Miracle-dz/UniFAR-FTUs huggingface dataset:
Data editing perspectives

Data editing, tracing and correcting errors in records, takes up a great deal of the avail­ able human resources for the production of statistics. As budget restraints become more severe, the pressure to obtain more efficient data editing procedures increases. There is a need for procedures that restrict the attention of human judgment to errors that are crucial for the quality of the statistical outcomes and that leave the remaining decisions to automatic procedures. The present contribution firstly deals with the types of errors that occur in survey research, then summarizes the capabilities of the state-of-the-art micro editing software systems and finally gives an overview of more efficient data editing methods. Next an overview is given of fully automatic editing, and of methods to edit records with influential errors only: selective editing, aggregate editing and graphical macro editing.
MPI-based scalable computing platform for parallel numerical application

Developing parallel numerical applications, such as simulators and solvers, involves a variety of challenges in dealing with data partitioning, workload balancing, data dependencies, and synchronization. Many numerical applications share the need for an underlying parallel framework for parallelization on multi-core/multi-machine hardware. In this thesis, a computing platform for parallel numerical applications is designed and implemented. The platform performs parallelization by multiprocessing over MPI library, and serves as a layer of abstraction that hides the complexities in dealing with data distribution and inter-process communication. It also provides the essential functions that most numerical application use, such as handling datadependency, workload-balancing, and overlapping communication and computation. The performance evaluation of the parallel platform shows that it is highly scalable for large problems. Thesis Supervisor: John R. Williams Title: Professor, Department of Civil and Environmental Engineering
A future-adaptive password scheme

Many authentication schemes depend on secret passwords. Unfortunately, the length and randomness of user-chosen passwords remain fixed over time. In contrast, hardware improvements constantly give attackers increasing computational power. As a result, password schemes such as the traditional UNIX user-authentication system are failing with time. This paper discusses ways of building systems in which password security keeps up with hardware speeds. We formalize the properties desirable in a good password system, and show that the computational cost of any secure password scheme must increase as hardware improves. We present two algorithms with adaptable cost--eksblowfish, a block cipher with a purposefully expensive key schedule, and bcrypt, a related hash function. Failing a major breakthrough in complexity theory, these algorithms should allow password-based systems to adapt to hardware improvements and remain secure well into the future.
Broadband communication: modeling, analysis and synthesis of an ATM switching element

When there are many people who don't need to expect something more than the benefits to take, we will suggest you to have willing to reach all benefits. Be sure and surely do to take this broadband communication modeling analysis synthesis of an atm switching element that gives the best reasons to read. When you really need to get the reason why, this broadband communication modeling analysis synthesis of an atm switching element book will probably make you feel curious.
Book Reviews

The historical backdrop to these two books by Erik Hollnagel and David Woods is growth in the power of technology over recent decades and the resulting transformations of work in human-machine systems, such as power plants and transport systems. These changes created a requirement to better understand and design systems from the perspective of the human operator. The authors originally formulated Cognitive Systems Engineering (CSE) in the early 1980s with the ultimate objective of designing joint cognitive systems (JCSs) that can effectively control the situations in which they have to function. The JCS is a fundamental concept of CSE, through which a human-machine ensemble is seen as a single functional entity. A key benefit of the application of CSE is enhanced system safety. ‘‘Joint Cognitive Systems: Foundations of Cognitive Systems Engineering’’ (referred to hereafter as JCS-Foundations) characterizes CSE as a conceptual and methodological basis for research on human-machine systems. The main responsibility for writing this book lay with Erik Hollnagel. ‘‘Joint Cognitive Systems: Patterns in Cognitive Systems Engineering’’ (referred to hereafter as JCSPatterns) emphasizes approaches to research and design in CSE and was written primarily by David Woods. The two books can be read independently of each other, but are complementary. Both are of interest to students, educators, engineers and researchers interested in the performance and safety of humanmachine systems. The driving forces for the development of CSE were a) the growing complexity of socio-technical systems, b) the problems, failures, and accidents resulting from a clumsy use of emerging technologies, and c) limitations of the information processing paradigm. That paradigm, which has long provided a basis for the study of human-machine systems, is characterized in JCS-Foundations. The influences of the Shannon-Weaver communication model and the stimulusorganism-response (S-O-R) framework upon its development are highlighted, including a stress on interaction between human and machine. While recognizing that this approach has provided an enormously valuable way of thinking about Book Reviews Journal of Risk Research Vol. 10, No. 3, 413–421, April 2007
Ergonomic criteria for the evaluation of human-computer interfaces

