Miracle-dz/UniFAR-FTUs huggingface dataset:
The design of a robust 3D Reconstruction system for video sequences in non controlled environments

Along this thesis, a novel and robust approach for obtaining 3D models from video sequences captured with hand-held cameras is adressed. This work defines a fully automatic pipeline that is able to deal with diferent types of sequences and acquiring devices. The designed and implemented system follows a divide and conquer approach. An smart frame decimation process reduces the temporal redundancy of the input video sequence and selects the best conditioned frames for the reconstruction step. Next, the video is split into overlapped clips with a fixed and small number of Key-frames. This allows to parallelize the Structure and Motion process which translates into a dramatic reduction in the computational complexity. The short length of the clips allows an intensive search for the best solution at each step of the reconstruction, which improves the overall system performance. The process of feature tracking is embedded within the reconstruction loop for each clip as a difference with other approaches. The last contribution of this thesis is a final registration step that merges all the processed clips to the same coordinate frame. This last step consists on a set of linear algorithms that combine information of the structure (3D points) and motion (cameras) shared by partial reconstructions of the same static scene to more accurately estimate their registration to the same coordinate system. The performance for the presented algorithm as well as for the global system is demonstrated in experiments with real data.
The Project Management Institute, project management handbook

Foreword Preface The Author THE PROJECT CONTEXT 1. Key Issues in Project Management (Peter W. G. Morris) 2. Strategic Project Management (David Clelend) 3. Managing the Black Boxes of the Project Environment (Rolf A. Lundin & Anders Soderholm) 4. Stakeholder Management (David I. Cleland) 5. Developing Winning Proposals (Joan Knutson) 6. Organizational Structure and Project Management (Robert C. Ford & W. Alan Randolph) SCOPE MANAGEMENT AND PLANNING 7. Project Scope Management (Jeffery K. Pinto) 8. Methods of Selecting and Evaluating Projects (Dorla A. Evans & William E. Sounder) 9. Project Risk Management (R. Max Widerman) 10. Work Breakdown Structures (Gene R. Simmons & Christopher M. Lucarelli) 11. Network Planning and Scheduling (Jack Gido & James P. Clements) 12. Schedule Control (Jack Gido & James P. Clements) 13. Project Resource Planning (Marie Scotto) 14. Closing Out the Project (J. Davidson Frame) HUMAN RESOURCE MANAGEMENT 15. The Project Manager (Barry Z. Posner & James M. Kouzes) 16. Power, Politics, and Project Management (Jeffrey K. Pinto) 17. Team Building (Hans J. Thamhain) 18. Cross-Functional Cooperation (David Wilemon) 19. Project Leadership (David F. Caldwell & Barry Z. Posner) 20. Project Team Motivation (Peg Thoms) 21. Negotiation Skills (John M. Magenau) 22. Conflict Management (Vijay K. Verma) INTEGRATIVE ISSUES IN PROJECT MANAGEMENT 23. Critical Success Factors (Jeffrey K. Pinto & Dennis P. Slevin) 24. Four Failures in Project Management (Kenneth G. Cooper) 25. The Future of Project Management (Jeffrey K. Pinto) Notes Index.
Economy and optionality: Interpretations of subjects in Italian

An analysis of subject placement in Italian argues that placement is not determined entirely by case, but also partly by interpretational considerations. The crucial step in the argument is that there are independent well-formedness conditions on discourse structures and that the apparent interpretational effects on preposed subjects of unaccusatives in Italian are actually effects that derive from judgments of felicity in discourse. The apparent optionality of syntactic movement is in fact conditioned by an interface constraint that requires each well-formed discourse representation structure to have a set of corresponding terminal syntactic structures. These considerations interact with a notion of global Economy to derive the correlation between subject placement, optionality, and interpretation. This conclusion actually reinforces rather than threatens the autonomy of syntax. It removes any features from the syntax that have purely interpretational motivation and leaves a simple theory of argument licensing that is purely structural. Contains 23 references. (MSE) *****,,,,,. *********',A*1.A;r*********Ak***********. 'c**************AA;c****** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * *************************. *et. :. A A ::************************************
Mean Field Simulation for Monte Carlo Integration

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters.
Neuromorphic systems for legged robot control

