Miracle-dz/UniFAR-FTUs huggingface dataset:
Latent variable decomposition for posteriors or likelihood based subband ASR

Latent variable decomposition permits factorisation of posterior probability based, or likelihood based, speech unit discriminant functions into a composition of simpler functions which can be analysed separately and evaluated more accurately in the presence of band-limited noise, or other source of data mismatch. See [2,7] for a more self contained introduction to this subject. In this report we present the essential theoretical issues, and implementation details, for the key points concerning this approach to multiband ASR. In particular, we show that the posteriors and likelihood based multiband decompositions are very closely linked.
An Evaluation of the S2Ia switched-current architecture for (delta)(sigma) modulator ADCs

Switched-Current (SI) is a design methodology by which discrete time, current mode, analog circuits can be implemented using standard digital CMOS processes, allowing the addition of analog signal processing circuits, analog to digital converters (ADCs), digital to analog converters (DACs) and other analog and mixed-signal circuits to otherwise digital only microchips without the need and expense of any extra fabrication steps. SI circuits operate by employing a secondary effect in CMOS circuits, a transistor's gate capacitance, to store charge and thus form a current memory cell. A current memory cell is one of the basic building blocks found in most SI circuits and is usually the distinguishing feature of the various approaches to SI circuit design. Delta Sigma Modulators (DSMs) are discrete time, mixed-signal circuits making them well suited to implementation using the SI methodology. These circuits can form the basis of either an A D C or DAC and thus provide a good example of the SI technique employing a particular current memory cell implementation. For this work, a First Order DSM-based A D C was designed and simulated to verify the feasibility of a variant of the S I Switched-Current Memory Cell architecture, the S Ia Switched-Current Memory Cell, in a low-voltage, digital, 0.5/j.m CMOS process. The A D C design was targeted towards voiceband (4kHz bandwidth) applications over which it achieved a 6-bit resolution and separately attained a greater than 80kHz bandwidth. Extension of the First Order DSM employed in this design to a Second Order D S M would increase the
A Method for Extracting Word Lists from the 361-billion Token Google Books Corpus

The recent release by Michel et al. (2011) of n-gram data on the Google Books corpus allows the creation of new English word frequency lists based on one of the largest collections of text in the world. However, the amount of data involved creates a number of technical problems. This article describes the process of creating a software tool to overcome those problems, and then provides instructions for extracting word lists of various kinds. The tool is free to download, adapt and share under an open-source software license. An example of what can be done – an update of existing BNC and GSL/AWL word frequency lists using data from the corpus – is given at the end of the article. Introduction: About Word lists and Corpora Lists of the most frequent words or word families in English can be useful for learning and teaching, whether memorized directly or used indirectly to create level appropriate materials and tests. Lists used include the General Service List (West, 1953) based on the Brown corpus (Francis & Kucera, 1979), the Academic Word List supplement to the GSL (Coxhead, 2000), the British National Corpus lists (Leech Rayson & Wilson, 2001; Nation, 2006) and the JACET 8000 (Ishikawa et al., 2003), also based on the British National Corpus but supplemented with six million tokens of text targeted at the needs of Japanese students. The lists above are the ones most commonly seen in the Japanese EFL University context while larger and more up-to-date alternatives do exist, they have restrictions on access and distribution that limit their utility in the classroom. Each word list is based on a corpus, and inherits strengths and weaknesses from that corpus. This article describes a process for extracting a new word frequency list from the Google Books corpus using lists prepared and released by Michel et al. (2011). These lists have a number of
AVS Quick Mode Selection Algorithm Based on Adaptive Threshold

In accordance with the complexity of AVS motion search and block mode selection algorithm, the paper poses a AVS quick mode selection algorithm based on premature termination norm and adaptive threshold. The algorithm can avoid much cost calculation of the useless macro block and save a lot of time on moving search and block mode selection in encoding process. Experimental results show that the computational capacity saved by the algorithm can amount to 78.6% at most, and the dropped level of Bits is larger than PSNR. The encoding speed can be effectively increased without the lower encoding performance.
ARIMAA: developing a higher ranked fall back move generator using a relational database

