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Hierarchical Stabilization and Tracking Control of a Flexible-Joint Bipedal Robot Based on Anti-Windup and Adaptive Approximation Control
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Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptive approximation-based feedback linearization control (so-called adaptive computed torque control) combined with an anti-windup compensator is designed to track the desired COM produced by the high-level command. Along the length of the support sole, the ZMP with physical restrictions serves as the control input signal. The viability of the suggested controller is established using Lyapunov’s theory. The low-level control tracks the intended joint movements for a bipedal mechanism with flexible joints. We use two control strategies: position-based adaptive approximation control and cascaded position-torque adaptive approximation control (cascaded PTAAC). The interesting point is that the cascaded PTAAC can be extended to deal with variable impedance robotic joints by using the required velocity concept, including the desired velocity and terms related to control errors such as position, force, torque, or impedance errors if needed. A 6-link bipedal robot is used in simulation and validation experiments to demonstrate the viability of the suggested control structure.

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Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Monitoring the Expansion of Unplanned Urbanization and its Impact on Climate Change based on Google Earth Engine Service, a Case Study of Baghdad / Iraq
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     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Electrical stimulation for the treatment of Knee joint osteoarthritis
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Abstract 20 patients with osteoarthritis of the knee joint were treated by electrical stimulation in the form of 6 sessions every other day each sessions of diphase fixe (DF) for 4 minutes followed by rest for 4 minutes then treated with a monophase fixe (MF) for 2 minutes. By clinical & statistical analysis ( P value < 0.05) we conclude that the electrical stimulation is effective as one method in the treatment of osteoarthritis.

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Sun Dec 01 2013
Journal Name
Al- Mustansiriyah Journal Science
Convex Approximation by q- Meyer-König-Zeller Durrmeyer Operators
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Approximation fixed point theorems via generalized like contraction mappings
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Publication Date
Wed Sep 02 2020
Journal Name
International Journal Of Pharmaceutical Research
A Study of Anti-Fungal Activity for Some Antibiotics Against Aspergillus spp. and Candida spp. in Iraqi patients with Diabetes Mellitus
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Publication Date
Sat Jun 18 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Anti-Inflammatory Activity of Gingko Biloba Extract in Cotton Pellet-Induced Granuloma in Rats: A comparative Study with Prednisolone and Dexamethasone
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The current study was designed to evaluate the anti-inflammatory effect of GKB in the rat model of granulomatous inflammation. Thirty rats were distributed into five groups:  The first group served as negative control group that received distilled water (DW) only without inducting inflammation, positive control group; treated with DW with the induction of inflammation and they were assigned to cotton pellet-induced granuloma, ginkgo biloba (GKB) treated group (200mg/kg/day), dexamethasone-treated group (1mg/kg), and Prednisolone treated group (5mg/kg). All the treatments were given orally for seven consecutive days.  On day eight, the rats were anesthetized and the pellets together with granulation tissue were carefully removed

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Publication Date
Fri Jan 10 2025
Journal Name
International Journal Of Scientific Research In Science, Engineering And Technology
Image Cryptography Based on Chebyshev Polynomials and Transposition- Substitution Transformations
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The confirming of security and confidentiality of multimedia data is a serious challenge through the growing dependence on digital communication. This paper offers a new image cryptography based on the Chebyshev chaos polynomials map, via employing the randomness characteristic of chaos concept to improve security. The suggested method includes block shuffling, dynamic offset chaos key production, inter-layer XOR, and block 90 degree rotations to disorder the correlations intrinsic in image. The method is aimed for efficiency and scalability, accomplishing  complexity order for n-pixels over specific cipher rounds. The experiment outcomes depict great resistant to cryptanalysis attacks, containing statistical, differential and brut

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Color image compression based on spatial and magnitude signal decomposition
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<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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