Locomotion automation is a very challenging and complex problem to solve. Besides the obvious navigation problems, there are also problems regarding the environment in which navigation has to be performed. Terrains with obstacles such as rocks, steps or high inclinations, among others, pose serious difficulties to normal wheeled vehicles. The flexibility of legged locomotion is ideal for these types of terrains but this alternate form of locomotion brings with it its own challenges to be solved, caused by the high number of degrees of freedom inherent to it. This problem is usually computationally intensive, so an alternative, using simple and hardware amenable bio-inspired systems, was studied. The goal of this thesis was to investigate if using a biologically inspired learning algorithm, integrated in a fully biologically inspired system, can improve its performance on irregular terrain by adapting its gait to deal with obstacles in its path. At first, two different versions of a learning algorithm based on unsupervised reinforcement learning were developed and evaluated. These systems worked by correlating different events and using them to adjust the behaviour of the system so that it predicts difficult situations and adapts to them beforehand. The difference between these versions was the implementation of a mechanism that allowed for some correlations to be forgotten and suppressed by stronger ones. Secondly, a depth from motion system was tested with unsatisfactory results. The source of the problems are analysed and discussed. An alternative system based on stereo vision was implemented, together with an obstacle detection system based on neuron and synaptic models. It is shown that this system is able to detect obstacles in the path of the robot. After the individual systems were completed, they were integrated together and the system performance was evaluated in a series of 3D simulations using various scenarios. These simulations allowed to conclude that both learning systems were able to adapt to simple scenarios but only the one capable of forgetting past correlations was able to adjust correctly in the more complex experiments. Declaration of originality I hereby declare that the research recorded in this thesis and the thesis itself was composed and originated entirely by myself in the School of Engineering at The University of Edinburgh.
La perception et la mesure des discriminations racistes et sexistes

Les discriminations se sont finalement imposees comme l’un des mecanismes de production des inegalites qui jalonnent la societe francaise et participent a la constitution de groupes de populations minorises. Cette these aborde la question de la perception, de l’identification et de la denonciation des discriminations racistes et sexistes sous un angle methodologique a partir des donnees de l’enquete Trajectoires et Origines (TeO). Il n’existe pas de correspondance automatique entre les discriminations telles qu’elles se produisent et leurs declarations. Cette these invalide les soupcons de sur declaration des discriminations racistes qu’implique leur enregistrement massif et confirme l’existence d’une sous-declaration des discriminations sexistes qui les fait apparaitre comme un phenomene marginal. L’enquete TeO parvient a contourner les obstacles qui limitent les declarations de discriminations racistes que sont le doute, le rejet d’un positionnement victimaire, la valorisation du merite, la resignation mais ne parvient pas a pallier les mecanismes qui inhibent les declarations de discriminations sexistes. Le deficit de sensibilisation des femmes, le discredit du feminisme, leur interiorisation associee a leur caractere principalement systemique rendent les discriminations sexistes insaisissables. De plus, l’analyse intersectionnelle met au jour comment le croisement d’une situation de dominant liee au sexe a une situation de domine liee a la pretendue race place les hommes racises au cœur d’une intersection generatrice de tensions qui rendent les discriminations a leur encontre plus manifestes que celles subies par les femmes racisees.
A Multidisciplinary Approach to the Reuse of Open Learning Resources

II ACKNOWLEDGMENTS . IV PREFACE.V CONTRIBUTIONS. V MOTIVATION. VI AVAILABILITY. VI LICENSING. VI CONTENTS.VIII LIST OF FIGURES . X LIST OF TABLES . XI
Visual Computing Tools for Studying Micro-scale Diffusion

Title of dissertation: VISUAL COMPUTING TOOLS FOR STUDYING MICRO-SCALE DIFFUSION Sujal Bista, Doctor of Philosophy, 2014 Dissertation directed by: Professor Amitabh Varshney Department of Computer Science In this dissertation, we present novel visual computing tools and techniques to facilitate the exploration, simulation, and visualization of micro-scale diffusion. Our research builds upon the latest advances in visualization, high-performance computing, medical imaging, and human perception. We validate our research using the driving applications of nano-assembly and diffusion kurtosis imaging (DKI). In both of these applications, diffusion plays a central role. In the former it mediates the process of transporting micronsized particles through moving lasers, and in the latter it conveys brain micro-geometry. Nanocomponent-based devices, such as bio-sensors, electronic components, photonic devices, solar cells, and batteries, are expected to revolutionize health care, energy, communications, and the computing industry. However, in order to build such useful devices, nanoscale components need to be properly assembled together. We have developed a hybrid CPU/GPU-based computing tool to understand complex interactions between lasers, optical beads, and the suspension medium. We demonstrate how a highperformance visual computing tool can be used to accelerate an optical tweezers simulation to compute the force applied by a laser onto micro particles and study shadowing (refraction) behavior. This represents the first steps toward building a real-time nanoassembly planning system. A challenge in building such a system, however, is that optical tweezers systems typically lack stereo depth cues. We have developed a visual tool to provide an enhanced perception of a scene’s 3D structure using the kinetic depth effect. The design of our tool has been informed by user studies of stereo perception using the kinetic-depth effect on monocular displays. Diffusion kurtosis imaging is gaining rapid adoption in the medical imaging community due to its ability to measure the non-Gaussian property of water diffusion in biological tissues. Compared with the traditional diffusion tensor imaging (DTI), DKI can provide additional details about the underlying microstructural characteristics of neural tissues. It has shown promising results in studies on changes in gray matter and mild traumatic brain injuries, where DTI is often found to be inadequate. However, the highly detailed spatio-angular fields in DKI datasets present a special challenge for visualization. Traditional techniques that use glyphs are often inadequate for expressing subtle changes in the DKI fields. In this dissertation, we outline a systematic way to manage, analyze, and visualize spatio-angular fields using spherical harmonics lighting functions to facilitate insights into the micro-structural properties of the brain. VISUAL COMPUTING TOOLS FOR STUDYING MICRO-SCALE DIFFUSION
Digital Editions for Corpus Linguistics: Representing manuscript reality in electronic corpora

