Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Interval Analysis to Bound Numerical Errors in Scientific Computing

In scientific computing, the approximation of continuous physical phenomena by floating-point numbers gives rise to rounding error. The behaviour of rounding errors is difficult to predict, and most scientific applications ignore it. For applications in which the accuracy of the result is critical, this is not an acceptable choice. Interval analysis is an alternative to conventional floating-point computation that offers guaranteed error bounds. Despite this advantage, interval methods have rarely been applied in high performance scientific computing. In part, this is because of the additional cost associatedwith performing interval operations over the corresponding floating-point operations. Another issue is the lack of example applications of interval analysis; many scientific users simply do not know that an alternative to floating-point computation exists. This thesis develops and demonstrates techniques by which interval analysis can be feasibly applied to scientific computing. Methods are shown by which the performance of interval codes may be significantly improved on the UltraSPARC platform: hand-optimised codes for vector functions are developed that are around 60% faster than the Sun interval implementation, and an alternative method of interval multiplication is developed that is around 30% faster than the method used by other implementations. The benefits of interval analysis are demonstrated through application to an example scientific problem: the evaluation of electrostatic potentials. Alternative methods of evaluation are analysed: two new accurate methods of summation are proposed and proven to reduce rounding error in this application. This demonstration includes what is believed to be the first interval implementation of the fast multipole method. The implementation is used to explore the balance between rounding and truncation errors in the method, which has previously been ignored. The results suggest that rounding error may affect the accuracy that can be practically achieved using the method. The results also provide guidance in choosing parameters to minimise error.
Investigating the usefulness of stack traces in bug triaging

In software engineering, resources such as time, money and developers, are limited. Often when bugs are found in the software developed, bug triaging is used to prioritise bug reports and allocate resources to it. When the number of bugs is considerable, this will require a vast amount of time and effort. The goal of this research is to investigate the usefulness of stack traces in bug reports for the assessment of bug report properties, using existing metrics of bug reports and files, being severity, priority and time-to-fix. In order to investigate the usefulness of stack traces, a research framework and methodology are developed. Overall, we can conclude that stack traces can be used to link software artifacts. Also, stack traces can be a valuable input for prediction models, for example using metrics of related bugs and source files.
Testing the roles of disfluency and rate of speech in the coordination of conversation

This thesis is concerned with two different accounts of how speakers coordinate conversation. In both accounts it is suggested that aspects of the manner in which speech is performed (its disfluency and its rate) are integral to the smooth performance of conversation. In the first strand, we address Clark's (1996) suggestion that speakers design hesitations, such as filled pauses (e.g. uh and um), repetitions and prolongations, to signal to their audience that they are experiencing difficulties during language production. Such signals allow speakers to account for their use of time, particularly when they experience disruptions during production. The account is tested against three criteria, proposed by Kraljic and Brennan (2005), for evaluating whether a feature of speech is being designed: That it be produced with regularity, that it be interpretable by listeners, and that its production varies according to the speaker's communicative intention. While existing literature offers support for the first two criteria, neither an experiment with dyads nor analyses of dialogue in the Map Task Corpus (MTC; Anderson et al., 1991) found support for the third criterion. We conclude that, rather than being signals of difficulty, hesitations are merely symptoms which listeners may exploit to aid comprehension. In the second strand, we tested Wilson and Wilson's (2005) oscillator theory of the timing of turn-taking. This suggests that entrainment between conversational partners' rates of speech allow them to make precise predictions about when each others' turns are going to end, and, subsequently, when they can begin a turn of their own. As a critical test of the theory, we predicted that speakers who were more tightly entrained would produce more seamless turn-taking. Again using the MTC, we found no evidence of a relationship between how closely entrained speakers were and how precisely they timed the beginning of their turns relative to the ends of each others' turns.
Assist-Pro: Um Assistente Baseado em Conhecimento para Apoiar a Definição de Processos de Software