Patrick McKee ARIMAA: DEVELOPING A HIGHER RANKED FALL BACK MOVE GENERATOR USING A RELATIONAL DATABASE Dr. Nancy Tinkham, Ph.D. Master of Science in Computer Science Our approach to playing the game of Arimaa understands that the game was created to showcase the limits of brute force computing power. Using a relational database, we will be able to view similar situations that have already been played out, inventory a number of suitable reactions and make the best move given a number of attributes. This results in us making a decision that can theoretically result in a win, and hopefully will. Measurable positive results have been procured specifically from the area of concentration component of the research. In the area of concentration component we target a specific square on the board based on prior moves. This square becomes the focal point of our research that we develop an attribute index for. After querying the database to see if we can find a previous game that contained this exact same area of concentration, we either make a move or fall back. If we fall back, we take into account our developed shrinking method where we target specific pieces whose strengths essentially do not matter in terms of making a move. It is with this action that we have developed measurable positive results that, with further research, may amount to a permanent fixture as a better fall back move generator.
THE IMPACT OF WRITE BACK ON CACHE PERFORMANCE

This paper quantifies the impact of write policies and allocation policies on the cache performance. Adding write back to a cache design increases hardware cost, since additional storage for dirty bits is required. Furthermore, write back is not always faster. This paper derives a criterion which allows to check easily whether write back improves the performance of a given memory system. This is done with the help of extensive cache simulations on a MIPS RISC architecture with SPEC92 benchmarks as workload.
A model of information use behavior by scientists

The services that are provided in a library are at various levels and varieties. Library automation services such as computerized OPAC, e-mail based reference service etc., are be- ing provided. Also, Web based services like Web Opac, E-Journals, CD-ROM Collection search, Bibliographical database services such as Engineering village 2, Compendex, Chemi- cal Abstract, Web of science, are being provided. The researcher approaching the library in search of information must be satisfied with proper provision for information. With this in view, it seems essential to provide the right information to the right user at the right time and in the right form. In order to provide for such a information facility in the digital en- vironment, library should be managed more effectively and efficiently. Library automation services such as computerized OPAC, e-mail based reference service etc., are being provided. Profile based services like my TOC, Document delivery services are also provided. Specialised departmental library services like Envis, Bio-informatics etc., are made available. Union Catalogue of books and journals have been created. In a digital environment information is always available in digital form. This provides an oppor- tunity for enhanced service effectiveness. For this purpose, library collection and services are devel- oped in response to the demands of the Digital environment in the form of e-books and e-journals. There are a number of barriers to information in the pre-digital environments which may be overcome in the digital environment. Therefore user needs such as- current approach, everyday approach, ex- haustive approach, Catching up approach can be handled by a variety of services tailor made to serve such needs. Scientists are an extraordinary diverse group of professionals. An attribute common to all scientists is their use of information. To view the information seeking behavior of scientists within a conceptual framework of the scientists, they must be considered as an information processor. This article uses this chosen framework to discuss information seeking behaviour of scientists, reviewing selected literature and empirical studies from information centers and proposes a model for information use based on the studies on the relationship between task performance and information searching by end users.
Managing Consistency of Business Process Models across Abstraction Levels

Process models support the transition from business requirements to IT implementations. An organization that adopts process modeling often maintain several co-existing models of the same business process. These models target different abstraction levels and stakeholder perspectives. Maintaining consistency among these models has become a major challenge for such an organization. For instance, propagating changes requires identifying tacit correspondences among the models, which may be only in the memories of their original creators or may be lost entirely. Although different tools target specific needs of different roles, we lack appropriate support for checking whether related models maintained by different groups of specialists are still consistent after independent editing. As a result, typical consistency management tasks such as tracing, differencing, comparing, refactoring, merging, conformance checking, change notification, and versioning are frequently done manually, which is time-consuming and error-prone. This thesis presents the Shared Model, a framework designed to improve support for consistency management and impact analysis in process modeling. The framework is designed as a result of a comprehensive industrial study that elicited typical correspondence patterns between Business and IT process models and the meaning of consistency between them. The framework encompasses three major techniques and contributions: 1) matching heuristics to automatically discover complex correspondences patterns among the models, and to maintain traceability among model parts—elements and fragments; 2) a generator of edit operations to compute the difference between process models; 3) a process model synchronizer, capable of consistently propagating changes made to any model to its counterpart. We evaluated the Shared Model experimentally. The evaluation shows that the framework can consistently synchronize Business and IT views related by correspondence patterns, after non-simultaneous independent editing.
Sources of Variability in a Proteomic Experiment

