The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout.
Wildland fires are natural calamities that bring enormous environmental and economic damage worldwide
and some of them cause human death. Achieving effective fire fighting is associated with the possibilities
of predicting the characteristics of fire behaviour. Special attention needs to be drawn to meteorological
conditions and their effect on fire spread in a bed of vegetation. On the other hand, studying the effect of
forest fires on the environment is of equal significance for building the strategy and specific actions to be
undertaken in the fire fighting process.
We investigate whether wording, stylistic choices, and online behavior can be used to predict the age category of blog authors. Our hypothesis is that signiﬁcant changes in writing style distinguish pre-social media bloggers from post-social media bloggers. Through experimentation with a range of years, we found that the birth dates of students in college at the time when social media such as AIM, SMS text messaging, MySpace and Facebook ﬁrst became popular, enable accurate age prediction. ...
Scientists, engineers and the like are a strange lot. Unperturbed by societal norms,
they direct their energies to finding better alternatives to existing theories and concocting
solutions to unsolved problems. Driven by an insatiable curiosity, they record
their observations and crunch the numbers. This tome is about the science of crunching.
It’s about digging out something of value from the detritus that others tend to
leave behind. The described approaches involve constructing models to process the
The lake ecosystem of Hanoi has a very important role. However, the water quality in the lakes of Hanoi is declining; they're more and more polluted. Among that, eutrophication is the most popular one. Therefore, the assessment and prediction of eutrophication is necessary. One of the effective tools for assessing and predicting eutrophycation is the use of mathematical models. In this paper, we used the Vollenweider model, empirical watershed model and Jorgensen model to determine the eutrophycation of Bay Mau Lake by phosphorous concentration in the lake water.
This monograph discusses U.S. Air Force progress toward implementing sense and respond logistics or, as defined more broadly, sense and respond combat support. It describes some of the research that has been conducted on the military combat support system, focusing on improvements in prediction capability,
We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. ...
Biomass Properties and Prediction Tools for Vegetation Wildland-Urban Interface (WUI) Fires 1.1 Overview Wildland fires are natural calamities that bring enormous environmental and economic damage worldwide and some of them cause human death. Achieving effective fire fighting is associated with the possibilities of predicting the characteristics of fire behaviour. Special attention needs to be drawn to meteorological conditions and their effect on fire spread in a bed of vegetation.
We consider the problem of predicting which words a student will click in a vocabulary learning system. Often a language learner will ﬁnd value in the ability to look up the meaning of an unknown word while reading an electronic document by clicking the word. Highlighting words likely to be unknown to a reader is attractive due to drawing his or her attention to it and indicating that information is available. However, this option is usually done manually in vocabulary systems and online encyclopedias such as Wikipedia. Furthurmore, it is never on a per-user basis. ...
We present a global joint model for lemmatization and part-of-speech prediction. Using only morphological lexicons and unlabeled data, we learn a partiallysupervised part-of-speech tagger and a lemmatizer which are combined using features on a dynamically linked dependency structure of words. We evaluate our model on English, Bulgarian, Czech, and Slovene, and demonstrate substantial improvements over both a direct transduction approach to lemmatization and a pipelined approach, which predicts part-of-speech tags before lemmatization. ...
This paper focuses on the analysis and prediction of so-called aware sites, deﬁned as turns where a user of a spoken dialogue system ﬁrst becomes aware that the system has made a speech recognition error. We describe statistical comparisons of features of these aware sites in a train timetable spoken dialogue corpus, which reveal signiﬁcant prosodic differences between such turns, compared with turns that ‘correct’ speech recognition errors as well as with ‘normal’ turns that are neither aware sites nor corrections. ...
Near-perfect automatic accent assignment is attainable f o r citation-style speech, but better computational models are needed to predict accent in extended, spontaneous discourses. This paper presents an empirically motivated theory o f the discourse focusing nature o f accent in spontaneous speech. Hypotheses based on this theory lead to a new approach to accent prediction, in which patterns of deviation from citation form accentuation, defined at the constituent or noun phrase level, are atttomatically learned from an annotated corpus. ...
We present a new chart parsing method for Lambek grammars, inspired by a method for DTree grammar parsing. The formulae of a Lambek sequent are firstly converted into rules of an indexed grammar formalism, which are used in an Earley-style predictive chart algorithm. The method is non-polynomial, but performs well for practical purposes - - much better than previous chart methods for Lambek grammars.
Online community is an important source for latest news and information. Accurate prediction of a user’s interest can help provide better user experience. In this paper, we develop a recommendation system for online forums. There are a lot of differences between online forums and formal media. For example, content generated by users in online forums contains more noise compared to formal documents. Content topics in the same forum are more focused than sources like news websites.
Text prediction is the task of suggesting text while the user is typing. Its main aim is to reduce the number of keystrokes that are needed to type a text. In this paper, we address the inﬂuence of text type and domain differences on text prediction quality. By training and testing our text prediction algorithm on four different text types (Wikipedia, Twitter, transcriptions of conversational speech and FAQ) with equal corpus sizes, we found that there is a clear effect of text type on text prediction quality: training and testing on the same text type gave percentages of saved...
Morphological lexica are often implemented on top of morphological paradigms, corresponding to different ways of building the full inﬂection table of a word. Computationally precise lexica may use hundreds of paradigms, and it can be hard for a lexicographer to choose among them. To automate this task, this paper introduces the notion of a smart paradigm. It is a metaparadigm, which inspects the base form and tries to infer which low-level paradigm applies. If the result is uncertain, more forms are given for discrimination.
We propose a set of open-source software modules to perform structured Perceptron Training, Prediction and Evaluation within the Hadoop framework. Apache Hadoop is a freely available environment for running distributed applications on a computer cluster. The software is designed within the Map-Reduce paradigm. Thanks to distributed computing, the proposed software reduces substantially execution times while handling huge data-sets. The distributed Perceptron training algorithm preserves convergence properties, thus guaranties same accuracy performances as the serial Perceptron. ...
Concerns about the cost and quality of health care have resulted in a national effort to determine the health outcomes of medical and surgical services. This report concentrates on developing criteria that risk-assessment systems should meet to permit consumers to intelligently evaluate them. It also presents a comparison of several selected mortality prediction models.......
Machine learning is all about making predictions; language is full of complex rich structure. Structured prediction marries these two. However, structured prediction isn’t always enough: sometimes the world throws even more complex data at us, and we need reinforcement learning techniques.
This paper extends the training and tuning regime for phrase-based statistical machine translation to obtain ﬂuent translations into morphologically complex languages (we build an English to Finnish translation system). Our methods use unsupervised morphology induction. Unlike previous work we focus on morphologically productive phrase pairs – our decoder can combine morphemes across phrase boundaries. Morphemes in the target language may not have a corresponding morpheme or word in the source language.