This technical report presents first a brief summary of the research conducted towards the design of ergonomic criteria for the evaluation of human computer interfaces (HCI), and then, the full description of the most recent set of criteria (version 2.1) both in english and french. The summary outlines the context in which the criteria were developed, the goal of the criteria approach, the experiments conducted, and the results obtained. The set of ergonomic criteria that resulted from this work consists of a list of 18 elementary criteria (including 9 main criteria). The criteria are presented along with their definitions, rationales, examples of guidelines, and comments setting out the distinctions between some of them.
Introduction to a future scholarly edition of Alice's adventures in wonderland and Through the looking-glass and what Alice found there

WONDERLAND AND THROUGH THE LOOKING-GLASS AND WHAT ALICE FOUND THERE by HAYLEY ESTHER HEDGPETH (Under the Direction of Simon Gatrell) ABSTRACT Despite Lewis Carroll’s foremost position in the children’s literature canon, a scholarly edition of his two most famous works, Alice’s Adventures in Wonderland and Through the Looking-Glass and What Alice Found There, has yet to appear. This thesis introduces a projected edition of these two works, in which I examine how the publication history and Carroll’s revisions influence editorial decisions.
Review on Sentence - Level Clustering with Various Fuzzy Clustering Techniques

Clustering plays an important role in the area of data mining. Its application extends to many natural language processing tasks such as text mining, document clustering, discovering the similar groups of linguistic terms, information retrieval etc. There are many available data clustering methods for sentence clustering. But in fuzzy clustering data elements can go to blend in more than one cluster with different cluster membership values, and these values indicate the strength of association between the clusters and data elements. So by incorporating fuzzy clustering techniques in sentence clustering domains can give optimal results than other methods, because a sentence can represent more than one concept within a document. This paper is intended to learn and evaluate various Fuzzy Clustering techniques in the context of sentencelevel clustering. Index Terms Fuzzy Clustering, Sentence Level Clustering, FRECCA algorithm, Cluster-Membership, Text Mining.
Managing complexity reducing perplexity.Modeling biological systems

Complex macroscopic behaviour can arise in many-body systems with only very simple elements as a consequence of the combination of competition and inhomogeneity. This paper attempts to illustrate how statistical physics has driven this recognition, has contributed new insights and methodologies of wide application influencing many fields of science, and has been stimulated in return.
Nuevas tendencias en fundamentos teóricos y aplicaciones de la minería de datos aplicada a la clasificación de textos en lenguaje natural

Departamento de Lenguajes y Ciencias de La Computacion Escuela Tecnica Superior de Ingenieria Informatica Doctor of Philosophy by Jose Maŕia Carmona Cejudo In the last few years there has been a rapid increase in the amount of electronically available data. This has fostered the emergence of novel data mining and machine learning applications able to extract information and knowledge. A significant proportion of these data sources are in the form of natural text, something which involves difficulties not present in other domains, such as their unstructured nature and the high dimensionality of the datasets. Natural text has to be preprocessed so that it can be analyzed by computers, and learning algorithms have to be able to cope with such highdimensional feature spaces. Text mining techniques are invaluable to extract knowledge from natural text, as well as from other types of unstructured, alphabet-based data such as DNA strings. Many of these data sources are not available as closed-ended datasets, but rather as data streams of examples that arrive in a sequence over time. This includes many text data sources, such as web pages, emails or blog posts. Given the unbounded nature of these datasets, it is important to work with scalable algorithms that use reduced time and memory. Additionally, it is important for the algorithms to be able to adapt to changes in the underlying statistical distributions governing the data. This is especially difficult in the case of data streams, because of their high dimensionality. In order for text streams to be computationally tractable, it is necessary to previously reduce the dimensionality of the datasets, employing only the most relevant terms in the learning algorithms. However, the importance of the terms change over time, which in practice means that it is necessary to work under the assumption of a dynamic feature space. Keeping track of this evolving high-dimensional feature space is an intrinsically complex problem, since the importance of each feature depends on the others. Such challenges are tackled in this thesis. We present GNUsmail, a framework for text stream classification in the domain of electronic email, and use it to study the nature of concept drift in text streams. We introduce a framework for adaptive classification, ABC-DynF, which is able to adapt to dynamic feature spaces, incorporating new features and labels to previously existing models. We also study the problem of summarization in text streams, and propose TFSIDF / BM25, an approach for approximate weighting function approximation which makes it possible to extract keywords and construct word clouds from text streams in an efficient way. Finally, we present STFSIDF, an incremental approach for online feature selection which minimizes the number of weight recalculations while keeping continuously updated lists of the most relevant features. STFSIDF uses approximate algorithms to reduce the space complexity derived from the high dimensionality of the data sources.
The Segmentation Guidelines for the Penn Chinese Treebank (3.0)

