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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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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

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Publication Date
Wed Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Biodegradation of Diesel Contaminated Soil Using Single Bacterial Strains and a Mixed Bacterial Consortium
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This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel  88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and

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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical Cellular Archive
Immunological and molecular detection of herpes simplex virus type 1 and 2 in patients clinically diagnosed with parkinson’s disease and multiple sclerosis
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To determine the relationship between herpes simplex virus 1, 2 and neurological disorders, sixty samples from patients with neurological diseases were collected (40 patients with Multiple sclerosis and 20 patients with Parkinson’s disease) all of whom attended both the Neurological science Hospital as well as the Neuropathology consultation Department in Baghdad Hospital In Iraq. The samples were collected in the time frame between November 2017 and April 2018. The ages of the patients that were investigated were between (17-76) years and compared to a control group consisting of 25 samples collected from apparently healthy individuals. All the studied groups were subjected to the measurement of anti-HSV 1, 2 IgG antibodies by the means

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

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Publication Date
Fri Aug 28 2020
Journal Name
2 Nd Al-noor International Conference For Science And Technology
Removal of Sulfur Compounds in Iraqi Kerosene Using 1-Ethyl -3- Methyllimidazolium Acetate
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In the present study, 1-ethyl -3-methyllimidazolium acetate ionic liquid is introduced for extractive desulfurization of Iraqi kerosene (1622ppm) and compared with 1-ethyl -3- methyllimidazolium tetrafloroborate. The effect of ionic liquid/ fuel ratio (1/9, 1/4, 1/2), temperature (25, 30,40oC), stirring speed (300,450rpm) and time (10, 30, 90, 180, 360 min) were studied. Sulfur compound analysis was performed using X-Ray fluorescence. The ionic liquid with acetate anion (OAc) showed better performance than tetrafloborate (BF4). The maximum extraction efficiency was 32% achieved at 1/2 IL/Fuel and 40oC after 90min. The oxidation step using hydrogen peroxide (8ml/200ml), catalyzed by acetic acid (2ml) and followed by ionic liquid extraction h

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Publication Date
Wed Feb 20 2019
Journal Name
Political Sciences Journal
Assessing the Impact of reformation in wise Administration of Ruling and constant development : A study of Arab Political
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The research has been talked on specific an important notions concerning with the dimensions of effectiveness of good governance and sustainable development inside all Arab states, So that the scientific article reflected the role of investments in various sections of institutional business by draw attention toward different projects about analyzing the whole political reality according to the standard indications of political and social stability on the regional level and international aspects. Therefore, the study resembled scientific contains and the dimensions of political reform and administrative overhauling within governmental system in order to achieve all raw objectives for sustainable development. All international and

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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
The level of evaluation of the educational counselors ’performance as a predictor of their level of satisfaction with their evaluation
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The current research aims to reveal the level of satisfaction of the mentors with the evaluation of their performance according to gender (male - female) and to formulate the predictive equation for the level of performance (dependent variable) from knowing the level of satisfaction with the evaluation (independent variable). (16 paragraphs) contains alternatives to the answer that measures the level of satisfaction (weak, medium, and high) (1,2,3), that is, with a hypothetical average of (32). It consisted of 100 educational counselors consisting of 45 males and 55 females, the results of the research concluded that the level of satisfaction with performance is below the mean when compared with the hypothetical average of the scale of s

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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Publication Date
Fri Apr 05 2019
Journal Name
International Journal Of Nanoelectronics And Materials
Characterization and Responsivity of Graphene Loaded Zinc Sulphide within Visible Light Spectrum
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In this study, the nanocrystal-ZnS-loaded graphene was synthesized by a facile coprecipitation route. The effect of graphene on the characterization of Zinc Sulphide (ZnS) was investigated. The X-ray Diffraction (XRD) results reveal that ZnS has cubic system while hexagonal structure which is observed by loading graphene during the preparation of ZnS. Energy Dispersive X-ray Spectroscopy (EDS) analysis proved the presence of all expected elements in the prepared materials. Nanosize of fabricated materials has been measured using Scanning Electron Microscopy (SEM) technique. This study also found that the graphene plays a critical role in lowering the optical energy gap of ZnS nanoparticles from 4 eV to 3.2 eV. The characterization of detec

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