With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

Visible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th

the electron correlation effect for inter-shell can be described by evaluating the fermi hole and partial fermi hole for Li atom comparing with Be+ and B+2 ions

Purpose: The concept of complete street is one of the modern trends concerned with diversifying means of transportation and reducing the disadvantages of mechanical transportation modes. This paper discusses the role of complete streets can play in developing the urban environment in the Alyarmok District of Baghdad.   Method/design/approach: The linear regression method used to analyze the opinions of 100 respondents surveyed in the study area in order to find the relationship between the urban environment and the complete street elements.   Theoretical framework: The Modern trends in urban planning aim to find alternatives to the policies of traditional transportation planning that focus on vehicular mobi

The present work describes guggul as a novel carrier for some anti-inflammatory drugs. Guggulusomes containing different concentration of guggul with aceclofenac were prepared by sonication method and characterized for vesicle shape, size, size-distribution, pH, viscosity, spread ability, homogeneity, and accelerated stability in-vitro drug permeation through mouse skin. The vesicles exhibited an entrapment efficiency of 93.2 ± 12%, vesicle size of 0.769 ± 3μm and a zeta potential of - 6.21mV. In vitro drug release was analyzed using Franz’s diffusion cells. The cumulative release of the guggulusomes gel (G2) was 75.8% in 18 hrs, which is greater than that all the gel formulation. The stability profile of prepare

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS