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On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach. The developed on-board DT offered a model where interaction with the unknown payload and aerial robot dynamics is informed. Beside this, the results showed the ability of the introduced DT to foretell the conditions of the forces acting on the payload which helped to predict the situation of aerial manipulation process. Additionally, the results showed that the DT model could detect real-time errors in the physical asset.

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Smartphone -Based Model for Human Activity Recognition
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

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Publication Date
Sun Nov 04 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
MEASURING OBESITYLEVEL BY BIO-ELECTRICAL IMPEDANCE ANALYSIS TECHNIQUE AND COMPARED TO TRADITIONAL METHODS: MEASURING OBESITYLEVEL BY BIO-ELECTRICAL IMPEDANCE ANALYSIS TECHNIQUE AND COMPARED TO TRADITIONAL METHODS
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This study aimed to determine obesity level of some population in Baghdad by using Bio-electrical impedance analysis (BIA) and compared with anthropometric measurements such as body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR). Statistical analysis results of linear correlation coefficients for obesity indicators showed that BIA correlation 0.92 was most significant and reliable for obesity measurement.

Results of BIA method for age group 20-29 years showed that 44.4% of females were healthy body while 37.8% of males suffer from increased body fat. Results of age group 30-39 year showed that 32.6 of females were in healthy body and 42% of males were obese. In case age group 40-4

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of the Genotoxicity of the Aerial Parts of Iraqi Euphorbia cyathophora on Bone Marrow and Spleen Cells in Mice
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The aim of the study was extraction of arial part of Euphorbia cyathophora constituents with methanol and evaluate its effect on mitotic index and total chromosomal aberration bone marrow cell and spleen cell in mice  200 gm of E. cyathophora fine powder was defatted then extracted by cold maceration 80% ethanol for seven days. The extract was filtered and dried in a rotary evaporator then the dried extract was suspended with water and consecutively extracted using chloroform, ethyl acetate for each. The aqueous layer was then mixed with 100ml methanol. These fractions are dried under reduced pressure to obtain the dry extract. Twenty-four Albino mice were used for the experiment. The animals were divided into four groups: Gr

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
A Review Study on Forgery and Tamper Detection Techniques in Digital Images
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Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system
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These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Tue Oct 30 2018
Journal Name
Journal Of Engineering
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
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