Miracle-dz/UniFAR-FTUs huggingface dataset:
A new method to evaluate blocking probability on high elevation satellites viewed from land vehicles

In this paper, we propose a new method for evaluating the probability of interruptions in communication links between a vehicle in different geographic areas and a satellite at a certain elevation-azimuth angle with respect to the orientation of the vehicle. This method uses the Global Positioning System. The results suggests that EFSAT is more suitable for land-mobile satellite communications than a geostationary satellite in terms of blocking by features on the ground in both cities, expressways and rural areas.
A 1.5-V 12-bit power-efficient continuous-time third-order ΣΔ modulator

This paper presents the design strategy, implementation, and experimental results of a power-efficient third-order low-pass /spl Sigma//spl Delta/ analog-to-digital converter (ADC) using a continuous-time (CT) loop filter. The loop filter has been implemented by using active RC integrators. Several power optimizations, design requirements, and performance limitations relating to circuit nonidealities in the CT modulator are presented. The influence of the low supply voltage on the various building blocks such as the amplifier as well as on the overall /spl Sigma//spl Delta/ modulator is discussed. The ADC was implemented in a 3.3-V 0.5-/spl mu/m CMOS technology with standard threshold voltages. Measurements of the low-power 1.5-V CT /spl Sigma//spl Delta/ ADC show a dynamic range and peak signal-to-noise-plus-distortion ratio of 80 and 70 dB, respectively, in a bandwidth of 25 kHz. The measured power consumption is only 135 /spl mu/W from a single 1.5-V power supply.
New developments related to the Hirsch index

It is shown that the h-index on the one hand, and the A- and g-indices on the other, measure different things. The A-index, however, seems overly sensitive to one extremely highly cited article. For this reason it would seem that the g-index is the more useful of the two. As to the h- and the g-index: they do measure different aspects of a scientist’s publication list. Certainly the h-index does not tell the full story, and, although a more sensitive indicator than the h-index, neither does the g-index. Taken together, g and h present a concise picture of a scientist’s achievements in terms of publications and citations.
Extending AdaBoost:Varying the Base Learners and Modifying the Weight Calculation

AdaBoost has been considered one of the best classifiers ever developed, but two important problems have not yet been addressed. The first is the dependency on the “weak” learner, and the second is the failure to maintain the performance of learners with small error rates (i.e. “strong” learners). To solve the first problem, this work proposes using a different learner in each iteration known as AdaBoost Dynamic (AD) thereby ensuring that the performance of the algorithm is almost equal to that of the best “weak” learner executed with AdaBoost.M1. The work then further modifies the procedure to vary the learner in each iteration, in order to locate the learner with the smallest error rate in its training data. This is done using the same weight calculation as in the original AdaBoost; this version is known as AdaBoost Dynamic with Exponential Loss (AB-EL). The results were poor, because AdaBoost does not perform well with strong learners, so, in this sense, the work confirmed previous works’ results. To determine how to improve the performance, the weight calculation is modified to use the sigmoid function with algorithm output being the derivative of the same sigmoid function, rather than the logistic regression weight calculation originally used by AdaBoost; this version is known as AdaBoost Dynamic with Logistic Loss (AB-DL). This work presents the convergence proof that binomial weight calculation works, and that this approach improves the results for the strong learner, both theoretically and empirically. AB-DL also has some disadvantages, like the search for the “best” classifier and that this search reduces the diversity among the classifiers. In order to attack these issues, another algorithm is proposed that combines AD “weak” leaner execution policy with a small modification of AB-DL’s weight calculation, called AdaBoost Dynamic with Added Cost (AD-AC). AD-AC also has a theoretical upper bound error, and the algorithm offers a small accuracy improvement when compared with AB-DL, and traditional AdaBoost approaches. Lastly, this work also adapts AD-AC’s weight calculation approach to deal with data stream problem, where classifiers must deal with very large data sets (in the order of millions of instances), and limited memory availability.
Enhanced mobile computing using cloud resources

The purpose of this research is to investigate, review and analyse the use of cloud resources for the enhancement of mobile computing. Mobile cloud computing refers to a distributed computing relationship between a resourceconstrained mobile device and a remote high-capacity cloud resource. Investigation of prevailing trends has shown that this will be a key technology in the development of future mobile computing systems. This research presents a theoretical analysis framework for mobile cloud computing. This analysis framework is a structured consolidation of the salient considerations identified in recent scientific literature and commercial endeavours. The use of this framework in the analysis of various mobile application domains has elucidated several significant benefits of mobile cloud computing including increases in system performance and efficiency. Based on recent scientific literature and commercial endeavours, various implementation approaches for mobile cloud computing have been identified, categorized and analysed according to their architectural characteristics. This has resulted in a set of advantages and disadvantages for each category of system architecture. Overall, through the development and application of the new analysis framework, this work provides a consolidated review and structured critical analysis of the current research and developments in the field of mobile cloud computing.
The Prime Machine : a user-friendly corpus tool for English language teaching and self-tutoring based on the Lexical Priming theory of language

