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Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets mentioned above and it emerges that the accuracy of the proposed system is 96.2%, which is better than the other methods in the IoTID20 Dataset, while the accuracy with the second dataset UNSW-NB15 yielded 98.85%. Lastly, using the third dataset, IoT-23, the suggested technique achieved 99.93%.

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Publication Date
Thu Nov 22 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Finite Elements Analysis Study of Warming Effect on Deboned Force for Embedded NiTinol Wire into Linear Low Density Polyethylene
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This study presents the debonding propagation in single NiTi wire shape memory alloy into linear low-density polyethylene matrix composite the study of using the pull-out test. The aim of this study is to investigate the pull-out tests to check the interfacial strength of the polymer composite in two cases, with activation NiTinol wire and without activation. In this study, shape memory alloy NiTinol wire 2 mm diameter and linear fully annealed straight shape were used. The study involved experimental and finite element analysis and eventually comparison between them. This pull-out test is considered a substantial test because its results have a relation with behavior of smart composite materials. The pull-out test was carried out by a u

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Economics And Finance Studies
INTEGRATION BETWEEN COBIT AND COSO FOR INTERNAL CONTROL AND ITS REFLECTION ON AUDITING RISK WITH CORPORATE GOVERNANCE AS THE MEDIATING VARIABLE
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Effect of synthesis parameters on the formation 4A zeolite crystals: characterization analysis and heavy metals uptake performance study for water treatment
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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
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), Bay

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Wed Aug 27 2025
Journal Name
2025 International Conference On Electrical, Communication And Computer Engineering (icecce)
A Hybrid Deep Learning Approach for Fault Classification in Electric Vehicle Drive Motors
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

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Publication Date
Tue Sep 06 2016
Journal Name
Al-qadisiyah Journal For Administrative And Economic Sciences
Awareness of the regulatory and administrative leadership and its role in achieving the effectiveness of the internal control system and achieve fair accountability
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The research aims to achieve a set of the most important objectives of the review of the role of creative administrative leadership in achieving aspects of economic reform in various government institutions and indicate the role of supervisory awareness of administrative leadership in the revitalization of the role of the internal control system to achieve the best use of available resources. This paper deals with three problems is the loss of financial resources of the state as a result of the growing phenomenon of administrative and financial corruption in the majority of government institutions, and the weakness of the role of the internal control system in the province on the resources available and to achieve the best use of these reso

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Engineering
Comparative Biosorption Of Pb(II), Cr(III) AND Cd(II) Ions In Single Component System By Live And Dead Anaerobic Biomass, Bath Study
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In this study, dead and live anaerobic biomass was used in biosorption of Pb(II), Cr(III) and Cd(II) ions from a synthetic wastewater. The biosorption was investigated by batch adsorption experiments. It was found that, the biosorption capacities were significantly affected by biosorbent dosage. The process follows Langmuir isotherm (regression coefficient 0.995, 0.99 and 0.987 for Pb(II), Cr(III) and Cd(II) ions, respectively, onto dead anaerobic biomass) model with uniform distribution over the biomass surface. The experimental uptake capacity was 51.56, 29.2 and 28 mg/g for Pb(II), Cr(III) and Cd(II), respectively, onto dead anaerobic biomass, compared with 35, 13.6 and 11.8 mg/g for Pb(II), Cr(III) and Cd(II), respectively, onto live

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
A Mathematical Model of a Thermally Activated Roof (TAR) Cooling System Using a Simplified RC-Thermal Model with Time Dependent Supply Water Temperature
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This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Sustainability of Agricultural Productivity of Potato Crop in Desert Soils and Evaluation of Water Productivity Under Drip Irrigation System with Future Climate Changes
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A field experiment was conducted during the spring season 2020 in Karbala proving/ Al-Sharia Distrit, located at latitude N 32° 42' 13.8" and longitude E 43° 54' 36.6" and at an altitude of 27 m above sea level. The experiment included a study of two factors: the first, Irrigation Interval, three treatments were used: irrigation treatment every 2 days, Irrigation treatment every 4 days, and Irrigation treatment every 6 days. The second factor is the addition of soil conditioners, in which four treatments were used: the control treatment without any addition, the treatment of adding bio-organic fertilizers, the treatment of adding water-conserving technology (polymer), and the treatment of adding water-conserving technology + fertilizers O

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