Search results for " artificial intelligence"
showing 10 items of 1992 documents
A Note on Keys and Keystreams of Chacha20 for Multi-key Channels
2018
In this paper we analyze the keystreams generated by the Chacha20 stream cipher. We also compare these to the ones generated by its predecessor, the RC4 stream cipher. Due to the proposed multi-key channels in the upcoming TLS 1.3 standard we analyze the behavior of the keystream in the boundary case where there is a single bit difference between two keys used for the initiation of the stream cipher algorithms. The goal is to check whether a single bit change in the key has any predictable influence on the bits of the keystream output.
Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)
2021
Forest fires are undesirable situations with tremendous impacts on wildlife and people&rsquo
DNS Tunneling Detection Techniques – Classification, and Theoretical Comparison in Case of a Real APT Campaign
2017
Domain Name System (DNS) plays an important role as a translation protocol in everyday use of the Internet. The purpose of DNS is to translate domain names into IP addresses and vice versa. However, its simple architecture can easily be misused for malicious activities. One huge security threat concerning DNS is tunneling, which helps attackers bypass the security systems unnoticed. A DNS tunnel can be used for three purposes: as a command and control channel, for data exfiltration or even for tunneling another protocol through it. In this paper, we surveyed different techniques for DNS tunneling detection. We classified those first based on the type of data and then within the categories b…
Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
2020
Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to…
Modeling crowd dynamics through coarse-grained data analysis
2018
International audience; Understanding and predicting the collective behaviour of crowds is essential to improve the efficiency of pedestrian flows in urban areas and minimize the risks of accidents at mass events. We advocate for the development of crowd traffic management systems, whereby observations of crowds can be coupled to fast and reliable models to produce rapid predictions of the crowd movement and eventually help crowd managers choose between tailored optimization strategies. Here, we propose a Bi-directional Macroscopic (BM) model as the core of such a system. Its key input is the fundamental diagram for bi-directional flows, i.e. the relation between the pedestrian fluxes and d…
A hybrid multi-criteria approach to GPR image mining applied to water supply system maintenance
2018
[EN] Data processing techniques for Ground Penetrating Radar (GPR) image mining provide essential information to optimize maintenance management of Water Supply Systems (WSSs). These techniques aim to elaborate on radargrams in order to produce meaningful graphical representations of critical buried components of WSSs. These representations are helpful non-destructive evaluation tools to prevent possible failures in WSSs by keeping them adequately monitored. This paper proposes an integrated multi-criteria decision making (MCDM) approach to prioritize various data processing techniques by means of ranking their outputs, namely their resulting GPR image representations. The Fuzzy Analytic Hi…
Event-based encoding from digital magnetic compass and ultrasonic distance sensor for navigation in mobile systems
2016
Event-based encoding reduces the amount of generated data while keeping relevant information in the measured magnitude. While this encoding is mostly associated with spiking neuromorphic systems, it can be used in a broad spectrum of tasks. The extension of event-based data representation to other sensors would provide advantages related to bandwidth reduction, lower computing requirements, increased processing speed and data processing. This work describes two event-based encoding procedures (magnitude-event and rate-event) for two sensors widely used in industry, especially for navigation in mobile systems: digital magnetic compass and ultrasonic distance sensor. Encoded data meet Address…
A Special Issue on Advances in Machine Learning for Remote Sensing and Geosciences [From the Guest Editors]
2016
Machine learning has become a standard paradigm for the analysis of remote sensing and geoscience data at both local and global scales. In the upcoming years, with the advent of new satellite constellations, machine learning will have a fundamental role in processing large and heterogeneous data sources. Machine learning will move from mere statistical data processing to actual learning, understanding, and knowledge extraction. The ambitious goal is to provide responses to the challenging scientific questions about the earth system. This special issue aims at providing an updated, refreshing view of current developments in the field. For this special issue, we have collected five articles t…
High Performance FOC for Induction Motors with Low Cost ATSAM3X8E Microcontroller
2018
In this paper the Authors present the Arduino Due board application for an induction motor field oriented control (FOC) algorithm. The low cost Arduino Due board is equipped with a ATSAM3X8E microcontroller that performs the algorithm calculation, data processing, current signals and speed/position data acquisition. The control algorithm has been developed with the help of the open source Arduino integrated development environment, whereas a user friendly control interface, used to manage the speed or position set point, has been developed in Java language by means of an other open source software, namely, Processing. An experimental test bed has been set up in order to validate the FOC sys…
Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption
2019
In machine learning applications in the energy sector, it is often necessary to have both highly accurate predictions and information about the probabilities of certain scenarios to occur. We address this challenge by integrating and combining long short-term memory networks (LSTMs) and online density estimation into a real-time data streaming architecture of an energy trader. The online density estimation is done in the MiDEO framework, which estimates joint densities of data streams based on ensembles of chains of Hoeffding trees. One attractive feature of the solution is that queries can be sent to the here-called forecast-based point density estimators (FPDE) to derive information from …