Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Biostatistical Methods for Curved and Censored Biomedical Data

EMIL A. CORNEA: Advanced Biostatistical Methods for Curved and Censored Biomedical Data (Under the direction of Joseph G. Ibrahim and Hongtu T. Zhu) This research was dedicated to analyze two types of biomedical data: curved data lying on a manifold and censored survival data from clinical trials. The main part of the research aims at developing a general regression framework for the analysis of a manifold-valued response in a Riemannian symmetric space (RSS) and its association with Euclidean covariates of interest, such as age. Such data arises frequently in medical imaging, computational biology, and computer vision, among many others. We developed an intrinsic regression model solely based on an intrinsic conditional moment assumption, avoiding specifying any parametric distribution on RSS. We proposed various link functions from the Euclidean space of covariates to the RSS of responses. We constructed parameter estimates and test statistics, and determined their asymptotic distributions and geometric invariant properties. Simulation studies were used to evaluate the finite sample properties of our method. We applied our model to investigate the association between covariates, including gender, age, and diagnosis, and the shape of the Corpus Callosum contours from the Alzheimer’s Disease Neuroimaging Initiative dataset, in both cross-sectional and longitudinal cases. In oncology clinical trials, progression-free survival (PFS) has been a key endpoint to support licensing approval, and it is recommended to have the investigator’s tumor assessments verified by an independent review committee blinded to study treatments, especially in open-label studies. Agreement between these evaluations may vary for
APPLICATION OF TRAFFIC CONFLICT ANALYSIS AT INTERSECTIONS

The objective of this project was to develop standard definitions in regard to what constitutes a traffic conflict and to design a data collection procedure that will minimize individual differences in the observation and recording of conflicts. Midwest Research Institute has fulfilled that objective through a state-of-the-art review; development of candidate definitions; comprehensive field studies (including the recruitment and training of conflicts observers); and, following an assessment of the collected data and the field procedures, documentation of the findings in a form for direct use both in other research projects and in practical applications. This report provides sufficient information for individuals having no prior experience in the use of the technique to initiate new applications. The procedures manual, instructor's guide, and sample data collection forms provided in the appendixes should be particularly useful. (Author)
Recognition of the numbers in the Polish language

Automatic Speech Recognition is one of the hottest research and application problems in today’s ICT technologies. Huge progress in the development of the intelligent mobile systems needs an implementation of the new services, where users can communicate with devices by sending audio commands. Those systems must be additionally integrated with the highly distributed infrastructures such as computational and mobile clouds, Wireless Sensor Networks (WSNs), and many others. This paper presents the recent research results for the recognition of the separate words and words in short contexts (limited to the numbers) articulated in the Polish language. Compressed Sensing Theory (CST) is applied for the first time as a methodology of speech recognition. The effectiveness of the proposed methodology is justified in numerical tests for both separate words and short sentences. Keywords—Automatic Speech Recognition, Compressed Sensing, Sparse Classification.
Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is N P-hard and also has O (|V |3) constraints, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.
Videogaming and Exploring EFL Students´ Literacy Practices in Warcraft: A Massively Multiplayer Online Game (MMOG)

El presente trabajo pretende revisar una experiencia de investigacion de un contexto despues de la escuela que adopta World of Warcraft , un juego masivo en linea multi-jugador popular, para el aprendizaje del idioma Ingles . A traves del juego dentro de World of Warcraft estudiantes realizaron diferentes retos linguisticos dentro del mundo virtual. Observacion , la coleccion de producciones efectuados por los participantes y entrevistas se utilizaron para recopilar datos sobre las practicas de lectura y escritura que surgieron cuando se jugaba el video juego y los efectos sobre el desarrollo de habilidades de lectura y escritura con el aprendizaje de Ingles como lengua extranjera . Los resultados de la investigacion muestran que los estudiantes participan en dos categorias de practicas de lectoescritura en Ingles : practicas de lectura y escritura dentro del juego y practicas de lectura y escritura mas alla del juego. Como conclusion tambien se pudo obtener que los estudiantes aprendieron el idioma Ingles que fue determinado por la participacion en multiples practicas de lectoescritura . Por ultimo, estos resultados de la investigacion revelan en detalles mas minuciosos si la idea de utilizar los mundos virtuales cumplira con los requisitos de la educacion del siglo 21 .
Unsupervised learning : foundations of neural computation

