Mining drug networks is a very important research issue to discover hidden relations between multi drug-entities relations, such as multi drug-pathways, multi drug-targets, and multi drug-diseases. One very important relation is the drug-pathway, where drugs affect the human body through their pathways. In this paper, a probabilistic Heterogeneous Network Multi-label Classifier (HNMC) is proposed to classify multi drug-pathways relations. Data is collected from Drugbank.ca [1], Kegg (keg drug, Kegg diseases, Kegg pathways, Kegg orthologs, Kegg brite) [2] and small molecular pathways [3,4]. For drug-pathways data, two datasets are considered: one is based on Drug-Drug Interaction (DDI) and the other is based on Drug-Pathways Interactions (DPI). HNMC has proved its efficiency with an average of 90% precision, 92.35% recall, 92% accuracy, and 96% ROC

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

A low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands is presented. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results using only red markers for controlling the robot's movements.

A low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands is presented. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results using only red markers for controlling the robot's movements.

Human-robot interaction is an evolving area of research in the past few years. Human-robot interaction deals with how humans can interact with, send data to, or receive data from robots. One of the major obstacles in this field is how the robot can obtain the depth information of the surrounding objects. Few years ago, Microsoft has released a depth sensor that computes the depth information using IR rays. Many researches are conducted to control robots using depth sensors, such as Microsoft Kinect and Asus Xition. Although depth sensors are considered to be low cost, it may be unavailable for many users. In this work, we develop a low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results compared to those provided by depth sensors.

Human-robot interaction is an evolving area of research in the past few years. Human-robot interaction deals with how humans can interact with, send data to, or receive data from robots. One of the major obstacles in this field is how the robot can obtain the depth information of the surrounding objects. Few years ago, Microsoft has released a depth sensor that computes the depth information using IR rays. Many researches are conducted to control robots using depth sensors, such as Microsoft Kinect and Asus Xition. Although depth sensors are considered to be low cost, it may be unavailable for many users. In this work, we develop a low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results compared to those provided by depth sensors.