Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Representation and Estimation of Spatial Uncertainty

This paper describes a general method for estimating the nominal relationship and expected error (covariance) between coordinate frames representing the relative locations of ob jects. The frames may be known only indirectly through a series of spatial relationships, each with its associated error, arising from diverse causes, including positioning errors, measurement errors, or tolerances in part dimensions. This estimation method can be used to answer such questions as whether a camera attached to a robot is likely to have a particular reference object in its field of view. The calculated estimates agree well with those from an independent Monte Carlo simulation. The method makes it possible to decide in advance whether an uncertain relationship is known accu rately enough for some task and, if not, how much of an improvement in locational knowledge a proposed sensor will provide. The method presented can be generalized to six degrees offreedom and provides a practical means of esti mating the relationships ( position and orientation) among objects, as well as estimating the uncertainty associated with the relationships.
Adaptive Learning Algorithms and Data Cloning

This thesis is in the field of machine learning: the use of data to automatically learn a hypothesis to predict the future behavior of a system. It summarizes three of my research projects. We first investigate the role of margins in the phenomenal success of the Boosting Algorithms. AdaBoost (Adaptive Boosting) is an algorithm for generating an ensemble of hypotheses for classification. The superior out-of-sample performance of AdaBoost has been attributed to the fact that it can generate a classifier which classifies the points with a large margin of confidence. This led to the development of many new algorithms focusing on optimizing the margin of confidence. It was observed that directly optimizing the margins leads to a poor performance. This apparent contradiction has been the topic of a long unresolved debate in the machine-learning community. We introduce new algorithms which are expressly designed to test the margin hypothesis and provide concrete evidence which refutes the margin argument. We then propose a novel algorithm for Adaptive sampling under Monotonicity constraint. The typical learning problem takes examples of the target function as input information and produces a hypothesis that approximates the target as an output. We consider a generalization of this paradigm by taking different types of information as input, and producing only specific properties of the target as output. This is a very common setup which occurs in many different real-life settings where the samples are expensive to obtain. We show experimentally that our algorithm achieves better performance than the existing methods, such as Staircase procedure and PEST. One of the major pitfalls in machine learning research is that of selection bias. This is mostly introduced unconsciously due to the choices made during the learning process, which often lead to over-optimistic estimates of the performance. In the third project, we introduce a new methodology for systematically reducing selection bias. Experiments show that using cloned datasets for model selection can lead to better performance and reduce the selection bias.
Handbook for Evaluation and Life Cycle Planning for Software. Volume 4. Test and Independent Verification and Validation.

Abstract : This document is Volume 4 of the Handbook for Evaluation and Life Cycle Planning for Software (HELPS). This volume provides the user with comprehensive checklists and guides to validate an independent assessment process for computer programs. It also discusses the requirements and preparation necessary for the various phases of testing. Test plans and procedures are also discussed. (Author)
Advancend algorithms for sound reproduction enhancement in portable multimedia devices

In this thesis, a study of the problems related to the audio reproduction in the context of mobile devices has been carried out. The main topics are audio spatialization techniques, low frequency enhancement approaches and advanced techniques for room equalization, taking into consideration different types of equalizers. Considering this scenario, the work could be divided in two parts. In the first part of this work an advanced audio reproduction enhancement architecture for mobile devices has been presented. The main problems to solve in this context are the low computational capabilities and the physical dimensions of the loudspeakers. These problems can create a negative influence on the audio reproduction, and a suitable solution has to be introduced. Starting from the state of the art, the main purpose is to develop a suitable architecture of advanced algorithms, capable to enhance the audio reproduction, creating an integrated acoustic system with low computational effort. With this perspective, the system architecture is composed of three components, i.e., a crosstalk canceller, a multipoint equalizer and a virtual bass enhancer. The crosstalk canceller is based on an efficient, flexible and low complexity algorithm; this component aims to enhance the acoustical spatialization effect in respect of the common sterephonic reproduction, reducing the coupling between the audio channels on the listener eardrums. The advanced multipoint equalizer aims to clear as much as possible the sound image, trying to reduce the distorsion effect of the environment on the overall frequency response of the system. The reproduction enhancement of low frequencies is obtained exploiting a well known psycoacoustic effect, i.e., the missing fundamental, that allows to the human ear the perception of a missing frequency taking advantage of its higher harmonics. In the second part of the work, the study of graphic equalizers has been presented. These systems are very common in both consumer and professional contexts and they are used to alter the reproduced sound image. They suffer from perfomance lack due to low computational capabilities, reducing the number of available bands. In this context, a high quality graphic equalizer structure based on analysis and synthesis FIR filterbank has been optimized in order to reduce its computational cost but keeping unmodified its perfomance
Low Complexity ML Detection Based on Linear Detectors in MIMO Systems

