Miracle-dz/UniFAR-FTUs huggingface dataset:
Verification of Group Address Registration Protocol using PROMELA and SPIN

This paper demonstrates robustness and e ectiveness of Group Address Registration Protocol (GARP) by successful use of SPIN(3). GARP is a datalink-level protocol for dynamically joining and leaving multicast groups on a bridged LAN. It is currently in the process of standardization as a part of IEEE P802.1p(1). SPIN is used to verify a model of multicast-base LAN described in PROMELA(3). The protocol has been proved to be free from incorrectness such as unspeci ed receptions and deadlocks. It has also been proved that there is no violation of a temporal claim for membership consistency. SPIN is found to be very powerful and easy to use without much knowledge of the formal veri cation. GARP is well modeled in PROMELA though it depends heavily on timers and multicasting which are not directly supported by PROMELA.
Parallel Adaptive Mesh Refinement

As large-scale, parallel computers have become more widely available and numerical models and algorithms have advanced, the range of physical phenomena that can be simulated has expanded dramatically. Many important science and engineering problems exhibit solutions with localized behavior where highly-detailed salient features or large gradients appear in certain regions which are separated by much larger regions where the solution is smooth. Examples include chemically-reacting flows with radiative heat transfer, high Reynolds number flows interacting with solid objects, and combustion problems where the flame front is essentially a two-dimensional sheet occupying a small part of a three-dimensional domain. Modeling such problems numerically requires approximating the governing partial differential equations on a discrete domain, or grid. Grid spacing is an important factor in determining the accuracy and cost of a computation. A fine grid may be needed to resolve key local features while a much coarser grid may suffice elsewhere. Employing a fine grid everywhere may be inefficient at best and, at worst, may make an adequately resolved simulation impractical. Moreover, the location and resolution of fine grid required for an accurate solution is a dynamic property of a problem's transient features and may not be known a priori. Adaptive mesh more » refinement (AMR) is a technique that can be used with both structured and unstructured meshes to adjust local grid spacing dynamically to capture solution features with an appropriate degree of resolution. Thus, computational resources can be focused where and when they are needed most to efficiently achieve an accurate solution without incurring the cost of a globally-fine grid. Figure 1.1 shows two example computations using AMR; on the left is a structured mesh calculation of a impulsively-sheared contact surface and on the right is the fuselage and volume discretization of an RAH-66 Comanche helicopter [35]. Note the ability of both meshing methods to resolve simulation details by varying the local grid spacing. « less
Automatic speaker recognition under adverse conditions

Speaker verification is the process of verifying the identity of a person by analysing their speech. There are several important applications for automatic speaker verification (ASV) technology including suspect identification, tracking terrorists and detecting a person’s presence at a remote location in the surveillance domain, as well as person authentication for phone banking and credit card transactions in the private sector. Telephones and telephony networks provide a natural medium for these applications. The aim of this work is to improve the usefulness of ASV technology for practical applications in the presence of adverse conditions. In a telephony environment, background noise, handset mismatch, channel distortions, room acoustics and restrictions on the available testing and training data are common sources of errors for ASV systems. Two research themes were pursued to overcome these adverse conditions: Modelling mismatch and modelling uncertainty. To directly address the performance degradation incurred through mismatched conditions it was proposed to directly model this mismatch. Feature mapping was evaluated for combating handset mismatch and was extended through the use of a blind clustering algorithm to remove the need for accurate handset labels for the training data. Mismatch modelling was then generalised by explicitly modelling the session conditions as a constrained offset of the speaker model means. This session variability modelling approach enabled the modelling of arbitrary sources of mismatch, including handset type, and halved the error rates in many cases. Methods to model the uncertainty in speaker model estimates and verification scores were developed to address the difficulties of limited training and testing data. The Bayes factor was introduced to account for the uncertainty of the speaker model estimates in testing by applying Bayesian theory to the verification criterion, with improved performance in matched conditions. Modelling the uncertainty in the verification score itself met with significant success. Estimating a confidence interval for the "true" verification score enabled an order of magnitude reduction in the average quantity of speech required to make a confident verification decision based on a threshold. The confidence measures developed in this work may also have significant applications for forensic speaker verification tasks.
Staff Development in Writing Instruction and the Reading/Language Arts Framework for California Public Schools: A Review of the Literature.