An important requirement for software quality is to define a software development process. However, software process definition is a complex activity that requires intensive use of knowledge. So, it is worth to offer knowledge-based support to this activity. In this paper we present Assist-Pro, a knowledge-based assistant to aid software engineers to define software processes. We also discuss its development process using knowledge components available in a Knowledge Server.
The design and implementation of Kaleidoscope, a constraint imperative programming language

A constraint is a relation that should be maintained. Constraints are well-suited for object-oriented programming, particularly domains such as interactive graphics and simulation. The Constraint Imperative Programming (CIP) family of languages combines declarative constraints with imperative object-oriented programming and was developed to allow constraints to respond to a change in object structure. This dissertation presents contributions to the design and implementation of constraint imperative languages. A design for a constraint imperative language, Kaleidoscope '93, is presented that is based on a perturbation model for mutable objects, consistent with object mutation in conventional object-oriented languages. Aliasing is an implicit relation that conflicts with the declarative nature of constraints. A declarative mechanism for object identity is described that generalizes constraints to different aspects of object structure. The major drawback of CIP with respect to multi-way constraints systems is performance, particularly for constraint-intensive programs. The performance gap between user-defined constraints in constraint imperative languages and constraint solvers used by conventional object-oriented languages is dramatically reduced by incremental constraint satisfaction optimizations in the Kaleidoscope virtual machine. The runtime penalty for using constraints in CIP languages is further reduced by static constraint satisfaction techniques.
Performance, Utopia, and the "Utopian Performative"

This essay is a rumination of sorts, the beginning of an inquiry into the ways in which performance might provide us with experiences of utopia. How can perform ance, in itself, be a Utopian gesture? Why do people come together to watch other people labor on stage, when contemporary culture solicits their attention with myriad other forms of representation and opportunities for social gathering? Why do people continue to seek the liveness, the present-tenseness that performance and theatre offer? Is the desire to be there, in the moment, an expression of a Utopian impulse? Certainly, people are drawn to theatre and performance by fashion and by taste, by the need to collect the cultural capital that theatre going provides. Live theatre remains a powerful site at which to establish and exchange notions of cultural taste, to set standards, and to model fashions, trends, and styles.
From Peers to the Cloud: Utilizing Distributed Resources for Content Delivery and User Collaboration

In this thesis, we tackle the problem of content delivery and user collaboration with emerging Internet technologies. Our investigation starts from peer-to-peer (P2P) sharing with social relations to contemporary cloud computing with flexible resource provisioning. We seek to leverage distributed resources for efficient sharing and collaboration, which leads to a hybrid system design that seamlessly bridges users’ local resources to public datacenters. We first explore social-network-based optimizations in peer-to-peer content delivery. We give solid evidences that long-term social relations can be found and applied to enhance the sharing efficiency in peer-to-peer networks, and present practical implementation strategies for the popular BitTorrent system. We then investigate the performance of cloud-based file synchronization applications and identify the bottlenecks in their system design, in particular, the task interferences. We propose an interference-aware provisioning algorithm, which effectively mitigates the problem. We further examine the users’ interactions in state-of-the-art cloud-based distributed interactive applications. We find that, despite the benefit in terms of cost savings and better scalability, the cloud-based deployment greatly increases the users’ interaction latency. We demonstrate that a smart assignment algorithms for virtual machines can remarkably reduce such latency. Finally, we present a real-world system design that effectively bridges users’ local resources to enterprise cloud platforms. Our measurements as well as system analysis indicate that it serves as a complement of great potentials to enterprise cloud services.
Modeling automated detection of children in images

During a child pornography investigation, law enforcement officers are required to manually sort through potentially hundreds of thousands of images found on seized digital media. This process is error prone, time-consuming, and places considerable strain on department resources as well as the investigators themselves. This thesis examines the use of automated facial feature detection to estimate the age of a human in an image. The ability to automate the detection between an adult and a child in a sexually explicit digital image will assist law enforcement agencies combating the production and trafficking of child pornography. The proposed method uses open source Haar classifiers to extract facial feature information from images, and predict a subjects age based on anthropometric computations. Classification, regression, and hybrid approaches to machine learning are used to train and test age-estimation models. Manually-plotted facial landmarks are used as ground truth labels to measure the accuracy of 1) automated feature detection of the eyes, nose and mouth, and 2) age-estimation based on the extracted features. Currently, this methodology has been implemented to distinguish between classes of children and adults with an accuracy of approximately 70%.
Flexible Scheduling in Hard Real-Time Systems

