Fast and Exact Warping of Time Series Using Adaptive Segmental Approximations

Similarity search is a core module of many data analysis tasks, including search by example, classification, and clustering. For time series data, Dynamic Time Warping (DTW) has been proven a very effective similarity measure, since it minimizes the effects of shifting and distortion in time. However, the quadratic cost of DTW computation to the length of the matched sequences makes its direct application on databases of long time series very expensive. We propose a technique that decomposes the sequences into a number of segments and uses cheap approximations thereof to compute fast lower bounds for their warping distances. We present several, progressively tighter bounds, relying on the existence or not of warping constraints. Finally, we develop an index and a multi-step technique that uses the proposed bounds and performs two levels of filtering to efficiently process similarity queries. A thorough experimental study suggests that our method consistently outperforms state-of-the-art methods for DTW similarity search.     

Reverse nearest neighbors in large graphs

A reverse nearest neighbor (RNN) query returns the data objects that have a query point as their nearest neighbor (NN). Although such queries have been studied quite extensively in Euclidean spaces, there is no previous work in the context of large graphs. In this paper, we provide a fundamental lemma, which can be used to prune the search space while traversing the graph in search for RNN. Based on it, we develop two RNN methods; an eager algorithm that attempts to prune network nodes as soon as they are visited and a lazy technique that prunes the search space when a data point is discovered. We study retrieval of an arbitrary number k of reverse nearest neighbors, investigate the benefits of materialization, cover several query types, and deal with cases where the queries and the data objects reside on nodes or edges of the graph. The proposed techniques are evaluated in various practical scenarios involving spatial maps, computer networks, and the DBLP coauthorship graph.     

Reference structure tomography

Reference structure tomography (RST) uses multidimensional modulations to encode mappings between radiating objects and measurements. RST may be used to image source-density distributions, estimate source parameters, or classify sources. The RST paradigm permits scan-free multidimensional imaging, data-efficient and computation-efficient source analysis, and direct abstraction of physical features. We introduce the basic concepts of RST and illustrate the use of RST for multidimensional imaging based on a geometric radiation model.     

Searching efficient plans for emergency rescue through simulation: the case of a metro fire

In this paper we present the way we modelled and simulated a metro system in the case of a tunnel fire, and discuss the ways this simulation may support the search for efficient rescue plans. The metro system was modelled as a complex adaptive system, comprising four interacting and co-evolving subsystems: (i) the fire and the released smoke, (ii) the group of passengers, (iii) the technological system, and (iv) the metro personnel. Based on this model, an agent-based simulation was developed. This simulation provides an appropriate dynamic representation of the designers problem space, enabling him (i) to apprehend the critical dependencies and invariants of the system under consideration, (ii) to identify the features that should characterise the designed emergency rescue plans, and (iii) to assess their efficiency. To demonstrate the usefulness of the adopted approach for the design of an efficient emergency rescue plan, the results of two experiments exploring alternative sequences of the metro personnels actions under different circumstances are presented.     

MeteoBayes: Effective Plan Recognition in a Weather Dialogue System

When you've called a voice portal for any kind of information retrieval, chances are that an automated system guided the entire interaction. It might have correctly identified your goal, but probably only after asking too many questions. MeteoBayes is a meteorological information dialogue system that lets you use natural language to direct the interaction. Based on Bayesian networks, MeteoBayes' inference engine attempts to identify user intentions by consulting its past dialogue repository. For unfamiliar words, MeteoBayes has an unknown-term disambiguation module that learns word similarities from texts to avoid unnecessary system inquiries, thus speeding up the understanding process     

Gaussian Mixture Clustering and Language Adaptation for the Development of a New Language Speech Recognition System

The porting of a speech recognition system to a new language is usually a time-consuming and expensive process since it requires collecting, transcribing, and processing a large amount of language-specific training sentences. This work presents techniques for improved cross-language transfer of speech recognition systems to new target languages. Such techniques are particularly useful for target languages where minimal amounts of training data are available. We describe a novel method to produce a language-independent system by combining acoustic models from a number of source languages. This intermediate language-independent acoustic model is used to bootstrap a target-language system by applying language adaptation. For our experiments, we use acoustic models of seven source languages to develop a target Greek acoustic model. We show that our technique significantly outperforms a system trained from scratch when less than 8 h of read speech is available     

Development of NiO-based thin film structures as efficient H2 gas sensors operating at room temperatures

P-type NiO thin films have been developed on high resistivity Si and SiO₂ substrates by a pulsed laser deposition technique using an ArF^? 193 nm excimer laser at deposition temperature of 300 °C and in 40 Pa partial oxygen pressure. Structures based on such NiO films as host material in the form of Au-NiO Schottky diodes have been subsequently developed under vacuum. In a different procedure, an n-SnO₂ layer has been deposited by a CVD technique on a NiO film to produce a p/n heterojunction. The sensing properties of all above structures have been tested upon exposure to a H₂ flow in air ambient gas at various operating temperature ranging from 30 to 180 °C. For the NiO films, the optimum temperature was about 150 °C exhibiting a sensitivity of 94%. After surface sensitization of NiO by Au the NiO films showed an H₂ response at operating temperature of 30 °C. The sensitivity of p-NiO/n-SnO₂ heterojunction devices was extracted from I-V measurements in air and under H₂ flow mixed in air. In this case a dramatic increase of the sensitivity was achieved at operating temperature of 30 °C for a forward bias of 0,2 V.     

Detecting unauthorized and compromised nodes in mobile ad hoc networks

Security of mobile ad hoc networks (MANET) has become a more sophisticated problem than security in other networks, due to the open nature and the lack of infrastructure of such networks. In this paper, the security challenges in intrusion detection and authentication are identified and the different types of attacks are discussed. We propose a two-phase detection procedure of nodes that are not authorized for specific services and nodes that have been compromised during their operation in MANET. The detection framework is enabled with the main operations of ad hoc networking, which are found at the link and network layers. The proposed framework is based on zero knowledge techniques, which are presented through proofs.     

Multifold node authentication in mobile ad hoc networks

An ad hoc network is a collection of nodes that do not need to rely on a predefined infrastructure to keep the network connected. Nodes communicate amongst each other using wireless radios and operate by following a peer‐to‐peer network model. In this article, we propose a multifold node authentication approach for protecting mobile ad hoc networks. The security requirements for protecting data link and network layers are identified and the design criteria for creating secure ad hoc networks using multiple authentication protocols are analysed. Such protocols, which are based on zero‐knowledge and challenge‐response techniques, are presented through proofs and simulation results. Copyright © 2007 John Wiley & Sons, Ltd.     

Automatic speech recognition performance in different room acoustic environments with and without dereverberation preprocessing

The performance of recent dereverberation methods for reverberant speech preprocessing prior to Automatic Speech Recognition (ASR) is compared for an extensive range of room and source-receiver configurations. It is shown that room acoustic parameters such as the clarity (C50) and the definition (D50) correlate well with the ASR results. When available, such room acoustic parameters can provide insight into reverberant speech ASR performance and potential improvement via dereverberation preprocessing. It is also shown that the application of a recent dereverberation method based on perceptual modelling can be used in the above context and achieve significant Phone Recognition (PR) improvement, especially under highly reverberant conditions.