Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards three-dimensional face recognition in the real

Due to the natural, non-intrusive, easily collectible, widespread applicability, machine-based face recognition has received significant attention from the biometrics community over the past three decades. Compared with traditional appearance-based (2D) face recognition, shape-based (3D) face recognition is more stable to illumination variations, small head pose changes, and varying facial cosmetics. However, 3D face scans captured in unconstrained conditions may lead to various difficulties, such as non-rigid deformations caused by varying expressions, data missing due to self occlusions and external occlusions, as well as low-quality data as a result of some imperfections in the scanning technology. In order to deal with those difficulties and to be useful in real-world applications, in this thesis, we propose two 3D face recognition approaches: one is focusing on handling various expression changes, while the other one can recognize people in the presence of large facial expressions, occlusions and large pose various. In addition, we provide a provable and practical surface meshing algorithm for data-quality improvement. To deal with expression issue, we assume that different local facial region (e.g. nose, eyes) has different intra-expression/inter-expression shape variability, and thus has different importance. Based on this assumption, we design a learning strategy to find out the quantification importance of local facial regions in terms of their discriminating power. For facial description, we propose a novel shape descriptor by encoding the micro-structure of multi-channel facial normal information in multiple scales, namely, Multi-Scale and Multi-Component Local Normal Patterns (MSMC-LNP). It can comprehensively describe the local shape changes of 3D facial surfaces by a set of LNP histograms including both global and local cues. For face matching, Weighted Sparse Representation-based Classifier (W-SRC) is formulated based on the learned quantification importance and the LNP histograms. The proposed approach is evaluated on four databases: the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC, including face scans in the presence of diverse expressions and action units, or several prototypical expressions with different intensities, or facial expression variations combine with strong facial similarities (i.e. identical twins). Extensive experimental results show that the proposed 3D face recognition approach with the use of discriminative facial descriptors can be able to deal with expression variations and perform quite accurately over all databases, and thereby has a good generalization ability. To deal with expression and data missing issues in an uniform framework, we propose a mesh-based registration free 3D face recognition approach based on a novel local facial shape descriptor and a multi-task sparse representation-based face matching process. [. ]
MATLAB for Economics and Econometrics A Beginners Guide

This beginners' guide to MATLAB for economics and econometrics is an updated and extended version of Frain (2010). The examples and illustrations here are based on Matlab version 8.3 (R2014a). It describes the new MATLAB Desktop, contains an introductory MATLAB session showing elementary MATLAB operations, gives details of data input/output, decision and loop structures, elementary plots, describes the LeSage econometrics toolbox and shows how to do maximum likelihood estimation. Various worked examples of the use of MATLAB in economics and econometrics are also given. I see MATLAB not only as a tool for doing economics/econometrics but as an aid to learning economics/econometrics and understanding the use of linear algebra there. This document can also be seen as an introduction to the MATLAB on-line help, manuals and various specialist MATLAB books.
Data Mining of Machine Learning Performance Data

ith the development and penetration of data mining within different fields and industries, many data mining algorithms have emerged. The selection of a good data mining algorithm to obtain the best result on a particular data set has become very important. What works well for a particular data set may not work well on another. The goal of this thesis is to find associations between classification algorithms and characteristics of data sets by first building a file of data sets, their characteristics and the performance of a number of algorithms on each data set; and second applying unsupervised clustering analysis to this file to analyze the generated clusters and determine whether there are any significant patterns. Six classification algorithms were applied to 59 data sets and then three clustering algorithms were applied to the data generated. The patterns and properties of the clusters formed were then studied. The major discovery made by analyzing the generated clusters is that the clusters were formed based on accuracy of the algorithms. The data sets were grouped as either belonging to a cluster having average error rates, lower, about average or higher than average error rates of the population. This suggests that there are three kinds of data sets on the 59 data sets considered: 'easy-to-learn data sets', 'moderate-to-learn', and 'hard-to-learn data sets'. Another discovery made by this thesis is that the number of instances in a data set was not useful for clustering analysis of the machine learning performance data. It was the only significant variable in clustering the data sets and prevented analysis based on other variables including the variables that contain values for the accuracy of each classification algorithm. While not directly relevant to clustering, it was also found that the number of instances and number of attributes in the data sets do not have strong influence on the performance of the data mining algorithms on the 59 data sets considered as high error rates were obtained for both small data sets with a small number of attributes and large data sets with a large number of attributes. Experiments performed for this thesis also allowed the comparison of the performance of the 6 classification algorithms with their default parameter settings. It was discovered that in terms of performance, the top three algorithms were Kernel Density, C4.5, and Naïve Bayes, followed by Rule Learner, IBK and OneR. W-III-Declaration I certify that all …
On a method to authenticate and verify digital streams

