Miracle-dz/UniFAR-FTUs huggingface dataset:
Autocalibration of sparse images for Structure from Motion and 3D reconstruction

Autocalibration of sparse images for Structure from Motion and 3D Reconstruction This PhD thesis is about the estimation of calibration parameters for images one would like to use with standard algorithms of Structure from Motion (SfM) and 3D reconstruction from image feature correspondences, namely the focal length and the distortion model. In the eld of Structure from Motion and 3D reconstruction from images, the usual approach consists of a sequence of steps, each of which produces a set of data to the next one. In sum, the classical pipeline will normally base itself on rst detecting visual features on the available images, then identifying point correspondences in image pairs and then computing the relative pose of the cameras and the coordinates of the corresponding triangulated points in 3D space from the point matches. Most times, multiple images of the scene will be available, so systems will have ways of aggregating data from multiple images in a single reconstruction. The computation of the relative camera poses is normally achieved by computing the essential matrix relating two images. However, for the computation of the essential matrix between two images, one must know or at least have a good estimate for the calibration information of the cameras that captured the images in the rst place. A lot of the work in this eld in recent years has targeted the use of the enormous amount of shared image online as a source of data for Structure from Motion pipelines. It is often easy to assemble large datasets of images of a given landmark through searches in online image sharing platforms. Some of those images include calibration information in the form of EXIF tags embedded in the image les by most modern digital cameras, but most available image les do not actually include this data for various reasons. Images without focal length information are usually discarded by Structure fromMotion pipelines. Distortion parameters are usually never available in this scenario, and often distortion may just be neglected while still getting a reasonable model. However including distortion compensation may often contribute to achieve a better model of the scene, especially if distortion is considerable. This thesis addresses the estimation of calibration parameters when they are not available, so that additional images may be included in the 3D reconstruction of a given scene, and a better model may be obtained. The approach is to take advantage of known (or a good approximation of) calibration information of some of the images of the scene one seeks to reconstruct, to estimate calibration information of uncalibrated views of the same scene, so that a better reconstruction may be achieved. By taking advantage of
MODELING AND FORECASTING DISPLACEMENTS IN CONCRETE DAM : AN ARDL BOUNDS TESTING APPROACH

In this paper is carried out modeling and forecasting of horizontal displacement, in the direction of flow, of a concrete block of Itaipu Hydroelectric Power Plant based on measurements of the direct pendulum and considering the influence of temperature variation and variation reservoir level. The methodology involves the Autoregressive Distributed Lags Model (ARDL) and the Bounds Testing approach Pesaran et al. (2001), which has some advantages over conventional cointegration tests when the time series is stationary (I(0)) and/or integrated of order one (I(1)). The main objective is to present a model for prediction of displacements providing a contribution to the technicians and engineers in decision-making with respect to the monitoring of this block. The Eviews software was used to estimate the model parameters. The analysis confirms the existence of a long-run relationship between the variables. It evaluated correct model specification, independence, normality and homoscedasticity of the residuals and, finally, the stability of the model, as well, the model could be used for prediction purposes. Accuracy measurements RMSE and MAPE were calculated and confidence intervals were built.
Diurnal and sub-diurnal oscillations in GPS coordinates

This paper presents the results of the frequency and time-frequency analyses of the coordinates of permanent GPS sites obtained from short-time solutions. The aim was to estimate the usefulness of GPS observations for the short-period geodynamical studies, and check how tidal models in Bernese fit to individual sites conditions. This study shows that East-West component is noisier than North-South and the East-West oscillations have greater energy, this can be the influence of using short-time solutions. There are some oscillation in tidal frequency on few of analysed sites coordinates. These oscillations could be explained by the residual ocean tidal loading effect. More detailed description of the observed oscillations needs further studies on the method of precise coordinates determination with sub-daily sampling rate. The paper contains preliminary results of analyses on the short-time GNSS solutions conducted in the Centre of Applied Geomatics of the Warsaw Military University of Technology.
COPD exacerbations: impact and prevention

Educational aims To describe the impact of COPD exacerbations and the importance of the frequent exacerbator phenotype. To describe the spectrum of pharmacological and non-pharmacological interventions that reduce exacerbation frequency and severity. To discuss the role of novel interventions, such as long term macrolide use and dual bronchodilatation, in COPD exacerbation prevention. Summary Exacerbations are key events for patients with chronic obstructive pulmonary disease (COPD). Exacerbations drive health status and contribute to disease progression and exacerbation prevention is a key goal of therapy in COPD. The majority of COPD exacerbations are triggered by respiratory viral infections and/or bacterial infections. Some patients are especially susceptible to frequent exacerbations and these patients need to be targeted for preventative therapy. A number of pharmacological therapies exist that can prevent COPD exacerbations and reduce hospital admissions. Non-pharmacological interventions for exacerbation prevention include pulmonary rehabilitation, long-term oxygen therapy and home noninvasive ventilator support, though the evidence base for these is less well developed. Improved management of the acute exacerbation will also prolong the time to the next exacerbation event.
Mining Literal Correlation Rules from Itemsets

