Search results for "COMMUNICATION"

Opinion dynamics in social networks through mean field games

2016

Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous social networks. Each such network is characterized by a vector state, a vector-valued controlled input, and a vector-valued exogenous disturbance. The controlled input of each network aims to align its state to the mean distribution of other networks' states in spite of the actions of the disturbance. One of the contributions of this paper is a detailed analysis of the resulting mean-field game for the cases of both polytopic and $mathcal L_2$ bounds on controls and disturbances. A second contrib…

Input Selection Methods for Soft Sensor Design: A Survey

2020

Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …

Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations

2020

Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…

Nonlinear statistical retrieval of surface emissivity from IASI data

2017

Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…

Aesthetic considerations for the min-max K-Windy Rural Postman Problem

2017

[EN] The aesthetic quality of routes is a feature of route planning that is of practical importance, but receives relatively little attention in the literature. Several practitioners have pointed out that the visual appeal of a proposed set of routes can have a strong influence on the willingness of a client to accept or reject a specific routing plan. While some work has analyzed algorithmic performance relative to traditional min-sum or min-max objective functions and aesthetic objective functions, we are not aware of any work that has considered a multi-objective approach. This work considers a multi-objective variant of the Min-Max K-Vehicles Windy Rural Postman Problem, discusses sever…

A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm

2013

Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…

Rough Set Theory for Optimization of Packet Management Mechanism in IP Routers

2020

Bandwidth and consequently optimum overall efficiency of network system relies greatly on mechanism of packet management in IP routers. Our research objective is to implement rough set theory to minimizing number of the network system attributes responsible for decision making in selection of those packets, which improve its transmission. Such an approach is called priority queuing system model, as we assign priority to the packets selected, following rough set theory. Regardless of the file format, for all the routers, packets are transmitted in sequence one-by-one. Nonetheless, quality of streaming data largely depends on how much the packet loss is minimized, or eliminated at all, if pos…

Survey of Cyber Threats in Air Traffic Control and Aircraft Communications Systems

2018

Air traffic control systems based on the ADS-B standard have been widely adopted in civil aviation to the point that they are now considered the de facto standard. ADS-B provides major benefits to airports and airlines by increasing the safety of air traffic management and control and allowing more flights to travel near busy airports. However, the ADS-B technology lacks sufficient security measures. The ADS-B system is vulnerable and exposed to cyberattacks. We survey the potential known threats and attacks against ADS-B and assess the potential cybersecurity threats to air traffic management and control. The widespread use of ADS-B and the lack of security features in it, i.e., all the AD…

The changing functions of the mass media: A historical perspective

1989

Secure and efficient verification for data aggregation in wireless sensor networks

2017

Summary The Internet of Things (IoT) concept is, and will be, one of the most interesting topics in the field of Information and Communications Technology. Covering a wide range of applications, wireless sensor networks (WSNs) can play an important role in IoT by seamless integration among thousands of sensors. The benefits of using WSN in IoT include the integrity, scalability, robustness, and easiness in deployment. In WSNs, data aggregation is a famous technique, which, on one hand, plays an essential role in energy preservation and, on the other hand, makes the network prone to different kinds of attacks. The detection of false data injection and impersonation attacks is one of the majo…