This thesis presents the design and evaluation of a new concordancer called The Prime Machine which has been developed as an English language learning and teaching tool. The software has been designed to provide learners with a multitude of examples from corpus texts and additional information about the contextual environment in which words and combinations of words tend to occur. The prevailing view of how language operates has been that grammar and lexis are separate systems and sentences can be constructed merely by choosing any syntactic structure and slotting in vocabulary. Over the last few decades, however, corpus linguistics has presented challenges to this view of language, drawing on evidence which can be found in the patterning of language choices in texts. Nevertheless, despite some reports of success from researchers in this area, only a limited number of teachers and learners of second language seem to make direct use of corpus software tools. The desire to develop a new corpus tool grew out of professional experience as an English language teacher and manager in China. This thesis begins by introducing some background information about the role of English in international higher education and the language learning context in China, and then goes on to describe the software architecture and the process by which corpus texts are transformed from their raw state into rows of data in a sophisticated database to be accessed by the concordancer. It then introduces innovations including several aspects of the search screen interface, the concordance line display and the use of collocation data. The software provides a rich learning platform for language learners to independently look up and compare similar words, different word forms, different collocations and the same words across two corpora. Underpinning the design is a view of language which draws on Michael Hoey's theory of Lexical Priming. The software is designed to make it possible to see tendencies of words and phrases which are not usually apparent in either dictionary examples or the output from other concordancing software. The design features are considered from a pedagogical perspective, focusing on English for Academic Purposes and including important software design principles from Computer Aided Language Learning. Through a small evaluation involving undergraduate students, the software has been shown to have great potential as a tool for the writing process. It is believed that The Prime Machine will be a very useful corpus tool which, while simple to operate, provides a wealth of information for English language teaching and self-tutoring.
The Role of Texual Input Enhancement in the Second Language Acquisition of English Passive Voice

Key words: Texual Input Enhancement, Explicit,the second language acquisition, English passive voice ABSTRACT The question of whether or not grammar should be taught has been determinedly debated in the fields of language pedagogy and second language acquisition. Some scholars (e.g. Ellis, 2003) are against form-oriented language instructions such as the Grammar Translation Method, because they state that grammar is acquired naturally if students are exposed to the sufficient input so there is no need to be taught. Others (e.g. White, 1987) have an opposing opinion, focusing on the inclusion of formal grammar teaching. They argue that instruction is necessary, as some grammatical features cannot be acquired naturally. Taking into consideration that both techniques aim to present the input in such way that learners’ attention is drawn to the target feature, the research conducted here focuses on how textual input enhancement affected the acquisition of the passive construction in English in the long term that compares traditional ‘form-focused’ instruction. Sharwood Smith (1991:118) defines input enhancement as ‘the process by which language input becomes salient to the learner. ’ Ninety Libyan students from one Libyan university participated in the study, were randomly assigned to one of three different conditions; enhancement, explicit and control groups. Participants in the enhancement group received enhanced reading passages in English with all passive forms highlighted; participants in the explicit group received explicit teaching and participants in the control group received no enhanced reading texts or instructions. An analysis of the participants’ responses revealed that participants in the explicit group show better knowledge of English passive than the enhancement and control groups. However, they were unable to show further improvement in the delayed post-test (long term) as the enhancement group did. The results of this study showed that textual input enhancement proven to be more effective in the long term than explicit and no instruction conditions.
Computing consensus translation from multiple machine translation systems

We address the problem of computing a consensus translation given the outputs from a set of machine translation (MT) systems. The translations from the MT systems are aligned with a multiple string alignment algorithm and the consensus translation is then computed. We describe the multiple string alignment algorithm and the consensus MT hypothesis computation. We report on the subjective and objective performance of the multilingual acquisition approach on a limited domain spoken language application. We evaluate five domain-independent off-the-shelf MT systems and show that the consensus-based translation performance is equal to or better than any of the given MT systems, in terms of both objective and subjective measures.
New approaches to using scientific data - statistics, data mining and related technologies in research and research training

