Semantic caching for web-based spatial applications

Client-side caching of spatial data is an important yet very much under investigated issue. Effective caching of vector spatial data has the potential to greatly improve the performance of spatial applications in the Web and wireless environments. In this paper, we study the problem of semantic spatial caching, focusing on effective organization of spatial data and spatial query trimming to take advantage of cached data. Semantic caching for spatial data is a much more complex problem than semantic caching for aspatial data. Several novel ideas are proposed in this paper for spatial applications. A number of typical spatial application scenarios are used to generate spatial query sequences. An extensive experimental performance study is conducted based on these scenarios using real spatial data. We demonstrate a significant performance improvement using our ideas.

Investigations of attentional processing in parietal and occipital human cortical regions with magnetoencephalography

Attention defines our mental ability to select and respond to stimuli, internal or external, on the basis of behavioural goals in the presence of competing, behaviourally irrelevant, stimuli. The frontal and parietal cortices are generally agreed to be involved with attentional processing, in what is termed the 'fronto-parietal' network. The left parietal cortex has been seen as the site for temporal attentional processing, whereas the right parietal cortex has been seen as the site for spatial attentional processing. There is much debate about when the modulation of the primary visual cortex occurs, whether it is modulated in the feedforward sweep of processing or modulated by feedback projections from extrastriate and higher cortical areas. MEG and psychophysical measurements were used to look at spatially selective covert attention. Dual-task and cue-based paradigms were used. It was found that the posterior parietal cortex (PPC), in particular the SPL and IPL, was the main site of activation during these experiments, and that the left parietal lobe was activated more strongly than the right parietal lobe throughout. The levels of activation in both parietal and occipital areas were modulated in accordance with attentional demands. It is likely that spatially selective covert attention is dominated by the left parietal lobe, and that this takes the form of the proposed sensory-perceptual lateralization within the parietal lobes. Another form of lateralization is proposed, termed the motor-processing lateralization, the side of dominance being determined by handedness, being reversed in left- relative to right-handers. In terms of the modulation of the primary visual cortex, it was found that it is unlikely that V1 is modulated initially; rather the modulation takes the form of feedback from higher extrastriate and parietal areas. This fits with the idea of preattentive visual processing, a commonly accepted idea which, in itself, prevents the concept of initial modulation of V1.

Monetary cost -efficient query distribution in ISDN -connected heterogeneous databases

Current technology permits connecting local networks via high-bandwidth telephone lines. Central coordinator nodes may use Intelligent Networks to manage data flow over dialed data lines, e.g. ISDN, and to establish connections between LANs. This dissertation focuses on cost minimization and on establishing operational policies for query distribution over heterogeneous, geographically distributed databases. Based on our study of query distribution strategies, public network tariff policies, and database interface standards we propose methods for communication cost estimation, strategies for the reduction of bandwidth allocation, and guidelines for central to node communication protocols. Our conclusion is that dialed data lines offer a cost effective alternative for the implementation of distributed database query systems, and that existing commercial software may be adapted to support query processing in heterogeneous distributed database systems. ^

Homomorphic encryption and database query privacy

Homomorphic encryption is a particular type of encryption method that enables computing over encrypted data. This has a wide range of real world ramifications such as being able to blindly compute a search result sent to a remote server without revealing its content. In the first part of this thesis, we discuss how database search queries can be made secure using a homomorphic encryption scheme based on the ideas of Gahi et al. Gahi’s method is based on the integer-based fully homomorphic encryption scheme proposed by Dijk et al. We propose a new database search scheme called the Homomorphic Query Processing Scheme, which can be used with the ring-based fully homomorphic encryption scheme proposed by Braserski. In the second part of this thesis, we discuss the cybersecurity of the smart electric grid. Specifically, we use the Homomorphic Query Processing scheme to construct a keyword search technique in the smart grid. Our work is based on the Public Key Encryption with Keyword Search (PEKS) method introduced by Boneh et al. and a Multi-Key Homomorphic Encryption scheme proposed by L´opez-Alt et al. A summary of the results of this thesis (specifically the Homomorphic Query Processing Scheme) is published at the 14th Canadian Workshop on Information Theory (CWIT).

