Oracle Database 11g Performance Tuning Recipes is a ready reference for database administrators in need of immediate help with performance issues relating to Oracle Database. The book takes an example-based approach, wherein each chapter covers a specific problem domain. Within each chapter are "recipes," showing by example how to perform common tasks in that chapter’s domain. Solutions in the recipes are backed by clear explanations of background and theory from the author team. Whatever the task, if it’s performance-related, you’ll probably find a recipe and a solution in this book....
The Handbook of Bioinspired Algorithms and Applications seeks to provide an opportunity for researchers
to explore the connection between biologically inspired (or bioinspired) techniques and the development
of solutions to problems that arise in a variety of problem domains. The power of bioinspired paradigms
lies in their capability in dealingwith complex problemswith little or no knowledge about the search space,
and thus is particularly well suited to deal with a wide range of computationally intractable optimizations
and decision-making applications....
Due to the enormous progress in computer technology and numerical methods
that have been achieved in recent years, the use of numerical simulation methods
in industry gains more and more importance. In particular, this applies
to all engineering disciplines. Numerical computations in many cases offer a
cost effective and, therefore, very attractive possibility for the investigation
and optimization of products and processes.
We show that the Dirichlet to Neumann map for the equation ∇·σ∇u = 0 in a two-dimensional domain uniquely determines the bounded measurable conductivity σ. This gives a positive answer to a question of A. P. Calder´n o from 1980. Earlier the result has been shown only for conductivities that are suﬃciently smooth. In higher dimensions the problem remains open. Contents Introduction and outline of the method
The purpose of ebook Control engineering problems with solutions is to provide both worked examples and additional problems, with answers only. A major objective is to enable the reader to develop confidence in analytical work by showing how calculations can be checked using Matlab/Simulink.
We consider a semi-supervised setting for domain adaptation where only unlabeled data is available for the target domain. One way to tackle this problem is to train a generative model with latent variables on the mixture of data from the source and target domains. Such a model would cluster features in both domains and ensure that at least some of the latent variables are predictive of the label on the source domain.
This paper presents grammar error correction for Japanese particles that uses discriminative sequence conversion, which corrects erroneous particles by substitution, insertion, and deletion. The error correction task is hindered by the difﬁculty of collecting large error corpora. We tackle this problem by using pseudoerror sentences generated automatically.
Call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical customer issues and their solutions, greeting styles. Currently these models are manually created over time.
We describe an approach to domain adaptation that is appropriate exactly in the case when one has enough “target” data to do slightly better than just using only “source” data. Our approach is incredibly simple, easy to implement as a preprocessing step (10 lines of Perl!) and outperforms stateof-the-art approaches on a range of datasets. Moreover, it is trivially extended to a multidomain adaptation problem, where one has data from a variety of different domains.
Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting perspective. We formally analyze and characterize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, corresponding to the different distributions of instances and classiﬁcation functions in the source and the target domains. ...
We notion of argue that in domains can be where it a strong can be Mann and Moore , on the other hand, while assembling texts dynamically to suit their audience, do so by "over-generating" the set of facts that will be related, and then passing them all through a special filter, leaving out those that are judged to be already known to the audience and letting through those that are new. McKeown  uses a similar technique -- her generator, like Mann and Moore's, must examine every potentially mentionable object in the domain data base and make...
We investigate the problem of domain adaptation for parallel data in Statistical Machine Translation (SMT). While techniques for domain adaptation of monolingual data can be borrowed for parallel data, we explore conceptual differences between translation model and language model domain adaptation and their effect on performance, such as the fact that translation models typically consist of several features that have different characteristics and can be optimized separately.
We examine some of the frequently disregarded subtleties of tokenization in Penn Treebank style, and present a new rule-based preprocessing toolkit that not only reproduces the Treebank tokenization with unmatched accuracy, but also maintains exact stand-off pointers to the original text and allows ﬂexible conﬁguration to diverse use cases (e.g. to genreor domain-speciﬁc idiosyncrasies).
This study presents a novel approach to the problem of system portability across different domains: a sentiment annotation system that integrates a corpus-based classiﬁer trained on a small set of annotated in-domain data and a lexicon-based system trained on WordNet.
Sentence compression is the task of producing a summary at the sentence level. This paper focuses on three aspects of this task which have not received detailed treatment in the literature: training requirements, scalability, and automatic evaluation. We provide a novel comparison between a supervised constituentbased and an weakly supervised wordbased compression algorithm and examine how these models port to different domains (written vs. spoken text).
My consents are organized within the framework suggested by the Panel Chair, Barbara Grosz, which I find very appropriate. All of my conlnents pertain to the various issues raised by her; however, wherever possible I will discuss these issues more in the context of the "information seeking" interaction and the data base doma/n. The primary question is how the purpose of the interaction or "the problem context" affects what is said and how it is interpreted. The ~ separate aspects of this question that must be considered are the function and the domain of the discourse. I. Types of...
This abstract describes a natural language system which deals usefully with ungrammatical input and describes some actual and potential applications of it in computer aided second language learning. However, this is not the only area in which the principles of the system might be used, and the aim in building it was simply to demonstrate the workability of the general mechanism, and provide a framework for assessing developments of it. BACKGROUND The really hard problem in natural language processing, for any purpose, is the role of non-linguistic knowledge in the understanding process. ...
The structure of problem-solving discourse in the expert advising setting can be modeled by adding a layer of metaplans to a plan-based model of the task domain. Classes of metaplans are introduced to model both the agent's gradual refinement and instantiation of a domain plan for a task and the space of possible queries about preconditions or fillers for open variable slots that can be motivated by the exploration of particular classes of domain plans.