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Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of the compressed signal relative to the size of the uncompressed signal. The proposed algorithms where fulfilled with the use of Matlab package

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Antibacterial Photodynamic Effect of 532 nm Diode-Pumped Solid State and 650 nm Diode Lasers on Methicillin Resistant Staphylococcus Aureus in Vitro
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The photodynamic inactivation against Methicillin-resistant Staphylococcus aureus using two different lasers, 532 nm diode pumped solid state laser (DPSS) in combination with safranin O and 650 nm diode laser in combination with methylene blue was investigated in the present work. A hundred swab samples were collected from patients with burn and wound infections admitted to two hospitals in Baghdad (Specialized Burns Hospital in Medical City and Al Imamein Al Jwadein Medical City Hospital) from December 2015 to February 2016 Antimicrobial susceptibility was performed by using Kirby- Bauer method. The irradiation experiments included four groups; a control group, a photosensitizer only group, a laser irradiation only group and a laser irr

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Prioritized Text Detergent: Comparing Two Judgment Scales of Analytic Hierarchy Process on Prioritizing Pre-Processing Techniques on Social Media Sentiment Analysis
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Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

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Publication Date
Mon Feb 27 2023
Journal Name
Tem Journal
Predicting Age and Gender Using AlexNet
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Due to the availability of technology stemming from in-depth research in this sector and the drawbacks of other identifying methods, biometrics has drawn maximum attention and established itself as the most reliable alternative for recognition in recent years. Efforts are still being made to develop a user-friendly system that is up to par with security-system requirements and yields more reliable outcomes while safeguarding assets and ensuring privacy. Human age estimation and Gender identification are both challenging endeavours. Biomarkers and methods for determining biological age and gender have been extensively researched, and each has advantages and disadvantages. Facial-image-based positioning is crucial for many application

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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The theory of convergent between standard and optimal cost supporting actual cost in an Enterprise: بحث تطبيقي في معمل الألبسة الرجالية في النجف للفترة من 2007-2020
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The research aims to achieve proof of convergence between optimal costs and standard costs in calculating costs for the economic unit, support efforts aimed at adopting optimal costs in cost accounts and accounting thought in general, and achieve benefit from the theory of convergence between optimal costs and standard costs in the field of achieving actual costs in The economic unit in order to reduce and converge, and this came to address the possibility of adopting the concept of optimal costs in the production costs calculations for the purposes of rationalizing administrative decisions, and rationalizing the preparation of financial statements within management accounting.

The research concluded that

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Publication Date
Wed Aug 05 2026
Journal Name
Technology In Agronomy
Modeling wheat harvest index using stacking ensemble learning and seeder operational parameters
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Publication Date
Tue Jul 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

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Publication Date
Tue Mar 07 2017
Journal Name
The First International Conference For Engineering Research
Colony Counting Using iPad and iPhone Applications
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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Object Detection and Distance Measurement Using AI
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the performance of some r- (k,d) class estimators with the (PCTP) estimator that used in estimating the general linear regression model in the presence of autocorrelation and multicollinearity problems at the same time "
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In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

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