Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Signal Processing: A Practical Guide for Engineers and Scientists

The Breadth and Depth of DSP Statistics, Probability and Noise ADC and DAC DSP Software Linear Systems Convolution Properties of Convolution The Discrete Fourier Transform Applications of the DFT Fourier Transform Properties Fourier Transform Pairs The Fast Fourier Transform Continuous Signal Processing Introduction to Digital Filters Moving Average Filters Windowed-Sinc Filters Custom Filters FFT Convolution Recursive Filters Chebyshev Filters Filter Comparison Audio Processing Image Formation and Display Linear Image Processing Special Imaging Techniques Neural Networks (and more! ) Data Compression Digital Signal Processors Getting Started with DSPs Complex Numbers The Complex Fourier Transform The Laplace Transform The z-Transform Index
Efficient Compression and Rasterization Algorithms for Graphics Hardware

Despite rapid development, modern graphics hardware is still much too slow to render photo-realistic images in real time, and it will most likely remain so if we rely only on yearly growth in hardware performance. Therefore, better algorithms are constantly needed in order to advance the field. In the first part of this thesis, we present new algorithms for hardware rasterization. We investigate different aspects of sampling, which leads to a new family of very inexpensive sampling schemes. Based on a perceptual error metric, the best performing patterns are presented. Our study of sampling also considers the use of conservative rasterization, and we present two novel algorithms designed to work on existing graphics hardware. Our final contribution for rasterization is a hardware algorithm for efficiently rasterizing multiple views of a three-dimensional scene. The current norm for multi-view rasterization is to process each view separately, but in this work, we exploit the inherent coherence by considering all views simultaneously. This is done by sorting the rasterization order among all views. In the second part of this thesis, we consider compression algorithms for graphics hardware. Although compression does not provide anything new in terms of features, it is a good way of improving performance and lowering memory usage in a hardware system. Our contributions in this field are two new compression algorithms. The first is suited for real-time compression and decompression of depth values, and the second suited is for compression and decompression of high dynamic range textures. (Less)
Effective Finite Element Analysis Workflow for Structural Mechanics

The Finite Element Method (FEM) is a technique for finding the approximate solutionof differential equations. It is commonly used in structural analysis to evaluate thedeformation and internal stresses of a structure that is subject to outer loads. Thisthesis investigates the Finite Element Analysis (FEA) workflow that is used at AndritzHydro AB, with the objective to find solutions that make the workflow more timeeffective. The current workflow utilises Siemens NX and Salome for pre- andpost-processing, and Code Aster as the FEM solver. Two different approaches thatimprove the workflow are presented. The first suggest that the entire FEA workflowis migrated to NX using the built-in FEM package of NX called Advanced Simulation.The second approach utilises the Salome API (Application Programming Interface) tocreate a customised toolbox (a script containing several functions) that automateseveral repetitive and cumbersome steps of the workflow, therefore effectivelyreducing the time that is required by the analyst to perform FEA. Due to the positiveresults and ease-of-use, the Salome toolbox is preferred over the license cost andsteep learning curve that is related to NX and Advanced Simulation.
Performance and Portfolio Assessment for Language Minority Students. Program Information Guide Series, 9.

Well-designed assessment procedures are essential to meeting the needs of language minority students acquiring English as their second language. Assessment is involved at many steps in a continuum of services for these students: in initial identification, in the placement of students into appropriate instructional programs, in monitoring the progress students make within these programs, in reassigning students to different levels within a program depending on their growth in English language skills, in moving students out of special programs and into mainstream classes, and in following the progress of these students in the mainstream. This continuum is wholly dependent at each step on the appropriate selection, use, and interpretation of relatively complex assessment procedures.
Generic Dynamic DataContainer for Rapid Game Development

In this thesis I detail an easy to use system for dynamic data storage aimed at use in educational games and game systems. Evaluation of current approaches in use by educators and students suggest a large degree of ad hoc systems in place for data persistence. I evaluate my system against existing techniques including a flat file, XML, and SQL systems. I provide a dynamic, easy to use solution to data persistence in the environment of educational game development.
On the Role of Regularization Parameters in Fitness Functions for Evolutionary Designed Artificial N

