2,750 research outputs found
Goal Driven Interaction (GDI) vs. Direct Manipulation (MD), an empirical comparison
Interacción'15, September 07-09, 2015, Vilanova i la Geltrú, Spain ACM 978-1-4503-3463-1/15/09. http://dx.doi.org/10.1145/2829875.2829892This paper presents a work in process about Goal Driven Interaction (GDI), a style of interaction intended for inexperienced, infrequent and occasional users, whose main priorities are to use a system and achieve their goals without cost in terms of time or effort. GDI basic philosophy is to guide the user about the "what" to do and the "how" to do it in each moment of the interaction process, without requiring from the user a previous knowledge to use the interface. This interaction style was introduced in previous work, where a description of its characteristics and the most appropriate user interface for it, were described. Those works included a methodology for the analysis and synthesis of the whole interactive process through a language of specification. This paper presents partial results we are collecting in real user testing, with the main aim of comparing GDI with direct manipulation interfaces (MD), nevertheless the most extended and commonly regarded as the most suitable for novice and experienced users.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Aplicación de la Descomposición Empírica en Modo a la Predicción del Mercado Bursátil con los Modelos de ARIMA-ARCH y Redes Neuronales Artificiales Evolutivas
Tesis de Maestría donde se propone un modelo de Ensembles de Redes Neuronales Artificiales para predecir series de tiempo financiaeras de MéxicoEl mercado bursátil es un sistema dinámico que se caracteriza por su complejidad, volatilidad, no estacionariedad, irregularidad, pero sobre todo por las repentinas y pronunciadas caídas en los precios. Dadas estas características, y con el fin de contrarrestar las fluctuaciones aparentemente aleatorias, la inherente no linealidad en los datos financieros, y puesto que en muchos de los enfoques tradicionales que abordan la predicción del mercado bursátil en periodos de crisis, estos por lo regular no son capaces de capturar de manera fiable los rasgos distintivos del fenómeno. En esta investigación, se propone como primer paso, descomponer a los indicadores que representan al mercado accionario de los Estados Unidos y México en periodos de crisis, mediante la herramienta llamada Descomposición Empírica en Modos (DEM) que se encarga de descomponer la serie original de los índices accionarios en un número finito de descomposiciones llamadas Funciones de Modo Intrínseco (FMIs) y un elemento residual. A continuación, cada una de las FMIs y el residuo, son pronosticadas individualmente, utilizando por un lado, un modelo paramétrico (Autorregresivo Integrado de Media Móvil-Modelo de Volatilidad Condicional Heterocedástico (ARIMA-ARCH)) y por otro lado, por un modelo no paramétrico Redes Neuronales Artificiales (RNAs), este último es configurado por medio de un algoritmo evolutivo llamado Selección de Características de Programación Evolutiva de Redes Neuronales Artificiales (FS- EPNet). Posteriormente, se adquiere la predicción del modelo paramétrico, mediante la suma de las predicciones resultantes de cada FMI y del residuo, de igual forma se realiza el mismo procedimiento para obtener la predicción final del modelo no paramétrico. Finalmente, las predicciones de los modelos paramétrico y no paramétrico son combinadas mediante un promedio ponderado, para producir una combinación de pronósticos, estas predicciones a su vez son comparadas. Los resultados empíricos obtenidos demuestran que los modelos que colaboraron en conjunción con la técnica de descomposición de señales DEM, tienen una predicción más precisa de la crisis bursátil, a diferencia de los modelos que confeccionaron su pronóstico de manera aislada.COMECyT, CONACy
The fate of non-trivial entanglement under gravitational collapse
We analyse the evolution of the entanglement of a non-trivial initial quantum
field state (which, for simplicity, has been taken to be a bipartite state made
out of vacuum and the first excited state) when it undergoes a gravitational
collapse. We carry out this analysis by generalising the tools developed to
study entanglement behaviour in stationary scenarios and making them suitable
to deal with dynamical spacetimes. We also discuss what kind of problems can be
tackled using the formalism spelled out here as well as single out future
avenues of research.Comment: 9 pages, 2 figures. v2: Added Journal reference and small changes to
match published versio
Gamma-rays from the compact colliding wind region in Cyg OB2 #5
In this contribution we model the non-thermal emission (from radio to
gamma-rays) produced in the compact (and recently detected) colliding wind
region in the multiple stellar system Cyg OB2 #5. We focus our study on the
detectability of the produced gamma-rays.Comment: To appear in the proceedings of the 5th International Symposium on
High-Energy Gamma-Ray Astronomy (Gamma2012), held in Heidelberg, July 9-13,
201
Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications
The 3rd Generation Partnership Project (3GPP) has recently established in
Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast
communications. Such novel paradigm is known as vehicle--to--vehicle (V2V)
\textit{mode-3} and consists in eNodeBs engaging only in the distribution of
sidelink subchannels among vehicles in coverage. Thereupon, without further
intervention of the former, vehicles will broadcast their respective signals
directly to their counterparts. Because the allotment of subchannels takes
place intermittently to reduce signaling, it must primarily be conflict-free in
order not to jeopardize the reception of signals. We have identified four
pivotal types of allocation requirements that must be guaranteed: one quality
of service (QoS) requirement and three conflict conditions which must be
precluded in order to preserve reception reliability. The underlying problem is
formulated as a maximization of the system sum-capacity with four types of
constraints that must be enforced. In addition, we propose a three-stage
suboptimal approach that is cast as multiple independent knapsack problems
(MIKPs). We compare the two approaches through simulations and show that the
latter formulation can attain acceptable performance at lesser complexity
Poster Abstract: Hierarchical Subchannel Allocation for Mode-3 Vehicle-to-Vehicle Sidelink Communications
In V2V Mode-3, eNodeBs assign subchannels to vehicles in order for them to
periodically broadcast CAM messages \cite{b2}. A crucial aspect is to ensure
that vehicles in the same cluster will broadcast in orthogonal time
subchannels\footnote{A subchannel is a time-frequency resource chunk capable of
sufficiently conveying a CAM message.} to avoid conflicts. In general,
resource/subchannel allocation problems can be represented as weighted
bipartite graphs. However, in this scenario there is an additional time
orthogonality constraint which cannot be straightforwardly handled by
conventional graph matching methods \cite{b3}. Thus, in our approach the
mentioned constraint has been taken into account. We also perform the
allocation task in a sequential manner based on the constrainedness of each
cluster. To illustrate the gist of the problem, in Fig. 1 we show two partially
overlapping clusters where a conflict between vehicles and is
generated as the allotted subchannels are in the same subframe
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