2008 International Conference on Computer and Electrical Engineering, 2008
The scope of this paper is to present the necessity to improve the existent ambient intelligence ... more The scope of this paper is to present the necessity to improve the existent ambient intelligence model with respect to data security. The security of such a model poses a great challenge due to the fact that different networks are mixing in order to provide such an environment. In ...
This paper presents a self-sufficient solar-powered real-time Deep Learning (DL) based system tha... more This paper presents a self-sufficient solar-powered real-time Deep Learning (DL) based system that runs inference 100% on solar energy and which is composed of an Nvidia Jetson TX2 board and a dual-axis solar tracker based on the cast-shadow principle. In order to have a higher energy being generated by the solar tracker as well as a lower energy consumption by the real-time DL-based system, we have: a) updated our solar tracker’s panel with a higher number of polycrystalline photovoltaic (PV) cells and connected it to a chain of two inverters, one accumulator and one solar charge controller; b) implemented a motion detection method that triggers the inference process only when there is substantial movement in webcam frame. Experimental results show that our solar tracker generates sufficient and constant solar energy for all the 4 DL models (VGG-19, InceptionV3, ResNet-50 and MobileNetV2) that are running in real-time on the Nvidia Jetson TX2 platform and which requires more than 5...
This paper presents a Data Science-oriented application for image classification tasks that is ab... more This paper presents a Data Science-oriented application for image classification tasks that is able to automatically: a) gather images needed for training Deep Learning (DL) models with a built-in search engine crawler; b) remove duplicate images; c) sort images using built-in pre-trained DL models or user’s own trained DL model; d) apply data augmentation; e) train a DL classification model; f) evaluate the performance of a DL model and system by using an accuracy calculator as well as the Accuracy Per Consumption (APC), Accuracy Per Energy Cost (APEC), Time to closest APC (TTCAPC) and Time to closest APEC (TTCAPEC) metrics calculators. Experimental results show that the proposed Computer Vision application has several unique features and advantages, proving to be efficient regarding execution time and much easier to use when compared to similar applications.
This paper presents a mathematical approach for determining the reliability of solar tracking sys... more This paper presents a mathematical approach for determining the reliability of solar tracking systems based on three fault coverage-aware metrics which use system error data from hardware, software as well as in-circuit testing (ICT) techniques, to calculate a solar test factor (STF). Using Euler’s named constant, the solar reliability factor (SRF) is computed to define the robustness and availability of modern, high-performance solar tracking systems. The experimental cases which were run in the Mathcad software suite and the Python programming environment show that the fault coverage-aware metrics greatly change the test and reliability factor curve of solar tracking systems, achieving significantly reduced calculation steps and computation time.
This paper presents a modified global energy production computation formula that replaces the tra... more This paper presents a modified global energy production computation formula that replaces the traditional Performance Ratio (PR) with a novel Solar Reliability Factor (SRF) for mobile solar tracking systems. The SRF parameter describes the reliability and availability of a dual-axis solar tracker, which powers a smart home automation system entirely by using clean energy. By applying the SRF in the global energy production formula of solar tracking systems, we can predict the energy generation in real time, allowing proper energy management of the entire smart home automation system. Regarding static deployed Photovoltaic (PV) systems, the PR factor is preserved to compute the power generation of these devices accurately. Experimental results show that the energy production computation constantly fluctuates over several days due to the SRF parameter variation, showing a 26.11% reduction when the dual-axis solar tracker’s availability is affected by system errors and maximum power ge...
This paper presents an improved mathematical model for calculating the solar test factor (STF) an... more This paper presents an improved mathematical model for calculating the solar test factor (STF) and solar reliability factor (SRF) of a photovoltaic (PV) automated equipment. By employing a unified metrics system and a combined testing suite encompassing various energy-efficient testing techniques, the aim of this paper is to determine a general fault coverage and improve the global SRF of a closed-loop dual-axis solar tracking system. Accelerated testing coupled with reliability analysis are essential tools for assessing the performance of modern solar tracking devices since PV system malfunctioning is directly connected to economic loss, which is an important aspect for the solar energy domain. The experimental results show that the unified metrics system is potentially suitable for assessing the reliability evaluation of many types of solar tracking systems. Additionally, the proposed combined testing platform proves efficient regarding fault coverage (overall coverage of 66.35% f...
One of the main motivations behind social network analysis is the quest for understanding opinion... more One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinctopinion formation phasesandsocial balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level) opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes...
