A generalized Drucker–Prager viscoplastic yield surface model for asphalt concrete

A generalized Drucker–Prager (GD–P) viscoplastic yield surface model was developed and validated for asphalt concrete. The GD–P model was formulated based on fabric tensor modified stresses to consider the material inherent anisotropy. A smooth and convex octahedral yield surface function was developed in the GD–P model to characterize the full range of the internal friction angles from 0° to 90°. In contrast, the existing Extended Drucker–Prager (ED–P) was demonstrated to be applicable only for a material that has an internal friction angle less than 22°. Laboratory tests were performed to evaluate the anisotropic effect and to validate the GD–P model. Results indicated that (1) the yield stresses of an isotropic yield surface model are greater in compression and less in extension than that of an anisotropic model, which can result in an under-prediction of the viscoplastic deformation; and (2) the yield stresses predicted by the GD–P model matched well with the experimental results of the octahedral shear strength tests at different normal and confining stresses. By contrast, the ED–P model over-predicted the octahedral yield stresses, which can lead to an under-prediction of the permanent deformation. In summary, the rutting depth of an asphalt pavement would be underestimated without considering anisotropy and convexity of the yield surface for asphalt concrete. The proposed GD–P model was demonstrated to be capable of overcoming these limitations of the existing yield surface models for the asphalt concrete.

On Affine Connections in a Riemannian Manifold with a Circulant Metric and two Circulant Affinor Structures

Ива Р. Докузова, Димитър Р. Разпопов - В настоящата статия е разгледан клас V оттримерни риманови многообразия M с метрика g и два афинорни тензора q и S. Дефинирана е и друга метрика ¯g в M. Локалните координати на всички тези тензори са циркулантни матрици. Намерени са: 1) зависимост между тензора на кривина R породен от g и тензора на кривина ¯R породен от ¯g; 2) тъждество за тензора на кривина R в случая, когато тензорът на кривина ¯R се анулира; 3) зависимост между секционната кривина на прозволна двумерна q-площадка {x, qx} и скаларната кривина на M.

Semi-Symmetric Algebras: General Constructions. Part II

2000 Mathematics Subject Classification: 15A69, 15A78.

Special compositions in affinely connected spaces without a torsion

2000 Mathematics Subject Classification: 53B05, 53B99.

An integrated functional mapping and source localization platform for brain research

The premise of this dissertation is to create a highly integrated platform that combines the most current recording technologies for brain research through the development of new algorithms for three-dimensional (3D) functional mapping and 3D source localization. The recording modalities that were integrated include: Electroencephalography (EEG), Optical Topographic Maps (OTM), Magnetic Resonance Imaging (MRI), and Diffusion Tensor Imaging (DTI). This work can be divided into two parts: The first part involves the integration of OTM with MRI, where the topographic maps are mapped to both the skull and cortical surface of the brain. This integration process is made possible through the development of new algorithms that determine the probes location on the MRI head model and warping the 2D topographic maps onto the 3D MRI head/brain model. Dynamic changes of the brain activation can be visualized on the MRI head model through a graphical user interface. The second part of this research involves augmenting a fiber tracking system, by adding the ability to integrate the source localization results generated by commercial software named Curry. This task involved registering the EEG electrodes and the dipole results to the MRI data. Such Integration will allow the visualization of fiber tracts, along with the source of the EEG, in a 3D transparent brain structure. The research findings of this dissertation were tested and validated through the participation of patients from Miami Children Hospital (MCH). Such an integrated platform presented to the medical professionals in the form of a user-friendly graphical interface is viewed as a major contribution of this dissertation. It should be emphasized that there are two main aspects to this research endeavor: (1) if a dipole could be situated in time at its different positions, its trajectory may reveal additional information on the extent and nature of the brain malfunction; (2) situating such a dipole trajectory with respect to the fiber tracks could ensure the preservation of these fiber tracks (axons) during surgical interventions, preserving as a consequence these parts of the brain that are responsible for information transmission.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Reduced-parameter model of head-related transfer functions for synthesized spatial audio