Nowadays, data mining tools are becoming more and more popular to extract knowledge from a huge volume of data. In this paper, our aim is to extract Literal Correlation Rules: Correlation Rules admitting literal patterns given a set of items and a binary relation. If a pattern represents a valid Correlation Rule, then any literal belonging to its Canonical Base represents a valid Literal Correlation Rule. Moreover, in order to highlight only relevant Literal Correlation Rules, we add a pruning step based on a support threshold. To extract such rules, we modify the LHS-CHI2 Algorithm and perform some experiments.
dieta Insulin homeostasis , energy metabolism and body composition – dietary macronutrients ’ effect

ANA CAROLINA PINHEIRO VOLP1; HELEN HERMANA MIRANDA HERMSDORFF2; JOSEFINA BRESSAN3 1Especialista em Terapia NutricionalUniversidade Federal do Paraná (UFPR). Mestre em Ciência da NutriçãoUniversidade Federal de Viçosa (UFV). Doutoranda em Ciência e Tecnologia dos Alimentos (UFV) 2Mestre em Ciência da NutriçãoDepartamento de Nutrição e Saúde (UFV). 3Josefina Bressan PhD. Professora AdjuntoDepartamento de Nutrição e Saúde (UFV). Endereço para correspondência: Ana Carolina Pinheiro Volp Campus Universitário Departamento de Nutrição e Saúde (UFV) CEP 36571-000, Viçosa, MG E-mail: anavolp@gmail.com Agradecimentos: À Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG) e à Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) pelo apoio financeiro e pelo incentivo à pesquisa. VOLP, A. C. P.; HERMSDORFF, H. H. M. ; BRESSAN, J. Insulin homeostasis,
Chapter 2 Application-Specific Multi-Threaded Dynamic Memory Management

This chapter presents the methodology and the corresponding software framework developed to systematically explore the design space of Multi-Threaded Dynamic Memory Management (MTh-DMM). We developed two exploration approaches: (a) a two-phase constraint-orthogonal and (b) a single-phase aggressive exploration methodologies. Pareto optimal configurations are generated considering various design targets. Experimental results evaluate the solution quality delivered by the proposed exploration approaches and by state-of-the art general purpose dynamic memory management solutions, based on a real-life multi-threaded network application.
Adaptação do Rapid Serial Visual Presentation - RSVP- para as investigações de leitura de textos com sinc ronização dos estímulos auditivo e visual

The Serial Rapid Visual Presentation (RSVP) develop ed for Foster (1970). It's one technique used in the presentation of texts in studies on reading. It consists of the successive presentation of words written in a fixed point of a screen, with fast exposition of the word . However, it is not applied in the inquiries that associate auditory and visual stimulus. In this work we consider some adaptations in the RSVP to synchroniz e auditory and visual stimulus, without losing of sight the effectiveness of the speed of presentation of this technique.
Modelling the Dependability of Free and Open Source Software : A Quantitative Approach

The increasing popularity and adoption of Free and Open Source Software (F/OSS) has fostered heated debates about the dependability of software developed in such an open, highly distributed context. Claims are made in favour of and against F/OSS as a viable alternative to proprietary software. Due to the complex nature of software dependability, and the large number of interacting factors involved, a wider systemic view is required to produce more defensible claims regarding dependability. In this paper, we propose a quantitative approach based on system dynamics to validate stated claims about F/OSS dependability. We sketch a first attempt towards a computer simulation model to test different hypotheses by using empirical data. The model applicability is demonstrated by an illustrative example; the preliminary results obtained are comparable to data reported in the literature. The example supports our belief in the validity of the system dynamics approach as a testing vehicle to explain observed phenomena and support or disprove argued hypotheses. The model is also useful for predicting future behaviour of F/OSS development projects.
Major Qualifying Projects ( All Years ) Major Qualifying Projects April 2016 Automatic Contact Surface Detection

Motion planners for humanoid robots search the space of all possible contacts the robot can make with its environment. In order to define this space, it is necessary to define all available surfaces in the environment with which the robot may make contact. We introduce a method to automatically detect these surfaces in real time, enabling humanoid robot motion planners to operate in any environment without requiring costly manual pre-processing. The system maintains a set of known planar surfaces, expressed as two dimensional polygons, and detects new surfaces and new areas of existing surfaces as the robot moves through the environment. The only required inputs are data from commonly available sensors and a small set parameters which depend only on the characteristics of the robot and sensor. No advance knowledge of the environment is necessary. In real-world environments, Surface Detection detects an initial set of surfaces within 1.5 seconds, and the average time to detect a newly-visible surface is less than two seconds. The system is capable of detecting all planar surfaces in a real-world environment and providing them to a motion planner in real time.
Preliminary Study on The Reduction of Mercury Content in Steam Coal by Using a Pneumatic Vibrating Concentrating Table

