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Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint repulsive force and the off-sensors attractive force. These secondary forces and modified primary forces are merged to overcomethe drawbacks like dead ends and U shape traps. The proposed algorithm acquirs information of unknown environment by collecting the readings of five infrared sensors with detecting range of 0.8 m. The proposed algorithm is applied on two different environments also it is compared with another algorithm. The simulation and experimental results confirm that the proposed algorithm always converges to the desired target. In addition, the performance of algorithm is well and meets the requirements in terms of saved time and computational resources.

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Publication Date
Thu Jun 20 2024
Journal Name
Frontiers In Microbiology
Removal of mobile genetic elements from the genome of Clostridioides difficile and the implications for the organism’s biology
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Clostridioides difficile is an emerging pathogen of One Health significance. Its highly variable genome contains mobile genetic elements (MGEs) such as transposons and prophages that influence its biology. Systematic deletion of each genetic element is required to determine their precise role in C. difficile biology and contribution to the wider mobilome. Here, Tn5397 (21 kb) and ϕ027 (56 kb) were deleted from C. difficile 630 and R20291, respectively, using allele replacement facilitated by CRISPR-Cas9. The 630 Tn5397 deletant transferred PaLoc at the same frequency (1 × 10−7

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Petrophysical Analysis of an Iraqi Gas Field (Mansuriya Gas Field)
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Mansuriya Gas field is an elongated anticlinal structure aligned from NW to SE, about 25 km long and 5-6 km wide. Jeribe formation is considered the main reservoir where it contains condensate fluid and has a uniform thickness of about 60 m. The reservoir is significantly over-pressured, (TPOC, 2014).

This research is about well logs analysis, which involves the determination of Archie petrophysical parameters, water saturation, porosity, permeability and lithology. The interpretations and cross plots are done using Interactive Petrophysics (IP) V3.5 software.

The rock parameters (a, m and n) values are important in determining the water saturation where (m) can be calcul

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Publication Date
Fri Dec 31 2021
Journal Name
Political Sciences Journal
The application of smart power in the regional power struggle in the Middle East after 2011
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Receipt date:12/7/2020 accepted date:24/1/2021 Publication date:31/12/2021

 Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

The constant characteristic of international relations is the constant change due to political, economic and military developments in addition to technology, and this in turn has led to many transformations in the concept of power, its uses, and the elements that form power and its distribution, and according to those variables, the concept of power has shifted from hard to soft, up to smart powe

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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Wed Jun 27 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Building Geological Model for Tertiary Reservoir of Exploration Ismail Oil Field, North Iraq
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Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. ‎[1].

   A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling ‎[2].

   Ismail field is exploration structure, located in the north Iraq, about 55 km north-west of Kirkuk city, to the north-west of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer ‎[3].

   Tertiary period reservoir sequences (Main Limestone), which comprise many economica

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
Mapping Paddy Rice Fields Using Landsat and Sentinel Radar Images in Urban Areas for Agriculture Planning
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     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being

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