A low complexity system based on multiple weighted decision trees for indoor localization

[EN] Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.

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.

Aggregazione delle query per sistemi pub/sub: il progetto SALES

I sistemi mobili rappresentano una classe di sistemi distribuiti caratterizzata dalla presenza di dispositivi portatili eterogenei quali PDA, laptop e telefoni cellulari che interagiscono tra loro mediante una rete di interconnessione wireless. Una classe di sistemi mobili di particolare interesse è costituita dai sistemi basati sul modello di interazione publish/subscribe. Secondo tale schema, i nodi all'interno di una rete possono assumere due ruoli differenti: i produttori di informazione, chiamati publisher, ed i consumatori di informazione, chiamati subscriber. Tipicamente, l'interazione tra essi è mediata da un gestore di eventi che indirizza correttamente le informazioni ricevute dai publisher verso i subscriber interessati, sulla base degli interessi espressi da questi ultimi tramite sottoscrizioni. Nella progettazione di sistemi mobili, a differenza di quelli tradizionali basati su nodi fissi, bisogna tenere conto di problemi quali la scarsa capacità computazionale dei dispositivi e la limitata larghezza di banda delle reti wireless. All'interno di tale ambito, stanno recentemente assumendo sempre maggiore importanza i sistemi context-aware, ovvero sistemi mobili che sfruttano i dati provenienti dall'ambiente circostante e dai dispositivi stessi per adattare il proprio comportamento e notificare agli utenti la presenza di informazioni potenzialmente utili. Nello studio di questi sistemi, si è notato che i nodi che si trovano nella stessa area geografica generano tipicamente delle sottoscrizioni che presentano tra loro un certo grado di similarità e coperture parziali o totali. Il gruppo di ricerca del DEIS dell’Università di Bologna ha sviluppato un'infrastruttura di supporto per sistemi mobili context-aware, chiamata SALES. Attualmente il sistema progettato non considera le similarità delle sottoscrizioni e quindi non sfrutta opportunamente tale informazione. In questo contesto si rende necessario l'adozione di opportune tecniche di aggregazione delle sottoscrizioni atte ad alleggerire la computazione dei nodi mobili e le comunicazioni tra loro. Il lavoro presentato in questa tesi sarà finalizzato alla ricerca, all'adattamento ed all'implementazione di una tecnica di aggregazione delle sottoscrizioni. Tale tecnica avrà lo scopo di rilevare e sfruttare le similarità delle sottoscrizioni ricevute dal sistema al fine di ridurne il numero; in questo modo, quando un nodo riceverà un dato, il processo di confronto tra l'insieme delle sottoscrizioni memorizzate e il dato ricevuto sarà più leggero, consentendo un risparmio di risorse computazionali. Inoltre, adattando tali tecniche, sarà possibile modulare anche il traffico dati scaturito dalle risposte alle sottoscrizioni. La struttura di questa tesi prevede un primo capitolo sui sistemi context-aware, descrivendone le principali caratteristiche e mettendo in luce le problematiche ad essi associate. Il secondo capitolo illustra il modello di comunicazione Publish/Subscribe, modello di riferimento per i moderni sistemi context-aware e per i sistemi mobili in generale. Il terzo capitolo descrive l'infrastruttura SALES sulla quale si è progettata, implementata e testata la soluzione proposta in questa tesi. Il quarto capitolo presenta le principali tecniche di aggregazione delle sottoscrizioni e spiega come possono essere adattate al contesto di questa tesi. Il quinto capitolo effettua l'analisi dei requisiti per comprendere meglio il comportamento della soluzione; seguono la progettazione e l’implementazione della soluzione su SALES. Infine, il sesto capitolo riporta in dettaglio i risultati ottenuti da alcuni degli esperimenti effettuati e vengono messi a confronto con quelli rilevati dal sistema di partenza.

