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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
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Manganese Ions (Mn2+) from a Simulated Wastewater by Electrocoagulation/ Electroflotation Technologies with Stainless Steel Mesh Electrodes: Process Optimization Based on Taguchi Approach
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This study depicts the removal of Manganese ions (Mn2+) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm2, time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics
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The research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear

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Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Manganese Ions (Mn2+) from a Simulated Wastewater by Electrocoagulation/ Electroflotation Technologies with Stainless Steel Mesh Electrodes: Process Optimization Based on Taguchi Approach
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This study depicts the removal of Manganese ions (Mn2+) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm2, time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis of variance (ANO

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Publication Date
Sun Oct 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A novel data offloading scheme for QoS optimization in 5G based internet of medical things
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Surface Plasmon Resonance (SPR)-Based Multimode Optical Fiber Sensors for Electrical Transformer Oil Aging Detection
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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

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Publication Date
Tue Jun 14 2022
Journal Name
Chemical Papers
Nile red based dye D–π–A as a promising material for solar cell applications
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A recently reported Nile red (NR) dye conjugated with benzothiadiazole species paves the way for the development of novel organic-based sensitizers used in solar cells whose structures are susceptible to modifications. Thus, six novel NR structures were derived from two previously developed structures in laboratories. In this study, density functional theory (DFT) calculations and time-dependent DFT (TD-DFT) were used to determine the optoelectronic properties of the NR-derived moieties such as absorption spectra. Various linkers were investigated in an attempt to understand the impact of π-linkers on the optoelectronic properties. According to the findings, the presence of furan species led to the planarity of the molecule and a reduction

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Publication Date
Thu May 31 2012
Journal Name
Journal Of Baghdad College Dentistry
An evaluation of water absorption of Giomer in comparison to other resin-based restorative materials
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Background: Polymeric composites have been widely used as dental restorative materials. A fundamental knowledge and understanding of the behavior of these materials in the oral cavity is essential to improve their properties and performance. The goal of this study was to measure water sorption of four composite resins containing different filler and resin matrix contents. Materials and method: Resin composite specimens giomer (Beautifil II) Filtek™ P90, Filtek™ Z350 XT, and Tetric N Ceram were prepared in a cylindrical mould of 3mm thickness and 6mm diameter (n=10) and light cured . All specimens placed in silica-gel desiccators at 37˚C for seven days, a constant weight was obtained. All samples were immersed in deionized distill

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
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This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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Publication Date
Sun Oct 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A novel data offloading scheme for QoS optimization in 5G based internet of medical things
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

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