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Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bayesian regularized neural networks (BRNNs), Bayesian additive regression trees (BART), extreme gradient boosting (xgBoost), and hybrid neural fuzzy inference system (HNFIS) were used considering the complex relationship of rainfall with sea level pressure. Principle components of SLP domain correlated with daily rainfall were used as predictors. The results revealed that the efficacy of AI models is predicting daily rainfall one day before. The relative performance of the models revealed the higher performance of BRNN with normalized root mean square error (NRMSE) of 0.678 compared with HNFIS (NRMSE = 0.708), BART (NRMSE = 0.784), xgBoost (NRMSE = 0.803), and ELM (NRMSE = 0.915). Visual inspection of predicted rainfall during model validation using density-scatter plot and other novel ways of visual comparison revealed the ability of BRNN to predict daily rainfall one day before reliably.

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Thu Mar 20 2025
Journal Name
3rd International Conference On Construction Engineering At: Damascus, Syria
Investigation on the Moment-Curvature Relationship in GFRP Reinforced Concrete Beams
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Experimental Investigation about the Effects of Blockage on Upstream Box Culverts
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This experimental study focuses on scouring in box culvert inlets under steady-state conditions and at different percentages of blockage ranging from 0% to 65%, and also looks at the hydraulics of water in the culvert. The investigation shows that the blockage of the culverts has influenced the scouring pattern at the blocked culverts' entrances. Ten experiments were carried out at the laboratory to see how blockage impacts the scouring pattern upstream of a box culvert during steady flow. Both partially blocked and unblocked cases were implemented in this study. The experimental tests were done until the equilibrium scour occurred, which took about 3.5 hours of water flow to reach equilibrium conditions.  The results r

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Publication Date
Thu Nov 01 2012
Journal Name
2012 First National Conference For Engineering Sciences (fnces 2012)
Laboratory investigation in the Hydrated lime effect on asphalt concrete mixture
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This investigation was undertaken to evaluate the effectiveness of using Hydrated lime as a (partial substitute) by weight of filler (lime stone powder) with five consecutive percentage namely (1.0, 1.5, 2.0, 2.5, 3.0) % by means of aggregate treatment, by introducing dry lime on dry and 2–3% Saturated surface aggregate on both wearing and binder coarse. Marshall design method, indirect tensile test and permanent deformation under repeated loading of Pneumatic repeated load system at full range of temperature (20, 40, 60) C0 were examined The study revealed that the use of 2.0% and 1.5 % of dry and wet replacement extend the pavement characteristics by improving the Marshall properties and increasing the TSR%. Finally, increase permanent

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Publication Date
Thu Jul 28 2022
Journal Name
Mechanics Based Design Of Structures And Machines
Experimental investigation on the damping characteristics in dry and saturated sands
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Thu Sep 01 2022
Journal Name
Iaes International Journal Of Robotics And Automation
Implementation of a complex fractional order proportional-integral-derivative controller for a first order plus dead time system
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This paper presents the implementation of a complex fractional order proportional integral derivative (CPID) and a real fractional order PID (RPID) controllers. The analysis and design of both controllers were carried out in a previous work done by the author, where the design specifications were classified into easy (case 1) and hard (case 2) design specifications. The main contribution of this paper is combining CRONE approximation and linear phase CRONE approximation to implement the CPID controller. The designed controllers-RPID and CPID-are implemented to control flowing water with low pressure circuit, which is a first order plus dead time system. Simulation results demonstrate that while the implemented RPID controller fails to stabi

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Publication Date
Sun Jan 01 2023
Journal Name
Rawal Medical Journal
Obesity in COVID-19 patients is a complex interaction
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Objective: To assess role of obesity in Covid-19 patients on antibodies production, diabetes development, and treatment of this disease. Methodology: This observational study included 200 Covid-19 patients in privet centers from January 1, 2021 to January 1, 2022. All patients had fasting blood sugars and anti-Covid-19 antibodies. Anthropometric parameters were measured in all participants. Results: The patients were divided into two groups according to body weight; normal body weight (50) and excess body weight (150). There was a significant difference between them regarding age. Diabetes mellitus developed in 20% of normal weight patients while 80% of excess weight patients had diabetes (p=0.0001). Antibodies production (IgM and

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Publication Date
Thu Jan 01 2015
Journal Name
Chemistry And Materials Research
Anticancer Activity of New Di-Nuclear Copper (I) Complex
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In-vitro biological activities of the free new H4L ( indole-7-thiocarbohydrazone) ligand and its Ni(II), Pd(II) , Pt(II), Cu(II), Ag(I), Zn(II) and Cd(II) complexes are screened against two cancerous cell lines, that revealed significant activity only for [Cu2Cl2(H4L)2(PPh3)2] after 72 h treatment by the highest tested concentrations. The Copper(I) complex was characterized by X-ray Crystallography and the NMR spectra, whereas it has been confirmed to have momentous cytotoxicity against ovarian, breast cancerous cell lines (Caov-3, MCF-7). The apoptosis-inducing properties of the Cu(I) complex have been investigated through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.

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