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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
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Use special Erwa to determine the number of live bacteria in different models
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Used in the study especially calibrated Erwa to determine the number of neighborhood or the Alayoshi number of bacteria in the count modeling and casting method dishes in addition to using the drop method yielded significant results for a match between the methods used ..

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Wed Jul 01 2020
Journal Name
International Journal Of Drug Delivery Technology
Gold nanoparticle: Synthesis, functionalization, enhancement, drug delivery and therapy: A review
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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Mechanical Engineering
Corrosion Resistance Enhancement for Low Carbon Steel by Gas Phase Coating
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Corrosion Resistance Enhancement for low carbon steel is very important to extend its life service, the coating process is one of the methods which can using to achieve this, and it's the most important in surface treatments to improve the properties of metals and alloys surfaces such as corrosion resistance. In this work, low carbon steel was nitrided and coated with nano zinc using gas phase coating technical, to enhance the resistance of corrosion. The process included adding two layers. The first, a nitride layer, was added by precipitating nitrogen (N) gas, and the second, a zinc (Zn) layer, was added by precipitating Zn. The process of precipitating was carried out at different periods (5, 10, and 15 minutes). Scan electron mi

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Publication Date
Fri Jan 01 2016
Journal Name
Isi Bilimi Ve Teknigi Dergisi/ Journal Of Thermal Science And Technology,
Enhancement of natural convection heat transfer of pin fin having perforated with inclination angle
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Publication Date
Mon Jul 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Enhancement of tooth eruption by using amniotic stem cells (Immunohistochemical study of VEGF marker)
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Background: Tooth eruption is a localized process in the jaws which exhibits precise timing and bilateral symmetry. Develop within the jaws and their eruption is a complex infancy process during which they move through bone to their functional positions within the oral cavity. For species with more than one set of teeth, eruption of the second set also accomplishes. The key to the successful clinical management of tooth eruption consists of understanding that this process consists largely of the local regulation of alveolar bone metabolism to produce bone resorption in the direction of eruption and shift and formation of bone at the opposite side.The amniotic sac contains a considerable quantity of stem cells. These amniotic stem cells are

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Publication Date
Fri Mar 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancement of Biogas production and organic reduction of sludge by different pre-treatment processes
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Anaerobic digestion (AD) is the most common process for dealing with primary and secondary wastewater sludge. In the present work, four pre-treatment methods (ultrasonic, chemical, thermal, and thermo-chemical) are investigated in Al-Rustumya Wastewater Treatment plant in order to find their effect on biogas production and volatile solid removal efficiency during anaerobic digestion.
Two frequencies of ultrasonic wave were used 30 KHz and 50 KHz during the pre-treatment. Sodium hydroxide was added in different amounts to give three pH values of 9, 10 and 11 in chemical pre-treating processes. The sludge was heated at 60oC and 80oC through thermal pre-treatment experiment. Also, the sludge was treated thermo-chemically at 80 oC and pH

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Comparison among variable selection models and its application to health dataset
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