Advances in Intelligent Systems and Computing, 2015
Motivated by the constantly growing interest and real-world applicability shown in complex networ... more Motivated by the constantly growing interest and real-world applicability shown in complex networks, we model and optimize the network formed by road networks in cities from an innovative perspective. We detect traffic hotspots which lead to congestion using the betweenness centrality of the road graph. This is shown to have a power-law distribution which we set out to redistribute and equalize. Optimization at a macro-level is not feasible because of the graph size, and thus we recursively narrow down the methodology to a sub-optimization of city neighborhoods. To that end, the paper introduces a genetic algorithm which redistributes betweenness optimization at a neighborhood level, district level, and city level to reduce and/or eliminate congestion hotspots, by changing street directions, without adding any new roads. Experimental results yield an improvement with a factor of 4 times in terms of reducing load off from hotspots and transferring it to neighboring streets.
2015 IEEE Congress on Evolutionary Computation (CEC), 2015
In present days, the road network in any major city faces the constant pressure of accommodating ... more In present days, the road network in any major city faces the constant pressure of accommodating an ever increasing number of vehicles while conserving a congestion-free status. However, identifying key intersections that will soon become congested is a difficult task, performed by tedious, thorough simulations; even more difficult is to adapt the road network so as to increase its efficiency and avoid congestion. We argue upon the social component of road traffic and propose an alternative way to detect hotspots leading to congestion by using techniques borrowed from complex network analysis. We will use the betweenness centrality and argue upon its power-law distribution, which we set out to redistribute and equalize. The paper introduces a genetic algorithm that redistributes the betweenness values at a community level in a city by changing street directions and number of available lanes in order to reduce (and possibly even eliminate) congestion hotspots. Experimental results in terms of reducing traffic loads from hotspots and transferring to neighboring streets yield an improvement with a factor of up to 90% times without adding significant costs or modifying the existing infrastructure.
2015 20th IEEE European Test Symposium (ETS), 2015
Because the hardware realization of cryptographic systems is more and more attractive in terms of... more Because the hardware realization of cryptographic systems is more and more attractive in terms of their performance, and since hardware implementations can be favorable adapted with self-testing techniques, in this paper we present a hardware offline error detection methodology protecting the Galois Field inversion modules of the Advanced Encryption Standard. The proposed test solution is built around the self-test capabilities of the field inverters when several units are linked together. The Units under Test are stimulated with pseudorandom test vectors, and the error detection mechanism is constructed as a conventional Built-In Self-Test. The AES inversion modules are stimulated with both exhaustive and deterministic test vectors and the correctness of the modules outputs is assessed by means of signature comparison. The error detection mechanism is validated in terms of the fault coverage when considering Single Stuck-at Faults.
2008 International Conference on Computer and Electrical Engineering, 2008
The scope of this paper is to present the necessity to improve the existent ambient intelligence ... more The scope of this paper is to present the necessity to improve the existent ambient intelligence model with respect to data security. The security of such a model poses a great challenge due to the fact that different networks are mixing in order to provide such an environment. In ...
This paper presents a self-sufficient solar-powered real-time Deep Learning (DL) based system tha... more This paper presents a self-sufficient solar-powered real-time Deep Learning (DL) based system that runs inference 100% on solar energy and which is composed of an Nvidia Jetson TX2 board and a dual-axis solar tracker based on the cast-shadow principle. In order to have a higher energy being generated by the solar tracker as well as a lower energy consumption by the real-time DL-based system, we have: a) updated our solar tracker’s panel with a higher number of polycrystalline photovoltaic (PV) cells and connected it to a chain of two inverters, one accumulator and one solar charge controller; b) implemented a motion detection method that triggers the inference process only when there is substantial movement in webcam frame. Experimental results show that our solar tracker generates sufficient and constant solar energy for all the 4 DL models (VGG-19, InceptionV3, ResNet-50 and MobileNetV2) that are running in real-time on the Nvidia Jetson TX2 platform and which requires more than 5...
This paper presents a Data Science-oriented application for image classification tasks that is ab... more This paper presents a Data Science-oriented application for image classification tasks that is able to automatically: a) gather images needed for training Deep Learning (DL) models with a built-in search engine crawler; b) remove duplicate images; c) sort images using built-in pre-trained DL models or user’s own trained DL model; d) apply data augmentation; e) train a DL classification model; f) evaluate the performance of a DL model and system by using an accuracy calculator as well as the Accuracy Per Consumption (APC), Accuracy Per Energy Cost (APEC), Time to closest APC (TTCAPC) and Time to closest APEC (TTCAPEC) metrics calculators. Experimental results show that the proposed Computer Vision application has several unique features and advantages, proving to be efficient regarding execution time and much easier to use when compared to similar applications.
This paper presents a mathematical approach for determining the reliability of solar tracking sys... more This paper presents a mathematical approach for determining the reliability of solar tracking systems based on three fault coverage-aware metrics which use system error data from hardware, software as well as in-circuit testing (ICT) techniques, to calculate a solar test factor (STF). Using Euler’s named constant, the solar reliability factor (SRF) is computed to define the robustness and availability of modern, high-performance solar tracking systems. The experimental cases which were run in the Mathcad software suite and the Python programming environment show that the fault coverage-aware metrics greatly change the test and reliability factor curve of solar tracking systems, achieving significantly reduced calculation steps and computation time.
