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Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforward neural network (FNN) model. Data acquisition involved 60 subjects diagnosed with the studied cases. The implementation of FNN achieved an accuracy of 96.6% using 50% of the dataset as training data and 92.8% using only 30% training data. The comparison with related work shows good impact of using the differential values of pressure points as input for neural networks compared with raw data.

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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Structural Engineering
CFRP Strengthening of RC Beams with Multiple Openings Subjected to Static and Impact Loads
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The provision of openings in serviceable reinforced concrete beams may result in a substantial decline in the beam's capacity and integrity, indicating the necessity of opening strengthening. The present study investigates the experimental response of reinforced concrete T-beams with multiple web-strengthened openings disposed in shear span to static and impact loads. Fourteen RC T-beams were tested in two groups, each of seven beams. The first group was tested under static loading up to failure, while the second group was tested under repeated impact loading until the width of shear cracks reached 0.3 mm. The residual static strengths of the beams subjected to impact loading were then determined. The test variables considered were

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Publication Date
Sun Nov 01 2020
Journal Name
Civil Engineering Journal
Flexural Behavior of Composite GFRP Pultruded I-Section Beams under Static and Impact Loading
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In this study, the effect of glass fiber reinforced polymer (GFRP) section and compressive strength of concrete in composite beams under static and low velocity impact loads was examined. Modeling was performed and the obtained results were compared with the test results and their compatibility was evaluated.‎ Experimental tests of four composite beams were carried out, where two of them are control specimen with 20 MPa compressive strength of concrete deck slab and 50 MPa for other. Bending characteristics were affected by the strength of concrete under impact loading case, as it increased maximum impact force and damping time at a ratio of 59% and reduced the damping ratio by 47% compared to the reference hybrid beam. Under stat

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Publication Date
Wed Jun 01 2022
Journal Name
Civil And Environmental Engineering
A Soil-Pile Response under Coupled Static-Dynamic Loadings in Terms of Kinematic Interaction
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Abstract<p>Although the axial aptitude and pile load transfer under static loading have been extensively documented, the dynamic axial reaction, on the other hand, requires further investigation. During a seismic event, the pile load applied may increase, while the soil load carrying capacity may decrease due to the shaking, resulting in additional settlement. The researchers concentrated their efforts on determining the cause of extensive damage to the piles after the seismic event. Such failures were linked to discontinuities in the subsoil due to abrupt differences in soil stiffness, and so actions were called kinematic impact of the earthquake on piles depending on the outcomes of laboratory</p> ... Show More
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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Structural Engineering
CFRP Strengthening of RC Beams with Multiple Openings Subjected to Static and Impact Loads
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The provision of openings in serviceable reinforced concrete beams may result in a substantial decline in the beam's capacity and integrity, indicating the necessity of opening strengthening. The present study investigates the experimental response of reinforced concrete T-beams with multiple web-strengthened openings disposed in shear span to static and impact loads. Fourteen RC T-beams were tested in two groups, each of seven beams. The first group was tested under static loading up to failure, while the second group was tested under repeated impact loading until the width of shear cracks reached 0.3 mm. The residual static strengths of the beams subjected to impact loading were then determined. The test variables considered were

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Publication Date
Sat Jul 18 2026
Journal Name
Journal Of Studies And Researches Of Sport Education
دوافع اعتراض اللاعبين على قرارات الحكام في لعبة كرة القدم
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Investigating the Influence of Precursor Concentration on the Photodegradation of Methylene Blue using Biosynthesized ZnO from Pometia pinnata Leaf Extracts
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The ZnO nanoparticles were synthesized at various precursor concentrations i.e. 0.05, 0.1, and 0.5 M by biosynthesis method based on Pometia pinnata Leaf Extracts. Initial nanoparticle concentration influenced the optical bandgap, shape, and structure of nanoparticles. The photodegradation process was carried out under UV illumination. The efficiency of MB degradation was determined by measuring the decrease in MB concentration and by analyzing the optical absorption at 663 nm recorded by UV-Vis spectroscopy. Results showed that the biosynthesized ZnO nanoparticles exhibited efficient photodegradation of MB, with a maximum degradation rate of 80% after 90 minutes of exposure to UV-C light. The study highlights the potential of Pometia pi

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The role of organizational change in easing the organizational conflict: an exploratory study of the opinions of a sample of managers and workers in Iraq to EarthLink Network Services Company And communications
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Research on the role of organizational change in easing the organizational conflict focuses for being one of the important topics and relatively modern and which have a significant impact on the future of organizations, so this study was to identify the relationship and the impact of organizational change and of deportation (technological, organizational structure, human resources, the change in the task) at the organizational conflict in the Earth company link Iraq, in order to reach the goals of the research, it has been the development of a questionnaire distributed to a random sample of (100) composed employees from managers and heads of departments and the people and staff at the Earth company link Iraq, the study found: the

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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