Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of course errors on CVOR antennas (including effects of mutual coupling between elements)

VOR (VHF omnidirectional radio range) is a radio beacon navigation aid giving aircraft bearing information from VOR stations. Currently, two types of VOR are in use in Japan, the conventional type (hereinafter referred to as CVOR) and the Doppler type (hereinafter referred to as DVOR). This paper will describe the bearing error resulting from including the effects of mutual coupling between elements. We therefore calculated coupling between the Alford loop elements and analyzed the bearing error by using the data obtained. In this paper, we also propose a method to minimize the bearing error. <<ETX>>
A new method for estimating subject specific body segment parameters using motion tracking data

Current segment inertial parameter estimation methods can be categorised as either regression, geometric or mass scanning based. Regression methods estimate segment parameters by developing regression equations using cadaver or live subject data. Geometric based methods model body segments as basic geometric shapes and calculate segment parameters assuming uniform density throughout the volume. Mass scanning methods also assume uniform density, but calculate segment shape and volume from mass scanning measurements. The first category does not yield subject specific segment parameters. The other two categories require time-consuming segment measurements and uniform density assumptions. This paper presents a new method for estimating subject specific body segment parameters that utilises work and energy equations and only requires kinematic and kinetic data from a standard walking trial. A preliminary evaluation of this method has been performed and results were comparable to current anthropometric data and average values obtained from mass scanning technology.
Automatic lipreading by optical-flow analysis

While the acoustic signal is the primary cue in human speech recognition, the visual cue is also very useful, especially when the acoustic signal is distorted. A computer system is developed for automatic recognition of continuously spoken words by using only visual data. The velocity of lip motions may be measured from optical flow data which allows muscle action to be estimated. Pauses in muscle action result in zero velocity of the flow and are used to locate word boundaries. The pattern of muscle action is used to recognize the spoken words.
Finite-state pre-processing for natural language analysis

Wide-coverage natural language parsers are typically not very efficient. Finite-state techniques are less powerful, but offer the advantage of being very fast, and good at representing language locally. This dissertation constitutes empirical research into the construction and use of a finite-state approximation of a wide-coverage parser to increase parsing performance. The finite-state approximation is in the form of a hidden Markov model, inferred from parser-annotated data. This model is used in a part-of-speech tagger, which is applied in various ways and using several different models to reduce ambiguity in parsing, by setting it up as a filter that removes unlikely options in the first stage of parsing.
Techniques to Improve the word alignments in Statistical Machine Translation from English to Malayalam

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam translation using statistical models like translation model, language model and a decoder. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set up among the sentence pairs of the source and target language before subjecting them for training. This paper is deals with the techniques which can be adopted for improving the alignment model of SMT. Incorporating the parts of speech information into the bilingual corpus has eliminated many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER
Media Education: Literacy, Learning and Contemporary Culture

Preface and Acknowledgments. Part I: Rationales:. 1. Why Teach the Media? 2. New Media Childhoods. 3. Media Literacies. Part II: The State of the Art:. 4. Defining the Field. 5. Classroom Strategies. 6. Locating Media Education. Part III: Media Learning:. 7. Becoming Critical. 8. Getting Creative. 9. Defining Pedagogy. Part IV: New Directions:. 10. Politics, Pleasure and Play. 11. Digital Literacies. 12. New Sites of Learning. References. Index
Safe and practical decoupling of aspects with join point interfaces

In current aspect-oriented systems, aspects usually carry, through their pointcuts, explicit references to the base code. Those references are fragile and give up important software engineering properties such as modular reasoning and independent evolution of aspects and base code. In this work, we introduce a novel abstraction called Join Point Interfaces, which, by design, supports modular reasoning and independent evo- lution by decoupling aspects from base code and by providing a modular type-checking algorithm. Join point interfaces can be used both with implicit announcement through pointcuts, and with explicit announce- ment, using closure join points. Join point interfaces further offer polymorphic dispatch on join points, with an advice-dispatch semantics akin to multi-methods. In this work, we show how our proposal solves a large number of problems observed in previous related approaches. We have implemented join point interfaces as an open-source extension to AspectJ. A first study on existing aspect-oriented programs supports our initial design in general, but also highlights some limitations, which we then address by introducing parametric polymorphism and a more permissive quantification mechanism. As a result, join point interfaces are a safe and practical way of decoupling aspects.
Ballot technique to analyze unslotted CDMA with fixed packet lengths

