Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
Previous sections have reviewed issues in describing grammar, issues that were mainly concerned with what to describe, how to describe it and how to account for differing approaches and their implications in terms of theory and pedagogy in applied linguistics. But however precise and thorough researchers may attempt to be in addressing these issues, there are certain limitations to descriptions of grammar given in isolation from all other parts of the language system
There are many kinds of methods of teaching grammar, no matter what they are, these approaches can generally be classified into two approaches-deductive and inductive. What an appropriate grammar teaching approach is by examining the inductive and deductive approaches to grammar teaching and learning. It starts with the definitions of inductive and deductive approaches to grammar teaching, followed by a contrastive study of these two approaches in terms of both the bases and the application. Finally, it explores the inductive approach and outlines the benefits of this approach and suggests an alternative view of grammar teaching.
In response to the misconception that Communicative Language Teaching means no teaching of grammar, it is argued that grammar is as important as traffic rules for safe and smooth traffic on the road. To achieve appropriate and effective commu-nication, a communicative approach to college grammar teaching and learning is proposed. Both teachers and learners should change their attitudes toward and conceptions about grammar teaching and learning;additionally, teaching grammar in the com-pany of reading and writing helps learners learn and acquire grammar in meaningful contexts.
The new role of grammar instruction now is based on the increasing understandings that grammar per se is a comprehensive conglomerate. The paper examines the inductive approach to EFL grammar instruction. It starts with some theoretical considerations on inductive approach to formal grammar instruction, followed by its methodological considerations such as how to deal with grammar generalizations and exceptions, learner variables, and grammar complexity, and proposes a sensitive and dynamic balance of explorations and explanations in EFL grammar instruction.
Grammar is an important part of language learning. In order for students to have a functional knowledge of a language (in other words, that they can spontaneously produce language) they must have at least some knowledge about the grammatical con⁃structs of the language in question. How grammar can be taught? Considering various second language teaching methods, teaching grammar through Communicative Language Teaching Approach is the most talked. Emphasis in this article is put on the applica⁃tion of Communicative Language Teaching Approach in grammar teaching in college English classes.
Killgallon, Don; Killgallon, Jenny
Across America, in thousands of classrooms, from elementary school to high school, the time-tested sentence-composing approach has given students tools to become better writers. Now the authors present a much anticipated sentence-composing grammar worktext for college writing. This book presents a new and easier way to understand grammar: (1) Noun…
When it comes to definitions of grammar,confusion abounds.One problem is that the word grammar means different things to different people.For many,the term sugges tsa list of do's and don't's,rules that tell us we should say It is I,not It is me,that we should not say ain't,or that weshould avoid ending a sentence with a preposition.For oth
To solve the ambiguous understanding of Grammar Teaching position,based on explicit grammatical knowledge,this paper discusses the grammar position in EFL,compares both its pros and cons between deductive and inductive approaches,and indicates that grammar teaching by either approach alone has disadvantages,should adopt a combination technique.
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
Rule, Hannah J.
This article applies the neuroscientific concept of embodied simulation--the process of understanding language through visual, motor, and spatial modalities of the body--to rhetorical grammar and sentence-style pedagogies. Embodied simulation invigorates rhetorical grammar instruction by attuning writers to the felt effects of written language,…
Datta, Sutapa; Mukhopadhyay, Subhasis
Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.
Datta, Sutapa; Mukhopadhyay, Subhasis
Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner. PMID:25886273
Full Text Available Proponents of a Universal Grammar argue that humans are born with a dedicated language system that shapes and restricts the number of grammars found in human languages (Chomsky, 2005. It is essentially innate and has a genetic manifestation. Such an innate system is necessary because human grammars are too complex to be passed on through social interactions and probabilistic learning alone. However, this view is contested by a combination of emergentist approaches and a number of studies suggest that many of the core assumptions of Universal Grammar are either unnecessary or do not hold. Furthermore, this review will explore theoretical criticism of the Universal Grammar research programme.
Hussein Islam Abdullah
Full Text Available Over the years, there has been a decline in the competency of the English Language in Malaysian schools. Many parties among them the Ministry of Education, relevant NGOs, academicians and people have expressed concern over the matter. The Education Ministry through its transformational policy has taken several measures to overcome the matter. It is employing appropriate strategies to solve the problems. The focus is on learning and teaching strategies as well as the content of the language. There is no doubt that grammar is a very important component in acquiring the language in primary and secondary schools. The English teachers mostly use the communicative approach in teaching grammar. This is in line with the KBSR syllabus in mid 1980s which emphasized on the communicative method. Teachers’ training and materials such as textbooks cater for the covert method. However, some tend to ignore the structural approach which is equally effective and meaningful to increase the level of the students’ proficiency which was popular in the 1960s. The paper discusses on the two different approaches used – the covert and overt approaches – their strengths as well as weaknesses. Application of both approaches is also taken into consideration giving a better view of how grammar should be taught in schools.
Full Text Available This paper describes a corpus-based approach to teaching and learning spoken grammar for English for Academic Purposes with reference to Bhatia’s (2002 multi-perspective model for discourse analysis: a textual perspective, a genre perspective and a social perspective. From a textual perspective, corpus-informed instruction helps students identify grammar items through statistical frequencies, collocational patterns, context-sensitive meanings and discoursal uses of words. From a genre perspective, corpus observation provides students with exposure to recurrent lexico-grammatical patterns across different academic text types (genres. From a social perspective, corpus models can be used to raise learners’ awareness of how speakers’ different discourse roles, discourse privileges and power statuses are enacted in their grammar choices. The paper describes corpus-based instructional procedures, gives samples of learners’ linguistic output, and provides comments on the students’ response to this method of instruction. Data resulting from the assessment process and student production suggest that corpus-informed instruction grounded in Bhatia’s multi-perspective model can constitute a pedagogical approach in order to i obtain positive student responses from input and authentic samples of grammar use, ii help students identify and understand the textual, genre and social aspects of grammar in real contexts of use, and therefore iii help develop students’ ability to use grammar accurately and appropriately.
How to teach English grammar effectively is an important subject of the comprehensive course for English majors.The Communicative approach must be applied to the English grammar teaching.This paper illustrates the features of communicative grammar teaching and necessity of applying communicative approach to English Grammar Teaching and how to apply communicative approach to English Grammar Teaching.In classroom teaching,a variety of communicative situations should be created without dull teaching;a colorful of classroom activities should be designed;real situation communicative practices should be intensified to make English grammar teaching active and efficient.
Constructionist approach with its brand-new perspective has begun to demonstrate its dynamic power. This paper attempts to review the basic ideas, achievements and comparison with generative grammar of Construction Grammar and generalize some problems and future research prospects.
Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776
Juang, C. H.; Huang, X. H.; Fleming, J. W.
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Full Text Available Gender stereotyping in educational materials (especially in EFL textbooks has been a common theme in linguistic research (cf., e. g., Hellinger 1980; Porreca 1984; Freebody/Baker 1987; Sunderland 1994; Lee/Collins 2010. However, very little attention has been paid to the representation of men and women in EFL/ESL grammar textbooks; i. e. the way both genders are portrayed in constructed examples of usage and practice sentences. The present contribution is intended to fill this gap. The paper investigates the scope of gender stereotyping from a diachronic perspective: it seeks to demonstrate whether and how the images of men and women have changed following the dissemination of guidelines for non-sexist language and equal treatment of the two genders in English language educational materials. To this aim, two corpora have been compiled. The first one includes sentences derived from three EFL textbooks published in the 1970s and 1980s, while the other one contains analogous data from three 21st century titles. The contrastive analysis of the sentences in the two corpora across 11 semantic domains has found that the recently published grammar textbooks portray the two genders in a much less stereotyped way than the 20th century course books.
Cloutier, R.A.; Hamilton-Brehm, A.M.; Kretzschmar, W.A.
This collection of essays focuses on current approaches to variation and change in historical English grammar and lexicon. Of the twelve papers in the collection, half are based on grammar and syntax, half on lexical developments. The volume highlights the contributions that strong empirical
The aim of this paper is to explore the analysis of Universal Grammar (UG) approach on Second Language Acquisition (SLA). This paper is significant as the sources for teacher or researcher of the second language since this elaboration is deeply focusing on the use of UG on SLA. The method used in this academic writing is inductive method of…
This paper puts forward to compare teaching method between grammar-translation and CLT in grammar teaching. Gram⁃mar leaning is a basic concept in English learning as grammar is an important element in a communicative approach to language. This paper discussed CLT method can help and encourage student to study, however, grammar-translation method is able to under⁃stand.
Full Text Available This research aims to define a sustainable resource in Computer-Assisted Language Learning (CALL. In order for a CALL resource to be sustainable it must work within existing educational curricula. This feature is a necessary prerequisite of sustainability because, despite the potential for educational change that digitalization has offered since the nineteen nineties, curricula in traditional educational institutions have not fundamentally changed, even as we move from a pre-digital society towards a digital society. Curricula have failed to incorporate CALL resources because no agreed-upon pedagogical language enables teachers to discuss CALL classroom practices. Systemic Functional Grammar (SFG can help to provide this language and bridge the gap between the needs of the curriculum and the potentiality of CALL-based resources. This paper will outline how SFG principles can be used to create a pedagogical language for CALL and it will give practical examples of how this language can be used to create sustainable resources in classroom contexts.
Full Text Available Although history of grammar instruction dates back far in time, it is only since the sixties that we see various methods through which this subject is taught. What was done took place as an in-class activity with almost no tasks performed out of class except for assignments. Thus, this descriptive case study aims to add one new dimension to the already existing methodology introducing a blog-integrated approach emphasizing individual-generated learning. Unlike its predecessors, the approach requires individuals to select texts, analyze targeted structural points in authentic texts, and produce similar structures through modelling, all performed on weblogs, with full participation and collaboration of learners embracing the notion of “self-directed” learning. Although the designed approach aims to teach and reinforce English grammar to English learners, it does not limit itself to this field. All subjects, requiring activation of latent knowledge can certainly benefit from it, notably the L2 domain
This paper presents a comprehensive review of the functional approach and cognitive approach to the nature of language and its relation to other aspects of human cognition. The paper starts with a brief discussion of the origins and the core tenets of the two approaches in Section 1. Section 2 discusses the similarities and differences between the three full-fledged structural functional grammars subsumed in the functional approach： Halliday＇s Systemic Functional Grammar （SFG）, Dik＇s Functional Grammar （FG）, and Van Valin＇s Role and Reference Grammar （RRG）. Section 3 deals with the major features of the three cognitive frameworks： Langacker＇s Cognitive Grammar （CG）, Goldberg＇s Cognitive Construction Grammar （CCG）, and Croft＇s Radical Construction Grammar （RCG）. Section 4 compares the two approaches and attempts to provide a unified functional-cognitive grammar. In the last section, the author concludes the paper with remarks on the unidirectional shift from functional grammar to cognitive grammar that may indicate a reinterpretation of the traditional relationship between functional and cognitive models of grammar.
Preminger, Arie; Franck, Raphael
The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...
Crawford, William J.
Grammar is a component in all language skills: reading, writing, speaking, and listening. Teachers need to know rules of grammar (teacher knowledge) as well as techniques that help students use grammar effectively and effortlessly (teaching knowledge). Using reflective practice to help teachers become comfortable with teaching grammar, this…
Instructors' edition without answer keysDiscount of 20% offered when 10 ebooks are sold- e.g. they will be sold for 263.60/ £151.90 instead of 329.50/£189.90French Grammar in Context presents a unique and exciting approach to learning grammar. Authentic texts from a rich variety of sources, literary and journalistic, are used as the starting point for the illustration and explanation of key areas of French grammar. Each point is consolidated with a wide range of written and spoken exercises. Grammar is presented not as an end in itself, but as a
Mastering grammar is the foundation in the proficiency of a language. Grammar teaching is also an essential part of language teaching. However, with the communicative approach was introduced into China, many foreign language teachers gradually make little of grammar teaching. In terms of the theory of linguistics, this paper specifically explores…
The value of grammar instruction in foreign language learning and teaching has been a focus of debate for quite some time, which has resulted in different views on grammar and grammar teaching as well as different teaching approaches based on different perspectives or in different language learning contexts. To explore some modes for grammar…
Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.
Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.
Algorithms for the construction of the Chomsky and Greibach normal forms for a fuzzy context-free grammar using the algebraic approach are presented and illustrated by examples. The results obtained in this paper may have useful applications in fuzzy languages, pattern recognition, information storage and retrieval, artificial intelligence, database and pictorial information systems. 16 references.
A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena....... The formalism extends previous logic programming based grammars with a form of context-sensitive rules and the possibility to include extra-grammatical hypotheses in both head and body of grammar rules. Among the applications are straightforward implementations of Assumption Grammars and abduction under...... integrity constraints for language analysis. CHR grammars appear as a powerful tool for specification and implementation of language processors and may be proposed as a new standard for bottom-up grammars in logic programming....
A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena....... The formalism extends previous logic programming based grammars with a form of context-sensitive rules and the possibility to include extra-grammatical hypotheses in both head and body of grammar rules. Among the applications are straightforward implementations of Assumption Grammars and abduction under...... integrity constraints for language analysis. CHR grammars appear as a powerful tool for specification and implementation of language processors and may be proposed as a new standard for bottom-up grammars in logic programming....
In this article Karen Adams demonstrates how to incorporate group grammar techniques into a classroom activity. In the activity, students practice using the target grammar to do something they naturally enjoy: learning about each other.
Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named
Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A
The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming
Examines the theoretical rationales (universal grammar, information-processing theories, skill-learning theories) for input-based grammar teaching and reviews classroom-oriented research (i.e., enriched-input studies, input-processing studies) that has integrated this option. (Author/VWL)
As Wight (1999, p.33) pointed out to“know a language was to know the grammar of it”, hence grammar teaching is usually the main approach in second or foreign language teaching. This paper presents an analysis from three aspects to il-lustrate why classroom grammar teaching benefits adult learners. However, if grammar is overstated, some negative results will occur. Therefore a balance between grammar teaching and communicative skill teaching is need, as is a balance between accuracy and fluency.
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a
ZHANG Jing-wen; LI Yi-an
English grammar is thought as one of the most important parts in both language learning and teaching. While few peo⁃ple know there is more than one kind of English grammar. This essay provides the features and comparison between two com⁃monly used English grammar, namely descriptive grammar and prescriptive grammar, and assist English teachers to explore further in grammar teaching.
@@ The trouble with teaching grammar is that we are never quite sure whether it works or not:its effects are uncertain and hard to assess.Michael Swan looks at grammar teaching and the carry-over to spontaneous production by students.
A Communicative Grammar of English has long been established as a grammar innovative in approach, reliable in coverage, and clear in its explanations. This fully revised and redesigned third edition provides up-to-date and accessible help to teachers, advanced learners and undergraduate students of English. Part One looks at the way English grammar varies in different types of English, such as 'formal' and 'informal', 'spoken' and 'written'; Part Two focuses on the uses of grammar rather than on grammatical structure and Part Three provides a handy alphabetically arranged guide to
Lee, Kyu J.; Kunii, T. L.; Noma, T.
In this paper, we propose a syntactic pattern recognition method for non-schematic drawings, based on a new attributed graph grammar with flexible embedding. In our graph grammar, the embedding rule permits the nodes of a guest graph to be arbitrarily connected with the nodes of a host graph. The ambiguity caused by this flexible embedding is controlled with the evaluation of synthesized attributes and the check of context sensitivity. To integrate parsing with the synthesized attribute evaluation and the context sensitivity check, we also develop a bottom up parsing algorithm.
Full Text Available German grammar is constantly perceived as difficult, a strong disincentive to learning the language, yet the underlying principles are basically simple. If applied consistently, using uncomplicated techniques based on the concept of markedness, German of a high level of accuracy can be produced.Starting with the unjustifiably much-feared adjective endings, this pilot scheme, funded with the help of the Challenge Fund of the University of Kent, demonstrates the principles of German word-order and the marking of case and gender and how, with some minor adjustment, the easily learnable der/die/das paradigm and the awareness that once this has been mastered and case and gender have already been marked, only one of the two unmarked endings -e or -en is required to give all the necessary patterns for producing correctly inflected adjective endings. If case and gender are not marked by an article the endings of der/ die/ das can with some slight modifications be added to the adjective. So with this easily acquired knowledge, adjective endings can be handled with confidence.On this basis the program, still a work in progress, offers a theoretical grounding couched in understandable terms, a terminological glossary and an easily accessible expandable set of technologically based exercises with extensive linked help functions. These can be used serially as an entire learning unit or selectively to enable students to put their knowledge into practice and improve their skill and success in German.Following this pilot, the approach is to be extended to other common grammatical problems, e. g. word order, passive (Zustands- vs. Vorgangspassiv, indirect speech, subordinate clauses, prepositions of movement and location, past tense forms and subjunctive use.
Fokkens, A.S.; Avgustinova, T.; Zhang, Yi
This paper introduces the CLIMB (Comparative Libraries of Implementations with Matrix Basis) methodology and grammars. The basic idea behind CLIMB is to use code generation as a general methodology for grammar development in order to create a more systematic approach to grammar development. The
Of the many issues surrounding grammar, perhaps the hottest debate is whether to teach it or not. We review briefly argu⁃ments against and in support of grammar teaching before examining current grammar approaches in second language teaching.
Full Text Available This paper presents a new systematic approach for the uniform random generation of combinatorial objects. The method is based on the notion of object grammars which give recursive descriptions of objects and generalize context-freegrammars. The application of particular valuations to these grammars leads to enumeration and random generation of objects according to non algebraic parameters.
Robinson, Jane J
.... The theory of systematic variation affords better direction for gathering data on rule-governed language use and a means for representing the results in formal grammars that predict speech behavior...
This paper describes the nature of grammar as "universalness". The universal grammar indicates that all the languages in the world have identical grammar. This is discussed from three aspects, which gives insight into grammar acquisition.
Full Text Available This paper presents our proposal and the implementation of an algorithm for automated refactoring of context-free grammars. Rather than operating under some domain-specific task, in our approach refactoring is perfomed on the basis of a refactoring task defined by its user. The algorithm and the corresponding refactoring system are called mARTINICA. mARTINICA is able to refactor grammars of arbitrary size and structural complexity. However, the computation time needed to perform a refactoring task with the desired outcome is highly dependent on the size of the grammar. Until now, we have successfully performed refactoring tasks on small and medium-size grammars of Pascal-like languages and parts of the Algol-60 programming language grammar. This paper also briefly introduces the reader to processes occurring in grammar refactoring, a method for describing desired properties that a refactored grammar should fulfill, and there is a discussion of the overall significance of grammar refactoring.
Vaeth, Michael; Skovlund, Eva
For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.
Culik II and Cogen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this paper we consider an analogous extension of the LL(k) grammars called the LL-regular grammars. The relation of this class of grammars to other classes of grammars will be shown. Any LL-regular
Answering key questions such as 'Why study grammar?' and 'What is standard English?', Introducing English Grammar guides readers through the practical analysis of the syntax of English sentences. With all special terms carefully explained as they are introduced, the book is written for readers with no previous experience of grammatical analysis. It is ideal for all those beginning their study of linguistics, English language or speech pathology, as well as students with primarily literary interests who need to cover the basics of linguistic analysis. The approach taken is in line with current research in grammar, a particular advantage for students who may go on to study syntax in more depth. All the examples and exercises use real language taken from newspaper articles, non-standard dialects and include excerpts from studies of patients with language difficulties. Students are encouraged to think about the terminology as a tool kit for studying language and to test what can and cannot be described using thes...
Livingston, Sue; Toce, Andi; Casey, Toce; Montoya, Fernando; Hart, Bonny R.; O'Flaherty, Carmela
This study first briefly describes an instructional approach to teaching grammar known as X-Word Grammar and then compares its effectiveness in assisting students in achieving grammatical accuracy with traditionally taught grammar. Two groups of L2 pre-college students were taught using curricula and practice procedures in two different grammar…
Dorier, Matthieu; Ibrahim, Shadi; Antoniu, Gabriel; Ross, Rob
The increasing gap between the computation performance of post-petascale machines and the performance of their I/O subsystem has motivated many I/O optimizations including prefetching, caching, and scheduling. In order to further improve these techniques, modeling and predicting spatial and temporal I/O patterns of HPC applications as they run has become crucial. In this paper we present Omnisc'IO, an approach that builds a grammar-based model of the I/O behavior of HPC applications and uses it to predict when future I/O operations will occur, and where and how much data will be accessed. To infer grammars, Omnisc'IO is based on StarSequitur, a novel algorithm extending Nevill-Manning's Sequitur algorithm. Omnisc'IO is transparently integrated into the POSIX and MPI I/O stacks and does not require any modification in applications or higher-level I/O libraries. It works without any prior knowledge of the application and converges to accurate predictions of any N future I/O operations within a couple of iterations. Its implementation is efficient in both computation time and memory footprint.
Dries F. Benoit
Full Text Available After its introduction by Koenker and Basset (1978, quantile regression has become an important and popular tool to investigate the conditional response distribution in regression. The R package bayesQR contains a number of routines to estimate quantile regression parameters using a Bayesian approach based on the asymmetric Laplace distribution. The package contains functions for the typical quantile regression with continuous dependent variable, but also supports quantile regression for binary dependent variables. For both types of dependent variables, an approach to variable selection using the adaptive lasso approach is provided. For the binary quantile regression model, the package also contains a routine that calculates the fitted probabilities for each vector of predictors. In addition, functions for summarizing the results, creating traceplots, posterior histograms and drawing quantile plots are included. This paper starts with a brief overview of the theoretical background of the models used in the bayesQR package. The main part of this paper discusses the computational problems that arise in the implementation of the procedure and illustrates the usefulness of the package through selected examples.
Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.
To the problem of neglecting grammar teaching when the Communicative approach is encouraged,this paper tries to analyze the position of teaching grammar and put forward some suggestions on how to balance grammar and communication teaching.
Forest grammar,a new type of high-dimensional grammar,is proposed in this paper,of which both the left and the right parts of every production are concatenations of tree structures.A classification of forest grammar is studied,especially,a subclass of the forest grammar,i.e.the context-sensitive forest grammar,and one of its subclasses is defined,called the weak precedence forest grammar.
This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.
Hengeveld, K.; Mackenzie, J.L.
This article presents a proposal for the organization of the Contextual Component in Functional Discourse Grammar. A guiding principle in this proposal is that, given the fact that Functional Discourse Grammar is a theory of grammar, the Contextual Component should provide the information that is
Full Text Available The present research attempts to assess teachers' perception on the success of using inductive approach in the classroom at Preparatory Year Program, Najran University. It also inquires the difficulties that are usually faced by students (in teachers' opinion in a grammar class. In order to collect data, 20 teachers were requested to fill in a questionnaire consisting of ten statements (based on key elements of inductive teaching. The questionnaires were analyzed by using 5-Point Likert-scales of agreement. Besides, the researcher also personally interviewed the teachers by using a set of certain questions covering the same theme. The study is divided into two parts; the first part contains detailed analysis and discussion on the statements of the questionnaire and the second part comprises a detailed analysis and discussion on the responses of interview. As results, it is revealed that a majority of teachers supported the use of inductive approach in the classroom because of its learner-centred nature. Inductive methods help students acquire the critical thinking and self-directed learning skills (Prince & Felder, 2007. However, some teachers (with a negligible percentage were not so enthusiastic about using inductive approach.
King, Lid, Ed.; Boaks, Peter, Ed.
Papers from a conference on the teaching of grammar, particularly in second language instruction, include: "Grammar: Acquisition and Use" (Richard Johnstone); "Grammar and Communication" (Brian Page); "Linguistic Progression and Increasing Independence" (Bernardette Holmes); "La grammaire? C'est du bricolage!" ("Grammar? That's Hardware!") (Barry…
Grammar teaching, as one essential aspect of English language teaching (ELT), has been and continues to be an area of some controversy and debates, which entails the emergency of diverse classroom practices for language teachers:Focus on Form or Focus on FormS. Connected with the specific context of grammar teaching in Chinese higher education, this paper tends to re-consider the place of grammar teaching in the classroom, and come up with some feasible approaches to instructing grammar so as to make appropriate connections between grammatical forms and the meanings.
@@ Grammar is often misunderstood in the language teaching field.The misconception lies in the view that grammar is a collection of arbitrary rules about static structures in the language.Further questionable claims are that the structures do not have to be taught,learners will acquire them on their own,or if the structures are taught,the lessons that ensue will he boring.Consequently,communicative and proficiency-based teaching approaches sometimes unduly limit grammar instruction.Of the many claims about grammar that deserve to be called myths,this digest will challenge ten.
Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad
In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.
Instead of being a boring subject, grammar is in fact one of the most exciting, creative, relevant subjects. It is sometimes described as the skeleton of a language, but it is much more than bones. It is the language's heartbeat, for without grammar; there can be no meaningful or effective communication. And grammar has different definitions and categories according to different contexts. By first reviewing the past linguists, especially those grammarians and their research, the paper makes some comparisons between some categories of grammar and puts forward that there is no 'good' or 'bad' grammar but knowing grammar or knowing about grammar really has a close relationship with effective communication.
Grammar teaching is the important component of communicative language teaching, and also the teaching content of communicative approach. This study is going to analyze the status of English grammar learning, the theoretical basis of CLT, and some difficulties with regard to grammar education in China, while discussing teachers might try to adjust the current grammar approach in communicative English teaching.
Jurhill, Dennis A.
"O! this learning, what a thing it is." -W. Shakespeare, "The Taming of the Shrew." The aim of this action research was to find out if active grammar involvement amongst students might lead to better results. My approach was to activate my students during grammar instruction by using cooperative learning: that is a form of…
Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)
New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.
Full Text Available A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data. Inaccuracy in model inputs is typically ignored on model fitting. We provide a practical approach for regression with inaccurate data: the mathematics is easy, and the linear programming formulations simple to use even in a spreadsheet. This self-contained elementary presentation introduces interval linear systems and requires only basic knowledge of algebra. Feature selection is automatic; but can be controlled to find only a few most relevant inputs; and joint feature selection is enabled for multiple modeled outputs. With more features than cases, a novel connection to compressed sensing emerges: robustness against interval errors-in-variables implies model parsimony, and the input inaccuracies determine the regularization term. A small numerical example highlights counterintuitive results and a dramatic difference to total least squares.
Fekri Ali Shawtari
Full Text Available Corporate governance has become a centre of attention in corporate management at both micro and macro levels due to adverse consequences and repercussion of insufficient accountability. In this study, we include the Malaysian stock market as sample to explore the impact of intense monitoring on the relationship between intellectual capital performance and market valuation. The objectives of the paper are threefold: i to investigate whether intense monitoring affects the intellectual capital performance of listed companies; ii to explore the impact of intense monitoring on firm value; iii to examine the extent to which the directors serving more than two board committees affects the linkage between intellectual capital performance and firms' value. We employ two approaches, namely, the Ordinary Least Square (OLS and the quantile regression approach. The purpose of the latter is to estimate and generate inference about conditional quantile functions. This method is useful when the conditional distribution does not have a standard shape such as an asymmetric, fat-tailed, or truncated distribution. In terms of variables, the intellectual capital is measured using the value added intellectual coefficient (VAIC, while the market valuation is proxied by firm's market capitalization. The findings of the quantile regression shows that some of the results do not coincide with the results of OLS. We found that intensity of monitoring does not influence the intellectual capital of all firms. It is also evident that intensity of monitoring does not influence the market valuation. However, to some extent, it moderates the relationship between intellectual capital performance and market valuation. This paper contributes to the existing literature as it presents new empirical evidences on the moderating effects of the intensity of monitoring of the board committees on the relationship between performance and intellectual capital.
Suleiman, Mani; Demirhan, Haydar; Boyd, Leanne; Girosi, Federico; Aksakalli, Vural
Episodes of care involving similar diagnoses and treatments and requiring similar levels of resource utilisation are grouped to the same Diagnosis-Related Group (DRG). In jurisdictions which implement DRG based payment systems, DRGs are a major determinant of funding for inpatient care. Hence, service providers often dedicate auditing staff to the task of checking that episodes have been coded to the correct DRG. The use of statistical models to estimate an episode's probability of DRG error can significantly improve the efficiency of clinical coding audits. This study implements Bayesian logistic regression models with weakly informative prior distributions to estimate the likelihood that episodes require a DRG revision, comparing these models with each other and to classical maximum likelihood estimates. All Bayesian approaches had more stable model parameters than maximum likelihood. The best performing Bayesian model improved overall classification per- formance by 6% compared to maximum likelihood, with a 34% gain compared to random classification, respectively. We found that the original DRG, coder and the day of coding all have a significant effect on the likelihood of DRG error. Use of Bayesian approaches has improved model parameter stability and classification accuracy. This method has already lead to improved audit efficiency in an operational capacity.
The paper presents a short summary of our work in the area of regression benchmarking and its application to software development. Specially, we explain the concept of regression benchmarking, the requirements for employing regression testing in a software project, and methods used for analyzing the vast amounts of data resulting from repeated benchmarking. We present the application of regression benchmarking on a real software project and conclude with a glimpse at the challenges for the fu...
Camhi, Paul J.; Ebsworth, Miriam Eisenstein
This action research study evaluates a classroom approach incorporating a reflective, metacognitive component within a second language process-oriented writing environment. Inspired by the literature and developed by the first author, this approach seeks to provide English language learners (ELLs) with a command of metalinguistic principles…
The syntactic parsing algorithm of weak precedence forest grammar has been introduced and the correctness and unambiguity of this algorithm have been proved. An example is given to the syntactic parsing procedure of weak precedence forest grammar.
WU Cai-ling; WANG Xi
More and more researchers have now agreed upon the necessity of teaching grammar, but it still remains controversial as how to teach the forms, with the central consideration of not to harm the meaning-focused communicative teaching method. In this essay, one of the issues in grammar teaching will be discussed as how to present new grammar to learners, through evaluating and modifying a particular presentation activity in a grammar-teaching textbook.
Should grammar be taught at all?Is it a hindrance or anaid?Communicative language teaching approach seems to havecast doubts on the value of grammar teaching.The present paperargues that the positive effect of grammar in College Englishteaching and learning should not be overlooked.Grammar servesas a means to the final achievement of language proficiency.Itis time for language teachers to reconsider the role of grammarand to come up with a more appropriate and thus,moreeffective treatment of grammar in College English teaching.