Mercury content in hard coal is relatively small. However, considering the large amounts of coal burned in Poland, considerable quantities of mercury are released to the atmosphere. Mercury occurs mainly in pyrite and marcasite included in mineral matter in coal, but it is also present in coal organic matter. Certain, sometimes substantial, amounts of mercury are found in the roof and bottom layers of coal fields, which pass to run-of-mine coal in the mining process. It is possible to remove impurities with gangue coming from these layers and impurities originating from stone inserts in coal fields. It is also possible to remove the liberated iron sulphide particles. But, as practice shows, wet enrichment methods (jigging, flotation) are often imprecise. The concentrates contain certain amounts of gangue and sulphur compounds which results in the passing mercury compounds to commercial products. The Katowice Branch if the Institute of Mechanized Construction and Rock Mining has been conducting research on method for deshaling of dry run-of-mine for several years. In the study a system equipped with a pneumatic vibrating concentrating table was used. The system, when properly adjusted, allows effective removal of these contaminants. It is therefore possible to deshale the excavated material and also to remove mercury compounds occurring in the high density fractions. This article discusses the sources and emissions of mercury, its content in hard coal and legal considerations regarding mercury emissions. Also presented are the preliminary results of research on mercury removal using a pneumatic vibrating concentrating table.
Geometric abstractions for information processing in sensor networks

Computerized devices are becoming smaller and more ubiquitous. Equally importantly, they are becoming more interconnected. A Sensor Network is a model for such interconnected systems. Each sensor device obtains and stores information that is potentially useful to others. The challenge is to efficiently search and deliver the important information to the relevant parties. Given the large number of devices and corresponding quantities of data, this is not easy. Fortunately for us, communication is efficient and fast when addressing nearby devices. This permits us to utilize their relative locations to construct efficient methods. The proximity and location information can be leveraged through the use of geometry. The complexity of a network and data hide simpler geometric structures that are not obvious at first sight. The objective in this dissertation is to identify such concealed structures that can be useful and can be computed in the network. An abstract structure or abstraction helps us to understand and represent the network and data in more convenient ways. This approach is useful in managing the data in the network, as well as in managing the network itself. Its utility is demonstrated through accompanying algorithms in each part of the dissertation.
Sprituality and resilience effects on employee awareness and engagement in csr: an overview and research agenda

As an individual, employee is the main organisation stakeholder who is also recognised as an asset, internal customer and the organisation representative. Their participation and proactive support is crucial to organisation's CSR practices. Their CSR awareness is a process of observation; retention and imitation of the organisational CSR practices into the motivation to demonstrate it as their personal engagement in CSR practices. However, a little is known about the linkage between employee CSR awareness and their engagement in CSR as earlier researches are more focus on organisation CSR awareness and its influence on employee engagement. This research hypothesizes the significant underlying influence of individual spirituality and resilience that interplays as mediator and moderator to the relationship between individual awareness and engagement in CSR.
PERFORMANCE OF PREMIUM SERVICE IN QOS IP NETWORK

The QoS IP network concept is presently under definition and testing phase. The objective of this network is to provide a variety of communication services to meet multi-service network requirements, as it was effectively made in the case of ATM. This paper investigates, so called, Premium service defined inside the DiffServ architecture and designated for streaming-oriented applications, like audio or video based. The Premium service should guarantee low packet delay as well as low packet losses. Two approaches for providing this service in the network are considered, which are based on PQ (Priority Queuing) or WFQ (Weighted Fair Queuing) schedulers. Their performances are compared in term of such parameters as maximum jitter, mean packet delay and packet loss ratio. A simplified analysis of Premium service is also included.
Box-Counting Dimension and Beyond

This paper explores different analytical and computational methods of computing the box-counting dimension of a fractal-like set, such as the attractor associated with a chaotic dynamical system. Because attractors cannot be described exactly, but can only be approximated by computational methods, the box-counting dimension is typically measured computationally. Using alternative measures of chaotic behavior, such as the Lyapunov exponents, it is possible to estimate the accuracy of a computational approximation. The box-counting dimension definition is extended to include subsets of regular subspaces of R∞. These sets include products of Cantor sets and attractors associated with infinite dimensional dynamical systems, such as the Kot-Schaffer model. Computational approaches to computing the box-counting dimension of the Kot-Schaffer attractor are discussed and the results for this attractor are discussed.
Chapter 2 All Relevant Feature Selection Methods and Applications

