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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
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
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Thu Aug 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Smart Irrigation Technique in the Fixed Irrigation System Based on Soil Moisture Content
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Abstract<p>The growing water demand has raised serious concerns about the future of irrigated agriculture in many parts all over the world, changing environmental conditions and shortage of water (especially in Iraq) have led to the need for a new system that efficiently manages the irrigation of crops. With the increasing population growing at a rapid pace, traditional agriculture will have a tough time meeting future food demands. Water availability and conservation are major concerns for farmers. The configuration of the smart irrigation system was designed based on data specific to the parameters concerning the characteristics of the plant and the properties of soil which are measured once i</p> ... Show More
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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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Publication Date
Tue Jul 24 2018
Journal Name
Sensors
Adaptive Windowing Framework for Surface Electromyogram-Based Pattern Recognition System for Transradial Amputees
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Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

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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
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Modified Symmetric Key Fully Homomorphic Encryption Scheme Based on Read-Muller Code
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Homomorphic encryption became popular and powerful cryptographic primitive for various cloud computing applications. In the recent decades several developments has been made. Few schemes based on coding theory have been proposed but none of them support unlimited operations with security.   We propose a modified Reed-Muller Code based symmetric key fully homomorphic encryption to improve its security by using message expansion technique. Message expansion with prepended random fixed length string provides one-to-many mapping between message and codeword, thus one-to many mapping between plaintext and ciphertext. The proposed scheme supports both (MOD 2) additive and multiplication operations unlimitedly.   We make an effort to prove

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Publication Date
Tue Sep 01 2020
Journal Name
International Journal Of Hydrogen Energy
Hydrogen gas sensing based on nanocrystalline SnO2 thin films operating at low temperatures
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Publication Date
Sun Mar 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reduction of Aromatic Content from Hexane by Silica Gel
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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Improvement of Diesel Fuel Engine Performance by Nanoparticles Additives
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This study was done to investigate the impact of different nanoparticles on diesel fuel characteristics, Iraqi diesel fuel was supplied from al-Dura refinery and was treated to enhance performance by improving its characteristics. Two types of nanoparticles were mixed with Iraqi diesel fuel at various weight fractions of 30, 60, 90, and 120 ppm. The diesel engine was tested and run at a constant speed of 1600 rpm to examine and evaluate the engine's performance and determine emissions. In general, ZnO additives' performance analysis showed they are more efficient for diesel fuel engines than CeO. The performance of engine diesel fuel tests showed that the weight fraction of nanoparticles at 90 and 120 ppm give a similar performance,

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