An overview of Noam Chomsky's theories about transformational grammar and phonology is given. Since Chomsky was interested in characterizing what it is to know a language, the ways in which we demonstrate knowledge of our native language are discussed in detail. Particular emphasis is placed on describing how the transformational approach actually…
Yan, Jing; Wang, Yun; Luo, Si-Jun; Qiao, Yan-Jiang
Interpreting the molecular interactions in Chinese herbal medicine will help to understand the molecular mechanisms of Traditional Chinese medicines (TCM) and predict the new pharmacological effects of TCM. Yet, we still lack a method which could integrate the concerned pieces of parsed knowledge about TCM. To solve the problem, a new method named TCM grammar systems was proposed in the present article. The possibility to study the interactions of TCM at the molecular level using TCM grammar systems was explored using Herba Ephedrae Decoction (HED) as an example. A platform was established based on the formalism of TCM grammar systems. The related molecular network of Herba Ephedrae Decoction (HED) can be extracted automatically. The molecular network indicates that Beta2 adrenergic receptor, Glucocorticoid receptor and Interleukin12 are the relatively important targets for the anti-anaphylaxis asthma function of HED. Moreover, the anti-anaphylaxis asthma function of HED is also related with suppressing inflammation process. The results show the feasibility using TCM grammar systems to interpret the molecular mechanism of TCM. Although the results obtained depend on the database absolutely, recombination of existing knowledge in this method provides new insight for interpreting the molecular mechanism of TCM. TCM grammar systems could aid the interpretation of the molecular interactions in TCM to some extent. Moreover, it might be useful to predict the new pharmacological effects of TCM. The method is an in silico technology. In association with the experimental techniques, this method will play an important role in the understanding of the molecular mechanisms of TCM. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Mahaputri, Ratna Andhika
This article provides comprehensive explanation about several models of grammar. The first model of grammar which is explained is considered from the functional grammar and associated with the American linguist Noam Chomsky that is Transformational Grammar. This model of grammar is consisted of three components they are phrase structure rule, the lexicon, and transformation. The second model of grammar which is explained in this article is Minimalist Grammar. This article also compares her...
Grammar learning has often been regarded as a structure based activity .Grammar games which are worth paying attention to and implementing in the classroom can help learner to learn and recall a grammar material in a pleasant, entertaining way and motivate learners,promote the communicative competence and generate the fluency. In this essay, the author compares the use of games in learning grammar with some traditional techniques for grammar presentation and revision, in order to find the advantages of using games. Also the author discusses how to choose appropriate games and when to use games.
S.Y. Park (Sung); W. Wang (Wendun); N. Huang (Naijing)
markdownabstract__Abstract__ Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile regression framework that is robust to model misspecification. Unlike conventional correlation-based tests, the proposed quantile contagion test
Mesic, Vanes; Muratovic, Hasnija
Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge
Full Text Available Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal
Essential French Grammar is an innovative reference grammar and workbook for intermediate and advanced undergraduate students of French (CEFR levels B2 to C1). Its clear explanations of grammar are supported by contemporary examples and lively cartoon drawings. Each chapter contains: * real-life language examples in French, with English translations * a 'key points' box and tables that summarise grammar concepts * a variety of exercises to reinforce learning * a contemporary primary source or literary extract to illustrate grammar in context. To aid your understanding, this book also contains a glossary of grammatical terms in French and English, useful verb tables and a key to the exercises. Together, these features all help you to grasp complex points of grammar and develop your French language skills.
The traditional grammar teaching method can’t make learners communicate in real contexts accurately and luently.The author will probe the effects of communicative approach applied in grammar teaching in this essay.
Morrissey, Glenda; Young, Barbara N.
The variety of theories relating to teaching ESL learners leads to contradictory ideas about teaching a second language. This paper focuses on the continuing importance of grammar in teaching and the current resurgence in interest in returning to grammar as an important component in the classroom.
This article aims to answer three questions:(1)Why there exists a discrepancy between the learner’sgrammar knowledge and their communicative skills?(2)What problems are there with grammar tests andteaching?(3)How should grammar be taught as"away of talking"rather than"a description of rules"?
@@ 1 Definition of grammar Grammar is the science dealing with the systematic rules of a language, its forms, inflections, syntax, and the art of using them correctly. It is summarized from language use and practice, and reflects the logic of thinking in people's speech or writing.
In this case study, I will show how directing a movie on grammar can help students improve their oral skills as well as their language competency, team working and planning skills, and also teach them about learning itself. I will present an innovative teaching project that uses the medium of film to get students engaged with grammar and that aims…
We have always advocated that those teaching the Use of English must seek out novel ways of teaching the grammar of English to take out the drudgery of the present approach. Here, we proposed using Linguistic deviation as a tool for teaching English grammar. This approach will produce students who are both strong in ...
This response to Azar (this volume) intends to discuss from an academic's perspective the main points raised in her paper (i.e., grammar-based instruction and its relation to focus on form and error correction) and, to encourage a more concept-based approach to grammar instruction (CBT). A CBT approach to language development argues that the…
Buchmueller, Thomas C; Grazier, Kyle; Hirth, Richard A; Okeke, Edward N
We use 4 years of data from the retiree health benefits program of the University of Michigan to estimate the effect of price on the health plan choices of Medicare beneficiaries. During the period of our analysis, changes in the University's premium contribution rules led to substantial price changes. A key feature of this 'natural experiment' is that individuals who had retired before a certain date were exempted from having to pay any premium contributions. This 'grandfathering' creates quasi-experimental variation that is ideal for estimating the effect of price. Using regression discontinuity methods, we compare the plan choices of individuals who retired just after the grandfathering cutoff date and were therefore exposed to significant price changes to the choices of a 'control group' of individuals who retired just before that date and therefore did not experience the price changes. The results indicate a statistically significant effect of price, with a $10 increase in monthly premium contributions leading to a 2 to 3 percentage point decrease in a plan's market share. Copyright © 2012 John Wiley & Sons, Ltd.
Xie, Yuanpu; Xing, Fuyong; Shi, Xiaoshuang; Kong, Xiangfei; Su, Hai; Yang, Lin
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and large variations in cell sizes and shapes. In addition, the ever-increasing amount of available datasets and the high resolution of whole-slice scanned images pose a further demand for efficient processing algorithms. In this paper, we present a novel structured regression model based on a proposed fully residual convolutional neural network for efficient cell detection. For each testing image, our model learns to produce a dense proximity map that exhibits higher responses at locations near cell centers. Our method only requires a few training images with weak annotations (just one dot indicating the cell centroids). We have extensively evaluated our method using four different datasets, covering different microscopy staining methods (e.g., H & E or Ki-67 staining) or image acquisition techniques (e.g., bright-filed image or phase contrast). Experimental results demonstrate the superiority of our method over existing state of the art methods in terms of both detection accuracy and running time. Copyright © 2017. Published by Elsevier B.V.
Full Text Available The optimization of turbine density in wind farms entails a trade-off between the usage of scarce, expensive land and power losses through turbine wake effects. A quantification and prediction of the wake effect, however, is challenging because of the complex aerodynamic nature of the interdependencies of turbines. In this paper, we propose a parsimonious data driven regression wake model that can be used to predict production losses of existing and potential wind farms. Motivated by simple engineering wake models, the predicting variables are wind speed, the turbine alignment angle, and distance. By utilizing data from two wind farms in Germany, we show that our models can compete with the standard Jensen model in predicting wake effect losses. A scenario analysis reveals that a distance between turbines can be reduced by up to three times the rotor size, without entailing substantial production losses. In contrast, an unfavorable configuration of turbines with respect to the main wind direction can result in production losses that are much higher than in an optimal case.
Archangeli, Diana; Pulleyblank, Douglas
The question of identifying the properties of language that are specific human linguistic abilities, i.e., Universal Grammar, lies at the center of linguistic research. This paper argues for a largely Emergent Grammar in phonology, taking as the starting point that memory, categorization, attention to frequency, and the creation of symbolic systems are all nonlinguistic characteristics of the human mind. The articulation patterns of American English rhotics illustrate categorization and systems; the distribution of vowels in Bantu vowel harmony uses frequencies of particular sequences to argue against Universal Grammar and in favor of Emergent Grammar; prefix allomorphy in Esimbi illustrates the Emergent symbolic system integrating phonological and morphological generalizations. The Esimbi case has been treated as an example of phonological opacity in a Universal Grammar account; the Emergent analysis resolves the pattern without opacity concerns.
Bárbara Amaral da Silva
Full Text Available From the notion of parody, credibility and legitimacy, coming mainly from studies in discourse analysis, and ideas from the sociolinguistic we intend to develop a brief comparison between the Expositive Grammar – Advanced Course (46st ed.:1926 of Eduardo Carlos Pereira, who initially presents itself as a merely descriptive grammar, and the Portuguese Grammar by the Confused Method, written by Mendes Fradique (4st ed.: 1985. We observed that the first one claims to be “expositive” when it is clearly prescriptive. The work of Mendes Fradique uses humor and irony to parody prescriptive grammars, criticizing the “good use”. In order to prove the above statement, we selected some of the concepts presented by those works, checking the position taken by each one. Among them is the very concept of grammar, language etc.
Aksit, Mehmet; Mostert, Rene; Haverkort, Boudewijn R.H.M.
The concept of grammar inheritance is introduced. Grammar inheritance is a structural organization of grammar rules by which a grammar inherits rules from ancestor grammars or may have its own rules inherited by descendant grammars. Grammar inheritance supports reusability and extensibility of
Currently, the concept of spoken grammar has been mentioned among Chinese teachers. However, teach-ers in China still have a vague idea of spoken grammar. Therefore this dissertation examines what spoken grammar is and argues that native speakers’ model of spoken grammar needs to be highlighted in the classroom teaching.
@@ There are two kinds of grammar, prescriptive grammar and descriptive grammar. The prescriptive grammar gives orders how a language ought to be used rather than simply describing how it is used.This type of grammar lays down a lot of rules for the student to follow but the gifted philologist Edward Sapir points out that all grammatical rules leak. This type of grammar also warns the student against what are called ‘Shall-nots', but these ‘Shall-nots' are more likely to cause the student muchconcern rather than helping him to exprese his ideas in English. On the contrary, the descriptive grammar just describes how a language is used.
The concept of vector grammars under the string semantic is introduced.The dass of vector grammars is given,which is similar to the dass of Chomsky grammars.The regular vector grammar is divided further.The strong and weak relation between the vector grammar and scalar grammar is discussed,so the spectrum system graph of scalar and vector grammars is made.The equivalent relation between the regular vector grammar and Petri nets (also called PN machine) is pointed.The hybrid PN machine is introduced,and its language is proved equivalent to the language of the context-free vector grammar.So the perfect relation structure between vector grammars and PN machines is formed.
The present essay studies the role of grammar in young learners' classroom, perceived by the English teachers in China. The study gives a detailed description of what the role of grammar is like in young learners' classroom, by interviewing primary school teachers both from a city in a developed coastal city and a less developed city in central China. It highlights the differences in the perceptions of teachers on the prominence of grammar in their classes. These differences may indicate regional disparity and potential factors for teachers' teaching approaches to grammar instruction.
@@ 1 Introduction When we talk about grammar, we will usually refer to the detailed instruction rules of grammar. In China, grammar is usually taught explicitly in formal instructions, which is different from that in some western countries. So there are some controversial questions coming out: Should there be formal instruction of grammar?
Drabinová, Adéla; Martinková, Patrícia
In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…
The easy way to master French grammar French Grammar For Dummies is a logical extension and complement to the successful language learning book, French For Dummies. In plain English, it teaches you the grammatical rules of the French language, including parts of speech, sentence construction, pronouns, adjectives, punctuation, stress and verb tenses, and moods. Throughout the book, you get plenty of practice opportunities to help you on your goal of mastering basic French grammar and usage. Grasp the grammatical rules of French including parts of speech, sentenc
Fatemipour, Hamidreza; Hemmati, Shiva
Grammar Consciousness-Raising (GCR) is an approach to teaching of grammar which learners instead of being taught the given rules, experience language data. The data challenge them to rethink, restructure their existing mental grammar and construct an explicit rule to describe the grammatical feature which the data illustrate (Ellis, 2002). And…
A new grammar formalism, CHR Grammars (CHRG), is proposed that provides a constraint-solving approach to language analysis, built on top of the programming language of Constraint Handling Rules in the same way as Definite Clause Grammars (DCG) on Prolog. CHRG works bottom-up and adds the following......, integrity constraints, operators a la assumption grammars, and to incorporate other constraint solvers. (iv)~Context-sensitive rules that apply for disambiguation, coordination in natural language and tagger-like rules....
The role of the grammar teaching: from communicative approaches to the common European framework of reference for languages THE ROLE OF THE GRAMAMAR TEACHING: FROM COMMUNCATIVE APPROACHES TO THE COMMON EUROPEAN FRAMEWORK OF REFERENCE FOR LANGUAGES
José López Rama
Full Text Available In the history of language teaching, the role of grammar has been addressed by a number of linguistic theories, pedagogies and, currently, within the Common European Framework of Reference for Languages (CEF. The way grammar is considered has a decisive influence on pedagogical practices, learning processes and many other areas involved in language teaching. This paper constitutes a revision of how grammar has evolved in the last fifty years paying special attention to its evolving role in both communicative (CLT and post-communicative approaches and in the CEF.From this revision, some controversial issues concerning the pedagogic value of teaching grammar will arise as well, such as whether grammar is worth teaching in the classroom or not and how it should be taught.Even though there exists a parallel linguistic framework between CLT and the CEF, some issues still need revision concerning the notion of grammatical competence and its role for language teaching.Históricamente, el papel de la gramática en la enseñanza de lenguas se ha justificado y cuestionado tanto por teorías lingüísticas como, actualmente, dentro del Marco Común Europeo de Referencia. La forma de contemplar la gramática influye de modo fundamental en la metodología docente, en la elaboración de manuales de texto y en los procesos de aprendizaje, entre otros. Este artículo revisa el papel de la gramática en los últimos cincuenta años prestando especial atención al método comunicativo, los post-comunicativos y dentro del Marco Común Europeo de Referencia. En respuesta, se revisa la posible controversia sobre la propia definición de gramática y su valor en enseñanza de lenguas extranjeras.
Bouwers, E.; Bravenboer, M.; Visser, E.
A wide range of parser generators are used to generate parsers for programming languages. The grammar formalisms that come with parser generators provide different approaches for defining operator precedence. Some generators (e.g. YACC) support precedence declarations, others require the grammar to
Grammar teaching is one of the most difficult and important points in the middle school. However, there exist some problems with present grammar teaching, such as students＇ poor knowledge of grammar, improper teaching methods and the ignorance of grammar
focused communicative approaches over the years, studies report that most language teachers still follow transmission-based grammar-oriented approaches. It is known that the success of any curriculum innovation is dependent on teachers.
Onyiah, Leonard C
Introductory Statistical Inference and Regression Analysis Elementary Statistical Inference Regression Analysis Experiments, the Completely Randomized Design (CRD)-Classical and Regression Approaches Experiments Experiments to Compare Treatments Some Basic Ideas Requirements of a Good Experiment One-Way Experimental Layout or the CRD: Design and Analysis Analysis of Experimental Data (Fixed Effects Model) Expected Values for the Sums of Squares The Analysis of Variance (ANOVA) Table Follow-Up Analysis to Check fo
Yelland, Lisa N; Salter, Amy B; Ryan, Philip
Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.
Mariam Mohamed Nor
Full Text Available There have been so many ongoing disputes on different approaches to teaching grammar. This study aims to evaluate the effectiveness of teaching grammar using Gass comprehended Input technique (GCI (1997 (implicit and to explore the undergraduates’ perception on the GCI technique. The respondents consisted of 30 undergraduates’ who are currently pursuing their Bachelor of English. Using the qualitative method, the research instrument was a set of 23- item interview and content analysis of the students’ written work. Results showed that the teaching of grammar using explicit instructions was more preferred than implicit instruction for complex components in grammatical rules. However, implicit instruction is equally effective regardless of the proficiency levels to enable pedagogy to be executed. It is also noted that there is lots of room for improvement, since the undergraduates have a weak grasp of the basic tense aspect of English grammar. Therefore, the Malaysian Ministry of Education should consider having grammar formally taught in isolation as what was practised previously.
Hannay, M.; Hengeveld, K.; Brisard, F.; Östman, J.O.; Verschueren, J.
This chapter introduces Functional Discourse Grammar, focusing on the way in which this model is capable of accounting for the grammatical encoding of pragmatic distinctions and for the typological variation found in this area of grammar.
interpretation of attribute grammars. The framework is used to construct a strictness analysis for attribute grammars. Results of the analysis enable us to transform an attribute grammar such that attributes are evaluated during parsing, if possible. The analysis is proved correct by relating it to a fixpoint...... semantics for attribute grammars. An implementation of the analysis is discussed and some extensions to the analysis are mentioned....
This innovative grammar text is an ideal resource for writers, language students, and current and future classroom teachers who need an accessible "refresher" in a step-by-step guide to essential grammar. Rather than becoming mired in overly detailed linguistic definitions, Nancy Sullivan helps writers and students understand and apply grammatical concepts and develop the skills they need to enhance their own writing. Along with engaging discussions of both contemporary and traditional terminology, Sullivan's text provides clear explanations of the basics of English grammar and a highly practical, hands-on approach to mastering the use of language. Complementing the focus on constructing excellent sentences, every example and exercise set is contextually grounded in language themes. Teachers, students, and writers will appreciate the streamlined, easy-to-understand coverage of essential grammar, as well as the affordable price. This is an ideal textbook for future teachers enrolled in an upper-level grammar c...
Full Text Available Abstract: The aim of this paper is to critically assess the presentation of English grammar in textbooks used in secondary schools in Indonesia. The influence of the Communicative Approach is in evidence in the books examined, and yet the importance of explicit grammar instruction is not ignored, reflecting the view of many today that grammatical forms cannot be successfully learnt merely on the basis of comprehensible input. Despite recognition of its central role, the grammar instruction presented in the textbooks invites questions as to its linguistic adequacy and accuracy. Writers often seem unwilling to take on board the insights recorded in the influential and authoritative descriptive grammars of recent years, continuing to accept tacitly the principles exposed in Traditional Grammar.
Zulkufli, Nurul Liyana binti Mohamad; Turaev, Sherzod; Tamrin, Mohd Izzuddin Mohd; Azeddine, Messikh
In this paper, we define Watson-Crick context-free grammars, as an extension of Watson-Crick regular grammars and Watson-Crick linear grammars with context-free grammar rules. We show the relation of Watson-Crick (regular and linear) grammars to the sticker systems, and study some of the important closure properties of the Watson-Crick grammars. We establish that the Watson-Crick regular grammars are closed under almost all of the main closure operations, while the differences between other Watson-Crick grammars with their corresponding Chomsky grammars depend on the computational power of the Watson-Crick grammars which still need to be studied.
Achawanantakun, Rujira; Sun, Yanni; Takyar, Seyedeh Shohreh
Many noncoding RNAs (ncRNAs) function through both their sequences and secondary structures. Thus, secondary structure derivation is an important issue in today's RNA research. The state-of-the-art structure annotation tools are based on comparative analysis, which derives consensus structure of homologous ncRNAs. Despite promising results from existing ncRNA aligning and consensus structure derivation tools, there is a need for more efficient and accurate ncRNA secondary structure modeling and alignment methods. In this work, we introduce a consensus structure derivation approach based on grammar string, a novel ncRNA secondary structure representation that encodes an ncRNA's sequence and secondary structure in the parameter space of a context-free grammar (CFG) and a full RNA grammar including pseudoknots. Being a string defined on a special alphabet constructed from a grammar, grammar string converts ncRNA alignment into sequence alignment. We derive consensus secondary structures from hundreds of ncRNA families from BraliBase 2.1 and 25 families containing pseudoknots using grammar string alignment. Our experiments have shown that grammar string-based structure derivation competes favorably in consensus structure quality with Murlet and RNASampler. Source code and experimental data are available at http://www.cse.msu.edu/~yannisun/grammar-string.
Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan
Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.
Nielson, Hanne Riis; Skyum, S.
It is shown that any well-defined attribute grammar is k-visit for some k. Furthermore, it is shown that given a well-defined grammar G and an integer k, it is decidable whether G is k-visit. Finally it is shown that the k-visit grammars specify a proper hierarchy with respect to translations...
Schlechtingen, Meik; Santos, Ilmar
This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal...
Grammar is an important component of English. Without grammar, it is not possible to communicate meaning successfully. Therefore, teachers and educators have to pay close attention to teaching grammar effectively. Based on the writer‘s experience in teaching grammar using the traditional way, many students still had difficulty in acquiring the grammar points. The grammar meetings were not effective, and the students did not thoroughly understand the grammar exercises. The students seemed bore...
Characterized by clear and accessible explanations, numerous examples and sample sentences, a new section on register and tone, and useful appendices covering topics including age and time, A Comprehensive French Grammar, Sixth Edition is an indispensable tool for advanced students of French language and literature.A revised edition of this established, bestselling French grammarIncludes a new section on register and medium and offers expanded treatment of French punctuationFeatures numerous examples and sample sentences, and useful appendices covering topics including age, time, and dimension
Christiansen, Henning; Dahl, Veronica
By extending logic grammars with constraint logic, we give them the ability to create knowledge bases that represent the meaning of an input string. Semantic information is thus defined through extra-grammatical means, and a sentence's meaning logically follows as a by-product of string rewriting....... We formalize these ideas, and exemplify them both within and outside first-order logic, and for both fixed and dynamic knowledge bases. Within the latter variety, we consider the usual left-to-right derivations that are traditional in logic grammars, but also -- in a significant departure from...
Long trusted as the most comprehensive, up-to-date and user-friendly grammar available, French Grammar and Usage is a complete guide to French as it is written and spoken today. It includes clear descriptions of all the main grammatical phenomena of French, and their use, illustrated by numerous examples taken from contemporary French, and distinguishes the most common forms of usage, both formal and informal.Key features include:Comprehensive content, covering all the major structures of contemporary French User-friendly organisation offering easy-to-find sections with cross-referencing and i
Ward, Lesley J
If you're confused by commas, perplexed by pronouns, and plain terrified by tenses, English Grammar For Dummies will put your fears to rest. Packed with expert guidance, it covers everything from sentence basics to rules even your English teacher didn't know - if you want to brush up on your grammar, this is the only guide you'll ever need. Discover how to: avoid common grammatical errors; get to grips with apostrophes; structure sentences correctly; use verbs and find the right tense; and decide when to use slang or formal English.
Chan, Yea-Kuang; Tsai, Yu-Ching
The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.
Chan, Yea-Kuang; Tsai, Yu-Ching [Institute of Nuclear Energy Research, Taoyuan City, Taiwan (China). Nuclear Engineering Division
The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.
IntroductionToday many Chinese students think of English grammar as an unpopular and difficult part of theirEnglish lessons Even more worryingly,that attitude is one they have usually picked up from theirteachers.Namely,grammar seems to be hard work for EFL teachers and students.So should grammarteaching be abolishedWhy do many teachers and students take a negative attitude toward grammarInthis paper,first,I will attempt to discuss the place of grammar in EFL teaching.Next,I will outline thetraditional methods of grammar teaching and the results of this kind of grammar teaching.Finally,I willput forward some suggestions on how to make grammar teaching more interesting in Chinese classrooms.
Spady, Richard; Stouli, Sami
We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...
Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K
To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods
This book is a descriptive grammar of Lepcha, a Tibeto-Burman language spoken in Sikkim, Darjeeling district in West Bengal in India, in Ilam district in Nepal, and in a few villages of Samtsi district in south-western Bhutan. The data for this study were collected during several sojourns amongst
Zaytsev, V.; Pierantonio, A.; Schätz, B.; Tamzalit, D.
The evolution of a software language (whether modelled by a grammar or a schema or a metamodel) is not limited to development of new versions and dialects. An important dimension of a software language evolution is maturing in the sense of improving the quality of its definition. In this paper, we
The teaching of grammar has been in sad decline since medieval times, when it included the whole skill of creating in language. Our textbook community has moved through a series of ineffective fashions, from those of Fries to post-Chomsky. All have presumed to replace prescriptive rules with realistic explanations. But all have fallen, like the…
Arlington County Public Schools, VA. REEP, Arlington Education and Employment Program.
This document provides the Arlington Education and Employment Program's (REEP) favorite techniques for teaching English-as-a-Second-Language (ESL) grammar. The focus, levels, and materials needed are presented for each of the techniques as well as the steps to follow. (Adjunct ERIC Clearinghouse for ESL Literacy Education) (Author/VWL)
Nguyen, Tam Thi Minh
Bih is a Chamic (Austronesian) language spoken by approximately 500 people in the Southern highlands of Vietnam. This dissertation is the first descriptive grammar of the language, based on extensive fieldwork and community-based language documentation in Vietnam and written from a functional/typological perspective. The analysis in this work is…
V. Zaytsev (Vadim)
htmlabstractIn this paper, we study controlled adaptability of metamodel transformations. We consider one of the most rigid metamodel transformation formalisms — automated grammar transformation with operator suites, where a transformation script is built in such a way that it is essentially meant
Chinese character structure has often been described as representing a kind of grammar, but the notion of character grammar has hardly been explored. Patterns in character element reduplication are particularly grammar-like, displaying discrete combinatoriality, binarity, phonology-like final prominence, and potentially the need for symbolic rules (X→XX). To test knowledge of these patterns, Chinese readers were asked to judge the acceptability of fake characters varying both in grammaticality (obeying or violating reduplication constraints) and in lexicality (of the reduplicative configurations). While lexical knowledge was important (lexicality improved acceptability and grammatical configurations were accepted more quickly when also lexical), grammatical knowledge was important as well, with grammaticality improving acceptability equally for lexical and nonlexical configurations. Acceptability was also higher for more frequent reduplicative elements, suggesting that the reduplicative configurations were decomposed. Chinese characters present an as-yet untapped resource for exploring fundamental questions about the nature of the human capacity for grammar. Copyright © 2015 Elsevier B.V. All rights reserved.
Introduction Among the plethora of foreign language teaching methods and approaches there are the grammar-translation method, the direct method, the audiolingual method and the communicative approach to name but a few. Of the major methods, grammar-translation gets the most criticism and is thought to be obsolete. However, in my view it is suitable for China given the country’s present language learning situation, and, in practice, is not at all ineffectual.
Culik and Cohen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this report we consider the analogous extension of the LL(k) grammers, called the LL-regular grammars. The relations of this class of grammars to other classes of grammars are shown. Every LL-regular
Through a case study of a first-language English teacher's approach to teaching writing, the significance of conceptual and affective beliefs about grammar for pedagogical practice is explored. The study explores a perceived dichotomy between grammar and creativity, examining a belief that attention to grammar is separate and secondary to the…
Full Text Available Although procedure time analyses are important for operating room management, it is not easy to extract useful information from clinical procedure time data. A novel approach was proposed to analyze procedure time during anesthetic induction. A two-step regression analysis was performed to explore influential factors of anesthetic induction time (AIT. Linear regression with stepwise model selection was used to select significant correlates of AIT and then quantile regression was employed to illustrate the dynamic relationships between AIT and selected variables at distinct quantiles. A total of 1,060 patients were analyzed. The first and second-year residents (R1-R2 required longer AIT than the third and fourth-year residents and attending anesthesiologists (p = 0.006. Factors prolonging AIT included American Society of Anesthesiologist physical status ≧ III, arterial, central venous and epidural catheterization, and use of bronchoscopy. Presence of surgeon before induction would decrease AIT (p < 0.001. Types of surgery also had significant influence on AIT. Quantile regression satisfactorily estimated extra time needed to complete induction for each influential factor at distinct quantiles. Our analysis on AIT demonstrated the benefit of quantile regression analysis to provide more comprehensive view of the relationships between procedure time and related factors. This novel two-step regression approach has potential applications to procedure time analysis in operating room management.
Yoo S.; Yang, Y.; Carbonell, J.
Email overload, even after spam filtering, presents a serious productivity challenge for busy professionals and executives. One solution is automated prioritization of incoming emails to ensure the most important are read and processed quickly, while others are processed later as/if time permits in declining priority levels. This paper presents a study of machine learning approaches to email prioritization into discrete levels, comparing ordinal regression versus classier cascades. Given the ordinal nature of discrete email priority levels, SVM ordinal regression would be expected to perform well, but surprisingly a cascade of SVM classifiers significantly outperforms ordinal regression for email prioritization. In contrast, SVM regression performs well -- better than classifiers -- on selected UCI data sets. This unexpected performance inversion is analyzed and results are presented, providing core functionality for email prioritization systems.
Helmreich, James E.; Krog, K. Peter
We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…
Full Text Available The capability to validate and view or play binary file formats, as well as to convert binary file formats to standard or current file formats, is critically important to the preservation of digital data and records. This paper describes the extension of context-free grammars from strings to binary files. Binary files are arrays of data types, such as long and short integers, floating-point numbers and pointers, as well as characters. The concept of an attribute grammar is extended to these context-free array grammars. This attribute grammar has been used to define a number of chunk-based and directory-based binary file formats. A parser generator has been used with some of these grammars to generate syntax checkers (recognizers for validating binary file formats. Among the potential benefits of an attribute grammar-based approach to specification and parsing of binary file formats is that attribute grammars not only support format validation, but support generation of error messages during validation of format, validation of semantic constraints, attribute value extraction (characterization, generation of viewers or players for file formats, and conversion to current or standard file formats. The significance of these results is that with these extensions to core computer science concepts, traditional parser/compiler technologies can potentially be used as a part of a general, cost effective curation strategy for binary file formats.
Chamroukhi, Faicel; Samé, Allou; Govaert, Gérard; Aknin, Patrice
Time series are used in many domains including finance, engineering, economics and bioinformatics generally to represent the change of a measurement over time. Modeling techniques may then be used to give a synthetic representation of such data. A new approach for time series modeling is proposed in this paper. It consists of a regression model incorporating a discrete hidden logistic process allowing for activating smoothly or abruptly different polynomial regression models. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The M step of the EM algorithm uses a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm to estimate the hidden process parameters. To evaluate the proposed approach, an experimental study on simulated data and real world data was performed using two alternative approaches: a heteroskedastic piecewise regression model using a global optimization algorithm based on dynamic programming, and a Hidden Markov Regression Model whose parameters are estimated by the Baum-Welch algorithm. Finally, in the context of the remote monitoring of components of the French railway infrastructure, and more particularly the switch mechanism, the proposed approach has been applied to modeling and classifying time series representing the condition measurements acquired during switch operations.
Manning, Molly; Franklin, Sue
In cognitive grammar (CG), there is no clear division between language and other cognitive processes; all linguistic form is conceptually meaningful. In this pilot study, a CG approach was applied to investigate whether people with aphasia (PWA) have cognitive linguistic difficulty not predicted from traditional, componential models of aphasia. Narrative samples from 22 PWA (6 fluent, 16 non-fluent) were compared with samples from 10 participants without aphasia. Between-group differences were tested statistically. PWA had significant difficulty with temporal sequencing, suggesting problems that are not uniquely linguistic. For some, these problems were doubly dissociated with naming, used as a general measure of severity, which indicates that cognitive linguistic difficulties are not linked with more widespread brain damage. Further investigation may lead to a richer account of aphasia in line with contemporary linguistics and cognitive science approaches.
Full Text Available As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.
Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De
As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.
Full Text Available We introduce an imbalanced data classification approach based on logistic regression significant discriminant and Fisher discriminant. First of all, a key indicators extraction model based on logistic regression significant discriminant and correlation analysis is derived to extract features for customer classification. Secondly, on the basis of the linear weighted utilizing Fisher discriminant, a customer scoring model is established. And then, a customer rating model where the customer number of all ratings follows normal distribution is constructed. The performance of the proposed model and the classical SVM classification method are evaluated in terms of their ability to correctly classify consumers as default customer or nondefault customer. Empirical results using the data of 2157 customers in financial engineering suggest that the proposed approach better performance than the SVM model in dealing with imbalanced data classification. Moreover, our approach contributes to locating the qualified customers for the banks and the bond investors.
Davis Brent M.
Full Text Available One of the major problems in language teaching is developing grammatical accuracy. This paper proposes that using error correction based on a functional grammar in a task-based learning approach may be a suitable solution. Towards this end an emic (using categories intrinsic to the language functional grammar of the verb phrase is proposed and a description of how this fits into the focus on form component of task-based learning is provided.
English learners may have such experience that most of them can't be able to speak English apropriately and fluently even if they have gained a lot of grammar knowledge. The approach of teaching grammar discussed in this paper focuses on training students' communicative ability. And it is benefical to stimulating the activeness and interest of students and fostering the ability to solve the problems independently.
In this article it is shown how a corpus-based dictionary grammar may be compiled — that is, a mini-grammar fully based on corpus data and specifically written for use in and inte-grated with a dictionary. Such an effort is, to the best of our knowledge, a world's first. We exem-plify our approach for a Northern Sotho ...
Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H
It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.
Grammar is an aspect of language about which learners have different opinions. Some learners are very interested in ifnding out or learning grammar rules and doing lots of grammar exercises. Others hate grammar and think it is the most boring part of learning a new language. Whatever opinion you have, however, you cannot escape from grammar; it is in every sentence you read or write, speak or hear. Grammar is simply the word for the rules that people follow when they use a language. We need those rules in the same way as we need the rules in a game. If there are no rules, or if everybody follows their own rules, the game would soon break down. It's the same with language; without rules we would not be able to communicate with other people. So you cannot escape from grammar, but the key question here is: what is the best way to learn grammar? You can learn the rules of a game by simply playing the game. You will certainly make mistakes; you may even get hurt. Eventually, however, you will know how to play. Of course, the rules of a language are very much more complicated than the rules of any game, but in fact this is exactly how you learned your own language. Nobody taught you the rules of your mother tongue as you were growing up but now you never make a grammar mistake.
Acquiring the grammar system is vital in the foreign language learning, and there has always been the debate on how learners can best acquire the English grammar. Inthis paper, two methods for teaching grammar will be presented--traditional practice and consciousness-raising. Both thetwo methods have their ad-vantages and disadvantages. But in practice, it is a better idea to combine different methods to make grammar teaching more effective. In addition, the consideration of different individual learners is also very important.
Paul Robert Martin Werfette
Full Text Available Analysis of quantitative structure - activity relationship (QSAR for a series of antimalarial compound artemisinin derivatives has been done using principal component regression. The descriptors for QSAR study were representation of electronic structure i.e. atomic net charges of the artemisinin skeleton calculated by AM1 semi-empirical method. The antimalarial activity of the compound was expressed in log 1/IC50 which is an experimental data. The main purpose of the principal component analysis approach is to transform a large data set of atomic net charges to simplify into a data set which known as latent variables. The best QSAR equation to analyze of log 1/IC50 can be obtained from the regression method as a linear function of several latent variables i.e. x1, x2, x3, x4 and x5. The best QSAR model is expressed in the following equation, (;; Keywords: QSAR, antimalarial, artemisinin, principal component regression
Baser, Furkan; Demirhan, Haydar
Accurate estimation of the amount of horizontal global solar radiation for a particular field is an important input for decision processes in solar radiation investments. In this article, we focus on the estimation of yearly mean daily horizontal global solar radiation by using an approach that utilizes fuzzy regression functions with support vector machine (FRF-SVM). This approach is not seriously affected by outlier observations and does not suffer from the over-fitting problem. To demonstrate the utility of the FRF-SVM approach in the estimation of horizontal global solar radiation, we conduct an empirical study over a dataset collected in Turkey and applied the FRF-SVM approach with several kernel functions. Then, we compare the estimation accuracy of the FRF-SVM approach to an adaptive neuro-fuzzy system and a coplot supported-genetic programming approach. We observe that the FRF-SVM approach with a Gaussian kernel function is not affected by both outliers and over-fitting problem and gives the most accurate estimates of horizontal global solar radiation among the applied approaches. Consequently, the use of hybrid fuzzy functions and support vector machine approaches is found beneficial in long-term forecasting of horizontal global solar radiation over a region with complex climatic and terrestrial characteristics. - Highlights: • A fuzzy regression functions with support vector machines approach is proposed. • The approach is robust against outlier observations and over-fitting problem. • Estimation accuracy of the model is superior to several existent alternatives. • A new solar radiation estimation model is proposed for the region of Turkey. • The model is useful under complex terrestrial and climatic conditions.
Christiansen, Asger Nyman; Bærentzen, Jakob Andreas
in a directed cyclic graph. Furthermore, the basic productions are chosen such that Generic Graph Grammar seamlessly combines the capabilities of L-systems to imitate biological growth (to model trees, animals, etc.) and those of split grammars to design structured objects (chairs, houses, etc.). This results...
Explicit teaching of grammar and improvement in the grammar of student writing. J Parkinson. Abstract. No Abstract. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT. Article Metrics. Metrics Loading ... Metrics powered by PLOS ALM
Full Text Available Wittgenstein is the author of two conceptions of “grammar”, that were meant to be tools of reaching the same goal: discrediting of the traditional, i.e. “metaphysical” questions of philosophy. His early conception concerns logical grammar being the language of logic notation, which is devoid of logical constants. This idea was supported by the ontological thesis that there are no logical objects. In fact, it was not indispensable for achieving the intended purpose, since the elimination of philosophical problems was provided by the semantic argument that the only sensible statements are those of the natural sciences. The second concept of grammar, presented in the writings of the later Wittgenstein, seems more ambiguous. Grammar is a set of rules of the language game, having a status of grammatical statements. Examples of such statements are diverse, and desirable, according to the authors, reformulation of them all into concrete orders or prohibitions seems problematic. In the Investigations Wittgenstein distinguishes between deep and surface grammar, which serves to determine the proper task of philosophy as description of the deep grammar (especially the grammar of philosophically relevant words. In this sense New Philosophy is a kind of philosophical grammar. Wittgensteinian grammar is also anti-philosophical, as it aims at the elimination of erroneous (pseudometaphysical claims derived from misleading forms of surface grammar. Despite the differences in the concepts of language and grammar in the early and late Wittgenstein, he has not changed his critical approach to the traditional philosophical questions.
Alexander Olawumi Dabor
Full Text Available The objective of this study is to investigate the casuality between corporate social responsibility and firm financial performance. The study employed two least square regression approaches. Fifty-two firms were selected using the scientific method. The findings revealed that corporate social responsibility and firm performance in manufacturing sector are mutually related at 5%. The study recommended that management of manufacturing companies in Nigeria should expend on CSR to boost profitability and corporate image.
The salmon farming industry has gained increased attention from investors, portfolio managers, financial analysts and other stakeholders the recent years. Despite this development, very little is known about the risk and return of salmon farming company stocks, and especially how the relationship between risk and return varies under different market conditions, given the volatile nature of the salmon farming industry. We approach this problem by using quantile regression to examine the relati...
Thu, Tran Hoang
This study investigates English as a second language (ESL) teachers' beliefs in grammar teaching. A 32-item questionnaire was administered to 11 ESL teachers in a language school in California. The results show that the participants generally believe that the formal study of grammar is essential to the eventual mastery of a foreign or second…
Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne
Existing evidence suggests that ambient ultrafine particles (UFPs) (regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Ahmad, Sumbul; Chase, Scott Curland
The concept of style is relevant for both the analysis and synthesis of designs. New styles are often formed by the adaptation of previous ones based on changes in design criteria and context. A formal characterization of style is given by shape grammars, which describe the compositional rules...... underlying a set of designs. Stylistic change can be modelled by grammar transformations, which allow the transformation of the structure and vocabulary of a grammar that is used to describe a particular style. In order for grammars to be useful beyond a single application, they should have the capability...... to be transformed according to changing design style needs. Issues of formalizing stylistic change necessitate a lucid and formal definition of style in the design language generated by a grammar. Furthermore, a significant aspect of the definition of style is the representation of aesthetic qualities attributed...
Kamarulzaman Ibrahim; Heng Khai Theng
Many safety studies are based on the analysis carried out on injury surveillance data. The injury surveillance data gathered for the analysis include information on number of employees at risk of injury in each of several strata where the strata are defined in terms of a series of important predictor variables. Further insight into the relationship between fatal injury rates and predictor variables may be obtained by the poisson regression approach. Poisson regression is widely used in analyzing count data. In this study, poisson regression is used to model the relationship between fatal injury rates and predictor variables which are year (1995-2002), gender, recording system and industry type. Data for the analysis were obtained from PERKESO and Jabatan Perangkaan Malaysia. It is found that the assumption that the data follow poisson distribution has been violated. After correction for the problem of over dispersion, the predictor variables that are found to be significant in the model are gender, system of recording, industry type, two interaction effects (interaction between recording system and industry type and between year and industry type). Introduction Regression analysis is one of the most popular
Liu, Chunping; Laporte, Audrey; Ferguson, Brian S
In the health economics literature there is an ongoing debate over approaches used to estimate the efficiency of health systems at various levels, from the level of the individual hospital - or nursing home - up to that of the health system as a whole. The two most widely used approaches to evaluating the efficiency with which various units deliver care are non-parametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Productivity researchers tend to have very strong preferences over which methodology to use for efficiency estimation. In this paper, we use Monte Carlo simulation to compare the performance of DEA and SFA in terms of their ability to accurately estimate efficiency. We also evaluate quantile regression as a potential alternative approach. A Cobb-Douglas production function, random error terms and a technical inefficiency term with different distributions are used to calculate the observed output. The results, based on these experiments, suggest that neither DEA nor SFA can be regarded as clearly dominant, and that, depending on the quantile estimated, the quantile regression approach may be a useful addition to the armamentarium of methods for estimating technical efficiency.
MacDonald, Maryellen C; Weiss, Daniel J
Structural priming is poorly understood and cannot inform accounts of grammar for two reasons. First, those who view performance as grammar + processing will always be able to attribute psycholinguistic data to processing rather than grammar. Second, structural priming may be simply an example of hysteresis effects in general action planning. If so, then priming offers no special insight into grammar.
This book discusses the way Chinese scholars developed a national grammar. Chinese didnt develop grammar until Chinas contact with Western grammar books in the 19th Century. The first indigenous grammar was published in 1889. It included some traditional notions, but mainly imitated European
Bai, Yun; Wang, Pu; Li, Chuan; Xie, Jingjing; Wang, Yin
Water is one of the most important resources for economic and social developments. Daily water demand forecasting is an effective measure for scheduling urban water facilities. This work proposes a multi-scale relevance vector regression (MSRVR) approach to forecast daily urban water demand. The approach uses the stationary wavelet transform to decompose historical time series of daily water supplies into different scales. At each scale, the wavelet coefficients are used to train a machine-learning model using the relevance vector regression (RVR) method. The estimated coefficients of the RVR outputs for all of the scales are employed to reconstruct the forecasting result through the inverse wavelet transform. To better facilitate the MSRVR forecasting, the chaos features of the daily water supply series are analyzed to determine the input variables of the RVR model. In addition, an adaptive chaos particle swarm optimization algorithm is used to find the optimal combination of the RVR model parameters. The MSRVR approach is evaluated using real data collected from two waterworks and is compared with recently reported methods. The results show that the proposed MSRVR method can forecast daily urban water demand much more precisely in terms of the normalized root-mean-square error, correlation coefficient, and mean absolute percentage error criteria.
Then the paper explains the concept of context in teaching grammar and describes the reasons for teaching grammar in context. The last part of the paper demonstrates how grammar is taught in context. These sample lessons are taken from different sources based on experts when teaching grammar in context.Teaching grammar in context is more useful and can help the students to master English better.
Kiani, Alishir; Chwalibog, André; Nielsen, Mette O
Late gestation energy expenditure (EE(gest)) originates from energy expenditure (EE) of development of conceptus (EE(conceptus)) and EE of homeorhetic adaptation of metabolism (EE(homeorhetic)). Even though EE(gest) is relatively easy to quantify, its partitioning is problematic. In the present...... study metabolizable energy (ME) intake ranges for twin-bearing ewes were 220-440, 350- 700, 350-900 kJ per metabolic body weight (W0.75) at week seven, five, two pre-partum respectively. Indirect calorimetry and a linear regression approach were used to quantify EE(gest) and then partition to EE......(conceptus) and EE(homeorhetic). Energy expenditure of basal metabolism of the non-gravid tissues (EE(bmng)), derived from the intercept of the linear regression equation of retained energy [kJ/W0.75] and ME intake [kJ/W(0.75)], was 298 [kJ/ W0.75]. Values of the intercepts of the regression equations at week seven...
Becker, S.; Peter, M.; Fritsch, D.
The paper presents a grammar-based approach for the robust automatic reconstruction of 3D interiors from raw point clouds. The core of the approach is a 3D indoor grammar which is an extension of our previously published grammar concept for the modeling of 2D floor plans. The grammar allows for the modeling of buildings whose horizontal, continuous floors are traversed by hallways providing access to the rooms as it is the case for most office buildings or public buildings like schools, hospitals or hotels. The grammar is designed in such way that it can be embedded in an iterative automatic learning process providing a seamless transition from LOD3 to LOD4 building models. Starting from an initial low-level grammar, automatically derived from the window representations of an available LOD3 building model, hypotheses about indoor geometries can be generated. The hypothesized indoor geometries are checked against observation data - here 3D point clouds - collected in the interior of the building. The verified and accepted geometries form the basis for an automatic update of the initial grammar. By this, the knowledge content of the initial grammar is enriched, leading to a grammar with increased quality. This higher-level grammar can then be applied to predict realistic geometries to building parts where only sparse observation data are available. Thus, our approach allows for the robust generation of complete 3D indoor models whose quality can be improved continuously as soon as new observation data are fed into the grammar-based reconstruction process. The feasibility of our approach is demonstrated based on a real-world example.
This best-selling comprehensive descriptive grammar forms a complete course, ideal for all students studying English Language ,whether on a course or for self-study. Broadly based on Hallidayan systemic-functional grammar but also drawing on cognitive linguistics and discourse analysis, English Grammar is accessible, avoiding overly theoretical or technical explanations.Divided into 12 self-contained chapters based around language functions, each chapter is divided into units of class-length material. Key features include:Numerous authentic texts from a wide range of sources, both spoken and w
English Grammar Workbook For Dummies, UK Edition is grammar First Aid for anyone wanting to perfect their English and develop the practical skills needed to write and speak correctly. Each chapter focuses on key grammatical principles, with easy-to-follow theory and examples as well as practice questions and explanations. From verbs, prepositions and tenses, to style, expressions and tricky word traps, this hands-on workbook is essential for both beginners looking to learn and practise the basics of English grammar, and those who want to brush up skills they already have - quickly, easily, and
Dr Roger Hawkins; Towell, Richard
This new edition of Practising French Grammar offers a set of varied and accessible exercises for developing a practical awareness of French as it is spoken and written today. The lively examples and authentic texts and cartoons have been updated to reflect current usage. A new companion website provides a wealth of additional interactive exercises to help consolidate challenging grammar points. Practising French Grammar provides concise summaries of key grammatical points at the beginning of each exercise, as well as model answers to the exercises and translations of difficult words, making i
Li, Zhi; Hegelheimer, Volker
In this paper, we report on the development and implementation of a web-based mobile application, "Grammar Clinic," for an ESL writing class. Drawing on insights from the interactionist approach to Second Language Acquisition (SLA), the Noticing Hypothesis, and mobile-assisted language learning (MALL), "Grammar Clinic" was…
Shoff, Carla; Chen, Vivian Yi-Ju; Yang, Tse-Chuan
Using geographically weighted regression (GWR), a recent study by Shoff and colleagues (2012) investigated the place-specific risk factors for prenatal care utilization in the US and found that most of the relationships between late or not prenatal care and its determinants are spatially heterogeneous. However, the GWR approach may be subject to the confounding effect of spatial homogeneity. The goal of this study is to address this concern by including both spatial homogeneity and heterogeneity into the analysis. Specifically, we employ an analytic framework where a spatially lagged (SL) effect of the dependent variable is incorporated into the GWR model, which is called GWR-SL. Using this innovative framework, we found evidence to argue that spatial homogeneity is neglected in the study by Shoff et al. (2012) and the results are changed after considering the spatially lagged effect of prenatal care utilization. The GWR-SL approach allows us to gain a place-specific understanding of prenatal care utilization in US counties. In addition, we compared the GWR-SL results with the results of conventional approaches (i.e., OLS and spatial lag models) and found that GWR-SL is the preferred modeling approach. The new findings help us to better estimate how the predictors are associated with prenatal care utilization across space, and determine whether and how the level of prenatal care utilization in neighboring counties matters. PMID:24893033
Yamagishi, Michel Eduardo Beleza
This seminal, multidisciplinary book shows how mathematics can be used to study the first principles of DNA. Most importantly, it enriches the so-called “Chargaff’s grammar of biology” by providing the conceptual theoretical framework necessary to generalize Chargaff’s rules. Starting with a simple example of DNA mathematical modeling where human nucleotide frequencies are associated to the Fibonacci sequence and the Golden Ratio through an optimization problem, its breakthrough is showing that the reverse, complement and reverse-complement operators defined over oligonucleotides induce a natural set partition of DNA words of fixed-size. These equivalence classes, when organized into a matrix form, reveal hidden patterns within the DNA sequence of every living organism. Intended for undergraduate and graduate students both in mathematics and in life sciences, it is also a valuable resource for researchers interested in studying invariant genomic properties.
We present the LexGram system, an amalgam of (Lambek) categorial grammar and Head Driven Phrase Structure Grammar (HPSG), and show that the grammar formalism it implements is a well-structured and useful tool for actual grammar development.
Medeiros, David P
A central concern of generative grammar is the relationship between hierarchy and word order, traditionally understood as two dimensions of a single syntactic representation. A related concern is directionality in the grammar. Traditional approaches posit process-neutral grammars, embodying knowledge of language, put to use with infinite facility both for production and comprehension. This has crystallized in the view of Merge as the central property of syntax, perhaps its only novel feature. A growing number of approaches explore grammars with different directionalities, often with more direct connections to performance mechanisms. This paper describes a novel model of universal grammar as a one-directional, universal parser. Mismatch between word order and interpretation order is pervasive in comprehension; in the present model, word order is language-particular and interpretation order (i.e., hierarchy) is universal. These orders are not two dimensions of a unified abstract object (e.g., precedence and dominance in a single tree); rather, both are temporal sequences, and UG is an invariant real-time procedure (based on Knuth's stack-sorting algorithm) transforming word order into hierarchical order. This shift in perspective has several desirable consequences. It collapses linearization, displacement, and composition into a single performance process. The architecture provides a novel source of brackets (labeled unambiguously and without search), which are understood not as part-whole constituency relations, but as storage and retrieval routines in parsing. It also explains why neutral word order within single syntactic cycles avoids 213-like permutations. The model identifies cycles as extended projections of lexical heads, grounding the notion of phase. This is achieved with a universal processor, dispensing with parameters. The empirical focus is word order in noun phrases. This domain provides some of the clearest evidence for 213-avoidance as a cross
Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.
This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard  discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth . Hans Georg Bock et.al  proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al , Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al .
Brabrand, Claus; Giegerich, Robert; Møller, Anders
It has been known since 1962 that the ambiguity problem for context-free grammars is undecidable. Ambiguity in context-free grammars is a recurring problem in language design and parser generation, as well as in applications where grammars are used as models of real-world physical structures. We...... observe that there is a simple linguistic characterization of the grammar ambiguity problem, and we show how to exploit this to conservatively approximate the problem based on local regular approximations and grammar unfoldings. As an application, we consider grammars that occur in RNA analysis...
Novikov, I; Fund, N; Freedman, L S
Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.
Su, Xianfang; Zhu, Huiming; You, Wanhai; Ren, Yinghua
The determinants of exchange rates have attracted considerable attention among researchers over the past several decades. Most studies, however, ignore the possibility that the impact of oil shocks on exchange rates could vary across the exchange rate returns distribution. We employ a quantile regression approach to address this issue. Our results indicate that the effect of oil shocks on exchange rates is heterogeneous across quantiles. A large US depreciation or appreciation tends to heighten the effects of oil shocks on exchange rate returns. Positive oil demand shocks lead to appreciation pressures in oil-exporting countries and this result is robust across lower and upper return distributions. These results offer rich and useful information for investors and decision-makers.
Kumar, Akansha; Tsvetkov, Pavel V.
desired power peaking limits, desired effective and infinite neutron multiplication factors, high fast fission factor, high thermal efficiency in the conversion from thermal energy to electrical energy using the Brayton cycle, and high fuel burn-up. It is to be noted that we have kept the total mass of the fuel as constant. In this work, we present a module based (modular) approach to perform the optimization wherein, we have defined the following modules: single fuel pin cell, whole core, thermal–hydraulics, and energy conversion. In each of the modules we have defined a specific set of parameters and optimization objectives. The GA system (GAS), and RS together, play the role of optimizing each of the individual modules, and integrating the modules to determine the final nuclear reactor core. However, implementation of GA could lead to a local minimum or a non-unique set of parameters, those meet the specific optimization objectives. The GA code is built using Java, neutronic analysis using MCNP6, thermal–hydraulics calculations using Java, and regression analysis using R
Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian
Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.
Mumtaz, Ubaidullah; Ali, Yousaf; Petrillo, Antonella
The increase in the environmental pollution is one of the most important topic in today's world. In this context, the industrial activities can pose a significant threat to the environment. To manage problems associate to industrial activities several methods, techniques and approaches have been developed. Green supply chain management (GSCM) is considered one of the most important "environmental management approach". In developing countries such as Pakistan the implementation of GSCM practices is still in its initial stages. Lack of knowledge about its effects on economic performance is the reason because of industries fear to implement these practices. The aim of this research is to perceive the effects of GSCM practices on organizational performance in Pakistan. In this research the GSCM practices considered are: internal practices, external practices, investment recovery and eco-design. While, the performance parameters considered are: environmental pollution, operational cost and organizational flexibility. A set of hypothesis propose the effect of each GSCM practice on the performance parameters. Factor analysis and linear regression are used to analyze the survey data of Pakistani industries, in order to authenticate these hypotheses. The findings of this research indicate a decrease in environmental pollution and operational cost with the implementation of GSCM practices, whereas organizational flexibility has not improved for Pakistani industries. These results aim to help managers regarding their decision of implementing GSCM practices in the industrial sector of Pakistan. Copyright © 2017 Elsevier B.V. All rights reserved.
D'Ulizia, A; Ferri, F; Grifoni, P
The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.
Full Text Available Abstract Background Two annual surveys, the abattoir and the fallen stock, monitor the presence of scrapie across Europe. A simple comparison between the prevalence estimates in different countries reveals that, in 2003, the abattoir survey appears to detect more scrapie in some countries. This is contrary to evidence suggesting the greater ability of the fallen stock survey to detect the disease. We applied meta-analysis techniques to study this apparent heterogeneity in the behaviour of the surveys across Europe. Furthermore, we conducted a meta-regression analysis to assess the effect of country-specific characteristics on the variability. We have chosen the odds ratios between the two surveys to inform the underlying relationship between them and to allow comparisons between the countries under the meta-regression framework. Baseline risks, those of the slaughtered populations across Europe, and country-specific covariates, available from the European Commission Report, were inputted in the model to explain the heterogeneity. Results Our results show the presence of significant heterogeneity in the odds ratios between countries and no reduction in the variability after adjustment for the different risks in the baseline populations. Three countries contributed the most to the overall heterogeneity: Germany, Ireland and The Netherlands. The inclusion of country-specific covariates did not, in general, reduce the variability except for one variable: the proportion of the total adult sheep population sampled as fallen stock by each country. A large residual heterogeneity remained in the model indicating the presence of substantial effect variability between countries. Conclusion The meta-analysis approach was useful to assess the level of heterogeneity in the implementation of the surveys and to explore the reasons for the variation between countries.
Grammar is sometimes defined aft"the way words are put together to make correct sentences"(Ur,2004,P.75).The aim of teaching grammar is to raise the rates of the correctness of language use and help the students transfer the isolated language points to apply language.In this essay，the author introduces two kinds of Conlnlon methods in English grammar class. And there are some key principles in grammar teaching.
Full Text Available The aims of this study are to describe the implementation of snowball throwing in teaching grammar and to investigate the benefits of applying snowball throwing. The research was conducted at STKIP Siliwangi Bandung. This study applied qualitative research involving one class consisting of second semester students in English Department who were taking the subject of foundation of English Grammar. The data were obtained from classroom observation and students’ interview. The findings showed that there are seven stages in implementing snowball throwing in teaching grammar. The stages consist of preparing teaching material, forming group, re-explaining the material to the member of the group, formulating question, tossing the ball, answering questions and evaluating teaching and learning process. In addition, the findings also revealed that there are some benefits from applying snowball throwing in teaching grammar such as improving students’ comprehension in learning grammar, creating enjoyable learning atmosphere, increasing students’ vocabulary, developing students’ speaking skill, developing students’ cooperation skill and increasing students’ participation in the class.
van Dijk, Chantal N; van Witteloostuijn, Merel; Vasić, Nada; Avrutin, Sergey; Blom, Elma
When sending text messages on their mobile phone to friends, children often use a special type of register, which is called textese. This register allows the omission of words and the use of textisms: instances of non-standard written language such as 4ever (forever). Previous studies have shown that textese has a positive effect on children's literacy abilities. In addition, it is possible that children's grammar system is affected by textese as well, as grammar rules are often transgressed in this register. Therefore, the main aim of this study was to investigate whether the use of textese influences children's grammar performance, and whether this effect is specific to grammar or language in general. Additionally, studies have not yet investigated the influence of textese on children's cognitive abilities. Consequently, the secondary aim of this study was to find out whether textese affects children's executive functions. To investigate this, 55 children between 10 and 13 years old were tested on a receptive vocabulary and grammar performance (sentence repetition) task and various tasks measuring executive functioning. In addition, text messages were elicited and the number of omissions and textisms in children's messages were calculated. Regression analyses showed that omissions were a significant predictor of children's grammar performance after various other variables were controlled for: the more words children omitted in their text messages, the better their performance on the grammar task. Although textisms correlated (marginally) significantly with vocabulary, grammar and selective attention scores and omissions marginally significantly with vocabulary scores, no other significant effects were obtained for measures of textese in the regression analyses: neither for the language outcomes, nor for the executive function tasks. Hence, our results show that textese is positively related to children's grammar performance. On the other hand, use of textese does
Chantal N van Dijk
Full Text Available When sending text messages on their mobile phone to friends, children often use a special type of register, which is called textese. This register allows the omission of words and the use of textisms: instances of non-standard written language such as 4ever (forever. Previous studies have shown that textese has a positive effect on children's literacy abilities. In addition, it is possible that children's grammar system is affected by textese as well, as grammar rules are often transgressed in this register. Therefore, the main aim of this study was to investigate whether the use of textese influences children's grammar performance, and whether this effect is specific to grammar or language in general. Additionally, studies have not yet investigated the influence of textese on children's cognitive abilities. Consequently, the secondary aim of this study was to find out whether textese affects children's executive functions. To investigate this, 55 children between 10 and 13 years old were tested on a receptive vocabulary and grammar performance (sentence repetition task and various tasks measuring executive functioning. In addition, text messages were elicited and the number of omissions and textisms in children's messages were calculated. Regression analyses showed that omissions were a significant predictor of children's grammar performance after various other variables were controlled for: the more words children omitted in their text messages, the better their performance on the grammar task. Although textisms correlated (marginally significantly with vocabulary, grammar and selective attention scores and omissions marginally significantly with vocabulary scores, no other significant effects were obtained for measures of textese in the regression analyses: neither for the language outcomes, nor for the executive function tasks. Hence, our results show that textese is positively related to children's grammar performance. On the other hand
Morrill, Glyn; Valentín, Oriol
In type logical categorial grammar the analysis of an expression is a resource-conscious proof. Anaphora represents a particular challenge to this approach in that the antecedent resource is multiplied in the semantics. This duplication, which corresponds logically to the structural rule of contraction, may be treated lexically or syntactically. Furthermore, anaphora is subject to constraints, which Chomsky (1981) formulated as Binding Principles A, B, and C. In this paper we consider English anaphora in categorial grammar including reference to the binding principles. We invoke displacement calculus, modal categorial calculus, categorial calculus with limited contraction, and entertain addition of negation as failure.
Construction grammars (Lakoff, Women, fire and dangerous things: What categories reveal about the Mind, University of Chicago Press, 1987; Langacker, Foundations of cognitive grammar: Theoretical pre-requisites, Stanford University Press, 1987; Croft, Radical construction grammar: Syntactic theory in typological perspective, Oxford University…
This article presents the original concept of drama grammar, the synthesis of grammar instruction and drama pedagogy, which integrates both structural and communicative paradigms through a dialectic combination of acting and linguistic analysis. Based on the principles of drama pedagogy, drama grammar makes use of techniques from the performing…
Morris, Rebecca; Perry, Thomas
In October 2015 the Department for Education (DfE) permitted a grammar school in Tonbridge, Kent, to open up an annexe in Sevenoaks, 10 miles away. Amidst claims that the annexe was essentially a new grammar school, the decision reignited an old debate about the value of academically-selective "grammar" schools in England. The intensity…
Felton, A. J.; Smith, M. D.
Heightened climatic variability due to atmospheric warming is forecast to increase the frequency and severity of climate extremes. In particular, changes to interannual variability in precipitation, characterized by increases in extreme wet and dry years, are likely to impact virtually all terrestrial ecosystem processes. However, to date experimental approaches have yet to explicitly test how ecosystem processes respond to multiple levels of climatic extremity, limiting our understanding of how ecosystems will respond to forecast increases in the magnitude of climate extremes. Here we report the results of a replicated regression experimental approach, in which we imposed 9 and 11 levels of growing season precipitation amount and extremity in mesic grassland during 2015 and 2016, respectively. Each level corresponded to a specific percentile of the long-term record, which produced a large gradient of soil moisture conditions that ranged from extreme wet to extreme dry. In both 2015 and 2016, asymptotic responses to water availability were observed for soil respiration. This asymmetry was driven in part by transitions between soil moisture versus temperature constraints on respiration as conditions became increasingly dry versus increasingly wet. In 2015, aboveground net primary production (ANPP) exhibited asymmetric responses to precipitation that largely mirrored those of soil respiration. In total, our results suggest that in this mesic ecosystem, these two carbon cycle processes were more sensitive to extreme drought than to extreme wet years. Future work will assess ANPP responses for 2016, soil nutrient supply and physiological responses of the dominant plant species. Future efforts are needed to compare our findings across a diverse array of ecosystem types, and in particular how the timing and magnitude of precipitation events may modify the response of ecosystem processes to increasing magnitudes of precipitation extremes.