A main criterion for the accuracy of solutions of Artiicial Neural Networks (ANNs) for classii-cation tasks is the architecture. In order to nd problem-adapted topologies of ANNs, we adopted the evolutionary approach to ANN design by employing a Genetic Algorithm (GA) to evolve ANNs which are represented using a direct encoding method. The role of tness functions used by the GA is investigated, especially, the impact of a tness function expressing both, the learning error and a toplogy-dependent regularization term, is studied. A parallel system { the netGEN system { which has been implemented by the authors is generating problem{adapted Feed{Forward ANNs being trained by Error{Back{Propagation. Empirical results on a real world problem taken from the PROBEN1 ANN benchmark suite are presented.
A self-learning rule base for command following in dynamical systems

In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.
Automated Recognition and Extraction of Enzyme Kinetic Entities from Text

Developing accurate kinetic models depends on the availability of kinetic parameters, which can usually only be retrieved in the form of published articles. The extremely large number of publications makes it advantageous to develop tools for automated recognition and extraction of entities related to enzyme kinetics. The idea of this project is to provide a tool that can be used by database annotators as well as the kinetic modeling community to quickly gather appropriate data. The approach that will be used in this work is known as “Template filling” (Gaizauskas et al., 2003).
Systematic Review on Automated Testing (Types, Effort and ROI)

Software organizations always want to build software by minimizing their resources to reduce overall cost and by maintaining high quality to produce reliable software. Software testing helps us to achieve these goals in this regard. Software testing can be manual or automated. Manual testing is a very expensive activity. It takes much time to write test cases and run them one by one. It can be error-prone due to much involvement of human throughout the process. Automated testing reduces the testing time which results in reduction of overall software cost as well as it provides other benefits i.e. early time to market, improved quality. Organizations are willing to invest in test automation. Before investment, they want to know the expected cost and benefits for AST. Effort is the main factor, which increase the cost of testing. In this thesis, a systematic review have been conducted which identifies and summarizes all the retrieved research concerning the automated testing types, effort estimation and return on investment (ROI) / cost-benefit analysis for automated testing. To conduct the systematic review, the author has developed a comprehensive plan which follows the procedure presented in [15]. This plan provides guidance to identify relevant research articles of a defined period. After the identification of research articles, it collects, evaluates and then interprets all the retrieved data about automated testing types, effort estimation and ROI. The results have been presented in statistical and descriptive form which provides different aspects of the data. The statistical results have been presented with the help of tables and graphs which show different aspects of data i.e. any gaps in research work of automated testing, number of articles for each testing type. The answers of the questions have been presented in descriptive form. The descriptive results show 22 automated testing types, 17 Industrial case studies out of 60 studies, benefits of automated testing and effort estimation models. The discussion part highlighted some important facts about the retrieved data and provides practical implications for conducting systematic reviews. Finally it is concluded that systematic reviews are good means of finding and analyzing research data about a topic, phenomena and area of interest. It also provides support to researchers for conducting and investigating more research.
Distributional Cues to Grammatical Categorization: Acquiring Categories in a Miniature Artificial Grammar.

A crucial component of language acquisition involves organizing words into grammatical categories and discovering relations between them. The organization of words into categories, and the generalization of patterns from some seen word combinations to novel ones, account for important aspects of the expansion of linguistic knowledge in the early stages of language acquisition. One hypothesis of how learners handle the problem of categorization is that they exploit distributional information in the input to discover the category structure of natural languages (e.g., Braine, 1987). However, given the information processing limitations of young children and the complexity of the computational processes that would be entailed, this hypothesis has often been thought to be an unlikely contributor to categorization. Indeed, many studies have argued that in order for a learner to successfully utilize distributional information for category learning, there must be multiple correlated cues to category structure in the input (e.g., Gomez & Gerken, 2000). This, however, has been somewhat of a puzzle: grammatical categories and subcategories in natural languages do not always have reliable phonological, morphological, or semantic cues (Maratsos & Chalkley, 1980). Rather, learners must utilize distributional cues about the linguistic contexts in which words occur to acquire such categories. In this thesis we hypothesize that the patterning of tokens in a corpus of linguistic input is sufficient, along with a small set of learning biases, to extract the underlying structural categories in a language. We present a series of artificial
Principles of Medical Physiology