The design and implementation of increasingly complex hard real-time computer applications has been limited by the severe restrictions imposed by run-time support systems, in particular the scheduler. The restrictions arise from the assumptions required to afford 100% guarantees to processes with hard deadlines. This constrains the application to conform to the model required by the scheduler. For example, rate-monotonic scheduling, as originally proposed, restricts systems to periodic independent processes, with no shared resources. This thesis examines the trade-offs between the constraints required to enable offline feasibility analysis and the demand for increased fleidbility of the next generation of hard real-time systems. Initially, feasibility analysis is developed for a flexible process model. Tests are derived for static priority pre-emptive scheduling which relaxes the common restriction that the period of a periodic process must be equal to its deadline. One result of relaxing this constraint is that sporadic processes can be accommodated directly. The feasibility analysis is extended to permit processes that have their first execution offset from the 'initial start of system execution. This enables process sets with arbitrary precedence constraints to be expressed. An optimal priority assignment algorithm for processes that have offsets is given. Guaranteeing process deadlines using pessimistic estimations of processor and resource requirements implies that at run-time, an underutilisation of system resources will occur. An approach is proposed to identify this spare system capacity as soon as possible within the execution of a process. Conventionally, this spare capacity is used for the executions of processes without hard deadlines. This thesis presents an approach that enables spare capacity to be allocated to processes with hard deadlines so that system utility can be increased. This thesis contends that the adoption of such an approach imposes no real restrictions upon the application engineer, and greatly increases the flexibility of hard real-time systems, enabling many of the requirements of the next generation of hard real-time applications to be met.
StreamSage Unsupervised ASR-Based Topic Segmentation

StreamSage, Inc. is a pure ASR (automatic speech recognition) group; we've developed an unsupervised method for topic segmentation using ASR information only. For purposes of TRECVID, we partnered with the Dublin City University, a mostly video group, to generate all the required runs. We describe here our ASR-only topic segmentation. Our method was developed for in-depth story segments
How Less Data Can Be Better

During your study, you have probably been warned on many occasions that you can only draw valid conclusions or construct an accurate model if you have enough data. Therefore, the more data you have, the better your model is. However, what if you are in a situation where there is a relative abundance of data? Then the large size of the dataset might also have drawbacks. Fitting a model to your data can take quite some time or can even be impossible. Moreover what to do if you have more data from one part of the design space than from another? Will your model be accurate throughout the whole space or will it be more accurate in areas with more data at the cost of less accuracy in other areas with less data? In this article, we take a look at the effect of using a large non-uniform dataset to fi t a Kriging model. We show that using a subset instead of the complete available dataset can have a number if benefi ts. Furthermore, we introduce and compare several new and current methods for selecting an adequate subset from the original dataset. In short, we will show that less data can be better.
Constraints preserving schema mapping from XML to relations

As XML becomes a standard for data representation on the internet, there is a growing interest in storing XML using relational database technology. To date, none of these techniques have considered the semantics of XML as expressed by keys and foreign keys. In this paper, we present a storage mapping which preserves not only the content and structure of XML data, but also its semantics.
Using rapidly-exploring random tree-based algorithms to find smooth and optimal trajectories

Sampling-based methods such as Rapidly-exploring Random Tree (RRT) have been successfully used in solving motion planning problems in highdimensional and complex environments. The RRT algorithm is the most popular and has the ability to find a feasible solution faster than other algorithms. The drawback of using RRT is that, as the number of samples increases, the probability that the algorithm converges to a sub-optimal solution increases. Furthermore, the path generated by this algorithm is not smooth (tree form). The RRT-based methods will be discussed and simulations are given to evaluate the performance of the methods.
Computational Multiscale Modeling of Fluids and Solids: Theory and Applications