With the introduction of the "whole language" approach to literacy and an emphasis on "across the curriculum" learning, the effective instruction of writing has taken on an added importance during the past two decades in California. Recent public demands for a "back to basics" school curriculum where the mastering of individual skills is valued has prompted the issuance of rigorous statewide standards and the rewriting of the California Reading/Language Arts Framework. In response to these events, this paper answers the following questions: (1) What are the current practices to inservice teachers of upper elementary students in the instruction of writing? ; and (2) Which staff development models for the instruction of writing are best in accord with the new Reading/Language Arts Framework? The paper presents sections on the following: relevant definitions; a history of the topic/major contributors and contributions; major issues and controversies; model practices and programs; synthesis and analysis; conclusions; and recommendations. Contains 21 references and a 9-item bibliography. (NKA) ******************************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ******************************************************************************** Staff development in Writing Instruction and the Reading/Language Arts Framework for California Public Schools: A Review of the Literature Rose M. Witucki April 5, 1999 Presented to Dr. Mary Jo Lass In partial fulfillment for requirements of EDEL 501: Enhancing Teacher Effectiveness Through Instructional and Personal Strategies U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CN1 CENTER (ERIC) (I(This document has been reproduced as V:l received from the person or organization V::1 originating it. CA 0 Minor changes have been made to T-1 C4 improve reproduction quality. 0 California State University Long Beach Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. BESTCOPYAVAILABLE 2 1 PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) cs
Harnessing computational resources for efficient exhaustive search

6 Kurzfassung. 6 Introduction 1.1 Exhaustive Search . 7 1.2 SearchBench: A Tool for Exhaustive Backward Search . 8 1.3 Games and Puzzles . 9 1.4 State of the Art . 9 1.5 Thesis Structure . 10 Search Problems 2.1 Search Model . 12 2.2 Fixpoint Existence. 15 2.3 Computation Strategies . 17 2.4 Combining Backward and Forward Search . 20 SearchBench: Architecture and Interface 3.1 Project Overview. 22 3.2 User Interface . 23 3.3 Programmer Interface . 26 3.4 Indexing Functions. 34 3.5 Value Gather Functions . 35 SearchBench: Algorithms and Implementation 4.1 Retrograde Analysis . 40 4.2 Run-Time Prediction. 42 4.3 Verification. 45 4.4 Data Compression . 48 4.5 Parallelization. 49 Nine Men’s Morris 5.1 Rules. 51 5.2 Bushy. 52 5.3 Solving Nine Men’s Morris. 53 5.4 Midgame and Endgame State Space . 54 5.5 Database Computation . 57 5.6 Opening Search . 61 5.7 Database Compression . 64 Sliding Tile Puzzles 6.1 Optimally Solving the 15-Puzzle . 71 6.2 Many-Empty Databases . 72 6.3 One-Empty Databases . 75 6.4 Refinements and Results . 77 6.5 Hardest 15-Puzzle Position . 79 6.6 Solving the 24-Puzzle . 83 Conclusion 7.1 Summary and Lessons . 85 7.2 Future Research . 86 Appendix A: Nine Men’s Morris Statistics Appendix B: 15-Puzzle Test Suite Results Appendix C: 80-Move 15-Puzzle Positions References 6 ABSTRACT, KURZFASSUNG
FRAME-BY-FRAME HMM ADAPTATION FOR REVERBERANT SPEECH RECOGNITION

This paper describes a technique for robust speech recognition under a reverberant environment. Acoustic signals are distorted by their reflection inside a room, and this reverberation degrades the performance of automatic speech recognition system. When the effect of reverberation spans for several frames, dealing such the distortion due to reverberation simply as convolutive distortion is not sufficient. In such cases, it becomes necessary to consider the reverberation effect of other frames over current frame. In this paper, frame-synchronous estimation of reverberation component and HMM combination are proposed to deal with such distortion. The proposed technique was evaluated with an isolated word reverberant speech recognition task, and the result showed improvement in recognition performance. Moreover, use of Jacobian adaptation for a frame-synchronous model adaptation is investigated.
Linked, Interactive Views of Linked Data

To minimize the power consumption, the disclosed semiconductor integrated circuit device, comprises; a bias circuit for generating a predetermined voltage fixed between a first supply voltage and a second supply voltage; a driver circuit for receiving an inversion input signal and a non-inversion input signal each vibrating between the first and second supply voltages, for converting the received input signals into a signal vibrating between an output voltage of the bias circuit and the first supply voltage, and for driving a transfer path by the converted signal; a voltage divider circuit for dividing an output voltage of the bias circuit; and a receiver circuit for detecting the signal for driving the transfer path by use of an output of the voltage divider circuit as a reference voltage, and for converting the detected signal into a signal vibrating between the first/supply voltage and the second supply voltage.
Operative Computer Learning with Cooperative Task and Reward Structures

