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SBOA: A Novel Heuristic Optimization Algorithm
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A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducted tests on ten single-objective functions from the 2019 benchmark functions of the Evolutionary Computation (CEC), as well as twenty-four single-objective functions from the 2022 CEC benchmark functions, in addition to four engineering problems. Seven comparative algorithms were utilized: the Differential Evolution Algorithm (DE), Sparrow Search Algorithm (SSA), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA), Butterfly Optimization Algorithm (BOA), Lion Swarm Optimization (LSO), and Golden Jackal Optimization (GJO). The results of these diverse experiments were compared in terms of accuracy and convergence curve speed. The findings suggest that SBOA is a straightforward and viable approach that, overall, outperforms the aforementioned algorithms.

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Publication Date
Thu Feb 01 2024
Journal Name
International Journal Of Biological Macromolecules
A novel designed nanofibrous mat based on hydroxypropyl methyl cellulose incorporating mango peel extract for potential use in wound care system
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Publication Date
Fri Oct 01 2021
Monitoring and controlling the speed and direction of a DC motor through FPGA and comparison of FPGA for speed and performance optimization
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<span lang="EN-US">We are living in the 21<sup>st</sup> century, an era of acquiring necessity in one click. As we, all know that technology is continuously reviving to stay ahead of advancements taking place in this world of making things easier for mankind. Technology has been putting his part in introducing different projects as we have used the field programmable gate arrays (FPGAs) development board of low cost and programmable logic done by the new evolvable cyclone software is optimized for specific energy based on Altera Cyclone II (EP2C5T144) through which we can control the speed of any electronic device or any Motor Control IP product targeted for the fan and pump. Altera Cyclone FPGAs’ is a board thro

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Publication Date
Fri Oct 04 2024
Journal Name
Analytical And Bioanalytical Chemistry Research
Optimization and Validation of a GC-FID/QuEChERS Method for Quantitative Determination of Spiromesifen Residues in Tomato Fruits, Leaves and Soil Matrices
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Pesticides serve a crucial function in contemporary farming practices, safeguarding agricultural crops against pest infestations and boosting production outputs. However, indiscriminate use has caused environmental and human health damage. This study aimed to develop and validate a gas chromatography-flame ionization detection (GC-FID) methodology for the direct and routine analysis of spiromesifen residues in soil, leaves, and tomato fruits. The proposed method prioritizes simplicity by avoiding derivatization steps, offering advantages over existing approaches that utilize lengthy multi-step extraction or derivatization prior to GC analysis. A key novelty of this work is the development of a QuEChERS extraction coupled directly to GC-FID

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model
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This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; 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
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Multidimensional Systolic Arrays of LMS Algorithm Adaptive (FIR) Digital Filters
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A multidimensional systolic arrays realization of LMS algorithm by a method of mapping regular algorithm onto processor array, are designed. They are based on appropriately selected 1-D systolic array filter that depends on the inner product sum systolic implementation. Various arrays may be derived that exhibit a regular arrangement of the cells (processors) and local interconnection pattern, which are important for VLSI implementation. It reduces latency time and increases the throughput rate in comparison to classical 1-D systolic arrays. The 3-D multilayered array consists of 2-D layers, which are connected with each other only by edges. Such arrays for LMS-based adaptive (FIR) filter may be opposed the fundamental requirements of fa

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Sun Apr 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Information Hiding using LSB Technique based on Developed PSO Algorithm
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<p>Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most effi

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Art Image Compression Based on Lossless LZW Hashing Ciphering Algorithm
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Abstract<p>Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and </p> ... Show More
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