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Treating of oil-based drill cuttings by earthworms
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This study assessed the advantage of using earthworms in combination with punch waste and nutrients in remediating drill cuttings contaminated with hydrocarbons. Analyses were performed on day 0, 7, 14, 21, and 28 of the experiment. Two hydrocarbon concentrations were used (20000 mg/kg and 40000 mg/kg) for three groups of earthworms number which were five, ten and twenty earthworms. After 28 days, the total petroleum hydrocarbon (TPH) concentration (20000 mg/kg) was reduced to 13200 mg/kg, 9800 mg/kg, and 6300 mg/kg in treatments with five, ten and twenty earthworms respectively. Also, TPH concentration (40000 mg/kg) was reduced to 22000 mg/kg, 10100 mg/kg, and 4200 mg/kg in treatments with the above number of earthworms respectively. The present study revealed that the trend of degradation was observed to increase significantly with an increase in Earthworms number and with an increase in number of tested days. The results of this study have shown that TPH with certain concentrations can be reduced to acceptable levels by using the selected earthworms named Allolobophora. Also the study results revealed that the present bioremediation can be considered an additional option to deal with the local petroleum contaminated sites.

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Sat Nov 02 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
Acetic acid concentration estimation using plastic optical fiber sensor based surface Plasmon resonance
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Optical fiber chemical sensor based surface Plasmon resonance for sensing and measuring the refractive index and concentration for Acetic acid is designed and implemented during this work. Optical grade plastic optical fibers with a diameter of 1000μm were used with a diameter core of 980μm and a cladding of 20μm, where the sensor is fabricated by a small part (10mm) of optical fiber in the middle is embedded in a resin block and then the polishing process is done, after that it is deposited with about (40nm) thickness of gold metal and the Acetic acid is placed on the sensing probe.

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Publication Date
Tue Dec 01 2020
Journal Name
Minar International Journal Of Applied Sciences And Technology
INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS
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Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Sat Dec 30 2023
Journal Name
Traitement Du Signal
Optimizing Acoustic Feature Selection for Estimating Speaker Traits: A Novel Threshold-Based Approach
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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
ESO-based repetitive control for rejecting periodic and aperiodic disturbances in piezoelectric actuators
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This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
BER performance enhancement for secure wireless communication systems based on chaotic-MIMO techniques
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The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Robot Arm Path Planning Using Modified Particle Swarm Optimization based on D* algorithm
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Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

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Publication Date
Wed Sep 26 2018
Journal Name
Communications In Computer And Information Science
A New RGB Image Encryption Based on DNA Encoding and Multi-chaotic Maps
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