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
The need to exchange large amounts of real-time data is constantly increasing in wireless communication. While traditional radio transceivers are not cost-effective and their components should be integrated, software-defined radio (SDR) ones have opened up a new class of wireless technologies with high security. This study aims to design an SDR transceiver was built using one type of modulation, which is 16 QAM, and adding a security subsystem using one type of chaos map, which is a logistic map, because it is a very simple nonlinear dynamical equations that generate a random key and EXCLUSIVE OR with the originally transmitted data to protect data through the transmission. At th
... Show MoreMissing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s
... Show MoreInterested current Research measuring damage currency Swap by converting The ministry of higher Education and scientific Research money The Iraqi dinar To U.S dollar by Trade Bank Of Iraq , And that The damage Generated resulting from Deferent Between the Exchange Rate adopted From Central Bank of Iraq and Market Exchange Rate adopted by The Trade Bank Of Iraq , and Which led to the greet damage ( losses ) in Bearing by the ministry, which led to the reduction of the financial allocations for licensed curriculum outside of Iraq , and this in turn leads to reduction in the number of students Sender ( scholarships ) outside Iraq.
Where the estimated loss (damage) that suffer by the Ministry of H
... Show MoreOptical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
... Show MoreIn this review paper, several studies and researches were surveyed for assisting future researchers to identify available techniques in the field of classification of Synthetic Aperture Radar (SAR) images. SAR images are becoming increasingly important in a variety of remote sensing applications due to the ability of SAR sensors to operate in all types of weather conditions, including day and night remote sensing for long ranges and coverage areas. Its properties of vast planning, search, rescue, mine detection, and target identification make it very attractive for surveillance and observation missions of Earth resources. With the increasing popularity and availability of these images, the need for machines has emerged to enhance t
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
... Show More The most likely fusion reaction to be practical is Deuterium and Helium-3 (ð·âˆ’ð»ð‘’
3 ), which is highly desirable because both Helium -3 and Deuterium are stable and the reaction produces a 14 ð‘€ð‘’𑉠proton instead of a neutron and the proton can be shielded by magnetic fields. The strongly dependency of the basically hot plasma parameters such as reactivity, reaction rate, and energy for the emitted protons, upon the total cross section, make the problems for choosing the desirable formula for the cross section, the main goal for our present work.
Gas lift is one of the artificial lift techniques which it is frequently implemented to raise oil production. Conventionally, the oil wells produce depending on the energy of reservoir pressure and solution gas which declines due to continuous production. Therefore, many oil wells after a certain production time become unable to lift oil to the surface. Thus, the continuity of production requires implementation of gas lift which works to decrease the average fluid density in the tubing by injection gas through the annulus into the tubing. This paper aims to get maximum oil production of an Iraqi giant oil field at optimum injected gas rate. The field is located in south of Iraq and in
Let G be a graph, each edge e of which is given a weight w(e). The shortest path problem is a path of minimum weight connecting two specified vertices a and b, and from it we have a pre-topology. Furthermore, we study the restriction and separators in pre-topology generated by the shortest path problems. Finally, we study the rate of liaison in pre-topology between two subgraphs. It is formally shown that the new distance measure is a metric
This research investigates solid waste management in Al-Kut City. It included the collection of medical and general solid waste generated in five hospitals different in their specialization and capacity through one week, starting from 03/02/2012. Samples were collected and analyzed periodically to find their generation rate, composition, and physical properties. Analysis results indicated that generation rate ranged between (1102 – 212) kg / bed / day, moisture content and density were (19.0 % - 197 kg/ m3) respectively for medical waste and (41%-255 kg/ m3) respectively for general waste. Theoretically, medical solid waste generated in Al-Kut City (like any other city), affected by capacity, number of patients in a day, and hosp
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