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.

Using a prioritized MAC protocol to execute the database operation join in networked embedded computer systems

Database query languages on relations (for example SQL) make it possible to join two relations. This operation is very common in desktop/server database systems but unfortunately query processing systems in networked embedded computer systems currently do not support this operation; specifically, the query processing systems TAG, TinyDB, Cougar do not support this. We show how a prioritized medium access control (MAC) protocol can be used to efficiently execute the database operation join for networked embedded computer systems where all computer nodes are in a single broadcast domain.

Mice with chronic GSH deficit display phenotypical anomalies that resemble key aspects of schizophrenia

ABSTRACTSchizophrenia is a major psychiatric disorder occurring with a prevalence of 1% in the worldwide population. It develops progressively with psychosis onset in late adolescence or earlyadulthood. The disorder can take many different facets and has a highly diffuse anddistributed neuropathology including deficits in major neurotransmitter systems,myelination, stress regulation, and metabolism. The delayed onset and the heterogeneouspathology suggest that schizophrenia is a developmental disease that arises from interplayof genetic and environmental factors during sensitive periods. Redox dysregulation due to animbalance between pro-oxidants and antioxidant defence mechanisms is among the riskfactors for schizophrenia. Glutathione (GSH) is the major cellular redox regulator andantioxidant. Levels of GSH are decreased in cerebrospinal fluid, prefrontal cortex and postmortemstriatum of schizophrenia patients. Moreover, polymorphisms of the key GSHsynthesizingenzyme, glutamate-cysteine ligase, modifier (GCLM) subunit, are associatedwith the disease, suggesting that GSH deficit is of genetic origin. Here we used miceknockout (KO) for the GCLM gene, which display chronic GSH deficit (~70 to 80% decrease)to investigate the direct link between redox dysregulation and schizophrenia. Accordingly,we evaluated whether GCLM KO compared to normal wildtype mice display behavioralchanges that relate to schizophrenia symptoms and whether their brains showmorphological, functional or metabolic alterations that resemble those in patients.Moreover, we exposed pubertal GCLM mice to repeated mild stress and measured theirhormonal and behavioral stress reactivity. Our data show that chronic GSH deficit isassociated with altered emotion- and stress-related behaviors, deficient prepulse inhibition,pronounced amphetamine-induced hyperlocomotion but normal spatial learning andworking memory. These changes represent important schizophrenia endophenotypes.Moreover, this particular pattern of change indicates impairment of the ventralhippocampus (VH) and related circuitry as opposed to the dorsal hippocampus (DH), which isimplicated in spatial information processing. This is consistent with a selective deficit ofparvalbumin positive interneurons and gamma oscillation in the VH but not DH. Increasedlevels of circulating stress hormones in KO mice following pubertal stress corroborate VHdysfunction as it is involved in negative feedback control of the stress response. VHstructural and functional deficits are frequently found in the schizophrenic brain. Metabolicevaluation of the developing GCLM KO anterior cortex using in vivo magnetic resonancespectroscopy revealed elevated glutamine (Gln), glutamate (Glu), Gln/Glu and N-acetylaspartate(NAA) during the pre-pubertal period. Similar changes are reported in earlyschizophrenia. Overall, we observe phenotypic anomalies in GSH deficient GCLM KO micethat correspond to major schizophrenia endophenotypes. This supports an important rolefor redox dysregulation in schizophrenia and validates the GCLM KO mouse as model for thedisease. Moreover, our results indicate that puberty may be a sensitive period for redoxsensitivechanges highliting the importance of early intervention. Gln, Gln/Glu, Glu and NAAmay qualify as early metabolic biomarkers to identify young at-risk individuals. Since chronictreatment with NAC normalized most metabolic changes in GCLM KO mice, NAC may be oneadjunct treatment of choice for early intervention in patients.RESUMELa schizophrénie est une maladie psychiatrique majeure avec une prévalence de 1% dans lapopulation. Son développement est progressif, les premières psychoses apparaissant àl'adolescence ou au début de l'âge adulte. La