Weighted Inequalities and Lipschitz Spaces

In this thesis I have characterized the trace measures for particular potential spaces of functions defined on R^n, but "mollified" so that the potentials are de facto defined on the upper half-space of R^n. The potential functions are kind Riesz-Bessel. The characterization of trace measures for these spaces is a test condition on elementary sets of the upper half-space. To prove the test condition as sufficient condition for trace measures, I had give an extension to the case of upper half-space of the Muckenhoupt-Wheeden and Wolff inequalities. Finally I characterized the Carleson-trace measures for Besov spaces of discrete martingales. This is a simplified discrete model for harmonic extensions of Lipschitz-Besov spaces.

Weighted geometric mean of large-scale matrices: numerical analysis and algorithms

Computing the weighted geometric mean of large sparse matrices is an operation that tends to become rapidly intractable, when the size of the matrices involved grows. However, if we are not interested in the computation of the matrix function itself, but just in that of its product times a vector, the problem turns simpler and there is a chance to solve it even when the matrix mean would actually be impossible to compute. Our interest is motivated by the fact that this calculation has some practical applications, related to the preconditioning of some operators arising in domain decomposition of elliptic problems. In this thesis, we explore how such a computation can be efficiently performed. First, we exploit the properties of the weighted geometric mean and find several equivalent ways to express it through real powers of a matrix. Hence, we focus our attention on matrix powers and examine how well-known techniques can be adapted to the solution of the problem at hand. In particular, we consider two broad families of approaches for the computation of f(A) v, namely quadrature formulae and Krylov subspace methods, and generalize them to the pencil case f(A\B) v. Finally, we provide an extensive experimental evaluation of the proposed algorithms and also try to assess how convergence speed and execution time are influenced by some characteristics of the input matrices. Our results suggest that a few elements have some bearing on the performance and that, although there is no best choice in general, knowing the conditioning and the sparsity of the arguments beforehand can considerably help in choosing the best strategy to tackle the problem.

Comparison of physiological triggering schemes for diffusion-weighted magnetic resonance imaging in kidneys

To determine the potential benefit of combined respiratory-cardiac triggering for diffusion-weighted imaging (DWI) of kidneys compared to respiratory triggering alone (RT).

Evaluation of renal allograft function early after transplantation with diffusion-weighted MR imaging

To determine the inter-patient variability of apparent diffusion coefficients (ADC) and concurrent micro-circulation contributions from diffusion-weighted MR imaging (DW-MRI) in renal allografts early after transplantation, and to obtain initial information on whether these measures are altered in histologically proven acute allograft rejection (AR).

Predicting and monitoring cancer treatment response with diffusion-weighted MRI

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Synthetic-echo time postprocessing technique for generating images with variable T2-weighted contrast: diagnosis of meniscal and cartilage abnormalities of the knee

To assess the feasibility and accuracy of a synthetic-echo time (TE) magnetic resonance (MR) postprocessing technique for the diagnostic evaluation of abnormalities of menisci and articular cartilage in the knee.

Diffusion-weighted imaging for the follow-up of patients after matrix-associated autologous chondrocyte transplantation

To evaluate the use of diffusion-weighted imaging (DWI) for the assessment of cartilage maturation in patients after matrix-associated autologous chondrocyte transplantation (MACT).

EPITHET: Positive Result After Reanalysis Using Baseline Diffusion-Weighted Imaging/Perfusion-Weighted Imaging Co-Registration

the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET) was a prospective, randomized, double-blinded, placebo-controlled, phase II trial of alteplase between 3 and 6 hours after stroke onset. The primary outcome of infarct growth attenuation on MRI with alteplase in mismatch patients was negative when mismatch volumes were assessed volumetrically, without coregistration, which underestimates mismatch volumes. We hypothesized that assessing the extent of mismatch by coregistration of perfusion and diffusion MRI maps may more accurately allow the effects of alteplase vs placebo to be evaluated.

Susceptibility-weighted imaging of the brain: Does gadolinium administration matter?

