Decolorization of red azo dye (Cibacron Red FN-R) from synthetic wastewater has been investigated as a function of solar advanced oxidation process. The photocatalytic activity using ZnO as a photocatalysis has been estimated. Different parameters affected the removal efficiency, including pH of the solution, initial dye concentration and H2O2 concentration were evaluated to find out the optimum value of these parameters. The results proved that the optimal pH value was 8 and the most efficient H2O2 concentration was 100mg/L. Toxicity reduction percent for effluent solution was also monitored to assess the degradation process. This treatment method was able to strongly reduce the color and toxicity of reactive red dye-238 to about (99 an

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

This study was conducted for evaluating the cytotoxic effect of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli on the proliferation of primary cancer cell cultures, obtained from tumor samples that were collected from (13) cancer patients and as follows: (five colon cancer patients, two bladder cancer patients, two breast cancer patients, two stomach cancer patients and two lung cancer patients), and on normal cell line (rat embryonic fibroblast / REF) (in vitro) with the use of different concentrations starting from (1) mg/ml and ending with (0.0002) mg/ml by making two fold serial dilutions by using the 96- well microtiter plate, and in comparison with negative (PBS) and positive (MMC, at concentration

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Criteria to be met in selecting the obtimal areas for generating alternative electric energy from wind

Electric vehicles are emerging as a sustainable alternative to conventional transportation. However, route planning in Internet of Vehicles environments remains challenging because conventional routing algorithms based on travel distance or time do not adequately consider electric vehicle-specific constraints. Existing routing strategies often overlook the combined effects of battery energy, traffic congestion, and charging requirements, resulting in inefficient routing decisions. This paper proposes an adaptive Energy, Congestion, and Charging-Aware Routing (ECCAR) protocol that uses energy-feasibility verification, cost-based charging-station selection, and route re-optimization for electric vehicles in Internet of Vehicles enviro

The aim of the research is to:. Preparation and implementation of special educational units using multimedia to learn the skill of scrolling from below. 2 to recognize the impact of the use of multimedia in learning the skill of scrolling from below. 3 to identify the differences between the tests after the two groups research in learning the skill of passing from the bottom volleyball. The research represented the students of the first stage and the sample of the research was drawn randomly and the number of (50) students were divided into two experimental and control groups and each group (25) students were used standardized tests and conducting pre-tests and the implementation of the main exp

Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

The aim of this research to study.

The dimensions of organizational learning have been defined(learning dynamics, individuals empowerment, knowledge management and technology application) as well as the dimensions of learning organization have been defined (culture values, knowledge transfer, communication and employee characteristics), Asset completion questionnaire was used to collect data of this research from a purposely sample represent forty employees who works in Iraqi Planning Ministry at different positions. The research divided to four parts :

The first to the research methodology, the second to the theoretical review o