This study was carried out to investigate the effects of magnetized water on accumulated infiltration depth. A test rig was designed and constructed for this purpose was installed at the water tests laboratory of the Department of Water Resources Engineering at the University of aghdad. The investigation was carried out by using two types of soil, different flow velocities throughout magnetizing device and different configuration of magnets over and under the water passage of the magnetizing device. The soils that were used in the experiments are clayey and sandy soils. Six different flow velocities throughout magnetizing device ranged between 0.29 to 1.19 cm/s and ten configurations of arranging the magnets over and under the water passage of the magnetizing device were used. The magnates are sintered neodymium-iron-boron type. Tests results obtained with magnetized water were compared with those of untreated water. Results showed that magnetizing water increases the accumulated infiltration depth for the two types of soil. The highest increase in the accumulated infiltration depth is achieved under low flow velocity throughout the magnetizing device and with ten magnets. This highest increase for the clayey and sandy soils was 98.2% and 34.2%, respectively.
Blockchain has garnered the most attention as the most important new technology that supports recent digital transactions via e-government. The most critical challenge for public e-government systems is reducing bureaucracy and increasing the efficiency and performance of administrative processes in these systems since blockchain technology can play a role in a decentralized environment and execute a high level of security transactions and transparency. So, the main objectives of this work are to survey different proposed models for e-government system architecture based on blockchain technology implementation and how these models are validated. This work studies and analyzes some research trends focused on blockchain
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreThis paper deals with the subjective reflections of consumer values on fashion design. The consumer self is determined by the consumer's idea of himself, according to the intellectual, spiritual and social values, and these values take their intellectual reflection in the form of material values that the consumer finds in fashion design. These values are based on considerations between what is intellectual represented by the values of the consumer, and what is material determined by the fashion design, which also proceed from values that are visible or implied in costume design, such as the function, beauty and symbol. The consumer self gets its material image represented in the
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
... Show MoreText categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
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