The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.
The study aimed to investigate the relationship between the multiple intelligence and the numerical sense. The chosen population of the study was the 4th secondary stage students. The sample consisted of 400 female and male student. The researcher utilized two test; multiple intelligence test which include three categories of intelligence (logical-mathematical, spatial, and linguistics) consisted of (36) item, and the numerical sense test that consisted of (44) item. The two tests were constructed by the researcher himself. The psychometric properties of the test were also verified. The results showed that there was a correlation between the multiple intelligence and the numerical sense as well as the students’ means scores
... Show MoreThe Eurasian marsh frog Pelophylax ridibundus is a widespread species in Iraq. Examination of intestine of 25 marsh frogs collected in Al-Diwaniya city, middle of Iraq during the period from September to November 2014 revealed the presence of Nematotaenia dispar (Cestoda), Cosmocerca commutata and Cosmocercoides variabilis (Nematoda). Infection rates and intensity have been presented in this paper.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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Research Hypothesis from the fact that kicks off the effect that agricultural production in Iraq plays an important role in overcoming the food problem and achieving food security, but he became far far away from the provision of sufficient quantities of food products and then securing the Iraqi consumer food basket by the challenges faced by the agricultural sector.
To prove the hypothesis research in its structure in three axes came, the first axis eating historical significance to the subject of food over time periods as well as to clarify the concept of food security, and the second axis touched on the most important challenges facing the agricultural sector in Iraq and prevent the achievement of food requirements for members of
Delays and disruption are a common issue in both community and personal building programs The problem exists all throughout the world, but it is particularly prevalent in Iraq, where millions of dollars are squandered each time as a outcome. Delays and interruptions may have serious consequences not just for Iraq's construction plans, but also for the country's economic and social status. While numerous studies have been conducted to investigate the factors driving delays and disruption in Iraqi construction projects, slight consideration has been given to by what means project management implements and approaches have affected the occurrence of project delays and disruption. After analyzing the crucial reasons for delays and instability in
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The purpose of current study is to analyze the computer textbooks content for intermediate stage in Iraq according to the theory of multiple intelligence. By answering the following question “what is the percentage of availability of multiple intelligence in the content of the computer textbooks on intermediate stage (grade I, II) for the academic year (2017-2018)? The researcher followed the descriptive analytical research approach (content analysis), and adopted an explicit idea for registration. The research tool was prepared according the Gardner’s classification of multiple intelligence. It has proven validity and reliability. The study found the percentage of multiple intelligence in the content of computer textbooks for the in
... Show MoreCyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func