— Recently, digital streams have become widely used to make audio, video, and other media available in real-time over the Internet. As with other transmission methods, the recipient needs to have a possibility to verify the source and authenticity of the received information. Several techniques have been proposed to deal with this issue. Most of them are vulnerable to packet losses or they introduce unacceptable computational and/or communication overheads. Some of the graph-based techniques provide immunity to burst losses of certain length. However, these techniques are not immune to the loss of packets containing signatures or occasional burst of lengths greater than the assumed one. In the paper, we propose a modiﬁcation to one of the graph-based techniques that introduces immunity to the loss of packets containing signatures, without introducing any additional overheads.
Synthetic voice construction using statistical methods.

The generation of realistic observation sequences from HMM state distributions has been successfully applied to the problem of speech synthesis. This approach features unprecedented qualities, from automated synthetic voice construction, voice conversion and language independence, to speaking style variability and emotional expression. However, output quality from these synthesis systems do not yet meet the standards set by state-of-theart unit selection synthesis. This paper aims to provide insight into factors causing degradation of speech quality. An alternative voice coding scheme based on the sinusoidal model is investigated and a modified voice construction procedure outlined.
A program for the conservation of prehistoric mural paintings on mud renderings in the American Southwest

The paper will describe the conservation treatments of prehistoric mural paintings (c. AD 1150) on mud renderings in two rooms at Aztec Ruins National Monument, New Mexico, an archaeological site under the jurisdiction of the National Park Service. The objectives of the projects were: utilization of the inherent rheological properties of the murals as part of the conservation treatment; development of methods to remove deleterious aged coatings of shellac and cellulose nitrate; and implementation of conservation backfilling of one mural to address long-term preservation. These treatments are the first comprehensive conservation programmes for prehistoric murals on mud renderings in the United States.
The enhancement of machine translation for low-density languages using Web-gathered parallel texts

The majority of the world's languages are poorly represented in informational media like radio, television, newspapers, and the Internet. Translation into and out of these languages may offer a way for speakers of these languages to interact with the wider world, but current statistical machine translation models are only effective with a large corpus of parallel texts - texts in two languages that are translations of one another - which most languages lack. This thesis describes the Babylon project which attempts to alleviate this shortage by supplementing existing parallel texts with texts gathered automatically from the Web -- specifically targeting pages that contain text in a pair of languages. Results indicate that parallel texts gathered from the Web can be effectively used as a source of training data for machine translation and can significantly improve the translation quality for text in a similar domain. However, the small quantity of high-quality low-density language parallel texts on the Web remains a significant obstacle.
The application of classification techniques to the heart rates of miners in escapeways

The techniques of signal processing and pattern classification have been applied, in this thesis, for the classification of the miners' heart rates during rescue operations. These techniques were used because of the limitations noted of the traditional statistical approach used in analyzing the nonstationary heart rates of the miners during rescue operations, The properties and application scope of wavelet are discussed . An appropriate wavelet, namely db4, is selected to perform a dyadic decomposition of the miners' heart rates. The decomposition results are prepared for extracting the feature vectors. Some programs developed in MATLAB language are used for extracting feature vectors from the decomposition results of the miners' heart rate data. Pattern classification techniques are discussed. One program package of classification, based on the LBG algorithm, is applied for the classification of the miners' heart rates. The classification method used produced encouragmg result m spite of limited sample size. The result of the study provides a significant trial in analyzing the nonstationary time series, such as the heart rates of miners during rescue operations, by using signal processing and pattern classification techniques. A total of 37 subjects were classified into four groups. Group 4 members were associated with relatively higher oxygen consumption rates.
Characterising continuous optimisation problems for particle swarm optimisation performance prediction

Real-world optimisation problems are often very complex. Population-based metaheuristics, such as evolutionary algorithms and particle swarm optimisation (PSO) algorithms, have been successful in solving many of these problems, but it is well known that they sometimes fail. Over the last few decades the focus of research in the field has been largely on the algorithmic side with relatively little attention being paid to the study of the problems. Questions such as ‘Which algorithm will most accurately solve my problem? ’ or ‘Which algorithm will most quickly produce a reasonable answer to my problem? ’ remain unanswered. This thesis contributes to the understanding of optimisation problems and what makes them hard for algorithms, in particular PSO algorithms. Fitness landscape analysis techniques are developed to characterise continuous optimisation problems and it is shown that this characterisation can be used to predict PSO failure. An essential feature of this approach is that multiple problem characteristics are analysed together, moving away from the idea of a single measure of problem hardness. The resulting prediction models not only lead to a better understanding of the algorithms themselves, but also takes the field a step closer towards the goal of informed decision-making where the most appropriate algorithm is chosen to solve any new complex problem.
A Review on Design, Implementation and Performance analysis of the Image Inpainting Technique based on TV model