This book has been specifically designed with the needs of the student in mind. Lengthy explanations are avoided and the material is presented in a concise form that not only makes it easy to understand but also easy to remember and reproduce, which is precisely what the student needs. Key features - Short chapters are organized in the sequence preferred by most physiology teachers - The contents of each chapter are tailored to provide just enough material for a single lecture (occasionally two lectures), making it very handy for teachers. (The book contains 120 chapters) - Basics of relevant physics and chemistry are made extremely simple. This is welcomed by both physiology teachers and students, for efficient teaching and learning - Schematic diagrams in 3D perspective are employed to elucidate difficult anatomical concepts, including the gross structure of the brain - Simple analogies of difficult concepts are given, often comically illustrated. Apparent paradoxes are highlighted and simple answers are provided - Difficult topics are presented with elegant simplicity and brevity without compromising on the core concepts. These include membrane electrophysiology, electromyography, hemostatic balance, electrocardiography, cardiac output, hemodynamics, respiratory mechanics, counter-current multiplier system, body fluid and electrolyte balance, gastric acid secretion, calcitropic hormones, fetoplacental unit, memory and learning, synaptic transmission and sensorimotor mechanisms
Shared Power: What Is It? How Does It Work? How Can We Make It Work Better?

The book explores the concept of shared power arrangements as ways in which public issues are, or can be, addressed. One series of chapters focuses on major conceptual or theoretical topics that cut across all policy areas and levels of analysis; while another series of chapters explores power sharing within particular policy areas, so that the meaning and the limits of power sharing might be addressed across policy domains.
Portfolio selection without default risk in the fixed income market

In this paper we propose a new portfolio selection model to invest in the fixed income market without taking the default risk. The solution of the portfolio choice problem (without default risk) is useful to address better the investors' choices in particular in the recent credit risk crisis during which several firms went bankrupt. Generally investors require a higher rate of return when they invest in bonds of a firm that can easily go bankrupt. For this reason we need to consider CDSs contracts to hedge the default risk of investments in the fixed income market. In this paper, we first describe the credit risk market and we summarize the valuation of classic financial instruments used to hedge the default risk. Secondly, we deal with the problem to hedge the risk in a dynamic framework using credit default swaps (CDSs). Thus we propose a new portfolio selection analysis where we evaluate the ex-post impact of portfolio investments hedged by the default risk. Key-Words: portfolio selection, default risk, credit default swap, fixed income market, immunization problem.
Optimal Experience in Virtual Environments among College Level Developmental Readers

In this study, we examined optimal experience and the antecedents of flow as reported by college-level developmental reading students using Second Life, a multi-user virtual environment. In an educational context, Second Life provided a space for demonstrating 21st century skills including communication, collaboration, problem-solving, and creativity. The researchers in this study examined optimal experience or flow, in particular, toward discovering the extent to which participants reported a prolonged, focused concentration during reading activities within Second Life that either preceded or paralleled the aforementioned 21st century skills. Participants were 42 students enrolled in two developmental reading courses in the fall 2009 semester. Both quantitative and qualitative data were collected and analyzed, yielding results that confirmed that optimal experience was attained and that further served as a catalyst toward demonstrated 21st century skills.
Subband adaptive array for multirate multicode DS-CDMA

Recently, multicode CDMA has been adopted for multirate implementation in wideband multimedia networks. However, in such networks, the two main factors which affect system performance are multiple access interference (MAI), particularly of high data rate (HDR) users on low data rate (LDR) users, and intersymbol interference (ISI) due to multipath fading. To mitigate both MAI and ISI for multirate multicode CDMA, we propose an efficient adaptive array scheme for multirate multicode CDMA using subband signal processing. We also propose the use of the so-called cyclic prefix spread code combining with the scheme to maximize diversity gain in multipath fading environments. SINR and BER performance of 3 class users are explored by computer simulation.
The Structures of Computation: A Distributed Cognitive Analysis of Requirements Evolution in Diverse Software Development Environments

Despite decades of research, effective requirements engineering (RE) remains a significant challenge for software development projects. In addition, the study of RE processes has failed to keep pace with dramatic changes in IS development practice. In this study, we frame RE as a fundamentally socio-technical computational task in which diverse social actors and artifacts collaboratively “compute” the requirements for a n envisioned software system. Through the perspective of distributed cognition, we analyze the distributed RE activities of three IS development projects, representing distinct methodological approaches. We develop models of the computational structures of these projects to support a novel analytical basis for comparison and contrast of three development methodologies - structured development
Completeness of CPSA

Abstract : The Cryptographic Protocol Shapes Analyzer (cpsa) is a program for automatically characterizing the possible executions of a protocol compatible with a specified partial execution. This paper presents a mathematically rigorous theory that backs up the implementation of cpsa in Haskell, and proves the algorithm produces characterizations that are complete, and that the algorithm enumerates these characterizations.
A method for linking field-surveyed and aerial-detected single trees using cross correlation of position images and the optimization of weighted tree list graphs.