SOURCES OF VARIABILITY IN A PROTEOMIC EXPERIMENT Scott D. Crawford Department of Statistics Master of Science The study of proteomics holds the hope for detecting serious diseases earlier than is currently possible by analyzing blood samples in a mass spectrometer. Unfortunately, the statistics involved in comparing a control group to a diseased group are not trivial, and these difficulties have led others to incorrect decisions in the past. This paper considers a nested design that was used to quantify and identify the sources of variation in the mass spectrometer at BYU, so that correct conclusions can be drawn from blood samples analyzed in proteomics. Algorithms were developed which detect, align, correct, and cluster the peaks in this experiment. The variation in the m/z values as well as the variation in the intensities was studied, and the nested nature of the design allowed us to estimate the sources of that variation. The variation due to the machine components, including the mass spectrometer itself, was much greater than the variation in the preprocessing steps. This conclusion inspires future studies to investigate which part of the machine steps is causing the most variation.
Using metrics from multiple layers to detect attacks in wireless networks

The IEEE 802.11 networks are vulnerable to numerous wireless-specific attacks. Attackers can implement MAC address spoofing techniques to launch these attacks, while masquerading themselves behind a false MAC address. The implementation of Intrusion Detection Systems has become fundamental in the development of security infrastructures for wireless networks. This thesis proposes the designing a novel security system that makes use of metrics from multiple layers of observation to produce a collective decision on whether an attack is taking place. The Dempster-Shafer Theory of Evidence is the data fusion technique used to combine the evidences from the different layers. A novel, unsupervised and self- adaptive Basic Probability Assignment (BPA) approach able to automatically adapt its beliefs assignment to the current characteristics of the wireless network is proposed. This BPA approach is composed of three different and independent statistical techniques, which are capable to identify the presence of attacks in real time. Despite the lightweight processing requirements, the proposed security system produces outstanding detection results, generating high intrusion detection accuracy and very low number of false alarms. A thorough description of the generated results, for all the considered datasets is presented in this thesis. The effectiveness of the proposed system is evaluated using different types of injection attacks. Regarding one of these attacks, to the best of the author knowledge, the security system presented in this thesis is the first one able to efficiently identify the Airpwn attack.
Advanced Microwave Tube Computer Experiments Research

Abstract : As one of the pioneering efforts in object-oriented (OO) scientific programming, XOOPIC has demonstrated conclusively the benefits of the methods. The code extensibility and development costs are lower, and the development more rapid than traditional methods. Similar methods of simplifying development and maintenance are now propagating into industrial and laboratory codes, including MRC's MAGIC and AF Phillips Lab's ICE-PIC.
Understanding Digital Signal Processing

From the Publisher: This is undoubtedly the most accessible book on digital signal processing (DSP) available to the beginner. Using intuitive explanations and well-chosen examples, this book gives you the tools to develop a fundamental understanding of DSP theory. The author covers the essential mathematics by explaining the meaning and significance of the key DSP equations. Comprehensive in scope, and gentle in approach, the book will help you achieve a thorough grasp of the basics and move gradually to more sophisticated DSP concepts and applications.
UAV Parameter Estimation with Gaussian Process Approximations

Madu Prasad Hemakumara Doctor of Philosophy (Research) The University of Sydney March 2013 UAV Parameter Estimation with Gaussian Process Approximations Unmanned Aerial Vehicles (UAVs) provide an alternative to manned aircraft for risk associated missions and applications where sizing constraints require miniaturized flying platforms. UAVs are currently utilised in an array of applications ranging from civilian research to military battlegrounds. A part of the development process for UAVs includes constructing a flight model. This model can be used for modern flight controller design and to develop high fidelity flight simulators. Furthermore, it also has a role in analysing stability, control and handling qualities of the platform. Developing such a model involves estimating stability and control parameters from flight data. These map the platform’s control inputs to its dynamic response. The modeling process is labor intensive and requires coarse approximations. Similarly, models constructed through flight tests are only applicable to a narrow flight envelope and classical system identification approaches require prior knowledge of the model structure, which, in some instances may only be partially known. This thesis attempts to find a solution to these problems by introducing a new system identification method based on dependent Gaussian processes. The new method would allow for high fidelity non-linear flight dynamic models to be constructed through experimental data. The work is divided into two main components. The first part entails the development of an algorithm that captures cross coupling between input parameters, and learns the system stability and control derivatives. The algorithm also captures any dependencies embodied in the outputs. The second part focuses on reducing the heavy computational cost, which is a deterrent to learning the model from large test flight data sets. In addition, it explores the capabilities of the model to capture any non-stationary behavior in the aerodynamic coefficients. A modeling technique was developed that uses an additive sparse model to combine global and local Gaussian processes to learn a multi-output system. Having a combined approximation makes the model suitable for all regions of the flight envelope. In an attempt to capture the global properties, a new sampling method is introduced to gather information about the output correlations. Local properties were captured using a non-stationary covariance function with KD-trees for neighbourhood selection. This makes the model scalable to learn from high dimensional large-scale data sets.
Identification of Track Irregularity using Wavelet Transfer Function