An alternative approach is presented for the regression of response data on predictor variables that are not logically or physically separable. The methodology is demonstrated by its application to a data set of heavy-duty diesel emissions. Because of the covariance of fuel properties, it is found advantageous to redefine the predictor variables as vectors, in which the original fuel properties are components, rather than as scalars each involving only a single fuel property. The fuel property vectors are defined in such a way that they are mathematically independent and statistically uncorrelated. Because the available data set does not allow definitive separation of vehicle and fuel effects, and because test fuels used in several of the studies may be unrealistically contrived to break the association of fuel variables, the data set is not considered adequate for development of a full-fledged emission model. Nevertheless, the data clearly show that only a few basic patterns of fuel-property variation affect emissions and that the number of these patterns is considerably less than the number of variables initially thought to be involved. These basic patterns, referred to as ''eigenfuels,'' may reflect blending practice in accordance with their relative weighting in specific circumstances. The methodology is believed to be widely applicable in a variety of contexts. It promises an end to the threat of collinearity and the frustration of attempting, often unrealistically, to separate variables that are inseparable.
Politis, Dimitris N
The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality. Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, co...
Evans, Wiley; Mathis, Jeremy T.; Winsor, Peter; Statscewich, Hank; Whitledge, Terry E.
northern Gulf of Alaska (GOA) shelf experiences carbonate system variability on seasonal and annual time scales, but little information exists to resolve higher frequency variability in this region. To resolve this variability using platforms-of-opportunity, we present multiple linear regression (MLR) models constructed from hydrographic data collected along the Northeast Pacific Global Ocean Ecosystems Dynamics (GLOBEC) Seward Line. The empirical algorithms predict dissolved inorganic carbon (DIC) and total alkalinity (TA) using observations of nitrate (NO3-), temperature, salinity and pressure from the surface to 500 m, with R2s > 0.97 and RMSE values of 11 µmol kg-1 for DIC and 9 µmol kg-1 for TA. We applied these relationships to high-resolution NO3- data sets collected during a novel 20 h glider flight and a GLOBEC mesoscale SeaSoar survey. Results from the glider flight demonstrated time/space along-isopycnal variability of aragonite saturations (Ωarag) associated with a dicothermal layer (a cold near-surface layer found in high latitude oceans) that rivaled changes seen vertically through the thermocline. The SeaSoar survey captured the uplift to aragonite saturation horizon (depth where Ωarag = 1) shoaled to a previously unseen depth in the northern GOA. This work is similar to recent studies aimed at predicting the carbonate system in continental margin settings, albeit demonstrates that a NO3--based approach can be applied to high-latitude data collected from platforms capable of high-frequency measurements.
Ulkhaq, M. M.; Widodo, A. K.; Yulianto, M. F. A.; Widhiyaningrum; Mustikasari, A.; Akshinta, P. Y.
The implementation of renewable energy in this globalization era is inevitable since the non-renewable energy leads to climate change and global warming; hence, it does harm the environment and human life. However, in the developing countries, such as Indonesia, the implementation of the renewable energy sources does face technical and social problems. For the latter, renewable energy sources implementation is only effective if the public is aware of its benefits. This research tried to identify the determinants that influence consumers’ intention in adopting renewable energy sources. In addition, this research also tried to predict the consumers who are willing to apply the renewable energy sources in their houses using a logistic regression approach. A case study was conducted in Semarang, Indonesia. The result showed that only eight variables (from fifteen) that are significant statistically, i.e., educational background, employment status, income per month, average electricity cost per month, certainty about the efficiency of renewable energy project, relatives’ influence to adopt the renewable energy sources, energy tax deduction, and the condition of the price of the non-renewable energy sources. The finding of this study could be used as a basis for the government to set up a policy towards an implementation of the renewable energy sources.
Tshisaphungo, Mpho; McKinnell, Lee-Anne; Bosco Habarulema, John
The ionosphere is well known to reflect radio wave signals in the high frequency (HF) band due to the present of electron and ions within the region. To optimise the use of long distance HF communications, it is important to understand the drivers of ionospheric storms and accurately predict the propagation conditions especially during disturbed days. This paper presents the development of an ionospheric storm-time index over the South African region for the application of HF communication users. The model will result into a valuable tool to measure the complex ionospheric behaviour in an operational space weather monitoring and forecasting environment. The development of an ionospheric storm-time index is based on a single ionosonde station data over Grahamstown (33.3°S,26.5°E), South Africa. Critical frequency of the F2 layer (foF2) measurements for a period 1996-2014 were considered for this study. The model was developed based on linear regression and neural network approaches. In this talk validation results for low, medium and high solar activity periods will be discussed to demonstrate model's performance.
McCrocklin, Shannon; Slater, Tammy
This article introduces an approach that middle-school teachers can follow to help their students carry out linguistic-based literary analyses. As an example, it draws on Systemic Functional Grammar (SFG) to show how J.K. Rowling used language to characterize Hermione as an intelligent female in "Harry Potter and the Deathly Hallows."…
Consciousness-raising about grammar in the second-language classroom: Utilising authentic samples of learner-learner interaction in a task-based oral activity. ... More recent studies argue that linguistic support must not be omitted from language teaching programmes within a task-based, communicative approach (Swain, ...
Drabinová, Adéla; Martinková, Patrícia
Roč. 54, č. 4 (2017), s. 498-517 ISSN 0022-0655 R&D Projects: GA ČR GJ15-15856Y Institutional support: RVO:67985807 Keywords : differential item functioning * non-linear regression * logistic regression * item response theory Subject RIV: AM - Education OBOR OECD: Statistics and probability Impact factor: 0.979, year: 2016
Full Text Available The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit using nonparametric statistical tests: One sample rank test and Wilcoxon signed rank test for two independent groups of samples. The results obtained with One sample rank test could not give statistical justification for the selection of linear vs. quadratic regression models because slight differences between the error (presented through the relative residuals were obtained. Estimation of the significance of the differences in the RR was achieved using Wilcoxon signed rank test, where linear and quadratic regression models were treated as two independent groups. The application of this simple non-parametric statistical test provides statistical confirmation of the choice of an adequate regression model.
Full Text Available Teaching grammar has been regarded as a process of understanding from the context. It means a teacher teaches the pupils contextually more than just the rules. However, I have my own experience that teaching grammar methods must depend on the purposes of learning grammar. Some people learn grammar as a means to fulfill the syllabus needs for schools but other people learn grammar for special purposes out of school syllabus, such as for entrance test. For these reasons, the methods of teaching grammar should be different. The students who learn grammar based on the school syllabus probably needs longer procedure of learning that usually uses contextual teaching through listening, speaking, writing, and reading. Nevertheless, students who learn grammar for test need shorter procedure of learning such as memorizing. Therefore, I propose giving a workshop of teaching grammar using memory enhancement as another alternative teaching grammar method. This workshop would show the class that grammar can be learnt through memory enhancement process, i.e.; mind map, music, memory technique and drill to boost up students understanding for test preparation.
Alkerwi, Ala'a; Vernier, Céderic; Sauvageot, Nicolas; Crichton, Georgina E; Elias, Merrill F
Objectives This study aimed to examine the most important demographic and socioeconomic factors associated with diet quality, evaluated in terms of compliance with national dietary recommendations, selection of healthy and unhealthy food choices, energy density and food variety. We hypothesised that different demographic and socioeconomic factors may show disparate associations with diet quality. Study design A nationwide, cross-sectional, population-based study. Participants A total of 1352 apparently healthy and non-institutionalised subjects, aged 18–69 years, participated in the Observation of Cardiovascular Risk Factors in Luxembourg (ORISCAV-LUX) study in 2007–2008. The participants attended the nearest study centre after a telephone appointment, and were interviewed by trained research staff. Outcome measures Diet quality as measured by 5 dietary indicators, namely, recommendation compliance index (RCI), recommended foods score (RFS), non-recommended foods score (non-RFS), energy density score (EDS), and dietary diversity score (DDS). The novel Correlated Component Regression (CCR) technique was used to determine the importance and magnitude of the association of each socioeconomic factor with diet quality, in a global analytic approach. Results Increasing age, being male and living below the poverty threshold were predominant factors associated with eating a high energy density diet. Education level was an important factor associated with healthy and adequate food choices, whereas economic resources were predominant factors associated with food diversity and energy density. Conclusions Multiple demographic and socioeconomic circumstances were associated with different diet quality indicators. Efforts to improve diet quality for high-risk groups need an important public health focus. PMID:25967988
Rovlias, Aristedis; Theodoropoulos, Spyridon; Papoutsakis, Dimitrios
Background: Chronic subdural hematoma (CSDH) is one of the most common clinical entities in daily neurosurgical practice which carries a most favorable prognosis. However, because of the advanced age and medical problems of patients, surgical therapy is frequently associated with various complications. This study evaluated the clinical features, radiological findings, and neurological outcome in a large series of patients with CSDH. Methods: A classification and regression tree (CART) technique was employed in the analysis of data from 986 patients who were operated at Asclepeion General Hospital of Athens from January 1986 to December 2011. Burr holes evacuation with closed system drainage has been the operative technique of first choice at our institution for 29 consecutive years. A total of 27 prognostic factors were examined to predict the outcome at 3-month postoperatively. Results: Our results indicated that neurological status on admission was the best predictor of outcome. With regard to the other data, age, brain atrophy, thickness and density of hematoma, subdural accumulation of air, and antiplatelet and anticoagulant therapy were found to correlate significantly with prognosis. The overall cross-validated predictive accuracy of CART model was 85.34%, with a cross-validated relative error of 0.326. Conclusions: Methodologically, CART technique is quite different from the more commonly used methods, with the primary benefit of illustrating the important prognostic variables as related to outcome. Since, the ideal therapy for the treatment of CSDH is still under debate, this technique may prove useful in developing new therapeutic strategies and approaches for patients with CSDH. PMID:26257985
Ruan, D; Yang, Y; Cao, M; Hu, P; Low, D
Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improved robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme
Ruan, D; Yang, Y; Cao, M; Hu, P; Low, D [UCLA, Los Angeles, CA (United States)
Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improved robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme
Yung Liu, Y.; Bement, A.L.
In this paper the methodology of multiple regressions as applied to Zircaloy-2 in-reactor creep data analysis and construction of constitutive equation are illustrated. While the resulting constitutive equation can be used in creep analysis of in-reactor Zircaloy structural components, the methodology itself is entirely general and can be applied to any creep data analysis. The promising aspects of multiple regression creep data analysis are briefly outlined as follows: (1) When there are more than one variable involved, there is no need to make the assumption that each variable affects the response independently. No separate normalizations are required either and the estimation of parameters is obtained by solving many simultaneous equations. The number of simultaneous equations is equal to the number of data sets. (2) Regression statistics such as R 2 - and F-statistics provide measures of the significance of regression creep equation in correlating the overall data. The relative weights of each variable on the response can also be obtained. (3) Special regression techniques such as step-wise, ridge, and robust regressions and residual plots, etc., provide diagnostic tools for model selections. Multiple regression analysis performed on a set of carefully selected Zircaloy-2 in-reactor creep data leads to a model which provides excellent correlations for the data. (Auth.)
Shariff, Nurul Sima Mohamad; Ferdaos, Nur Aqilah
Multicollinearity often leads to inconsistent and unreliable parameter estimates in regression analysis. This situation will be more severe in the presence of outliers it will cause fatter tails in the error distributions than the normal distributions. The well-known procedure that is robust to multicollinearity problem is the ridge regression method. This method however is expected to be affected by the presence of outliers due to some assumptions imposed in the modeling procedure. Thus, the robust version of existing ridge method with some modification in the inverse matrix and the estimated response value is introduced. The performance of the proposed method is discussed and comparisons are made with several existing estimators namely, Ordinary Least Squares (OLS), ridge regression and robust ridge regression based on GM-estimates. The finding of this study is able to produce reliable parameter estimates in the presence of both multicollinearity and outliers in the data.
National Aeronautics and Space Administration — The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to...
Learnability theory is an attempt to illuminate the concept of learnability using a mathematical model of learning. Two models of learning of categorial grammars are examined here: the standard model, in which sentences presented to the learner are flat strings of words, and one in which sentences are presented in the form of functor-argument…
Sokolik, M. E.
While several checklists exist for the evaluation of ESL/EFL textbooks, none includes suggestions for looking for specific biases, especially those found in the content of examples and sample sentences. Growing awareness in publishing has reduced problems in the presentation of gender-based and racial biases in most ESL/EFL grammar textbooks, but…
Lester, Mark, Ed.
This volume contains nineteen essays, dealing with various aspects of transformational grammar, by scholars such as Noam Chomsky, Eric H. Lenneberg, and Leon Jakobovits. These essays have been reprinted from sources such as "College English" and "Language Learning" and are intended for the most part for a nontechnical audience. The anthology is…
rules N = 0 //non-terminal index clusters = cluster(W) //number of clusters drive the number S productions //cluster function described in text...Essa, “Recognizing multitasked activities from video using stochastic context-free grammar,” AAAI/IAAI, pp. 770–776, 2002.  R. Nevatia, T. Zhao
This dissertation presents a comprehensive description of the grammar of Logba, one of the fourteen Ghana-Togo Mountain (GTM) languages spoken by approximately 7,500 speakers on the Southeastern frontier of the Ghana-Togo border. It is the outcome of fifteen months research in Logba speaking
This paper deals with the correctness proofs of attribute grammars using methods from abstract interpretation. The technique will be described by defining a live-variable analysis for a small flow-chart language and proving it correct with respect to a continuation style semantics. The proof...
Mohan, M.; Shrimali, Tarun
In the software industry, software testing becomes more important in the entire software development life cycle. Software testing is one of the fundamental components of software quality assurances. Software Testing Life Cycle (STLC)is a process involved in testing the complete software, which includes Regression Testing, Unit Testing, Smoke Testing, Integration Testing, Interface Testing, System Testing & etc. In the STLC of Regression testing, test case selection is one of the most importan...
Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul
Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.
Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W
Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.
Yung Liu, Y.; Bement, A.L.
In this paper the methodology of multiple regressions as applied to zircaloy-2 in-reactor creep data analysis and construction of constitutive equation are illustrated. While the resulting constitutive equation can be used in creep analysis of in-reactor zircaloy structural components, the methodology itself is entirely general and can be applied to any creep data analysis. From data analysis and model development point of views, both the assumption of independence and prior committment to specific model forms are unacceptable. One would desire means which can not only estimate the required parameters directly from data but also provide basis for model selections, viz., one model against others. Basic understanding of the physics of deformation is important in choosing the forms of starting physical model equations, but the justifications must rely on their abilities in correlating the overall data. The promising aspects of multiple regression creep data analysis are briefly outlined as follows: (1) when there are more than one variable involved, there is no need to make the assumption that each variable affects the response independently. No separate normalizations are required either and the estimation of parameters is obtained by solving many simultaneous equations. The number of simultaneous equations is equal to the number of data sets, (2) regression statistics such as R 2 - and F-statistics provide measures of the significance of regression creep equation in correlating the overall data. The relative weights of each variable on the response can also be obtained. (3) Special regression techniques such as step-wise, ridge, and robust regressions and residual plots, etc., provide diagnostic tools for model selections
Lopez Fontan, J.L.; Costa, J.; Ruso, J.M.; Prieto, G. [Dept. of Applied Physics, Univ. of Santiago de Compostela, Santiago de Compostela (Spain); Sarmiento, F. [Dept. of Mathematics, Faculty of Informatics, Univ. of A Coruna, A Coruna (Spain)
The application of a statistical method, the local polynomial regression method, (LPRM), based on a nonparametric estimation of the regression function to determine the critical micelle concentration (cmc) is presented. The method is extremely flexible because it does not impose any parametric model on the subjacent structure of the data but rather allows the data to speak for themselves. Good concordance of cmc values with those obtained by other methods was found for systems in which the variation of a measured physical property with concentration showed an abrupt change. When this variation was slow, discrepancies between the values obtained by LPRM and others methods were found. (orig.)
Full Text Available English is the most important second language in most non-English speaking countries, including Malaysia. A good English proficiency comes from good grasp of grammar. To conquer the problems of low English proficiency among Malaysians, it is important to identify the key motivators that could facilitate the process of grammar learning. In this digital age, technology can play a very important role and mobile technology could be one of it. Thus, this study aims at designing a mobile learning tool, namely the Intelligent Mobile Learning Tool for Grammar Learning (i-MoL to act as the “on-the-go” grammar learning support via mobile phones. i-MoL helps reinforce grammar learning through mobile phone with game-like applications, inquiry-based activities and flashcard-like information. The intelligent part of i-MoL lies in its ability to map the mobile-based grammar learning content to individual’s preferred learning styles based on Felder-Silverman Learning Style Model (FSLSM. The instructional system design through the ADDIE model was used in this study as a systematic approach in designing a novel and comprehensive mobile learning tool for grammar learning. In terms of implications, this study provides insights on how mobile technologies can be utilized to meet the mobility demand among language learners today.
Shafiq, M. Najeeb
Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Tripathy, G.R.; Das, Anirban.
used methods, the Least Square Regression (LSR) and Inverse Modeling (IM), to determine the contributions of (i) solutes from different sources to global river water, and (ii) various rocks to a glacial till. The purpose of this exercise is to compare...
Gleason, Philip M.; Resch, Alexandra M.; Berk, Jillian A.
This NCEE Technical Methods Paper compares the estimated impacts of an educational intervention using experimental and regression discontinuity (RD) study designs. The analysis used data from two large-scale randomized controlled trials--the Education Technology Evaluation and the Teach for America Study--to provide evidence on the performance of…
Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas
The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…
Curs, Bradley R.; Harper, Casandra E.
Using a regression discontinuity design, we investigate whether a merit-based financial aid program has a causal effect on the first-year grade point average of first-time out-of-state freshmen at the University of Oregon. Our results indicate that merit-based financial aid has a positive and significant effect on first-year collegiate grade point…
Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P
This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of
Raftery, Brian; Santos, Jennifer
Based on our own experiences teaching grammar in developmental writing classes and classes not dedicated to writing instruction, along with a history of scholarship that indicates a need for grammar pedagogies (e.g., Dougherty, 2012), instructor-designed grammar games can likely help facilitate learning about these mechanics of writing while…
Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mette Balslev
Information on the spatial variability of soil texture including soil clay content in a landscape is very important for agricultural and environmental use. Different prediction techniques are available to assess and map spatial variability of soil properties, but selecting the most suitable techn...... the prediction in OKst compared with that in OK, whereas RT showed the lowest performance of all (R2 = 0.52; RMSE = 0.52; and RPD = 1.17). We found RKrr to be an effective prediction method and recommend this method for any future soil mapping activities in Denmark....... technique at a given site has always been a major issue in all soil mapping applications. We studied the prediction performance of ordinary kriging (OK), stratified OK (OKst), regression trees (RT), and rule-based regression kriging (RKrr) for digital mapping of soil clay content at 30.4-m grid size using 6...
Rayner, Manny; Carter, David
We show how a general grammar may be automatically adapted for fast parsing of utterances from a specific domain by means of constituent pruning and grammar specialization based on explanation-based learning. These methods together give an order of magnitude increase in speed, and the coverage loss entailed by grammar specialization is reduced to approximately half that reported in previous work. Experiments described here suggest that the loss of coverage has been reduced to the point where ...
Jackendoff, Ray; Wittenberg, Eva
We suggest that one way to approach the evolution of language is through reverse engineering: asking what components of the language faculty could have been useful in the absence of the full complement of components. We explore the possibilities offered by linear grammar, a form of language that lacks syntax and morphology altogether, and that structures its utterances through a direct mapping between semantics and phonology. A language with a linear grammar would have no syntactic categories or syntactic phrases, and therefore no syntactic recursion. It would also have no functional categories such as tense, agreement, and case inflection, and no derivational morphology. Such a language would still be capable of conveying certain semantic relations through word order-for instance by stipulating that agents should precede patients. However, many other semantic relations would have to be based on pragmatics and discourse context. We find evidence of linear grammar in a wide range of linguistic phenomena: pidgins, stages of late second language acquisition, home signs, village sign languages, language comprehension (even in fully syntactic languages), aphasia, and specific language impairment. We also find a full-blown language, Riau Indonesian, whose grammar is arguably close to a pure linear grammar. In addition, when subjects are asked to convey information through nonlinguistic gesture, their gestures make use of semantically based principles of linear ordering. Finally, some pockets of English grammar, notably compounds, can be characterized in terms of linear grammar. We conclude that linear grammar is a plausible evolutionary precursor of modern fully syntactic grammar, one that is still active in the human mind.
Mustafa Mubarak Pathan
Full Text Available Teaching and learning a foreign language like English is not easy task. The situation become more difficult when the learners are primary school children and teaching and learning focus is grammar, an activity often regarded as ‘boring, ‘uninteresting’ and ‘’tedious’. However, one’s mastery over a language is determined by the appropriate use of language by that individual following grammatical rules and failing to follow the rules of grammar marks one’s use of language as erroneous. Therefore, systematic attempt is done to teach grammatical rules and structures to the language learners from the beginning of language teaching and learning process. However, the success or failure of learning, mastering and using the grammatical rules and structures is largely determined by the technique and approach used by the grammar teacher to teach. The leaner-cantered, interesting, motivating technique of grammar teaching is believed to generate positive results whereas traditional, teacher-centered, uninteresting, uninvolving method is believed to be a cause of failure for learners to learn and master grammar rules and structures. Therefore, the grammar teaching technique, which involves language learners, to maximum, in learning in amusing and creative way, motivating, challenging and stimulating his/her mental processes, and reducing classroom anxiety and fear, is desired and recommended for fruitful language teaching and learning process. In this respect, the present paper discusses the effectiveness of using games for teaching grammar to primary school students as a technique which could easily be utilised and exploited for maximum benefits for learners. The study is based on the practical experiment done on the students of two primary schools in Sebha city of Libya using grammar games. The results, which proved to be fruitful and positive, are discussed as a basis for the argument in support of using games for teaching grammar to school
Agarwal, Parul; Sambamoorthi, Usha
Depression is common among individuals with osteoarthritis and leads to increased healthcare burden. The objective of this study was to examine excess total healthcare expenditures associated with depression among individuals with osteoarthritis in the US. Adults with self-reported osteoarthritis (n = 1881) were identified using data from the 2010 Medical Expenditure Panel Survey (MEPS). Among those with osteoarthritis, chi-square tests and ordinary least square regressions (OLS) were used to examine differences in healthcare expenditures between those with and without depression. Post-regression linear decomposition technique was used to estimate the relative contribution of different constructs of the Anderson's behavioral model, i.e., predisposing, enabling, need, personal healthcare practices, and external environment factors, to the excess expenditures associated with depression among individuals with osteoarthritis. All analysis accounted for the complex survey design of MEPS. Depression coexisted among 20.6 % of adults with osteoarthritis. The average total healthcare expenditures were $13,684 among adults with depression compared to $9284 among those without depression. Multivariable OLS regression revealed that adults with depression had 38.8 % higher healthcare expenditures (p regression linear decomposition analysis indicated that 50 % of differences in expenditures among adults with and without depression can be explained by differences in need factors. Among individuals with coexisting osteoarthritis and depression, excess healthcare expenditures associated with depression were mainly due to comorbid anxiety, chronic conditions and poor health status. These expenditures may potentially be reduced by providing timely intervention for need factors or by providing care under a collaborative care model.
Okada, Keisuke; Samreth, Sovannroeun
This paper investigates the effect of foreign aid on corruption using a quantile regression method. Our estimation results illustrate that foreign aid generally lessens corruption and, in particular, its reduction effect is larger in countries with low levels of corruption. In addition, considering foreign aid by donors, our analysis indicates that while multilateral aid has a larger reduction impact on corruption, bilateral aid from the world’s leading donors, such as France, the United King...
Lusiana, Evellin Dewi
The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.
Culicover, Peter W; Jackendoff, Ray; Audring, Jenny
There is ample evidence that speakers' linguistic knowledge extends well beyond what can be described in terms of rules of compositional interpretation stated over combinations of single words. We explore a range of multiword constructions (MWCs) to get a handle both on the extent of the phenomenon and on the grammatical constraints that may govern it. We consider idioms of various sorts, collocations, compounds, light verbs, syntactic nuts, and assorted other constructions, as well as morphology. Our conclusion is that MWCs highlight the central role that grammar plays in licensing MWCs in the lexicon and the creation of novel MWCs, and they help to clarify how the lexicon articulates with the rest of the grammar. Copyright © 2017 Cognitive Science Society, Inc.
Yu, Wenbao; Park, Taesung
It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.
Full Text Available Background and Objective: In the analysis of dichotomous type response variable, logistic regression is usually used. However, the performance of logistic regression in the presence of sparse data is questionable. In such a situation, a common problem is the presence of high odds ratios (ORs with very wide 95% confidence interval (CI (OR: >999.999, 95% CI: 999.999. In this paper, we addressed this issue by using penalized logistic regression (PLR method. Materials and Methods: Data from case-control study on hyponatremia and hiccups conducted in Christian Medical College, Vellore, Tamil Nadu, India was used. The outcome variable was the presence/absence of hiccups and the main exposure variable was the status of hyponatremia. Simulation dataset was created with different sample sizes and with a different number of covariates. Results: A total of 23 cases and 50 controls were used for the analysis of ordinary and PLR methods. The main exposure variable hyponatremia was present in nine (39.13% of the cases and in four (8.0% of the controls. Of the 23 hiccup cases, all were males and among the controls, 46 (92.0% were males. Thus, the complete separation between gender and the disease group led into an infinite OR with 95% CI (OR: >999.999, 95% CI: 999.999 whereas there was a finite and consistent regression coefficient for gender (OR: 5.35; 95% CI: 0.42, 816.48 using PLR. After adjusting for all the confounding variables, hyponatremia entailed 7.9 (95% CI: 2.06, 38.86 times higher risk for the development of hiccups as was found using PLR whereas there was an overestimation of risk OR: 10.76 (95% CI: 2.17, 53.41 using the conventional method. Simulation experiment shows that the estimated coverage probability of this method is near the nominal level of 95% even for small sample sizes and for a large number of covariates. Conclusions: PLR is almost equal to the ordinary logistic regression when the sample size is large and is superior in small cell
Brabrand, Claus; Giegerich, Robert; Møller, Anders
It has been known since 1962 that the ambiguity problem for context-free grammars is undecidable. Ambiguity in context-free grammars is a recurring problem in language design and parser generation, as well as in applications where grammars are used as models of real-world physical structures. We...... observe that there is a simple linguistic characterization of the grammar ambiguity problem, and we show how to exploit this by presenting an ambiguity analysis framework based on conservative language approximations. As a concrete example, we propose a technique based on local regular approximations...
The relationship between grammar and the psychological processing of language. ... manner in which speakers perceive and psycholinguistically process information. ... order, metaphorical extensions, processing constraints, end-focus theory
Schiff, Rachel; Katan, Pesia
Complexity has been shown to affect performance on artificial grammar learning (AGL) tasks (categorization of test items as grammatical/ungrammatical according to the implicitly trained grammar rules). However, previously published AGL experiments did not utilize consistent measures to investigate the comprehensive effect of grammar complexity on task performance. The present study focused on computerizing Bollt and Jones's (2000) technique of calculating topological entropy (TE), a quantitative measure of AGL charts' complexity, with the aim of examining associations between grammar systems' TE and learners' AGL task performance. We surveyed the literature and identified 56 previous AGL experiments based on 10 different grammars that met the sampling criteria. Using the automated matrix-lift-action method, we assigned a TE value for each of these 10 previously used AGL systems and examined its correlation with learners' task performance. The meta-regression analysis showed a significant correlation, demonstrating that the complexity effect transcended the different settings and conditions in which the categorization task was performed. The results reinforced the importance of using this new automated tool to uniformly measure grammar systems' complexity when experimenting with and evaluating the findings of AGL studies.
Pastra, Katerina; Aloimonos, Yiannis
Language and action have been found to share a common neural basis and in particular a common ‘syntax’, an analogous hierarchical and compositional organization. While language structure analysis has led to the formulation of different grammatical formalisms and associated discriminative or generative computational models, the structure of action is still elusive and so are the related computational models. However, structuring action has important implications on action learning and generalization, in both human cognition research and computation. In this study, we present a biologically inspired generative grammar of action, which employs the structure-building operations and principles of Chomsky's Minimalist Programme as a reference model. In this grammar, action terminals combine hierarchically into temporal sequences of actions of increasing complexity; the actions are bound with the involved tools and affected objects and are governed by certain goals. We show, how the tool role and the affected-object role of an entity within an action drives the derivation of the action syntax in this grammar and controls recursion, merge and move, the latter being mechanisms that manifest themselves not only in human language, but in human action too. PMID:22106430
Conti-Ramsden, Gina; Ullman, Michael T; Lum, Jarrad A G
What memory systems underlie grammar in children, and do these differ between typically developing (TD) children and children with specific language impairment (SLI)? Whilst there is substantial evidence linking certain memory deficits to the language problems in children with SLI, few studies have investigated multiple memory systems simultaneously, examining not only possible memory deficits but also memory abilities that may play a compensatory role. This study examined the extent to which procedural, declarative, and working memory abilities predict receptive grammar in 45 primary school aged children with SLI (30 males, 15 females) and 46 TD children (30 males, 16 females), both on average 9;10 years of age. Regression analyses probed measures of all three memory systems simultaneously as potential predictors of receptive grammar. The model was significant, explaining 51.6% of the variance. There was a significant main effect of learning in procedural memory and a significant group × procedural learning interaction. Further investigation of the interaction revealed that procedural learning predicted grammar in TD but not in children with SLI. Indeed, procedural learning was the only predictor of grammar in TD. In contrast, only learning in declarative memory significantly predicted grammar in SLI. Thus, different memory systems are associated with receptive grammar abilities in children with SLI and their TD peers. This study is, to our knowledge, the first to demonstrate a significant group by memory system interaction in predicting grammar in children with SLI and their TD peers. In line with Ullman's Declarative/Procedural model of language and procedural deficit hypothesis of SLI, variability in understanding sentences of varying grammatical complexity appears to be associated with variability in procedural memory abilities in TD children, but with declarative memory, as an apparent compensatory mechanism, in children with SLI.