This paper is a review of an image inpainting method by which we can reconstruct a damaged or missing portion of an image. A fast image inpainting algorithm based on TV (Total variational) model is proposed on the basis of analysis of local characteristics, which shows the more information around damaged pixels appears, the faster the information diffuses. The algorithm first stratifies and filters the pixels around damaged region according to priority, and then iteratively inpaint the damaged pixels from outside to inside on the grounds of priority again. By using this algorithm inpainting speed of the algorithm is faster and greater impact. Index Terms—Image inpainting, TV model, priority, peak signal to noise ratio(PSNR).
Towards the validation of adaptive educational hypermedia using CAVIAr

Migrating from static courseware to Adaptive Educational Hypermedia presents significant risk to the course creator. In this paper we alleviate some of this risk by outlining how the CAVIAr courseware validation framework can be used to validate some pedagogical aspects in Adaptive Educational Hypermedia. To allow for this we present a novel method for interoperability in Adaptive Educational Hypermedia using Model Driven Engineering methodologies.
Semantic Infrastructure for a Ubiquitous Computing Environment

This thesis investigates one of the fundamental problems for Ubiquitous Computing: managing metadata to enable resource discovery. This work presents a flexible and general model of metadata, and proposes to use ontologies as a formal language for the metadata of a Ubiquitous Computing Environment. Ontologies provide a common language for metadata among diverse and autonomous entities and spaces in the Ubiquitous Computing Environment. Description Logic is introduced as a formal language for metadata. Description Logic can be used to represent the concepts of a model, and the formal semantics can be used to maintain logical consistency. This thesis presents important locality principles: a Ubiquitous Computing Environment is a local space, which needs a dynamic "working set" from the hypothetical universe of possible devices, services, and entities. This concept is familiar from other contexts (e.g., memory management), but has not been recognized or used in ontology based systems. These principles provide a key insight that led to development key algorithms for managing ontologies in a Ubiquitous Computing Environment: an algorithm for composing two ontologies, and semantic queries on ontologies. The composition algorithm is the key to dynamically updating a local ontology to maintain a working set of concepts from a larger universe of ontologies. The composition algorithm exploits the formal semantics of the ontologies to maintain logical consistency when combining ontologies from several sources. The logical relations defined in the ontology enable semantic queries which can discover not just exact matches but logically related concepts. An improved algorithm for semantic matching is proposed, which extends and refines previous work from the literature, using the formal semantics of the ontology to define what concepts are similar to each other. A prototype Ontology Service was built using standards and software from the "Semantic Web". The prototype implements algorithms for managing ontologies. The prototype was evaluated. In other work, the prototype Ontology Service was ported to Gaia.
Algorithms for large-scale astronomical problems

Modern astronomical datasets are getting larger and larger, which already include billions of celestial objects and take up terabytes of disk space. Meanwhile, many astronomical applications do not scale well to such large amount of data, which raises the following question: How can we use modern computer science techniques to help astronomers better analyze large datasets? To answer this question, we applied various computer science techniques to provide fast, scalable solutions to the following astronomical problems: • We developed algorithms to better work with big data. We found out that for some astronomical problems, the information that users require each time only covers a small proportion of the input dataset. Thus we carefully organized data layout on disk to quickly answer user queries, and the developed technique uses only one desktop computer to handle datasets with billions of data entries. • We made use of database techniques to store and retrieve data. We designed table schemas and query processing functions to maximize their performance on large datasets. Some database features like indexing and sorting further reduce the processing time of user quenes. • We processed large data using modern distributed computing frameworks. We considered widely-used frameworks in the astronomy world, like Message Passing Interface (MPI), as well as emerging frameworks such as MapReduce. The developed implementations scale well to tens of billions of objects on hundreds of compute cores. • During our research, we noticed that modem computer hardware is helpful to solve some sub-problems we encountered. One example is the use of Solid-State Drives (SSDs), whose random access time is faster than regular hard disk drives. The use of Graphics Processing Units (GPUs) is another example, which, under right circumstances, is able to achieve a higher level of parallelism than ordinary CPU clusters. • Some astronomical problems are machine learning and statistics problems. For example, the problem of identifying quasars from other similar astronomical objects can be formalized as a classification problem. In this thesis, we applied supervised learning techniques to the quasar detection problem. Additionally, in the context of big data, we also evaluated existing active learning algorithms which aim to reduce the total number of human labels. All the developed techniques are designed to work with datasets that contain billions of astronomical objects. We have tested them extensively on large datasets and report the running times. We believe the interdisciplinarity between computer science and astronomy has great potential, especially toward the big data trend.
Visual servoing in robotic manufacturing systems for accurate positioning