Introduction America is in a recession that is strangling budgets and challenging educational administrators to stretch existing resources. Compounding this challenge is the ever changing field of computer technology and the dire need to educate a technically competent work force. Currently, the United States is falling behind technological leaders such as Japan and Britain in our attempts to educate a technological work force. Although the reasons for this lack of success in teaching technology are diverse, the most common barriers are financial. These financial barriers are most noticeable in the regional inequities between suburban and rural schools and are manifested in the lack of computer equipment in schools, or outdated equipment not being replaced. (Mruk, 1987) Therefore, the teaching of computer technology is faced with a distinct educational problem: how can we educate more students using limited computer resources without sacrificing student aptitude or enjoyment of the learning event? Cooperative learning provides a plausible solution. Cooperative learning is a teaching strategy that encourages student success by alleviating overt competitiveness and substituting group encouragement. In cooperative learning, individuals work with their peers to achieve a common goal rather than competing against their peers or working separately from them. Research on the benefits of cooperative learning has shown an increase in academic achievement, positive attitudes towards learning and increased student satisfaction.
A Tutorial-style Introduction to Subspace Gaussian Mixture Models for Speech Recognition

This is an in-depth, tutorial-style introduction to the techniques involved in training a factor analyzed style of speech recognition system. Algorithms are explained in detail, with an emphasis on the how-to rather than the derivations. The recipe described here is both an extension to and a special case of the prior work we have done. Changes include a simplification of the procedure used to initialize these models, the introduction of “sub-models” which saves memory and may have modeling advantages, an extended approach to factor based speaker adaptation that uses the sub-models, and a mechanism to estimate a subspace-constrained version of Constrained MLLR transforms in this framework.
Still and Moving Image Compression Systems Using Multiscale Techniques

Multi-scale techniques have been popular methods for image and video compression. The basic idea behind these techniques is to decompose the original signals into several components of different scales, however the scale is defined, of different sizes. One then applies appropriate encoding strategies to different components to achieve compression by taking advantage of various properties. In this thesis, we review and present several new schemes of multi-scale techniques using linear and nonlinear systems. Linear techniques, which use linear filters for decomposition, have been thoroughly investigated and widely applied because of their simplicity in implementation and analysis. Herein we describe how to appropriately combine these techniques in order to process the signals more efficiently and advantageously; moreover, the picture quality of the quantized images can be improved. The sub-band coding technique is used as the basis for these combinations. As for the nonlinear technique, we would like to take advantage of the nonlinear features of images (such as edges) in compression to achieve compressing and enhancing of the images. Herein we design several nonlinear multi-resolution systems, using various nonlinear filters, to decompose the signals in a proper form. We show that, in terms of rate-distortion performance, where mean squared error is used as the distortion criterion, these schemes are close to, or even better than, JPEG standard, whereas the encoding and, especially, decoding complexity is lower than that of JPEG. We can obtain much better image quality (in the perceptual sense), however, by applying suitable simple and fast lossless compression schemes to sub-images. Simulation results are demonstrated to show the advantages and feasibility of the proposed scheme. In summary, we mention the current status and future trends of compression technologies.
Nonlinear Solid Mechanics: Theoretical Formulations and Finite Element Solution Methods

The main purpose of this book is to present all the ingredients for constructing the numerical models for representing the complex nonlinear behavior of structures and their components, which are represented as deformable solid bodies. Nonetheless, the book will also prove useful for those mostly interested in linear problems of mechanics, since the sure way to obtain a sound theoretical formulation of a linear problem goes through the consistent linearization of the more general nonlinear problem. The original French edition published by Hermes Science - Lavoisier Paris in 2006 was nominated for the Roberval Award for University Textbooks in French.
Enhanced Question Classification with Optimal Combination of Features

An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we introduce two new semantic features which improve the accuracy of classification. Furthermore, we developed a weighed approach to optimally combine different features. We also applied Latent Semantic Analysis (LSA) technique to reduce the large feature space of questions to a much smaller and efficient feature space. We adopted two different classifiers: Back-Propagation Neural Networks (BPNN) and Support Vector Machines (SVM). We found that applying LSA on question classification can not only make the question classification more time efficient, but it also improves the classification accuracy by removing the redundant features. Furthermore, we discovered that when the original feature space is compact and efficient, its reduced space performs better than a large feature space with a rich set of features. In addition, we found that in the reduced feature space, BPNN performs better than SVMs which are widely used in question classification. We tested our proposed approaches on the well-known UIUC dataset and succeeded to achieve a new record on the accuracy of classification on this dataset.
Image Processing Modules Implemented, Tested and Embedded in GIS tools

