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,

      Faintly continuous (FC) functions, entitled faintly S-continuous and faintly δS-continuous functions have been introduced and investigated via a -open and -open sets. Several characterizations and properties of faintly S-continuous and faintly -Continuous functions were obtained. In addition, relationships between faintly s- Continuous and faintly S-continuous function and other forms of FC function were investigated. Also, it is shown that every faintly  S-continuous is weakly S-continuous. The Convers is shown to be satisfied only if the co-domain of the function is almost regular.

The Old World Screwworm Fly Chrysomya bezziana is a new insect pest on cattles and other domestic recor¬ded for the first from Iraq. It was first observed in cow's vagina in September of 1996 in Shaikh Hammed (Tarmiya), near Baghdad city. Chrysomya bezziana Villeneuve is well known as one of the most important insect pests of livestock. Its larvae infest living tissues by causing myiasis. In a wide range of worm-blooded host species (Spradbery and Vanningham, 1980; Spradbery and Kirk. 1992). It is widely dist¬ributed species over an extensive area of tropical and subtropical Africa, the Arabian Gulf countries, Iran. Indian subcontinent. South-East Asia. Indonesia, and as far east as Papua New Guinea (Zurapt, 1965; Djalayer et al. 1978;

    The present study was carried out on forty eight epididymis of sexually mature dogs to elucidate light microscope features and the presence of testosterone receptors inside epididymis in different seasons. Twenty four dogs aged 3 years were used during the periods from 1/2/2015-1/2/2016. The epididymis were carefully dissected from the testis after orchidectomy operations and fixed, dehydrated, clarified and embedded in paraffin. Sections were stained with hematoxylin and eosin and periodic acid schiff. As well as, paraffin embedded cytoimmunochemistry technique was used for detection of testosterone receptors. Muscular coats showed no significant differences during different seasons or among segments. Epithelial heigh

Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co