Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

Cognitive radio applications for enhanced spectrum efficiency

The aim of this thesis is the study of techniques for efficient management and use of the spectrum based on cognitive radio technology. The ability of cognitive radio technologies to adapt to the real-time conditions of its operating environment, offers the potential for more flexible use of the available spectrum. In this context, the international interest is particularly focused on the “white spaces” in the UHF band of digital terrestrial television. Spectrum sensing and geo-location database have been considered in order to obtain information on the electromagnetic environment. Different methodologies have been considered in order to investigate spectral resources potentially available for the white space devices in the TV band. The adopted methodologies are based on the geo-location database approach used either in autonomous operation or in combination with sensing techniques. A novel and computationally efficient methodology for the calculation of the maximum permitted white space device EIRP is then proposed. The methodology is suitable for implementation in TV white space databases. Different Italian scenarios are analyzed in order to identify both the available spectrum and the white space device emission limits. Finally two different applications of cognitive radio technology are considered. The first considered application is the emergency management. The attention is focused on the consideration of both cognitive and autonomic networking approaches when deploying an emergency management system. The cognitive technology is then considered in applications related to satellite systems. In particular a hybrid cognitive satellite-terrestrial is introduced and an analysis of coexistence between terrestrial and satellite networks by considering a cognitive approach is performed.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Role of outgrowth endothelial cells for applications in tissue engineering

Co-culture systems, consisting of outgrowth endothelial cells (OEC) and primary osteoblasts (pOB), represent a prom¬ising instrument to mimick the natural conditions in bone repair processes and provide a new concept to develop constructs for bone replacement. Furthermore, co-culture of OEC and pOB could provide new insights into the molecular and cellular mechanisms that control essential processes during bone repair. The present study described several advantages of the co-culture of pOB and OEC for bone tissue engineering applications, including beneficial effects on the angiogenic activation of OEC, as well as on the assembly of basement membrane matrix molecules and factors involved in vessel maturation and stabilization. The ongoing angiogenic process in the co-culture system proceeded during the course of co-cultivation and correlated with the upregulation of essential angiogenic factors, such as VEGF, angiopoietins, basement membrane molecules and mural cell-specific markers. Furthermore the co-culture system appeared to maintain osteogenic differentiation capacity.rnrnAdditional treatment of co-cultures with growth factors or morphogens might accelerate and improve bone formation and furthermore could be useful for potential clinical applications. In this context, the present study highlights the central role of the morphogen, sonic hedgehog, which has been shown to affect angiogenic activation as well as osteogenic differentiation in the co-culture model of OEC and pOB. Treatment of co-cultures with sonic hedgehog resulted in an increased formation of microvessel-like structures as early as after 24 hours. This proangiogenic effect was induced by the upregulation of the proangiogenic factors, VEGF, angiopoietin1 and angiopoietin 2. In contrast to treatment with a commonly used proangiogenic agent, VEGF, Shh stimulation induced an increased expression of factors associated with vessel maturation and stabilization, mediated through the upregulation of growth factors that are strongly involved in pericyte differentiation and recruitment, including PDGF-BB and TGFbeta. In addition, Shh treatment of co-cultures also resulted in an upregulation of osteogenic differentiation markers like alkaline phosphatase, osteocalcin, osteonectin and osteopontin, as well as an increased matrix calcification. This was a result of upregulation of the osteogenic differentiation regulating factors, BMP2 and RUNX2 which could be assessed in response to Shh treatment. rn

Searching and retrieving in content-based repositories of formal mathematical knowledge