This paper introduces a new project, Digital Editions for Corpus Linguistics (DECL), which aims to create a framework for producing online editions of historical manuscripts suitable for both corpus linguistic and historical research. Up to now, few digital editions of historical texts have been designed with corpus linguistics in mind. Equally, few historical corpora have been compiled from original manuscripts. By combining the approaches of manuscript studies and corpus linguistics, DECL seeks to enable editors of historical manuscripts to create editions which also constitute corpora.The DECL framework will consist of encoding guidelines compliant with the TEI XML standard, together with tools based on existing open source models and software projects. DECL editions will contain diplomatic transcriptions of the manuscripts, into which linguistic, palaeographic and codicological features will be encoded. Additional layers of contextual, codicological and linguistic annotation can be added freely to the editions using standoff XML tagging.The paper first introduces the theoretical and research-ideological background of the DECL project, and then proceeds to discuss some of the limitations and problems of traditional digital editions and historical corpora. The solutions to these problems offered by DECL are then introduced, with reference to other projects offering similar solutions. Finally, the goals of the project are placed in the wider context of current trends in digital editing and corpus compilation.
UDC as a non-disciplinary classification system for a high-school library

The paper addresses issues in establishing a user-friendly systematic collection arrangement following a merger of two high school and college library collections classified according to UDC. In the way it was used, this scheme presented some weaknesses with respect to collection usage. Due to the disciplinary nature of UDC, subjects and phenomena are dispersed in the scheme according to the disciplines in which they are the subject of study. At the same time students in a school library often seek interdisciplinary subjects and need access to clusters of documents which according to UDC may be classed in several different knowledge areas. The author illustrates how this problem was resolved by re-arranging the collection according to phenomena. This was achieved by interpreting UDC numbers as if they represented specific phenomena. Thus, by superimposing some local indexing rules onto a disciplinary knowledge organization system it was possible to collocate interdisciplinary subjects under a single class number. Furthermore, by reversing subject numbers and form auxiliaries (atlases, dictionaries, textbooks etc.) which is an option envisaged in the design of UDC, documents were collocated in the way they are most frequently used by students. The author suggests that, in practice, one often needs to overcome the constraints of disciplinary classification and he discusses the approach used in his school library collection.
The Match Box algorithm for parallel production system match

We introduce Match Box, a new increments matching algorithm for determining the tuple instantiations of forward-chaining production rules. Match Box is rooted in the mathematical interconnections between tuple and binding spaces, a framework also applicable to other pattern matching algorithms. The idea is to precompute a rule's binding space, and then have each binding independently monitor working memory for the incremental formation of tuple instantiations. A key feature of Match Box is that on a massively parallel architecture, it can perform a rule's computationally intensive incremental join testing in constant time. It also finds application on conventional serial processors. This work was supported in part by grant R29 LM 04707 from the National Library of Medicine. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of the National Library of Medicine or the U.S. government.
Stochastic Modeling and Estimation of Wireless Channels with Application to Ultra Wide Band Systems

I am submitting herewith a dissertation written by Yanyan Li entitled “Stochastic Modeling and Estimation of Wireless Channels with Application to Ultra Wide Band Systems. ” I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Electrical Engineering.
Practical Time-Frequency Analysis, Volume 9: Gabor and Wavelet Transforms, with an Implementation in S

