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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
Tue Oct 26 2021
Journal Name
Series On Biomechanics
Monitoring and analysis of plantar pressure map and foot motions using a wearable sensing system
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Publication Date
Wed Oct 18 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Personal Hygiene for Adults with Diabetic Foot
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Objective: The aim of the study is to assess the personal hygiene of adult patients with
diabetic foot.
Methodology: ٨ descriptive study was carried out in Baghdad teaching hospital, Al-Karama teaching hospital
and Al-Kindey teaching hospital for the period of 10/1/2006 to 1/9/2006. A purposive "non probability" sample
of (100) patient.
Questionnaire was constructed for achieving the purpose of the study. Data were collected through the
application of the questionnaire and interview technique. Data were analyzed through descriptive statistical
approach (frequency & percentage) and inferential statistical approach (chi-square ع correlation) by using of
SPSS.
Results: The study results indicated that the ra

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Publication Date
Sun Nov 04 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Personal Hygiene for Adults with Diabetic Foot
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Objective: The aim of the study is to assess the personal hygiene of adult patients with
diabetic foot.
Methodology: A descriptive study was carried out in Baghdad teaching hospital, Al-Karama teaching hospital
and Al-Kindey teaching hospital for the period of 10/1/2006 to 1/9/2006. A purposive "non probability" sample
of (100) patient.
Questionnaire was constructed for achieving the purpose of the study. Data were collected through the
application of the questionnaire and interview technique. Data were analyzed through descriptive statistical
approach (frequency & percentage) and inferential statistical approach (chi-square & correlation) by using of
SPSS.
Results: The study results indicated that the

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Brain Tumor Detection Method Using Unsupervised Classification Technique
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Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Enhancement of corrosion protection of metal carbon steel C45 and stainless steel 316 by using inhibitor (Schiff base) in sea water
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This research has presented a solution to the problem faced by alloys: the corrosion problem, by reducing corrosion and enhancing protection by using an inhibitor (Schiff base). The inhibitor (Schiff base) was synthesized by reacting of the substrates materials (4-dimethylaminobenzaldehyde and 4-aminoantipyrine). It was diagnosed by infrared technology IR, where the IR spectrum and through the visible beams proved that the Schiff base was well formed and with high purity. The corrosion behavior of carbon steel and stainless steel in a saline medium (artificial seawater 3.5%NaCl) before and after using the inhibitor at four temperatures: 20, 30, 40, and 50 C° was studied by using three electrodes potentiostat. The corrosion behavior was

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Publication Date
Wed Aug 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Vaccination of chicken against Coccidiosis by using live Oocysts of different species of Eimeria
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The study was conducted to vaccinate chickens against coccidiosis  using alive vaccine contain seven species of chicken Eimeria,  E. tenella, E. brunetti, E. necatrix, E. maxima, E. mevati, E. acervulina  and E. praecox.    A total of 120 chicks were divided into two main groups: broiler group and egg laying group.  The birds of each group were allocated on to three pins, each contains 20 chicks.  The birds of the experiment were vaccinated at day nine of age, with a suspension of mixed Eimeria which contain 50 Oocysts of E. tenella with a different percent of other species, respectively.  The vaccine was given to chicks in the 1st pins of each group with drinking water,  the chicks in th

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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