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bsj-1074
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty. We also present a method for selecting the speakers used for MLP training which further improves identification performance.

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Neural Tube Defects in Iraq
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1.
Embryonic Origin of Neural Tube Defects.
Insaf Jasim Mahmoud
2.
Etiology of Neural Tube Defectss.
Ali Abdul Razzak Obed
3.
Epidemiology of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi
4.
Surgical Management of Neural Tube Defects.
Laith Thamer Al-Ameri
5.
Prevention of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Windows-Based Special Applications Router
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The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks
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Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

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Publication Date
Wed Sep 08 2021
Journal Name
Egyptian Journal Of Chemistry
Synthesis And Characterization Of Metal(II) Complexes With Azo Dye Ligand And Their Industrial And Biological Applications
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Azo ligand 4-((2-hydroxy-3,5-dimethylphenyl)diazenyl) benzoic acid was synthesized from 4-aminobenzoic acid and 2,4- dimethylphenol. Azo dye compounds have been characterized by different techniques (1H-NMR, UV-Vis and FT-IR). Metal chelates of (ZnII, CdII and HgII) have been synthesized with azo ligand (L). Produced compounds have been identified by using spectral studies, elemental analysis(C.H.N.) and conductivity. Produced metal chelates were studied using mole ratio as well sequences contrast types. Rate of concentration(1×10-4-3×10-4 Mole/L) sequence Beer's law. Compound solutions have been noticed height molar absorptivity. The addendum of ligand and compounds has applied as disperse dyes on cotton fabrics for antibacterial activit

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Global Trends In Pharmaceutical Sciences
A REVIEW: CEFPODOXIME PROXETIL (DOXEF. PROXETIL) DISCOVERY, PREPARATION, APPLICATIONS AND COMPARISON WITH CEFPODOXIME- CLAVULANIC ACID IN ACTIVITY
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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Symposium On Networks, Computers And Communications (isncc)
An Interference Mitigation Scheme for Millimetre Wave Heterogeneous Cloud Radio Access Network with Dynamic RRH Clustering
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Publication Date
Sun May 01 2022
Journal Name
Optical Fiber Technology
Optical fiber sensor network integrating SAC-OCDMA and cladding modified optical fiber sensors coated with nanomaterial
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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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