The mean approach is one of the methods for pooling cross section and time series data for mathematical-statistical modelling. Though a simple approach, its results are sometimes paradoxical in nature. However, researchers still continue using it for its simplicity. Here, the paper investigates the nature and source of such unwanted phenomena. (author). 7 refs
Full Text Available Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model and (ii to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate
Šarić, Željko; Xu, Xuecai; Duan, Li; Babić, Darko
This study intended to investigate the interactions between accident rate and traffic signs in state roads located in Croatia, and accommodate the heterogeneity attributed to unobserved factors. The data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the heterogeneity, a panel quantile regression model was proposed, in which quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, while the panel data model accommodates the heterogeneity attributed to unobserved factors. Results revealed that (1) low visibility of material damage (MD) and death or injured (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3)average speed limit and the number of invalid traffic signs per km exhibited a high accident rate. To our knowledge, it's the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by involving the visibility, the present study demonstrates that the low visibility causes a relatively higher risk of MD and DI; It is noteworthy that average speed limit corresponds with accident rate positively; The number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; The number of invalid traffic signs per km are significant for accident rate, thus regular maintenance should be kept for a safer roadway environment.
Allard, Alexandra; Takman, Johanna; Uddin, Gazi Salah; Ahmed, Ali
We evaluate the N-shaped environmental Kuznets curve (EKC) using panel quantile regression analysis. We investigate the relationship between CO 2 emissions and GDP per capita for 74 countries over the period of 1994-2012. We include additional explanatory variables, such as renewable energy consumption, technological development, trade, and institutional quality. We find evidence for the N-shaped EKC in all income groups, except for the upper-middle-income countries. Heterogeneous characteristics are, however, observed over the N-shaped EKC. Finally, we find a negative relationship between renewable energy consumption and CO 2 emissions, which highlights the importance of promoting greener energy in order to combat global warming.
Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a
Pham, Hung T; Reilly, Barry
This paper uses mean and quantile regression analysis to investigate the gender pay gap for the wage employed in Vietnam over the period 1993 to 2002. It finds that the Doi moi reforms appear to have been associated with a sharp reduction in gender pay gap disparities for the wage employed. The average gender pay gap in this sector halved between 1993 and 2002 with most of the contraction evident by 1998. There has also been a narrowing in the gender pay gap at most selected points of the con...
Barry Reilly & T. Hung Pham
This paper uses mean and quantile regression analysis to investigate the gender pay gap for the wage employed in Vietnam over the period 1993 to 2002. It finds that the Doi moi reforms have been associated with a sharp reduction in gender wage disparities for the wage employed. The average gender pay gap in this sector halved between 1993 and 2002 with most of the contraction evident by 1998. There has also been a contraction in the gender pay at most selected points of the conditional wage d...
Full Text Available One of the climate models used to predict the climatic conditions is Global Circulation Models (GCM. GCM is a computer-based model that consists of different equations. It uses numerical and deterministic equation which follows the physics rules. GCM is a main tool to predict climate and weather, also it uses as primary information source to review the climate change effect. Statistical Downscaling (SD technique is used to bridge the large-scale GCM with a small scale (the study area. GCM data is spatial and temporal data most likely to occur where the spatial correlation between different data on the grid in a single domain. Multicollinearity problems require the need for pre-processing of variable data X. Continuum Regression (CR and pre-processing with Principal Component Analysis (PCA methods is an alternative to SD modelling. CR is one method which was developed by Stone and Brooks (1990. This method is a generalization from Ordinary Least Square (OLS, Principal Component Regression (PCR and Partial Least Square method (PLS methods, used to overcome multicollinearity problems. Data processing for the station in Ambon, Pontianak, Losarang, Indramayu and Yuntinyuat show that the RMSEP values and R2 predict in the domain 8x8 and 12x12 by uses CR method produces results better than by PCR and PLS.
Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.
Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability
Full Text Available This paper aims to bring theoretical linguistics and cognition-general theories of learning into closer contact. I argue that linguists' notions of rich UGs are well-founded, but that cognition-general learning approaches are viable as well and that the two can and should co-exist and support each other. Specifically, I use the observation that any theory of UG provides a learning criterion -- the total memory space used to store a grammar and its encoding of the input -- that supports learning according to the principle of Minimum Description-Length. This mapping from UGs to learners maintains a minimal ontological commitment: the learner for a particular UG uses only what is already required to account for linguistic competence in adults. I suggest that such learners should be our null hypothesis regarding the child's learning mechanism, and that furthermore, the mapping from theories of UG to learners provides a framework for comparing theories of UG.
Full Text Available A model is proposed to characterize the type of knowledge acquired in Artificial Grammar Learning (AGL. In particular, Shannon entropy is employed to compute the complexity of different test items in an AGL task, relative to the training items. According to this model, the more predictable a test item is from the training items, the more likely it is that this item should be selected as compatible with the training items. The predictions of the entropy model are explored in relation to the results from several previous AGL datasets and compared to other AGL measures. This particular approach in AGL resonates well with similar models in categorization and reasoning which also postulate that cognitive processing is geared towards the reduction of entropy.
Hoffmann, John P
Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes--all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapte...
Soltanzadeh, Ahmad; Mohammadfam, Iraj; Moghimbeigi, Abbas; Ghiasvand, Reza
Construction industry involves the highest risk of occupational accidents and bodily injuries, which range from mild to very severe. The aim of this cross-sectional study was to identify the factors associated with accident severity rate (ASR) in the largest Iranian construction companies based on data about 500 occupational accidents recorded from 2009 to 2013. We also gathered data on safety and health risk management and training systems. Data were analysed using Pearson's chi-squared coefficient and multiple regression analysis. Median ASR (and the interquartile range) was 107.50 (57.24- 381.25). Fourteen of the 24 studied factors stood out as most affecting construction accident severity (p<0.05). These findings can be applied in the design and implementation of a comprehensive safety and health risk management system to reduce ASR.
Full Text Available In this paper, the mathematical modeling of the flow in a porous cylinder with a focus on applications to solid rocket motors is presented. As usual, the cylindrical propellant grain of a solid rocket motor is modeled as a long tube with one end closed at the headwall, while the other remains open. The cylindrical wall is assumed to be permeable so as to simulate the propellant burning and normal gas injection. At first, the problem description and formulation are considered. The Navier-Stokes equations for the viscous flow in a porous cylinder with regressing walls are reduced to a nonlinear ODE by using a similarity transformation in time and space. Application of Differential Transformation Method (DTM as an approximate analytical method has been successfully applied. Finally the results have been presented for various cases.
Gemmill, Marin C; Costa-Font, Joan; McGuire, Alistair
An understanding of the relationship between cost sharing and drug consumption depends on consistent and unbiased price elasticity estimates. However, there is wide heterogeneity among studies, which constrains the applicability of elasticity estimates for empirical purposes and policy simulation. This paper attempts to provide a corrected measure of the drug price elasticity by employing meta-regression analysis (MRA). The results indicate that the elasticity estimates are significantly different from zero, and the corrected elasticity is -0.209 when the results are made robust to heteroskedasticity and clustering of observations. Elasticity values are higher when the study was published in an economic journal, when the study employed a greater number of observations, and when the study used aggregate data. Elasticity estimates are lower when the institutional setting was a tax-based health insurance system.
Bridges, J F; Hanson, R M
This paper inquires into the effects that Diagnosis Related Groups (DRGs) have had on the ability to explain patient-level costs in a specialist paediatrics hospital. Two hedonic models are estimated using 1996/97 New Children's Hospital (NCH) patient level cost data, one with and one without a casemix index (CMI). The results show that the inclusion of a casemix index as an explanatory variable leads to a better accounting of cost. The full hedonic model is then used to simulate a funding model for the 1997/98 NCH cost data. These costs are highly correlated with the actual costs reported for that year. In addition, univariate regression indicates that there has been inflation in costs in the order of 4.8% between the two years. In conclusion, hedonic analysis can provide valuable evidence for the design of funding models that account for casemix.
Mujasi, Paschal N; Asbu, Eyob Z; Puig-Junoy, Jaume
Hospitals represent a significant proportion of health expenditures in Uganda, accounting for about 26 % of total health expenditure. Improving the technical efficiency of hospitals in Uganda can result in large savings which can be devoted to expand access to services and improve quality of care. This paper explores the technical efficiency of referral hospitals in Uganda during the 2012/2013 financial year. This was a cross sectional study using secondary data. Input and output data were obtained from the Uganda Ministry of Health annual health sector performance report for the period July 1, 2012 to June 30, 2013 for the 14 public sector regional referral and 4 large private not for profit hospitals. We assumed an output-oriented model with Variable Returns to Scale to estimate the efficiency score for each hospital using Data Envelopment Analysis (DEA) with STATA13. Using a Tobit model DEA, efficiency scores were regressed against selected institutional and contextual/environmental factors to estimate their impacts on efficiency. The average variable returns to scale (Pure) technical efficiency score was 91.4 % and the average scale efficiency score was 87.1 % while the average constant returns to scale technical efficiency score was 79.4 %. Technically inefficient hospitals could have become more efficient by increasing the outpatient department visits by 45,943; and inpatient days by 31,425 without changing the total number of inputs. Alternatively, they would achieve efficiency by for example transferring the excess 216 medical staff and 454 beds to other levels of the health system without changing the total number of outputs. Tobit regression indicates that significant factors in explaining hospital efficiency are: hospital size (p Uganda.
Fan, Jung-Wei; Friedman, Carol
Biomedical natural language processing (BioNLP) is a useful technique that unlocks valuable information stored in textual data for practice and/or research. Syntactic parsing is a critical component of BioNLP applications that rely on correctly determining the sentence and phrase structure of free text. In addition to dealing with the vast amount of domain-specific terms, a robust biomedical parser needs to model the semantic grammar to obtain viable syntactic structures. With either a rule-based or corpus-based approach, the grammar engineering process requires substantial time and knowledge from experts, and does not always yield a semantically transferable grammar. To reduce the human effort and to promote semantic transferability, we propose an automated method for deriving a probabilistic grammar based on a training corpus consisting of concept strings and semantic classes from the Unified Medical Language System (UMLS), a comprehensive terminology resource widely used by the community. The grammar is designed to specify noun phrases only due to the nominal nature of the majority of biomedical terminological concepts. Evaluated on manually parsed clinical notes, the derived grammar achieved a recall of 0.644, precision of 0.737, and average cross-bracketing of 0.61, which demonstrated better performance than a control grammar with the semantic information removed. Error analysis revealed shortcomings that could be addressed to improve performance. The results indicated the feasibility of an approach which automatically incorporates terminology semantics in the building of an operational grammar. Although the current performance of the unsupervised solution does not adequately replace manual engineering, we believe once the performance issues are addressed, it could serve as an aide in a semi-supervised solution. Copyright © 2011 Elsevier Inc. All rights reserved.
The article is devoted for the effective ways of teaching grammar. Actuality of the theme is justified as it sets conditions for revealing high progress in teaching a foreign language and for developing effective methods which can be helpful for foreign language teachers. Different progressive methods of teaching English grammar are given in this paper as well.
This selective review of the second language acquisition and applied linguistics research literature on grammar learning and teaching falls into three categories: where research has had little impact (the non-interface position), modest impact (form-focused instruction), and where it potentially can have a large impact (reconceiving grammar).…
Goldefus, F.; Masopust, Tomáš; Meduna, A.
Roč. 411, 40-42 (2010), s. 3661-3667 ISSN 0304-3975 Institutional research plan: CEZ:AV0Z10190503 Keywords : cooperating distributed grammar system * cooperating derivation mode * left-forbidding grammar * generative power * descriptional complexity Subject RIV: BA - General Mathematics Impact factor: 0.838, year: 2010 http://www.sciencedirect.com/science/article/pii/S0304397510003440
The paper first traces the history of thinking about language from the Greek writers of the fifth century BC to the development of the first Greek grammar in about 100 BC. Since the glories of Ancient Greek literature predate the development of grammar, there is every reason to doubt the received wisdom that one must have an explicit knowledge of…
@@ 1 Definition of grammar People sometlmes descibe grammaras the "rules" of a language, to be accurate,grammar is the science dealing with thesystematic rules of a language,its forms,inflections,syntax,and the rules of usingthem correctly.It is summarized from lan-guage use and practice,and reflects thelogic of thinking in people's speech orwriting.
When being a student in grade school as well as in high school (1934-1946), grammar was heavily emphasized in English/language arts classes, particularly in grades four through the senior year in high school. Evidently, teachers and school administrators then saw a theoretical way to assist pupils in writing achievement. Grammar and writing were…
Sag, Ivan A.; Wasow, Thomas
We explore the consequences of letting the incremental and integrative nature of language processing inform the design of competence grammar. What emerges is a view of grammar as a system of local monotonic constraints that provide a direct characterization of the signs (the form-meaning correspondences) of a given language. This…
Richards, Jack C.; Reppen, Randi
Grammar can be viewed both as knowledge and as ability. When viewed as knowledge, the focus is on rules for sentence formation. When viewed as ability, the focus is on how grammar is used as a resource in the creation of spoken and written texts. Twelve principles are proposed as the basis for a pedagogy that focusses on acquiring learning to use…
Wang, Shudong; Smith, Simon
This paper describes an ongoing language-learning project, three years into its development. We examine both the feasibility and the limitations of developing English reading and grammar skills through the interface of mobile phones. Throughout the project, reading and grammar materials were regularly sent to students' mobile phones. Students read…
Full Text Available The aim of this paper discussed about how to enhance students’ higher order thinking that should be done by teacher in teaching grammar. Usually teaching grammar was boring and has the same way to learn like change the pattern of sentence into positive, negative and introgative while the students’ need more various way to develop their thinking. The outcome of students’ competence in grammar sometimes not sufficient enough when the students’ occured some test international standart like Test of English Foreign Language, International English Language Testing. Whereas in TOEFL test it needed higher order thinking answer, so teacher should develop students’ higher order thingking in daily teaching grammar in order to make the students’ enhance their thinking are higher. The method was used in this paper by using field study based on the experience of teaching grammar. It can be shown by students’ toefl score was less in stucture and written expression. The result of this paper was after teacher gave some treatments to enhance students’ higher order thinking in teaching grammar, the students’ toefl scores are sufficient enough as a part of stucture and written expression. It can concluded that it needed some strategies to enhancce students higher order thinking by teaching grammar it can make students’ higher toefl score. Teachers should be creative and inovative to teach the students’ started from giving the students’ question or test in teaching grammar.
Robiah Adnan; Mohd Nor Mohamad; Halim Setan
This research provides a clustering based approach for determining potential candidates for outliers. This is modification of the method proposed by Serbert et. al (1988). It is based on using the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS). (Author)
Mazenq, Julie; Dubus, Jean-Christophe; Gaudart, Jean; Charpin, Denis; Viudes, Gilles; Noel, Guilhem
Particulate matter, nitrogen dioxide (NO 2 ) and ozone are recognized as the three pollutants that most significantly affect human health. Asthma is a multifactorial disease. However, the place of residence has rarely been investigated. We compared the impact of air pollution, measured near patients' homes, on emergency department (ED) visits for asthma or trauma (controls) within the Provence-Alpes-Côte-d'Azur region. Variables were selected using classification and regression trees on asthmatic and control population, 3-99 years, visiting ED from January 1 to December 31, 2013. Then in a nested case control study, randomization was based on the day of ED visit and on defined age groups. Pollution, meteorological, pollens and viral data measured that day were linked to the patient's ZIP code. A total of 794,884 visits were reported including 6250 for asthma and 278,192 for trauma. Factors associated with an excess risk of emergency visit for asthma included short-term exposure to NO 2 , female gender, high viral load and a combination of low temperature and high humidity. Short-term exposures to high NO 2 concentrations, as assessed close to the homes of the patients, were significantly associated with asthma-related ED visits in children and adults. Copyright © 2017 Elsevier Ltd. All rights reserved.
Full Text Available Evidence collected in many parts of the world suggests that, compared to older students, students who are relatively younger at school entry tend to have worse academic performance and lower levels of income. This study examined how relative age in a grade affects suicide rates of adolescents and young adults between 15 and 25 years of age using data from Japan.We examined individual death records in the Vital Statistics of Japan from 1989 to 2010. In contrast to other countries, late entry to primary school is not allowed in Japan. We took advantage of the school entry cutoff date to implement a regression discontinuity (RD design, assuming that the timing of births around the school entry cutoff date was randomly determined and therefore that individuals who were born just before and after the cutoff date have similar baseline characteristics.We found that those who were born right before the school cutoff day and thus youngest in their cohort have higher mortality rates by suicide, compared to their peers who were born right after the cutoff date and thus older. We also found that those with relative age disadvantage tend to follow a different career path than those with relative age advantage, which may explain their higher suicide mortality rates.Relative age effects have broader consequences than was previously supposed. This study suggests that policy intervention that alleviates the relative age effect can be important.
Beklemishev, Lev; Vereshchagin, Nikolai
The book contains English translations of three outstanding dissertations in mathematical logic and complexity theory. L. Beklemishev proves that all provability logics must belong to one of the four previously known classes. The dissertation of M. Pentus proves the Chomsky conjecture about the equivalence of two approaches to formal languages: the Chomsky hierarchy and the Lambek calculus. The dissertation of N. Vereshchagin describes a general framework for criteria of reversability in complexity theory.
Larson, Nicholas B; Schaid, Daniel J
Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.
Zhang, Yue-Jun; Peng, Hua-Rong; Liu, Zhao; Tan, Weiping
The transport sector appears a main energy consumer in China and plays a significant role in energy conservation. Improving energy efficiency proves an effective way to reduce energy consumption in transport sector, whereas its effectiveness may be affected by the rebound effect. This paper proposes a dynamic panel quantile regression model to estimate the direct energy rebound effect for road passenger transport in the whole country, eastern, central and western China, respectively, based on the data of 30 provinces from 2003 to 2012. The empirical results reveal that, first of all, the direct rebound effect does exist for road passenger transport and on the whole country, the short-term and long-term direct rebound effects are 25.53% and 26.56% on average, respectively. Second, the direct rebound effect for road passenger transport in central and eastern China tends to decrease, increase and then decrease again, whereas that in western China decreases and then increases, with the increasing passenger kilometers. Finally, when implementing energy efficiency policy in road passenger transport sector, the effectiveness of energy conservation in western China proves much better than that in central China overall, while the effectiveness in central China is relatively better than that in eastern China. - Highlights: • The direct rebound effect (RE) for road passenger transport in China is estimated. • The direct RE in the whole country, eastern, central, and western China is analyzed. • The short and long-term direct REs are 25.53% and 26.56% within the sample period. • Western China has better energy-saving performance than central and eastern China.
Abdulmajeed, Rufaidah Kamal; Hameed, Sarab Khalil
Teachers who teach a new language grammar do not usually have the time and the proper situation to introduce humour when starting a new topic in grammar. There are many different opinions about teaching grammar. Many teachers seem to believe in the importance of grammar lessons devoted to a study of language rules and practical exercises. Other…
This paper attempts to elaborate the importance of grammar teaching at college through the four linguistic skills: listening, speaking, reading,and writing.The nature of grammar determines the significance of grammar teaching. This paper shows the importance of grammar teaching from its relationship with listening,speaking,reading and writing.
The study of grammar has been paid much attention and the grammar instruction becomes an emphasis and key problem in English language teaching and learning. How to instruct students grammar appropriately becomes controversial for some English teachers increasingly. Some linguistics, theorists and teachers hold that the grammar instruction should…
This study aimed at investigating English grammar knowledge of a group of Thai university students. The three main research questions revolved around their knowledge of English grammar, the kinds of difficulties they had encountered in using the grammar as well as their perceptions of the roles of grammar in using English. The participants were…
Suggests that English teachers need to know that grammar is a difficult subject; know what children know about grammar; know that grammatical error is complex; and know more about language than just grammar. Concludes with the advice of Noam Chomsky--that grammar should be taught for its own intrinsic interest. (RS)
The equivalence problem for context-free grammars is "given two arbitrary grammars, do they generate the same language?" Since this is undecidable in general, attention has been restricted to decidable subclasses of the context-free grammars. For example, the classes of LL(k) grammars and real-time
H.J.S. Basten (Bas)
textabstractThe Meta-Environment enables the creation of grammars using the SDF formalism. From these grammars an SGLR parser can be generated. One of the advantages of these parsers is that they can handle the entire class of context-free grammars (CFGs). The grammar developer does not have to
In the literature results can be found which claim consistency for the subspace method under certain quite weak assumptions. Unfortunately, a new result gives a counter example showing inconsistency under these assumptions and then gives new more strict sufficient assumptions which however does n...... not include important model structures as e.g. Box-Jenkins. Based on a simple least squares approach this paper shows the possible inconsistency under the weak assumptions and develops only slightly stricter assumptions sufficient for consistency and which includes any model structure...
Chen, Kuilin; Yu, Jie
Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations
Najera-Zuloaga, Josu; Lee, Dae-Jin; Arostegui, Inmaculada
Health-related quality of life has become an increasingly important indicator of health status in clinical trials and epidemiological research. Moreover, the study of the relationship of health-related quality of life with patients and disease characteristics has become one of the primary aims of many health-related quality of life studies. Health-related quality of life scores are usually assumed to be distributed as binomial random variables and often highly skewed. The use of the beta-binomial distribution in the regression context has been proposed to model such data; however, the beta-binomial regression has been performed by means of two different approaches in the literature: (i) beta-binomial distribution with a logistic link; and (ii) hierarchical generalized linear models. None of the existing literature in the analysis of health-related quality of life survey data has performed a comparison of both approaches in terms of adequacy and regression parameter interpretation context. This paper is motivated by the analysis of a real data application of health-related quality of life outcomes in patients with Chronic Obstructive Pulmonary Disease, where the use of both approaches yields to contradictory results in terms of covariate effects significance and consequently the interpretation of the most relevant factors in health-related quality of life. We present an explanation of the results in both methodologies through a simulation study and address the need to apply the proper approach in the analysis of health-related quality of life survey data for practitioners, providing an R package.
Persons with a college degree are more likely to engage in eHealth behaviors than persons without a college degree, compounding the health disadvantages of undereducated groups in the United States. However, the extent to which quality of recent eHealth experience reduces the education-based eHealth gap is unexplored. The goal of this study was to examine how eHealth information search experience moderates the relationship between college education and eHealth behaviors. Based on a nationally representative sample of adults who reported using the Internet to conduct the most recent health information search (n=1458), I evaluated eHealth search experience in relation to the likelihood of engaging in different eHealth behaviors. I examined whether Internet health information search experience reduces the eHealth behavior gaps among college-educated and noncollege-educated adults. Weighted logistic regression models were used to estimate the probability of different eHealth behaviors. College education was significantly positively related to the likelihood of 4 eHealth behaviors. In general, eHealth search experience was negatively associated with health care behaviors, health information-seeking behaviors, and user-generated or content sharing behaviors after accounting for other covariates. Whereas Internet health information search experience has narrowed the education gap in terms of likelihood of using email or Internet to communicate with a doctor or health care provider and likelihood of using a website to manage diet, weight, or health, it has widened the education gap in the instances of searching for health information for oneself, searching for health information for someone else, and downloading health information on a mobile device. The relationship between college education and eHealth behaviors is moderated by Internet health information search experience in different ways depending on the type of eHealth behavior. After controlling for college
Tomczyk, Aleksandra; Ewertowski, Marek; White, Piran; Kasprzak, Leszek
The dual role of many Protected Natural Areas in providing benefits for both conservation and recreation poses challenges for management. Although recreation-based damage to ecosystems can occur very quickly, restoration can take many years. The protection of conservation interests at the same as providing for recreation requires decisions to be made about how to prioritise and direct management actions. Trails are commonly used to divert visitors from the most important areas of a site, but high visitor pressure can lead to increases in trail width and a concomitant increase in soil erosion. Here we use detailed field data on condition of recreational trails in Gorce National Park, Poland, as the basis for a regression tree analysis to determine the factors influencing trail deterioration, and link specific trail impacts with environmental, use related and managerial factors. We distinguished 12 types of trails, characterised by four levels of degradation: (1) trails with an acceptable level of degradation; (2) threatened trails; (3) damaged trails; and (4) heavily damaged trails. Damaged trails were the most vulnerable of all trails and should be prioritised for appropriate conservation and restoration. We also proposed five types of monitoring of recreational trail conditions: (1) rapid inventory of negative impacts; (2) monitoring visitor numbers and variation in type of use; (3) change-oriented monitoring focusing on sections of trail which were subjected to changes in type or level of use or subjected to extreme weather events; (4) monitoring of dynamics of trail conditions; and (5) full assessment of trail conditions, to be carried out every 10-15 years. The application of the proposed framework can enhance the ability of Park managers to prioritise their trail management activities, enhancing trail conditions and visitor safety, while minimising adverse impacts on the conservation value of the ecosystem. A.M.T. was supported by the Polish Ministry of
Full Text Available Learning a foreign language offers a great challenge to students since it involves learning different skills and subskills. Quite a few number of researches have been done so far on the relationship between gender and learning a foreign language. On the other hand, two major approaches in teaching grammar have been offered by language experts, inductive and deductive. The present study examines which method of teaching grammar is more fruitful for Iranian male and female students. For this purpose, 150 freshman students, 110 females and 40 males, majoring in English were selected from all available students at Abadeh and Shiraz Azad universities. All the subjects took the NTC's grammar test prior to the instruction as pre-test. Then, they were divided into two groups and were taught grammar inductively and deductively in each group for one semester. At the end of the instruction, the same test was taken as post-test. The comparison between the students' pre and post-test indicated that there was a significant improvement in their knowledge of grammar. By the way, through a two-way ANOVA, it was found out that males learned grammar better when they were taught inductively and females showed a better performance when they were taught deductively.
Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.
Missing covariate data often arise in biomedical studies, and analysis of such data that ignores subjects with incomplete information may lead to inefficient and possibly biased estimates. A great deal of attention has been paid to handling a single missing covariate or a monotone pattern of missing data when the missingness mechanism is missing at random. In this article, we propose a semiparametric method for handling non-monotone patterns of missing data. The proposed method relies on the assumption that the missingness mechanism of a variable does not depend on the missing variable itself but may depend on the other missing variables. This mechanism is somewhat less general than the completely non-ignorable mechanism but is sometimes more flexible than the missing at random mechanism where the missingness mechansim is allowed to depend only on the completely observed variables. The proposed approach is robust to misspecification of the distribution of the missing covariates, and the proposed mechanism helps to nullify (or reduce) the problems due to non-identifiability that result from the non-ignorable missingness mechanism. The asymptotic properties of the proposed estimator are derived. Finite sample performance is assessed through simulation studies. Finally, for the purpose of illustration we analyze an endometrial cancer dataset and a hip fracture dataset.
Abubakar M. Miyim
Full Text Available The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS/Access Points (APs in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency.
Yamagishi, Michel Eduardo Beleza; Herai, Roberto H.
Chargaff once said that "I saw before me in dark contours the beginning of a grammar of Biology". In linguistics, "grammar" is the set of natural language rules, but we do not know for sure what Chargaff meant by "grammar" of Biology. Nevertheless, assuming the metaphor, Chargaff himself started a "grammar of Biology" discovering the so called Chargaff's rules. In this work, we further develop his grammar. Using new concepts, we were able to discovery new genomic rules that seem to be invaria...
Kate, Rohit J
Clinical reports are written using a subset of natural language while employing many domain-specific terms; such a language is also known as a sublanguage for a scientific or a technical domain. Different genres of clinical reports use different sublaguages, and in addition, different medical facilities use different medical language conventions. This makes supervised training of a parser for clinical sentences very difficult as it would require expensive annotation effort to adapt to every type of clinical text. In this paper, we present an unsupervised method which automatically induces a grammar and a parser for the sublanguage of a given genre of clinical reports from a corpus with no annotations. In order to capture sentence structures specific to clinical domains, the grammar is induced in terms of semantic classes of clinical terms in addition to part-of-speech tags. Our method induces grammar by minimizing the combined encoding cost of the grammar and the corresponding sentence derivations. The probabilities for the productions of the induced grammar are then learned from the unannotated corpus using an instance of the expectation-maximization algorithm. Our experiments show that the induced grammar is able to parse novel sentences. Using a dataset of discharge summary sentences with no annotations, our method obtains 60.5% F-measure for parse-bracketing on sentences of maximum length 10. By varying a parameter, the method can induce a range of grammars, from very specific to very general, and obtains the best performance in between the two extremes.
Nielsen, Helena Skyt; Rosholm, Michael
of economic transition, because items as privatization and deregulation were on the political agenda. The focus is placed on the public-private sector wage gap, and the results show that this gap was relatively favorable for the low-skilled and less favorable for the high-skilled. This picture was further......We investigate the determinants of wages in Zambia and based on the quantile regression approach, we analyze how their effects differ at different points in the wage distribution and over time. We use three cross-sections of Zambian household data from the early nineties, which was a period...
Andrias Tri Susanto
Full Text Available This research article reports a qualitative study which was conducted to investigate ways successful EFL learners learned English grammar. The subjects of this research were eight successful EFL learners from six different countries in Asia: China, Indonesia, Japan, South Korea, Thailand, and Vietnam. The data was collected by interviewing each subject in person individually at an agreed time and place. The result showed that all the grammar learning processes described by the subjects were closely linked to the framework of Associative Cognitive CREED. There were also some contributing factors that could be integrally combined salient to the overall grammar learning process. However, interestingly, each subject emphasized different aspects of learning.
Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.
Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.
Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be
Stollenwerk, Björn; Welchowski, Thomas; Vogl, Matthias; Stock, Stephanie
Despite the increasing availability of routine data, no analysis method has yet been presented for cost-of-illness (COI) studies based on massive data. We aim, first, to present such a method and, second, to assess the relevance of the associated gain in numerical efficiency. We propose a prevalence-based, top-down regression approach consisting of five steps: aggregating the data; fitting a generalized additive model (GAM); predicting costs via the fitted GAM; comparing predicted costs between prevalent and non-prevalent subjects; and quantifying the stochastic uncertainty via error propagation. To demonstrate the method, it was applied to aggregated data in the context of chronic lung disease to German sickness funds data (from 1999), covering over 7.3 million insured. To assess the gain in numerical efficiency, the computational time of the innovative approach has been compared with corresponding GAMs applied to simulated individual-level data. Furthermore, the probability of model failure was modeled via logistic regression. Applying the innovative method was reasonably fast (19 min). In contrast, regarding patient-level data, computational time increased disproportionately by sample size. Furthermore, using patient-level data was accompanied by a substantial risk of model failure (about 80 % for 6 million subjects). The gain in computational efficiency of the innovative COI method seems to be of practical relevance. Furthermore, it may yield more precise cost estimates.
