Virtual reality engineering paradigm for the simulation and gamification of real-time applications

2020 ◽  
Author(s):  
S. J. Syed Ali Fathima ◽  
M. Suguna
2019 ◽  
Vol 15 (5) ◽  
pp. 155014771984531 ◽  
Author(s):  
Dmitry Bankov ◽  
Evgeny Khorov ◽  
Andrey Lyakhov ◽  
Mark Sandal

Being of high importance, real-time applications, such as online gaming, real-time video streaming, virtual reality, and remote-control drone and robots, introduce many challenges to the developers of wireless networks. Such applications pose strict requirements on the delay and packet loss ratio, and it is hardly possible to satisfy them in Wi-Fi networks that use random channel access. The article presents a novel approach to enable real-time communications by exploiting an additional radio. This approach was recently proposed by us in the IEEE 802.11 Working Group and attracted much attention. To evaluate its gain and to study how real-time traffic coexists with the usual one, a mathematical model is designed. The numerical results show that the proposed approach allows decreasing the losses and delays for the real-time traffic by orders of magnitude, while the throughput for the usual traffic is reduced insignificantly in comparison to existing networks.


2011 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Roberto Cesar Cavalcante Vieira ◽  
Creto Vidal ◽  
Joaquim Bento Cavalcante-Neto

Virtual tridimensional creatures are active actors in many types of applications nowadays, such as virtual reality, games and computer animation. The virtual actors encountered in those applications are very diverse, but usually have humanlike behavior and facial expressions. This paper deals with the mapping of facial expressions between virtual characters, based on anthropometric proportions and geometric manipulations by moving influence zones. Facial proportions of a base model is used to transfer expressions to any other model with similar global characteristics (if the base model is a human, for instance, the other models need to have two eyes, one nose and one mouth). With this solution, it is possible to insert new virtual characters in real-time applications without having to go through the tedious process of customizing the characters’ emotions.


1989 ◽  
Author(s):  
Insup Lee ◽  
Susan Davidson ◽  
Victor Wolfe

Author(s):  
Mohsen Ansari ◽  
Amir Yeganeh-Khaksar ◽  
Sepideh Safari ◽  
Alireza Ejlali

2020 ◽  
Vol 6 (3) ◽  
pp. 127-130
Author(s):  
Max B. Schäfer ◽  
Kent W. Stewart ◽  
Nico Lösch ◽  
Peter P. Pott

AbstractAccess to systems for robot-assisted surgery is limited due to high costs. To enable widespread use, numerous issues have to be addressed to improve and/or simplify their components. Current systems commonly use universal linkage-based input devices, and only a few applicationoriented and specialized designs are used. A versatile virtual reality controller is proposed as an alternative input device for the control of a seven degree of freedom articulated robotic arm. The real-time capabilities of the setup, replicating a system for robot-assisted teleoperated surgery, are investigated to assess suitability. Image-based assessment showed a considerable system latency of 81.7 ± 27.7 ms. However, due to its versatility, the virtual reality controller is a promising alternative to current input devices for research around medical telemanipulation systems.


Author(s):  
R.K. Clark ◽  
I.B. Greenberg ◽  
P.K. Boucher ◽  
T.F. Lunt ◽  
P.G. Neumann ◽  
...  

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.


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