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A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation results based Maltab package show the control methodology has effectiveness performance in terms of the excellent dynamic behavior of the vehicle model by minimizing the tracking error and smoothness control signals without saturation state obtained, especially when adding a bounded external disturbances to the vehicle model.

 

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
WLAN Integrated with GPRS Network Securely
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In this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.

      Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy  was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP ad

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using Wavelet Network
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            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

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Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Ultra Wideband Cognitive Network Objective Issues
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Due to that the Ultra Wide Band (UWB) technology has some attractive features like robustness to multipath fading, high data rate, low cost and low power consumption, it is widely use to implement cognitive radio network. Intuitively, one of the most important tasks required for cognitive network is the spectrum sensing. A framework for implementing spectrum sensing for UWB-Cognitive Network will be presented in this paper. Since the information about primary licensed users are known to the cognitive radios then the best spectrum sensing scheme for UWB-cognitive network is the matched filter detection scheme. Simulation results verified and demonstrated the using of matched filter spectrum sensing in cognitive radio network with UWB and pro

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Communications
SDN Implementation in Data Center Network
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Publication Date
Sat Jun 26 2021
Journal Name
2021 Ieee International Conference On Automatic Control & Intelligent Systems (i2cacis)
Vulnerability Assessment on Ethereum Based Smart Contract Applications
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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Text Cryptography based on Arabic Words Characters Number
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Cryptography is a method used to mask text based on any encryption method, and the authorized user only can decrypt and read this message. An intruder tried to attack in many manners to access the communication channel, like impersonating, non-repudiation, denial of services, modification of data, threatening confidentiality and breaking availability of services. The high electronic communications between people need to ensure that transactions remain confidential. Cryptography methods give the best solution to this problem. This paper proposed a new cryptography method based on Arabic words; this method is done based on two steps. Where the first step is binary encoding generation used t

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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Hybrid LDPC-STBC communications system based on chaos
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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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