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The Estimation of Vibrational Energy of Two Coupled (Welded) Plates Using Statistical Energy Analysis
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This paper deals with a method called Statistical Energy Analysis that can be applied to the mechanical and acoustical systems like buildings, bridges and aircrafts …etc. S.E.A as a tool can be applied to the resonant systems in the circumstances of high frequency or/and complex structure». The parameters of S.E.A such as coupling loss factor, internal loss factor, modal density and input power are clarified in this work ; coupled plate sub-systems and explanations are presented for these parameters. The developed system is assumed to be resonant, conservative, linear and there is an equipartition of energy between all the resonant modes within a given frequency band in a given sub-system. The aim of this work is to find the energy stored in the sub-systems for two coupled (welded) plates in rectangular angle systems and study the effect of changing sub-systems dimensions, the results shows that as surface area of directly driven plates A1 increases energy level of plate 1 increases while a reduction in the energy level of indirectly driven plate (plate 2) is noticed. This is because of the strength of coupling decreases towards the weak coupling condition and this leads to a reduction in the power transferred from plate 1 to plate 2 and consequently a lower energy level for plate 2. In addition the effect of changing the internal loss factor for a range of (0.00001-0.1) causes a reduction of the values of energy level in these sub-systems. because the increasing of internal loss factor values led to the increasing of the material resistance and that will dissipate the energy flow across those sub-systems. A comparison is made between S.E.A models built by FORTRAN program and Finite Element model solved by ANSYS package.

 

 

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
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

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Publication Date
Sun Jun 09 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Rebamipide Film using Casting Technique for Local Action
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Abstract

The aim of this study was to prepare rebamipide ocular inserts in order to extend its release on the ocular surface for dry eye treatment. Solubility study was applied to the drug with or without l-arginine using different solvents. Solvent casting technique was used to prepare the inserts; l-arginine was used to solubilize the drug, hydroxypropyl methylcellulose grades (E5 and K15M) and poly ethylene glycol 200 were used as excipients. The inserts were evaluated for their physical and mechanical properties, moisture loss% and absorption %, surface pH, and in-vitro drug release. The use l-arginine exhibited an enhancement of rebamipide solubility in both deionized water and phosphate buffer (pH 7.4) by a

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Determination of essential and trace elements in various vegetables using ICP-MS
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Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Colloid And Interface Science
Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks
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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES
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Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Assessment of Traditional Asphalt Mixture Performance Using Natural Asphalt from Sulfur Springs
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This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement. Consequently, HSNA can serve as an

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Publication Date
Wed Aug 13 2025
Journal Name
Mechanics Of Time-dependent Materials
Performance evaluation of highly modified asphalt binders using elastomeric and plastomeric polymers
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Highly Modified Asphalt (HiMA) binders have garnered significant attention due to their superior resistance to rutting, fatigue cracking, and thermal distress under heavy traffic loads and extreme environmental conditions. While elastomeric polymers such as Styrene- Butadiene-Styrene (SBS) have been extensively used in HiMA applications, the potential of plastomeric polymers, including Polyethylene (PE) and Ethylene Vinyl Acetate (EVA), remains largely unexplored. This study aims to evaluate the performance of reference binder (RB) modified with plastomeric HiMA asphalt in comparison to SBS-modified binders and determine the optimal polymer dosage for achieving an optimal balance between rutting resistance and fatigue durability. The experi

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Mon Jul 01 2013
Journal Name
Optics & Laser Technology
Evaluation of PMMA joining to stainless steel 304 using pulsed Nd:YAG laser
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This paper reports an experimental study of welding of dissimilar materials between transparent Polymethylmethacrylate (PMMA) and stainless steel 304 sheets using a pulsed mode Nd:YAG laser. The process was carried out for two cases; laser transmission joining (LTJ) and conduction joining (CJ). The former is achieved when the joint is irradiated from the polymer side and the latter when the joint is irradiated from the opposite side (metal side). The light and process parameters represented by the peak power (Pp), pulse duration (τ), pulse repetition rate (PRR), scanning speed (ν) and pulse shape have a significant effect on the joint strength (Fb), joint bead width (b), joint quality and appearance. The optimum parameters were determined

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