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An intersection-based segment aware algorithm for geographic routing in VANETs
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route for the transmission of the packets of data in the direction of their destination by taking into consideration the status of the traffic segment when selecting the next intersection. Through this algorithm, a new formula for assessing the status of the segment is presented based on three elements: density, connectivity, and distance. To evaluate this routing algorithm, simulations are performed, once the results are obtained, they are compared with the existing routing algorithms. The evaluation of results offered evidence that our routing algorithm did well in terms of packet delivery ratio and packet delivery delay.

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Taibah University Medical Sciences
Preparing polycaprolactone scaffolds using electrospinning technique for construction of artificial periodontal ligament tissue
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Objectives The strategies of tissue-engineering led to the development of living cell-based therapies to repair lost or damaged tissues, including periodontal ligament and to construct biohybrid implant. This work aimed to isolate human periodontal ligament stem cells (hPDLSCs) and implant them on fabricated polycaprolactone (PCL) for the regeneration of natural periodontal ligament (PDL) tissues. Methods hPDLSCs were harvested from extracted human premolars, cultured, and expanded to obtain PDL cells. A PDL-specific marker (periostin) was detected using an immunofluorescent assay. Electrospinning was applied to fabricate PCL at three concentrations (13%, 16%, and 20% weight/volume) in two forms, which were examined through field emission

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Single-Phase Grid-Tied Transformerless Inverter of Zero Leakage Current for PV System
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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Physics
Evaluation of Mechanical Properties for Epoxy reinforced with palm oil /Zinc oxide composites
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In this research, the effect of reinforcing epoxy resin composites with a filler derived from chopped agriculture waste from oil palm (OP). Epoxy/OP composites were formed by dispersing (1, 3, 5, and 10 wt%) OP filler using a high-speed mechanical stirrer utilizing a hand lay-up method. The effect of adding zinc oxide (ZnO) nanoparticles, with an average size of 10-30 nm, with different wt% (1,2,3, and 5wt%) to the epoxy/oil palm composite,  on the behavior of an epoxy/oil palm composite was studied with different ratios (1,2,3, and 5wt%) and an average size of  10-30 nm.  Fourier Transform Infrared (FTIR) spectrometry and mechanical properties (tensile, impact, hardness, and wear rate) were used to examine the composites. The FTIR

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Quadrupole Moment & Deformation Parameter for Even-Even 38Sr (A=76-102) Nuclide
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Publication Date
Tue Sep 29 2020
Journal Name
Reaction Kinetics, Mechanisms And Catalysis
Development of two-step noncatalytic esterification of waste cooking oil for biodiesel preparation
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An innovative two-step noncatalytic esterifcation technique was proposed to synthesize alkyl esters from free fatty acids simulated in waste cooking oil, as a pretreatment process for biodiesel production, without adding any catalyst under normal conditions of pressure and temperature. The efect of methanol:oil molar ratio, reaction time, mixing rate, and reaction temperature were investigated. The results confrmed that the conversion of the reaction was increased when increasing the methanol molar ratio and decreased in prolonged reaction temperature. High conversion (94.545%) was successfully achieved at optimized conditions of 115:1, 65:1 methanol:oil molar ratio in the frst step and second step, respectively, other conditions i

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Controlled Release
Surface engineering tumor cells with adjuvant-loaded particles for use as cancer vaccines
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Publication Date
Mon Sep 04 2017
Journal Name
International Journal Of Environmental Science And Technology
A review of permeable reactive barrier as passive sustainable technology for groundwater remediation
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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Experimental Evaluation of Evaporative Cooling for Enhancing Photovoltaic Panels Efficiency Using Underground Water
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This paper presents an experimental study of cooling photovoltaic (PV) panels using evaporative cooling. Underground (geothermal energy) water used to extract heat from it during cooling and cleaning of PV panels. An experimental test rig was constructed and tested under hot and dusty climate conditions in Baghdad. An active cooling system was used with auxiliary an underground water tank to provide cold water as a coolant over both PV surfaces to reduce its temperature. The cellulose pad has been arranged on the back surface and sprays cooling on the front side. Two identical PV panels modules used: without cooling and evaporative water cooling. The experiments are comprised of four cases: Case (I): backside cooling, Ca

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