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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
Fri Dec 16 2022
Journal Name
Journal Of The College Of Languages (jcl)
The official business style of the Russian literary language. Problems of formation.: Официально-деловой стиль русского литературного языка. Проблематика формирования.
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In the article we consider features of official style, its functions and factors which influence the definition of the style. The topicality of the issue can be explained by rapid development of market economy which affects in its turn business correspondence. In this regard, there are a lot of cliché, terms and professionalisms appeared recently. Only correct usage of them can serve as a key to successful communication in Russian as well as other languages. This work highlights documents that are part of the diplomatic style such as declarations, credentials, notes, resolutions and other documents. The administrative style can include orders and instructions.

Аннотация.

 В данной статье рассмо

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Publication Date
Mon Oct 01 2012
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Ischemic VSD
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Background: Ischemic VSD or ventricular septal rupture (VSR) is a rare but lethal complication of myocardial infarction (MI). Multi-system coronary disease is present in more than 50% of these patients. The event occurs 2-8 days after an infarction and often precipitates cardiogenic shock. The differential diagnosis of postinfarction cardiogenic shock should exclude free ventricular wall rupture and rupture of the papillary muscles. To avoid the high morbidity and mortality associated with the disorder, patients should undergo emergent surgery. Concomitant coronary artery bypass may be required.
Objective: This study stressed on a very serious complication of a common pathology (myocardial infarction), despite it,s lethal complication

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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Monitoring of environmental variations of marshes in Iraq using Adaptive classification method.
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The object of the presented study was to monitor the changes that had happened
in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To
fulfill this goal, different satellite images had been used in different times, MSS
1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means which is unsupervised
classification and Neural Net which is supervised classification was used to classify
the satellite images 0Tand finally by use 0Tadaptive classification 0Twhich is0T3T 0T3Tapply
s0Tupervised classification on the unsupervised classification. ENVI soft where used
in this study.

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
استعمال انحدار الاسقاطات المتلاحقة و الشبكات العصبية في تجاوز مشكلة البعدية
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المستخلص يهدف هذا البحث الى تجاوز مشكلة البعدية من خلال طرائق الانحدار اللامعلمي والتي تعمل على تقليل جذر متوسط الخطأ التربيعي (RMSE) , أذ تم  استعمال طريقة انحدار الاسقاطات المتلاحقة  (PPR)    ,والتي تعتبر احدى طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية (curse of dimensionality) , وان طريقة (PPR) من التقنيات الاحصائية التي تهتم بأيجاد الاسقاطات الاكثر أهمية في البيانات المتعددة الابعاد , ومع ايجاد كل اسقاط

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Geological Journal
Development of 1D-Synthetic Geomechanical Well Logs for Applications Related to Reservoir Geomechanics in Buzurgan Oil Field
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Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Sat Oct 01 2016
Journal Name
I-manager’s Journal On Communication Engineering And Systems
SOLVING NETWORK CONGESTION PROBLEM BY QUALITY OF SERVICE ANALYSIS USING OPNET
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Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
WSN-WCCS: A Wireless Sensor Network Wavelet Curve Ciphering System
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With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS).  The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN.  It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show

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