Susceptibility-weighted MR imaging (SWI) is usually obtained without administration of intravenous gadolinium (Gd). However, it is occasionally necessary to perform SWI after Gd is injected. The effects of Gd on SWI have not been systematically examined. The aim of this prospective study was to investigate whether performing SWI after Gd would influence the diagnostic image quality, parenchymal signal and vascular enhancement. An additional aim is to suggest potential future applications for Gd-enhanced SWI.

Diffusion-weighted MR imaging of the placenta in fetuses with placental insufficiency

PURPOSE: To evaluate diffusion-weighted magnetic resonance (MR) imaging of the human placenta in fetuses with and fetuses without intrauterine growth restriction (IUGR) who were suspected of having placental insufficiency. MATERIALS AND METHODS: The study was approved by the local ethics committee, and written informed consent was obtained. The authors retrospectively evaluated 1.5-T fetal MR images from 102 singleton pregnancies (mean gestation ± standard deviation, 29 weeks ± 5; range, 21-41 weeks). Morphologic and diffusion-weighted MR imaging were performed. A region of interest analysis of the apparent diffusion coefficient (ADC) of the placenta was independently performed by two observers who were blinded to clinical data and outcome. Placental insufficiency was diagnosed if flattening of the growth curve was detected at obstetric ultrasonography (US), if the birth weight was in the 10th percentile or less, or if fetal weight estimated with US was below the 10th percentile. Abnormal findings at Doppler US of the umbilical artery and histopathologic examination of specimens from the placenta were recorded. The ADCs in fetuses with placental insufficiency were compared with those in fetuses of the same gestational age without placental insufficiency and tested for normal distribution. The t tests and Pearson correlation coefficients were used to compare these results at 5% levels of significance. RESULTS: Thirty-three of the 102 pregnancies were ultimately categorized as having an insufficient placenta. MR imaging depicted morphologic changes (eg, infarction or bleeding) in 27 fetuses. Placental dysfunction was suspected in 33 fetuses at diffusion-weighted imaging (mean ADC, 146.4 sec/mm(2) ± 10.63 for fetuses with placental insufficiency vs 177.1 sec/mm(2) ± 18.90 for fetuses without placental insufficiency; P < .01, with one false-positive case). The use of diffusion-weighted imaging in addition to US increased sensitivity for the detection of placental insufficiency from 73% to 100%, increased accuracy from 91% to 99%, and preserved specificity at 99%. CONCLUSION: Placental dysfunction associated with growth restriction is associated with restricted diffusion and reduced ADC. A decreased ADC used as an early marker of placental damage might be indicative of pregnancy complications such as IUGR.

Diffusion-weighted MR imaging of native and transplanted kidneys

Applications of diffusion-weighted (DW) magnetic resonance (MR) imaging outside the brain have gained increasing importance in recent years. Owing to technical improvements in MR imaging units and faster sequences, the need for noninvasive imaging without contrast medium administration, mainly in patients with renal insufficiency, can be met successfully by applying this technique. DW MR imaging is quantified by the apparent diffusion coefficient (ADC), which provides information on diffusion and perfusion simultaneously. By using a biexponential fitting process of the DW MR imaging data, these two entities can be separated, because this type of fitting process can serve as an estimate of both the perfusion fraction and the true diffusion coefficient. DW MR imaging can be applied for functional evaluation of the kidneys in patients with acute or chronic renal failure. Impairment of renal function is accompanied by a decreased ADC. Acute ureteral obstruction leads to perfusion and diffusion changes in the affected kidney, and renal artery stenosis results in a decreased ADC. In patients with pyelonephritis, diffuse or focal changes in signal intensity are seen on the high-b-value images, with increased signal intensity corresponding to low signal intensity on the ADC map. The feasibility and reproducibility of DW MR imaging in patients with transplanted kidneys have already been demonstrated, and initial results seem to be promising for the assessment of allograft deterioration. Overall, performance of renal DW MR imaging, presuming that measurements are of high quality, will further boost this modality, particularly for early detection of diffuse renal conditions, as well as more accurate characterization of focal renal lesions.