Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder
The current research aims to identify the fear of intimacy and post-traumatic stress disorder among Yazidi women and the correlation between them. To achieve the objectives of the research, the researcher adopted the Descutner, 1991 & (Thelen) scale, which consisted of (35) items. The researcher also adopted the post-traumatic stress disorder scale for (Davidson, 1995) translated by (Abdul Aziz Thabet), which consists of (17) items. These two scales were administered to a sample of (200) individuals. Then, the researcher analyzes the data using the Statistical Package for Social Sciences (SPSS). The results showed that the research sample of Yazidi women has a fear of intimacy. The research sample of Yazidi women is characterized by
... Show MoreObjective: The aim of this study is to find out the impact of life events upon onset of depression, to describe the
prevalence of life events among depressed patients.
Methodology: Retrospective a case-control study conducted in AL-Diwanyia Teaching Hospital, Psychiatric
Department on A non-probability (purposive sample) of (60) depressed patients and (60) of healthy person were matched
with them from general population. The data were collected through the use of semi-structured interview by
questionnaire, which consists of two parts (1) divide, section A. cover letter and B. Sociodemographic data which consists
of 9-items, (2) Life events questionnaire consists of 51-items distributed to six dimensions include, family
Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle
... Show MoreThe fluctuation properties of energy spectrum, electromagnetic transition intensities and electromagnetic moments in nucleus are investigated with realistic shell model calculations. We find that the spectral fluctuations of are consistent with the Gaussian orthogonal ensemble of random matrices. Besides, we observe a transition from an order to chaos when the excitation energy is increased and a clear quantum signature of the breaking of chaoticity when the single-particle energies are increased. The distributions of the transition intensities and of the electromagnetic moments are well described by a Porter-Thomas distribution. The statistics of electromagnetic transition intensities clearly deviate from a Porter-Thomas distribution (i
... Show MoreThis article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss
... Show MoreThis study is to investigate the possibility of using activated carbon prepared from Iraqi date-pits (ADP) which are produced from palm trees (Phoenix dactylifera L.) as low-cost reactive material in the permeable reactive barrier (PRB) for treating lead (Pb<sup>+2</sup>) from the contaminated groundwater, and then compare the results experimentally with other common reactive materials such as commercial activated carbon (CAC), zeolite pellets (ZP). Factors influencing sorption such as contact time, initial pH of the solution, sorbent dosage, agitation speed, and initial lead concentration has been studied. Two isotherm models were used for the description of sorption data (Langmuir and Freundlich). The maximum lead sorp
... Show MoreMalaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f
... Show MorePermeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.
This paper will try to develop the permeability predictive model for one of Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).
Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua
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