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Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators
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The control of an aerial flexible joint robot (FJR) manipulator system with underactuation is a difficult task due to unavoidable factors, including, coupling, underactuation, nonlinearities, unmodeled uncertainties, and unpredictable external disturbances. To mitigate those issues, a new robust fixed-time sliding mode control (FxTSMC) is proposed by using a fixed-time sliding mode observer (FxTSMO) for the trajectory tracking problem of the FJR attached to the drones system. First, the underactuated FJR is comprehensively modeled and converted to a canonical model by employing two state transformations for ease of the control design. Then, based on the availability of the measured states, a cascaded FxTSMO (CFxTSMO) is constructed to estimate the unmeasurable variables and lumped disturbances simultaneously in fixed-time, and to effectively reduce the estimation noise. Finally, the FxTSMC scheme for a high-order underactuated FJR system is designed to guarantee that the system tracking error approaches to zero within a fixed-time that is independent of the initial conditions. The fixed-time stability of the closed-loop system of the FJR dynamics is mathematically proven by the Lyapunov theorem. Simulation investigations and hardware tests are performed to demonstrate the efficiency of the proposed controller scheme. Furthermore, the control technique developed in this research could be implemented to the various underactuated mechanical systems (UMSs), like drones, in a promising way.

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Publication Date
Fri Sep 06 2024
Journal Name
Journal Of Optics
Synthesis of N-A cysteine-capped CdTe QDs for optical biosensing
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In this investigation, water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals), utilizing N-acetyl cysteine as a stabilizer, were prepared to assess their potential in differentiating between DNA extracted from pathogenic bacteria (e.g. Escherichia coli isolated from urine specimen) and intact DNA (extracted from blood of healthy individuals) for biomedical sensing prospective. Following the optical characterization of the synthesized QDs, the XRD analysis illustrated the construction of NAC-CdTe-QDs with a grain size of 7.1 nm. The prepared NAC-CdTe-QDs exhibited higher PL emission features at of 550 nm and UV-Vis absorption peak at 300 nm. Additionally, the energy gap quantified via PL and UV–Vis were 2.2 eV

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Publication Date
Wed Jan 01 2020
Journal Name
Arab Journal Of Basic And Applied Sciences
Analytic and numerical solutions for linear and nonlinear multidimensional wave equations
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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
Fabrication of Electroluminescence Device for PEDOT:PSS / ploy TPD/Eu2O3 Nanoparticles junction
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We manufactured the nanoparticles light emitting diode (NPs-LED) for organic and inorganic semiconductors to achieve electroluminescence (EL). The nanoparticles of Europium oxide(Eu2O3) were incorporated into the thin film layers of the organic compounds, poly(3,4,- ethylene dioxythiophene)/polystyrene sulfonic acid (PEDOT:PSS), N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’- diamine (poly TPD) and polymethyl methacrylate (PMMA), by the spin coating and with the help of the phase segregation method. The EL of NPs-LED, was study for the different bias voltages (20, 25, 30) V at the room temperature, from depending on the CIE 1931 color spaces and it was generated the white light at 20V, t

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Publication Date
Tue Dec 30 2014
Journal Name
College Of Islamic Sciences
Excuse for ignorance in Islamic law         Financial transactions: (Contemporary Applied Models)
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The researcher highlighted in his research on an important subject that people need, which is the excuse of ignorance in Islamic law. , As the flag of light and ignorance of darkness. Then the researcher lameness of the reasons for research in this subject as it is one of the assets that should be practiced by the ruler and the judge and the mufti and the diligent and jurisprudent, but the public should identify the issues that ignore ignorance and issues that are not excused even if claimed ignorance.
 Then the researcher concluded the most important results, and recommendations that he wanted to set scientific rules for students of science and Muslims in general, to follow the issues of legitimacy and learn its provisions and i

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Publication Date
Tue Aug 01 2023
Journal Name
Biomedical Signal Processing And Control
Decoding transient sEMG data for intent motion recognition in transhumeral amputees
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Publication Date
Sun Feb 25 2024
Journal Name
Iraqi Journal Of Agricultural Sciences
THE EFFICIENCY OF GUM-SILICA CMPOSITE FOR REMOVING OF WASTEWATER TURBIDITY
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A novel mixed natural coagulant has been developed to remove sewage pollutants and heavy metals from Qanat- al- Jayesh by using low cost adsorbent natural materials. In these materials, significant interaction contains Arabic gum mixed with extracted silica from rice husk ash (natural coagulants) by the Batch device approach, using two variables, pH values ranging from 5-8 and contact times between 0.25-5 hrs. All wastewater samples were collected after treatment by adsorbents and examined for determination of residual heavy metal concentrations: Pb, Ni, Zn and Cu by atomic absorption spectroscopy (AAS), turbidity, pH, total dissolved salts (TDS), electrical conductivity (EC) and total salinity (TS). The results obtained indicate Th

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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Sun Feb 25 2024
Journal Name
Iraqi Journal Of Agricultural Sciences
THE EFFICIENCY OF GUM-SILICA CMPOSITE FOR REMOVING OF WASTEWATER TURBIDITY
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A novel mixed natural coagulant has been developed to remove sewage pollutants and heavy metals from Qanat- al- Jayesh by using low cost adsorbent natural materials. In these materials, significant interaction contains Arabic gum mixed with extracted silica from rice husk ash (natural coagulants) by the Batch device approach, using two variables, pH values ranging from 5-8 and contact times between 0.25-5 hrs. All wastewater samples were collected after treatment by adsorbents and examined for determination of residual heavy metal concentrations: Pb, Ni, Zn and Cu by atomic absorption spectroscopy (AAS), turbidity, pH, total dissolved salts (TDS), electrical conductivity (EC) and total salinity (TS). The results obtained indicate Th

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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