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As wireless networks shift towards denser deployments, simulations take longer time to run and consume more resources. Simulation of the physical (PHY) layer is particularly time consuming and, as such, its implementation requires the use of abstracted models with low computational complexity, in order to provide accurate results in reasonable time. Although Mutual Information Effective SINR Mapping...
Fuzzy rule interpolation is one of the tools for reducing computational complexity of fuzzy systems, and can be used when there are gaps in the knowledge base. These gaps can be natural, due to cost, or due to rule base reduction. The fuzzy interpolation methods are all descendent techniques of Kóczy and Hirota's linear interpolation. In this paper we provide a retrospective on the development of...
Apache Spark is an open source distributed data processing platform that uses distributed memory abstraction to process large volume of data efficiently. However, performance of a particular job on Apache Spark platform can vary significantly depending on the input data type and size, design and implementation of the algorithm, and computing capability, making it extremely difficult to predict the...
Current and future interferometric imaging arrays in radio astronomy may be limited by the accuracy with which various direction-dependent effects, such as the antenna gain patterns, can be corrected. Doing this in an efficient manner during the calibration and imaging process is especially difficult due to these effects often being also baseline-dependent. A newly proposed method, called A-stacking,...
Meteorological stations often have biased distributions in remote areas, and sample biases typically lead to biased estimation of areal precipitation. We introduce a method termed the Biased Sentinel Hospital based Area Disease Estimation (B-SHADE) to correct for the bias in the locations of meteorological observations and to obtain a best linear unbiased estimation of the mean areal precipitation...
Next generation embedded systems will massively adopt on-chip many core architectures to provide both performance and energy-efficiency. This trend will definitely establish the convergence of embedded computing and high-performance computing. In such a context, one major design challenge will concern the choice of adequate architecture parameters given system requirements. Moreover, it will affect...
Accurate electromagnetic models of measured antennas are available from the expansion of the measured field using equivalent currents [1–4]. The constructed model is importable in commercial Computational Electromagnetic (CEM) solvers in the form of a Huygens Box [5–9]. In flushmounted antenna applications, the measurement of the antenna sited in a locally relevant scenario and subsequent data processing...
This paper addresses the problem of parameter optimization for Markov random field (MRF) models for supervised classification of remote sensing images. MRF model parameters generally impact on classification accuracy, and their automatic optimization is still an open issue especially in the supervised case. The proposed approach combines a mean square error (MSE) formulation with Platt's sequential...
Schedulability analysis for real-time systems has been the subject of prominent research over the past several decades. One of the key foundations of schedulability analysis is an accurate worst case execution time (WCET) measurement for each task. In real-time systems that support preemption, the cache related preemption delay (CRPD) can represent a significant component (up to 44% as documented...
This paper proposes an approach to develop reduced-order electrochemical battery models for controls. The reduced-order models are derived from detailed electrochemical battery models, which combine ionic and electronic processes in the level of active material particles, through a significant model reduction with the order of hundreds or more. The reduction is possible through the understanding of...
Machine learning classifiers are widely used for text categorization however a classifier misclassifies some of the instances into a category that is relevant to their actual category. The categorization ability of a classifier can be improved by filtering dataset with better classifier and removing such category for misclassified instances. In this paper we proposed a two level approach where level-1...
This article aims to present a preliminary study of single point incremental sheet forming (SPIF) with warm for aluminum sheet of 1 millimeter (mm) thickness, with a propose of evaluate the contribution of adding heat for the process and even, how to reduce the processing time. For this evaluation was compared the dimensional errors between the pieces formed by the process with warm and without warm...
Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technology used for estimating displacement of the earth's surface. Phase unwrapping is the most important step in InSAR processing and relies on successful selection of points that appear stable across a set of satellite images taken over time. This paper presents a new algorithm for selecting these points, a problem known as persistent...
This paper proposes MultiExplorer, a new toolset for MPSoCs modelling, experimentation, and design space exploration, by combining fast high-abstraction simulation and low-level physical estimates (power, area, and timing). The MultiExplorer infrastructure takes a range of high and low-level parameters to improve accuracy in the design of a multiprocessor system on a chip. Our toolset results show...
Even though the electricity HPFC (Hourly Price Forward Curve) is still surprisingly under-researched the prediction of electricity prices is highly important in order to keep power plants profitable or in order to optimize the electricity purchases based on future customers demand. In this work two methods to model and predict HPFC based on neural networks will be proposed and compared to more common...
This paper presents an average-value model of a line commutated converter-based HVDC system using dynamic phasors. The model represents the low-frequency dynamics of the converter and its ac and dc systems, and has lower computational requirements than a conventional electromagnetic transient (EMT) switching model. The developed dynamic-phasor model is verified against an EMT model of the CIGRE HVDC...
Use of multiple scripts for information communication through various media is quite common in a multilingual country. Optical character recognition of such document images or videos assists in indexing them for effective information retrieval. Hence, script identification from multi-lingual documents/images is a necessary step for selecting the appropriate OCR, due the absence of a single OCR system...
People often need help when filling out paper forms, because they do not fully understand the meaning of form fields. Commonly adopted solutions are referring to the form filling instructions or consulting other people. However, they are either inefficient or inconvenient. In this paper, we propose a situation-aware and interactive system, named Interact Form, to help people fill out paper forms....
This study proposes an Intelligent Tutor System for assessing slide presentations from novice undergraduate students. To develop such system, two learner models (rule based model and clustering model) were built using 80 presentations graded by three human experts. An experiment to determine the best learner model and students' perception was carried out using 51 presentations uploaded by students...
This paper introduces an enhanced equivalent model of the half-bridge symmetrical monopole Modular Multilevel Converter (MMC) topology for the analyses of the electromagnetic transients. As compared with the existing MMC models, the proposed model reduces the simulation computational time without compromising accuracy, and contrary to the existing models, it provides accurate representation of the...
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