MMSE, ZF and ML are the decoding mechanisms for V-BLAST system, and ML shows the best performance decoding the original signal among them. However, it has a problem that the computation complexity is increased exponentially according to the number of transmit antennas and transmit degrees. In this paper, we propose a low complexity linear ML detection algorithm having low computation complexity, then analyze the system performance in BER and computation complexity comparing with other algorithms. In the simulation, the BER performance of the proposed algorithm is superior than ZF and MMSE detection algorithms, and similar to ML detection algorithm. However, its computation complexity was 50% less than ML algorithm. From the results, we confirm that the proposed algorithm is superior than other ML detection algorithms.
SAMPLING, SPECIFICATION AND ESTIMATION AS SOURCES OF INACCURACY IN COMPLEX TRANSPORT MODELS - SOME EXAMPLES ANALYSED BY MONTE CARLO SIMULATION AND BOOTSTRAP

In the paper, modern methods, such as Monte Carlo Simulations and Bootstrap, are used to illustrate the total impact on final model quality from Sampling, Specification and Estimation procedures respectively. A set of different model types from the transport area are used for illustration of the large, unsolved and hidden problems of model quality that modern complex transport models are subject to. (A) For the covering abstract see ITRD E107985.
The National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) Software: Version 3 (User's Manual)

Abstract : The Invertebrate Data Analysis System (IDAS) software provides an accurate, consistent, and efficient mechanism for analyzing invertebrate data collected as part of the National Water-Quality Assessment Program and stored in the Biological Transactional Database (Bio-TDB). The IDAS software is a stand-alone program for personal computers that run Microsoft (MS) Windows . It allows users to read data downloaded from Bio-TDB and stored either as MS Excel or MS Access files. The program consists of five modules. The Edit Data module allows the user to subset, combine, delete, and summarize community data. The Data Preparation module allows the user to select the type(s) of sample(s) to process, calculate densities, delete taxa based on laboratory processing notes, combine lifestages or keep them separate, select a lowest taxonomic level for analysis, delete rare taxa, and resolve taxonomic ambiguities. The Calculate Community Metrics module allows the user to calculate over 130 community metrics, including metrics based on organism tolerances and functional feeding groups. The Calculate Diversities and Similarities module allows the user to calculate nine diversity and eight similarity indices. The Data export module allows the user to export data to other software packages and produce tables of community data that can be imported into spreadsheet and word-processing programs. Though the IDAS program was developed to process invertebrate data downloaded from USGS databases, it will work with other data sets that are converted to the USGS (Bio-TDB) format. Consequently, the data manipulation, analysis, and export procedures provided by the IDAS program can be used by anyone involved in using benthic macroinvertebrates in applied or basic research.
Register allocation via graph coloring

Register Allocation is one of the most important problems in compiler optimization. It is also one of the most studied problems in compiler theory, and a vast number of different algorithms exist to solve it. Register Allocation can happen over a basic block (local register allocation), over a whole function/procedure (global register allocation), or across function boundaries traversed via call-graph (inter-procedural register allocation). The objective of this technical paper is to give an overview of the Graph Coloring approach, and how it can be applied to perform Local Register Allocation. The target audience for this paper would be Computer Science students studying Compiler Development, or Compiler Developers interested in understanding the Graph Coloring Algorithm for Register Allocation.
Laser-pointer Tracking for Multi-user Interaction

This thesis presents the implementation of a system for multi-user interaction using laser pointers. The system looks for multi-user interaction in Virtual Reality environments and approaches the problem by taking into account the scalability of the system (large screens, multiple users). The text describes the tracking algorithm and how the extracted information from it can be used as interaction input on the 2D and 3D space. Moreover describes the implementation of a device that can be used in cross-platform Virtual Reality systems. The thesis concludes by presenting the results of the work that was conducted.
Extending Educational Computing

