LCD motion‐blur estimation using different measurement methods

Abstract— The primary goal of this study was to find a measurement method for motion blur which is easy to carry out and gives results that can be reproduced from one lab to another. This method should be able to also take into account methods for reduction of motion blur such as backlight flashing. Two methods have been compared. The first method uses a high‐speed camera that permits us to directly picture the blurred‐edge profile. The second one exploits the mathematical analysis of the motion‐blur formation to construct the blurred‐edge profile from the temporal step response. Measurement results and method proposals are given and discussed.     

The Influence of the Internet on European Journalism

This study investigates how European journalists evaluate the changes that have occurred in their profession since the Internet has been integrated in newsrooms. How do journalists perceive the features and innovations associated with the Internet? What are the principal changes in the profession? Do practitioners believe that the quality of journalism has been raised or lowered? To answer to these research questions, we carried out a survey across 11 European countries–Cyprus, Estonia, Finland, Greece, Ireland, Italy, Lithuania, United Kingdom, Slovenia, Spain, Sweden–of 239 journalists, working for 40 of the most‐read print/online news outlets in these countries. The survey shows that the opportunity to use the Internet to reinforce the social functions of journalism has not been fully recognised.     

GLSV: Graphics library stereo vision for OpenGL

This work proposes the development of an auxiliary library for use with OpenGL, to facilitate the creation of graphic applications incorporating stereoscopic representation. This library, christened graphics library stereo vision (GLSV), is designed to remove all calculations involving knowledge of stereo vision theory from the task performed by the programmer without the latter having to change the way he/she has been working with the OpenGL library. The GLSV is distributed under the terms of the GNU Library General Public License agreement.     

A non-linear forecasting system for the Ebro River at Zaragoza,Spain

This paper addresses the problem of modelling and forecasting river flows and levels based on flood routing type models. Though this is generally considered as a non-linear problem, very often it is treated by linear models. A forecasting system is built for the level and flow measurements registered in the Ebro River at the station of Zaragoza (Spain), with the main purpose of preventing floods in an early stage of development. The model takes advantage of the wealth of data available at the Ebro Hydrographical Confederation and is non-linear in essence. The system is obtained by application of system identification tools, starting from a linear specification and relating the parameters of the model estimated to some transformation of the input in the system. Such transformation requires the application of a Kalman Filter in a particular set up and the full estimation algorithm involves an iterative procedure. The model is fully developed on a data set and is thoroughly validated on a different span of data.     

Fault detection and isolation in nonlinear systems

This paper deals with fault detection and identification in dynamic systems when the system dynamics can be modeled by smooth nonlinear differential equations including affine, bilinear or linear parameter varying (LPV) systems. Two basic approaches will be considered, these apply differential algebraic and differential geometric tools.In the differential algebraic approach the state elimination methods will be used to derive nonlinear parity relations. In the specific case when a reconstruction of the fault signal is needed the dynamic inversion based approach will be investigated. This approach will also be studied from geometric point of view. The geometric approach, as proposed by Isidori and De Persis, is suitable to extend the detection filter and unknown input observer design approaches (well elaborated for LTI systems) to affine nonlinear systems.Beyond the development of the theory of fault detection and identification it is equally important to offer computable methods and to analyze the robustness properties against uncertainties. Both the observer based and the inversion based approaches will be elaborated for LPV systems that may offer computational tools inherited from linear systems and also allow to design for robustness utilizing results from robust filtering and disturbance attenuation.     

Self-managed topologies in P2P networks

The problem of efficient resource location is an important open issue in P2P systems. This paper introduces DANTE, a self-adapting P2P system that changes its peer links to form topologies where resources are located in an efficient manner via random walks. Additionally, this same self-adaptation capacity makes DANTE capable of reacting to events like changes in the system load or attacks on well-connected nodes by adjusting the topology to the new scenario. This adaptive behavior emerges as the global result of the individual work of nodes, without the intervention of any central entity or the need for global knowledge. Simulations show that this adaptation process makes the system scalable, resilient to attacks, and tolerant to a high transitivity of peers. Simulations are also used to compare this solution with other well-known self-adapting P2P system. From these results it can be concluded that the topologies achieved by DANTE offer better performance.     

Distributed Latency-Energy Minimization and interference avoidance in TDMA Wireless Sensor Networks

This paper presents Latency-Energy Minimization Medium Access (LEMMA), a new TDMA-based MAC protocol for Wireless Sensor Networks (WSNs), specially suited to extend the lifetime of networks supporting alarm-driven, delay-sensitive applications characterized by convergecast traffic patterns and sporadic traffic generation. Its cascading time-slot assignment scheme conciliates low end-to-end latency with a low duty-cycle, while supporting multi-sink WSN topologies. Unlike most of the current solutions, LEMMA’s time-slot allocation protocol makes decisions based on the interference actually experienced by the nodes, instead of following the simple but potentially ineffective n-hop approach. Simulation results are presented to demonstrate the ineffectiveness of the n-hop time-slot allocation in comparison with LEMMA, as well as to evaluate the performance of LEMMA against L-MAC, T-MAC and Low Power Listening. The results show that under the target scenario conditions, LEMMA presents lower interference between assigned time-slots and lower end-to-end latency, while matching its best contender in terms of energy-efficiency.     

Finite-source M/M/S retrial queue with search for balking and impatient customers from the orbit

The present paper deals with a generalization of the homogeneous multi-server finite-source retrial queue with search for customers in the orbit. The novelty of the investigation is the introduction of balking and impatience for requests who arrive at the service facility with a limited capacity and FIFO queue. Arriving customers may balk, i.e., they either join the queue or go to the orbit. Moreover, the requests are impatient and abandon the buffer after a random time and enter the orbit, too. In case of an empty buffer, each server searches for a customer in the orbit after finishing service. All random variables involved in the model construction are supposed to be exponentially distributed and independent of each other. The primary aim of this analysis is to show the effect of balking, impatience, and buffer size on the steady-state performance measures. Concentrating on the mean response time, several numerical examples are investigated by the help of the MOSEL-2 tool used for creating the model and calculating the stationary characteristics.     

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems

Recently, multi-objective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. This contribution analyzes different application alternatives in order to attain the desired accuracy/interpr-etability balance by maintaining the improved accuracy that a tuning of membership functions could give but trying to obtain more compact models. In this way, we propose the use of multi-objective evolutionary algorithms as a tool to get almost one improved solution with respect to a classic single objective approach (a solution that could dominate the one obtained by such algorithm in terms of the system error and number of rules). To do that, this work presents and analyzes the application of six different multi-objective evolutionary algorithms to obtain simpler and still accurate linguistic fuzzy models by performing rule selection and a tuning of the membership functions. The results on two different scenarios show that the use of expert knowledge in the algorithm design process significantly improves the search ability of these algorithms and that they are able to improve both objectives together, obtaining more accurate and at the same time simpler models with respect to the single objective based approach.

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An artificial life approach to dense stereo disparity

This article presents an adaptive approach to improving the infection algorithm that we have used to solve the dense stereo matching problem. The algorithm presented here incorporates two different epidemic automata along a single execution of the infection algorithm. The new algorithm attempts to provide a general behavior of guessing the best correspondence between a pair of images. Our aim is to provide a new strategy inspired by evolutionary computation, which combines the behaviors of both automata into a single correspondence problem. The new algorithm will decide which automata will be used based on the transmission of information and mutation, as well as the attributes, texture, and geometry, of the input images. This article gives details about how the rules used in the infection algorithm are coded. Finally, we show experiments with a real stereo pair, as well as with a standard test bed, to show how the infection algorithm works.