This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

Tomato (Solanum lycopersicum) is acknowledged worldwide as one of the major vegetable crops, as is the case in Iraq. This research in 2024 was designed to recognize the species of Root-Knot Nematode (RKN) in central Iraq, assess its distribution, and study the level of susceptibility of 5 tomato varieties (SPEEDY, GS-12, SUPER LUX, TALA, and JUDIVIS). Since there is a threat of chemical nematicides, a greenhouse study was performed to evaluate other control methods, such as the use of organic fertilizers and the extract of nettles (Urtica dioica). Root-knot nematode (RKN) species consisting of Meloidogyne incognita, M. arenaria, and M. javanica were found in Baghdad, while only M. incognita was found in Babil. Molecular identificati

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

The field experiment was conducted with the aim of developing and testing an automatic sprayer for agricultural spray experiments and studying the effect of spray pressure, spray speed and spray height on the spraying process. The effects of the major spraying factors (pressure, speed, and height) on the spraying performance of the automatic sprayer were studied. This study included several traits: First - the drop sizes - Second - the penetration of the spray into the vegetation cover - Third, the spray wasted. The results showed: - First: - Increase in coverage percentage when using the first speed, 2 km / h, which amounted to 26.85%. An increment in the spraying penetration of the vegetation cover was observed at the second speed

The Internet image retrieval is an interesting task that needs efforts from image processing and relationship structure analysis. In this paper, has been proposed compressed method when you need to send more than a photo via the internet based on image retrieval. First, face detection is implemented based on local binary patterns. The background is notice based on matching global self-similarities and compared it with the rest of the image backgrounds. The propose algorithm are link the gap between the present image indexing technology, developed in the pixel domain, and the fact that an increasing number of images stored on the computer are previously compressed by JPEG at the source. The similar images are found and send a few images inst

Objectives The strategies of tissue-engineering led to the development of living cell-based therapies to repair lost or damaged tissues, including periodontal ligament and to construct biohybrid implant. This work aimed to isolate human periodontal ligament stem cells (hPDLSCs) and implant them on fabricated polycaprolactone (PCL) for the regeneration of natural periodontal ligament (PDL) tissues. Methods hPDLSCs were harvested from extracted human premolars, cultured, and expanded to obtain PDL cells. A PDL-specific marker (periostin) was detected using an immunofluorescent assay. Electrospinning was applied to fabricate PCL at three concentrations (13%, 16%, and 20% weight/volume) in two forms, which were examined through field emission

The daily practices of humans produce various types of waste, which are a threat to the health and environment surrounding it, especially after the increase in quantities as a result of population growth and technological development, and here came the need for recycling solid waste as one of the modern concepts that achieve environmental benefits, The aim of the research is to evaluate the project of sorting and recycling of solid waste in the district of Mahmoudiya and whether its work is sustainable ,Conforming to modern standards, using standard checklists to determine the gap between the current laboratory reality and the requirements of those standards , Using the case study methodology as the most appropriate approach

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t