This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the fourth category was represented by special roads that lead certain service.
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreReservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
... 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
... Show MoreMany authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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Praise be to God, Lord of the Worlds, and prayers and peace be upon the Master of the Messengers, his family and all his companions, then after:
This is a brief research that contained its two rudders the command and its Style in Surat Al-Ma’idah a fundamental rhetorical study, and the study clarified the meaning of imperative in both; the Arabic language and in the terminology of the fundamentalists and rhetoricians in a concise manner, and then indicated the imperative of the command , the true meaning, and the meanings interpretated as an imperative form. I have mentioned some verses of Surat Al-Ma’idah, so what I have quot
... Show MoreIt is no secret to anyone that studying and investigating books of jurisprudence, despite their suffering, is a pleasure that cannot be compared to pleasure, and it has benefits and importance that cannot be limited and summed up, and it has great fruits that researchers and students of knowledge reap, as well as enriching libraries with jurisprudential material, after dusting them and taking them out to the light of libraries to be seen. Researchers and scholars, generation after generation, so that this nation can benefit from this pioneering intellectual and scientific product that was written for us by our first ancestors of working scholars who enriched human civilization with this scientific material, which has become a beacon guid
... Show MoreThe high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:
Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alk)
The developed model will aid the predictiv
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