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

Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Abstract
This study aimed to survey fungi associated with the product Indomie and Chips being the trades Iargely by a very important segment of society who are the children, beside consumed by adults, but less so, as the survey results to accompany some fungui samples sterile showed proportions presence included various fungi like. Aspergillus flavus, Aspergillus niger, Penicillium Spp., Fusarium graminearum, F.moniliforme, Alternaria alternate and Rhizopus Spp., and other fungi sterile are not diagnosed. The results showed large dominion fungi A. niger by presence sterile samples of both producers, followed by infection in Fusarium Spp., Penicillium Spp., and A. alternata by infection percentage 55, 20 and 17% respectively for the pr

This experiment was carried out at the Field of Poultry, Department of Animal Resources, College of Agriculture, University of Baghdad, during the period from 1/5/2011 until 5/7/2011 to study the effect of adding arginine to laying hens diet on certain blood traits. A total of 100 Brown Lohmann laying hen chickens, 38 weeks of age, were randomly distributed into four treatment groups, with 25 hens for each treatment. Treatment groups were: T1: bird-fed diet with no additional arginine (control group); T2, T3, and T4: bird-fed diet supplemented with 0.4, 0.7, and 0.9%, respectively. Therefore, the total amounts of arginine in the four treatments (T1, T2, T3, and T4) become 1.1, 1.5, 1.8, and 2.0%, respectively. Results of this experiment rev