Sumner, Anne E; Luercio, Marcella F; Frempong, Barbara A; Ricks, Madia; Sen, Sabyasachi; Kushner, Harvey; Tulloch-Reid, Marshall K
The disposition index, the product of the insulin sensitivity index (S(I)) and the acute insulin response to glucose, is linked in African Americans to chromosome 11q. This link was determined with S(I) calculated with the nonlinear regression approach to the minimal model and data from the reduced-sample insulin-modified frequently-sampled intravenous glucose tolerance test (Reduced-Sample-IM-FSIGT). However, the application of the nonlinear regression approach to calculate S(I) using data from the Reduced-Sample-IM-FSIGT has been challenged as being not only inaccurate but also having a high failure rate in insulin-resistant subjects. Our goal was to determine the accuracy and failure rate of the Reduced-Sample-IM-FSIGT using the nonlinear regression approach to the minimal model. With S(I) from the Full-Sample-IM-FSIGT considered the standard and using the nonlinear regression approach to the minimal model, we compared the agreement between S(I) from the Full- and Reduced-Sample-IM-FSIGT protocols. One hundred African Americans (body mass index, 31.3 +/- 7.6 kg/m(2) [mean +/- SD]; range, 19.0-56.9 kg/m(2)) had FSIGTs. Glucose (0.3 g/kg) was given at baseline. Insulin was infused from 20 to 25 minutes (total insulin dose, 0.02 U/kg). For the Full-Sample-IM-FSIGT, S(I) was calculated based on the glucose and insulin samples taken at -1, 1, 2, 3, 4, 5, 6, 7, 8,10, 12, 14, 16, 19, 22, 23, 24, 25, 27, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150, and 180 minutes. For the Reduced-Sample-FSIGT, S(I) was calculated based on the time points that appear in bold. Agreement was determined by Spearman correlation, concordance, and the Bland-Altman method. In addition, for both protocols, the population was divided into tertiles of S(I). Insulin resistance was defined by the lowest tertile of S(I) from the Full-Sample-IM-FSIGT. The distribution of subjects across tertiles was compared by rank order and kappa statistic. We found that the rate of failure of resolution of S(I) by
Hamdi, Salah; Ben Abdallah, Asma; Bedoui, Mohamed Hedi
The sequence of Q, R, and S peaks (QRS) complex detection is a crucial procedure in electrocardiogram (ECG) processing and analysis. We propose a novel approach for QRS complex detection based on the deterministic finite automata with the addition of some constraints. This paper confirms that regular grammar is useful for extracting QRS complexes and interpreting normalized ECG signals. A QRS is assimilated to a pair of adjacent peaks which meet certain criteria of standard deviation and duration. The proposed method was applied on several kinds of ECG signals issued from the standard MIT-BIH arrhythmia database. A total of 48 signals were used. For an input signal, several parameters were determined, such as QRS durations, RR distances, and the peaks' amplitudes. σRR and σQRS parameters were added to quantify the regularity of RR distances and QRS durations, respectively. The sensitivity rate of the suggested method was 99.74% and the specificity rate was 99.86%. Moreover, the sensitivity and the specificity rates variations according to the Signal-to-Noise Ratio were performed. Regular grammar with the addition of some constraints and deterministic automata proved functional for ECG signals diagnosis. Compared to statistical methods, the use of grammar provides satisfactory and competitive results and indices that are comparable to or even better than those cited in the literature.
Norman, Elisabeth; Price, Mark C; Jones, Emma
In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning. Copyright © 2011 Elsevier Inc. All rights reserved.
Al-kazzaz, Dhuha; Bridges, Alan; Chase, Scott Curland
This paper describes a new methodology of deriving innovative hybrid designs using shape grammars of heterogeneous designs. The method is detailed within three phases of shape grammars: analysis, synthesis and evaluation. In the analysis phase, the research suggests that original rules of each...... design component are grouped in subclass rule sets to facilitate rule choices. Additionally, adding new hybrid rules to original rules expands the options available to the grammar user. In the synthesis phase, the research adopts state labels and markers to drive the design generation. The former...... is implemented with a user guide grammar to ensure hybridity in the generated design, while the latter aims to ensure feasible designs. Lastly evaluation criteria are added to measure the degree of innovation of the hybrid designs. This paper describes the derivation of hybrid minaret designs from a corpus...
C. Murni Wahyanti
Full Text Available Current developments in foreign language teaching have shown the need to reconsider the role of grammar. It is argued that grammar understanding can promote more precise use of the foreign language. This belief has led to an increased interest in grammar teaching, including grammar teaching for young learners. In teaching English to young learners, activities that can promote grammar awareness are needed. The activities should be presented in context to make sure that the meaning is clear. The activities should also be creatively designed in order to challenge students‘ motivation and involvement. Grammar activities presented creatively in meaningful contexts are useful for noticing the language patterns. This paper focuses on the changing status of grammar, the importance of grammar in the young learner classroom, and how to raise grammar awareness through creative language activities. It also reports the result of a small-scale study on implementing grammarawareness activities for teaching English to Elementary School students.
浅野, 美代子; マーコ, ユー K.W.
This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...
presumed. Basic references on the systemic framework include [Berry 75, Berry 77, Halliday 76a, Halliday 76b, Hudson 76, Halliday 81, de Joia 80...Edinburgh, 1979. [do Joia 80] de Joia , A., and A. Stanton, Terms in Systemic Linguistics, Batsford Academic and Educational, Ltd., London, 1980. -’C...1 A Grammar for Text Generation- -The Challenge ................................. 1 *1.2 A Grammar for Text Generation--The Design
An eminent scholar explains the essentials of English grammar to those who never studied the basics as well as those who need a refresher course. Inspired by Strunk & White's classic The Elements of Style, this user-friendly guide focuses exclusively on grammar, explaining the individual parts of speech and their proper arrangement in sentence form. A modest investment of 90 minutes can provide readers of all ages with simple but important tools that will improve their communication skills. Dover (2011) original publication.
Dougherty, Ray C
This book's main goal is to show readers how to use the linguistic theory of Noam Chomsky, called Universal Grammar, to represent English, French, and German on a computer using the Prolog computer language. In so doing, it presents a follow-the-dots approach to natural language processing, linguistic theory, artificial intelligence, and expert systems. The basic idea is to introduce meaningful answers to significant problems involved in representing human language data on a computer. The book offers a hands-on approach to anyone who wishes to gain a perspective on natural language
We all use language in different ways, depending on the situations we find ourselves in. In formal contexts we are usually expected to use a formal level of Standard English-the English codified in grammars, usage guides, and dictionaries. In May I Quote You on That? Stephen Spector offers a new approach to learning Standard English grammar and usage. The product of Spector's forty years of teaching courses on the English language, this book makes the conventions of formal writing and speech easier and more enjoyable to learn than traditional approaches usually do. Each lesson begins with humo
Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu
A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.
Fatekurohman, Mohamat; Nurmala, Nita; Anggraeni, Dian
Lungs are the most important organ, in the case of respiratory system. Problems related to disorder of the lungs are various, i.e. pneumonia, emphysema, tuberculosis and lung cancer. Comparing all those problems, lung cancer is the most harmful. Considering about that, the aim of this research applies survival analysis and factors affecting the endurance of the lung cancer patient using comparison of exact, Efron and Breslow parameter approach method on hazard ratio and stratified cox regression model. The data applied are based on the medical records of lung cancer patients in Jember Paru-paru hospital on 2016, east java, Indonesia. The factors affecting the endurance of the lung cancer patients can be classified into several criteria, i.e. sex, age, hemoglobin, leukocytes, erythrocytes, sedimentation rate of blood, therapy status, general condition, body weight. The result shows that exact method of stratified cox regression model is better than other. On the other hand, the endurance of the patients is affected by their age and the general conditions.
Hwu, Fenfang; Sun, Shuyan
The present study investigates the interaction between two types of explicit instructional approaches, deduction and explicit-induction, and the level of foreign language aptitude in the learning of grammar rules. Results indicate that on the whole the two equally explicit instructional approaches did not differentially affect learning…
Full Text Available Abstract Background It is quite common that the genetic architecture of complex traits involves many genes and their interactions. Therefore, dealing with multiple unlinked genomic regions simultaneously is desirable. Results In this paper we develop a regression-based approach to assess the interactions of haplotypes that belong to different unlinked regions, and we use score statistics to test the null hypothesis of non-genetic association. Additionally, multiple marker combinations at each unlinked region are considered. The multiple tests are settled via the minP approach. The P value of the "best" multi-region multi-marker configuration is corrected via Monte-Carlo simulations. Through simulation studies, we assess the performance of the proposed approach and demonstrate its validity and power in testing for haplotype interaction association. Conclusion Our simulations showed that, for binary trait without covariates, our proposed methods prove to be equal and even more powerful than htr and hapcc which are part of the FAMHAP program. Additionally, our model can be applied to a wider variety of traits and allow adjustment for other covariates. To test the validity, our methods are applied to analyze the association between four unlinked candidate genes and pig meat quality.
Full Text Available Purpose. The purpose of this paper is to study a class of the natural languages called the lattice-valued phrase structure languages, which can be generated by the lattice-valued type 0 grammars and recognized by the lattice-valued Turing machines. Design/Methodology/Approach. From the characteristic of natural language, this paper puts forward a new concept of the l-valued Turing machine. It can be used to characterize recognition, natural language processing, and dynamic characteristics. Findings. The mechanisms of both the generation of grammars for the lattice-valued type 0 grammar and the dynamic transformation of the lattice-valued Turing machines were given. Originality/Value. This paper gives a new approach to study a class of natural languages by using lattice-valued logic theory.
The grammar written in Latin, in 1668, by the Jesuit missionary Father Diego Luis de Sanvitores (1627-1672) is the oldest description we have of Chamorro, a language spoken on the Mariana islands. The grammar received a number of bad reviews and as a consequence has become neglected and almost
Watson, Annabel Mary
This paper reports on an investigation of L1 English teachers' conceptual and evaluative beliefs about teaching grammar, one strand of a larger Economic and Social Research Council (ESRC)-funded investigation into the impact of contextualised grammar teaching [RES-062-23-0775]. Thirty-one teachers in English secondary schools were interviewed…
Full Text Available the relationship more accurately in terms of MSE, RMSE and MAE, than a standard parametric approach (multiple linear regression). These results provide a platform for using the developed nonparametric regression model based on in situ measurements to predict p...
Štefančínová, Iveta; Valovičová, Ä½ubomíra
Content and Language Integrated Learning (CLIL) is one of the most outstanding approaches in foreign language teaching. This teaching method has promising prospects for the future of modern education as teaching subject and foreign languages are combined to offer a better preparation for life in Europe, especially when the mobility is becoming a highly significant factor of everyday life. We realized a project called Foreign languages in popularizing science at grammar school. Within the project five teachers with approbation subjects of English, French, German and Physics attended the methodological courses abroad. The teachers applied the gained experience in teaching and linking science teaching with the teaching of foreign languages. Outputs of the project (e.g. English-German-French-Slovak glossary of natural science terminology, student activity sheets, videos with natural science orientation in a foreign language, physical experiments in foreign languages, multimedia fairy tales with natural contents, posters of some scientists) are prepared for the CLIL-oriented lessons. We collected data of the questionnaire for students concerning attitude towards CLIL. The questionnaire for teachers showed data about the attitude, experience, and needs of teachers employing CLIL in their lessons.
Kate Rohit J
Full Text Available Abstract Background Clinical reports are written using a subset of natural language while employing many domain-specific terms; such a language is also known as a sublanguage for a scientific or a technical domain. Different genres of clinical reports use different sublaguages, and in addition, different medical facilities use different medical language conventions. This makes supervised training of a parser for clinical sentences very difficult as it would require expensive annotation effort to adapt to every type of clinical text. Methods In this paper, we present an unsupervised method which automatically induces a grammar and a parser for the sublanguage of a given genre of clinical reports from a corpus with no annotations. In order to capture sentence structures specific to clinical domains, the grammar is induced in terms of semantic classes of clinical terms in addition to part-of-speech tags. Our method induces grammar by minimizing the combined encoding cost of the grammar and the corresponding sentence derivations. The probabilities for the productions of the induced grammar are then learned from the unannotated corpus using an instance of the expectation-maximization algorithm. Results Our experiments show that the induced grammar is able to parse novel sentences. Using a dataset of discharge summary sentences with no annotations, our method obtains 60.5% F-measure for parse-bracketing on sentences of maximum length 10. By varying a parameter, the method can induce a range of grammars, from very specific to very general, and obtains the best performance in between the two extremes.
Koh, T S; Wu, X Y; Cheong, L H; Lim, C C T
The assessment of tissue perfusion by dynamic contrast-enhanced (DCE) imaging involves a deconvolution process. For analysis of DCE imaging data, we implemented a regression approach to select appropriate regularization parameters for deconvolution using the standard and generalized singular value decomposition methods. Monte Carlo simulation experiments were carried out to study the performance and to compare with other existing methods used for deconvolution analysis of DCE imaging data. The present approach is found to be robust and reliable at the levels of noise commonly encountered in DCE imaging, and for different models of the underlying tissue vasculature. The advantages of the present method, as compared with previous methods, include its efficiency of computation, ability to achieve adequate regularization to reproduce less noisy solutions, and that it does not require prior knowledge of the noise condition. The proposed method is applied on actual patient study cases with brain tumors and ischemic stroke, to illustrate its applicability as a clinical tool for diagnosis and assessment of treatment response.
Camilo Andrés Bonilla Carvajal
Full Text Available The Grammar-Translation method is frequently referred to as the traditional ineffective approach par excellence. Such view is often justified by the claim that before the Audiolingual method oral performance in foreign language was not reached, and language classes were reduced to memorizing grammar rules and lists of vocabulary. Nevertheless, this opinion is derived from unproved claims, mainly made by misinformed authors for they offer no compelling empirical evidence to validate their restrictive descriptions where translation is shown as an invalid metacognitive strategy. The aim of this paper is to demonstrate that Grammar-Translation is merely an arbitrary historic label, developed by methodologists and theoreticians to encompass the history of language teaching from 1790 through 1950. References to Grammar-Translation are critically reviewed to make evident they are biased inferences based on partial evidence to account for the existence of any such methodology. The assumption that Grammar-Translation did exist, and that it is the negative model of teaching practices that should be better avoided at all costs, might reflect an unconstructive and unfounded ideological interest of mainstream theoreticians and unsuspecting teachers.
Hossein Nassaji; Sandra Fotos
@@ With the rise of communicative methodology in the late 1970s, the role of grammar instruction in second language learning was downplayed, and it was even suggested that teaching grammar was not only unhelpful but might actually be detrimental.
Listening and grammar are the most difficult subjects for both teacher and students. This passage discussed how to visual aid and brain storming in the listening class;and the importance of confidence in the grammar teaching and learning.
Baydaroğlu, Özlem; Koçak, Kasım; Duran, Kemal
Prediction of water amount that will enter the reservoirs in the following month is of vital importance especially for semi-arid countries like Turkey. Climate projections emphasize that water scarcity will be one of the serious problems in the future. This study presents a methodology for predicting river flow for the subsequent month based on the time series of observed monthly river flow with hybrid models of support vector regression (SVR). Monthly river flow over the period 1940-2012 observed for the Kızılırmak River in Turkey has been used for training the method, which then has been applied for predictions over a period of 3 years. SVR is a specific implementation of support vector machines (SVMs), which transforms the observed input data time series into a high-dimensional feature space (input matrix) by way of a kernel function and performs a linear regression in this space. SVR requires a special input matrix. The input matrix was produced by wavelet transforms (WT), singular spectrum analysis (SSA), and a chaotic approach (CA) applied to the input time series. WT convolutes the original time series into a series of wavelets, and SSA decomposes the time series into a trend, an oscillatory and a noise component by singular value decomposition. CA uses a phase space formed by trajectories, which represent the dynamics producing the time series. These three methods for producing the input matrix for the SVR proved successful, while the SVR-WT combination resulted in the highest coefficient of determination and the lowest mean absolute error.
Full Text Available Abstract Background HPV infection is a worldwide problem strictly linked to the development of cervical cancer. Persistence of the infection is one of the main factors responsible for the invasive progression and women diagnosed with intraepithelial squamous lesions are referred for further assessment and surgical treatments which are prone to complications. Despite this, there are several reports on the spontaneous regression of the infection. This study was carried out to evaluate the effectiveness of a long term polyhexamethylene biguanide (PHMB-based local treatment in improving the viral clearance, reducing the time exposure to the infection and avoiding the complications associated with the invasive treatments currently available. Method 100 women diagnosed with HPV infection were randomly assigned to receive six months of treatment with a PHMB-based gynecological solution (Monogin®, Lo.Li. Pharma, Rome - Italy or to remain untreated for the same period of time. Results A greater number of patients, who received the treatment were cleared of the infection at the two time points of the study (three and six months compared to that of the control group. A significant difference in the regression rate (90% Monogin group vs 70% control group was observed at the end of the study highlighting the time-dependent ability of PHMB to interact with the infection progression. Conclusions The topic treatment with PHMB is a preliminary safe and promising approach for patients with detected HPV infection increasing the chance of clearance and avoiding the use of invasive treatments when not strictly necessary. Trial registration ClinicalTrials.gov Identifier NCT01571141
English has an important position in the basic education stage as a language subject. English teaching requires students to have the abilities of listening, speaking, reading and writing in high school. If students want to learn these skills well, they should not only memorize vocabularies, but also master grammar knowledge. This paper illustrates the importance of English grammar for learning English and lists the common grammar mistakes. It also introduces some skills of learning English grammar.
50 years has seen Systemic-Functional Grammar(SFG)growing into its prosperity. With the efforts of Halliday and many other linguists, SFG has developed from Scale and Category Grammar to Systemic Grammar and then to Functional Gram-mar. The development of this general linguistic theory’s features and framework is the main focus of this study. SFG views lan-guage as a social semiotic resource people use to express meanings in context.
Constraints are an important notion in grammars and language analysis, and constraint programming techniques have been developed concurrently for solving a variety of complex problems. In this chapter we consider the synthesis of these branches into practical and effective methods for language...... methods that combine constraints with logic grammars such as Definite Clause Grammars and CHR Grammars, and show also a direct relationship to abductive reasoning....
Grammar based framework has been introduced allowing the production of binding site descriptors for analysis of protein sequences. Experiments have shown that not only is this new approach valid, but produces human-readable descriptors for binding sites which have been beyond the capability of current machine learning techniques.
Ibrahim, Mohamed S.; Bridges, Alan; Chase, Scott Curland
This paper describes a teaching experience conducted and carried out as part of the coursework of first year students. The workshop is the third of three workshops planned to take place during the course of the first year studio, aimed at introducing new ways of thinking and introducing students...... to a new pattern of architectural education. The experiment was planned under the theme of “Evaluation” during the final stage. A grammatical approach was chosen to deliver the methodology in the design studio, based on shape grammars....
Full Text Available The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The system controls dimming of street lights which is based on traffic intensity. Each luminaire’s light level is adjusted individually to comply with the lighting norms to ensure safety. Benefits of applying the dual graph grammar are twofold. First, it increases expressive power of the mathematical model that the system uses. It becomes possible to take into account complex geographical distribution of sensors and logical dependencies among them. Second, it increases the system’s efficiency by reducing the problem size during run-time. Experimental results show a reduction of the computation time by a factor of 2.8. The approach has been verified in practice.
Johnson, S B
There are a wide variety of computer applications that deal with various aspects of medical language: concept representation, controlled vocabulary, natural language processing, and information retrieval. While technical and theoretical methods appear to differ, all approaches investigate different aspects of the same phenomenon: medical sublanguage. This paper surveys the properties of medical sublanguage from a formal perspective, based on detailed analyses cited in the literature. A review of several computer systems based on sublanguage approaches shows some of the difficulties in addressing the interaction between the syntactic and semantic aspects of sublanguage. A formalism called Conceptual Graph Grammar is presented that attempts to combine both syntax and semantics into a single notation by extending standard Conceptual Graph notation. Examples from the domain of pathology diagnoses are provided to illustrate the use of this formalism in medical language analysis. The strengths and weaknesses of the approach are then considered. Conceptual Graph Grammar is an attempt to synthesize the common properties of different approaches to sublanguage into a single formalism, and to begin to define a common foundation for language-related research in medical informatics.
María Nayra Rodríguez Rodríguez
Full Text Available In the present article we intend to make a reflection on the introduction of target language literature in foreign language classrooms. We will analyze the use of short-short stories as a didactic resource in Spanish as Foreign Language classrooms. To this end, we will research different teaching methodologies that have been implemented and investigate the validity of this genre as a suitable material for teaching grammar. We will make an approximation to Focus on Form as an effective approach, which integrates grammar teaching within a communicative context.
Teaching Grammar, Structure and Meaning introduces teachers to some basic ideas from the increasingly popular field of cognitive linguistics as a way of explaining and teaching key grammatical concepts. Particularly suitable for those teaching post-16 English Language, this book offers a methodology for teaching key aspects of linguistic form and an extensive set of learning activities. Written by an experienced linguist and teacher, this book contains:· an evaluation of current approaches to the teaching of grammar and linguistic form· a revised pedagogy based on principles from cognitive sci
López Garrido, Ramon
The current teaching trend of ESL is focused on maximizing the use of the L2 so that the student learns the language through linguistic immersion. This approach leaves the L1 out of the game, even though research has shown it can also be beneficial for the learner. My research intends to demonstrate that translation of English grammar tenses into Spanish can be a helpful way of assimilating English grammar more easily and faster, especially for those students with a poor command of English. ...
Madsen, Ole Lehrmann; Kristensen, Bent Bruun
To improve the readability of a grammar it is common to use extended context free grammars (ECFGs) which are context free grammars (CFGs) extended with the repetition operator (*), the alternation operator (¦) and parentheses to express the right hand sides of the productions. The topic treated h...
Al-Mekhlafi, Abdu Mohammed; Nagaratnam, Ramani Perur
The role of grammar instruction in an ESL/EFL context has been for decades a major issue for students and teachers alike. Researchers have debated whether grammar should be taught in the classroom and students, for their part, have generally looked upon grammar instruction as a necessary evil at best, and an avoidable burden at worst. The paper…
Hansen, Maj-Britt Mosegaard
This book is an advanced student's grammar of French that integrates traditional grammar with knowledge and insights from modern linguistics. It assumes some prior knowledge of French grammar but is designed to be accessible to those with no background in linguistics.
Schwartz, Misha; Goad, Heather
This article proposes that second language learners can use indirect positive evidence (IPE) to acquire a phonological grammar that is a subset of their L1 grammar. IPE is evidence from errors in the learner's L1 made by native speakers of the learner's L2. It has been assumed that subset grammars may be acquired using direct or indirect negative…
The research examined the impact on teachers of the grammar element of a new statutory test in Spelling, Punctuation and Grammar (SPaG) in primary schools in England. The research aimed to evaluate the nature and the extent of changes to the teaching of grammar and to wider literacy teaching since the introduction of the test in 2013. The research…
This article addresses key issues and considerations for teachers wanting to incorporate spoken grammar activities into their own teaching and also focuses on six common features of spoken grammar, with practical activities and suggestions for teaching them in the language classroom. The hope is that this discussion of spoken grammar and its place…
Student projects that involve writing generative grammars in the computer language, "LOGO," are described in this paper, which presents a grammar-running control structure that allows students to modify and improve the grammar interpreter itself while learning how a simple kind of computer parser works. Included are procedures for…
R. Lämmel (Ralf); V. Zaytsev (Vadim)
textabstractGrammar convergence is a method that helps in discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for
Cohen, Andrew D.; Pinilla-Herrera, Angela; Thompson, Jonathan R.; Witzig, Lance E.
After a brief introduction to language learner strategies and grammar strategies as a subcategory, it is pointed out that research on the use of grammar strategies by learners of a second language (L2) has been limited. The article then describes the construction of a website with strategies for learning and performing Spanish grammar, with a…
Nijholt, Antinus; Gecsec, F.
It will be shown that the equivalence problem for LL-regular grammars is decidable. Apart from extending the known result for LL(k) grammar equivalence to LLregular grammar equivalence, we obtain an alternative proof of the decidability of LL(k) equivalence. The equivalence prob]em for LL-regular
Bransen, Jeroen; van Binsbergen, L.Thomas; Claessen, Koen; Dijkstra, Atze
Many computations over trees can be specified using attribute grammars. Compilers for attribute grammars need to find an evaluation order (or schedule) in order to generate efficient code. For the class of linearly ordered attribute grammars such a schedule can be found statically, but this problem
Zhang, Zibin; Cai, Wenxin; Feng, Xiangzhao
China is the largest electricity consumption country after it has passed the United States in 2011. Residential electricity consumption in China grew by 381.35% (12.85% per annum) between 2000 and 2013. In order to deal with rapid growth in residential electricity consumption, an increasing block pricing policy was introduced for residential electricity consumers in China on July 1st, 2012. Using difference-in-differences models with a fuzzy regression discontinuity design, we estimate a causal effect of price on electricity consumption for urban households during the introduction of increasing block pricing policy in Guangdong province of China. We find that consumers do not respond to a smaller (approximately 8%) increase in marginal price. However, consumers do respond to a larger increase in marginal price. An approximately 40% increase in marginal price induces an approximately 35% decrease in electricity use (284 kW h per month). Our results suggest that although the increasing block pricing could affect the behavior of households with higher electricity use, there is only a limit potential to overall energy conservation. - Highlights: • Estimate electricity consumption changes in response to the IBP in China. • Employ quasi-experimental approach and micro household level data in China. • Households do not respond to a smaller increase in marginal price. • 40% increase in marginal price induces a 35% decrease in electricity use.
Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.
In Chile, a new law introduced in March 2012 lowered the blood alcohol concentration (BAC) limit for impaired drivers from 0.1% to 0.08% and the BAC limit for driving under the influence of alcohol from 0.05% to 0.03%, but its effectiveness remains uncertain. The goal of this investigation was to evaluate the effects of this enactment on road traffic injuries and fatalities in Chile. A retrospective cohort study. Data were analyzed using a descriptive and a Generalized Linear Models approach, type of Poisson regression, to analyze deaths and injuries in a series of additive Log-Linear Models accounting for the effects of law implementation, month influence, a linear time trend and population exposure. A review of national databases in Chile was conducted from 2003 to 2014 to evaluate the monthly rates of traffic fatalities and injuries associated to alcohol and in total. It was observed a decrease by 28.1 percent in the monthly rate of traffic fatalities related to alcohol as compared to before the law (Plaw (Plaw implemented in 2012 in Chile. Chile experienced a significant reduction in alcohol-related traffic fatalities and injuries, being a successful public health intervention.
Yuehjen E. Shao
Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.
Siti Choirun Nisak
Full Text Available Time series forecasting models can be used to predict phenomena that occur in nature. Generalized Space Time Autoregressive (GSTAR is one of time series model used to forecast the data consisting the elements of time and space. This model is limited to the stationary and non-seasonal data. Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA is GSTAR development model that accommodates the non-stationary and seasonal data. Ordinary Least Squares (OLS is method used to estimate parameter of GSTARIMA model. Estimation parameter of GSTARIMA model using OLS will not produce efficiently estimator if there is an error correlation between spaces. Ordinary Least Square (OLS assumes the variance-covariance matrix has a constant error ~(, but in fact, the observatory spaces are correlated so that variance-covariance matrix of the error is not constant. Therefore, Seemingly Unrelated Regression (SUR approach is used to accommodate the weakness of the OLS. SUR assumption is ~(, for estimating parameters GSTARIMA model. The method to estimate parameter of SUR is Generalized Least Square (GLS. Applications GSTARIMA-SUR models for rainfall data in the region Malang obtained GSTARIMA models ((1(1,12,36,(0,(1-SUR with determination coefficient generated with the average of 57.726%.
A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (pdf) over such a shape space and to sample models according to the designed pdf. First, we propose a user interface that enables a user to quickly provide preference scores for selected shapes and suggest sampling strategies to decide which models to present to the user to evaluate. Second, we propose a novel kernel function to encode the similarity between two procedural models. Third, we propose a framework to interpolate user preference scores by combining multiple techniques: function factorization, Gaussian process regression, autorelevance detection, and l1 regularization. Fourth, we modify the original grammars to generate models with a pdf proportional to the user preference scores. Finally, we provide evaluations of our user interface and framework parameters and a comparison to other exploratory modeling techniques using modeling tasks in five example shape spaces: furniture, low-rise buildings, skyscrapers, airplanes, and vegetation.
Full Text Available In a recent paper (M. Barash, A. Okhotin, "Defining contexts in context-free grammars", LATA 2012, the authors introduced an extension of the context-free grammars equipped with an operator for referring to the left context of the substring being defined. This paper proposes a more general model, in which context specifications may be two-sided, that is, both the left and the right contexts can be specified by the corresponding operators. The paper gives the definitions and establishes the basic theory of such grammars, leading to a normal form and a parsing algorithm working in time O(n^4, where n is the length of the input string.
Full Text Available In his post-Tractatus work on natural language use, Wittgenstein defended the notion of what he dubbed the autonomy of grammar. According to this thought, grammar - or semantics, in a more recent idiom - is essentially autonomous from metaphysical considerations, and is not answerable to the nature of things. The argument has several related incarnations in Wittgenstein’s post-Tractatus writings, and has given rise to a number of important insights, both critical and constructive. In this paper I will argue for a potential connection between Wittgenstein’s autonomy argument and some more recent internalist arguments for the autonomy of semantics. My main motivation for establishing this connection comes from the fact that the later Wittgenstein’s comments on grammar and meaning stand in opposition to some of the core assumptions of semantic externalism.
Leng, Chin Hai; Siraj, Saedah; Asmawi, Adelina; Dewitt, Dorothy; Ranee, Alina
This study was aimed at developing a Bahasa Melayu grammar learning portal for Form Two students (BMGLP). A developmental approach was used in this study. Needs analysis was carried out on the Bahasa Melayu teachers and Form Two students. The results of needs analysis on Form Two students showed that they preferred topics such as question…
A Eurocentric approach was the only possible point of departure for those originally attempting to set out the grammatical structure of isiXhosa. Not being mother-tongue speakers, their commendable efforts were inevitably done from the perspective of the grammar of European languages such as Latin and English.
Brand, van den M.G.J.; Sellink, M.P.A.; Verhoef, C.
We present an approach for the generation of components for a software renovation factory. These components are generated from a contex-free grammar definition that recognizes the code that has to be renovated. We generate analysis and transformation components that can be instantiated with a
Fischer, Kerstin; Alm, Maria
between the contributions of lexical and grammatical constructions. In accordance with Croft’s (2001) Radical Construction Grammar approach, cross-linguistic comparison is then carried out on the basis of the conceptual space, which comprises the language specific sets of functions discourse and modal...