This paper surveys technological changes that affect the collection, organization, analysis and presentation of data. It considers changes or improvements that ought to influence the research process and direct the use of technology. It explores implications for graduate research training. The insights of Evidence-Based Medicine are widely relevant across many different research areas. Its insights provide a helpful context within which to discuss the use of technological change to improve the research process. Systematic data-based overview has to date received inadequate attention, both in research and in research training. Sharing of research data once results are published would both assist systematic overview and allow further scrutiny where published analyses seem deficient. Deficiencies in data collection and published data analysis are surprisingly common. Technologies that offer new perspectives on data collection and analysis include data warehousing, data mining, new approaches to data visualization and a variety of computing technologies that are in the tradition of knowledge engineering and machine learning. There is a large overlap of interest with statistics. Statistics is itself changing dramatically as a result of the interplay between theoretical development and the power of new computational tools. I comment briefly on other developing mathematical science application areas – notably molecular biology. The internet offers new possibilities for cooperation across institutional boundaries, for exchange of information between researchers, and for dissemination of research results. Research training ought to equip students both to use their research skills in areas different from those in which they have been immediately trained, and to respond to the challenge of steadily more demanding standards. There should be an increased emphasis on training to work cooperatively. “At bottom my critique is pretty simple-minded: Nobody pays much attention to the assumptions, and technology tends to overwhelm common sense. ” [Freedman 1987. ] “I personally look forward to the proper balance that will emerge from the mixing of computational algorithm-oriented approaches characterizing the database and computer science communities with the powerful mathematical theories and methods for estimation developed in statistics. ” [Fayyad 1998. ] “Statistics has been the most successful information science. Those who ignore statistics are condemned to re-invent it. ” [Efron, quoted in Friedman 1997. ] “Some members of the profession are trying hard to make changes, by teaching courses in which substantive questions come first and technique is introduced to find answers. Of course, all too often, technique comes first; data come in as purely decorative illustrations – a practice not confined to statistics departments. ” [Freedman 1991. ]
Event visibility in Austrian Sign Language (ÖGS)

This paper focuses on the phonological visibility of event structure of non-classifier predicates in Austrian Sign Language (OGS) as proposed in the Event Visibility Hypothesis (EVH) (Grose et al. 2006; Wilbur in press). The aim of this paper is to investigate the event structure of OGS predicate signs and to test the applicability of the EVH. The analysis provides evidence that the event structure of OGS predicates is also phonologically visible and that the two unrelated sign languages ASL and OGS use the same set of morphemes to mark telic and atelic event structures. The actual phonological realizations of these morphemes, however, are language dependent. The present paper adds to the EVH with a discussion of the observed inability of some predicates to be marked for telicity and with the analysis of mouth nonmanuals which are suggested to be sensitive to the event structure. These nonmanuals divide into two types: (1) continuous posture or P-nonmanuals, composed of a single facial posture which functions as an adverbial modifier of the event, and (2) discontinuous transition or T-nonmanuals, composed of a single abrupt change in the position of the articulator, which appear to emphasize the initial or final portion of the event structure.
Morpheme Order and Semantic Scope: APPENDIXES

1. Introduction: beginning the journey Part I. First Steps: 2. Introducing the problem 3. Global uniformity and local variability: a possible account Part II. The Lexical Terms: 4. First stop: introducing the lexical items 5. A brief side trip: the position of the verb stem 6. Ordering of the lexical items 7. Voice/valence 8. Summary: lexical items Part III. The Functional Items: 9. An introduction to the functional elements 10. Pronominals 11. The aspect system 12. Qualifiers and their ordering 13. On the ordering of functional items Part IV. A View of the Lexicon: 14. The scopal hypothesis and simplifying the lexicon 15. Evidence from the lexicon Part V. The End of the Journey: 16. Looking back, looking ahead Part VI. Appendices: Appendix 1. Templates and affix ordering Appendix 2. The languages Appendix 3. Summary of constraints and language differences Notes References Indexes.
STYLE IN SWIFT CREEK PADDLE ART

Abstract Woodland period Swift Creek designs have received considerable attention in recent years. Bettye Broyles and Frankie Snow, among few others, have created a working corpus within which stylistic aspects of Swift Creek designs can be explored. Here, we focus both on “observer” models that governed acceptable visual form and on “task” models used by Swift Creek artisans to produce that form by creating paddle designs. Reconstructed procedures for several paddle designs emphasize the stepwise nature of creating art in this style. We discuss the key importance of guide points, guidelines, and creatively manipulated bandwork in Swift Creek compositions. Using this approach, we hope to demonstrate the value of reconstructed whole paddle designs in the study of layout, symmetry, design concept, and other stylistic domains. Finally, we chart the historical trajectories of selected style characteristics through time and offer suggestions for future research in this domain.
Discriminative and generative approaches for long- and short-term speaker characteristics modeling: application to speaker verification

