Miracle-dz/UniFAR-FTUs huggingface dataset:
Cluster-Based Query Expansion Using Language Modeling for Biomedical Literature Retrieval.

Cluster-based Query Expansion Using Language Modeling for Biomedical Literature Retrieval and Classification Xuheng Xu Xiaohua Hu, Ph.D. The tremendously huge volume of biomedical literature, scientists' specific information needs, long terms of multiples words, and fundamental problems of synonym and polysemy have been challenging issues facing the biomedical information retrieval community researchers. Search engines have significantly improved the efficiency and effectiveness of biomedical literature searching. The search engines, however, are known to return many results that are irrelevant to the intention of a user’s query, in other words, perform not very sound in terms of precision and recall. To further improve precision and recall of biomedical informational retrieval, various query expansion strategies are widely used. In this thesis, we concentrate on empirical comparison, experiments and evaluations in investigating query expansion methods. We also use the findings as an empirical justification for cluster-based query expansion. We have investigated broadly many methods of query expansion such as local analysis, global analysis, ontology-based term reweighting across various search engines and obtained important insights. Among the findings, two-stage concept-based latent semantic analysis strategy and cluster-based query expansion have been presented and the Singular Value Decomposition (SVD) technique in the Latent Semantic Indexing (LSI) is utilized in the proposed method. In contrast to other query expansion methods, our strategy
The Slaying of Lady Mondegreen, being a Study of French Tonal Association and Alignment and their Role in Speech Segmentation

This dissertation investigates French intonational structure and the role of languagespecific intonational cues to speech segmentation, the listener’s task of determining where words begin and end. The Lady Mondegreen of the title never existed: she was created in the imagination of a young child who missegmented a line from one of her favorite poems. French intonation is characterized by an obligatory fundamental frequency (f 0) rise on the last syllable of a phrase (1a) and an optional early rise near the beginning (1b). (1) a. Les gamins sages jardinaient. ‘The good kids were gardening. ’ b. Les gamins sages jardinaient. A production experiment examined the text-to-tune alignment of these rises, the timing of f 0 peaks and valleys with respect to segmental landmarks. The low starting point of the early rise was consistently located at the function word-content word boundary (e.g., the determiner-noun boundary in les | gamins sages). There was also sometimes an f 0 inflection or elbow at that boundary, even where there was no early rise. The evidence supports a model in which the early rise is a bitonal phrase accent and the late rise a bitonal pitch accent. Three perception experiments examined whether the early rise and f 0 elbow serve as cues to content word beginnings. Natural speech was recorded and f 0 manipulated ii through resynthesis. In Experiment 1, participants listened to noise-masked minimal and near-minimal pairs of phrases differing only in segmentation and presence versus absence of an early rise (e.g., le niveau de mécénat ‘the level of patronage’/ le niveau de mes sénats ‘the level of my senates’) and indicated what they heard. Listeners interpreted an early rise as a marker of a content word beginning. In Experiment 2, the timing of the early rise was manipulated in minimal pairs of nonwords. Sequences like were perceived as two words (mes lamondines ‘my lamondines’) when the early rise started at the second syllable ([ ]) and as a single word (mélamondine) when it started at the first syllable ( ). Using a similar paradigm, Experiment 3 showed that not only early rises, but also simple f 0 elbows, cued content word beginnings.
Vision-Based System for Occupancy and Posture Analysis

Over the past few years advances in computer vision have given promise of robust systems for safety applications in cars. In particular, we seek to develop a way to deploy a passenger-side airbag that is aware of the occupant in the passenger seat. There is hope to avoid extensive injury due to airbag deployment in multiple passenger classes; children, babies, adults. Our approach is to use a combination of two computer vision methods: invisible structured lighting and correlation-based stereo matching. The environment of an automobile poses challenges to these methods. Computer vision relies heavily on intensity values to function properly, and the interior environment of a car has a large amount of different lighting conditions. To get around this caveat the monochrome cameras cut light below 850nm. This reduces our consideration of illumination values to near infrared and produces a monochrome image of the target. Structured lighting improves textured-ness and gives further constraint on the depth of the target [1]. Projecting a sine-wave grating onto the scene that has a known structure with each stripe having a random width. This is to ensure accuracy when using correlation-based window matching using brightness values in each image. When stripes are of the same width there is a “phase ambiguity” about what pixel belong to which stripe. It is important to ensure that each adjacent stripe is of a different width to ensure good matching. The method just described eliminates this problem during stereo matching. Stereo matching uses a correlation window that is applied to the “reference” image and scans the other image in the stereo pair for a matching brightness [3]. The correlation window achieves its best results when it is larger than the largest stripe in the image. This avoids the problem of areas in the disparity map where we can lose depth information due to a window that is too small. For a good treatment of a correlation window based matching see [3].
Influence of the clay content of a lime-treated soil on its compression strength

