μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Relative abundances of planktonic foraminifera from surface sediments of the Drake Passage, Southern Ocean (Table 1)

Based on a qualitative and quantitative evaluation of Recent sediments samples (top 3 cm of cores as well as Petersen grab samples) from the Drake Passage, between South America and Antarctica, the distribution of planktonic foraminifera and their relation to oceanographic conditions was investigated. The Antarctic Convergence - the northern limit of the cold Antarctic Surface Water - is shown to be of major importance in controlling the distributional pattern of planktonic species as well as their total numbers. South of the convergence, Globigerina pachyderma is usually the only species found in the sediment. It occurs with abundances not greater than 6000 per gram dry sediment, and at most stations less than 100 specimens per gram of dry sediment were recovered. At a number of deep-sea stations below 3700 m depth approx. no planktonic foraminifera were found at all. It is most probable, that at least some of these stations are located below the limit of CaCO3 dissolution. North of the Antarctic Convergence planktonic foraminiferal numbers are much higher and range from 1800 to 120000 per gram of dry sediment. Eight species are the major constituents of the population: Globigerina pachyderma, Globigerina bulloides, Globogerina quinqueloba, Globigerina inflata, Globorotalia truncatolinoides, Globorotalia scitula, Globigerinita glutinata and Globigerinita uvula. The widespread occurrence of Globorotalia truncatulinoides, which in the northern hemisphere is usually a subtropical form, is especially noteworthy. Another Globigerina, morphologically similar to G. pachyderma, has been recognized frequently north of the Antarctic Convergence. Globigerina megastoma which has its type area in the Drake Passage, has been found only rarely. Orbulina universa occurs in samples from the areas of higher water temperature around the South American Continent. Globigerina pachyderma is predominantly sinistrally coiled throughout the area investigated, but a slight increase in the percentage of dextrally coiled specimens may be noticed with increasing water temperature, i.e. from south to north.

Facilitating soil-and plant-water research through the use of TDR

The development of TDR for measurement of soil water content and electrical conductivity has resulted in a large shift in measurement methods for a breadth of soil and hydrological characterization efforts. TDR has also opened new possibilities for soil and plant research. Five examples show how TDR has enhanced our ability to conduct our soil- and plant-water research. (i) Oxygen is necessary for healthy root growth and plant development but quantitative evaluation of the factors controlling oxygen supply in soil depends on knowledge of the soil water content by TDR. With water content information we have modeled successfully some impact of tillage methods on oxygen supply to roots and their growth response. (ii) For field assessment of soil mechanical properties influencing crop growth, water content capability was added to two portable soil strength measuring devices; (a) A TDT (Time Domain Transmittivity)-equipped soil cone penetrometer was used to evaluate seasonal soil strengthwater content relationships. In conventional tillage systems the relationships are dynamic and achieve the more stable no-tillage relationships only relatively late in each growing season; (b) A small TDR transmission line was added to a modified sheargraph that allowed shear strength and water content to be measured simultaneously on the same sample. In addition, the conventional graphing procedure for data acquisition was converted to datalogging using strain gauges. Data acquisition rate was improved by more than a factor of three with improved data quality. (iii) How do drought tolerant plants maintain leaf water content? Non-destructive measurement of TDR water content using a flat serpentine triple wire transmission line replaces more lengthy procedures of measuring relative water content. Two challenges remain: drought-stressed leaves alter salt content, changing electrical conductivity, and drought induced changes in leaf morphology affect TDR measurements. (iv) Remote radar signals are reflected from within the first 2 cm of soil. Appropriate calibration of radar imaging for soil water content can be achieved by a parallel pair of blades separated by 8 cm, reaching 1.7 cm into soil and forming a 20 cm TDR transmission line. The correlation between apparent relative permittivity from TDR and synthetic aperture radar (SAR) backscatter coefficient was 0.57 from an airborne flyover. These five examples highlight the diversity in the application of TDR in soil and plant research.

Towards pattern-based design recovery

A method and a corresponding tool is described which assist design recovery and program understanding by recognising instances of design patterns semi-automatically. The approach taken is specifically designed to overcome the existing scalability problems caused by many design and implementation variants of design pattern instances. Our approach is based on a new recognition algorithm which works incrementally rather than trying to analyse a possibly large software system in one pass without any human intervention. The new algorithm exploits domain and context knowledge given by a reverse engineer and by a special underlying data structure, namely a special form of an annotated abstract syntax graph. A comparative and quantitative evaluation of applying the approach to the Java AWT and JGL libraries is also given.

