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Hybrid DWT-DCT compression algorithm & a new flipping block with an adaptive RLE method for high medical image compression ratio
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Huge number of medical images are generated and needs for more storage capacity and bandwidth for transferring over the networks. Hybrid DWT-DCT compression algorithm is applied to compress the medical images by exploiting the features of both techniques. Discrete Wavelet Transform (DWT) coding is applied to image YCbCr color model which decompose image bands into four subbands (LL, HL, LH and HH). The LL subband is transformed into low and high frequency components using Discrete Cosine Transform (DCT) to be quantize by scalar quantization that was applied on all image bands, the quantization parameters where reduced by half for the luminance band while it is the same for the chrominance bands to preserve the image quality, the zigzag scan is applied on the quantized coefficients and the output are encoded using DPCM, shift optimizer and shift coding for DC while adaptive RLE, shift optimizer then shift coding applied for AC, the other subbands; LH, HL and HH are compressed using the scalar quantization, Quadtree and shift optimizer then shift coding. In this paper, a new flipping block with an adaptive RLE is proposed and applied for image enhancement. After applying DCT system and scalar quantization, huge number of zeros produced with less number of other values, so an adaptive RLE is used to encode this RUN of zeros which results with more compression.Standard medical images are selected to be used as testing image materials such as CT-Scan, X-Ray, MRI these images are specially used for researches as a testing samples. The results showed high compression ratio with high quality reconstructed images  

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Laser
Parametric Optimization for Fatigue Life of 6061-T6 Aluminum Thin Sheets Processed with High-Speed Laser Shock Peening
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Abstract: Aluminum alloys grade 6061-T6 are characterized by their excellent properties and processing characteristics which make them ideal for varieties of industrial applications under cyclic loading, aluminum alloys show less fatigue life than steel alloys of similar strength. In the current study, a nanosecond fiber laser of maximum pulse energy up to 9.9 mJ was used to apply laser shock peening process (LSP) on aluminum thin sheets to introduce residual stresses in order to enhance fatigue life under cyclic loading Box-Behnken design (BBD) based on the design of experiments (DOE) was employed in this study for experimental design data analysis, model building and optimization The effect of working parameters spot size (ω), scannin

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design and Simulation of L1-Adaptive Controller for Position Control of DC Servomotor
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This paper presents L1-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L1-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L1-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L1-adaptive controller ensured uniformly bounded

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
ADAPTIVE CYCLIC PREFIX LENGTH FOR CONVOLUITIONAL CODE OFDM SYSTEM IN FREQUENCY SELECTIVE CHANNEL
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Orthogonal Frequency Division Multiplexing (OFDM) is one of recent years multicarrier modulation used in order to combat the Inter Symbol Interference (ISI) introduced by frequency selective mobile radio channel. The circular extension of the data symbol, commonly referred to as cyclic prefix is one of the key elements in an OFDM transmission scheme. This paper study The influence of the cyclic prefix duration on the BER performance of an OFDM-VCPL (Orthogonal frequency division multiplexing - Variable Cyclic Prefix Length) system and the conventional OFDM system with frame 64-QAM modulation is evaluated by means of computer simulation in a multipath fading channel. The adaptation of CP is done with respect to the delay spread estimation

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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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Publication Date
Mon Nov 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Solution of Riccati matrix differential equation using new approach of variational ‎iteration method
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To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

Publication Date
Wed May 12 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
The Relationship of Healthy Rationalist Pundit Thinking to the Spiking and Block Performance of Volleyball For Junior Players
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Publication Date
Sun Dec 28 2025
Journal Name
Al-fatih Journal
The impact of training on the sand development in the carrying(Speed ​​and power performance) BalambarzhEmpirical researchOn the young players Basra Balambarzh
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تعد المبارزة أحد الألعاب الرياضية التي يتأثر فيها الأداء بتطور القدرات الخاصة بالأداء ومنها تحمل (سرعة وقوة الأداء ),وأن أكثر الأساليب السابقة في تدريب تطوير تحمل(سرعة وقوة الأداء) بالمبارزة تكون على ارض صلبة مثل الخشب والألمنيوم آو الإسفلت وفي بعض القاعات يكون التارتان, وظل هذا الأسلوب لفترات طويلة في العراق ،حيث تستخدم تدريبات الإثقال التي تعمل على تنمية تحمل القوة . أما في الوقت الحاضر فقد ظهر اتجاه حديث في

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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)
Validity of Generalized Standard Addition Method for a Mixture of Amino Acid Analysis
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A Modified version of the Generlized standard addition method ( GSAM) was developed. This modified version was used for the quantitative determination of arginine   (Arg) and glycine ( Gly) in arginine  acetyl salicylate – glycine complex . According to this method two linear equations were solved to obtain the amounts of (Arg) and (Gly). The first equation was obtained by spectrophotometic measurement of the total absorbance of (Arg) and (Gly) colored complex with ninhydrin . The second equation was obtained by measuring the total acid consumed by total amino groups of (Arg) and ( Gly). The titration was carried out in non- aqueous media using perchloric acid in glacial acetic acid as a titrant. The developed metho

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Publication Date
Wed Mar 25 2015
Journal Name
Comptes Rendus Chimie
A novel method for the synthesis of biodiesel from soybean oil and urea
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The increasing demand for energy has encouraged the development of renewable resources and environmentally benign fuel such as biodiesel. In this study, ethyl fatty esters (EFEs), a major component of biodiesel fuel, were synthesized from soybean oil using sodium ethoxide as a catalyst. By-products were glycerol and difatty acyl urea (DFAU), which has biological characteristics, as antibiotics and antifungal medications. Both EFEs and DFAU have been characterized using Fourier transform infrared (FTIR) spectroscopy, and 1H nuclear magnetic resonance (NMR) technique. The optimum conditions were studied as a function of reaction time, reactant molar ratios, catalyst percentage and the effect of organic solvents. The conversion ratio of soybea

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