The purpose of this paper is to illustrate the vulnerabilities found through the studies, mainly through the methods of preventing an attack of a Smart Grid. Having a contingency plan of attacks is not something compl...
ISBN:
(数字)9781728116242
ISBN:
(纸本)9781728116259
The purpose of this paper is to illustrate the vulnerabilities found through the studies, mainly through the methods of preventing an attack of a Smart Grid. Having a contingency plan of attacks is not something complex and should be part of everyday business, it's wrong to think that answering a security incident only happens in cases of mega attacks, such as WannaCry. Any Security threat must be taken seriously, no matter how small the threat is, because the threat might just be a test of vulnerability. The main goal of this article is to prevent cyber-attacks of Smart Grid using MAC Value Analysis. On this article the goal is to protect the network from these attacks.
As the need for safe and secure communication solution for drone applications increases, this paper is analyzing today's status starting with the existing standards and solutions to hypothetical solutions, standar...
ISBN:
(数字)9781728116242
ISBN:
(纸本)9781728116259
As the need for safe and secure communication solution for drone applications increases, this paper is analyzing today's status starting with the existing standards and solutions to hypothetical solutions, standard drafts and trends for enabling developers to implement reliable solutions. When evaluating a large quantity of articles, papers and case-studies approaching this subject, the authors' focus was on the state of the art, technology comparison, existing standards, development trends and on highlighted safety and security issues.
This work is based on the implementation of new concepts for adaptive traffic signal controller using a neurofuzzy system approach and simulations on reference test cases. In our neuro-fuzzy controller, the parameters...
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This work is based on the implementation of new concepts for adaptive traffic signal controller using a neurofuzzy system approach and simulations on reference test cases. In our neuro-fuzzy controller, the parameters of the fuzzy membership functions are adjusted using a neural network. The neural learning algorithm may then be considered as reinforcement learning. However, the major difficulty for this neuro-fuzzy system under consideration is such that the most usual neural learning algorithms cannot be used. A specific learning algorithm is proposed to be used both for constant traffic volumes and also for changing volumes. Starting from the initial membership functions, the learning algorithm modifies the parameters of the membership functions in different ways at different but constant traffic volumes. The membership functions after the proposed learning algorithm produce smaller delays than the initial membership functions. An additional contribution is for specific changes in the rule base of the fuzzy traffic signal controller in order to reduce delays in various traffic volumes conditions in a test/reference traffic junction.
Smart crop monitoring is a new concept for different modern agricultural research and production management. The paper presents a hierarchical structure of data processing from the sensors used in crop monitoring. The...
Smart crop monitoring is a new concept for different modern agricultural research and production management. The paper presents a hierarchical structure of data processing from the sensors used in crop monitoring. The proposed system consists in the integration of multi WSN network at ground level, a team of UAVs at aerial level, with the mission of both direct data acquisition and data collecting from WSN. The information from UAV is next transmitted to a central data analysis and interpretation via internet. To this end, a multi levels data processing structure is proposed: in field processing, fog computing processing and cloud computing processing. The design of an efficient UAV trajectory for collecting of data and obstacle avoidance and, also, a model of intelligent data processing and transmission are proposed.
Integrating innovative technologies in terrestrial-satellite networks are needed to enable Unmanned Aerial Vehicles (UAV) application developers to achieve better results and optimize solutions. Managing a complex UAV...
Integrating innovative technologies in terrestrial-satellite networks are needed to enable Unmanned Aerial Vehicles (UAV) application developers to achieve better results and optimize solutions. Managing a complex UAV - Satellite modem integration process, the authors of this study have performed a series of measurement of throughput and latency time to evaluate the feasibility of the Satellite communication system for remote control and command of a distant UAV.
This paper describes a color texture classification scheme that uses fractal features like: box-counting fractal dimension and differential box-counting fractal dimension. Color textured images can be represented on m...
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ISBN:
(数字)9781728134581
ISBN:
(纸本)9781728134598
This paper describes a color texture classification scheme that uses fractal features like: box-counting fractal dimension and differential box-counting fractal dimension. Color textured images can be represented on multiple color spaces and recent developments for color texture analysis and classification are increasing. Following this concept, a texture image is obtained using Local Binary Pattern whereupon fractal features are extracted from it. For testing this color texture classification scheme two datasets (BarkTex and VisTex) are used, and the results are compared with three other methods. We propose a modified formula for calculating the Local Binary Pattern of a color textured image and advance the algorithm for this technique. The fractal features prove to be suitable in the classification process and the accuracy rates we had obtained are close to state-of-the-art approaches using a much smaller feature space.
Covariance matrix estimation techniques require high acquisition costs that challenge the sampling systems’ storing and transmission capabilities. For this reason, various acquisition approaches have been developed t...
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Nowadays, unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) are often integrated in collaborative systems for data collection. In this paper, a specific UAV trajectory design for effective and secure...
Nowadays, unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) are often integrated in collaborative systems for data collection. In this paper, a specific UAV trajectory design for effective and secure data collection from ground sensors is presented. Depending of the amount of data and radio communication characteristics, two types of trajectory are designed: segment tracking and loitering in a circle around the WSN cluster head.
In this paper, the traffic sign recognition module of a small-scale autonomous car prototype will be presented. The process undergoing the choice of an appropriate algorithm, as well as the factors taken into consider...
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ISBN:
(数字)9781728108780
ISBN:
(纸本)9781728108797
In this paper, the traffic sign recognition module of a small-scale autonomous car prototype will be presented. The process undergoing the choice of an appropriate algorithm, as well as the factors taken into consideration will be presented in the form of a case study. The current literature presents various ways of achieving the recognition of traffic signs, but most of them are computational expensive, or have difficulty in offering consistent results in conditions that are different from the prerecorded ones. Since the processing on the car is carried on an embedded platform from Nvidia (Jetson TX2), this study is based on the same board, the stream being captured with a low-cost webcam. Classical algorithms like SURF (Speeded Up Robust Features), SIFT (Scale Invariant Feature Transform) or ORB (Oriented fast and Rotated Brief) offer reliable results when the lighting condition between the reference image and the image obtained from the camera are similar. In our setup, the algorithms mentioned above start to behave badly in low light conditions. Therefore, this paper discusses the possibility of using Haar like features alongside a classifier for detecting traffic signs.
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