Digital systems can generate left and right audio channels that create the effect of virtual sound source placement (spatialization) by processing an audio signal through pairs of Head-Related Transfer Functions (HRTFs) or, equivalently, Head-Related Impulse Responses (HRIRs). The spatialization effect is better when individually-measured HRTFs or HRIRs are used than when generic ones (e.g., from a mannequin) are used. However, the measurement process is not available to the majority of users. There is ongoing interest to find mechanisms to customize HRTFs or HRIRs to a specific user, in order to achieve an improved spatialization effect for that subject. Unfortunately, the current models used for HRTFs and HRIRs contain over a hundred parameters and none of those parameters can be easily related to the characteristics of the subject. This dissertation proposes an alternative model for the representation of HRTFs, which contains at most 30 parameters, all of which have a defined functional significance. It also presents methods to obtain the value of parameters in the model to make it approximately equivalent to an individually-measured HRTF. This conversion is achieved by the systematic deconstruction of HRIR sequences through an augmented version of the Hankel Total Least Squares (HTLS) decomposition approach. An average 95% match (fit) was observed between the original HRIRs and those re-constructed from the Damped and Delayed Sinusoids (DDSs) found by the decomposition process, for ipsilateral source locations. The dissertation also introduces and evaluates an HRIR customization procedure, based on a multilinear model implemented through a 3-mode tensor, for mapping of anatomical data from the subjects to the HRIR sequences at different sound source locations. This model uses the Higher-Order Singular Value Decomposition (HOSVD) method to represent the HRIRs and is capable of generating customized HRIRs from easily attainable anatomical measurements of a new intended user of the system. Listening tests were performed to compare the spatialization performance of customized, generic and individually-measured HRIRs when they are used for synthesized spatial audio. Statistical analysis of the results confirms that the type of HRIRs used for spatialization is a significant factor in the spatialization success, with the customized HRIRs yielding better results than generic HRIRs.

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

Buraco negros, correspondência AdS/BCFT e fluido/gravidade

Einstein’s equations with negative cosmological constant possess the so-called anti de Sitter space, AdSd+1, as one of its solutions. We will later refer to this space as to the "bulk". The holographic principle states that quantum gravity in the AdSd+1 space can be encoded by a d−dimensional quantum field theory on the boundary of AdSd+1 space, invariant under conformal transformations, a CFTd. In the most famous example, the precise statement is the duality of the type IIB string theory in the space AdS5 × S 5 and the 4−dimensional N = 4 supersymmetric Yang-Mills theory. Another example is provided by a relation between Einstein’s equations in the bulk and hydrodynamic equations describing the effective theory on the boundary, the so-called fluid/gravity correspondence. An extension of the "AdS/CFT duality"for the CFT’s with boundary was proposed by Takayanagi, which was dubbed the AdS/BCFT correspondence. The boundary of a CFT extends to the bulk and restricts a region of the AdSd+1. Neumann conditions imposed on the extension of the boundary yield a dynamic equation that determines the shape of the extension. From the perspective of fluid/gravity correspondence, the shape of the Neumann boundary, and the geometry of the bulk is sourced by the energy-momentum tensor Tµν of a fluid residing on this boundary. Clarifying the relation of the Takayanagi’s proposal to the fluid/gravity correspondence, we will study the consistence of the AdS/BCFT with finite temperature CFT’s, or equivalently black hole geometries in the bulk.

Analisi del catalogo Europeo-Mediterraneo degli RCMT: 18 anni di dati.

L'RCMT (Regional Centroid Moment Tensor), realizzato e gestito dai ricercatori dell'INGV (Istituto Nazionale di Geofisica e Vulcanologia), è dal 1997 il catalogo di riferimento per gli eventi sismici avvenuti nell'area Europea-Mediterranea, ossia nella regione avente longitudine compresa tra 10° W e 40° E e latitudine compresa tra 25° N e 60° N. Tale regione è caratterizzata da un'attività tettonica complessa, legata non soltanto alla convergenza delle placche Euroasiatica ed Africana, ma anche al movimento di altre placche minori (ad esempio, la placca Arabica), che tutte insieme danno origine ad una vasta gamma di regimi tettonici. Col termine RCMT si indica un particolare tipo di tensore momento sismico, la cui determinazione avviene su scala regionale, per eventi sismici aventi M_w >= 4.5 (M_w >= 4.0 per gli eventi che avvengono nella penisola italica). Il tensore momento sismico è uno strumento fondamentale per caratterizzare natura ed entità di un terremoto. Da esso, infatti, oltre alla magnitudo momento M_w, si ricava anche il meccanismo focale. Comunemente rappresentato sotto forma di beach ball, consente di individuare il tipo di movimento (distensivo, compressivo o trascorrente, o anche una combinazione del primo o del secondo con il terzo) avvenuto sulla faglia che ha provocato il terremoto. I tensori momento sismico permettono, quindi, di identificare le faglie che si attivano durante una sequenza sismica, di comprendere la loro cinematica e di ipotizzare la successiva evoluzione a breve termine. Scopo di questa relazione di laurea è stato derivare le relazioni che intercorrono fra le M_w dell'RCMT e le M_w del CMT (Centroid Moment Tensor della Columbia University), del GFZ (Deutsches GeoForschungsZentrum di Postdam) e del TDMT (Time Domain Moment Tensor). Le relazioni sono state ottenute applicando il metodo dei minimi quadrati agli eventi comuni, che sono stati selezionati utilizzando alcuni semplici programmi scritti in Fortran.

