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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
Tue Sep 23 2025
Journal Name
Journal Of Plant Protection Research
Smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Handling a problem of transport solid waste in Baghdad City to Healthy landfill sites using transportation Model
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 A problem of solid waste became in the present day common global problem among all countries, whether developing or developed countries, and can say that no country in the world today is immuning from this dilemma which must find appropriate solutions. The problem has reached a stage that can not ignore or delay, but has became a daily problem occupies the minds of ecologists, economists and politicians took occupies center front in the lists of  priorities for the countries in terms of finding solutions to the rapid scientific and radical them. and that transport costs constitute an important component of total costs borne by the municipal districts in the process of disposal of solid waste, so any improvement in the

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Simultaneous Determination of Piroxicam and Codeine Phosphate Hemihydrate in a Pharmaceutical Dosage Form Using Validated HPLC Method
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An easy, eclectic, precise high-Performance Liquid Chromatographic (HPLC) procedure was evolved and validated to estimate of Piroxicam and Codeine phosphate. Chromatographic demarcation was accomplished on a C18 column [Use BDS Hypersil C18, 5μ, 150 x 4.6 mm] using a mobile phase of methanol: phosphate buffer (60:40, v/v, pH=2.3), the flow rate was 1.1 mL/min, UV detection was at 214 nm. System Suitability tests (SSTs) are typically performed to assess the suitability and effectiveness of the entire chromatography system. The retention time for Piroxicam was found to be 3.95 minutes and 1.46 minutes for Codeine phosphate. The evolved method has been validated through precision, limit of quantitation, specificity,

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Wed Jan 01 2025
Journal Name
Al Mustansiriyah Journal Of Pharmaceutical Sciences
1, 3, 4-OXADIAZOLE: Synthesis Derivatives &Biological Activities. A Review article
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Heterocyclic compounds serve as crucial structural elements in the field of pharmaceutical medicinal chemistry. The five-membered heterocyclic nucleus of 1,3,4-oxadiazole occupies a distinctive position within medicinal chemistry and plays a vital role in the development of anticancer agents. Recognized as a significant pharmacophore for approximately 85 years, 1,3,4-oxadiazole is in high demand across various biological and chemical disciplines. This small and straightforward nucleus is found in numerous compounds that are the focus of research concerning their properties, synthesis, derivatives, and pharmacological activities, including anticancer, antibacterial, antimalarial, anti-inflammatory, antidepressant, analgesic, and antiviral

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of Stability of Cefamandol and Ceftazidime with Clavulanic Acid Against Extended Spectrum ?- Lactamase
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The aim of this study is to evaluate in-vitro activity of Cefamandol (Cfm) and Ceftazidime (Cfz), in combination with Clavulanic acid (CA) against ten complicated multiresistant uropathogenic E.coli .One hundred clinical strains were isolated from patients with chronic urinary tract infections (UTIs), these isolates were identified by the Api identification systems. The antimicrobial susceptibility tests were determined by Kirby-Bauer method, all of them were sensitive to Imipenem (Imp). Ten strains were chosen for the present study, they were resistant to Ampicillin (Amp), Amoxicillin (Amo), Carbenicillin (Cb), Ticarcillin (Tic), Azlocillin (Azl), Amoxicillin\ Potassium Clavulanate {Augmentin(Amc)}, (Amo\CA), Ticarcillin\ Potas

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Publication Date
Thu Dec 19 2024
Journal Name
Ieee Explorer
A Novel Flow Priority and Continuity Control Mechanism in SDN Network
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In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Science And Research (ij
Mathematical Models for Predicting of Organic and Inorganic Pollutants in Diyala River Using AnalysisNeural Network
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Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

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Publication Date
Sun Dec 18 2022
Journal Name
Journal Of The College Of Basic Education
A (k,ℓ) Span in Three Dimensional Projective Space PG(3,p) Over Galois Field where p=4
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الغرض من هذا العمل هو دراسة الفضاء الإسقاطي ثلاثي الأبعاد PG (3، P) حيث p = 4 باستخدام المعادلات الجبرية وجدنا النقاط والخطوط والمستويات وفي هذا الفضاء نبني (k، ℓ) -span وهي مجموعة من خطوط k لا يتقاطع اثنان منها. نثبت أن الحد الأقصى للكمال (k، ℓ) -span في PG (3،4) هو (17، ℓ) -span ، وهو ما يساوي جميع نقاط المساحة التي تسمى السبريد.

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