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over the past nine years.This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
TABU SEARCH HEURISTIC FOR THE VEHICLE ROUTING PROBLEM WITH STOCHASTIC DEMANDS AND CUSTOMERS - REVISED EDITION

This paper considers a version of the stochastic vehicle routing problem where customers are present with some probality and have random demands. A tabu search heuristic is developed for this problem. Comparisons with known optimal solutions indicate that the heuristic solves the problem to optimality in the vast majority of cases and deviations from optimality are almost always smamll.
Quality of Service in IP Networks

A multihop example X1(t) X2(t) SP Y1(t) EDF C C Z1(t) GPS C 1 2 δ1 δ2 w1 w2 () () () () 1 2 1 1 average value , , , variance rt X t X t Y t Z t rbt ⎧ ≡ ⎨ ⎩ Calculate the probability density of the end-to-end delay of the traffic flow X2(t) Y2(t) Z2(t)
Integrating multiple literacies and digital storytelling in language learning : a case study

The evolution of digital technologies in all sectors of society, including education, implies a paradigm shift in teaching methods. In Portugal, the new national curriculum for Portuguese language teaching at Elementary School level highlights the role of technologies, considering that these new methods, “require mastery of multiple literacies, namely digital and computer literacies – associated with information and communications technologies – and visual literacy – reading images” [1] (p. 3). Lankshear and Nobel [2] admit that literacy takes a central position in educational policies, the development of curriculum and teaching practices. For these authors "literacy is now centre stage in education policy, curriculum development, and everyday thinking about educational practice" (p 7). However, the concept combines a multiplicity of texts and discourses requiring the incorporation of such forms of constructing meaning, other than the written form. In this context, we attempt to provide through student developed multimodal digital narratives, the chance to access a multiplicity of textual environments, in particular digital and visual ones. We set out a case study [3] designed to answer the following research question: how can multimodal texts contribute to development of the study of narrative? The study was carried out with a class of Year 7 students (12 year olds). The first author was the class Portuguese teacher. Data was collected through participant observation, semi-structured interviews with students and analysis of student digital productions. Data analysis is based on the content analysis method. The results make it possible to conclude that: the students developed linguistic, digital and visual skills which gave rise to the construction of meanings in multimodal texts; the use of digital narrative favoured the study of narrative in Portuguese; the use of technological tools contributed to student motivation and commitment. In this article we provide: a) a brief theoretical contextualisation of digital narratives in the context of mother language learning; b) the project carried out with 13 year olds; c) the research methodology underlying this project; d) the results obtained.
LSCOM Lexicon Definitions and Annotations (Version 1.0)

The DTO sponsored LSCOM workshop is developing an expanded multimedia concept lexicon on the order of 1000. Concepts related to events, objects, locations, people, and programs have been selected following a multi-step process involving input solicitation, expert critiquing, comparison with related ontologies, and performance evaluation. Participants of the process include representatives from intelligence community users, ontology specialists, and multimedia analytics researchers. In addition, each concept has been qualitatively assessed according to some criteria, such as utility (usefulness), observability (by humans), and feasibility (by automatic detection). An annotation process was completed in late 2005 by student annotators at Columbia University and CMU, over the entire development set of TRECVID 2005 videos. Human subjects judge the presence or absence of each concept in the key frame of each subshot, resulting in a total of 61901 labels for each concept. Out of the 834 initial selected concepts, the first version of LSCOM annotations consists of 449 unique concepts (39 LSCOM-Lite concepts included) over the entire TRECVID 2005 development set (61901 subshots).
Digital System Design with SystemVerilog