With the present number of forestry remote sensing and field plot survey methods several data sources can be combined to potentially achieve a higher accuracy than with a single data source. Some of these datasets contain single tree information and it would be of great value when designing survey techniques if one could automatically link data from different sources belonging to the same tree. In this paper such a method for linking field-surveyed and aerial detected trees is described and evaluated. A simulation study and experimental data show the accuracy of the algorithm at different settings. The method correctly links >90 % of the trees if the corresponding datasets have a position error standard deviation of 1 [m] and 10 % omission and commission errors.
Advances in speech, hearing and language processing

The phoneme and the acoustical speech signal, W.Jassem pragmatic phonetics, K.Morton the ethological approach to the study of first language acquisition by children, R.Narashimhan exploring the role of the dorsal cochlear nucleus in the perception of voice onset time, M.J.Pont and R.I. Damper whither speech systems? a discussion of some characteristics of spoken language which may effect the commercial viability of speech technology, A.F. Newell speech databases, R.Carre speech processing for cochlear implants, J.B. Millar et al human factors studies of the speech driven word processors - experiments using a simulated natural rate large vocabulary continuous speech recognition system, A.F. Newell et al.
Tipos para seguridad basada en flujo de información y computación auditada

Garantizar la confidencialidad de la informacion restringiendo su acceso solo a usuarios autorizados es uno de los pilares de la seguridad informatica actual. Sin embargo, una vez otorgado dicho acceso no se conserva control alguno sobre como se utiliza. El Analisis del Flujo de Informacion (IFA) estudia como se transmite la informacion por diferentes mecanismos. Para ello se vale de politicas de flujo de informacion previamente establecidas. IFA vela por el cumplimiento de las mismas, a traves de tecnicas de analisis estatico de programas o a traves de monitores de ejecucion. De esta manera se logra un control sobre el uso de los datos, que aplica mas alla del momento en que se otorga el acceso a los mismos. Una alternativa a esta modalidad de control de uso de los datos es utilizar computacion auditada. En este caso, las operaciones sobre los datos son permitidas pero tambien auditadas. Las contribuciones de esta tesis son dos. En primer lugar, presentamos un sistema de tipos para Bytecode JVM que garantiza que el flujo de la informacion sea seguro, incluso en el caso en que diferentes instancias de una clase puedan tener atributos cuyo nivel de seguridad varia de acuerdo al contexto en el cual han sido instanciados. La seguridad viene dada por la propiedad de no-interferencia: una formulacion rigurosa de la ausencia de filtraciones de informacion sensible. Si bien esta propiedad es tecnicamente viable, en la practica hay muchos programas que permiten revelar intencionalmente cierta informacion sensible. Esto nos motiva a extender el Bytecode JVM con un mecanismo de "desclasificacion" que permite liberar informacion sensible. El riesgo que introduce es que el mismo pueda ser abusado, permitiendo desclasificar mas informacion sensible de la que originalmente se tenia prevista. Por tal motivo, extendemos el sistema de tipos para garantizar que estas situaciones no sucedan. Dicha extension satisface "desclasificacion robusta": un atacante no puede deducir ninguna informacion adicional a la permitida por la politica de seguridad ni tampoco puede influir en los datos que seran desclasificados. En segundo lugar, presentamos un analisis teorico de un modelo computacional funcional que mantiene un registro de su historia de computacion. A partir de un fragmento de la Logica de Justificacion (JL) de Artemov y el isomorfismo de Curry-de Bruijn-Howard obtenemos un calculo lambda que modela unidades auditadas de computacion. Reduccion en estas unidades auditadas genera trazas que estan confinadas a cada unidad auditada. Asimismo, estas unidades auditadas pueden consultar sus trazas para tomar decisiones en base a las mismas. Probamos seguridad de tipado y normalizacion fuerte para una restriccion del mismo. Este calculo lambda puede ser utilizado para definir programas que refuerzan una variedad de politicas de seguridad basadas en computacion auditada.
Study of Interferer Canceling Systems in a Software Defined Radio Receiver

This thesis describes the work related to an interferer rejection system employing frequency analysis and cancellation through phase-opposed signal injection. The first device in the frequency analysis chain, an analog fast Fourier transform application-specific integrated circuit (ASIC), was improved upon. The second device, a chained fast Fourier transform followed by a frequency analysis module employing cross-correlation for signal detection was specified, designed and implemented in VHDL.