What difference a writing centre makes:a small scale study

Purpose – Academic writing is often considered to be a weakness in contemporary students, while good reporting and writing skills are highly valued by graduate employers. A number of universities have introduced writing centres aimed at addressing this problem; however, the evaluation of such centres is usually qualitative. The paper seeks to consider the efficacy of a writing centre by looking at the impact of attendance on two “real world” quantitative outcomes – achievement and progression. Design/methodology/approach – Data mining was used to obtain records of 806 first-year students, of whom 45 had attended the writing centre and 761 had not. Findings – A highly significant association between writing centre attendance and achievement was found. Progression to year two was also significantly associated with writing centre attendance. Originality/value – Further, quantitative evaluation of writing centres is advocated using random allocation to a comparison condition to control for potential confounds such as motivation.

The factors affecting the optimal performance of eddy-current machines

This thesis presents an examination of the factors which influence the performance of eddy-current machines and the way in which they affect optimality of those machines. After a brief introduction to the types of eddy-current machine considered, the applications to which these machines are put are examined. A list of parameters by which to assess their performance is obtained by considering the machine as part of a system. in this way an idea of what constitutes an optimal machine is obtained. The third chapter then identifies the factors which affects the performance and makes a quantitative evaluation of the effect. Here the various alternative configurations and components are compared with regard to their influence on the mechanical, electromagnetic, and thermal performance criteria of the machine. Chapter four contains a brief review of the methods of controlling eddy-current machines by electronic methods using thyristors or transistors as the final control element. Where necessary, the results of previous workers in the field of electrical machines have been extended or adapted to increase the usefulness of this thesis.

Melamine phosphate as a component of intumescent coatings

Melamine orthophosphate has been shown to exhibit variations in its chemical constitution, and crystal shape and size, dependent upon the method of production. These crystal types have been incorporated with epoxy resin to produce intumescent coatings, which have been tested on a small scale fire testing device, designed and calibrated within this project. The factors influencing performance in three fire test regimes are the percentage loading of melamine phosphate, its chemical constitution, crystal size and shape, thermal degradation, and state of agglomeration . and dispersion in the coating, determined by the method of incorporation into the coating. When melamine phosphate is heat treated at 210ºC, a process designed to reduce its solubility, the performance of coatings produced with such material is profoundly affected, depending mainly on crystal size and shape alone. Consideration of heat transfer across the chars produced has allowed a quantitative evaluation of the thermal resistance of chars throughout a test. An optimum production route for melamine phosphate has been suggested, taking into account the requirements for weatherability of coatings as well as performance in a fire.

Multiview photometric stereo

This paper addresses the problem of obtaining complete, detailed reconstructions of textureless shiny objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under changing illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint but produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object's visual hull. This is then used to recover the illumination and initialize a multiview photometric stereo scheme to obtain a closed surface reconstruction. There are two main contributions in this paper: First, we describe a robust technique to estimate light directions and intensities and, second, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and, hence, allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with complete reconstructions of challenging real objects. Finally, we show experimentally how, even in the case of highly textured objects, this technique can greatly improve on correspondence-based multiview stereo results.

Characterization of tissue transglutaminase in human osteoblast-like cells

Tissue transglutaminase (tTG) is a calcium-dependent and guanosine 5'-triphosphate (GTP) binding enzyme, which catalyzes the post-translational modification of proteins by forming intermolecular ε(ϒ-glutamyl)lysine cross-links. In this study, human osteoblasts (HOBs) isolated from femoral head trabecular bone and two osteosarcoma cell lines (HOS and MG-63) were studied for their expression and localization of tTG. Quantitative evaluation of transglutaminase (TG) activity determined using the [1,414C]-putrescine incorporation assay showed that the enzyme was active in all cell types. However, there was a significantly higher activity in the cell homogenates of MG-63 cells as compared with HOB and HOS cells (p <0.001). There was no significant difference between the activity of the enzyme in HOB and HOS cells. All three cell types also have a small amount of active TG on their surface as determined by the incorporation of biotinylated cadaverine into fibronectin. Cell surface-related tTG was further shown by preincubation of cells with tTG antibody, which led to inhibition of cell attachment. Western blot analysis clearly indicated that the active TG was tTG and immunocytochemistry showed it be situated in the cytosol of the cells. In situ extracellular enzyme activity also was shown by the cell-mediated incorporation of fluorescein cadaverine into extracellular matrix (ECM) proteins. These results clearly showed that MG-63 cells have high extracellular activity, which colocalized with the ECM protein fibronectin and could be inhibited by the competitive primary amine substrate putrescine. The contribution of tTG to cell surface/matrix interactions and to the stabilization of the ECM of osteoblast cells therefore could by an important factor in the cascade of events leading to bone differentiation and mineralization.

