>G</mi> <mo>,</mo> <mi>X</mi> <mo>)</mo> </mrow> </math></alternatives></inline-formula> is</p> ... Show More
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