maladie a plusieurs présentations et uneneuropathologie étendue, qui inclut des déficits neurochimiques, métaboliques, de lamyélination et de la régulation du stress. L'émergence tardive et l'hétérogénéité de lapathologie suggèrent que la schizophrénie est une maladie développementale, favorisée pardes facteurs génétiques et environnementaux durant des périodes sensibles. La dérégulationrédox, due à un déséquilibre entre facteurs pro-oxidantes et défenses anti-oxidantes,constitue un facteur de risque. Le glutathion (GSH) est le principal régulateur rédox et antioxidantdes cellules, ses taux sont diminués dans le liquide céphalorachidien, le cortexpréfrontal et le striatum de patients. De plus, des variations du gène codant la sous-unitémodulatrice (GCLM) de la glutamate-cystéine ligase, enzyme de synthèse du GSH, sontassociés la maladie, suggérant que le déficit observé chez les patients est d'originegénétique. Nous avons donc utilisé des souris ayant une délétion du gène GCLM (KO), quiont un déficit chronique en GSH (70-80%), afin d'étudier le lien entre une dérégulation rédoxet la schizophrénie. Nous avons évalué si ces souris présentent des altérationscomportementales analogues aux symptômes de la maladie, et des modificationsstructurelles, fonctionnelles et métaboliques au niveau du cerveau, ressemblant à celles despatients. De plus, nous avons soumis les souris à des stresses modérés durant la puberté,puis mesuré les réponses hormonales et comportementales. Les animaux présentent undéficit pré-attentionnel du traitement des informations moto-sensorielles, un déficit pourcertains apprentissages, une réponse accrue à l'amphétamine, mais leurs mémoires spatialeet de travail sont préservées. Ces atteintes comportementales sont analogues à certainsendophénotypes de la schizophrénie. De plus, ces changements comportementaux sontlargement expliqués par une perturbation morphologique et fonctionnelle de l'hippocampeventral (HV). Ainsi, nous avons observé un déficit sélectif des interneurones immunoréactifsà la parvalbumine et une désynchronisation neuronale dans l'HV. L'hippocampe dorsal,impliqué dans l'orientation spatiale, demeure en revanche intact. L'augmentationd'hormones de stress dans le sang des souris KO suite à un stress prépubertal soutien aussil'hypothèse d'une dysfonction de l'HV, connu pour moduler ce type de réponse. Des déficitsstructurels et fonctionnels dans l'hippocampe antérieur (ventral) ont d'ailleurs été rapportéschez des patients schizophrènes. Par de résonance magnétique, nous avons également suivile profil métabolique du le cortex antérieur au cours du développement postnatal des sourisKO. Ces mesures ont révélé des taux élevés de glutamine (Gln), glutamate (Glu), du ratioGln/Glu, et de N-acétyl-aspartate (NAA) durant la période prépubertale. Des altérationssimilaires sont décrites chez les patients durant la phase précoce. Nous avons donc révélédes anomalies phénotypiques chez les souris GCLM KO qui reflètent certainsendophénotypes de la schizophrénie. Nos résultats appuient donc le rôle d'une dérégulationrédox dans l'émergence de la maladie et le potentiel des souris KO comme modèle. De plus,cette étude met en évidence la puberté comme période particulièrement sensible à unedérégulation rédox, renforçant l'importance d'une intervention thérapeutique précoce. Dansce cadre, Gln, Gln/Glu, Glu and NAA seraient des biomarqueurs clés pour identifier de jeunesindividus à risque. De part son efficacité dans notre modèle, NAC pourrait être unesubstance de choix dans le traitement précoce des patients.

Contrast sensitivity to radial frequencies modulated by Jn and j n Bessel profiles

We measured human contrast sensitivity to radial frequencies modulated by cylindrical (Jo) and spherical (j o) Bessel profiles. We also measured responses to profiles of j o, j1, j2, j4, j8, and j16. Functions were measured three times by at least three of eight observers using a forced-choice method. The results conform to our expectations that sensitivity would be higher for cylindrical profiles. We also observed that contrast sensitivity is increased with the j n order for n greater than zero, having distinct orderly effects at the low and high frequency ends. For n = 0, 1, 2, and 4 sensitivity tended to occur around 0.8-1.0 cpd while for n = 8 and 16 it seemed to shift gradually to 0.8-3.0 cpd. We interpret these results as being consistent with the possibility that spatial frequency processing by the human visual system can be defined a priori in terms of polar coordinates and discuss its application to study face perception.