This paper presents a modified global energy production computation formula that replaces the tra... more This paper presents a modified global energy production computation formula that replaces the traditional Performance Ratio (PR) with a novel Solar Reliability Factor (SRF) for mobile solar tracking systems. The SRF parameter describes the reliability and availability of a dual-axis solar tracker, which powers a smart home automation system entirely by using clean energy. By applying the SRF in the global energy production formula of solar tracking systems, we can predict the energy generation in real time, allowing proper energy management of the entire smart home automation system. Regarding static deployed Photovoltaic (PV) systems, the PR factor is preserved to compute the power generation of these devices accurately. Experimental results show that the energy production computation constantly fluctuates over several days due to the SRF parameter variation, showing a 26.11% reduction when the dual-axis solar tracker’s availability is affected by system errors and maximum power ge...
This paper presents an improved mathematical model for calculating the solar test factor (STF) an... more This paper presents an improved mathematical model for calculating the solar test factor (STF) and solar reliability factor (SRF) of a photovoltaic (PV) automated equipment. By employing a unified metrics system and a combined testing suite encompassing various energy-efficient testing techniques, the aim of this paper is to determine a general fault coverage and improve the global SRF of a closed-loop dual-axis solar tracking system. Accelerated testing coupled with reliability analysis are essential tools for assessing the performance of modern solar tracking devices since PV system malfunctioning is directly connected to economic loss, which is an important aspect for the solar energy domain. The experimental results show that the unified metrics system is potentially suitable for assessing the reliability evaluation of many types of solar tracking systems. Additionally, the proposed combined testing platform proves efficient regarding fault coverage (overall coverage of 66.35% f...
One of the main motivations behind social network analysis is the quest for understanding opinion... more One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinctopinion formation phasesandsocial balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level) opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes...
Advances in Intelligent Systems and Computing, 2015
Motivated by the constantly growing interest and real-world applicability shown in complex networ... more Motivated by the constantly growing interest and real-world applicability shown in complex networks, we model and optimize the network formed by road networks in cities from an innovative perspective. We detect traffic hotspots which lead to congestion using the betweenness centrality of the road graph. This is shown to have a power-law distribution which we set out to redistribute and equalize. Optimization at a macro-level is not feasible because of the graph size, and thus we recursively narrow down the methodology to a sub-optimization of city neighborhoods. To that end, the paper introduces a genetic algorithm which redistributes betweenness optimization at a neighborhood level, district level, and city level to reduce and/or eliminate congestion hotspots, by changing street directions, without adding any new roads. Experimental results yield an improvement with a factor of 4 times in terms of reducing load off from hotspots and transferring it to neighboring streets.
2015 IEEE Congress on Evolutionary Computation (CEC), 2015
In present days, the road network in any major city faces the constant pressure of accommodating ... more In present days, the road network in any major city faces the constant pressure of accommodating an ever increasing number of vehicles while conserving a congestion-free status. However, identifying key intersections that will soon become congested is a difficult task, performed by tedious, thorough simulations; even more difficult is to adapt the road network so as to increase its efficiency and avoid congestion. We argue upon the social component of road traffic and propose an alternative way to detect hotspots leading to congestion by using techniques borrowed from complex network analysis. We will use the betweenness centrality and argue upon its power-law distribution, which we set out to redistribute and equalize. The paper introduces a genetic algorithm that redistributes the betweenness values at a community level in a city by changing street directions and number of available lanes in order to reduce (and possibly even eliminate) congestion hotspots. Experimental results in terms of reducing traffic loads from hotspots and transferring to neighboring streets yield an improvement with a factor of up to 90% times without adding significant costs or modifying the existing infrastructure.
2015 20th IEEE European Test Symposium (ETS), 2015
Because the hardware realization of cryptographic systems is more and more attractive in terms of... more Because the hardware realization of cryptographic systems is more and more attractive in terms of their performance, and since hardware implementations can be favorable adapted with self-testing techniques, in this paper we present a hardware offline error detection methodology protecting the Galois Field inversion modules of the Advanced Encryption Standard. The proposed test solution is built around the self-test capabilities of the field inverters when several units are linked together. The Units under Test are stimulated with pseudorandom test vectors, and the error detection mechanism is constructed as a conventional Built-In Self-Test. The AES inversion modules are stimulated with both exhaustive and deterministic test vectors and the correctness of the modules outputs is assessed by means of signature comparison. The error detection mechanism is validated in terms of the fault coverage when considering Single Stuck-at Faults.
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