Lime treatment is an efficient way to stabilize soils. However, its efficiency is very limited in sandy soil for which cement treatment is often more adapted. It is believed that very low clay content can be enough to drastically increase the properties of a sandy soil by lime treatment. Hence, adding a low quantity of clayey materials in addition to lime can make sand stabilization possible. In this context, this paper presents the preliminary results of an experimental program carried out on different sandbentonite mixtures treated with lime and then compacted at normal optimum Proctor conditions. Lime-treated soils have been uniaxially compressed at different curing times (up to 56 days). The results show that the strength properties of lime-treated soils are considerably increased because of relatively low contents of bentonite added in pure sand. Also, beyond a given bentonite content, the soil strength starts to decrease when bentonite is further added. In parallel, a comparison is also made with the Proctor compaction curves. Starting from pure sand, the Proctor optimum density increases with the bentonite content, reaches a maximum density and then decreases with addition of clay.
Solving Heyawake puzzles using Answer Set Programming

This report exmamines automatic solving of Heyawake puzzles usingAnswer Set Programming. Heyawake is somewhat similar to the morewell known Sudoku but has not been as extensively researched whichmakes the game very interesting to examine.The game has previously been proven to be NP-complete so the focushas been on implementing the solver instead of making it fast althoughsome optimizations has been made.Answer Set Programming has long been used to solve NP-completeproblems and for Heyawake it is possible to solve normal sized puzzlesvery fast. Optimizing the solver proved to be hard unless you have extensiveknowledge of the Answer Set Programming solver that is used.
The PETS04 Surveillance Ground-Truth Data Sets

This paper summarizes the 28 video sequences available for result comparison in the PETS04 workshop. The sequences are from about 500 to 1400 frames in length, for a total of about 26500 frames. The sequences are annotated with both target position and activities by the CAVIAR research team members.
An eLearning narration modality study: In pursuit of faster, cheaper, and almost the same

AN ELEARNING NARRATION MODALITY STUDY: IN PURSUIT OF FASTER, CHEAPER, AND ALMOST THE SAME Richard David Homer Old Dominion University, 2012 Director: Dr. Richard C. Overbaugh The purpose of this study is to examine the effects o f five different eLearning modality practices on workplace learning and perceived learner satisfaction. Using a factorial posttest comparison design (with a control group), this experimental field study explored the learning effects and learner perceived satisfaction associated with the use of different modality approaches within an eLearning course delivered in a workplace. More than 3,000 study participants, who are part o f a U.S. federal workforce, where randomly assigned to one of five narration groups. A Learning Management System (LMS) gathered demographic data, administered the course, recorded individual test scores, learner satisfaction scores, and recorded times associated with course completion. Findings from this study suggest that in a U.S. workplace environment, eLearning using text-only (i.e., no voice narration) has similar learning outcomes to eLearning with narration. The important potential benefit of this finding is the reduction to costs associated with eLearning development and implementation—that is, faster and cheaper eLearning development while achieving almost the same learning outcomes. Coupled with the learner satisfaction finding in this study, that workplace learners preferred text-only over any of the forms of narration in this study, then a strong case begins to form for using text-only with straightforward content, for eLearning to be implemented in a U.S. workplace setting. Copyright, 2012, by Richard David Homer, All Right Reserved. This dissertation is dedicated to my wife. Helen—thank you for your love, encouragement, and patience. ACKNOWLEDGEMENT I want to first thank my wife who is, and always has been, there for me throughout our journey. I want to thank Dr. Richard Overbaugh, my chair and friend who stuck with me until my successful conclusion. I also want to thank all the members o f my committee for their time and commitment to help and guide those who think they can. I want to thank all the other individuals in my life who have been supportive of this effort, especially, Aaron, Carrie, and Venus—your roles helped me succeed, and for that, I am grateful. Finally, I want my daughter Stefanie to know that I love her and that all things are possible when the right measure of patience and persistence are applied.
Api protocol compliance in object-oriented software

