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Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression algorithms. In this research, the design of SEA based on different speech models (Laplacian model or Gaussian model) has been implemented using two types of discrete transforms, which are Discrete Tchebichef Transform and Discrete Tchebichef-Krawtchouk Transforms. The proposed estimator consists of dual stages of a wiener filter that can effectively estimate the clean speech signal. The evaluation measures' results show the proposed SEA's ability to enhance the noisy speech signal based on a comparison with other types of speech models and a self-comparison based on different types and levels of noise. The presented algorithm's improvements ratio regarding the average SNRseq are 1.96, 2.12, and 2.03 for Buccaneer, White, and Pink noise, respectively.

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Publication Date
Tue Jan 10 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Enhancement the Educational Technology by Using 5G Networks
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With the spread of global markets for modern technical education and the diversity of programs for the requirements of the local and global market for information and communication technology, the universities began to race among themselves to earn their academic reputation. In addition, they want to enhance their technological development by developing IMT systems with integrated technology as the security and fastest response with the speed of providing the required service and sure information and linking it The network and using social networking programs with wireless networks which in turn is a driver of the emerging economies of technical education. All of these facilities opened the way to expand the number of students and s

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Publication Date
Thu Jun 01 2017
Journal Name
Process Biochemistry
Microbial levan from Brachybacterium phenoliresistens : Characterization and enhancement of production
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
Enhancement In Ballistic Performance Of Composite Armor Through Nano Ceramic
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In this study, industrial fiber and polymer mixtures were used for high-speed impact (ballistic) applications where the effects of polymer (epoxy), polymeric
mixture (epoxy + unsaturated polyester), synthetic rubber (polyurethane), Kevlar fiber, polyethylene fiber (ultra High molecular weight) and carbon fiber.
Four successive systems of samples were prepared. the first system component made of (epoxy and 2% graphene and 20 layer of fiber), then ballistic test was
applied, the sample was successful in the test from a distance of 7 m. or more than, by using a pistol personally Glock, Caliber of 9 * 19 mm. The second
system was consisting of (epoxy, 2% graphene, 36 layers of fiber and one layer of hard rubber), it was succeeded

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Publication Date
Sat Mar 19 2022
Journal Name
Al-khwarizmi Engineering Journal
Enhancement of System Security by Using LSB and RSA Algorithms
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A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

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Publication Date
Mon Mar 27 2017
Journal Name
Optical And Quantum Electronics
Photocurrent enhancement of heat treated CdSe-sensitized titania nanotube photoelectrode
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Publication Date
Mon May 18 2026
Journal Name
Scientific Reports
Fluorescein spectrofluorometric quenching detection of chloride and iodide using eight-Blue-LEDs excitation and dual solar cells
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Abstract<p>This study presents a novel, custom‑built fluorescence detector for the precise determination of chloride and iodide ions based on their quenching effect on fluorescein. The detection system incorporates eight blue LEDs irradiation sources arranged at 0–90° angles relative to twin solar cell detectors connected. Two fluorescence quenching strategies were developed. The injected‑mixture mode (IMFQ) exhibited linear ranges of 0.00–1.00 mM for Cl⁻ and 0.00–1.25 mM for I⁻, with detection limits of 20 µM and 10 µmol L⁻¹, respectively. The continuous‑flow mode (CFFQ) demonstrated superior sensitivity with a dispersion factor of 1.33, wider linear ranges (0.1–6.0 m</p> ... Show More
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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
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The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
Qur'anic intentions in the Prophet’s Investigation (Selected models)
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This research deals with the role of Qur’anic intents in facilitating and facilitating the understanding of the reader and the seeker of knowledge of the verses of the Holy Qur’an, particularly in the doctrinal investigations (prophecies), and the feature that distinguishes reference to the books of the intentions or the intentional interpretations is that it sings from referring to the books of speakers and delving into their differences in contractual issues and facilitating access To the meanings, purposes and wisdom that the wise street wanted directly from the rulings and orders contained in the verses of the wise Qur’an.

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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