Automated robotic manufacturing systems require accurate robot positioning. Visual servoing is an increasing popular method to enhance such positioning accuracy. Based on the error signal definition, visual servoing is classified into three approaches, Position Based Visual Servoing (PBVS), Image Based Visual Servoing (IBVS) and Hybrid Visual Servoing (HVS). In this research, firstly, a novel Neural Network (NN) based hand-eye calibration is introduced in PBVS. A MultiLayer Perceptron NN is used to approximate the nonlinear coordinate transform from image coordinates to real world coordinates in visual servoing. The main advantages of NN based hand-eye calibration are that it can solve the hand-eye calibration problem without estimating the hand-eye transformation and can improve the object tracking accuracy as well. The experimental results in an industrial manufacturing robot show that the proposed calibration method outperforms the current solving transformation matrix method and free hand-eye calibration method for 2D object tracking. Secondly, a new approach to switching control of IBVS with laser pointer is proposed. The simple off-the-shelf laser pointer is applied to realize the depth estimation. The proposed system is robust to the camera calibration and hand-eye calibration error, and is object model free as well. Comparing with traditional IBVS, it avoids image singularities and image local minima, and is successful for only partial image features in the field of view. Moreover, the trajectory of the robot end effector is shortened. The experimental results are given to verify the effectiveness of the proposed method in a robotic manufacturing system for assembly
Methodological Proposal for Insole Prescription to Transfemural Amputees Based on Biomechanical Parameters: a principal component analysis approach.

s are presented below: Castro M. , Soares D.P., Machado L.J.R. ; Comparison of vertical GRF obtained from force plate, pressure plate and insole pressure system (2011). Proceedings of the 29th ISBS. Revista Portuguesa de Ciências do Desporto. 11 (2), 849. Voinescu M. , Soares D.P., Castro M. , Mendes E.A. , Davidescu A. , Machado L.J.R. (2011). A study of moments acting on the tibia during gait in the active elderly population. Proceedings of the 29th ISBS. Revista Portuguesa de Ciências do Desporto. 11 (2), 575. Soares D.P., Castro M.P., Sebastião R. A. , Thimoteo T. , Mendes E.A. (2010). Kinetic Gait Analysis Using Different Wedges in Elderly Population. Annals of the 17th Congress of the European Society of Biomechanics. Edinburgh-Scotland Mendes E.A. , Soares D.P., Castro M.P., Spence W.D. , Correia M.V. (2010). Pressure distribution, by quadrants on shod amputees and controls. Annals of the 17th Congress of the European Society of Biomechanics. Edinburgh – Scotland. Castro M.P., Soares D.P., Sebastião R. A. , Thimoteo T. , Mendes E.A. (2010). Pressure Gait Analysis of Elderly Population Using Different Wedges. Annals of the 17th Congress of the European Society of Biomechanics. Edinburgh – Scotland. Castro, M.P., Soares, D.P., Sebastião R. A. , Thimoteo T. , Mendes E.A. , Machado, L.J.R. (2010). Baropodometric analisys of amputees gait: a preliminary study. 13th World Congress of the International Society for Prosthetics and Orthotics and ORTHOPAEDIE + REHA-TECHNIK, Proceedings of 13th World Congress of the International Society for Prosthetics and Orthotics, Leipzig – Germany. Soares, D.P., Castro, M.P., Sebastião R.A. , Thimoteo T. , Mendes E.A. , Machado, L.J.R. (2010). The influence of different wedges in elderly gait kinetic parameters. 13th World Congress of the International Society for Prosthetics and Orthotics and ORTHOPAEDIE + REHA-TECHNIK, Proceedings of 13th World Congress of the International Society for Prosthetics and Orthotics, Leipzig – Germany. Mendes, E. , Soares, D.P., Castro, M.P., Spence, W.D. , Correia, M.V. (2010). Analysis of plantar pressure and balance of transfemoral amputees compared with non-amputee subjects, using their shoes. 13th World Congress of the International Society for Prosthetics and Orthotics and ORTHOPAEDIE + REHA-TECHNIK, Proceedings of 13th World Congress of the International Society for Prosthetics and Orthotics, Leipzig – Germany. Soares, D.P., Castro, M.P., Ribas, R. , Sebastião, R.A. , Mendes, E.M. , LaFortune, M.A., Machado, L.J.M. , (2009). Análise de marcha de indivíduos amputados comparativamente à marcha normal utilizando dinâmica inversa tridimensional; III Congresso Nacional de Biomecânica. Bragança – Portugal. 161-162.