Human interaction technology based on motion capture (MoCap) systems is a vital tool for human kinematics analysis, with applications in clinical settings, animations, and video games. We introduce a new method for analyzing and estimating dorsal spine movement using a MoCap system. The captured data by the MoCap system are processed and analyzed to estimate the motion kinematics of three primary regions; the shoulders, spine, and hips. This work contributes a non-invasive and anatomically guided framework that enables region-specific analysis of spinal motion which could be used as a clinical alternative to invasive measurement techniques. The hierarchy of our model consists of five main levels; motion capture system settings, marker data acquisition, generation of the dorsal spine skeleton, optic flow calculation in 3D space, and motion protocol analysis and evaluation. Points of interest (POIs) are identified at ten locations on the three selected regions; the acromion of the scapula, the vertebral column, and the greater trochanter of the femurs. The optic flow of these POIs is calculated based on their spatiotemporal positions in 3D space that facilitates the analysis of the articulated spine motion. We rigorously tested our model with various movement protocols including flexion, lateral-flexion, and twisting movements. The results demonstrated an exceptional performance with a minimal error of (2.09◦ ) compared with ground truth data. These findings highlight the accuracy of our model in estimating optic flow and tracking the motion of human spine.
In this study, the two researchers try to identify the degree of psychological flow among third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, by constructing a psychometric flow meter for third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, and the research sample reached 123 female students They represent 100% of the research community, and after conducting the scientific foundations for building the scale, the two researchers reached the final version of the psychometric flow scale with 21 items with four axes.
Continuous turbidimetric analysis (CTA) for a distinctive analytical application by employing a homemade analyser (NAG Dual & Solo 0-180°) which contained two consecutive detection zones (measuring cells 1 & 2) is described. The analyser works based on light-emitting diodes as a light source and a set of solar cells as a light detector for turbidity measurements without needing further fibres or lenses. Formation of a turbid precipitated product with yellow colour due to the reaction between the warfarin and the precipitation reagent (Potassium dichromate) is what the developed method is based on. The CTA method was applied to determine the warfarin in pure form and pharmaceu
Continuous turbidimetric analysis (CTA) for a distinctive analytical application by employing a homemade analyser (NAG Dual & Solo 0-180°) which contained two consecutive detection zones (measuring cells 1 & 2) is described. The analyser works based on light-emitting diodes as a light source and a set of solar cells as a light detector for turbidity measurements without needing further fibres or lenses. Formation of a turbid precipitated product with yellow colour due to the reaction between the warfarin and the precipitation reagent (Potassium dichromate) is what the developed method is based on. The CTA method was applied to determine the warfarin in pure form and pharmaceu
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreThis study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil: (contaminated soil with the a
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