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

            Nowadays, it is convenient for us to use a search engine to get our needed information. But sometimes it will misunderstand the information because of the different media reports. The Recommender System (RS) is popular to use for every business since it can provide information for users that will attract more revenues for companies. But also, sometimes the system will recommend unneeded information for users. Because of this, this paper provided an architecture of a recommender system that could base on user-oriented preference. This system is called UOP-RS. To make the UOP-RS significantly, this paper focused on movie theatre information and collect the movie database from the IMDb website that provides informatio

The purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε  VO.

The development of the internet of things (IoT) and the internet of robotics (IoR) are becoming more and more involved with our daily lives. It serves a variety of tasks some of them are essential to us. The main objective of SRR is to develop a surveillance system for detecting suspicious and targeted places for users without any loss of human life. This paper shows the design and implementation of a robotic surveillance platform for real-time monitoring with the help of image processing, which can explorer places of difficult access or high risk. The robotic live streaming is via two cameras, the first one is fixed straight on the road and the second one is dynamic with tilt-pan ability. All cameras have image processing capabilities t

Worldwide, shipping documents are still primarily created and handled in the traditional paper manner. Processes taking place in shipping ports as a result are time-consuming and heavily dependent on paper. Shipping documents are particularly susceptible to paperwork fraud because they involve numerous parties with competing interests. With the aid of smart contracts, a distributed, shared, and append-only ledger provided by blockchain technology allows for the addition of new records. In order to increase maritime transport and port efficiency and promote economic development, this paper examines current maritime sector developments in Iraq and offers a paradigm to secure the management system based on a hyper-ledger fabric blockchain p

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