All-relevant feature selection is a relatively new sub-field in the domain of feature selection. The chapter is devoted to a short review of the field and presentation of the representative algorithm. The problem of all-relevant feature selection is first defined, then key algorithms are described. Finally the Boruta algorithm, under development at ICM, University of Warsaw, is explained in a greater detail and applied both to a collection of synthetic and real-world data sets. It is shown that algorithm is both sensitive and selective. The level of falsely discovered relevant variables is low—on average less than one falsely relevant variable is discovered for each set. The sensitivity of the algorithm is nearly 100% for data sets for which classification is easy, but may be smaller for data sets for which classification is difficult, nevertheless, it is possible to increase the sensitivity of the algorithm at the cost of increased computational effort without adversely affecting the false discovery level. It is achieved by increasing the number of trees in the random forest algorithm that delivers the importance estimate in Boruta.
Distortion Invariant Feature Extraction with Echo State Networks

In complex pattern recognition tasks data usually exhibits many local distortions which significantly disturb the recognition process. A method for extracting temporal features from a signal that are invariant to these distortions is presented in this report. The idea is to use Echo State Network to generate a rich high-dimensional representation of data. Temporal features are then extracted by finding projections of the high-dimensional representation that are minimally influenced by the selected distortions while still carrying most of the information about the underlying signal required for the performed task. The algorithm performance is analyzed on synthetic signals as well as on high-dimensional handwriting data for shift and scale distortions. It is shown that the algorithm is capable to extract a low dimensional feature set from a reservoir which is invariant to the selected distortions and relevant to the performed task.
8. MATHEMATICAL MODELS OF HEMATOPOIETIC CELL REPLICATION AND CONTROL

The biological sciences offer an abundance of examples in which the dynamics are dependent on the past history of the system being studied. In the attempt to construct mathematical models for these processes, the dynamic equations are often framed either as functional equations or, more specifically, as differential delay equations. Often by studying the solution behavior of these model systems one can begin to understand the normal biological responses noted in the laboratory. Even more interesting are those clinical situations in which the normal dynamics of a system are replaced, in disease situations, by dynamics with different characteristics. Sometimes these characteristics involve the destabilization of a steady state in favor of periodic or aperiodic behavior, or the replacement by a new periodic regime of the normal periodic one. Such diseases are called “periodic diseases” (Glass and Mackey 1988; Mackey and Glass 1977; Reimann 1963) and are quite interesting in that they can often give clues about the nature of the underlying disease expressed as a shift in parameters giving rise to a bifurcation. Some of the most fascinating of these periodic diseases are the periodic diseases of the blood (periodic hematological diseases). It has long been suspected that periodic hematological diseases arise because of abnormalities in the feedback mechanisms which regulate blood-cell number (Dunn 1983; Kirk et al. 1968; Mackey 1978; Mackey 1979b; Mackey 1979a; Morley 1979; Wichmann and Loeffler 1988). Indeed this observation has provided a major impetus for mathematicians to determine the conditions for oscillation onset in these mechanisms. There have been two surprising predictions of these studies (Glass and Mackey 1979; Mackey and Glass 1977): (1) qualitative changes can occur in blood-cell dynamics as quantitative changes are made in feedback control; and (2) under appropriate conditions, these feedback mechanisms can produce aperiodic, irregular fluctuations (“chaotic” in the current vernacular) which could easily be mistaken for noise and/or experimental error (Bai-Lin 1984; Degn et al. 1987; Glass and Mackey 1988). The clinical significance is that it may be possible to develop new diagnostic and therapeutic strategies based on manipulation of feedback (Glass and Mackey 1979; Glass and Mac-
Coding of Auditory Information into Nerve-Action Potentials

Neuronal sound processing requires compression of the huge dynamic range of acoustical signals to the limited range which can be coded by neurons. Here we present a compressive inner ear model followed by a realistic inner hair cell model. Spike trains transmitted by the auditory nerve fibers allow for spectral, temporal and spatial information processing, which is required for robust speech recognition, especially in noisy environments.
Mise au point Échocardiographie-Doppler chez le petit animal Echocardiographic and cardiac Doppler in small animals

New echo-Doppler equipment with high frame rate and high frequency transducer recently permits to analyse hemodynamics in small animals such rabbits, rats and mice. We and other validated these techniques in comparison with invasive gold standard techniques. Acute or long term follow-up is now possible using these non invasive methods in animal models of human acute disease such shock, ARDS as well as chronic disease as hypertension, and may help for a better understanding of them. © 2003 Publié par Elsevier SAS pour Société de réanimation de langue française. Mots clés : Échocardiographie ; Doppler ; Petits animaux ; Souris ; Rats ; Lapins ; Hémodynamique