A technique to analyze the throughput of an L-channel CDMA (code-division multiple-access) network is presented. Two approximations are needed to use the technique. First, we need to divide the packet into minislots. Second, at most one arrival or one departure can occur in one minislot, but not both. The error due to the approximation is very small for small lambda /M and large M, where M is the bit size of the packet and lambda is the rate of the packet-arrival process. The technique is verified using M=64. Results obtained by the ballot technique are very close to the simulation results for low arrival rates and less accurate for higher arrival rates. The disadvantage of the ballot technique is that the solution is not given in a compact close form. <<ETX>>
Bayesian Analysis of Stochastic Frontier Models

In this chapter, we described a Bayesian approach to efficiency analysis using stochastic frontier models. With cross-sectional data and a log-linear frontier, a simple Gibbs sampler can be used to carry out Bayesian inference. In the case of a nonlinear frontier, more complicated posterior simulation methods are necessary. Bayesian efficiency measurement with panel data is then discussed. We show how a Bayesian analogue of the classical fixed effects panel data model can be used to calculate the efficiency of each firm relative to the most efficient firm. However, absolute efficiency calculations are precluded in this model and inference on efficiencies can be quite sensitive to prior assumptions. Accordingly, we describe a Bayesian analogue of the classical random effects panel data model which can be used for robust inference on absolute efficiencies. Throughout, we emphasize the computational methods necessary to carry out Bayesian inference. We show how random number generation from well-known distributions is sufficient to develop posterior simulators for a wide variety of models.
Optimization of History Tree in 3DR-Tree Index Structure

Many optimizations have been done to 3DR-tree index structure and many opinions have been proposed. Modification by splitting mechanism is one of them. There are two index trees in 3DR-tree index structure after modification: one is a history tree for past data storage and the other is an active tree for current data storage. In this article, optimization of history tree is firstly done and is proved theoretically. Then a correspondent insert algorithm is designed.
Preliminary experimental validation of a landmine detection system based on localized heating and sensing

In this paper we present results of experimental validation of a new methodology for anti-personnel mine (APM) detection for humanitarian demining, proposed by the authors and previously validated only by simulation. The technique is based on local heating and sensing by contactless thermometers (pyrometers). A large sand box (2.6m3) has been realized and fitted with a cart moving on rails and holding instrumentation. Accurate mine surrogates have been hidden in the sand together with confounders. Preliminary measurements are consistent with simulations and prove validity of the approach.
Text mining of multilingual corpora via computing semantic relatedness

This paper describes a new application of a text-mining algorithm to the text sources of bilingual corpora. In the past, the majority of the approaches applied to measuring semantic relatedness was based on edge counting methods through a semantic network, such as WordNet. It is not well suited for applications in specific domains in which the standard lexical knowledge bases are not available. In this work, we propose an alternative solution for acquisition of semantic relatedness from text corpora by means of a machine learning technique, namely the self-organizing maps. This paper presents a hybrid approach to discovering a concept-based feature map containing word clusters and document clusters from multilingual text collections. Using SOM-based automatic clustering techniques, we have conducted several experiments to uncover associated documents based on Chinese-English bilingual parallel corpora, and a hybrid Chinese-English corpus. In essence, this work provides a method for automatic text clustering, which resolves some of the language difficulties in concept discovery and categorization from multilingual text corpora.
Statistical relationship between atmospheric circulation and extreme precipitation in La Plata Basin

