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Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this research, need confirm the results of the preliminary study but also going forward in understanding the processes involved in these experiments. Two tracks are followed, first will concern with the development of classifiers based on statistical data already provided by the system "eye tracking", second will be more focused on finding new descriptors from the eye trajectories. In this paper, study used K-mean with Vector Measure Constructor Method (VMCM). In addition, briefly reflect used other method support vector machine (SVM) technique. The methods are playing important role to classify the people with and without autism specter disorder. The research paper is comparative study between these two methods.

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Publication Date
Mon May 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Improvement Using The Combination of Wavelet and Multiwavelet Transform
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      This paper introduces method of image enhancement using the combination of both wavelet and Multiwavelet transformation. New technique is proposed for image enhancement using one smoothing filter.

    A critically- Sampled Scheme of preprocessing method is used for computing the Multiwavelet.It is the 2nd norm approximation used to speed the procedures needed for such computation.

  An improvement was achieved with the proposed method in comparison with the conventional method. 

The performance of this technique has been done by computer using Visual Baisec.6 package.

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Publication Date
Fri Dec 25 2020
Journal Name
Al-nahrain Journal For Engineering Sciences
Comparison Sequences of Pick and Place System Controlled Using PLC
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Pick and place system is one of the significant employments of modern robots utilized in industrial environments. The objective of this research is to make a comparison of time sequences by combining multiple axes of sequences. A pick-place system implemented with pneumatic linear double-acting cylinders to applicator in automated systems processes for manufacturing. The challenge of 3-axes movement control was achieved using the PLC (Programmable Logic Controller) controller such that the merging between two or three axes was achieved according to the selected sequence of the program. The outcomes show the contrasted sequences and the reference in a constant velocity. The main variable parameter is the number of steps for each sequ

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Publication Date
Sat Oct 09 2021
Journal Name
Applied System Innovation
Design and Optimization of Vertical Axis Wind Turbines Using QBlade
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Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under di

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
EXTRACTING PECTIN FROM TOMATOES AND BEET PEELS AND USING IT IN THE MANUFACTURE OF YOGURT AND COMPARING THEM
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Pectin is available in many plants and in this study, the peels of tomatoes and beet were used to be an economical source of pectin production instead of dumping it with waste or using it as animal feed. The pectin extracted from the peels using different solutions, namely citric acid (2 M), oxalic acid (2%) and hydrochloric acid (0.5 M) the outcome of the extraction methods, 7. 1%, 6% and 11% respectively for tomatoes peels, while the pectin of beet peels were 8%, 6.5%, and 8.3%, and the highest percentage obtained in the manner of hydrochloric acid adopted in the manufacture of yogurt.Yogurt was manufactured with four treatments, in the first treatment standard pectin was added and the second treatment in addition to the pectin extracted

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Scopus
Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Informative accuracy investigation and updating map using remote sensing technique and GIS
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In this work, using GPS which has best accuracy that can be established set of GCPs, also two satellite images can be used, first with high resolution QuickBird, and second has low resolution Landsat image and topographic maps with 1:100,000 and 1:250,000 scales. The implementing of these factors (GPS, two satellite images, different scales for topographic maps, and set of GCPs) can be applying. In this study, must be divided this work into two parts geometric accuracy and informative accuracy investigation. The first part is showing geometric correction for two satellite images and maps.
The second part of the results is to demonstrate the features (how the features appearance) of topographic map or pictorial map (image map), Where i

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Publication Date
Mon Jun 08 1998
Journal Name
Journal Of King Saud University
Moment Capacity and Strength of Reinforced Concrete Members Using Stress- Strain Diagrams of Concrete and Steel
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Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Isolation and Partial Purification of Cell wall Lipopolysaccharides of Pseudomonas Aeruginosa and Using It as Vaccine
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This study ,the samples were   collected from "118 patients " suffering from burn wound contaminated with Pseudomonas aeruginosa and 100 health individuals (male and female ) as a control group ,the samples were wound swap and blood sample  .       Chromatography technique was employed to extract and purify cell wall containing lipopolysaccharide by using P. aeruginosa  isolate ATCC 15692,the purification done by addition of ammonuium sulfate, sodium dodecyl sulfat (SDS) anddialysis, gel filtration chromatography by using sepharose-4B.       Immunogenicity of  LPS component was determined by mice injection under the skin  ,then Ab concentration agai

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Construction of Anisotype CdS/Si Heterojunction and Lineup Using I-V and C-V Measurements
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Near-ideal p-CdS/n-Si heterojunction band edge lineup has been investigated for the first time with aid of I-V and C-V measurements. The heterojunction was manufactured by deposition of CdS films prepared by chemical spray pyrolysis technique (CSP) on monocrystalline n-type silicon. The experimental data of the conduction band offset Ec and valence band offset Ec were compared with theoretical values. The band offset Ec=530meV and Ev=770meV obtained at 300K. The energy band diagram of p-CdS/n-Si HJ was constructed. C-V measurements depict that the junction was an abrupt type and the built-in voltage was determined from C-2-V plot

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