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NOVEL POLYHYDROXYBUTYRATE (PHB) PRODUCTION USING A WASTE DATE SEED FEEDSTOCK
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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Sun Jan 01 2023
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Deep Learning-Based Approach for Classifying the Severity of Metal Corrosion Using Sem Images
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Study the Nuclear Structure of Some Even-Even Ca Isotopes Using the Microscopic Theory
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The root-mean square-radius of proton, neutron, matter and charge radii, energy level, inelastic longitudinal form factors, reduced transition probability from the ground state to first-excited 2+ state of even-even isotopes, quadrupole moments, quadrupole deformation parameter, and the occupation numbers for some calcium isotopes for A=42,44,46,48,50 are computed using fp-model space and FPBM interaction. 40Ca nucleus is regarded as the inert core for all isotopes under this model space with valence nucleons are moving throughout the fp-shell model space involving 1f7/2, 2p3/2, 1f5/2, and 2p1/2 orbits. Model space is used to present calculations using FPBM intera

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Publication Date
Mon Jun 01 2026
Journal Name
Ieee Access
Offline Voice-Controlled Lower Limb Rehabilitation Robot Using Forward Kinematics and Fuzzy Command Matching
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Lower limb Rehabilitation Robots (LLRRs) assist in therapeutic tasks that involve gait recovery and joint mobility recovery of the lower limbs, in patients recovering from neurologic injuries such as stroke as well as spinal cord injury. LLRRs can sometimes be driven by preprogrammed trajectories or Inverse Kinematics (IK) trajectories, which bring increased computational demand and command supported interaction. This paper proposes an interactive control framework for LLRRs using a hybrid mix of Forward Kinematics (FK) driven movement and an offline Voice Conversational Agent (VCA), based on the Vosk speech recognition engine. The framework proposed is modular in nature that is completely “local”, running offline with no need for the I

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
“Using the Statistical Analysis for deduction the childhood status in Iraq during 2006-2010”
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   To deduct the childhood status in Iraq, it was important manner to use statistical tools and approaches concerned with interpreting the causal relationships and their attitudes and use classification method for the important effects (variables) to draw an obvious picture of the phenomena under study in order to make it useful through investing, updating and improving it in by demographic studies in the future. Two statistical methods had been used in the field of analyzing data of multivariate analysis namely, Cluster Analysis and Factor Analysis.  

The present study focuses on four fundamental axes .The nutrition axis, health axis, Educational axis, and the social axis. The study has ca

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Effect of internal curing on performance of self-compacting concrete by using sustainable materials
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This paper is devoted to investigate the effect of internal curing technique on the properties of self-compacting concrete. In this study, self-compacting concrete is produced by using limestone powder as partial replacement by weight of cement with percentage of (5%), sand is partially replaced by volume with saturated fine lightweight aggregate which is thermostone aggregate as internal curing material in three percentages of (5%, 10%, 15%) for self-compacting concrete, and the use of two external curing conditions which are water and air. The experimental work was divided into three parts: in the first part, the workability tests of fresh self-compacting concrete were conducted. The second part included conducting compressive str

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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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Publication Date
Mon Mar 29 2021
Journal Name
Journal Of Engineering
Effluent quality assessment of sewage treatment plant using principal component analysis and cluster analysis
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Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m3/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Sun Mar 17 2019
Journal Name
Biochemical & Cellular Archives
EVALUATION OF THE POTASSIUM AVAILABILITY IN THE SALINE SOILS USING THE TRADITIONAL CHEMICAL CRITERION
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