The research aims to evaluate Islamic electronic libraries and their service for downloading research and illustrated books, explaining their origins, features and types. The research was limited to the libraries available on the Internet that provide the service for downloading research and illustrated books. The researcher relied on the survey approach to identify the libraries and a sample of them (20 libraries) was selected. For the purpose of evaluating it according to five criteria related to the preparation and publication of Islamic electronic libraries (the responsible party, the goals and objectives, the year, the services it provides, the sections and subject specializations of its contents) and five criteria related to the service of downloading research and illustrated books (the number of research and illustrated books available in it, methods of accessing the library’s sections and services). And its sources, the possibilities and strategies for searching in it, the information available about research and the illustrated book, the number of interfaces used to access and download the book or research). Among the conclusions that the research came out with are: 1- There is no specific definition for Islamic electronic libraries, and some Muslims define the Islamic website as a large library rich in information about Islam. 2- There are four types of Islamic electronic libraries. The first type represents stand-alone Islamic libraries that provide electronic information services, and the other three types represent ready-made Islamic programs available via premium CDs or DVDs, or available via the Internet and can be downloaded via various electronic technologies and devices, including computers and smartphones. And tablets. 3- The goal of publishing libraries may be to preach to the Sunni sect, such as the Ahl al-Hadith Library, or to the Imami Shiites, such as the Narjis Library. 4- The oldest Islamic libraries are the Ahl al-Bayt Islamic Library and the Islam Way Library, and the year of their establishment is 1998 .
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Granular carbon can be used after conventional filtration of suspended matter or, as a combination of filtration - adsorption medium. The choice of equipment depends on the severity of the organic removal problem, the availability of existing equipment, and the desired improvement of adsorption condition.
Design calculations on dechlorination by granular - carbon filters considering the effects of flow rate, pH , contact time, head loss and bed expansion in backwashing , particle size, and physical characteristics were considered assuming the absence of bacteria or any organic interface .
One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone
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The chemical, physical and toxicological effects on health of synthetic dyes that used as tracking dye in the electrophoresis requires seriously search about alternative tracking dye. The present study is aimed to find an alternative dye from safe food dyes which commonly used in food coloring. Five dyes were selected depending on their chemical properties and the availability in local market: Brilliant Blue FCF, Tartrazine, Sunset Yellow FCF, Carmoisine, and green traditional, three dyes were chosen to be mixed as loading buffer: Brilliant Blue FCF, Sunset Yellow FCF as a basic because it give the whole range size of most traditional loading buffers that available in market, and adding the Carmoisine as a new indicator for the bands less t
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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