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.
The present work deals with five species of parasitic Hymenoptera belonging to Pteromalidae, Eupelmidae and Eurytornidae which have been reared from brachid beetles. A new species, Eurytoma irakensis is described and the species, Bruchocida orientalis Crawford is recorded for the first time from Iraq.
The fresh water ecosystem constitute an essential and very important for human life, for this reason it should be kept away from all the chemical pollutants including the pesticides The best way for Fighting harmful insects.(such as Anophles larvae) is by the biological control.
In the present study two species of Cyclopoida: Copepod, Mesocyclops hyalinus and Cyclops agilis آ were used as predators for Anophles larvae.
The data showed that the percentages of predation were 65% and 56%
forM. hyalinus and C. agilis respectively
and the means of predation were 1.3 larvae/ female and 1.1
... Show MoreFlow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel
... Show MoreBabesiosis is a tick-borne disease caused by Babesia microti. We present a case of false positive HIV in the setting of confirmed babesiosis infection. An understanding that patients with babesiosis can have a false positive HIV test result is important in management decisions.
The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I
... Show MoreHepatitis-B (HBV) is a viral disease cause liver damage, cirrhosis, fibrosis and hepatocellular carcinoma. Present study attempted to elucidate the biochemical and haematological markers other than Australia antigen, of hepatitis,B,vairusV (HBsAg) for better assessment of HBV infection. The present study was conducted on 76 men, 50 of them were found to be HBeAg positive and 26 were negative, mean age was53±5.7years. Haematological parameters such as Absolute Erythrocyte( Abs Eryt), Absolute Leukocyte(Abs Leuk) , Haemoglobin(Hb), Packed Cell Volume(PCV),Mean Corpuscular Volume (MCV), Red Cell Distribution Width (RDW), Mean Corpuscular Haemoglobin (MCH),MCH Concentration(MCHC) ,Neutrophi
... Show MoreIn this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.
Abstract
This research aims to identify the relationship and the impact of the behavior of organizational citizenship in the performance of employees, as practiced behaviors organizational citizenship substantial role in achieving the objectives of both the organization and its staff at the same time, so it affects a large extent on the characteristics and performance of individuals employees and thus influence the success of the organization as a whole, problem of the research has indicated that there is a clear failure in the study of the impact of the behavior of organizational citizenship in the performance of employees, was chosen
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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