Modern software development is highly reliant on reusable APIs. APIs often define usage protocols that API clients must follow in order for code implementing the API to work correctly. Loosely speaking, API protocols define legal sequences of method calls on objects. In this work, protocols are defined based on typestates (Strom and Yemini, 1986; DeLine and Fahndrich, 2004b). Typestates leverage the familiar intuition of abstract state machines to define usage protocols. The goal of this work is to give developers comprehensive help in defining and following API protocols in object-oriented software. Two key technical contributions enable the proposed approach: (1) Object state spaces are defined with hierarchical state refinements. Hierarchical state spaces make specifications more succinct, elegantly deal with subtyping, express uncertainty, and enable more precise reasoning about aliasing. (2) A novel abstraction, called access permissions, combines typestate and aliasing information. Access permissions capture developers' design intent regarding API protocols and enable sound modular verification of API protocol compliance while allowing a great deal of flexibility in aliasing objects. This dissertation demonstrates that typestate-based protocols with state refinement and access permissions can be used for automated, static, modular enforcement of API protocols in practical object-oriented software. Formal and empirical results show that the presented approach captures common API protocols succinctly, allows sound modular checking of protocol compliance in object-oriented code, can be automated in tools for mainstream programming languages that impose low annotation burden on developers, and can check API protocols in off-the-shelf software with higher precision than previous approaches. This work puts automatic API protocol compliance checking within reach of being used in practice. It will enable rapid and correct use of APIs during initial construction and ensure that API clients and implementations remain consistent with the specified protocol during maintenance tasks.
Gowin's Knowledge Vee: A Heuristic for Adult Religious Education

The application of Gowin's knowledge vee as a means to design instruction for adult Bible study was investigated in this study. The study was designed to determine whether subjects using this instructional approach differed from subjects using traditional instructional materials regarding their attitudes toward Bible study, attendance, knowledge retention, application of study materials to life, and recruitment of new class members.
The Fast Fourier Transform as a Signal Processing Technique.

Abstract : The proliferation of digital equipment for use in making all types of measurements has necessitated drastic changes in the signal detection techniques used to quantify measured signals. More specifically, there has been an increased use of the kinds of digitizers whose output consists of sequential time slices of the measured signal in binary coded values that correspond to amplitude and time. This type of information is directly transferrable to a computer memory, where it can be processed by a wide variety of digital techniques. One of the most useful digital processes used to resolve amplitude and phase spectra from a digitized time-domain signal is the fast Fourier transform (FFT). This document attempts to give the reader a sound understanding of what the FFT does and how it can be applied to various measurement needs. (Author)
Evaluating Algorithms for Creation of Hierarchical Category Systems

1,4-diacyloxybutenes are prepared by reacting a 1,3-butadiene with a carboxylic acid and oxygen in the presence of a catalyst in a reactor, by a process in which the 3,4-diacyloxybutene formed as a by-product in the reaction is separated off from the reaction mixture, and some or all of this 3,4-diacyloxybutene is recycled to the reactor.
Analysis of the NETSCIENCE Social Network

This paper presents a basic analysis of the Net Science database together with a description of the techniques for social network analysis. The database was provided by M. Newman in May 2006 and contains a network of scientists who together coauthored the network theory and experiment. The analysis was performed using the Pajek software. Numerous pictures and tables have been created to illustrate the structure and show the most important parts of this network. Some of the notable findings include important groups of actors whose collaboration is important for the discoveries and development of the theory of networks, and those actors which are important with respect to the whole graph. Keywords-social network; pajek software; core; clique; island; centrality
Palmo : a novel pulsed based signal processing technique for programmable mixed-signal VLSI

In this thesis a new signal processing technique is presented. This technique exploits the use of pulses as the signalling mechanism. This Palmo1 signalling method applied to signal processing is novel, combining the advantages of both digital and analogue techniques. Pulsed signals are robust, inherently low-power, easily regenerated, and easily distributed across and between chips. The Palmo cells used to perform analogue operations on the pulsed signals are compact, fast, simple and programmable. To demonstrate the inherent suitability of the technique to programmable analogue implementations, two chips were fabricated and tested on boards containing a standard FPGA for doing the routing. Results from elementary lter implementations and A/D converters are presented to prove the validity of the approach. Finally a current-mode log-domain BiCMOS Palmo circuit is analysed, which enables much higher sample frequencies than the voltage domain Palmo counterparts. 1The name Palmo is derived from the Hellenic word A MO which means pulsebeat, pulse palpitation or series of pulses. Table of
Business intelligence : the savvy manager's guide, getting onboard with emerging IT

Business Intelligence and Information Exploitation. The Value of Information. Business Models and Information Flow. Data Models and Meta Data. Business Intelligence Environments. Business Rules. Data Profiling. Data Quality and Information Compliance. Information Integration. Alternate Information Contexts. Data Enhancement. Knowledge Discovery. Guide to Public Data. References.
Identification of Color Uniformity Defect on the Electronic Displays by Learning the Human Perception Records

