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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
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Different Hand and Finger Grip Patterns using Surface Electromyography and Hand Dynamometry
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Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
A review on Activated Carbon Prepared from Agricultural Waste using Conventional and Microwave Activation
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In the recent years the research on the activated carbon preparation from agro-waste and byproducts have been increased due to their potency for agro-waste elimination. This paper presents a literature review on the synthesis of activated carbon from agro-waste using microwave irradiation method for heating. The applicable approach is highlighted, as well as the effects of activation conditions including carbonization temperature, retention period, and impregnation ratio. The review reveals that the agricultural wastes heated using a chemical process and microwave energy can produce activated carbon with a surface area that is significantly higher than that using the conventional heating method.

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Building a Statistical Model to Detect Foreground Objects and using it in Video Steganography
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Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

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Publication Date
Wed Dec 28 2022
Journal Name
Structural Concrete
Enhancement of RC T‐beams toughness using laced stirrups reinforcement for blast response predictions
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Abstract<p>The dynamic behavior of laced reinforced concrete (LRC) T‐beams could give high‐energy absorption capabilities without significantly affecting the cost, which was offered through a combination of high strength and ductile response. In this paper, LRC T‐beams, composed of inclined continuous reinforcement on each side of the beam, were investigated to maintain high deformations as predicted in blast resistance. The beams were tested under four‐point loading to create pure bending zones and obtain the ultimate flexural capacities. Transverse reinforcement using lacing reinforcement and conventional vertical stirrups were compared in terms of deformation, strain, and toughness changes of the tes</p> ... Show More
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Publication Date
Thu Nov 01 2018
Journal Name
Colloids And Surfaces B: Biointerfaces
Green synthesis of silver nanoparticles using turmeric extracts and investigation of their antibacterial activities
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Radon concentrations assessment in tap water for different areas in Baghdad city using Rad7
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
USING A NEW METHOD TO INDUCE TARGETED GENETIC MUTATIONS IN POTATO VIRUS Y (PVY)
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Publication Date
Thu Apr 01 2021
Journal Name
Journal Of Bridge Engineering
Experimental Investigation of Curved-Soffit RC Bridge Girders Strengthened in Flexure Using CFRP Composites
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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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