This document describes the segmentation guidelines for the Penn Chinese Treebank Project. The goal of the project is the creation of a 100-thousand-word corpus of Mandarin Chinese text with syntactic bracketing. The Chinese Treebank has been released via the Linguistic Data Consortium (LDC) and is available to the public. The segmentation guidelines have been revised several times during the two-year period of the project. The previous two versions were completed in December 1998 and March 1999, respectively. This document is the third and final version. We have added an introduction chapter in order to explain some rationale behind certain decisions in the guidelines. We also include the English gloss to the Chinese words in the guidelines. In this document, we first discuss the notion of word and tests for wordhood that have been proposed in the literature. Then we give the specification for word segmentation. The specification is organized according to the potential Part-of-Speech tag of an expression and the internal structure of the expression. Next, we specify the treatment for some common collocations. Finally, we compare our guidelines with two segmentation standards: the first (Liu et al., 1993) is used in Mainland China and the second (CKIP, 1996) is used in Academia Sinica in Taiwan. Comments University of Pennsylvania Institute for Research in Cognitive Science Technical Report No. IRCS-00-06. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/ircs_reports/37 The Segmentation Guidelines for the Penn Chinese Treebank (3.0)
A Rule Based System for Speech Language Context Understanding

Speech or Natural language contents are major tools of communication. This research paper presents a natural language processing based automated system for understanding speech language text. A new rule based model has been presented for analyzing the natural languages and extracting the relative meanings from the given text. User writes the natural language text in simple English in a few paragraphs and the designed system has a sound ability of analyzing the given script by the user. After composite analysis and extraction of associated information, the designed system gives particular meanings to an assortment of speech language text on the basis of its context. The designed system uses standard speech language rules that are clearly defined for all speech languages as English, Urdu, Chinese, Arabic, French, etc. The designed system provides a quick and reliable way to comprehend speech language context and generate respective meanings.
Photogrammetric Reconstruction of the Great Buddha of Bamiyan, Afghanistan

In the valley of Bamiyan, Afghanistan, approximately 1700 years ago, two large standing Buddha statues were carved out of the sedimentary rock of the region. They were 53 and 38 m high and the larger one figured as the tallest representation of a standing Buddha in the world. In March 2001 the Taleban government militia demolished the colossal statues. After the destruction a group from ETH Zürich completed the computer reconstruction of the Great Buddha, which can serve as the basis for a physical reconstruction. This paper reports the results of the image‐based 3D reconstruction of the statue, performed on three different data‐sets in parallel and using different photogrammetric techniques and algorithms.
Community Media: A Global Introduction

Chapter 1 Introduction Chapter 2 1 Community Chapter 3 2 Access and Free Speech Chapter 4 3 Quality and the Public Interest Chapter 5 4 Diversity Chapter 6 5 Development Chapter 7 6 Access Reconfigured Chapter 8 7 Self-Representation Chapter 9 Useful websites Chapter 10 Bibliography
Survey On Data Security In Cloud Computing

Cloud Computing is a technique used to unite the power of various resources over network in a more efficient and scalable way to the end user. Cloud computing is one of the rapidly growing field of IT among the many business activities of large organization. It provides resources in the form of services as per usage base model. With the formation of cloud (pool) of various shared resources such as platform, application, infrastructure, storage over the network, it gives user on demand access to the resources on the scalable and dynamic way to avoid large upfront cost of investment. With the advantages, to access the services there is need to share resources and data including crucial information over the network, which lead to the hackers for various security issues. In this paper, we explore cloud computing along with its advantages with various security threats and existing authentication and encryption methods to provide security.
Decision Support System for Choosing a Model for a Software Development Life Cycle

Fuzzy arithmetic seems to be a well-developed and well-formalized branch of fuzzy sets theory. Nevertheless, there are some problems with its practical implementation. In practice, one can very often encounter the question of how to calculate the value of an arithmetic expression when its arguments are presented as linked fuzzy numbers. This article presents the generalization of Zadeh’s extension principle for arithmetic operations on fuzzy linked variables. Typical kinds of interaction between financial analyses parameters in industrial enterprises are discussed later. These interactions make use of nonlinear programming methods necessary to calculate the values of selected financial indices expressed by the fuzzy numbers. The article presents the problem of nonlinear programming applied to the calculation of the values of these indices. Additionally, the paper proposes the use of computer simulations in arithmetic operations on fuzzy linked variables. Furthermore, the example of gross profit calculations for two metallurgical companies is presented. The calculations done show that the interaction between the arguments of the arithmetic expression influences the final result significantly.
Recurrent neural networks for identification of nonlinear systems

