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Mobile-based Human Emotion Recognition based on Speech and Heart rate
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Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth, to the smartphone which in turn sends it to the server. At the server side, the speech features are extracted from the speech signal to be classified by neural network. To minimize the misclassification of the neural network, the user heart rate measurement is used to direct the extracted speech features to either excited (angry and happy) neural network or to the calm (sad and normal) neural network. In spite of the challenges associated with the system, the system achieved 96.49% for known speakers and 79.05% for unknown speakers

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Publication Date
Thu Dec 01 2022
Journal Name
Ieee Transactions On Human-machine Systems
Myoelectric Control With Fixed Convolution-Based Time-Domain Feature Extraction: Exploring the Spatio–Temporal Interaction
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Publication Date
Fri Feb 17 2023
Journal Name
Sustainability
Sustainable Utilization of Machine-Vision-Technique-Based Algorithm in Objective Evaluation of Confocal Microscope Images
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Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and e

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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
Super-twisting based integral sliding mode control applied to a rotary flexible joint robot manipulator
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In this paper, a single link flexible joint robot is used to evaluate a tracking trajectory control and vibration reduction by a super-twisting integral sliding mode (ST-ISMC). Normally, the system with joint flexibility has inevitably some uncertainties and external disturbances. In conventional sliding mode control, the robustness property is not guaranteed during the reaching phase. This disadvantage is addressed by applying ISMC that eliminates a reaching phase to ensure the robustness from the beginning of a process. To design this controller, the linear quadratic regulator (LQR) controller is first designed as the nominal control to decide a desired performance for both tracking and vibration responses. Subsequently, discontinuous con

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Publication Date
Tue Nov 18 2014
Journal Name
Conference: First International Engineering Conference (iec2014)at: Ishik University, Erbil, Krg, Iraq
Visualization of People Attraction from Mobile Phone Trace Database: A Case study on Armada 2008 in French City of Rouen
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The mobile phone is widespread all over the world. This technology is one of the most widespread with more than five billion subscriptions making people describe this interaction system as Wireless Intelligence. Mobile phone networks become the focus of attention of researchers, organizations and governments due to its penetration in all life fields. Analyzing mobile phone traces allows describing human mobility with accuracy as never done before. The main objective in this contribution is to represent the people density in specific regions at specific duration of time according to raw data (mobile phone traces). This type of spatio-temporal data named CDR (Call Data Records), which have properties of the time and spatial indications for th

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Study Tensile Strength and Wear Rate for Unsaturated Polyester Resin and Nitrile butadiene Rubber Polymer Blend
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Abstract

    Binary polymer blend was prepared by mechanical mixing method of unsaturated polyester resin with Nitrile Butadiene Rubber (NBR) with different weight ratios (0, 5, 10 and 15) % of (NBR). Tensile characteristics and wear rates of these blends were studied for all mixing ratios. The microstructure of fracture surfaces of the prepared samples were investigated by optical microscope. The results were showed that strain rates of the resin material increase after blending it with rubber while the ultimate tensile strength and Young’s modulus values of it will decrease. It is also noticed that the wear rate of resin decreases with increasing of (NBR) content.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
MODELING DEATH RATE OF THE COVID-19 PANDEMIC IN IRAQ
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sat Jan 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
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AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

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Publication Date
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Fri Apr 02 2021
Journal Name
New Trends In Information And Communications Technology Applications: 4th International Conference, Ntict 2020, Baghdad, Iraq, June 15, 2020, Proceedings 4
Iris recognition using localized Zernike features with partial iris pattern
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