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Path Planning of an Autonomous Mobile Robot using Enhanced Bacterial Foraging Optimization Algorithm
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This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algorithm and other two state-of-the-art algorithms. This study showed that the proposed method is effective and produces trajectories with satisfactory results.

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Publication Date
Fri Dec 30 2011
Journal Name
Al-kindy College Medical Journal
None anticipated bacterial urinary tract infections in type 2 diabetic patients relative to duration and angiopathies
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Background: Diabetes mellitus is a well
known metabolic and vascular illness associated
with high incidence of bacterial urinary tract
infections especially in diabetic complications
including both micro and macro-vascular types.
Objective: To study the incidence of bacterial
urinary tract infections in type 2 diabetic
patients, the type of micro-organism responsible
in relation to age, sex of patients, duration of the
disease & related micro & macrovascular
diabetic complications.
Methods: A prospective study of the diabetic
patients including 40 males with mean age of
54(±9) years and 50 females, mean age of 51(±7)
years and duration of the and sex matched
controls (27 males and 33

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Tue Apr 01 2025
Journal Name
Materials Today Communications
Engineered Composition and Morphology: Unveiling 2D Bi₂(W₁₋ₓMox)O₆ Nanosheets for Enhanced Optical and Ionizing Protection Applications
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
An Analytic Solution for Riccati Matrix Delay Differential Equation using Coupled Homotopy-Adomian Approach
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An efficient modification and a novel technique combining the homotopy concept with  Adomian decomposition method (ADM) to obtain an accurate analytical solution for Riccati matrix delay differential equation (RMDDE) is introduced  in this paper  . Both methods are very efficient and effective. The whole integral part of ADM is used instead of the integral part of homotopy technique. The major feature in current technique gives us a large convergence region of iterative approximate solutions .The results acquired by this technique give better approximations for a larger region as well as previously. Finally, the results conducted via suggesting an efficient and easy technique, and may be addressed to other non-linear problems.

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Contribution of Privatization in Tax Revenues: an applied research on a sample of filling stations
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The tax revenues achieved through projects of transition to private sector are regarded as an important source for using in achieving political, economic and social objectives. Since Iraq is heading towards free market economy, new strategies should be adopted to reform the taxation system from by a qualified taxation management office and to activate the taxation policy and to reconsider legislation in relation to the aware of the legible to the importance of disclosure of their taxable real income in order to arrive at contribution of privatization in the taxation revenues for the important role effect on economic activities. In the light of the above, the research is based upon a hypothesis which stipulates that privatization contribu

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Publication Date
Sun Sep 22 2024
Journal Name
Journal Of Petroleum Research And Studies
Optimizing Gas Lift for Improved Oil Recovery in a Middle East Field: A Genetic Algorithm Approach
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This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. Howev

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
A Genetic Algorithm for Task Allocation Problem in the Internet of Things
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In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Image Hiding Using Discrete Cosine Transform
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Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.

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