This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and ...
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One of the biggest challenges in learning from data streams is adapting the classification model to new data. Due to the evolving nature of data streams, they are subject to a phenomenon known as concept drift that ma...
One of the biggest challenges in learning from data streams is adapting the classification model to new data. Due to the evolving nature of data streams, they are subject to a phenomenon known as concept drift that makes previously learned knowledge and model outdated. Therefore, concept drift must be efficiently detected in order to adapt the classification model. While there exists a plethora of drift detectors, with different mechanisms, selecting the most suitable for a new stream is a difficult task, since apriori knowledge may not be available and changes over time can affect the performance of the detector. This paper proposes a framework that exploits statistical and temporal meta-features from sliding windows to dynamically recommend a suitable drift detector in real-time for unseen chunks of streams according to its properties using Meta-Learning. We performed experiments on 10 real-world data streams and 18 synthetic generated data streams that were subject to concept drift and class imbalance in order to evaluate the performance of the proposed framework. Experiments exposed that the proposed approach was able to enhance the concept drift detection in a variety of scenarios demonstrating robustness to class imbalance and the advantages of dynamically selecting the drift detector.
We present a hardware-accelerated SAT solver suitable for processor/Field Programmable Gate Arrays (FPGA) hybrid platforms, which have become the norm in the embedded domain. Our solution addresses a known bottleneck ...
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Trust and security are critical deployment require-ments for Industrial Internet of Things (IIoT) networks. A recent protocol, called TRUTH, integrates security mechanisms for authentication and privacy alongside a De...
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We propose a decomposition framework for the distributed optimization of general nonconvex sum-utility functions arising in the design of wireless multi-user interfering systems. Our main contributions are: i) the dev...
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ISBN:
(纸本)9781479903573
We propose a decomposition framework for the distributed optimization of general nonconvex sum-utility functions arising in the design of wireless multi-user interfering systems. Our main contributions are: i) the development of the first provably convergent Jacobi best-response algorithm, where all users simultaneously solve a suitably convexified version of the original sum-utility optimization problem;ii) the derivation of a general dynamic pricing mechanism that provides a unified view of existing pricing schemes that are based, instead, on heuristics;and iii) a framework that can be easily particularized to well-known applications, giving rise to practical algorithms that outperform all existing ad-hoc methods proposed for very specific problems. Our framework contains as special cases well-known gradient algorithms for nonconvex sum-utility problems, and many block-coordinate descents schemes for convex functions.
This paper presents the design of a low-noise capacitively-coupled instrumentation amplifier with a sub-1V power supply, which is suitable for low-power sensor data acquisition systems. This amplifier is part of an An...
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This paper presents a new multi-band stopband filter loaded by a shorted metamaterial circuit. Firstly, two filters loaded by stubs and open ring resonators (ORRs) are studied and compared. The ORRs allow more effects...
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High resolution requirements for airport surface traffic monitoring with lightweight, small, all-weather sensors call for the use of a network of millimetre-wave radars to perform the surveillance function in the surf...
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High resolution requirements for airport surface traffic monitoring with lightweight, small, all-weather sensors call for the use of a network of millimetre-wave radars to perform the surveillance function in the surface movement control and guidance system. In this paper a W-band radar employed as the basic sensor is described. Some results of recent and present field trials are reported.
Deformable models have been intensively studied in image analysis through the last decade, and are used for detection and recognition of flexible or rigid templates under diverse viewing conditions. Genetic algorithm ...
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Deformable models have been intensively studied in image analysis through the last decade, and are used for detection and recognition of flexible or rigid templates under diverse viewing conditions. Genetic algorithm (GA) based deformable models are used for generic visual landmark detection and interpretation. The developed system allows topologic localization and navigation using natural and artificial landmarks, exploiting deformable models' ability for handling landmark perspective variations. The resulting perception module has been integrated successfully in a complex navigation system. Various experimental results in real environments are presented on this paper, showing the effectiveness and capacity of the landmark detection and reading system.
Project size, as measured by the amount of investment required, is a relevant parameter to be used in project selection. The evaluation of a project portfolio must consider the variety of project sizes that may be met...
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ISBN:
(纸本)9781509002078
Project size, as measured by the amount of investment required, is a relevant parameter to be used in project selection. The evaluation of a project portfolio must consider the variety of project sizes that may be met, so that a proper model should be adopted to describe that variety, especially for its use in simulation. In this paper, a log-normal probability model is suggested to describe the dispersion of project sizes within a project portfolio. The model is obtained on the basis of two real datasets spanning over ten years of observations, and after comparison with competing Gamma and Pareto models. The parameters of the log-normal model are provided as resulting from the best-fit procedure, and indications are also given for the values to use in a simulation study.
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