Empirical conditional probabilities of extreme monthly precipitation averaged over three regions of the southern part of the La Plata basin were calculated as a function of three atmospheric indices: two of them represent low level moisture convergence and the third is related to the mid tropospheric circulation over southern South America. The first region includes southern Paraguay, northeastern Argentina, north of Uruguay and the western sector of southern Brazil, the second region stretches over part of southern Brazil, while the third region, surrounding the Plata Estuary extends over western Uruguay and eastern Argentina between 37 ° S and 32 ° S. Regional monthly precipitation was considered extreme when it exceeded its mean value plus one standard deviation. Conditional empirical probabilities of Months with Extreme Precipitation (MEP) are more than twice and even four times higher than climatic probabilities when they are calculated under the restriction that the atmospheric indices were beyond certain extreme thresholds empirically defined. Combined conditional probability is even higher when the values of two or the three indices over their respective thresholds take place at the same time, but these cases are less frequent. The index that renders higher conditional probabilities is the one that accounts for the low level moisture convergence in a region that is basically to the west and outside of the three regions. This reflects the fact that most of the mesoconvective systems, which originate to the west of these regions and then move eastwards, produce heavy precipitation that lead to monthly accumulated extremes. Copyright © 2013 Royal Meteorological Society
Small signal equivalent circuit modeling of the LCC-type parallel resonant converter

A small signal equivalent circuit model is obtained for the LCC-type parallel resonant converter in the form of a two port hybrid parameter model. This model is used to study the small signal behavior of the converter. Dynamic performance parameters like the control to output transfer function, audio-susceptibility, output impedance and input admittance have been plotted. Both exact (sampled) and approximate (continuous time) models are obtained. When the exact model is used, the results are found to be accurate upto the switching frequency. Experimental verification of the key results is presented. <<ETX>>
Computer Analysis of Essay Content for Automated Score Prediction

This report discusses the development and evaluation of a research prototype system designed to automatically score essay responses to the GMAT Analytical Writing Assessments: (a). Analysis of an Argument (Argument essays) and (b). Analysis of an Issue (Issue essays) item types. The system, Electronic Essay Rater (e-rater), was designed to automatically analyze several features of an essay and score the essay based on the features of writing as specified in holistic rubrics. E-rater uses a hybrid feature methodology. It incorporates several variables that are derived statistically, extracted through NLP techniques, or achieved by simple “counting” procedures. The version of the e-rater described in this report uses five sets of critical feature variables to build the final linear regression model used for predicting scores. The same set of critical variables was used to fit models for the issue and argument training essays and the following results were achieved. For the set of 275 cross-validation data, exact or adjacent agreement with human rater scores reached 95%. For the 282 cross-validation issue essays exact or adjacent agreement with human rater scores achieved 93%. The rich feature variables used as score predictors in e-rater could potentially be used to generate explanation of score predictions, and diagnostic and instructional information.
Eclipse Plug-ins

Producing a commercial-quality plug-in means going above and beyond the minimal requirements needed to integrate with Eclipse. It means attending to all those details that contribute to the fit and polish of a commercial offering. This comprehensive guide covers the entire process of plug-in development, including all the extra steps needed to achieve the highest quality results.Building on two internationally best-selling previous editions, Eclipse Plug-ins, Third Edition, has been fully revised to reflect the powerful new capabilities of Eclipse 3.4. Leading Eclipse experts Eric Clayberg and Dan Rubel present detailed, practical coverage of every aspect of plug-in development, as well as specific, proven solutions for the challenges developers are most likely to encounter. All code examples, relevant API listings, diagrams, and screen captures have been thoroughly updated to reflect both the Eclipse 3.4 API and the latest Java syntax. In addition, Clayberg and Rubel have completely revamped their popular Favorites View case study, reworking much of its content and recreating its code from scratch. The authors carefully cover new functionality added to existing Eclipse features, such as views and editors, and fully explain brand-new features such as Commands, GEF, and PDE Build.This extensively revised edition Thoroughly covers Eclipses new preferencesIlluminates the powerful new Eclipse Command Framework, which replaces Eclipses older Action FrameworkPresents extensive new discussions of using commands with views and editorsIntroduces Mylyn, the new task-focused interface that reduces information overload and simplifies multi-taskingContains an all-new chapter on using the Graphical Editing Framework (GEF) to build dynamic, interactive graphical user interface elementsWalks you step by step through the entire PDE Build processShows how to create update sites with p2, which replaces Eclipses old Update Manager This book is designed for every experienced developer interested in extending the Eclipse platform, the Rational Software Development Platform, or any other platform that supports Eclipse plug-ins.
FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics

