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Kernel-based machine learning intrusion detection systems for ICMPv6 DDoS detection
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Publication Date
Wed Dec 16 2020
Journal Name
Electronics
Downlink Training Design for FDD Massive MIMO Systems in the Presence of Colored Noise
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Massive multiple-input multiple-output (MaMi) systems have attracted much research attention during the last few years. This is because MaMi systems are able to achieve a remarkable improvement in data rate and thus meet the immensely ongoing traffic demands required by the future wireless networks. To date, the downlink training sequence (DTS) for the frequency division duplex (FDD) MaMi communications systems have been designed based on the idealistic assumption of white noise environments. However, it is essential and more practical to consider the colored noise environments when designing an efficient DTS for channel estimation. To this end, this paper proposes a new DTS design by exploring the joint use of spatial channel and n

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Emergency Messages Dissemination Challenges Through Connected Vehicles for Efficient Intelligent Transportation Systems: A Review
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Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and p

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Publication Date
Wed Nov 01 2017
Journal Name
International Journal Of Greenhouse Gas Control
Wettability of nano-treated calcite/CO2 /brine systems: Implication for enhanced CO2 storage potential
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Nanofluids are proven to be efficient agents for wettability alteration in subsurface applications including enhanced oil recovery (EOR). Nanofluids can also be used for CO2-storage applications where the CO2-wet rocks can be rendered strongly water-wet, however no attention has been given to this aspect in the past. Thus in this work we presents contact angle (θ) measurements for CO2/brine/calcite system as function of pressure (0.1 MPa, 5 MPa, 10 MPa, 15 MPa, and 20 MPa), temperature (23 °C, 50 °C and 70 °C), and salinity (0, 5, 10, 15, and 20% NaCl) before and after nano-treatment to address the wettability alteration efficiency. Moreover, the effect of treatment pressure and temperature, treatment fluid concentration (SiO2 wt%) and

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
Comparative Analysis of H2 and H∞ Robust Control Design Approaches for Dynamic Control Systems
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This paper discusses using H2 and H∞ robust control approaches for designing control systems. These approaches are applied to elementary control system designs, and their respective implementation and pros and cons are introduced. The H∞ control synthesis mainly enforces closed-loop stability, covering some physical constraints and limitations. While noise rejection and disturbance attenuation are more naturally expressed in performance optimization, which can represent the H2 control synthesis problem. The paper also applies these two methodologies to multi-plant systems to study the stability and performance of the designed controllers. Simulation results show that the H2 controller tracks a desirable cl

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Publication Date
Tue Mar 26 2024
Journal Name
World Electric Vehicle Journal
Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays
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The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

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Publication Date
Fri Dec 02 2022
Journal Name
Journal Of Physical Education
The Effect of Jigsaw Strategy on Learning Spiking in Volleyball for Sophomore Students
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The research aimed at designing teaching program using jigsaw in learning spiking in volleyball as well as identifying the effect of these exercises on learning spring in volleyball. The researchers used the experimental method on (25) students as experimental group and (27) students as controlling group and (15) students as pilot study group. The researchers conducted spiking tests then the data was collected and treated using proper statistical operations to conclude that the strategy have a positive effect in experimental group. Finally, the researchers recommended using the strategy in making similar studies on other subjects and skills.

Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Thu May 28 2026
Journal Name
International Journal Of Robotics And Control Systems
Integrating Multimodal Emotion Recognition with Deep Q-Learning for Adaptive Social Robot Interaction
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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Build and Implemented Learning Package for Prolog Programming Language Using Visual Basic.Net 2010
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E-Learning packages are content and instructional methods delivered on a computer
(whether on the Internet, or an intranet), and designed to build knowledge and skills related to
individual or organizational goals. This definition addresses: The what: Training delivered
in digital form. The how: By content and instructional methods, to help learn the content.
The why: Improve organizational performance by building job-relevant knowledge and
skills in workers.
This paper has been designed and implemented a learning package for Prolog Programming
Language. This is done by using Visual Basic.Net programming language 2010 in
conjunction with the Microsoft Office Access 2007. Also this package introduces several
fac

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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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