Semantic data broadcast for a mobile environment based on dynamic and adaptive chunking

2002 ◽  
Vol 51 (10) ◽  
pp. 1253-1268 ◽  
Author(s):  
K.C.K. Lee ◽  
Hong Va Leong ◽  
A. Si
2017 ◽  
Vol 23 (10) ◽  
pp. 10241-10245
Author(s):  
Mi-Sug Gu ◽  
Jeong-Hee Hwang

2009 ◽  
Vol 28 (10) ◽  
pp. 2544-2547
Author(s):  
Li-sheng CHEN ◽  
Hai-bin GUO ◽  
Fei-yue YE

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Camilla Follini ◽  
Valerio Magnago ◽  
Kilian Freitag ◽  
Michael Terzer ◽  
Carmen Marcher ◽  
...  

The application of robotics in construction is hindered by the site environment, which is unstructured and subject to change. At the same time, however, buildings and corresponding sites can be accurately described by Building Information Modeling (BIM). Such a model contains geometric and semantic data about the construction and operation phases of the building and it is already available at the design phase. We propose a method to leverage BIM for simple yet efficient deployment of robotic systems for construction and operation of buildings. With our proposed approach, BIM is used to provide the robot with a priori geometric and semantic information on the environment and to store information on the operation progress. We present two applications that verify the effectiveness of our proposed method. This system represents a step forward towards an easier application of robots in construction.


2020 ◽  
Vol 10 (23) ◽  
pp. 8351
Author(s):  
Rosangela Casolare ◽  
Fabio Martinelli ◽  
Francesco Mercaldo ◽  
Antonella Santone

The increase in computing capabilities of mobile devices has, in the last few years, made possible a plethora of complex operations performed from smartphones and tablets end users, for instance, from a bank transfer to the full management of home automation. Clearly, in this context, the detection of malicious applications is a critical and challenging task, especially considering that the user is often totally unaware of the behavior of the applications installed on their device. In this paper, we propose a method to detect inter-app communication i.e., a colluding communication between different applications with data support to silently exfiltrate sensitive and private information. We based the proposed method on model checking, by representing Android applications in terms of automata and by proposing a set of logic properties to reduce the number of comparisons and a set of logic properties automatically generated for detecting colluding applications. We evaluated the proposed method on a set of 1092 Android applications, including different colluding attacks, by obtaining an accuracy of 1, showing the effectiveness of the proposed method.


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