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

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

One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

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

Solar tracking systems used are to increase the efficiency of the solar cells have attracted the attention of
researchers recently due to the fact that the attention has been directed to the renewable energy sources. Solar tracking systems are of two types, Maximum Power Point Tracking (MPPT) and sun path tracking. Both types are studied briefly in this paper and a simple low cost sun path tracking system is designed using simple commercially available component. Measurements have been made for comparison between fixed and tracking system. The results have shown that the tracking system is effective in the sense of relatively high output power increase and low cost.

Background: War represents a major human crisis; it destroys communities and results in ingrained consequences for public health and well-being

Objective: We set this study to shed light on the public health status in Iraq after the successive wars, sanctions, sectarian conflicts, and terrorism, in light of certain health indicators.

Design: The primary source of data for this analysis comes from the Iraqi Ministry of Health, and The World Health Organization disease surveillance.

Results: Most of the morbidity indicators are high, even those that are relatively declining recently, are still higher than those repor

      Cadmium Oxide films have been prepared by vacuum evaporation technique on a glass substrate at room temperature. Structural and optical properties of the films are studied at different annealing temperatures (375 and 475) ËšC, for the thickness (450) nm at one hour. The crystal structure of the samples was studied by X- ray diffraction. The highest value of the absorbance is equal to (78%) in the wavelength (530) nm, at annealing temperature (375) ËšC. The value of at a rate of deposition is (10) nm/s. The value of optical energy gap found is equal to (2.22) eV.