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

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

            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

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

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

A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30^o, 45^o and 60^o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho

Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018

Identification of pathogens and locating their inocul¬um source (S) are the first strategies toward successful disease management program the pretransplating seedl¬ing damping - off problem on vegetable crops was found to be caused by Pythium aphanidermatum and Rhizocto¬nia solani. Both fungi were isolated from peat (moss) for the first time in Iraq. In addition, considerable num¬ber of pathogenic fungi was found as contaminants in soil samples from Alrashidiah vegetable covered farming station. Among the isolated fungi were: Pythium apha¬nidermatum, Rhizoctonia solani, Sclerotinia sclerotiorum, Fusarium oxysporum, Fusarium solani phialophora spp., Cephalisporium spp Rizopus stolonfier and Botrytis cine¬rea, in addition to several

Soil water use and water storage vary by vegetative management practices, and these practices affect land productivity and hydrologic processes. This study investigated the effects of agroforestry buffers (AB), grass buffers (GB), and biofuel crops (BC), relative to row crops (RC) on soil water use for a claypan soil in northern Missouri, USA. The experiment located at the Greenley Memorial Research Center included RC, AB, GB, and BC established in 1991, 1997, 1997, and 2012, respectively. Soil water reflectometer sensors installed at 5‐, 10‐, 20‐, and 40‐cm depths monitored soil water from April to November in 2017 and 2018. Results showed significant differences in weekly volumetric water content (VWC) among treatments for all fou