Keyword Join: Realizing Keyword Search in P2P-based Database Systems

In this paper, we present a P2P-based database sharing system that provides information sharing capabilities through keyword-based search techniques. Our system requires neither a global schema nor schema mappings between different databases, and our keyword-based search algorithms are robust in the presence of frequent changes in the content and membership of peers. To facilitate data integration, we introduce keyword join operator to combine partial answers containing different keywords into complete answers. We also present an efficient algorithm that optimize the keyword join operations for partial answer integration. Our experimental study on both real and synthetic datasets demonstrates the effectiveness of our algorithms, and the efficiency of the proposed query processing strategies.

Slicing the metric space to provide quick indexing of complex data in the main memory

Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

Dissociated lateralization of transient and sustained blood oxygen level-dependent signal components in human primary auditory cortex

Among other auditory operations, the analysis of different sound levels received at both ears is fundamental for the localization of a sound source. These so-called interaural level differences, in animals, are coded by excitatory-inhibitory neurons yielding asymmetric hemispheric activity patterns with acoustic stimuli having maximal interaural level differences. In human auditory cortex, the temporal blood oxygen level-dependent (BOLD) response to auditory inputs, as measured by functional magnetic resonance imaging (fMRI), consists of at least two independent components: an initial transient and a subsequent sustained signal, which, on a different time scale, are consistent with electrophysiological human and animal response patterns. However, their specific functional role remains unclear. Animal studies suggest these temporal components being based on different neural networks and having specific roles in representing the external acoustic environment. Here we hypothesized that the transient and sustained response constituents are differentially involved in coding interaural level differences and therefore play different roles in spatial information processing. Healthy subjects underwent monaural and binaural acoustic stimulation and BOLD responses were measured using high signal-to-noise-ratio fMRI. In the anatomically segmented Heschl's gyrus the transient response was bilaterally balanced, independent of the side of stimulation, while in opposite the sustained response was contralateralized. This dissociation suggests a differential role at these two independent temporal response components, with an initial bilateral transient signal subserving rapid sound detection and a subsequent lateralized sustained signal subserving detailed sound characterization.

MIRACLE at Ad-Hoc CLEF 2005: Merging and Combining Without Using a Single Approach

This paper presents the 2005 Miracle’s team approach to the Ad-Hoc Information Retrieval tasks. The goal for the experiments this year was twofold: to continue testing the effect of combination approaches on information retrieval tasks, and improving our basic processing and indexing tools, adapting them to new languages with strange encoding schemes. The starting point was a set of basic components: stemming, transforming, filtering, proper nouns extraction, paragraph extraction, and pseudo-relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. Second-order combinations were also tested, by averaging or selective combination of the documents retrieved by different approaches for a particular query. In the multilingual track, we concentrated our work on the merging process of the results of monolingual runs to get the overall multilingual result, relying on available translations. In both cross-lingual tracks, we have used available translation resources, and in some cases we have used a combination approach.

MIRACLE’s Hybrid Approach to Bilingual and Monolingual Information Retrieval

The main goal of the bilingual and monolingual participation of the MIRACLE team in CLEF 2004 was to test the effect of combination approaches on information retrieval. The starting point was a set of basic components: stemming, transformation, filtering, generation of n-grams, weighting and relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. A second order combination was also tested, mainly by averaging or selective combination of the documents retrieved by different approaches for a particular query.

