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bsj-3715
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 pitch, tone, and frequency. The speaker's models are created and saved in the system environment and used to verify the identity required by people accessing the systems, which allows access to various services that are controlled by voice, speaker identification involves two main parts: the first part is the feature extraction and the second part is the feature matching.

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Molecular Identification of Methylorubrum extorquens using PCR-Amplified MxaF Gene Fragments as A Molecular Marker
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  Methylotrophs bacteria are ubiquitous, and they have the ability to consume single carbon (C1) which makes them biological conversion machines. It is the first study to find facultative methylotrophic bacteria in contaminated soils in Iraq. Conventional PCR was employed to amplify MxaF that encodes methanol dehydrogenase enzyme. DNA templates were extracted from bacteria isolated from five contaminated sites in Basra. The gene specific PCR detected Methylorubrum extorquens as the most dominant species in these environments. The ability of M. extorquens to degrade aliphatic hydrocarbons compound was tested at the laboratory. Within 7 days, gas chromatographic (GC) studies of remaining utilize

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Fabrication and Characterization of Nanofibers Membranes using Electrospinning Technology for Oil Removal
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Oily wastewater is one of the most challenging streams to deal with especially if the oil exists in emulsified form. In this study, electrospinning method was used to prepare nanofiberous polyvinylidene fluoride (PVDF) membranes and study their performance in oil removal. Graphene particles were embedded in the electrospun PVDF membrane to enhance the efficiency of the membranes. The prepared membranes were characterized using a scanning electron microscopy (SEM) to verify the graphene stabilization on the surface of the membrane homogeneously; while FTIR was used to detect the functional groups on the membrane surface. The membrane wettability was assessed by measuring the contact angle. The PVDF and PVDF / Graphene membranes efficiency

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Improving Fractal Image Compression Scheme through Quantization Operation
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We explore the transform coefficients of fractal and exploit new method to improve the compression capabilities of these schemes. In most of the standard encoder/ decoder systems the quantization/ de-quantization managed as a separate step, here we introduce new way (method) to work (managed) simultaneously. Additional compression is achieved by this method with high image quality as you will see later.

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
COMPARATIVE STUDY FOR EDGE DETECTION OF NOISY IMAGE USING SOBEL AND LAPLACE OPERATORS
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Human recognition by utilizing voice recognition and visual recognition
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Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detecting Keratoconus by Using SVM and Decision Tree Classifiers with the Aid of Image Processing
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 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Determination of essential and trace elements in various vegetables using ICP-MS
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Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Planner And Development
Relationship of LST, NDVI, and NDBI using Landsat-8 data in Duhok city in 2019-2022
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One of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the

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