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Search results for: MASSIVELY PARALLEL COMPUTING
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
PublicationClimate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and...
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Angle Tracking Observer for Filtering Rotor Position Estimates in Sensorless Electric Drives
PublicationSensorless electric drives use measurements of electrical quantities to estimate rotor position and speed. Measurement errors deteriorate the estimation accuracy, thus additional means are necessary to remove high-frequency components from estimated signals. This paper proposes to use an Angle Tracking Observer (ATO) for reducing noise in rotor position estimates, which is related to random errors in the measurements. A simplified,...
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An annotated timeline of sensitivity analysis
PublicationThe last half a century has seen spectacular progresses in computing and modelling in a variety of fields, applications, and methodologies. Over the same period, a cross-disciplinary field known as sensitivity analysis has been making its first steps, evolving from the design of experiments for laboratory or field studies, also called ‘in-vivo’, to the so-called experiments ‘in-silico’. Some disciplines were quick to realize the...
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Vessel Energy Requirement Prediction from Acceleration Stage Towing Tests on Scale Models
PublicationOne of the most crucial tasks for naval architects is computing the energy required to meet the ship’s operational needs. When predicting a ship’s energy requirements, a series of hull resistance tests on a scale model vessel is carried out in constant speed stages, while the acceleration stage measurements are ignored. Another important factor in seakeeping analysis is the ship’s hydrodynamic added mass. The second law of dynamics...
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International Conference on Security in Pervasive Computing
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International Conference on Grid Computing and Applications
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Workshop on Power Aware Computing and Systems
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Computing in Education Group of Victoria Conference
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International Conference on Ubiquitous Intelligence and Computing
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International Conference on Grid and Cooperative Computing
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Asian International Mobile Computing Conference
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Workshop on Nature Inspired Distributed Computing
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Workshop on Ad Hoc and Ubiquitous computing
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International Conference on Distributed Computing and Networking
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Workshop on Mobile Computing Systems and Applications
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IEEE International Conference on Granular Computing
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ACM/IEEE Symposium on Edge Computing
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ACM Workshop on Scalable Trusted Computing
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Grace Hopper Celebration of Women in Computing
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International Conference on Affective Computing and Intelligent
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IEEE International Conference on Autonomic Computing
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International Conference on Advanced Computing and Communications
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ACM/SPIE Multimedia Computing and Networking
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IADIS International Conference Applied Computing
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ACM Symposium on Principles of Distributed Computing
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Asia-Pacific Services Computing Conference
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International Conference on Pervasive Computing and Applications
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International Conference on Service Oriented Computing
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International Computing Education Research Workshop
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International Conference on Intelligent Pervasive Computing
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Asilomar Conference on Signals, Systems and Computing
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IEEE International Conference on Cluster Computing
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IEEE International Conference on Services Computing
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Workshop On Java For High-Performance Computing
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International Colloquium on Theoretical Aspects of Computing
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International Workshop on Middleware for Grid Computing
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International Conference on Distributed Computing Systems
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International Symposium on Distributed Computing (was WDAG)
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International Forum on Applied Wearable Computing
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IEEE International Conference on Cloud Computing
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International Conference on High Performance Computing
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International Workshop on Soft Computing Applications
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Australasian Computing Education Conference (ACE)
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Digital Image Computing Techniques and Applications
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Workshop on Scientific Knowledge, Information, and Computing
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Variable-structure algorithm for identification of quasi-periodically varying systems
PublicationThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublicationOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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Movement perception with the use of a motorized delta armrest and virtual reality
PublicationIn this paper we present a combination of neuroscience experiments with the use of a parallel armrest robot to study the effects of temporal delays and spatial biases on the movement perception. A dedicated armrest to guide and manipulate the arm has been developed for these experiments. It is a three-degree-of-freedom Delta structure. In combination with a virtual reality application, the movement perception has been evaluated....