The Definitive, Up-to-Date Guide to Digital Design with SystemVerilog: Concepts, Techniques, and CodeTo design state-of-the-art digital hardware, engineers first specify functionality in a high-level Hardware Description Language (HDL)and todays most powerful, useful HDL is SystemVerilog, now an IEEE standard. Digital System Design with SystemVerilog is the first comprehensive introduction to both SystemVerilog and the contemporary digital hardware design techniques used with it.Building on the proven approach of his bestselling Digital System Design with VHDL, Mark Zwolinski covers everything engineers need to know to automate the entire design process with SystemVerilogfrom modeling through functional simulation, synthesis, timing simulation, and verification. Zwolinski teaches through about a hundred and fifty practical examples, each with carefully detailed syntax and enough in-depth information to enable rapid hardware design and verification. All examples are available for download from the book's companion Web site, zwolinski.org. Coverage includesUsing electronic design automation tools with programmable logic and ASIC technologiesEssential principles of Boolean algebra and combinational logic design, with discussions of timing and hazardsCore modeling techniques: combinational building blocks, buffers, decoders, encoders, multiplexers, adders, and parity checkersSequential building blocks: latches, flip- flops, registers, counters, memory, and sequential multipliersDesigning finite state machines: from ASM chart to D flip-flops, next state, and output logicModeling interfaces and packages with SystemVerilogDesigning testbenches: architecture, constrained random test generation, and assertion-based verificationDescribing RTL and FPGA synthesis modelsUnderstanding and implementing Design-for-TestExploring anomalous behavior in asynchronous sequential circuitsPerforming Verilog-AMS and mixed-signal modelingWhatever your experience with digital design, older versions of Verilog, or VHDL, this book will help you discover SystemVerilogs full power and use it to the fullest.
Annotation and indexing of video content basedon sentiment analysis

Due to scientific advances in mobility and connectivity, digital media can be distributed to multiple platforms by streams and video on demand services. The abundance of video productions poses a problem in term sof storage, organization and cataloging. How the movies or TV-series should be sorted and retrieved is much dictated by user preferences,motivating proper indexing and an notation of video content. While movies tend to be described by keywords or genre, this thesis constitutesan attempt to automatically index videos, based on their semantics. Representing a video by the sentiment it invokes, would not only be more descriptive, but could also be used to compare movies directly based onthe actual content. Since filmmaking is biased by human perception,this project looks to utilize these characteristics for machine learning.The video is modeled as a sequence of shots, attempting to capture the temporal nature of the information. Sentiment analysis of videos has been used as labels in a supervised learning algorithm, namely a SVM using a string kernel. Besides the specifics of learning, the work of this thesis involve other relevant fields such a feature extraction and videosegmentation. The results show that there are patterns in video fit for learning; however the performance of the method is inconclusive due to lack of data. It would therefore be interesting to evaluate the approach further, using more data along with minor modifications.
Clasificación y ejemplos del uso de ontologías en Ingeniería del Software

Resumen. Las ontologias se han convertido en herramientas que pueden asistir eficientemente en las actividades de desarrollo y mantenimiento de software ya que, al reducir la ambiguedad y proveer un marco de unificacion, ayudan a compartir conocimiento, facilitan la comunicacion y permiten una alta reutilizacion de conocimiento. En este trabajo se presentan varias clasificaciones de ontologias propuestas en la literatura y ejemplos de uso en ingenieria del software, que son analizados de acuerdo a ellas.
A Query Driven Computer Vision System: A Paradigm for Hierarchical Control Strategies during the Recognition Process of Three-Dimensional Visually Perceived Objects.

Abstract : We have developed a system called LANDSCAN, which is an integrated vision system and the recognition process is knowledge driven. This knowledge is generated by a query in English. The visual information is a stereo pair of images, and the description are being made on 3-dimensional information. Keywords: Computer applications, Image processing, Optical images, Natural language, Computer vision, Knowledge driven recognition, Scene analysis.
Concurrent implementation of the Crank-Nicolson method for heat transfer analysis

