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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
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Determination of cefotaxime-sodium at nanoscale level by a microflow injection cell via measuring turbidity using five irradiation sources (WSLEDs) with a single solar cell
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This work presents a completely new develop an analyzer, named NAG-5SX1-1D-SSP, that is simple, accurate, reproducible, and affordable for the determination of cefotaxime sodium (CFS) in both pure and pharmaceutical drugs. The analyzer was designed according to flow injection analysis, and conducted to turbidimetric measurements. Ammonium cerium nitrate was utilized as a precipitating agent. After optimizing the conditions, the analysis system exhibited a linear range of 0.008-27 mmol. L-1 (n=29), with a limit of detection of 439.3 ng/sample, a limit of quantification of 0.4805 mg/sample, and a correlation coefficient of 0.9988. The repeatability of the responses was assessed by performing six successive injections of CFS at concentra

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

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Publication Date
Fri Sep 20 2024
Journal Name
Journal Of Nano Research
Impact of Copper Doping on Nanocrystalline SnO<sub>2</sub> Thin Films Synthesized by Sol-Gel Coating and Chemical Bath Deposition for Gas Sensor Applications
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This work focuses on the preparation of pure nanocrystalline SnO2 and SnO2:Cu thin films on cleaned glass substrates utilizing a sol-gel spin coating and chemical bath deposition (CBD) procedures. The primary aim of this study is to investigate the possible use of these thin films in the context of gas sensor applications. The films underwent annealing in an air environment at a temperature of 500 C for duration of 60 minutes. The thickness of the film that was deposited may be estimated to be around 300 nm. The investigation included an examination of the structural, optical, electrical, and sensing characteristics, which were explored across various preparation circumstances, specifically focusing on varied

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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Alternative security solutions offered by virtual private network vpn model proposal to use alternatives to Cisco and Microsoft security in al-rasheed bank-delegate general office- northern region
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The study aims to provide a Suggested model for the application of Virtual Private Network is a tool that used to protect the transmitted data through the Web-based information system, and the research included using case study methodology in order to collect the data about the research area ( Al-Rasheed Bank) by using Visio to design and draw the diagrams of the suggested models and adopting the data that have been collected by the interviews with the bank's employees, and the research used the modulation of data in order to find solutions for the research's problem.

The importance of the study Lies in dealing with one of the vital topics at the moment, namely, how to make the information transmitted via

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Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Fri Jan 02 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Flattening of the posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion in relation to age using computed tomography
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Background: The posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion shows significant flattening. This study aimed to correlate between the flattening of the posterior slope of the articular eminence, with dental status, age, genders, on both sides using computed tomography. Materials and Methods: The sample of the present study was a total of 117 Iraqi subjects, who admitted to the maxillofacial department at Al-Sadr Teaching Hospital in Al-Najaf city. The examination was performed on CT scanner; the eminence inclination was measured in two methods using sagittal section. Results: Clinically, the inclination of articular eminence was higher in edentulous subjects than i

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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Assessment of Serum Levels of the WNT Pathway Antagonist (Dickkopf-1) in a Sample of Type 2 Diabetic Patients with Retinopathy using Two Groups of Antidiabetics
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Objectives: Dickkopf-1 (DKK-1) is WNT/b-catenin pathway antagonist which plays a detrimental role in the development of diabetic retinopathy (DR). This research aimed to assess serum DKK-1 levels in diabetic patients who have and have not developed DR and, compare them with the control subjects finding out whether we can use it as an indicator for DR early diagnosis and to find out which one of the widely used two groups of antidiabetic treatments had the greater effect on this biomarker and hence on the progression of DR. Methods: The study participants were divided into two subgroups: First, 70 patients (36 male, 34 female) with type 2 diabetes mellitus, among them 35 patients diagnosed with DR and 35 with no evidence of DR, and s

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