AbstractTeachers are crucial to the integration of technology for teaching and learning. This article discusses a school’s efforts in teacher development and support for technology over five years. Access was facilitated by allocating a laptop computer to each staff member. Concurrently, an in-house inservice program was offered. Reported personal use was extensive; teacher confidence level and skill improved markedly. However, use of computers in the classroom remained relatively low. Further measures were instituted, including a detailed five-year plan for information technology, network and hardware expansion, appointing more technical support staff, and introducing, then refining, a technology-coaches scheme with specified basic skills for all staff. Classroom use showed small but steady gains in amount and diversity. From this case, factors such as pedagogical beliefs and lack of a collaborative culture are identified as inhibiting implementation of technology in the classroom.
A Study on Killer Services in Ubiquitous Computing: The Case of the Scene of Labor Learning

In this study we designed the killer services for the scene of labor learning in ubiquitous computing. To achieve this study, we have explored the unmet needs of teachers in the scene of labor learning and examined whether the unmet needs could be served by the resources and capabilities of ubiquitous computing. Then, we have crafted a detail killer services that includes value propositions and resource maps by using statistical methodology. Finally, the killer services for the scene of labor learning proposed to serve educational users with the service architecture. The result of this study will be applied to develop new business model in ubiquitous computing as the basic research.
Contrôleurs reconfigurables ultra-faible consommation pour les réseaux de capteurs sans fil

Un nœud d'un reseau de capteurs sans fil traite dans ses unites de calcul les signaux issus de plusieurs types de capteurs et effectue differentes tâches liees aux protocoles de communication. Devant executer plusieurs types de controle, sa flexibilite est un parametre tres important. Les solutions a base de microcontroleurs ou de FPGA ont ete proposees pour aborder le besoin de flexibilite, mais au prix d'une efficacite energetique reduite. Dans cette these, des controleurs flexibles a ultra-faible energie bases sur un contexte de micro-tâches reconfigurables sont explores comme alternative. Des architectures modulaires pour des machines d'etats finis (FSM) et des chemins de donnees (DP) reconfigurables sont proposees. Les techniques de coupure de l'alimentation (PG pour power gating) sont utilisees pour adapter la consommation aux besoins et reduire la puissance statique. Dans un premier temps, des modeles pour l'estimation des parametres cles d'un circuit avec PG sont proposes au niveau porte. Ensuite, les opportunites des techniques PG sont determinees sur les FSM et DP reconfigurables pour en reduire l'energie. Dans les chemins de donnees, la reconfiguration fait varier la precision des operateurs et le PG permet d'eteindre les blocs logiques inutilises. Une gestion de l'alimentation au niveau lookup table (LUT) est proposee pour reduire les courants de fuite en mode actif et en veille dans les FSM reconfigurables. Des resultats montrent les tres bonnes performances des architectures proposees par rapport aux processeurs et FPGA.
B.6 Étude de la cohérence inter-représentations : vers une meilleure intégration des bases de données spatiales

Ces travaux se situent dans le cadre de l’intégration de bases de données spatiales. Depuis quelques années, la disponibilité croissante de l’Information Géographique a induit de nouveaux besoins pour les organismes producteurs et utilisateurs de données géographiques. Afin d’assurer une maintenance plus efficace des produits, de garantir une cohérence entre eux, et d’exploiter toute la richesse de l’information disponible sur une même portion de territoire, la définition de liens explicites entre plusieurs sources de données est aujourd’hui souhaitée. Ces liens constituent le pré-requis de l’unification ou intégration.
Statistical Sensor Fusion

Sensor fusion deals with Merging information from two or more sensors. Elsewhere the area of statistical signal processing provides a powerful toolbox to attack bothering theoretical and practical problems. The objective of this book is to explain state of the art theory and algorithms into statistical sensor fusion, covering estimation, detection and non-linear filtering theory with applications to localisation, navigation and tracking problems. The book starts with a review of the theory on linear and non-linear estimation, with a focus on sensor network applications. Then, general non-linear filter theory is surveyed with a Particular attention to Different variants of the Kalman filter and the particle filter. Complexity and implementation issues are discussed in detail. Simultaneous localisation and mapping (SLAM) is distressed as a challenging application area of high-dimensional non-linear filtering problems. The book spans the whole range from mathematical foundations provided in Extensive Appendices, to real-world problems the covered in a party surveying standard sensors, motion models and applications in this field. All models and algorithms are available as object-oriented Matlab code with an Extensive data file library, and the examples, Which are richly distressed to illustrate the theory, are supplemented by fully reproducible Matlab code.
High Performance Computing (HPC) Challenge (HPCC) Benchmark Suite Development

