The electrode in the microbial fuel cell has a significant effect on cell performance. The treatment of the electrode is a crucial step to make the electrode surface more habitable for bacteria growth, thus, increases the power production as well as waste treatment. In the current study, two graphite electrodes were treated by a microwave. The first electrode was treated with 100W microwave energy, while the second one was treated with 600W microwave energy. There is a significant enhancement in the surface of the graphite anode after the pretreatment process. The results show an increase in the power density from 10 mW/m² to 15 mW/m² with 100w treatment and to 13.47 mW/m² with 600w treatment. An organic

Fire incidences are classed as catastrophic events, which mean that persons may experience mental distress and trauma. The development of a robotic vehicle specifically designed for fire extinguishing purposes has significant implications, as it not only addresses the issue of fire but also aims to safeguard human lives and minimize the extent of damage caused by indoor fire occurrences. The primary goal of the AFRC is to undergo a metamorphosis, allowing it to operate autonomously as a specialized support vehicle designed exclusively for the task of identifying and extinguishing fires. Researchers have undertaken the tasks of constructing an autonomous vehicle with robotic capabilities, devising a universal algorithm to be employed

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The aim of research is to show the effect of Ferric Oxide (Fe2O3) on the electricity production and wastewater treatment, since 2.5% of Ferric Oxide (Fe2O3) (heated and non heated) nanoparticles has been used. Characterization of nanoparticles was done using X-ray Diffraction (XRD) and Scan Electron Microscopy (SEM). The influence of acidity was also studied on both wastewater treatmenton the Chemical Oxygen demand (COD) and Biological Oxygen Demand (BOD) and voltage output was studied. From the results, it was infused that the dosage of 0.025 g/l and an initial pH 7 were founded to be optimum for the effective degradation of effluents. The results concluded that the treatment of anaerobic sludge wastewater using Ferric Oxide (Fe2O3) in

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

The aim of this paper, is to design multilayer Feed Forward Neural Network(FFNN)to find the approximate solution of the second order linear Volterraintegro-differential equations with boundary conditions. The designer utilized to reduce the computation of solution, computationally attractive, and the applications are demonstrated through illustrative examples.