A Geographic Information System (GIS) is a software suite which provides a unified system for managing spatially referenced data. These systems deliver information to an end user through powerful visualisation and analysis tools which can be used to answer complex spatial queries. Current GIS software, such as ArcGIS, include a well developed suite of vector analysis tools which can be applied to geographic data, but these tools have only a limited ability to analyse raster data. Image processing algorithms provide an effective way to enhance raster data or to detect features of interest in raster data. The aim of this project is to develop an Image Processing Framework where user-developed image processing modules can be embedded within a desktop GIS tool, namely ArcGIS. This framework allows a GIS user to apply image processing techniques to rasters to extract relevant features. These image processing techniques are packaged into individual modules which are loaded into the framework using a plug-in architecture. This system can also be extended by writing additional plug-in modules. A novel software methodology was proposed for this project. The software development process was viewed a means of acquiring knowledge about the systems that needed to interact, and codifying this knowledge. In order to do this, a special test harness was created which unifies concepts from example code, unit testing, and documentation. This test harness allows a developer to create Code Experiments: short segments of code which demonstrate a particular aspect of the ArcGIS API. These segments of code are used to document and demonstrate the interactions between the Image Processing Framework and the ArcGIS API. This project successfully demonstrates linear feature detection from aeromagnetic datasets of the Yilgarn Craton in Western Australia.
Hidden Markov models and artificial neural networks for speech and speaker recognition

These Ecole polytechnique federale de Lausanne EPFL, n° 1860 (1998) Reference doi:10.5075/epfl-thesis-1860Print copy in library catalog Record created on 2005-03-16, modified on 2016-08-08
A Study of User Attitudes toward Persistent Cookies

In the tumultuous environment of rapid development standards and guidelines known as the Internet, the rights of the individual frequently are swept under by the mad rush of organizations to exploit the commercial potential of this brave new world. Civil and legal institutions are just now catching up to the problems faced and expected in this environment. Individual privacy, personal security, and the protection of property represent some of the most fundamental rights citizens have come to expect. One of these areas under scrutiny is the use of persistent cookies. This study seeks to identify and evaluate individual users awareness and opinions toward persistent cookies. The findings should provide valuable insight into the need for additional marketing education and privacy protection for users of these virtual markets, as well as provide a foundation for subsequent research into the use of such covert online data collection methods.
Time series analysis: forecasting and control rev. ed.

This text is divided into 4 parts: 1) stochastic models and their forecasting 2) stochastic model building 3) transfer function model building and 4) design of discrete control schemes. The book presents methods for building identifying fitting and checking models for time series and dynamic systems. Methods discussed are appropriate for discrete (sampled-data) systems where observation of the system and an opportunity to take control action occur at equally spaced intervals of time. These time series and dynamic models are illustrated in 3 important areas of application: 1) the forecasting of future values of a time series from current and past values; 2) the determination of the transfer function of a system--the determination of a dynamic input-output model that can show the effect on the output of a system subject to inertia of any given series of inputs; and 3) the design of simple feed forward and feedback control schemes by means of which potential deviations of the system output from a desired target may be compensated so far as possible.
Applying Goal-Oriented Action Planning to Games

A number of games have implemented characters with goal directed decision-making capabilities. A goal-directed character displays some measure of intelligence by autonomously deciding to activate the behavior that will satisfy the most relevant goal at any instance. Goal-Oriented Action Planning (GOAP) is a decision-making architecture that takes the next step, and allows characters to decide not only what to do, but how to do it. But why would we want to empower our characters with so much freedom?
Digital Image Ballistics from JPEG Quantization: A Followup Study

The lossy JPEG compression scheme employs a quantization table that controlstheamountofcompressionachieved. Becausedifferentcamerastypicallyemploy different tables, a comparison of an image’s quantization scheme to a database of known cameras affords a simpletechniqueforconfirmingordenying an image’s source. This report describes the analysis of quantization tables extracted from 1,000,000 images downloaded from Flickr.com.
Time-scoped searching of encrypted audit logs: (Extended abstract)

In this paper we explore restricted delegation of searches on encrypted audit logs. We show how to limit the exposure of private infor- mation stored in the log during such a search and provide a technique to delegate searches on the log to an investigator. These delegated searches are limited to authorized keywords that pertain to specific time periods, and provide guarantees of completeness to the investigator. Moreover, we show that investigators can efficiently find all relevant records, and can authenticate retrieved records without interacting with the owner of the log. In addition, we provide an empirical evaluation of our techniques using encrypted logs consisting of approximately 27, 000 records of IDS alerts collected over a span of a few months.