Time frequency analysis has been the object of intense research activity in the last decade. This book gives a self-contained account of methods recently introduced to analyze mathematical functions and signals simultaneously in terms of time and frequency variables. The book gives a detailed presentation of the applications of these transforms to signal processing, emphasizing the continuous transforms and their applications to signal analysis problems, including estimation, denoising, detection, and synthesis. To help the reader perform these analyses, Practical Time-Frequency Analysis provides a set of useful tools in the form of a library of S functions, downloadable from the authors' Web sites in the United States and France. Key Features* Detailed presentation of the Wavelet and Gabor transforms* Applications to deterministic and random signal theory* Spectral analysis of nonstationary signals and processes* Numerous practical examples ranging from speech analysis to underwater acoustics, earthquake engineering, internet traffic, radar signal denoising, medical data interpretation, etc* Accompanying software and data sets, freely downloadable from the book's Web page
Sentiment Analysis of Twitter: Using Knowledge based and Machine Learning Techniques

Twitter is a “micro-blogging” social networking website that has a large and rapidly growing user base. The aim of this paper is to collect tweets using a Twitter API on keywords #ConchitaWurst and #Eurovision2014.This paper will determine the sentiment orientation of the tweets. The classification model which this project will develop will determine whether the tweet status updates (which cannot exceed 140 characters) reflects positive opinion or negative opinion on the behalf of the person who tweeted. This paper will use a hybrid of knowledge based sentiment analysis methodologies such as which have been more traditionally used, and those of machine learning methodologies which used a more intuitive approach to sentiment such as Naive Bayes. The results of these two methodologies indicate an overwhelmingly positive response towards Conchita Wurst.
Paraphrasing by Case Alternation

This paper proposes a method of automatical paraphrasing of a simple sentence by case alternation. We make 43 case-alternation rules and three dictionaries: the verb dictionary, the dictionary that records intransitive verbs and their corresponding transitive verbs, and the dictionary that records animateness/inanimateness of nouns. A case-alternation rule consists of a case mapping, a predicate mapping, a condition for a noun phrase, and a condition for a verb. The condition for a noun phrase and the condition for a verb restrict the rule application to an input sentence. The rules consist of 24 rules that change the voice, 7 rules that do not change the voice but the verb, and 12 rules that change the other factor. We have constructed the paraphrase system by implementing these alternation rules. This system generates all possible paraphrasing. We have conducted an experiment with this system, and show the effectiveness of the method.
Processable English: The Theory Behind the PENG System

Abstract : This report describes the theoretical underpinnings of the PENG system. Designed by Rolf Schwitter, Marc Tilbrook, et al. at the Centre for Language Technology at Macquarie University, the system incorporates a text editor where authors write text in a controlled language called PENG. Authors of PENG text do not need to remember the restrictions placed on the language, since the PENG text editor guides the writing process. It does this by indicating the possible sentence constructs allowable from the current input. A controlled language processor translates PENG text to a logical theory which can then be checked for consistency and informativity, and may also be used for question-answering by third-party reasoning services. Although PENG is still a prototype, and has a number of issues, the system shows potential as a useful tool.
Dimension reduction using inverse spline regression

Title of dissertation: DIMENSION REDUCTION USING INVERSE SPLINE REGRESSION Kijoeng Nam, Doctor of Philosophy, 2014 Dissertation directed by: Professor Paul J. Smith Mathematical Statistics Program Professor Dmitry Dolgopyat Mathematics Program In high-dimensional data analysis, we often want to reduce the number of predictors without eliminating variables which are related to the response of interest. Inverse regression methods use the response variable when performing dimension reduction so that information regarding the relation between the covariates and the response is not lost. However, it is common to assume that the inverse regression function is linear or to use some other ad hoc approach. Instead, we propose a new dimension reduction method which models the inverse regression function as a spline. We develop asymptotics for our approach and demonstrate its performance through simulations and several data sets commonly found in the machine learning literature. We show that its performance is better than existing inverse regression based methods, especially when the dimension reduction space is a nonlinear manifold such as the Swiss roll example of Roweis and Saul (2000).
Covering of problem in wireless sensor networks

Sensor networks have attracted a lot of notice. Thus environments may consist of many inexpensive nodes, each capable of collecting, storing, and processing environmental information, and communicating with neighboring nodes through wireless links. We first study several relevant computational geometric problems. Then, a number of papers aimed at solving the coverage problem in wireless sensor networks are discussed. We will address issues such as surveillance and exposure of sensor networks, coverage and connectivity in network deployment, and coverage- and energy-preserving protocols for sensor networks.