Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff

The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Discrete   logarithms  are applied      in many    cryptographic problems  . For instance ,   in public   key .  and for construction of sets with disti nct sums of  k-clcments.  The   purpose o r  this   paper

is  to  modify  the  method ol' informationl1·iding  using        discrete logarithms  , introduce new properties of St - sets ,   uscdthe direct product   of    groups   to construct  cyclic group and finally, present modified   method   for   knapsack &

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Nowadays, due to our everyday stress and current stressful lifestyle, the loss of items appears a frequent issue and may be very inconvenient. In this regard, until the IoT becomes part of everyday life, we can use the software as an efficient tool to assist a person's searching, verifying, and finding lost belongings. This paper presents an Android-based application that we proposed and implemented to help users find lost items. Utilizing this software will enable the subscriber to record his request to the relevant authority. In addition, a special section offers to insert a contact telephone number or email to communicate between the person who found the item and the person who lost it. During testing, among other services, the p

This research was from an introduction, three topics and a conclusion, as follows:
The first topic: the concept of Islamic banks and their emergence and development, which includes three demands are:
The first requirement: the concept of Islamic banks and types, and there are two requirements:
* Definition of Islamic banks language and idiom.
* Types of Islamic banks.
The second requirement: the emergence and development of Islamic banks.
Third requirement: the importance of Islamic banks and their objectives.
We learned about the concept of banks and their origins and how they developed and what are the most important types of Islamic banks
The second topic: Formulas and sources of financing in Islamic banks and

This work illustrates an enhanced visible light photocatalytic degradation of methyl orange dye (M.O.) by employing BiOI / BiOCl composites prepared under room temperature and without any organic precursors. Various experimental parameters have been studied, namely; composition of the composite, irradiation time and cell material. Composition D which implied 75% BiOI and 25% BiOCl has shown the highest bleaching of M.O. dye. This confirms the optimum photo-sensitization phenomenon for this composition in comparison to others. In the optimum photo-sensitized composite the electron of the conduction band reveals better reducing power and the hole of the valence band exhibits more oxidative power than those of pure BiOI electron and hole. Acco