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Tolerating Permanent Faults in the Input Port of the Network on Chip Router
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Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets from the moment they enter the input component until they leave to the next router. The hardware redundancy approach is used to tolerate the faults in these fields due to their crucial role in managing the router operation. A built-in self-test logic is integrated into the input port to periodically detect permanent faults without interrupting router operation. These approaches make the NoC router more reliable than the unprotected NoC router with a maximum of 17% and 16% area and power overheads, respectively. In addition, the hardware redundancy approach preserves the network performance in the presence of a single fault by avoiding the virtual channel closure.

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Artificial Intelligence (ij-ai)
Evaluation of massive multiple-input multiple-output communication performance under a proposed improved minimum mean squared error precoding
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<span lang="EN-US">The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy- issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become con

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Mon Oct 13 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
Improvement of the Face Recognition Systems Security Against Morph Attacks using the Developed Siamese Neural Network
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Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

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Publication Date
Sun Mar 08 2015
Journal Name
All Days
Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin</p> ... Show More
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Publication Date
Sat Nov 08 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Concentrations of selected elements in permanent teeth and enamel among a group of adolescent girls in relation to severity of caries
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Background: Human teeth considered to be an important etiological host factor in relation to dental caries through its morphology and composition. Elements may incorporate in tooth structure during pre and post-eruptive period changing the resistance for caries. The aims of this study were to determine the concentration of selected major (Calcium and phosphorus) and trace elements (Ferrous iron, nickel, chromium and aluminum) in permanent teeth and enamel among a group of adolescent girls in relation to severity of dental caries Material and Methods: The study group consisted of 25 girls with an age of 13-15 years old referred by Orthodontists for extractions of upper first premolars (two sides). Tooth and enamel samples were prepared for

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Publication Date
Thu Feb 18 2021
Journal Name
Journal Of Optical Communications
Theoretical investigation of multiple input–multiple output (MIMO) technique for line of sight (LoS) underwater wireless optical communications system
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Abstract<p>In this paper, a theoretical investigation was suggested to study underwater wireless optical communication (UWOC) system based on multiple input–multiple output (MIMO) technique. The modulation schemes such as RZ-OOK, NRZ-OOK, 32-PPM and 4-QAM applied under different coastal water types. MIMO technique enabled the system to transmit data rate with longer distance link. The performance of the proposed system examined by BER and data rate as a metrics. Several impairments such as the types of water by the attenuation of coastal water and the distance link were taken into account for the transmission of the optical signal to appreciate the reliability of the MIMO technique. The theore</p> ... Show More
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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Parallel Routing in Wireless Sensor Network
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The limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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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
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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