The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

Smoking and central obesity have both been linked to periodontitis, but their combined relationship with periodontal disease may be influenced by demographic and behavioral factors. This cross-sectional study analyzed records of 420 adult dental patients attending the College of Dentistry at the University of Baghdad. Data included demographic characteristics, smoking status, periodontal clinical findings, body mass index (BMI), and waist-to-height ratio (WHtR). Periodontitis was defined according to the 2018 classification framework, and logistic regression models were used to examine the associations of smoking and obesity-related indicators with periodontitis. The overall prevalence of periodontitis was 36.4%. Participants with p

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

This article comprehensively examines the history, diagnosis, genetics, diversity, and treatment of SARS-CoV-2. It details the emergence of coronaviruses over the past 50 years, including the coronavirus from 2019 and its subsequent mutations, along with updated information about this virus. This review explains the development and nomenclature of coronaviruses, their cellular invasion through glycoprotein spikes binding to ACE-2 receptors, and the mechanism of cell entry via endocytosis. Diagnosis methods for COVID-19, including nucleic acid amplification, serology, and imaging techniques like chest X-ray and CT scan tests, are discussed. Treatment approaches for COVID-19 are outlined, emphasizing healthcare, antiviral medications like Rem

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t