In this thesis, the author presents a query language for an RDF (Resource Description Framework) database and discusses its applications in the context of the HELM project (the Hypertextual Electronic Library of Mathematics). This language aims at meeting the main requirements coming from the RDF community. in particular it includes: a human readable textual syntax and a machine-processable XML (Extensible Markup Language) syntax both for queries and for query results, a rigorously exposed formal semantics, a graph-oriented RDF data access model capable of exploring an entire RDF graph (including both RDF Models and RDF Schemata), a full set of Boolean operators to compose the query constraints, fully customizable and highly structured query results having a 4-dimensional geometry, some constructions taken from ordinary programming languages that simplify the formulation of complex queries. The HELM project aims at integrating the modern tools for the automation of formal reasoning with the most recent electronic publishing technologies, in order create and maintain a hypertextual, distributed virtual library of formal mathematical knowledge. In the spirit of the Semantic Web, the documents of this library include RDF metadata describing their structure and content in a machine-understandable form. Using the author's query engine, HELM exploits this information to implement some functionalities allowing the interactive and automatic retrieval of documents on the basis of content-aware requests that take into account the mathematical nature of these documents.

Polymer nanoparticles : their functionalization for biomedical applications and dynamics near an electrode

In this work, a method for the functionalization of biocompatible, poly(lactic acid)-based nanoparticles with charged moieties or fluorescent labels is presented. Therefore, a miniemulsion solvent evaporation procedure is used in which prepolymerized poly(L-lactic acid) is used together with a previously synthesized copolymer of methacrylic acid or a polymerizable dye, respectively, and an oligo(lactic acid) macromonomer. Alternatively, the copolymerization has been carried out in one step with the miniemulsion solvent evaporation. The increased stability in salty solutions of the carboxyl-modified nanoparticles compared to nanoparticles consisting of poly(lactic acid) only has been shown in light scattering experiments. The properties of the nanoparticles that were prepared with the separately synthesized copolymer were almost identical to those in which the copolymerization and particle fabrication were carried out simultaneously. During the characterization of the fluorescently labeled nanoparticles, the focus was on the stable bonding between the fluorescent dye and the rest of the polymer chain to ensure that none of it is released from the particles, even after longer storage time or during lengthy experiments. In a fluorescence correlation spectroscopy experiment, it could be shown that even after two weeks, no dye has been released into the solvent. Besides biomedical research for which the above described, functionalized nanoparticles were optimized, nanoparticles also play a role in coating technology. One possibility to fabricate coatings is the electrophoretic deposition of particles. In this process, the mobility of nanoparticles near electrode interfaces plays a crucial role. In this thesis, the nanoparticle mobility has been investigated with resonance enhanced dynamic light scattering (REDLS). A new setup has been developed in which the evanescent electromagnetic eld of a surface plasmon that propagates along the gold-sample interface has been used as incident beam for the dynamic light scattering experiment. The gold layer that is necessary for the excitation of the plasmon doubles as an electrode. Due to the penetration depth of the surface plasmon into the sample layer that is limited to ca. 200 nm, insights on the voltage- and frequency dependent mobility of the nanoparticles near the electrode could be gained. Additionally, simultaneous measurements at four different scattering angles can be carried out with this setup, therefore the investigation of samples undergoing changes is feasible. The results were discussed in context with the mechanisms of electrophoretic deposition.

Scale Up of PLA Nanoparticle Synthesis by Solvent Displacement and Functionalization of the Particles with a Silica Shell for Targeted Drug Delivery Applications

Biodegradable polymer nanoparticles have the properties necessary to address many of the issues associated with current drug delivery techniques including targeted and controlled delivery. A novel drug delivery vehicle is proposed consisting of a poly(lactic acid) nanoparticle core, with a functionalized, mesoporous silica shell. In this study, the production of PLA nanoparticles is investigated using solvent displacement in both a batch and continuous manner, and the effects of various system parameters are examined. Using Pluronic F-127 as the stabilization agent throughout the study, PLA nanoparticles are produced through solvent displacement with diameters ranging from 200 to 250 nm using two different methods: dropwise addition and in an impinging jet mixer. The impinging jet mixer allows for easy scale-up of particle production. The concentration of surfactant and volume of quench solution is found to have minimal impact on particle diameter; however, the concentration of PLA is found to significantly impact the diameter mean and polydispersity. In addition, the stability of the PLA nanoparticles is observed to increase as residual THF is evaporated. Lastly, the isolated PLA nanoparticles are coated with a silica shell using the Stöber Process. It is found that functionalizing the silica with a phosphonic silane in the presence of excess Pluronic F-127 decreases coalescence of the particles during the coating process. Future work should be conducted to fine-tune the PLA nanoparticle synthesis process by understanding the effect of other system parameters and in synthesizing mesoporous silica shells.

