This study aims to simulate and assess the hydraulic characteristics and residual chlorine in the water supply network of a selected area in Al-Najaf City using WaterGEMS software. Field and laboratory work were conducted to measure the pressure heads and velocities, and water was sampled from different sites in the network and then tested to estimate chlorine residual. Records and field measurements were utilized to validate WaterGEMS software. Good agreement was obtained between the observed and predicted values of pressure with RMSE range between 0.09–0.17 and 0.08–0.09 for chlorine residual. The results of the analysis of water distribution systems (WDS) during maximum demand hours showed that the pumps unit capability cannot cover the high water demand during that time and resulted in a loss of pressure values, which were ranged between 0.2 and 2.1 bar. Moreover, the simulated results of the residual chlorine levels were within the permissible limits of 0.4–0.7 ppm, in different locations in the network. Providing good quality and adequate water supply is an important component for human life development. Modeling WDS is an efficient method of gaining a true understanding of the functioning of the network and determining the factors and conditions affecting the performance of the network.
Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover. The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit
... 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 MoreSpecialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give
... Show MoreThe current study aimed to reveal the role of the high school (boys) in the Governorate of Qurayyat (KSA) in promoting intellectual security of students, and whether there were differences in the estimates of the study sample due to the variables; the current position, academic qualification, teaching specialization and years of experience. This study was conducted by applying the analytical descriptive method, and used questionnaire as a tool for data collection. The survey consisted of (44) ite
... Show MoreThe problem of solid waste from domestic, industrial, commercial and medical sources is one of the most important problems facing the local administration in all Iraqi cities. The danger of this problem increases with the rapid increase in the population, changing lifestyles, consumption patterns, limited land suitable for landfill, and high costs of collection and disposal. This research aims to solve these problems by determining the locations of current landfills located in the outskirts of Baghdad Governorate. The ArcGIS program was used, where the sites of the landfills were determined on the map and through the available data about the areas. it was concluded that the existing landfill sites do not meet environmental conditions and
... Show MoreThe economic units always sought to maintain its market position and Trchinh the technology management and modern methods that will support success factors .vdila about it has become a customer and one profitability analysis of the most practical way benefit of economic units as modern management focus their attention on achieving this satisfaction, as the customers make up the axis of the success of every organization and that there are many government units aiming to profit directs attention to customers and the number of these units increased continuously. The administration used the customer profitability analysis in order to obtain information to assist in making and decision-making process. How to use modern tec
... Show MoreThe fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreThe investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
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