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Reliability Analysis of Multibit Error Correcting Coding and Comparison to Hamming Product Code for On-Chip Interconnect
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Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high number of errors to be corrected by any scheme used in NoC. The high correction capability with moderate number of check bits along with the reduction in power and area requires further investigation in the accuracy of the reliability model. In this paper, reliability analysis is performed by modeling the residual error probability Presidual which represents the probability of decoder error or failure. New model to estimate Presidual of MECCRLB is derived, validated against simulation, and compared to HPC to assess the capability of MECCRLB. The results show that HPC outperforms MECCRLB from reliability perspective. The former corrects all single and double errors, and fails in 5.18% cases of the triple errors, whereas the latter is found to correct all single errors but fails in 32.5% of double errors and 38.97% of triple errors.

 

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
ANALYSIS UNBALANCED FACTORIAL EXPERIMENTS FOR THE RICE CROP
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Abstract:

           The great importance that distinguish these factorial experiments made ​​them subject a desirable for use and application in many fields, particularly in the field of agriculture, which is considered the broad area for experimental designs applications.

            And the second case for the factorial  experiment, which faces researchers have great difficulty in dealing with the case unbalance we mean that frequencies treatments factorial  are not equal meaning (that is allocated a number unequal of blocks or units experimental per tre

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Partial Least Squares and Principal Components Methods by Simulation
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Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Comparison Between the Performance of Human Translators and AI-Supported Applications
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This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts

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Publication Date
Wed Dec 20 2006
Journal Name
Al-nahrain Journal Of Science
perparation and Comparison Study of Some New bis (Arylimido) Triruthenum Complexes‏
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A comparison study was made for the reaction of triruthenium carbonyl Ru3(CO)12 with azoarene ArN=NAr . This reaction was monitored in two kinds of solvents , toluene , and n- octane , which yielded new triruthenium carbonyl complex Ru3(μ3-NAr)2(CO)9 . The reactions of azoarenes ArN=NAr with Ru3(CO)12 formed the following trinuclear compound of Ru3((μ3- NAr)2(CO)9 (Ar-C6H4Br-4) in law yield . In addition , to new isomers species of mononuclear cyclometallated of Ru(BrC6H4N-NC6H4NBr-4)2(CO)2 in different percentages . The mechanism of the reaction domenstrates that the formation of trinuclear bis arylimido complexes , and ortho metallated was , the result of cleavage of nitrogen –nitrogen bond . Monitoring this gave evidence that the rea

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Clinical And Experimental Dentistry
Comparison of the accuracy of intraoral digital impression system and conventional impression techniques for multiple implants in the full-arch edentulous mandible
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Thermal Performance Analysis of Compact Heat Exchangers for Thermoelectric Generators
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The efficiency of internal combustion engines (ICE) is usually about thirty percent of the total energy of the fuel. The residual energy is lost in the exhaust gas, the lubrication, and the cooling water in the radiators. Recently much of the researcher’s efforts have focused on taking advantage of wasted energy of the exhaust gas. Using a thermoelectric generator (TEG) is one of the promising ways. However, TEG depends entirely on the temperature difference, which may be offered by the exhaust muffler. An experimental test has been conducted to study the thermal performance of a different muffler internal design. The researchers resort to the use of lost energy in an ICE using TEG, which is one of the ways to take adv

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Publication Date
Wed Dec 28 2022
Journal Name
Journal Of Chemical Technology And Metallurgy
THERMODYNAMIC ANALYSIS OF MOISTURE ADSORPTION ISOTHERM FOR MEFENAMIC ACID TABLETS
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Publication Date
Thu Mar 01 2012
Journal Name
Al-khwarzmi Engineering Journal
Dynamic response analysis for the parabolic trough of solar collector
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parabolic trough