Using Context Information to Re-architect a System

Successful software systems cope with complexity by organizing classes into packages. However, a particular organization may be neither straightforward nor obvious for a given developer. As a consequence, classes can be misplaced, leading to duplicated code and ripple effects with minor changes effecting multiple packages. We claim that contextual information is the key to rearchitecture a system. Exploiting contextual information, we propose a technique to detect misplaced classes by analyzing how client packages access the classes of a given provider package. We define locality as a measure of the degree to which classes reused by common clients appear in the same package. We then use locality to guide a simulated annealing algorithm to obtain optimal placements of classes in packages. The result is the identification of classes that are candidates for relocation. We apply the technique to three applications and validate the usefulness of our approach via developer interviews.

LIKELIHOOD ESTIMATION OF CONJUGACY RELATIONSHIPS IN LINEAR MODELS WITH APPLICATIONS TO HIGH-THROUGHPUT GENOMICS

In the simultaneous estimation of a large number of related quantities, multilevel models provide a formal mechanism for efficiently making use of the ensemble of information for deriving individual estimates. In this article we investigate the ability of the likelihood to identify the relationship between signal and noise in multilevel linear mixed models. Specifically, we consider the ability of the likelihood to diagnose conjugacy or independence between the signals and noises. Our work was motivated by the analysis of data from high-throughput experiments in genomics. The proposed model leads to a more flexible family. However, we further demonstrate that adequately capitalizing on the benefits of a well fitting fully-specified likelihood in the terms of gene ranking is difficult.

Synthesis of chiral ferrosalen ligands and their applications in asymmetric catalysis

A new series of chiral ferrosalen ligands was designed and synthesized. The special feature of the ferrosalen ligands is that the chirality originated from the planar chiral ferrocenyl structure. For most known salen ligands, chirality comes from central and axial chiral centers. The key building block for the construction of these ferrosalen ligands was synthesized stereoselectively by a chiral auxiliary approach. This approach does not consume any chiral material, and does not require chiral HPLC resolution. Using this method, nine ligands were prepared using ferrocene as the starting material. In addition, the steric hindrance was modulated by changing the cyclopentadienyl group to the more bulky pentamethylcyclopentadienyl- and pentaphenylcyclopentadienyl- groups. The structure of these ligands was established by 1H and 13C NMR. The structure of a ferrosalen-Cu (II) complex was determined by single crystal X-ray diffraction analysis. All the chiral ferrosalen ligands were tested in catalytic asymmetric reactions including enantioselective carbonyl-ene reaction, enantioselective Strecker-type reaction and enantioselective silylcyanation. For the carbonyl-ene reaction, up to 99% yield and 29% enantiomeric excess (ee) were obtained using ligand-Co (III) as the catalysts; For the Strecker-type reaction, a maximum of 20% ee was obtained using ligand-AlCl as the catalyst; For the silylcyanation reaction, up to 99% yield and 26% ee were obtained using ligand-AlCl as the catalyst.

Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.

Development and modeling of thermally conductive resins for fuel cell bipolar plate applications

Thermally conductive resins are a class of material that show promise in many different applications. One growing field for their use is in the area of bipolar plate technology for fuel cell applications. In this work, a LCP was mixed with different types of carbon fillers to determine the effects of the individual carbon fillers on the thermal conductivity of the composite resin. In addition, mathematical modeling was performed on the thermal conductivity data with the goal of developing predictive models for the thermal conductivity of highly filled composite resins.