Le metodiche di Diffusion Weighted Imaging per la caratterizzazione della malattia policistica renale

La tecnica di Diffusion Weighted Imaging (DWI) si basa sullo studio del moto diffusivo delle molecole d’acqua nei tessuti biologici ed è in grado di fornire informazioni sulla struttura dei tessuti e sulla presenza di eventuali alterazioni patologiche. Il più recente sviluppo della DWI è rappresentato dal Diffusion Tensor Imaging (DTI), tecnica che permette di determinare non solo l’entità, ma anche le direzioni principali della diffusione. Negli ultimi anni, grazie ai progressi nella tecnica di risonanza magnetica, l’imaging di diffusione è stato anche applicato ad altri distretti anatomici tra cui quello renale, per sfruttarne le potenzialità diagnostiche. Tuttavia, pochi sono ancora gli studi relativi all’applicazione delle metodiche di diffusione per la valutazione della malattia policistica renale autosomica dominante (ADPKD). ADPKD è una delle malattie ereditarie più comuni ed è la principale causa genetica di insufficienza renale dell’adulto. La caratteristica principale consiste nella formazione di cisti in entrambi i reni, che progressivamente aumentano in numero e dimensioni fino a causare la perdita della funzionalità renale nella metà circa dei pazienti. Ad oggi non sono disponibili terapie capaci di arrestare o rallentare l’evoluzione di ADPKD; è possibile controllare le complicanze per evitare che costituiscano componenti peggiorative. Il lavoro di tesi nasce dalla volontà di indagare se la tecnica dell’imaging di diffusione possa essere utile per fornire informazioni sullo stato della malattia e sul suo grado di avanzamento. L’analisi di studio è concentrata sul calcolo del coefficiente di diffusione apparente (ADC), derivato dalle immagini DWI e valutato nella regione della midollare. L’obiettivo di questo lavoro è verificare se tale valore di ADC sia in grado di caratterizzare la malattia policistica renale e possa essere utilizzato in ambito clinico-diagnostico come indicatore prognostico nella progressione di questa patologia.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

New constraints on micro-seismicity and stress state in the western part of the North Anatolian Fault Zone : Observations from a dense seismic array

Major funding was provided by the UK Natural Environment Research Council (NERC) under grant NE/I028017/1 and partially supported by Boğaziçi University Research Fund (BAP) under grant 6922. We would like to thank all the project members from the University of Leeds, Boğaziçi University, Kandilli Observatory, Aberdeen University and Sakarya University. I would also like to thank Prof. Ali Pinar and Dr. Kıvanç Kekovalı for their valuable comments. Some of the figures were generated by GMT software (Wessel and Smith, 1995).

New constraints on micro-seismicity and stress state in the western part of the North Anatolian Fault Zone : Observations from a dense seismic array

Major funding was provided by the UK Natural Environment Research Council (NERC) under grant NE/I028017/1 and partially supported by Boğaziçi University Research Fund (BAP) under grant 6922. We would like to thank all the project members from the University of Leeds, Boğaziçi University, Kandilli Observatory, Aberdeen University and Sakarya University. I would also like to thank Prof. Ali Pinar and Dr. Kıvanç Kekovalı for their valuable comments. Some of the figures were generated by GMT software (Wessel and Smith, 1995).

Vacuum spacetimes with constant Weyl eigenvalues

Einstein spacetimes (that is vacuum spacetimes possibly with a non-zero cosmological constant A) with constant non-zero Weyl eigenvalues are considered. For type Petrov II & D this assumption allows one to prove that the non-repeated eigenvalue necessarily has the value 2A/3 and it turns out that the only possible spacetimes are some Kundt-waves considered by Lewandowski which are type II and a Robinson-Bertotti solution of type D. For Petrov type I the only solution turns out to be a homogeneous pure vacuum solution found long ago by Petrov using group theoretic methods. These results can be summarised by the statement that the only vacuum spacetimes with constant Weyl eigenvalues are either homogeneous or are Kundt spacetimes. This result is similar to that of Coley et al. who proved their result for general spacetimes under the assumption that all scalar invariants constructed from the curvature tensor and all its derivatives were constant.