The idea of the book is to provide a comprehensive overview of computational physics methods and techniques, that are used for materials modeling on different length and time scales. Each chapter first provides an overview of the physical basic principles which are the basis for the numerical and mathematical modeling on the respective length-scale. The book includes the micro-scale, the meso-scale and the macro-scale. The chapters follow this classification. The book will explain in detail many tricks of the trade of some of the most important methods and techniques that are used to simulate materials on the perspective levels of spatial and temporal resolution. Case studies are occasionally included to further illustrate some methods or theoretical considerations. Example applications for all techniques are provided, some of which are from the author s own contributions to some of the research areas. Methods are explained, if possible, on the basis of the original publications but also references to standard text books established in the various fields are mentioned.
An Investigation of an Agent-Based Scheduling in Decentralised Manufacturing Control

ABSTRACT This thesis investigates a scheduling algorithm for a heterarchical, distributed manufacturing system. Scheduling in a heterarchical, distributed system is a challenge as the algorithm must be able to operate in the absence of a coordinator and global information. A distributed scheduling method using a market based scheduling algorithm is investigated. Not only is this algorithm able to operate in the absence of a coordinator and global information, it also provides a good match between the software processing parts and the actual physical entities in a manufacturing system. In addition, each entity in the system is able to retain its private information.This thesis investigates a scheduling algorithm for a heterarchical, distributed manufacturing system. Scheduling in a heterarchical, distributed system is a challenge as the algorithm must be able to operate in the absence of a coordinator and global information. A distributed scheduling method using a market based scheduling algorithm is investigated. Not only is this algorithm able to operate in the absence of a coordinator and global information, it also provides a good match between the software processing parts and the actual physical entities in a manufacturing system. In addition, each entity in the system is able to retain its private information. It is found, using simulations, that the market based scheduling algorithm is able to give close-to-optimum solutions. There are instances when the algorithm does not perform well. The lower bound of the algorithm’s performance is derived and conditions under which the algorithm does not perform well are investigated. The market based scheduling algorithm is successfully implemented in the Cambridge Auto-ID Lab, an HMS testbed. Modifications are made to the original algorithm so that it can cope with the dynamics of the real time system and handle rush orders. It is shown in simulations and in a physical system that the algorithm is able to perform real time rescheduling, handle rush orders and produce good scheduling solutions according to some performance measures.
Compiler-Assisted Checkpointing

In this paper we present compiler-assisted checkpointing, a new technique which uses static program analysis to optimize the performance of checkpointing. We achieve this performance gain using libckpt, a checkpointing library which implements memory exclusion in the context of user-directed checkpointing. The correctness of user-directed checkpointing is dependent on program analysis and insertion of memory exclusion calls by the programmer. With compiler-assisted checkpointing, this analysis is automated by a compiler or preprocessor. The resulting memory exclusion calls will optimize the performance of checkpointing, and are guaranteed to be correct. We provide a full description of our program analysis techniques and present detailed examples of analyzing three fortran programs. The results of these analyses have been implemented in libckpt, and we present the performance improvements that they yield.
Abbreviated Historiography of Cubism

Serious historical study of Cubism distinct from partisan defense, attack, or efforts of vulgarization began only in the late 1920s. Until then, the issues generated by Cubism were still alive, and Cubism had not been wholly displaced as an avant-garde movement by Purism, Dada, abstraction, or Surrealism. Only, in fact, when Cubism seemed safely dead could the slow process of objective reconstruction begin. As Guillaume Janneau put it in L'Art Cubiste (1929), “the quarrels that still continue over its least manifestations have only a theoretical interest: they beat around a tomb. ” Conditioned by the then dominant return-to-reality position, Adolphe Basler and Charles Kunstler wrote about Cubism as a freakish aberration safely in the past, a “method of mutilation” of realistic forms that inevitably had to degenerate into an abstract, decorative art. They regarded it as a pseudo-philosophy against which even Picasso “had to break his nose. ” They dismissed the other pre-1914 Cubists—Delaunay, Le Fauconnier, .