Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
This paper presents a new data-driven air traffic modelling and analysis technique that can support operational risk analysis for unmanned aircraft integration. The proposed technique exploits advances in computer vision to autonomously extract and analyse the spatial distribution of arbitrary traffic densities, which can provide the foundation for quantitative and tailored risk assessments. The framework...
This paper contributes to the growing body of research that attempts to measure online, informal learning. We analyze skill progression in MIT App Inventor, an informal online learning environment with over 5 million users and 15.9 million projects/apps created. Our objective is to understand how people learn computational thinking concepts while creating mobile applications with App Inventor. In...
This paper describes a nonlinear Model Predictive Control (MPC) algorithm for a distributed parameter thermal system (a long duct). For prediction a specially designed neural model of the process is used. The model consists of a set of local neural sub-models, which calculate temperatures for a number of predefined locations of sensors, and a neural interpolator, which calculates the temperature for...
This paper discusses the time-constrained data delivery problem in vehicular ad hoc networks (VANETs). The unique characteristics of the network present great challenges to the issue. First, there are no always-connected forwarding routes between vehicles. Second, there is an intrinsic tradeoff between communication cost and delivery quality. Third, there is great uncertainty about vehicular mobilities...
Synchronous generators are widely utilized in microgrids with high penetration of distributed renewable energy resources for small scale power generation. An accurate model of a synchronous generator is key to effective planning and operation of a grid-tied microgrid as well as stabilizing the frequency and regulating the voltage in an islanded microgrid. In this paper, a new strategy, based on the...
In this paper we present a neurally plausible model of human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensorimotor interaction of an agent and the world. This model encompasses both learning sensorimotor correlations through motor babbling and also arm motion planning using spreading activation. This model is organized in three layers...
This paper is about copying on artificial agents humans’ perception of time and their ability to producecondensed short stories out of large free texts. We propose a model intended to objectivize processes that help to achievethis reasoning behaviour on machines.
We address the problem of full body human pose estimation in video. Most previous work consider body part, pose or trajectory of body part as basic unit to compose the pose sequence. In contrast, we consider tracklet of body part as the basic unit. Based on this medium granularity representation we develop a spatio-temporal graphical model to select an optimal tracklet for each part in each video...
Person re-identification is the process of recognizing a person across a network of cameras with non-overlapping fields of view. In this paper we present an unsupervised multi-shot approach based on a patch-based dynamic appearance model. We use deformable graph matching for person re-identification using histograms of color and texture as features of nodes. Each graph model spans multiple images...
Action recognition has been one of the challenging problems in the computer vision community. Most of the recent research work in this area exploits the motion features captured by dense trajectory descriptors. On the other hand, static image classification has seen the rise of deep learning architectures, with evidence that the output of intermediate layers could be successfully employed as a low...
We present a novel video representation for human action recognition by considering temporal sequences of visual words. Based on state-of-the-art dense trajectories, we introduce temporal bundles of dominant, that is most frequent, visual words. These are employed to construct a complementary action representation of ordered dominant visual word sequences, that additionally incorporates fine grained...
The design of high quality electron generators is important for a variety of applications including materials processing systems (including welding, cutting and additive manufacture), X-ray tubes for medical, scientific and industrial applications, microscopy, and lithography for integrated circuit manufacture. The many variants of electron gun required, and the increasing demands for highly optimised...
We present a new approach to extracting low-dimensional neural trajectories that summarize the electrocorticographic (ECoG) signals recorded with high-channel-count electrode arrays implanted subdurally. In our approach, Hidden-Markov Factor Analysis (HMFA), a finite set of factor analyzers are used to model the relationship between the high-dimensional ECoG neural space and a low-dimensional latent...
Kinematic and dynamic models are used to create simplified, yet accurate representations of reality. In application to biological systems, there is often a choice on what level of complexity is appropriate for the model. This paper introduces a structured method for obtaining an accurate model that can represent the sit-to-stand motion and reproduce the associated contact forces in the standing phase...
This paper presents a method for synthesis of control alphabet policies, given continuum descriptions of physical systems and tasks. First, we describe a model predictive control scheme, called switched sequential action control (sSAC), that generates global state-feedback control policies with low computational cost, given a control alphabet. During synthesis, sSAC alphabet policies are directly...
Many supervised approaches report state-of-the-art results for recognizing short-term actions in manually clipped videos by utilizing fine body motion information. The main downside of these approaches is that they are not applicable in real world settings. The challenge is different when it comes to unstructured scenes and long-term videos. Unsupervised approaches have been used to model the long-term...
This work proposes the use of Laguerre function in Predictive Functional Control (PFC) to produce well-posed decision making. The constant control input assumption of a classical PFC is replaced with the Laguerre polynomial and the steady state input of a system. With this slight modification, better consistency between model predictions and an actual system behaviour is achieved. In addition, the...
This paper addresses the complex problem of recognising threat situations from videos streamed by surveillance cameras. A behaviour recognition approach is proposed, which is based on a semantic recognition of the event. Low-level tracking information is transformed into high-level semantic descriptions mainly by analysis of the tracked object speed and direction. Semantic terms combined with automatically...
In this paper we propose an algorithm for multiple object tracking, a heavily researched but still challenging problem of computer vision. We follow the tracking by detection paradigm in an online fashion and formulate tracking as a typical assignment problem between detections and existing tracks that is solved by a modification of the Hungarian algorithm. Contrary to other methods that use a multitude...
This paper assesses the potential fuel savings benefits that can be gained from wind optimal flight trajectories. This question is posed on a 3 dimensional fixed flight network consisting of discrete waypoints which is representative of the size of Europe. The optimisation implements Dijkstra's shortest path algorithm to compute the minimum fuel burn route through a network and compares this to the...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.