On correctness in RDF stream processor benchmarking

Two complementary benchmarks have been proposed so far for the evaluation and continuous improvement of RDF stream processors: SRBench and LSBench. They put a special focus on different features of the evaluated systems, including coverage of the streaming extensions of SPARQL supported by each processor, query processing throughput, and an early analysis of query evaluation correctness, based on comparing the results obtained by different processors for a set of queries. However, none of them has analysed the operational semantics of these processors in order to assess the correctness of query evaluation results. In this paper, we propose a characterization of the operational semantics of RDF stream processors, adapting well-known models used in the stream processing engine community: CQL and SECRET. Through this formalization, we address correctness in RDF stream processor benchmarks, allowing to determine the multiple answers that systems should provide. Finally, we present CSRBench, an extension of SRBench to address query result correctness verification using an automatic method.

Gestión de la información en redes de sensores inalámbricos

La gestión del conocimiento (KM) es el proceso de recolectar datos en bruto para su análisis y filtrado, con la finalidad de obtener conocimiento útil a partir de dichos datos. En este proyecto se pretende hacer un estudio sobre la gestión de la información en las redes de sensores inalámbricos como inicio para sentar las bases para la gestión del conocimiento en las mismas. Las redes de sensores inalámbricos (WSN) son redes compuestas por sensores (también conocidos como motas) distribuidos sobre un área, cuya misión es monitorizar una o varias condiciones físicas del entorno. Las redes de sensores inalámbricos se caracterizan por tener restricciones de consumo para los sensores que utilizan baterías, por su capacidad para adaptarse a cambios y ser escalables, y también por su habilidad para hacer frente a fallos en los sensores. En este proyecto se hace un estudio sobre la gestión de la información en redes de sensores inalámbricos. Se comienza introduciendo algunos conceptos básicos: arquitectura, pila de protocolos, topologías de red, etc.… Después de esto, se ha enfocado el estudio hacia TinyDB, el cual puede ser considerado como parte de las tecnologías más avanzadas en el estado del arte de la gestión de la información en redes de sensores inalámbricos. TinyDB es un sistema de procesamiento de consultas para extraer información de una red de sensores. Proporciona una interfaz similar a SQL y permite trabajar con consultas contra la red de sensores inalámbricos como si se tratara de una base de datos tradicional. Además, TinyDB implementa varias optimizaciones para manejar los datos eficientemente. En este proyecto se describe también la implementación de una sencilla aplicación basada en redes de sensores inalámbricos. Las motas en la aplicación son capaces de medir la corriente a través de un cable. El objetivo de esta aplicación es monitorizar el consumo de energía en diferentes zonas de un área industrial o doméstico, utilizando redes de sensores inalámbricas. Además, se han implementado las optimizaciones más importantes que se han aprendido en el análisis de la plataforma TinyDB. Para desarrollar esta aplicación se ha utilizado como sensores la plataforma open-source de creación de prototipos electrónicos Arduino, y el ordenador de placa reducida Raspberry Pi como coordinador. ABSTRACT. Knowledge management (KM) is the process of collecting raw data for analysis and filtering, to get a useful knowledge from this data. In this project the information management in wireless sensor networks is studied as starting point before knowledge management. Wireless sensor networks (WSN) are networks which consists of sensors (also known as motes) distributed over an area, to monitor some physical conditions of the environment. Wireless sensor networks are characterized by power consumption constrains for sensors which are using batteries, by the ability to be adaptable to changes and to be scalable, and by the ability to cope sensor failures. In this project it is studied information management in wireless sensor networks. The document starts introducing basic concepts: architecture, stack of protocols, network topology… After this, the study has been focused on TinyDB, which can be considered as part of the most advanced technologies in the state of the art of information management in wireless sensor networks. TinyDB is a query processing system for extracting information from a network of sensors. It provides a SQL-like interface and it lets us to work with queries against the wireless sensor network like if it was a traditional database. In addition, TinyDB implements a lot of optimizations to manage data efficiently. In this project, it is implemented a simple wireless sensor network application too. Application’s motes are able to measure amperage through a cable. The target of the application is, by using a wireless sensor network and these sensors, to monitor energy consumption in different areas of a house. Additionally, it is implemented the most important optimizations that we have learned from the analysis of TinyDB platform. To develop this application it is used Arduino open-source electronics prototyping platform as motes, and Raspberry Pi single-board computer as coordinator.