Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

High performance shift invariant motion estimation and compensation in wavelet domain video compression

The contributions of this dissertation are in the development of two new interrelated approaches to video data compression: (1) A level-refined motion estimation and subband compensation method for the effective motion estimation and motion compensation. (2) A shift-invariant sub-decimation decomposition method in order to overcome the deficiency of the decimation process in estimating motion due to its shift-invariant property of wavelet transform. ^ The enormous data generated by digital videos call for an intense need of efficient video compression techniques to conserve storage space and minimize bandwidth utilization. The main idea of video compression is to reduce the interpixel redundancies inside and between the video frames by applying motion estimation and motion compensation (MEMO) in combination with spatial transform coding. To locate the global minimum of the matching criterion function reasonably, hierarchical motion estimation by coarse to fine resolution refinements using discrete wavelet transform is applied due to its intrinsic multiresolution and scalability natures. ^ Due to the fact that most of the energies are concentrated in the low resolution subbands while decreased in the high resolution subbands, a new approach called level-refined motion estimation and subband compensation (LRSC) method is proposed. It realizes the possible intrablocks in the subbands for lower entropy coding while keeping the low computational loads of motion estimation as the level-refined method, thus to achieve both temporal compression quality and computational simplicity. ^ Since circular convolution is applied in wavelet transform to obtain the decomposed subframes without coefficient expansion, symmetric-extended wavelet transform is designed on the finite length frame signals for more accurate motion estimation without discontinuous boundary distortions. ^ Although wavelet transformed coefficients still contain spatial domain information, motion estimation in wavelet domain is not as straightforward as in spatial domain due to the shift variance property of the decimation process of the wavelet transform. A new approach called sub-decimation decomposition method is proposed, which maintains the motion consistency between the original frame and the decomposed subframes, improving as a consequence the wavelet domain video compressions by shift invariant motion estimation and compensation. ^

Urban Education Research: A Paradigm Shift

Significantly due to the institutional separation of theory and practice, the gap between academia and society continues to broaden, arguably pointing towards the failure of traditional educational research and, to an extent, the university’s neglect to authenticate alternate epistemologies and methodologies that seek to elicit mobilization, activism, and reform.

Righe spettrali: formazione, shift, allargamento

L'analisi degli spetti astronomici ci fornisce informazioni cruciali per la comprensione degli oggetti astrofisici che li generano. In questo breve elaborato, si analizzano i processi fisici a livello microscopico che portano alla loro formazione, i meccanismi per i quali le righe subiscono uno shift, e quelli per cui il loro profilo viene modificato. Infine, si approfondiscono alcuni esempi astrofisici di spettri.

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.

Weighted mean depth of zooplankton measured during various cruises to the Baltic Sea

The Baltic Sea is the largest brackish water area of the world. On the basis of the data from 16 cruises, we show the seasonal and vertical distribution patterns of the appendicularians Fritillaria borealis, Oikopleura dioica and the cyclopoid copepod Oithona similis, in the highly stratified Bornholm Basin. These species live at least temporarily below the permanent halocline and use different life strategies to cope with the brackish environment. The cold-water species F. borealis is abundant in the upper layers of the water column before the thermocline develops. With the formation of the thermocline abundance decreases and the specimens outlast higher temperatures below the halocline. Distribution and strategy suggest that F. borealis might be a glacial relict species in the Baltic Sea. Although Oikopleura dioica is only abundant during summer, O. similis is present all year round. Both species have in common that their vertical distribution is restricted to the waters below the halocline, most likely due to their requirements of higher salinities. We argue that the observed strategies are determined by ecophysiological constraints and life history traits. These species share an omnivorous feeding behaviour and the capability to utilise a spectra of small particles as food. As phytoplankton concentration is negligible below the halocline, we suggest that these species feed on organic material and heterotrophic organisms that accumulate in the density gradient of the halocline. Therefore, the deep haline waters in the Baltic Sea represent a habitat providing shelter from predation and food supply for adapted species that allows them to gather sufficient resources and to maintain populations.

The spectra of linear fractional composition operators on weighted Dirichlet spaces

We completely determine the spectra of composition operators induced by linear fractional self-maps of the unit disc acting on weighted Dirichlet spaces; extending earlier results by Higdon [8] and answering the open questions in this context.

Paradigm shift in determining Neoproterozoic atmospheric oxygen

ACKNOWLEDGMENTS We thank the Geological Survey of Australia for permission to sample the Empress 1A and Lancer 1 cores, the Natural Sciences and Engineering Research Council of Canada for financial support (grant #7961–15) of U. Brand, and the National Natural Science Foundation of China for support of F. Meng and P. Ni (grants 41473039 and 4151101015). We thank M. Lozon (Brock University) for drafting and constructing the figures. We thank the editor, Brendan Murphy, as well as three reviewers (Steve Kesler, Erik Sperling, and an anonymous reviewer), for improving the manuscript into its final form ©The Authors Gold Open Access: This paper is published under the terms of the CC-BY license.

Latitudinal shift in thermal niche breadth results from thermal release during a climate-mediated range expansion

Funded by Biodiversity and Ecosystem Services in a Changing Climate Wenner-Gren Foundation Swedish Research Council The Royal Swedish Academy of Sciences Stiftelsen Anna-Greta Holger Crafoords Fund The Crafoord Foundation

Latitudinal shift in thermal niche breadth results from thermal release during a climate-mediated range expansion

Funded by Biodiversity and Ecosystem Services in a Changing Climate Wenner-Gren Foundation Swedish Research Council The Royal Swedish Academy of Sciences Stiftelsen Anna-Greta Holger Crafoords Fund The Crafoord Foundation

Latitudinal shift in thermal niche breadth results from thermal release during a climate-mediated range expansion

Funded by Biodiversity and Ecosystem Services in a Changing Climate Wenner-Gren Foundation Swedish Research Council The Royal Swedish Academy of Sciences Stiftelsen Anna-Greta Holger Crafoords Fund The Crafoord Foundation

Automata and men : the shift towards a human ideal in the fiction of Wyndham Lewis

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Weighted finite-state transducers in speech recognition : a compaction algorithm for non-determinizable transducers

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Weighted nucleoli and dually essential coalitions

We consider linearly weighted versions of the least core and the (pre)nucleolus and investigate the reduction possibilities in their computation. We slightly extend some well-known related results and establish their counterparts by using the dual game. Our main results imply, for example, that if the core of the game is not empty, all dually inessential coalitions (which can be weakly minorized by a partition in the dual game) can be ignored when we compute the per-capita least core and the per-capita (pre)nucleolus from the dual game. This could lead to the design of polynomial time algorithms for the per-capita (and other monotone nondecreasingly weighted versions of the) least core and the (pre)nucleolus in specific classes of balanced games with polynomial many dually esential coalitions.

Can mean shift trackers perform better?

Many tracking algorithms have difficulties dealing with occlusions and background clutters, and consequently don't converge to an appropriate solution. Tracking based on the mean shift algorithm has shown robust performance in many circumstances but still fails e.g. when encountering dramatic intensity or colour changes in a pre-defined neighbourhood. In this paper, we present a robust tracking algorithm that integrates the advantages of mean shift tracking with those of tracking local invariant features. These features are integrated into the mean shift formulation so that tracking is performed based both on mean shift and feature probability distributions, coupled with an expectation maximisation scheme. Experimental results show robust tracking performance on a series of complicated real image sequences. © 2010 IEEE.