A type of recurrent neural network is discussed which provides the potential for the modelling of unknown nonlinear systems with multi-inputs and multi-outputs. The proposed network is a generalization of the network described by Elman (1989). It is shown that the proposed network with appropriate neurons in the context layer can model unknown nonlinear systems. Based on a PID-like training objective function, the learning algorithm of the proposed network is considerably faster through the introduction of dynamic backpropagation, which is used to estimate the weights of both the feedforward and feedback connections. The techniques have been successfully applied to the modelling nonlinear plants and simulation results are included.
Planar Development of Digital Free‐Form Surfaces

Three are the main goals of this chapter. First, a detailed review of differential-geometry criteria for the developability of free-form surfaces is presented. Then, tools measuring accuracy of planar developments are introduced and analyzed. These tools are a prerequisite for evaluating the numerous methods/approaches proposed for generating flat developments of digital free-form surfaces whose level of involvement in many areas of CAD/CAM and Computer Graphics is constantly increasing. Finally, some of the most efficient surface flattening methods are analyzed and categorized followed by discussion of representative examples.
Understanding roi metrics for software test automation

Software test automation is widely accepted as an efficient software testing technique. However, automation has failed to deliver the expected productivity more often than not. The goal of this research was to find out the reason for these failures by collecting and understanding the metrics that affect software test automation and provide recommendations on how to successfully adopt automation with a positive return on investment (ROI). The metrics of concern were schedule, cost and effectiveness. The research employed an experimental study where subjects worked on individual manual and automated testing projects. The data collected were cross verified and supplemented with additional data from a feedback survey at the end of the experiment. The results of this study suggest that automation involves a heavy initial investment in terms of schedule and cost, which needs to be amortized over subsequent test cycles or even subsequent test projects. A positive ROI takes time and any decision to automate should take into consideration the profit margin per cycle and the number of cycles required to break even. In this regard, automation has been found to be effective for testing that is highly repetitive in nature like, smoke testing, regression testing, load testing and stress testing.
The application of parameter identification methods with competing systems to model a human interface device

Identification methods are applied to experimental data (hand motion) from a design study on a human interface system. The internal model of the Kalman filter employed for the state estimation implicitly utilizes two competing systems (involving an agonist and an antagonist human muscle actuator). The parameters (parsimonious representation) are obtained by minimizing the sums of the squares of the output error residuals, which are tested for whiteness. This technique is a generalization of a method borrowed from pharmacological studies.
Delta-sigma data converters : theory, design, and simulation

This comprehensive guide offers a detailed treatment of the analysis, design, simulation and testing of the full range of today's leading delta-sigma data converters. Written by professionals experienced in all practical aspects of delta-sigma modulator design, Delta-Sigma Data Converters provides comprehensive coverage of low and high-order single-bit, bandpass, continuous-time, multi-stage modulators as well as advanced topics, including idle-channel tones, stability, decimation and interpolation filter design
MPEG-4 Facial Animation: The Standard,Implementation and Applications

From the Publisher: This book concentrates on the animation of faces. The Editors put the MPEG-4 FA standard against the historical background of research on facial animation and model-based coding, and provide a brief history of the development of the standard itself. In part 2 there is a comprehensive overview of the FA specification with the goal of helping the reader understand how the standard really works. Part 3, forms the bulk of the book and covers the implementations of the standard on both encoding and decoding side. Several face animation techniques for MPEG-4 FA decoders are presented. While the standard itself actually specifies only the decoder, for applications it is interesting to look at the wide range of technologies for producing and encoding the FA contents. These include video analysis, speech analysis and synthesis, as well as keyframe animation. The last part of the book provides several examples of applications using the MPEG-4 FA standard. It will be useful for companies implementing products and services related to the new standard, researchers in several domains related to facial animation, as well as wider technical audience interested in new technologies and applications. · The main people involved in the standardization process are contributors to the book Provides several examples of applications using the MPEG-4 Facial Animation standard, including video and speech analysis This will become THE reference for the MPEG-4 Facial Animation Aids the understanding of the reasoning behind the standard specification, how it works and what the potential applications are Gives an overview of the technologies directly related to the standard and its implementation Essential reading for the Industry and research community especially engineers, researchers and developers.