Abstract : The goal of performance modeling is to measure predict, and understand the performance of a computer program or set of programs on a computer system. The applications of performance modeling are numerous, including evaluation of algorithms, optimization of code implementation, parallel library development, and comparison of system architectures, parallel system design, and procurement of new systems. The overall objective of this effort was to survey a number of DoD related applications in an effort to ascertain their needs with respect to determining what metrics exist, what metrics need to be developed.
CMOS Sigma-Delta Converters: Practical Design Guide

This book presents a systematic and comprehensive compilation of sigma-delta converter operating principles, the new advances in architectures and circuits, design methodologies and practical considerations # going from system-level specifications to silicon integration, packaging and measurements, with emphasis on nanometer CMOS implementation. The book emphasizes practical design issues – from high-level behavioural modelling in MATLAB/SIMULINK, to circuit-level implementation in Cadence Design FrameWork II. As well as being a comprehensive reference to the theory, the book is also unique in that it gives special importance on practical issues, giving a detailed description of the different steps that constitute the whole design flow of sigma-delta ADCs.
Multimodal Signal Processing: References

Bringing together experts in multimodal signal processing, this book provides a detailed introduction to the area, with a focus on the analysis, recognition, and interpretation of human communication. The technology described has powerful applications. For instance, automatic analysis of the outputs of cameras and microphones in a meeting can make sense of what is happening – who spoke, what they said, whether there was an active discussion, and who was dominant in it. These analyses are layered to move from basic interpretations of the signals to richer semantic information. The book covers the necessary analyses in a tutorial manner, going from basic ideas to recent research results. It includes chapters on advanced speech processing and computer vision technologies, language understanding, interaction modeling, and abstraction, as well as meeting support technology. This guide connects fundamental research with a wide range of prototype applications to support and analyze group interactions in meetings.
Self-organized Synaptic Learning of Gaits in Virtual Creatures: A neural simulation study within Connectology

The theory of Connectology sets forth three psychologically founded synaptic learning mechanisms that may describe all aspects of animal learning. Of particular interest to this thesis is the learning of animal motion behavior, or, more specifically, the development of synchronized and repetitive movement patterns - gaits. Computer simulations are performed according to the methodology of computational neuroethology: Artificial neural networks are simulated operating in a tight feedback loop with a structurally simple but mechanically realistic body and a physically realistic environment. Neural network learning is purely synaptical and is performed solely within the lifetime of one such ANN-controlled system. Additionally, the configuration parameter space is searched by means of genetic algorithms. Simulation results show examples of synchronized and repetitive movement patterns developing when neuronal and mechanical model parameters are appropriately specified. These simulations thereby provide the first examples known to us of a fully unsupervised and self-organized artificial neural system that synaptically learns synchronized and repetitive motor control. In spite of limited mechanical model complexity, the most efficient movement patterns to some degree resemble the gaits seen in nature.
Accents of English

Volume I: An Introduction: Preface Typographical conventions and phonetic symbols Part I. Aspects of Accent: 1. Linguistic and social variability 2. Accent phonology 3. How accents differ 4. Why accents differ Part II. Sets and Systems: 5. The reference accents 6. Standard lexical sets 7. Systems: a typology Part III. Developments and Processes: 8. Residualisms 9. British prestige innovations 10. Some American innovations 11. Some further British innovations Sources and further reading References Index.
PCA-FA： Applying Supervised Learning to Analyze Gene Expression Data

In previous gene expression data analyses, supervised learning has mainly focused on the classification of attribute data, such as the different experimental conditions, different known classes of the same tumor and sex, However, supervised learning classification is not suitable for interval-scaled attributes such as age and survival outcome of cancer patients, For this problem, this paper proposed a new method by combining two well-known methods: principal component analysis (PCA) and Fisher analysis (FA). The method, PCA-FA, realizes supervised learning with two types of attributes (nominal attributes and intervalscaled attributes). The fuzzy FA was introduced to model the interval-scaled attributes. In this paper, an approximate linear relationship between gene expression data of lung adenocarcinoma patients and survival outcome is successfully revealed by PCA-TA.
The Complete Guide to Digital Photography

Introduction: Why Shoot Digitally? Section One: Hardware Digital Cameras Computers Monitors Scanners Storage Printers Ways of Display Section Two: Working Digitally Imaging Software Image editing tools Filters Section Three: Techniques People Landscapes The urban landscape Nature Objects Action Section Four: Next Steps Concepts and Symbols Layer Upon Layer Constructs Photography and Artwork Photography and CGI Glossary Index