This article explores a proposed method for identifying and classifying the color uniformity defect on the electronic displays. A neural network learning approach utilizing the backpropagation learning algorithm is employed to search the dissimilarity of the color display condition. The color uniformity defect image perception among several conditions of some observations by human eyesight is used to supervise the training data of the neural networks. A supervisor of the training data is obtained by human expert eyes evaluate the white uniformity grade and compare with the standard grade, then labeling the perception grade into some certainty values. The trained network is used to identify and classify the grades level of the color uniformity defect on the electronic displays. For the experimental purpose, a simulation program is developed to generate the color uniformity defect on the monitor display. We make a comparison with a classical regression analysis method for validation of the proposed method.
Challenges With Session to Session Managementin Brain Computer Interfaces : A Comparison of Classification Methods for Motor Imagery Induced EEG Patterns

Brain computer interfaces (BCIs) enable communication between a brain and a computer, without the need for any motor actions. Electroencephalography (EEG) signals can be used as input for a BCI, but they need to go through a number of steps in the BCI to create useableoutput. One of the most critical steps is the classification algorithm,which is the step that is investigated in this report. A linear and anonlinear Support Vector Machine (SVM), together with a Linear Discriminant Analysis (LDA), are investigated in how well they can handlesession to session performance when classifying EEG data from three different recording sessions of three different test subjects. The results show that the average performance of the classifiers are in most cases similar, slightly above 60 %. The performance of the investigated algorithms differed depending on subject and session. The sometime slow performance of the classification algorithms may be due to the lowsignal-to-noise ratio in the EEG signals, or possibly even due to bad performance in producing recognizable EEG patterns by the test subjects.The conclusion drawn from the project is that data from different sessions can vary quite extensively, and in this project it was handledbest by the nonlinear SVM with RBF kernel, with the highest averageclassification accuracy.
Inexpensive Research in Marketing: Empowering the Technologically Challenged Entrepreneurs

While the U.S. entrepreneur has a relatively greater advantage of ready access to new technologies in the information age, the entrepreneur in developing nations is limited in that luxury for pursuing opportunities in the marketplace. Although the digital divide exists in the United States, the chasm is deeper in other nations around the world. Without the proper tools needed to reduce uncertainty surrounding decisions and, in turn, to lower the risk of failure, most entrepreneurs would be strapped with myopia of the market intricacies because information sciences and technologies are the lenses through which the consumer is studied and strategic plans are formulated. As a compromise, the technologically challenged entrepreneur has to resort to “cheap but good” research methodology. Despite the limitations and the challenges facing the entrepreneurs, there are a number of inexpensive methods explained in this article to generate objective information to reduce uncertainty. Without requiring sophisticated technologies for strategic decision-making, the entrepreneur can establish a successful enterprise by overcoming the challenge of the paucity of cutting edge technologies and thus becoming able to bridge the digital divide.
Bayesian Big Data Classification: A Review with Complements

This paper focuses on the specific problem of big data classification in a Bayesian setup using Markov Chain Monte Carlo methods. It discusses the challenges presented by the big data problems associated with classification and the existing methods to handle them. Next, a new method based on two-stage Metropolis-Hastings (MH) algorithm is proposed in this context. The purpose of of this algorithm is to reduce the exact likelihood computational cost in the big data context. In the first stage, a new proposal is tested by the approximate likelihood based model. The full likelihood based posterior computation will be conducted only if the proposal passes the first stage screening. Furthermore, this method is adopted into the consensus Monte Carlo framework. Methods are illustrated on two large datasets.
Open-Ended Search in High Quality Image Catalogues

E-commerce is one of the most challenging fields of application of the new Internet technologies. It is clear that the larger the number of items available to be presented, the more difficult it is to guide the user towards the product he is looking for. In this article we present a prototype for the interactive search of images in high-quality electronic catalogues. The system is based on a visual information search engine, and integrates a Color Management System for the faithful display of images.
Improving Student Information Search: A Metacognitive Approach

Metacognition is a set of active mental processes that allows users to monitor, regulate, and direct their personal cognitive strategies. Improving Student Information Search traces the impact of a tutorial on education graduate students? problem-solving in online research databases. The tutorial centres on idea tactics developed by Bates that represent metacognitive strategies designed to improve information search outcomes. The first half of the book explores the role of metacognition in problem-solving, especially for education graduate students. It also discusses the use of metacognitive scaffolds for improving students? problem-solving. The second half of the book presents the mixed method study, including the development of the tutorial, its impact on seven graduate students? search behaviour and outcomes, and suggestions for adapting the tutorial for other users. provides metacognitive strategies to improve students? information search outcomes incorporates tips to enhance database search skills in digital libraries includes seminal studies on information behaviour
Java Web Services Architecture

Preface. Section One: Web Services Overview. Service Oriented Architecture. Component-Based Services. Web Services Infrastructure. SOAP. WSDL. UDDI. ebXML. Section Two: JWSDP. JAXP. JAX-RPC. JAXM. JAXR. JAXB. Section Three: Transactions. Security. Practical Considerations. Futures. Appendixes: XML Schemas. JSTL. Index.