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Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterification reaction and showed considerable activity even after four consecutive recycling runs. The produced biodiesel after acid esterification and alkaline transesterification met the EN14214 international biodiesel standard specifications. To our best knowledge, this is the first study to introduce an acidic catalyst in capsule form. This method presents a new route for the safe storage of new materials to be used for biofuel production. Conductor-like screening model for real solvents (COSMO-RS) representation of the DES using σ-profile and σ-potential graphs indicated that MTPB and PTSA is a compatible combination due to the balanced presence and affinity towards hydrogen bond donor and hydrogen bond acceptor in each constituent.

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Simulation of a Wet Sulfuric Acid Process (WSA) for Utilization of Acid Gas Separated from Omani Natural Gas
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In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of   5000 m3/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature  and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for tw

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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
Fri Apr 04 2025
Journal Name
Journal Of Physical Education
Analytical Study of Goalkeeper Positioning Using MH System for Free Kick in Soccer
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Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Calculations of Signal to Noise Ratio (SNR) for Free Space Optical Communication Systems
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In this paper, we calculate and measure the SNR theoretically and experimental for digital full duplex optical communication systems for different ranges in free space, the system consists of transmitter and receiver in each side. The semiconductor laser (pointer) was used as a carrier wave in free space with the specification is 5mW power and 650nm wavelength. The type of optical detector was used a PIN with area 1mm2 and responsively 0.4A/W for this wavelength. The results show a high quality optical communication system for different range from (300-1300)m with different bit rat (60-140)kbit/sec is achieved with best values of the signal to noise ratio (SNR).

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Publication Date
Mon Dec 25 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Ketoprofen Nanosuspension Using Solvent Evaporation Technique
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The effective surface area of drug particle is increased by a reduction in the particle size. Since dissolution takes place at the surface of the solute, the larger the surface area, the further rapid is the rate of drug dissolution. Ketoprofen     is class II type drug according to (Biopharmaceutics Classification System BCS) with low solubility and high permeability. The aim of this investigation was to increase the solubility and hence the dissolution rate by the preparation of ketoprofen     nanosuspension using solvent evaporation method. Materials like PVP K30, poloxamer 188, HPMC E5, HPMC E15, HPMC E50, Tween 80 were used as stabilizers in perpetration of differ

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Reduction of Negative Effects For Moisture Tention of the Corn Plant by Spraying with Proline acid and Abscisic Acid.
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    This experiment was conducted in field of Agricultured Department Baquba/Diyala province in spring season 2011 to study the water stress by using foliar application concentrations of each Proline acid and Abscisic acid on proline content , ABA  content , chlorophyll content, protein conten and water content in leaves of Maize( cultivar, Buhooth 106).  The layout of the experiments was Split-  split plot design as RCBD with three replicates. The three concentrations   of spraying Proline acid levels ( 0 , 150 , 200 mg Proline .l-1 ) Three Abscisic acid levels ( 0 , 15 , 20 mgABA.l-1. ) and three periods of irrigation after(25, 50, 75%) of available water . Folair fertilizer were applied at three

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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