This paper presents a methodology for identifying track irregularity using a wavelet transfer function. An equivalent wavelet SISO (single-input single-output) transfer function is defined by the measured track geometry and the acceleration data measured at a bogie of a train. All the measured data with various sampling frequencies were rearranged according to the constant 25cm reference recording distance of the track recording vehicle used in the field. Before applying the wavelet transform, measured data were regressed by eliminating those out of the range. The inverse wavelet transfer function is also formulated to estimate track geometry. The closeness of the estimated track geometry to the actual one is evaluated by the coherence function and also by FRF (frequency response function). A track irregularity index is defined by comparing the variance of the estimation error from the intact condition and that from the current condition. A simulation study has been carried out to examine the proposed algorithm.
Girlfriend Abuse as a Form of Masculinity Construction among Violent, Marginal Male Youth

This study focuses on the development and effect of familial and gender ideologies on the masculine identities of thirty marginal male youth aged thirteen to seventeen years, all of whom were gang members or belonged to violent male peer groups. Qualitative, indepth interviews uncovered protest and negative masculine identities. Their abusive behavior, directed at girlfriends, gays, and racial minorities, is suggested to be a response to blocked access to traditional institutional benefits of patriarchy. Violence compensated for perceived threats to their masculine identities. The construction of masculinity was an ongoing process for these boys, negotiated and developed on a daily basis using available resources in their social space location. Significant differences within the sample explain the variation in the degree to which they embraced patriarchal-authoritarian models of family and gender, and variation in the forms and seriousness of their physical and sexual violence.
Interactive change of lighting in the portrait images

We are facing a number of applications for altering portrait photographs using the help of artificial intelligence. Apart from the entertainment purposes, modern computer technologies can also help us get dynamic effects from static images, an example of which is the subject of this study. Dealing with the change of lighting in portraits photographs through realtime rendering, this paper provides a method of obtaining an image with variable light source that affects the facial features generated on the basis of the face tracking data acquired from the existing static photograph. Thus, we get a portrait with altered light, as if such a source was present at the actual moment of photographing. This method aims to improve or even change the visual experience when viewing the image, so that its further application corresponds to the given context.
Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools

Bioinformatics for Beginners provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis, and demonstrates with examples targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis and points to many further study options. Avoids non-essential coverage yet fully describes the field for beginners - in approximately 200 pages of text Explains the molecular basis of evolution to place bioinformatic analysis in biological context Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools Over 100 figures aid in concept discovery and illustration
ANALISIS PENGARUH FAKTOR FUNDAMENTAL TERHADAP HARGA SAHAM SYARIAH YANG LISTING DI JAKARTA ISLAMIC INDEX (JII)

Saham syariah sudah mulai terlihat pertumbuhannya, hal ini berarti bahwa saham syariah menjadi pilihan para investor untuk menanamkan modalnya pada perusahaan-perusahaan yang berbasis syariah. Untuk menjadi investor pada saham termasuk saham syariah, maka kita harus bisa memprediksikan harga saham di masa yang akan datang agar bisa meraih keuntungan dari investasi tersebut. Banyak penelitian yang membahas tentang saham tetapi masih jarang yang mengangkat saham syariah. Penelitian ini bertujuan untuk mengetahui dan menganalisis pengaruh faktor fundamental yang dilihat dari rasio EPS, DER, ROA dan ROE terhadap harga saham syariah yang listing di JII pada tahun 2016. Saham – saham syariah yang dipilih adalah 18 perusahaan (dari 30 saham) yang listing di JII sejak tahun 2014 sampai sekarang dan tidak pernah mengalami pergantian. Analisis data menggunakan analisis regresi linier berganda dengan SPSS versi 17. Hasil analisis menunjukkan bahwa faktor fundamental (EPS, DER, ROA dan ROE) secara bersama-sama berpengaruh signifikan terhadap harga saham. Secara parsial hanya EPS dan ROE yang berpengaruh positif dan signifikan terhadap harga saham syariah yang listing di JII, sedangkan ROA berpengaruh negatif signifikan terhadap harga saham dan DER tidak berpengaruh terhadap harga saham.