To exploit the significant gains in computing speed provided by Multiple Instruction Multiple Data (MIMD) computers, concurrent methods for practical problems need to be investigated and test problems implemented on actual hardware. One such problem class is heat transfer analysis which is important in many aerospace applications. This paper compares the efficiency of two alternate implementations of heat transfer analysis on an experimental MIMD computer called the Finite Element Machine (FEM). The implicit Crank-Nicolson method is used to solve concurrently the heat transfer equations by both iterative and direct methods. Comparison of actual timing results achieved for the two methods and their significance relative to more complex problems are discussed.
ICOTS6, 2002: Albert 1 TEACHING INTRODUCTORY STATISTICS FROM A BAYESIAN PERSPECTIVE

This paper reviews the past and current interest in using Bayesian thinking to introduce statistical inference. Rationale for using a Bayesian approach is described and particular methods are described that make it easier to understand Bayes' rule. Several older and modern introductory statistics books are reviewed that use a Bayesian perspective. It is argued that a Bayesian perspective is very helpful in teaching a course in statistical literacy.
Swarm Approaches For Semantic Triple Clustering And Retrieval In Distributed RDF Spaces

Within the last decade, many new approaches have been developed towards a shift from the “classic” web, which is designed primarily for human use, to a machine-processable web, which can be used by heterogenous systems to cooperate in an independent and scalable manner. These approaches include new technologies for modeling semantic data to be commonly understood by applications such as data miners, web service clients, autonomous software agents, or reasoning tools, as well as new coordination models for a loose and scalable coupling of independent systems, varying from high-end servers to small embedded applications in PDAs, cell phones, or sensor nets. Especially the combination of semantically modeled domain knowledge and common web services to become semantic web services seems to be a promising technology in the respect of an internet-scale integration model. They overcome the tightly coupled message exchange pattern which is used in classic Web Services, but use Tuple Spaces instead, which accompany the Word Wide Web’s core paradigm of information exchange via persistent publication [1]. As those technologies imply internet-scalability, it is essential to investigate how decentralized and fully distributed architectures can be realized without significant performance impacts. Observing natural societies like swarms, flocks, or hives, they seem to provide many of the desired characteristics, such as scalability, dynamism, failure tolerance and simplicity. Swarm strategies are already successfully used in the field of peer-to-peer networking and special cases of linear optimization. This thesis implements and evaluates swarm-based approaches for semantic Tuple Spaces, based on the previous work of Daniel Graff, who implemented a LINDA Tuple Space system called SwarmLinda [2]. It extends this space with semantic triple clustering and retrieval by adapting common similarity measures for a distributed swarm-based architecture and by developing research strategies inspired by ant routing algorithms.
A Code Compression Technique for Chip Area Minimazation

In this report, we propose an object-code compression technique for instruction ROMs in embedded systems. The Byte Pair Encoding ,which is a kind of dictionary compression methods, has a very simple encoding/decoding scheme and can be decoded in any positions. We surmmarize necessities of compressing ROMs and extend the Byte Pair Encoding to encode/decode more effectively. We demonstrate the code compression for actual programs by the Byte Pair Encoding on the reduction of ROM area.
Approaching language transfer through text classification : explorations in the detection-based approach

1 Scott Jarvis: The Detection-Based Approach: An Overview 2 Scott Jarvis, Gabriela Castaneda-Jimenez and Rasmus Nielsen: Detecting L2 Writers' L1s on the Basis of their Lexical Styles 3 Scott Jarvis and Magali Paquot: Exploring the Role of N-Grams in L1 Identification 4 Scott A. Crossley and Danielle S. McNamara: Detecting the First Language of Second Language Writers Using Automated Indices of Cohesion, Lexical Sophistication, Syntactic Complexity, and Conceptual Knowledge 5 Yves Bestgen, Sylviane Granger and Jennifer Thewissen: Error Patterns and Automatic L1 Identification 6 Scott Jarvis, Yves Bestgen, Scott A. Crossley, Sylviane Granger, Magali Paquot, Jennifer Thewissen and Danielle S. McNamara: The Comparative and Combined Contributions of N-grams, Coh-Metrix Indices, and Error Types in the L1 Classification of Learner Texts 7 Scott A. Crossley: Detection-Based Approaches: Methods, Theories and Applications