A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

Ferramenta para avaliação e inferência de parâmetros de redes industriais sem fio

Wireless sensor networks (WSN) have gained ground in the industrial environment, due to the possibility of connecting points of information that were inaccessible to wired networks. However, there are several challenges in the implementation and acceptance of this technology in the industrial environment, one of them the guaranteed availability of information, which can be influenced by various parameters, such as path stability and power consumption of the field device. As such, in this work was developed a tool to evaluate and infer parameters of wireless industrial networks based on the WirelessHART and ISA 100.11a protocols. The tool allows quantitative evaluation, qualitative evaluation and evaluation by inference during a given time of the operating network. The quantitative and qualitative evaluation are based on own definitions of parameters, such as the parameter of stability, or based on descriptive statistics, such as mean, standard deviation and box plots. In the evaluation by inference uses the intelligent technique artificial neural networks to infer some network parameters such as battery life. Finally, it displays the results of use the tool in different scenarios networks, as topologies star and mesh, in order to attest to the importance of tool in evaluation of the behavior of these networks, but also support possible changes or maintenance of the system.

Metodologia para análise da dependabilidade de Smart Grids

Smart Grids are a new trend of electric power distribution, the future of current systems. These networks are continually being introduced in order to improve the reliability of systems, providing alternatives to energy supply and cost savings. Faced with increasing electric power grids complexity, the energy demand and the introduction of alternative sources to energy generation, all components of system require a fully integration in order to achieve high reliability and availability levels (dependability). The systematization of a Smart Grid from the Fault Tree formalism enable the quantitative evaluation of dependability of a specific scenario. In this work, a methodology for dependability evaluation of Smart Grids is proposed. A study of case is described in order to validate the proposal. With the use of this methodology, it is possible to estimate during the early design phase the reliability, availability of Smart Grid beyond to identify the critical points from the failure and repair distributions of components.

Single-cell functional analysis of parathyroid adenomas reveals distinct classes of calcium sensing behaviour in primary hyperparathyroidism.

Primary hyperparathyroidism (PHPT) is a common endocrine neoplastic disorder caused by a failure of calcium sensing secondary to tumour development in one or more of the parathyroid glands. Parathyroid adenomas are comprised of distinct cellular subpopulations of variable clonal status that exhibit differing degrees of calcium responsiveness. To gain a clearer understanding of the relationship among cellular identity, tumour composition and clinical biochemistry in PHPT, we developed a novel single cell platform for quantitative evaluation of calcium sensing behaviour in freshly resected human parathyroid tumour cells. Live-cell intracellular calcium flux was visualized through Fluo-4-AM epifluorescence, followed by in situ immunofluorescence detection of the calcium sensing receptor (CASR), a central component in the extracellular calcium signalling pathway. The reactivity of individual parathyroid tumour cells to extracellular calcium stimulus was highly variable, with discrete kinetic response patterns observed both between and among parathyroid tumour samples. CASR abundance was not an obligate determinant of calcium responsiveness. Calcium EC50 values from a series of parathyroid adenomas revealed that the tumours segregated into two distinct categories. One group manifested a mean EC50 of 2.40 mM (95% CI: 2.37-2.41), closely aligned to the established normal range. The second group was less responsive to calcium stimulus, with a mean EC50 of 3.61 mM (95% CI: 3.45-3.95). This binary distribution indicates the existence of a previously unappreciated biochemical sub-classification of PHPT tumours, possibly reflecting distinct etiological mechanisms. Recognition of quantitative differences in calcium sensing could have important implications for the clinical management of PHPT.

Hyperspectral Image Classification with Nonlinear Methods

This thesis introduces two related lines of study on classification of hyperspectral images with nonlinear methods. First, it describes a quantitative and systematic evaluation, by the author, of each major component in a pipeline for classifying hyperspectral images (HSI) developed earlier in a joint collaboration [23]. The pipeline, with novel use of nonlinear classification methods, has reached beyond the state of the art in classification accuracy on commonly used benchmarking HSI data [6], [13]. More importantly, it provides a clutter map, with respect to a predetermined set of classes, toward the real application situations where the image pixels not necessarily fall into a predetermined set of classes to be identified, detected or classified with.

The particular components evaluated are a) band selection with band-wise entropy spread, b) feature transformation with spatial filters and spectral expansion with derivatives c) graph spectral transformation via locally linear embedding for dimension reduction, and d) statistical ensemble for clutter detection. The quantitative evaluation of the pipeline verifies that these components are indispensable to high-accuracy classification.

Secondly, the work extends the HSI classification pipeline with a single HSI data cube to multiple HSI data cubes. Each cube, with feature variation, is to be classified of multiple classes. The main challenge is deriving the cube-wise classification from pixel-wise classification. The thesis presents the initial attempt to circumvent it, and discuss the potential for further improvement.