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Combined DWT and DCT Image Compression Using Sliding RLE Technique
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A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V color space information giving the approximate and the detail coefficients. The detail coefficients are quantized, coded using run length encoding (RLE) and SRLE. The approximate coefficients were coded using DCT, since DCT has superior compression performance when image information has poor power concentration in high frequency areas. This output is also quantized, coded using RLE and SRLE. Test results showed that the proposed DWT DCT SRLE system proved to have encouraging results in terms of Peak Signal-to-Noise Ratio (PSNR), Compression Factor (CF) and execution time when compared with some DWT based image compressions.

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Biosynthesis, Characterization, Adsorption and Antimicrobial studies of Vanadium Oxide Nanoparticles Using Punica Granatum Extract
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This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V2O5NPs nanoparticles from vanadium sulfate VSO4.H2O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V2O5NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V2O5

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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Design, Construction, and Control Tracking of Solar Thermal Concentrator by Using PLC in Erbil
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This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p

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Publication Date
Wed Jul 01 2026
Journal Name
South African Journal Of Chemical Engineering
Enhancement of water-based drilling fluid using novel composite of silica and alumina nanoparticles
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One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

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Publication Date
Sat Dec 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study the Effect of Using Microwave Radiation and H-Donors on Improving Heavy Oil
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The present research has investigated the effect of microwave energy on improving the flow properties of heavy crude oil. The fragmentation of crude oil molecules was carried out with and without using 1 and 10 wt. % concentration of various types of H-donors like tetralin, cyclohexane, and naphtha.  Microwave power of 320, 385, and 540 W and radiation time 1-9 min, and temperature were studied. The kinematic viscosity and asphaltene content were measured for evaluation the improving of heavy crude oil.    Results show that viscosity of crude oil decreased with increase H-donor concentration, a maximum percentage of viscosity reduction was10.63 % for tetralin at 6 min radiation time, while 8.67%, and 7.34% for cyclohexane a

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Publication Date
Sat Sep 12 2026
Journal Name
Measurement
Monitoring and analyzing potato movement dynamics in a chain digger using smart sensing techniques
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Publication Date
Mon Dec 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Synthesis and Characterization of Nano Y Zeolite Using MWCNT as Media for Crystal Growth
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   The present research was conducted to synthesis Y-Zeolite by sol-gel technique using MWCNT (multiwalled carbon nanotubes) as crystallization medium to get a narrow range of particle size distribution with small average size compared with ordinary methods. The phase pattern, chemical structure, particle size, and surface area were detected by XRD, FTIR, BET and AFM, respectively. Results shown that the average size of Zeolite with and without using MWCNT were (92.39) nm and (55.17) nm respectively .Particle size range reduced from (150-55) nm to (130-30) nm. The surface area enhanced to be (558) m2/g with slightly large pore volume (0.231) km3/g was obtained. Meanwhile, degree of crystallization decreased to 120%.

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Publication Date
Tue May 12 2026
Journal Name
Geomatics
Semantic Mapping of Urban Mobile Mapping LiDAR Using Panoramic OCR and Geometric Back-Projection
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This paper presents a deterministic system that combines textual semantic data from panoramic images with LiDAR point clouds in a mobile mapping setup. Urban scenes often include textual elements, such as signs and business names, that provide key details typically missing from LiDAR-based urban digital twins. The presented method uses deep learning-based OCR to extract text from street panoramas and then categorizes it into urban types using a rule-based classifier. Text regions are geometrically projected into the LiDAR environment by converting image coordinates into viewing rays that intersect LiDAR surfaces, such as facades. Data from multiple panoramas are merged with confidence-weighted spatial clustering to produce consisten

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Publication Date
Fri May 30 2025
Journal Name
Journal Of Internet Services And Information Security
Enhancing Lung Cancer Classification using CT Images using Processing Techniques Employing U-Net Architecture
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