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
To investigate the role of IL-6 and IL-8 in the immune-regulatory mechanisms involved in the recurrent spontaneous abortion of the first trimester of pregnancy. Serum level of IL-6 and IL-8 were determined in 25 women of age (20-35) years who had a spontaneous abortion of unknown aetiology during the first trimester of pregnancy .They were compared with the corresponding levels of 20 pregnant and non-pregnant women as control groups .cytokine levels were measured by (ELISA) technique .The women with spontaneous abortion had highly significant (P < 0.01) increased serum level of IL-8 and highly significant (P < 0.01 ) decreased level of IL-6 compared to those with normal pregnant and non-pregnant women. The results of this study ma
... Show MoreMammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti
Background: The diagnosis of prostatic pathology may be of challenging , as some difficult and suspected, atypical cases may lack basal cell layer by routine H&E sections . Antibodies against 34BE12(HMW-CK) and p63 aid the diagnosis of such cases , to distinguish benign from malignant prostatic lesions.
Objective: to identify basal cells in atypical prostatic lesions ,and distinguish benign from malignant prostatic lesions.
Type of the study: A retro-spective study.
Methods: 115cases of paraffin embedded prostatic tissue blocks ,diagnosed as : 76 cases were benign prostatic hy
... Show More<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami
... Show MoreThe combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show MoreSpray pyrolysis technique was subjected to synthesized (SnO2)1-x (TiO2: CuO) x Thin films on different substrates like glass and single crystal silicon using. The structure of the deposited films was studied using x-ray diffraction. A more pronounced diffraction peaks of SnO2 while no peaks of (CuO , TiO2 ) phase appear in the X-ray profiles by increasing of the content of (TiO2 , CuO) in the sprayed films. Mixing concentration (TiO2 , CuO) influences on the size of the crystallites of the SnO2 films ,the size of crystallites of the spray paralyzed oxide films change in regular manner by increasing of (TiO
... Show MoreComplexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4-thiadiazole-2-yl)phenyl) thiourea have been prepared and characteizedby elemental analysis, Ff-[R, and u.v./ visible spectra moreover,determination of metal content M%o by flame atomic absorptionspectroscopy, molar conductance in DMSO solution and magneticmoments (peffl.The result showed that the ligand (L) was coordinated to Mn+2, Ni+2,Ct+2,2n+2,Cd+2, and Hg+2 ions through the nitrogen atoms and sulpheratoms.From the result obtained, rhe following general formula [MLCl2] hasbeen given for the prepared complexes with an octahedral geometryaround the metal ions for all complexes.where M= Mn+2, Ni+2, cu+2, zn+2, cd+2, and Hg+2 l= l-phenyl-3-(2-(5-(phenyl amino
... Show MoreMixed metal ligand complexes is reported with Curcumin (CUM) as a primary ligand and 1:10-phenanthroline (phen ) as secondary ligand. The structures of these complexes are confirmed by using FT-IR and UV- electronic spectroscopies, magnetic moments, melting points , molar conductivity measurements .and the metal % analysis revealed that the complexes analyze indicates a six coordinated as[M(CUM)( Phen)2]Cl, M=Mn (II), Co(II), Ni(II),Cu(II) ,Zn(II) , Cd(II) , Hg(II) and [M’ (CUM)( Phen)2]Cl2 M’= Cr(III) &. Fe(III). In-vitro antimicrobial studies on ( Curcumin and 1:10-phenanthroline ligands and mixed metal ligand complexes against {(Bacillus subtilis (G+) , Esherichia Coli (G-) and as well as antifungal activities against Candida albican
... Show MorePreparation of superposed thin film (CdTe)1-xSex / ZnS) with concentration of (x= 0.1, 0.3, 0.5) at a temperature of substrate (Ts= 80 0C) by using Thermal Vacuum Evaporation System. The measurement of X-ray diffraction shows that the compounds CdTe, ZnS, (CdTe)1-xSex and (CdTe)1-xSex / ZnS have a polycrystalline structure, the C-V characteristic shows that the capacitance degrease by increasing the concentration (x) in reverse bias, while the I-V characteristic shows the current dark (Id) increase in forward and reverse bias by increasing (x) and the photocurrent (Iph) increase in reverse bias by increasing the concentration (x), the values of photocurrent are greater than from the values of the dark current for all concentrations
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