The speaker verification problem can be stated as follows: given two speech recordings, determine whether or not they have been uttered by the same speaker. Most current speaker verification systems are based on Gaussian mixture models. This probabilistic representation allows to adequately model the complex distribution of the speech frames. It however represents an inadequate basis for discriminating between speakers, which is the key issue in the area of speaker verification. In the first part of this thesis, we attempt to overcome these difficulties by proposing to combine support vector machines with two generative approaches based on Gaussian mixture models. In the second part of this thesis, we present a new approach to modeling the speaker's long-term prosodic and spectral characteristics. This novel approach is based on continuous approximations of the prosodic and cepstral contours. Finally, we perform a scores fusion between systems based on long- and short-term speaker features.
Memory-Based Approaches and Beyond

In this article, we discuss 2 issues that we believe any theory of discourse comprehension has to take account of-accessing irrelevant information and granularity. Along the lines that have been suggested as demonstrating the memory-based account, we describe some work in favor of the recruitment of apparently irrelevant information from memory during reading. In all cases, this information interferes with comprehension. We argue that the nature of interference can be instructive about stylistic effects and most clearly demonstrates the involvement of the process in comprehension. The second issue we discuss is granularity, or how specifically a concept is represented. We claim that granularity of representation is relevant to comprehension and discuss the problem in terms of scenario theory and the concept of readiness.
Using Augmented Reality to Facilitate Piping Assembly: An Experiment-Based Evaluation

AbstractCurrent practice utilizes two-dimensional (2D) drawings as the main visualization means to guide assembly. As an emerging technology, augmented reality (AR) integrates three-dimensional (3D) images of virtual objects into a real-world workspace. The insertion of digitalized information into the real-world workspace using AR can provide workers with the means to implement correct assembly procedures with improved accuracy and reduced errors. The limited available research concerning the applications of AR visualization means in assembly highlights the need for a structured methodology of addressing cognitive and usability issues for the application potentials of AR technology to be fully realized. Thus, the focus of the study presented in this paper is to investigate how much improvement in assembly productivity and performance can be achieved by lowering cognitive workload via AR. The AR system was developed in collaboration with Woodside Energy Ltd. following research project ECHO. Evaluation of .
An Empirical Study of Distributed Constraint Satisfaction Algorithms

An Empirical Study of Distributed Constraint Satisfaction Algorithms Younis Mohmaed Advisor: Professor Y. Xiang University of Guelph, 2011 Many real world problems are naturally distributed, whether they are spatially, cognitively, or otherwise. Distributed problems naturally lend themselves to solutions using multi-agent paradigms. Distributed Constraint Satisfaction Problems (DisCSPs) are a class of such distributed problems. In DisCSPs, variables and constraints are distributed between agents. Most distributed algorithms, although exponential in the worst-case, can have a good performance in the average case. The main purpose of this research is to statistically assess difference between the empirical performances of major state of the art DisCSP algorithms including Multi-Sectioned Constraint Network (MSCN) based algorithms, that have never been empirically compared against other DisCSP algorithms. In this thesis, we select a set of state of the art DisCSP algorithms and compare them on randomly generated instances of binary DisCSPs with a wide range of characteristics. Distributed algorithms ADOPT, DSA, DPOP, and MSCN based algorithms were selected based on a set of high level criteria. We explore how these algorithms relatively compare with each other on a range of DisCSPs with different parameters. Their performances are evaluated according to computation time (in the form of non-concurrent computational steps or NCCCs) and communication load (in the form of number of messages as well as volume of messages). Statistical parametric tests are used to aid interpretation of the performance results. In addition, this thesis discusses privacy issues associated with these DisCSP algorithms.
CMOS low-power analog circuit design

This chapter covers device and circuit aspects of low-power analog CMOS circuit design. The fundamental limits constraining the design of low-power circuits are first recalled with an emphasis on the implications of supply voltage reduction. Biasing MOS transistors at very low current provides new features but requires dedicated models valid in all regions of operation including weak, moderate and strong inversion. Low-current biasing also has a strong influence on noise and matching properties. All these issues are discussed, together with the particular aspects related to passive devices and parasitic effects. The design process has to be supported by efficient and accurate circuit simulation. To this end, the EKV compact MOST model for circuit simulation is presented. The use of the basic concepts such as pinch-off voltage, inversion factor and specific current are highlighted thanks to some very simple but fundamental circuits and to an effective use of the model. New design techniques that are appropriate for low-power and/or low-voltage circuits are presented with an emphasis on the analog floating point technique, the instantaneous companding principle, and their application to filters.