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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 Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Sun Jan 01 2012
Journal Name
Iraqi Journal Of Physics
Using remote sensing techniques to monitoring and evaluate the water cover in AL_Razzaza lake: Iraq at deferent periods
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Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the AlRazzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Using remote sensing techniques to monitoring and evaluate the water cover in AL_Razzaza lake: Iraq at deferent periods
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Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the Al-Razzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Awareness of Diagnosing Autism Spectrum Disorders and Social (Pragmatic) Communication Disorder among Student Teachers According to Some Variables
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The research aims to identify the level of awareness of student teachers in the behavioral disorders and autism specialization about the diagnosing Autism Spectrum Disorder and Social (Pragmatic) Communication Disorder according to some variables. The study was conducted on a sample of (113) student teachers. The researcher employed the awareness scale of a teacher-screening questionnaire for autism spectrum disorder and social pragmatic communication disorder. The results showed that the average of teachers in the total degree of awareness of autism spectrum disorder and social communication have recorded a moderate degree. As for the awareness of autism spectrum disorder was high. Then, the awareness of social communication disorder wa

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Formal questioning and its representations in the design of contemporary residential rooms for children with autism
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The formal investigation of the interior spaces of the residential bedrooms for children with autism is one of the basic tasks that should be known by the interior designer. Achieving an atmosphere compatible with his health condition, which contributes to generating a sense of spatial intimacy through the design dimension provided by the interior designer and his tireless endeavor to meet the needs of the child in an internal environment that achieves the functional dimension and spiritual approaches that enhance the child’s sense of spatial belonging and contribute to improving his mood and this positively reflects on his behavior and social integration. The current research has reached the most important design criteria that must be

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Publication Date
Wed Aug 17 2022
Journal Name
Aip Conference Proceedings
The effect of using Gaussian, Kurtosis and LogCosh as kernels in ICA on the satellite classification accuracy
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This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula

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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Mon Jul 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Monitoring and Prediction Functional Change of Land Uses Toward Urban Sustainability
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Urban land uses are in a dynamic state that varies over time, the city of Karbala in Iraq has experienced functional changes over the past 100 years, as the city is characterized by the presence of significant tourist and socio-economic activity represented by religious tourism, and it occur due to various reasons such as urbanization. The purpose of this study is to apply a Markov model to analyze and predict the behavior of transforming the use of land in Karbala city over time. This can include the conversion of agricultural land, or other areas into residential, commercial, industrial land uses. The process of urbanization is typically driven by population growth, economic development, based on a set of probabilities and transitions bet

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Publication Date
Thu Jan 01 2015
Journal Name
The 2d International Conference Of Buildings, Construction And Environmental Engineering (bcee2-2015)
Terrestrial Laser Scanning to Preserve Cultural Heritage in Iraq Using Monitoring Techniques
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