This monograph describes a new family of algorithms for the simultaneous localization and mapping (SLAM) problem in robotics, called FastSLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy, in a number of robot application domains and have been successfully applied in different dynamic environments, including a solution to the problem of people tracking.
Secure Programming for Linux and Unix HOWTO

This book provides a set of design and implementation guidelines for writing secure programs for Linux and Unix systems. Such programs include application programs used as viewers of remote data, web applications (including CGI scripts), network servers, and setuid/setgid programs. Specific guidelines for C, C++, Java, Perl, PHP, Python, Tcl, and Ada95 are included. For a current version of the book, see http://www.dwheeler. com/secure−programs
Waste water neutralization using a fuzzy neural network controller

In this paper, the pH neutralization process is identified and controlled using a fuzzy neural network structure. Three different approaches are compared. In the first method, a generic fuzzy controller was used in which membership functions and rule base are selected intuitively. For the second and third approaches, the fuzzy system is initialized using a fuzzy error backpropagation algorithm. While in the second case study no online adaptation takes place, in the last approach the membership functions are adjusted online. The results of these methods are presented and evaluated. In order to describe the system dynamics a radial basis function network was used.
Assessing Students’ Attitudes In A College Physics Course In Mexico

Considering the benefits of modeling instruction in improving conceptual learning while students work more like scientists, an implementation was made in an introductory Physics course in a Mexican University. Recently Brewe, Kramer and O’Brien have observed positive attitudinal shifts using modeling instruction in a course with a reduced number of students. These results are opposite to previous observations with methodologies that promote active learning. Inspired in those results, the Colorado Learning Attitudes about Science Survey (CLASS) was applied as pre and post tests in two Mechanics courses with modeling. In comparison to the different categories of the CLASS, significant positive shifts have been determined in Overall, Sophistication in Problem Solving, and Applied Conceptual Understanding in a sample of 44 students.
Exploring the power consumption of different motion estimation architectures for video compression

Power consumption is very critical for portable video applications. Motion estimation in the video encoder requires huge amount of computation and hence consumes the largest portion of power. This paper investigates the power consumption of different motion estimation architectures. Full search architectures were used as an example to illustrate the power consumption mechanism. The principle can be extended to other commonly used fast search architectures. The result of this study can serve as a guideline for the selection of the appropriate architecture for portable applications.
From Direct manipulation to Gestures

Optimizing the bandwidth of the communication channel between users and the system is fundamental for designing efficient interactive systems. Apart from the case of speech-based interfaces that rely on users’ natural language, this entails designing an efficient language that users can adopt and that the system can understand. My research has been focusing on studying and optimizing the two fol- lowing types of languages: interfaces that allow users to trigger actions through the direct manipulation of on-screen objects, and interactive systems that allow users to invoke commands by performing specific movements. Direct manipulation re- quires encoding most information in the graphical representation, mostly relying on users’ ability to recognize visual elements; whereas gesture-based interaction interprets the shape and dynamics of users’ movements, mostly relying on users’ ability to recall specific movements. This manuscript presents my main research projects about these two types of language, and discusses how we can increase the efficiency of interactive systems that make use of them. When using direct manip- ulation, achieving a high expressive power and a good level of usability depends on the interface’s ability to accommodate large graphical scenes while enabling the easy selection and manipulation of objects in the scene. When using gestures, it depends on the number of different gestures in the system’s vocabulary, as well as on the simplicity of those gestures, that should remain easy to learn and execute. I conclude with directions for future work around interaction with tangible objects.
The decipher speech recognition system

A large-vocabulary, continuous-speech system, called DECIPHER, which is based on a hidden Markov model (HMM) approach and is designed to achieve high word accuracy in a speaker-independent mode is described. The results of a series of experiments that test acoustic and phonological adaptation of the DECIPHER system to the pronunciations of a single speaker in a speaker-dependent task are presented. Estimating the probabilities of alternative pronunciations and speaker-dependent phonology are discussed. <<ETX>>