Greenyer, Joel; Kindler, Ekkart
and for model-based software engineering approaches in general. QVT (Query/View/Transformation) is the transformation technology recently proposed for this purpose by the OMG. TGGs (Triple Graph Grammars) are another transformation technology proposed in the mid-nineties, used for example in the FUJABA CASE...
Full Text Available The paper discusses authentic materials as a resource for teaching grammar to young learners. Difficulties in foreign-language grammar learning for Russian pupils are presented, and typical challenges are described. The paper provides a pre-/post-intervention study of the development of children’s grammar skills. The research question is, “How does one use authentic materials for teaching grammar in an English as a foreign language (EFL classroom?” A qualitative method is used to assess the learning outcomes of using authentic materials in teaching grammar to eight–nine-year-old pupils (the second year of studying English.
Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.
Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...
Romel M. Aceron
Full Text Available Teaching English advanced grammar and composition to college students is important as it provides them with high level of understanding and competence in the language. It guides them in putting words together into sentences and makes them orally produce sounds clearly and effectively. This paper aims to determine the attitudes and behavior towards advanced grammar and composition teaching among freshman college students of Batangas State University. Descriptive method of research has been used to analyze and interpret data. The following instruments such as self-made questionnaire, focus group discussion, data analysis, interview guide, have been utilized to gather data. To analyze and interpret data, mean scores have been used. Pearson’s (r Product Moment Correlation Method has been utilized to treat the null hypothesis with regard to the attitudes and behavior of the students towards advanced grammar and composition teaching. Based on the findings of the study, the students sometimes understand and feel the subject matters, i.e., morphology, phonology, grammar and usage, and mechanics and composition writing. They are also sometimes ready in particular lesson and activity which are given to them in class. The study also reveals that there is no significant relationship between the students’ attitudes and behavior towards AGCT. In this regard, college students taking advanced grammar and composition course must be well-motivated to understand, and must have the readiness to perform the activities entail in the subject areas of morphology, phonology, grammar and usage, and mechanics and composition writing through teacher’s varied approaches, strategies, researches, and integration.
Kumar, V.; Melet, A.; Meyssignac, B.; Ganachaud, A.; Kessler, W. S.; Singh, A.; Aucan, J.
Rising sea levels are a critical concern in small island nations. The problem is especially serious in the western south Pacific, where the total sea level rise over the last 60 years has been up to 3 times the global average. In this study, we aim at reconstructing sea levels at selected sites in the region (Suva, Lautoka—Fiji, and Nouméa—New Caledonia) as a multilinear regression (MLR) of atmospheric and oceanic variables. We focus on sea level variability at interannual-to-interdecadal time scales, and trend over the 1988-2014 period. Local sea levels are first expressed as a sum of steric and mass changes. Then a dynamical approach is used based on wind stress curl as a proxy for the thermosteric component, as wind stress curl anomalies can modulate the thermocline depth and resultant sea levels via Rossby wave propagation. Statistically significant predictors among wind stress curl, halosteric sea level, zonal/meridional wind stress components, and sea surface temperature are used to construct a MLR model simulating local sea levels. Although we are focusing on the local scale, the global mean sea level needs to be adjusted for. Our reconstructions provide insights on key drivers of sea level variability at the selected sites, showing that while local dynamics and the global signal modulate sea level to a given extent, most of the variance is driven by regional factors. On average, the MLR model is able to reproduce 82% of the variance in island sea level, and could be used to derive local sea level projections via downscaling of climate models.
WONG Fai; DONG Mingchui; HU Dongcheng
A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars,the grammar allows multiple target productions to be associated to a single production rule which can be used to guide a parser to infer different possible translational equivalences for a recognized input string according to the feature constraints of symbols in the pattern. An extended generalized LR algorithm was adapted to the parsing of the proposed formalism to analyze the syntactic structure of a language. The grammar was used as the basis for building a machine translation system for Portuguese to Chinese translation. The empirical results show that the grammar is more expressive when modeling the translational equivalences of parallel texts for machine translation and grammar rewriting applications.
Li, L.; Yang, C.
Climate extremes often manifest as rare events in terms of surface air temperature and precipitation with an annual reoccurrence period. In order to represent the manifold characteristics of climate extremes for monitoring and analysis, the Expert Team on Climate Change Detection and Indices (ETCCDI) had worked out a set of 27 core indices based on daily temperature and precipitation data, describing extreme weather and climate events on an annual basis. The CLIMDEX project (http://www.climdex.org) had produced public domain datasets of such indices for data from a variety of sources, including output from global climate models (GCM) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Among the 27 ETCCDI indices, there are six percentile-based temperature extremes indices that may fall into two groups: exceedance rates (ER) (TN10p, TN90p, TX10p and TX90p) and durations (CSDI and WSDI). Percentiles must be estimated prior to the calculation of the indices, and could more or less be biased by the adopted algorithm. Such biases will in turn be propagated to the final results of indices. The CLIMDEX used an empirical quantile estimator combined with a bootstrap resampling procedure to reduce the inhomogeneity in the annual series of the ER indices. However, there are still some problems remained in the CLIMDEX datasets, namely the overestimated climate variability due to unaccounted autocorrelation in the daily temperature data, seasonally varying biases and inconsistency between algorithms applied to the ER indices and to the duration indices. We now present new results of the six indices through a semiparametric quantile regression approach for the CMIP5 model output. By using the base-period data as a whole and taking seasonality and autocorrelation into account, this approach successfully addressed the aforementioned issues and came out with consistent results. The new datasets cover the historical and three projected (RCP2.6, RCP4.5 and RCP
Full Text Available Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature, quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.
van Rijn, M.
Although the term is alignment is typically associated with morphosyntactic expression of arguments of the Clause, alignment is also relevant to units of the Phrase. In Functional Discourse Grammar a basic distinction is made between two kinds of dependency relations obtaining both within Phrases
Madsen, Ole Lehrmann
Knuth has introduced attribute grammars (AGs) as a tool to define the semanitcs of context-free languages. The use of AGs in connection with programming language definitions has mostly been to define the context-sensitive syntax of the language and to define a translation in code for a hypothetic...
Dassow, J.; Masopust, Tomáš
Roč. 78, č. 1 (2012), s. 293-304 ISSN 0022-0000 Institutional research plan: CEZ:AV0Z10190503 Keywords : context-free grammars * derivation restriction * normal forms Subject RIV: BA - General Mathematics Impact factor: 1.000, year: 2012 http://www.sciencedirect.com/science/article/pii/S0022000011000572
Stevens, Alan M.
This paper presents evidence from Philippine languages which suggests a number of modifications in the theory of case grammar. Philippine languages and adjacent related languages mark the case relationship between the verb and one noun phrase in the sentence by a particle on the noun phrase and an affix on the verb, a phenomenon which in recent…
Originally an editorial for "English in Education," this short article summarises key issues in the imposition of a separate test for grammar, punctuation and spelling. It illustrates the poor foundations, lack of clarity and distortion of curriculum which invalidate the test.
GUMPERZ, JOHN J.; MISRA, VIDYA NIWAS
THIS BRIEF OUTLINE OF HINDI PHONOLOGY AND GRAMMAR IS INTENDED FOR FIRST AND SECOND YEAR STUDENTS OF HINDI WHO HAVE SOME PREVIOUS KNOWLEDGE OF THE ORAL AND WRITTEN LANGUAGE BUT WHO MAY HAVE HAD NO PREVIOUS TRAINING IN LINGUISTIC TERMINOLOGY. THE AUTHORS HAVE THEREFORE EMPHASIZED SIMPLICITY AND READABILITY RATHER THAN EXHAUSTIVENESS OR ORIGINALITY…
Szymczak, Bartlomiej Antoni
Categorial Grammar is a well established tool for describing natural language semantics. In the current paper we discuss some of its drawbacks and how it could be extended to overcome them. We use the extended version for deriving ontological semantics from text. A proof-of-concept implementation...
Thomas, Earl W.
This is a first-year text of Portuguese grammar based on the Portuguese of moderately educated Brazilians from the area around Rio de Janeiro. Spoken idiomatic usage is emphasized. An important innovation is found in the presentation of verb tenses; they are presented in the order in which the native speaker learns them. The text is intended to…
This grammar is a self-study manual intended to aid native speakers of English who are beginning the study of French. It is designed to supplement the French textbook, not to replace it. The common grammatical terms that are necessary for learning to speak and write French are explained in English and illustrated by examples in both French and…
Smoly, Ilan; Carmel, Amir; Shemer-Avni, Yonat; Yeger-Lotem, Esti; Ziv-Ukelson, Michal
Network querying is a powerful approach to mine molecular interaction networks. Most state-of-the-art network querying tools either confine the search to a prespecified topology in the form of some template subnetwork, or do not specify any topological constraints at all. Another approach is grammar-based queries, which are more flexible and expressive as they allow for expressing the topology of the sought pattern according to some grammar-based logic. Previous grammar-based network querying tools were confined to the identification of paths. In this article, we extend the patterns identified by grammar-based query approaches from paths to trees. For this, we adopt a higher order query descriptor in the form of a regular tree grammar (RTG). We introduce a novel problem and propose an algorithm to search a given graph for the k highest scoring subgraphs matching a tree accepted by an RTG. Our algorithm is based on the combination of dynamic programming with color coding, and includes an extension of previous k-best parsing optimization approaches to avoid isomorphic trees in the output. We implement the new algorithm and exemplify its application to mining viral infection patterns within molecular interaction networks. Our code is available online.
Becvar, J.; Nijholt, Antinus; Soisalon-Soininen, E.
In this paper we introduce the class of so called Ch(k) grammars [pronounced "chain k grammars"]. This class of grammars is properly contained in the class of LR(k) grammars and it properly contains the LL(k) grammars. However, the family of Ch[k) languages coincides with the family of LL(k)
Full Text Available My paper addresses a problem many of us in North American college language programs confront regularly, the solution to which regularly and frustratingly remains just out of our reach. I refer to the teaching of the most basic and most crucial element of Russian grammar, namely, its case system, and teaching it to our students whose native language, English, does not have such a system. As I teach the Russian cases, I see vividly the disconnect between grammar presented for students (simplified, episodic, based on the "pick it up along the way" principle and the learned papers on Russian grammar by linguists, which are barely comprehensible to a non-linguist. Materials in the middle are lacking-materials to help a literature professor acting as a "de facto" language instructor understand and address the needs of students as they learn this crucial segment of basic Russian grammar. This core element of Russian grammar is presented to students in the first year of college language study, is revisited in the second year, and very often by the third year students either manage to completely block it out from their memory (as if it were some traumatic experience that happened "a long time ago"-that is, before .summer break-but most importantly due to the lack of practice or demonstrate a partial or even complete lack of understanding or misunderstanding of this system forcing us to deal with it again in the third year. Not only is it frustrating for both the students and the language instructor; but from the point of view of their overall proficiency, the lack of control of the case system holds our students back. There can be no talk of advanced language proficiency without a complete and automatic mastery of this basic system. Unfortunately, regardless of the specific textbooks used, the students very often manage not to have a general idea and mastery of this system even by the third year of study.
Full Text Available Maps are the foundation of indoor location-based services. Many automatic indoor mapping approaches have been proposed, but they rely highly on sensor data, such as point clouds and users’ location traces. To address this issue, this paper presents a conceptual framework to represent the layout principle of research buildings by using grammars. This framework can benefit the indoor mapping process by improving the accuracy of generated maps and by dramatically reducing the volume of the sensor data required by traditional reconstruction approaches. In addition, we try to present more details of partial core modules of the framework. An example using the proposed framework is given to show the generation process of a semantic map. This framework is part of an ongoing research for the development of an approach for reconstructing semantic maps.
Hu, X.; Fan, H.; Zipf, A.; Shang, J.; Gu, F.
Maps are the foundation of indoor location-based services. Many automatic indoor mapping approaches have been proposed, but they rely highly on sensor data, such as point clouds and users' location traces. To address this issue, this paper presents a conceptual framework to represent the layout principle of research buildings by using grammars. This framework can benefit the indoor mapping process by improving the accuracy of generated maps and by dramatically reducing the volume of the sensor data required by traditional reconstruction approaches. In addition, we try to present more details of partial core modules of the framework. An example using the proposed framework is given to show the generation process of a semantic map. This framework is part of an ongoing research for the development of an approach for reconstructing semantic maps.
Cole, Peter; Hermon, Gabriella; Yanti
Languages around the world often appear to manifest nearly identical grammatical properties, but, at the same time, the grammatical differences can also be great, sometimes even seeming to support Joos's (1958) claim that "languages can differ from each other without limit and in unpredictable way" (p. 96). This state of affairs provides a puzzle for both nativist approaches to language like Generative Grammar that posit a fixed "Universal Grammar", and for approaches that minimize the contribution of innate grammatical structure. We approach this puzzling state of affairs by looking at one area of grammar, "Binding", the system of local and long distance anaphoric elements in a language. This is an area of grammar that has long been central to the Generative approach to language structure. We compare the anaphoric systems found in "familiar" (European-like) languages that contain dedicated classes of bound and free anaphors (pronouns and reflexives) with the anaphoric systems in endangered Austronesian languages of Indonesia, languages in which there is overlap or no distinction between pronouns and reflexives (Peranakan Javanese and Jambi Malay). What is of special interest about Jambi anaphora is not only that conservative dialects of Jambi Malay do not distinguish between pronouns and reflexives, but that Jambi anaphora appear to constitute a live snapshot of a unitary class of anaphora in the process of grammaticalization as a distinct system of pronouns and reflexives. We argue that the facts of Jambi anaphora cannot be explained by theories positing a Universal Grammar of Binding. Thus, these facts provide evidence that complex grammatical systems like Binding cannot be innate. Our results from Austronesian languages are confirmed by data from signed and creole languages. Our conclusion is that the human language learning capacity must include the ability to model the full complexity found in the syntax of the world's languages. From the perspective of child
Moyer, Douglas; Hirsch, Robert M.; Hyer, Kenneth
Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent
Hallquist, Michael N; Hwang, Kai; Luna, Beatriz
Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n=117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r=.10-.35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability. Copyright © 2013 Elsevier Inc. All rights reserved.
Almodad Biduk Asmani
Full Text Available The purpose of the research project is to find out how effective grammar teaching and learning using the Principled CLT method can improve the ability of freshman Binus University students to understand and use grammar knowledge for academic writing purposes. The research project is expected to result in computer-animated format which can be used as one of the main tools in teaching and learning grammar at tertiary level. The research project applies the descriptive quantitative approach, and thus uses numeric data. The research project involves two subject groups, which are experimental and control. The two groups are pre-tested so as to find out their level of grammar competency by their academic writing works. The experimental group receives the treatment of grammar learning by using the Principled CLT approach, while the control group receives the standard CLT approach. Then, the two groups have the post-test, and the results are compared. Through statistics, the numerical data show that there is no significant difference between the two methods’ results, and as a result, either method has its own strength and weaknesses. If one is to be implemented, it must be linked to the specific goals and purposes that each entails.
Mayr, Nina A.; Wang, Jian Z.; Lo, Simon S.; Zhang Dongqing; Grecula, John C.; Lu Lanchun; Montebello, Joseph F.; Fowler, Jeffrey M.; Yuh, William T.C.
Purpose: To assess individual volumetric tumor regression pattern in cervical cancer during therapy using serial four-dimensional MRI and to define the regression parameters' prognostic value validated with local control and survival correlation. Methods and Materials: One hundred and fifteen patients with Stage IB 2 -IVA cervical cancer treated with radiation therapy (RT) underwent serial MRI before (MRI 1) and during RT, at 2-2.5 weeks (MRI 2, at 20-25 Gy), and at 4-5 weeks (MRI 3, at 40-50 Gy). Eighty patients had a fourth MRI 1-2 months post-RT. Mean follow-up was 5.3 years. Tumor volume was measured by MRI-based three-dimensional volumetry, and plotted as dose(time)/volume regression curves. Volume regression parameters were correlated with local control, disease-specific, and overall survival. Results: Residual tumor volume, slope, and area under the regression curve correlated significantly with local control and survival. Residual volumes ≥20% at 40-50 Gy were independently associated with inferior 5-year local control (53% vs. 97%, p <0.001) and disease-specific survival rates (50% vs. 72%, p = 0.009) than smaller volumes. Patients with post-RT residual volumes ≥10% had 0% local control and 17% disease-specific survival, compared with 91% and 72% for <10% volume (p <0.001). Conclusion: Using more accurate four-dimensional volumetric regression analysis, tumor response can now be directly translated into individual patients' outcome for clinical application. Our results define two temporal thresholds critically influencing local control and survival. In patients with ≥20% residual volume at 40-50 Gy and ≥10% post-RT, the risk for local failure and death are so high that aggressive intervention may be warranted.
Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo
We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...
Hansen, Aslak Hedemann
The development in the consumption of fruit and vegetables in the period 1999-2004 in Denmark was investigated using quantile regression and two previously overlooked problems were identified. First, the change in the ten percent quantile samples decreased. This could have been caused by changes ...
Van Der Meer, D.; Hoekstra, P. J.; Van Donkelaar, M.; Bralten, J.; Oosterlaan, J.; Heslenfeld, D.; Faraone, S. V.; Franke, B.; Buitelaar, J. K.; Hartman, C. A.
Identifying genetic variants contributing to attention-deficit/hyperactivity disorder (ADHD) is complicated by the involvement of numerous common genetic variants with small effects, interacting with each other as well as with environmental factors, such as stress exposure. Random forest regression
Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.
A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…
van der Meer, D.; Hoekstra, P. J.; van Donkelaar, Marjolein M. J.; Bralten, Janita; Oosterlaan, J; Heslenfeld, Dirk J.; Faraone, S. V.; Franke, B.; Buitelaar, J. K.; Hartman, C. A.
Identifying genetic variants contributing to attention-deficit/hyperactivity disorder (ADHD) is complicated by the involvement of numerous common genetic variants with small effects, interacting with each other as well as with environmental factors, such as stress exposure. Random forest regression
Non-linear regression techniques are used widely to fit weed field emergence patterns to soil microclimatic indices using S-type functions. Artificial neural networks present interesting and alternative features for such modeling purposes. In this work, a univariate hydrothermal-time based Weibull m...
Yousufzai, M.A.K; Aansari, M.R.K.; Quamar, J.; Iqbal, J.; Hussain, M.A.
This communication presents the development of a comprehensive characterization of ozone layer depletion (OLD) phenomenon as a physical process in the form of mathematical models that comprise the usual regression, multiple or polynomial regression and stochastic strategy. The relevance of these models has been illuminated using predicted values of different parameters under a changing environment. The information obtained from such analysis can be employed to alter the possible factors and variables to achieve optimum performance. This kind of analysis initiates a study towards formulating the phenomenon of OLD as a physical process with special reference to the stratospheric region of Pakistan. The data presented here establishes that the Auto regressive (AR) nature of modeling OLD as a physical process is an appropriate scenario rather than using usual regression. The data reported in literature suggest quantitatively the OLD is occurring in our region. For this purpose we have modeled this phenomenon using the data recorded at the Geophysical Centre Quetta during the period 1960-1999. The predictions made by this analysis are useful for public, private and other relevant organizations. (author)
Fitzenberger, Bernd; Wilke, Ralf Andreas
if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...
De Silva, Anthony Mihirana
This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...
T. Nadana Ravishankar
Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.
Jensen, Kim Ebensgaard
While formalist approaches in the Chomskian tradition to language distinguish sharply between performance and competence in their modeling of language competence, performance and competence are considered to be in a mutually influential relation in usage-based models of language. Language...... competence, in the latter approach, is, much like in Dell Hymes’ notion of communicative competence, held to be experientially based in the sense that speakers establish their competence through inductive social-cognitive processes of schematization and conventionalization. Making a case for the usage......-based definition of the language system, his paper explores the interplay between performance and competence in a construction grammar perspective in which grammatical constructions are considered meaningful symbolic units on par with lexemes, in relation to the [V until ADJ]-construction, based on a study...
Full Text Available Information Extraction (IE is a natural language processing (NLP task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%.
Kolodny, Oren; Lotem, Arnon; Edelman, Shimon
We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this manner takes the form of a directed weighted graph, whose nodes are recursively (hierarchically) defined patterns over the elements of the input stream. We evaluated the model in seventeen experiments, grouped into five studies, which examined, respectively, (a) the generative ability of grammar learned from a corpus of natural language, (b) the characteristics of the learned representation, (c) sequence segmentation and chunking, (d) artificial grammar learning, and (e) certain types of structure dependence. The model's performance largely vindicates our design choices, suggesting that progress in modeling language acquisition can be made on a broad front-ranging from issues of generativity to the replication of human experimental findings-by bringing biological and computational considerations, as well as lessons from prior efforts, to bear on the modeling approach. Copyright © 2014 Cognitive Science Society, Inc.
Yu, Q.; Helmholz, P.; Belton, D.; West, G.
The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.
Aliana Lopes CÂMARA
Full Text Available This paper studies how the textbooks of Portuguese Language of Secondary School, approved by the Programa Nacional do Livro Didático-2014, approach the teaching of grammar, in particular as regards the treatment of the relative subordinate clause. For this, first we start with the comparison between the proposals manuals for teaching grammar and what was accomplished in the student book. Furthermore, we propose here an interface between the results of the analysis of textbooks and functional description of the relative clause. In other words, we try to verify as some descriptive aspects can be used in the teaching of relative clause, with the aim of developing reading and writing skills. In order to do that, we take as theoretical framework the different conceptions of grammar proposed in Travaglia (2009, 2011 and Functional Discourse Grammar (HENGEVELD; MACKENZIE, 2008. This research points to the need to emphasize the cohesive role established by the relative pronoun that introduces the relative clause, to understand the non-restrictive relative clause from its argumentative function and to review the distinction between subtypes of adjective clause from the criteria of omission of the subordinate clause.
Grammar is the guiding rules of language, and a good mastery of grammar is the basis of English learning. This paper starts from the problems in college students' current grammar learning and put forwards some strategies to improve their English grammar.
34 76b, Hudson 76, Halliday 81, de Joia 80, Fawcett 80].3 1.2. Design Goals for the Grammar Three kinds of goals have guided the work of creating Nigel...Davey 79] Davey, A., Discourse Production, Edinburgh University Press, Edinburgh, 1979. [ de Joia 80] de Joia , A., and A. Stenton, Terms in Systemic...1 1.1. The Text Generation Task as a Stimulus for Grammar Design .........................1I -1.2. Design Goals for the Grammar
Engels, G; Kreowski, H J; Rozenberg, G
Graph grammars originated in the late 60s, motivated by considerations about pattern recognition and compiler construction. Since then, the list of areas which have interacted with the development of graph grammars has grown quite impressively. Besides the aforementioned areas, it includes software specification and development, VLSI layout schemes, database design, modeling of concurrent systems, massively parallel computer architectures, logic programming, computer animation, developmental biology, music composition, visual languages, and many others.The area of graph grammars and graph tran
Madonna, Erica; Ginsbourger, David; Martius, Olivia
In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.
Matson, Johnny L.; Kozlowski, Alison M.
Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…
The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).
This paper aims to analyze the interaction between prefixes, verbs, and abstract argument structure constructions, using as a testing ground the locative alternation. It has been assumed that in order to participate in the locative alternation, a verb must specify a manner of motion from which a ...... between resultative prefixes, alternating verbs, and the more abstract change-of-state variant is driven by semantic coherence. Keywords: resultative prefixes, construction grammar, semantic coherence, locative alternation, Polish...
Lithuanian language is quite in an early stage of language processing. And therefore has a high demand on automated tools like taggers, parsers, word sense disambiguators etc. During the last 10 years only a few researchers were attempting to create a parser for Lithuanian language. However none of them are used in practices nowadays. The process of designing and implementing rule based parser for Lithuanian language is presented in this paper. Rules and constraints of the formal grammar foll...
Full Text Available In this paper we present an experimental functional realization of attribute grammar(AG system for personal computers. For AG system functioning only Turbo Prolog compiler is required. The system functioning is based on a specially elaborated metalanguage for AG description, universal syntactic and semantic constructors. The AG system provides automatic generation of target compiler (syntax--oriented software using Turbo Prolog as object language.
Grammar has finally let its hair down! Unlike uptight grammar books that overwhelm us with every single grammar rule, Kiss My Asterisk is like a bikini: it's fun, flirty, and covers only the most important bits. Its lessons, which are 100 percent free of complicated grammar jargon, have been carefully selected to include today's most common, noticeable errors—the ones that confuse our readers or make them wonder if we are, in fact, smarter than a fifth grader. What is the proper use of an apostrophe? When should an ellipsis be used instead of an em dash? Why do we capitalize President Obama bu
Yu, Wenbao; Park, Taesung
Motivation It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. Results We propose an AUC-based approach u...
Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Kammoun, Abla; Al-Naffouri, Tareq Y.
This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model
Hedenius, Martina; Persson, Jonas; Tremblay, Antoine; Adi-Japha, Esther; Veríssimo, João; Dye, Cristina D; Alm, Per; Jennische, Margareta; Bruce Tomblin, J; Ullman, Michael T
The Procedural Deficit Hypothesis (PDH) posits that Specific Language Impairment (SLI) can be largely explained by abnormalities of brain structures that subserve procedural memory. The PDH predicts impairments of procedural memory itself, and that such impairments underlie the grammatical deficits observed in the disorder. Previous studies have indeed reported procedural learning impairments in SLI, and have found that these are associated with grammatical difficulties. The present study extends this research by examining consolidation and longer-term procedural sequence learning in children with SLI. The Alternating Serial Reaction Time (ASRT) task was given to children with SLI and typically developing (TD) children in an initial learning session and an average of three days later to test for consolidation and longer-term learning. Although both groups showed evidence of initial sequence learning, only the TD children showed clear signs of consolidation, even though the two groups did not differ in longer-term learning. When the children were re-categorized on the basis of grammar deficits rather than broader language deficits, a clearer pattern emerged. Whereas both the grammar impaired and normal grammar groups showed evidence of initial sequence learning, only those with normal grammar showed consolidation and longer-term learning. Indeed, the grammar-impaired group appeared to lose any sequence knowledge gained during the initial testing session. These findings held even when controlling for vocabulary or a broad non-grammatical language measure, neither of which were associated with procedural memory. When grammar was examined as a continuous variable over all children, the same relationships between procedural memory and grammar, but not vocabulary or the broader language measure, were observed. Overall, the findings support and further specify the PDH. They suggest that consolidation and longer-term procedural learning are impaired in SLI, but that these
Hedenius, Martina; Persson, Jonas; Tremblay, Antoine; Adi-Japha, Esther; Veríssimo, João; Dye, Cristina D.; Alm, Per; Jennische, Margareta; Tomblin, J. Bruce; Ullman, Michael T.
The Procedural Deficit Hypothesis (PDH) posits that Specific Language Impairment (SLI) can be largely explained by abnormalities of brain structures that subserve procedural memory. The PDH predicts impairments of procedural memory itself, and that such impairments underlie the grammatical deficits observed in the disorder. Previous studies have indeed reported procedural learning impairments in SLI, and have found that these are associated with grammatical difficulties. The present study extends this research by examining the consolidation and longer-term procedural sequence learning in children with SLI. The Alternating Serial Reaction Time (ASRT) task was given to children with SLI and typically-developing (TD) children in an initial learning session and an average of three days later to test for consolidation and longer-term learning. Although both groups showed evidence of initial sequence learning, only the TD children showed clear signs of consolidation, even though the two groups did not differ in longer-term learning. When the children were re-categorized on the basis of grammar deficits rather than broader language deficits, a clearer pattern emerged. Whereas both the grammar impaired and normal grammar groups showed evidence of initial sequence learning, only those with normal grammar showed consolidation and longer-term learning. Indeed, the grammar-impaired group appeared to lose any sequence knowledge gained during the initial testing session. These findings held even when controlling for vocabulary or a broad non-grammatical language measure, neither of which were associated with procedural memory. When grammar was examined as a continuous variable over all children, the same relationships between procedural memory and grammar, but not vocabulary or the broader language measure, were observed. Overall, the findings support and further specify the PDH. They suggest that consolidation and longer-term procedural learning are impaired in SLI, but that
Suliman, Mohamed Abdalla Elhag
This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrix and hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator. Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems. Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.
Owusu-Edusei, Kwame; Gift, Thomas L; Leichliter, Jami S; Romaguera, Raul A
The number of categorical sexually transmitted disease (STD) clinics is declining in the United States. Federally qualified health centers (FQHCs) have the potential to supplement the needed sexually transmitted infection (STI) services. In this study, we describe the spatial distribution of FQHC sites and determine if reported county-level nonviral STI morbidity were associated with having FQHC(s) using spatial regression techniques. We extracted map data from the Health Resources and Services Administration data warehouse on FQHCs (ie, geocoded health care service delivery [HCSD] sites) and extracted county-level data on the reported rates of chlamydia, gonorrhea and, primary and secondary (P&S) syphilis (2008-2012) from surveillance data. A 3-equation seemingly unrelated regression estimation procedure (with a spatial regression specification that controlled for county-level multiyear (2008-2012) demographic and socioeconomic factors) was used to determine the association between reported county-level STI morbidity and HCSD sites. Counties with HCSD sites had higher STI, poverty, unemployment, and violent crime rates than counties with no HCSD sites (P < 0.05). The number of HCSD sites was associated (P < 0.01) with increases in the temporally smoothed rates of chlamydia, gonorrhea, and P&S syphilis, but there was no significant association between the number of HCSD per 100,000 population and reported STI rates. There is a positive association between STI morbidity and the number of HCSD sites; however, this association does not exist when adjusting by population size. Further work may determine the extent to which HCSD sites can meet unmet needs for safety net STI services.
Olive, David J
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
The grammar written in Latin, in 1668, by the Jesuit missionary Father Diego Luis de Sanvitores (1627-1672) is the oldest description we have of Chamorro, a language spoken on the Mariana islands. The grammar received a number of bad reviews and as a consequence has become neglected and almost forgotten. The main point of criticism has been that Sanvitores used the Latin grammatical framework to explain a language that in many ways does not fit this framework. In this thesis it is argued inst...
Full Text Available In order for intermediate students poor at English grammar to enjoy learning it, a unique methodology has been improved in the classroom. In this article illustrated vehicles relevant to the five basic sentence patterns are presented in order to show how helpful this method is to understand English grammar. Also, more enhanced areas of this theory are discussed, which clarifies the feasibility of this methodology. The items to be introduced in my method are gerund, the passive voice, the relative pronoun and so on.
Heimbauer, Lisa A; Conway, Christopher M; Christiansen, Morten H; Beran, Michael J; Owren, Michael J
Humans and nonhuman primates can learn about the organization of stimuli in the environment using implicit sequential pattern learning capabilities. However, most previous artificial grammar learning studies with nonhuman primates have involved relatively simple grammars and short input sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an artificial grammar-learning task that was more complex than most others previously used with nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial reaction time task in which two monkeys were exposed to grammar-generated sequences at sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the monkeys came to respond faster to the sequences generated from the artificial grammar compared to random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel sequences, responding significantly faster to novel instances of sequences produced using the familiar grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as complex as some used with humans, for sequences up to eight items long. These findings are discussed in relation to whether or not rhesus macaques and other primate species possess implicit sequence learning abilities that are similar to those that humans draw upon to learn natural language grammar.
Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David
Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.
Won, Kyoung-Jae; Sandelin, Albin; Marstrand, Troels Torben
MOTIVATION: Describing and modeling biological features of eukaryotic promoters remains an important and challenging problem within computational biology. The promoters of higher eukaryotes in particular display a wide variation in regulatory features, which are difficult to model. Often several...... factors are involved in the regulation of a set of co-regulated genes. If so, promoters can be modeled with connected regulatory features, where the network of connections is characteristic for a particular mode of regulation. RESULTS: With the goal of automatically deciphering such regulatory structures......, we present a method that iteratively evolves an ensemble of regulatory grammars using a hidden Markov Model (HMM) architecture composed of interconnected blocks representing transcription factor binding sites (TFBSs) and background regions of promoter sequences. The ensemble approach reduces the risk...
Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi
Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
Syd. Ali Zein Farmadi
Full Text Available Arabic grammar, known as nahwu, is necessary to comprehend the Holy Qur’an that is completely written in Arabic. However, many people get trouble to study this skill because there are various kinds of word formation and sentences that may be created from a single verb, noun, adjective, subject, predicate, object, adverb or another formation. This research proposes a new approach to identify the position and word function in Arabic sentence. The approach creates smart process that employs Natural Language Processing (NLP and expert system with modeling based on knowledge and inference engine in determining the word position. The knowledge base determines the part of speech while the inference engine shows the word function in the sentence. On processing, the system uses 82 templates consisting of 34 verb templates, 34 subject pronouns, 14 pronouns for object or possessive word. All the templates are in the form of char array for harakat (vowel and letters which become the comparators for determining the part of speech from input word sentence. Output from the system is an i’rab (the explanation of word function in sentence written in Arabic. The system has been tested for 159 times to examine word and sentence. The examination for word that is done 117 times has not made any error except for the word that is really like another word. While the detection for word function in sentence that is done 42 times experiment, there is no error too. An error happens when the part of speech from the word being examined is not included in the system yet, influencing the following word function detection. Keywords: I’rab, Arabic grammar, NLP, expert system, knowledge base, inference engine
Payande, Abolfazl; Tabesh, Hamed; Shakeri, Mohammad Taghi; Saki, Azadeh; Safarian, Mohammad
Growth charts are widely used to assess children's growth status and can provide a trajectory of growth during early important months of life. The objectives of this study are going to construct growth charts and normal values of weight-for-age for children aged 0 to 5 years using a powerful and applicable methodology. The results compare with the World Health Organization (WHO) references and semi-parametric LMS method of Cole and Green. A total of 70737 apparently healthy boys and girls aged 0 to 5 years were recruited in July 2004 for 20 days from those attending community clinics for routine health checks as a part of a national survey. Anthropometric measurements were done by trained health staff using WHO methodology. The nonparametric quantile regression method obtained by local constant kernel estimation of conditional quantiles curves using for estimation of curves and normal values. The weight-for-age growth curves for boys and girls aged from 0 to 5 years were derived utilizing a population of children living in the northeast of Iran. The results were similar to the ones obtained by the semi-parametric LMS method in the same data. Among all age groups from 0 to 5 years, the median values of children's weight living in the northeast of Iran were lower than the corresponding values in WHO reference data. The weight curves of boys were higher than those of girls in all age groups. The differences between growth patterns of children living in the northeast of Iran versus international ones necessitate using local and regional growth charts. International normal values may not properly recognize the populations at risk for growth problems in Iranian children. Quantile regression (QR) as a flexible method which doesn't require restricted assumptions, proposed for estimation reference curves and normal values.
Demir, Sezgin; Erdogan, Ayse
Grammar; while originating from the natural structure of the language also is the system which makes it possible for different language functions meet within the body of common rules especially communication. Having command of the language used, speaking and writing it correctly require strong grammar knowledge actually. However only knowing the…
The study of how learners acquire a second language (SLA) has helped to shape thinking about how to teach the grammar of a second language. There remain, however, a number of controversial issues. This paper considers eight key questions relating to grammar pedagogy in the light of findings from SLA. As such, this article complements…
Grammars of natural language are highly complex objects. This complexity is reflected in formal analyses found in both syntactic theory and computational grammars. In particular, there are two factors that make it notoriously difficult to make strong assertions about analyses for natural language
English language teachers create contexts to teach grammar so that meaningful learning occurs. In this study, English grammar is contextualized through environmental peace education activities to raise students' awareness of global issues. Two sources provided data to evaluate the success of this instructional process. Fourth-year pre-service…
van Binsbergen, L. Thomas; Bransen, Jeroen; Dijkstra, Atze
Attribute Grammars (AGs) extend Context-Free Grammars with attributes: information gathered on the syntax tree that adds semantics to the syntax. AGs are very well suited for describing static analyses, code-generation and other phases incorporated in a compiler. AGs are divided into classes based
This article examines seven online grammar guides for instances of linguistic sexism. The grammar sentences from .edu Websites were analyzed based on NCTE's "Guidelines for Gender-Fair Use of Language" (2002) using the criteria of generic he and man; titles, labels, and names; gender stereotypes; order of mention (firstness); and ratio of male to…
Chomsky's Transformational-Generative (TG) grammar is another revolution to linguistics after Saussure's strueturalism, and it plays an important role in the modem linguistics. Introducing the research perspective and method of TG grammar, this paper analyses its implications for the foreign language teaching.
Türkmen, Yasemin; Aydin, Selami
Studies conducted so far have mainly focused on the effects of online concordancers on teaching vocabulary, while there is a lack of research focusing on the effects of online concordancers on teaching and learning grammar. Thus, this study aims to review the studies on the effects of online concordancers on teaching and learning grammar and how…
In China,English is a foreign language,not a second language.Chinese students can't learn English well without learning its gram?mar first.As for English teachers,the most important is to help the students to grasp the spirit of English grammar learning.
Robinson, Lisa; Feng, Jay
Grammar Instruction has an important role to play in helping students to speak and write more effectively. The purpose of this study was to examine the effects of direct grammar instruction on the quality of student's writing skills. The participants in this study included 18 fifth grade students and two fifth grade teachers. Based on the results…
Hedjazi Moghari, Mona; Marandi, S. Susan
It is usually the case that learners of English as a foreign language (EFL) are exposed to language materials in class only, and of course in such a short space of time, they do not always find enough chance to practice English grammar features and become aware of their grammar mistakes. As a potential solution to this problem, the current study…
Fontich, Xavier; Camps, Anna
This article hopes to bring new insights to the debate about the effect of grammar knowledge on language use, especially writing. It raises the question of the need to look more closely at the following three questions: (1) What is the aim of grammar teaching?; (2) How capable are students of conceptualising about language and how is their…
In the history of formal English education in Japan, grammar used to be the mainstream. In the secondary education system, teachers used to spend many hours teaching grammar to the students. However, it has been replaced by the aural/oral method of teaching a foreign language. There was even a remark that teaching grammar hinders students from communicating fluently. Literally, there was a time when grammar was set aside in formal English education. However, the author noticed that in grammar classes, the students speak English more loudly and confidently without much hesitation than in other types of English classes. One of the reasons is that they are not worried about the contents of the speeches. They are simply concentrating on the forms. They are not afraid of making major mistakes, and the errors they make are minor so they do not feel embarrassed in public. The atmosphere of the grammar classes is very positive and the students enjoy speaking English. In this paper, the author shows how grammar classes can contribute to the acquisition of the students＇ speaking abilities and manners. ＂Learning grammar was a precious experience＂, one student reported after the course.
Booij, Geert; Audring, Jenny
This article presents a systematic exposition of how the basic ideas of Construction Grammar (CxG) (Goldberg, 2006) and the Parallel Architecture (PA) of grammar (Jackendoff, 2002]) provide the framework for a proper account of morphological phenomena, in particular word formation. This framework is referred to as Construction Morphology (CxM). As…
Al-wossabi, Sami A.
Recent studies in corpus linguistics have revealed apparent inconsistencies between the prescriptive grammar presented in EFL textbooks and the type of grammar used in the speech of native speakers. Such variations and learning gaps deprive EFL learners of the actual use of English and delay their oral/aural developmental processes. The focus of…
Functional grammar has received more and more attention from domestic scholars in the world of linguistics since 1970s, but it is still new to most EFL teachers. In spite of controversies about its applications into classroom teaching, this new grammar model has its own advantages and can facilitate EFL students to achieve academic success. This…
When designing grammars of natural language, typically, more than one formal analysis can account for a given phenomenon. Moreover, because analyses interact, the choices made by the engineer influence the possibilities available in further grammar development. The order in which phenomena are
Navest, Karlijn Marianne
From the second half of the eighteenth century onwards a knowledge of grammar served as an important marker of class in England. In order to enable their children to rise in society, middle-class parents expected their sons and daughters to learn English grammar. Since England did not have an
Explores concepts of formal language and automata theory underlying computational linguistics. A computational formalism is described known as a "logic grammar," with which computational systems process linguistic data, with examples in declarative and procedural semantics and definite clause grammars. (13 references) (CB)
Sloane, A.M.; Kats, L.C.L.; Visser, E.
Attribute grammars are a powerful specification paradigm for many language processing tasks, particularly semantic analysis of programming languages. Recent attribute grammar systems use dynamic scheduling algorithms to evaluate attributes by need. In this paper, we show how to remove the need for a
The concept of mirativity has come to interfere in the recently developed framework of Functional Discourse Grammar with what would be considered to be exclamative elsewhere. In addition, the concept of exclamative itself turns out to be ill-defined in various studies within the functional paradigm.
Research over the last decades has shown that language development in its multiple forms is characterized by a succession of stable and unstable states. However, the variation observed is neither expected nor can it be accounted for on the basis of traditional learning concepts conceived of within the Universal Grammar (UG) paradigm. In this…
principles and rules of a visual game landscape (the game territory and environment) for composing the forms of visual elements and structuring the meaning of perceptual experience. It creates the system of visual communication in a particular context’. This study employs two approaches which combine...... of visual grammar consists of the initial units named visual elements which are regulated by the visual operators under the visual syntactic rules; the player experience is count as part of these rules....
Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V
From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).
Mohebbi, Mohammadreza; Wolfe, Rory; Forbes, Andrew
This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference. PMID:24413702
Shelley M. ALEXANDER
Full Text Available We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems (GIS-based approaches: logistic regression and Akaike’s Information Criterion (AIC, Multiple Criteria Evaluation (MCE, and Bayesian Analysis (specifically Dempster-Shafer theory. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified (overall accuracy, the failure to predict a species where it occurred (omission error and the prediction of presence where there was absence (commission error. Our overall accuracy showed the logistic regression approach was the most accurate (74.51%. The multiple criteria evaluation was intermediate (39.22%, while the Dempster-Shafer (D-S theory model was the poorest (29.90%. However, omission and commission error tell us a different story: logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach (e.g. Dempster-Shafer that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans[Current Zoology 55(1: 28 – 40, 2009].
Le, Laetitia Minh Maï; Kégl, Balázs; Gramfort, Alexandre; Marini, Camille; Nguyen, David; Cherti, Mehdi; Tfaili, Sana; Tfayli, Ali; Baillet-Guffroy, Arlette; Prognon, Patrice; Chaminade, Pierre; Caudron, Eric
The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). Copyright © 2018 Elsevier B.V. All rights reserved.
Full Text Available Abstract: This paper offers an alternative to the teaching of a functional grammar course in Indonesian TEFL tertiary level context. An issue raised here is whether the course should directly require students to undertake textual analysis or provide them first with subjective reading experiences. This issue is inspired by Jones and Lock¹s approach to teaching grammar in context (2011. This paper reports on a study that focused on two related phases of dealing with texts: responding and analyzing. In the first phase, students were encouraged to take a personalised approach in responding to written English texts. They had the freedom to decide whether the texts were meaningful for them in certain ways. Mckee (2003 and Lehtonen (2000 posit that as the sole decision maker in meaning negotiation, readers perceive the meaningfulness of texts in very diverse ways. In the second phase of the study, the students undertook an individual analysis of different text types. This study reveals that a successful textual analysis is determined by how students make sense of the texts. The analysis of context of situation, for example, becomes meaningful to students after they demonstrate a proper position as a reader. This, in turn, helps them in gaining insights into the structure and grammar of those texts. Keywords: systemic functional linguistics, genre-based approach, textual analysis
Hayat, Matthew J; Higgins, Melinda
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.
Tran, Tammie M.
The problem. This research study explores an important issue in the field of TESOL (Teaching English to Speakers of Other Languages) and second language acquisition (SLA). Its purpose is to examine the relationship between Vietnamese students' L1 grammar knowledge and their English grammar proficiency. Furthermore, it investigates the extent to…
Full Text Available This study describes the development of a reservoir inflow forecasting model for typhoon events to improve short lead-time flood forecasting performance. To strengthen the forecasting ability of the original support vector machines (SVMs model, the self-organizing map (SOM is adopted to group inputs into different clusters in advance of the proposed SOM-SVM model. Two different input methods are proposed for the SVM-based forecasting method, namely, SOM-SVM1 and SOM-SVM2. The methods are applied to an actual reservoir watershed to determine the 1 to 3 h ahead inflow forecasts. For 1, 2, and 3 h ahead forecasts, improvements in mean coefficient of efficiency (MCE due to the clusters obtained from SOM-SVM1 are 21.5%, 18.5%, and 23.0%, respectively. Furthermore, improvement in MCE for SOM-SVM2 is 20.9%, 21.2%, and 35.4%, respectively. Another SOM-SVM2 model increases the SOM-SVM1 model for 1, 2, and 3 h ahead forecasts obtained improvement increases of 0.33%, 2.25%, and 10.08%, respectively. These results show that the performance of the proposed model can provide improved forecasts of hourly inflow, especially in the proposed SOM-SVM2 model. In conclusion, the proposed model, which considers limit and higher related inputs instead of all inputs, can generate better forecasts in different clusters than are generated from the SOM process. The SOM-SVM2 model is recommended as an alternative to the original SVR (Support Vector Regression model because of its accuracy and robustness.
Balint, Lajos; Dome, Peter; Daroczi, Gergely; Gonda, Xenia; Rihmer, Zoltan
In the last century Hungary had astonishingly high suicide rates characterized by marked regional within-country inequalities, a spatial pattern which has been quite stable over time. To explain the above phenomenon at the level of micro-regions (n=175) in the period between 2005 and 2011. Our dependent variable was the age and gender standardized mortality ratio (SMR) for suicide while explanatory variables were factors which are supposed to influence suicide risk, such as measures of religious and political integration, travel time accessibility of psychiatric services, alcohol consumption, unemployment and disability pensionery. When applying the ordinary least squared regression model, the residuals were found to be spatially autocorrelated, which indicates the violation of the assumption on the independence of error terms and - accordingly - the necessity of application of a spatial autoregressive (SAR) model to handle this problem. According to our calculations the SARlag model was a better way (versus the SARerr model) of addressing the problem of spatial autocorrelation, furthermore its substantive meaning is more convenient. SMR was significantly associated with the "political integration" variable in a negative and with "lack of religious integration" and "disability pensionery" variables in a positive manner. Associations were not significant for the remaining explanatory variables. Several important psychiatric variables were not available at the level of micro-regions. We conducted our analysis on aggregate data. Our results may draw attention to the relevance and abiding validity of the classic Durkheimian suicide risk factors - such as lack of social integration - apropos of the spatial pattern of Hungarian suicides. © 2013 Published by Elsevier B.V.
Gaudio, P; Gelfusa, M; Lupelli, I; Murari, A; Vega, J
A new approach to determine the power law expressions for the threshold between the H and L mode of confinement is presented. The method is based on two powerful machine learning tools for classification: neural networks and support vector machines. Using as inputs clear examples of the systems on either side of the transition, the machine learning tools learn the input–output mapping corresponding to the equations of the boundary separating the confinement regimes. Systematic tests with synthetic data show that the machine learning tools provide results competitive with traditional statistical regression and more robust against random noise and systematic errors. The developed tools have then been applied to the multi-machine International Tokamak Physics Activity International Global Threshold Database of validated ITER-like Tokamak discharges. The machine learning tools converge on the same scaling law parameters obtained with non-linear regression. On the other hand, the developed tools allow a reduction of 50% of the uncertainty in the extrapolations to ITER. Therefore the proposed approach can effectively complement traditional regression since its application poses much less stringent requirements on the experimental data, to be used to determine the scaling laws, because they do not require examples exactly at the moment of the transition. (paper)
Liu, Danping; Yeung, Edwina H; McLain, Alexander C; Xie, Yunlong; Buck Louis, Germaine M; Sundaram, Rajeshwari
Imperfect follow-up in longitudinal studies commonly leads to missing outcome data that can potentially bias the inference when the missingness is nonignorable; that is, the propensity of missingness depends on missing values in the data. In the Upstate KIDS Study, we seek to determine if the missingness of child development outcomes is nonignorable, and how a simple model assuming ignorable missingness would compare with more complicated models for a nonignorable mechanism. To correct for nonignorable missingness, the shared random effects model (SREM) jointly models the outcome and the missing mechanism. However, the computational complexity and lack of software packages has limited its practical applications. This paper proposes a novel two-step approach to handle nonignorable missing outcomes in generalized linear mixed models. We first analyse the missing mechanism with a generalized linear mixed model and predict values of the random effects; then, the outcome model is fitted adjusting for the predicted random effects to account for heterogeneity in the missingness propensity. Extensive simulation studies suggest that the proposed method is a reliable approximation to SREM, with a much faster computation. The nonignorability of missing data in the Upstate KIDS Study is estimated to be mild to moderate, and the analyses using the two-step approach or SREM are similar to the model assuming ignorable missingness. The two-step approach is a computationally straightforward method that can be conducted as sensitivity analyses in longitudinal studies to examine violations to the ignorable missingness assumption and the implications relative to health outcomes. © 2017 John Wiley & Sons Ltd.
Ho, Pham Vu Phi; The Binh, Nguyen
So far the students of Le Hong Phong Junior High School have been taught grammar with GTM (Grammar-Translation Method), which just prepares learners for conventional grammar-paper tests. Despite their considerable knowledge of grammar, the students fail to use the language they have learnt to communicate in real-life situations. The purpose of…
Traditional grammar instruction is a challenging element of the English curriculum; both students and teachers struggle with the rules and dull nature of grammar. However, understanding grammar is important because students need to understand the language they speak in order to be effective communicators, and teachers provide grammar instruction…
Svalberg, Agneta M.-L.
This article takes the view that grammar is driven by user choices and is therefore complex and dynamic. This has implications for the teaching of grammar in language teacher education and how teachers' cognitions about grammar, and hence their own grammar teaching, might change. In this small, interpretative study, the participants--students on…
This paper mainly deals with the idea that whether grammar teaching should be weakened or not ,the importance of grammar teaching,the present situation of grammar and some suggestions on how to teach grammar ,aiming at the improvement of English teaching and learning.
Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.
Sattler, Tine; Sekulic, Damir; Spasic, Miodrag; Osmankac, Nedzad; Vicente João, Paulo; Dervisevic, Edvin; Hadzic, Vedran
Previous investigations noted potential importance of isokinetic strength in rapid muscular performances, such as jumping. This study aimed to identify the influence of isokinetic-knee-strength on specific jumping performance in volleyball. The secondary aim of the study was to evaluate reliability and validity of the two volleyball-specific jumping tests. The sample comprised 67 female (21.96±3.79 years; 68.26±8.52 kg; 174.43±6.85 cm) and 99 male (23.62±5.27 years; 84.83±10.37 kg; 189.01±7.21 cm) high- volleyball players who competed in 1st and 2nd National Division. Subjects were randomly divided into validation (N.=55 and 33 for males and females, respectively) and cross-validation subsamples (N.=54 and 34 for males and females, respectively). Set of predictors included isokinetic tests, to evaluate the eccentric and concentric strength capacities of the knee extensors, and flexors for dominant and non-dominant leg. The main outcome measure for the isokinetic testing was peak torque (PT) which was later normalized for body mass and expressed as PT/Kg. Block-jump and spike-jump performances were measured over three trials, and observed as criteria. Forward stepwise multiple regressions were calculated for validation subsamples and then cross-validated. Cross validation included correlations between and t-test differences between observed and predicted scores; and Bland Altman graphics. Jumping tests were found to be reliable (spike jump: ICC of 0.79 and 0.86; block-jump: ICC of 0.86 and 0.90; for males and females, respectively), and their validity was confirmed by significant t-test differences between 1st vs. 2nd division players. Isokinetic variables were found to be significant predictors of jumping performance in females, but not among males. In females, the isokinetic-knee measures were shown to be stronger and more valid predictors of the block-jump (42% and 64% of the explained variance for validation and cross-validation subsample, respectively
Full Text Available Modal parameter estimation plays an important role in vibration-based damage detection and is worth more attention and investigation, as changes in modal parameters are usually being used as damage indicators. This paper focuses on the problem of output-only modal parameter recursive estimation of time-varying structures based upon parameterized representations of the time-dependent autoregressive moving average (TARMA. A kernel ridge regression functional series TARMA (FS-TARMA recursive identification scheme is proposed and subsequently employed for the modal parameter estimation of a numerical three-degree-of-freedom time-varying structural system and a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudolinear regression FS-TARMA approach via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics in a recursive manner.
Yanti; Cole, Peter; Hermon, Gabriella
Cole, Hermon, and Yanti (2015) argue that the empirical facts related to anaphoric binding in two dialects of Jambi Malay undermine the Classical Binding Theory. Reuland (2017) agrees with this conclusion but argues that the data are easily accounted for by his alternative Universal Grammar-based approach to Binding. In this response, we demonstrate that the alternative proposal for Jambi Malay rests on claims about the language that are incorrect. While we do not, indeed cannot, demonstrate that it is impossible for a Universal Grammar based proposal to account for the facts as outlined in CHY (2015), we conclude that those facts remain an outstanding challenge. Copyright © 2017 Elsevier B.V. All rights reserved.
Coll, Anna; Wilson, Mandy L; Gruden, Kristina; Peccoud, Jean
With the rapid advances in prediction tools for discovery of new promoters and their cis-elements, there is a need to improve plant expression methodologies in order to facilitate a high-throughput functional validation of these promoters in planta. The promoter-reporter analysis is an indispensible approach for characterization of plant promoters. It requires the design of complex plant expression vectors, which can be challenging. Here, we describe the use of a plant grammar implemented in GenoCAD that will allow the users to quickly design constructs for promoter analysis experiments but also for other in planta functional studies. The GenoCAD plant grammar includes a library of plant biological parts organized in structural categories to facilitate their use and management and a set of rules that guides the process of assembling these biological parts into large constructs.
Chou, Philip A.
We propose using two-dimensional stochastic context-free grammars for image recognition, in a manner analogous to using hidden Markov models for speech recognition. The value of the approach is demonstrated in a system that recognizes printed, noisy equations. The system uses a two-dimensional probabilistic version of the Cocke-Younger-Kasami parsing algorithm to find the most likely parse of the observed image, and then traverses the corresponding parse tree in accordance with translation formats associated with each production rule, to produce eqn I troff commands for the imaged equation. In addition, it uses two-dimensional versions of the Inside/Outside and Baum re-estimation algorithms for learning the parameters of the grammar from a training set of examples. Parsing the image of a simple noisy equation currently takes about one second of cpu time on an Alliant FX/80.
David M. Berry
Full Text Available Over the past thirty years there has been an increasing interest in the social and cultural implications of digital technologies and ‘informationalism’ from the social sciences and humanities. Generally this has concentrated on the implications of the “convergence” of digital devices and services, understood as linked to the discrete processing capabilities of computers, which rely on logical operations, binary processing and symbolic representation. In this paper, I wish to suggest that a ‘grammar of code’ might provide a useful way of thinking about the way in which digital technologies operate as a medium and can contribute usefully to this wider debate. I am interested in the way in which the dynamic properties of code can be understood as operating according to a grammar reflected in its materialisation and operation in the lifeworld – the discretisation of the phenomenal world. As part of that contribution in this paper I develop some tentative Weberian ‘ideal-types’. These ideal-types are then applied to the work of the Japanese composer, Masahiro Miwa, whose innovative ‘Reverse-Simulation music’ models the operation of basic low-level digital circuitry for the performance and generation of musical pieces.
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The paper addresses the modelling of information packaging in Functional Discourse Grammar (FDG, in particular the treatment of Topic, Comment and Focus. Current FDG has inherited the traditional Functional Grammar (FG representation of these categories as functions, which attach to Subacts of evocation. However, arguments of a formal, notional and descriptive nature can be advanced against pragmatic function assignment and in favour of an alternative analysis in which informational and evocational structures are dissociated so as to command their own primitives. In the context of a model of discourse knowledge organisation in which communicated contents are associated with packaging instructions that tell the Addressee how to treat the evoked knowledge, it is argued that focality can be modelled by means of a Focus operator that can attach to various constituents at the Interpersonal Level. Topicality, on the other hand, concerns binomial and monomial modes of presenting communicated contents. This can be rendered by means of the dedicated informational units Topic (Top and Comment (Cm, that interact in frames.
Aliaga, Daniel G; Rosen, Paul A; Bekins, Daniel R
Interactive visualization of architecture provides a way to quickly visualize existing or novel buildings and structures. Such applications require both fast rendering and an effortless input regimen for creating and changing architecture using high-level editing operations that automatically fill in the necessary details. Procedural modeling and synthesis is a powerful paradigm that yields high data amplification and can be coupled with fast-rendering techniques to quickly generate plausible details of a scene without much or any user interaction. Previously, forward generating procedural methods have been proposed where a procedure is explicitly created to generate particular content. In this paper, we present our work in inverse procedural modeling of buildings and describe how to use an extracted repertoire of building grammars to facilitate the visualization and quick modification of architectural structures and buildings. We demonstrate an interactive application where the user draws simple building blocks and, using our system, can automatically complete the building "in the style of" other buildings using view-dependent texture mapping or nonphotorealistic rendering techniques. Our system supports an arbitrary number of building grammars created from user subdivided building models and captured photographs. Using only edit, copy, and paste metaphors, the entire building styles can be altered and transferred from one building to another in a few operations, enhancing the ability to modify an existing architectural structure or to visualize a novel building in the style of the others.
Rosani, Andrea; Conci, Nicola; De Natale, Francesco G. B.
Automatic recognition of human activities and behaviors is still a challenging problem for many reasons, including limited accuracy of the data acquired by sensing devices, high variability of human behaviors, and gap between visual appearance and scene semantics. Symbolic approaches can significantly simplify the analysis and turn raw data into chains of meaningful patterns. This allows getting rid of most of the clutter produced by low-level processing operations, embedding significant contextual information into the data, as well as using simple syntactic approaches to perform the matching between incoming sequences and models. We propose a symbolic approach to learn and detect complex activities through the sequences of atomic actions. Compared to previous methods based on context-free grammars, we introduce several important novelties, such as the capability to learn actions based on both positive and negative samples, the possibility of efficiently retraining the system in the presence of misclassified or unrecognized events, and the use of a parsing procedure that allows correct detection of the activities also when they are concatenated and/or nested one with each other. An experimental validation on three datasets with different characteristics demonstrates the robustness of the approach in classifying complex human behaviors.
While there is a big literature on the benefits of pre-school education, only little is known why kindergarten attendance improves later-life outcomes. This is partly because most studies analyze the effect of complete 2 years pre-school programs. In order to shed light into the black box of kindergarten education, I am using the German National Educational Panel Study and regress the level of grammar skills - a main intelligence component - on the participation in a nationwide-used language ...
Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.
Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning. PMID:23094021
Full Text Available Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.
Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza
In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.
Shrivastava, Prashant Kumar; Pandey, Arun Kumar
Inconel-718 has found high demand in different industries due to their superior mechanical properties. The traditional cutting methods are facing difficulties for cutting these alloys due to their low thermal potential, lower elasticity and high chemical compatibility at inflated temperature. The challenges of machining and/or finishing of unusual shapes and/or sizes in these materials have also faced by traditional machining. Laser beam cutting may be applied for the miniaturization and ultra-precision cutting and/or finishing by appropriate control of different process parameter. This paper present multi-objective optimization the kerf deviation, kerf width and kerf taper in the laser cutting of Incone-718 sheet. The second order regression models have been developed for different quality characteristics by using the experimental data obtained through experimentation. The regression models have been used as objective function for multi-objective optimization based on the hybrid approach of multiple regression analysis and genetic algorithm. The comparison of optimization results to experimental results shows an improvement of 88%, 10.63% and 42.15% in kerf deviation, kerf width and kerf taper, respectively. Finally, the effects of different process parameters on quality characteristics have also been discussed.
Full Text Available Webquest is an internet based learning tool that can be used by students in learning English. This study investigates students’ perceptions about the use of Webquest to support learning grammar in Higher Education. Seventy-two of second semester students were involved as participants in this study. Questionnaire and interview were used to collect the data. The data were analyzed quantitatively and qualitatively. The result of this study revealed that students had positive perceptions toward the use of Webquest in learning grammar. They believed that Webquest can be used as one of effective internet based learning tools in studying grammar.
@@ The role of grammar instruction in foreign or second language acquisition is one of the most con troversial issues in foreign/second language teach ing and learning research. The advocators of gram mar instruction argue that grammar should be the core of language instruction and formal instruction enhances formal accuracy. On the other hand, crit ics naintain that the grammar knowledge has lim ited uses and may hinder the students from acquir ing the communicative competence and efficiency. Undoubtedly these two extreme theories often put teachers into a dilemma. What theory should they believe then? Do they accept the one and ignore the other?
Gross, Samuel M; Tibshirani, Robert
We consider the scenario where one observes an outcome variable and sets of features from multiple assays, all measured on the same set of samples. One approach that has been proposed for dealing with these type of data is "sparse multiple canonical correlation analysis" (sparse mCCA). All of the current sparse mCCA techniques are biconvex and thus have no guarantees about reaching a global optimum. We propose a method for performing sparse supervised canonical correlation analysis (sparse sCCA), a specific case of sparse mCCA when one of the datasets is a vector. Our proposal for sparse sCCA is convex and thus does not face the same difficulties as the other methods. We derive efficient algorithms for this problem that can be implemented with off the shelf solvers, and illustrate their use on simulated and real data. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org.
Jiang, Junjun; Hu, Ruimin; Han, Zhen; Wang, Zhongyuan; Chen, Jun
Face superresolution (SR), or face hallucination, refers to the technique of generating a high-resolution (HR) face image from a low-resolution (LR) one with the help of a set of training examples. It aims at transcending the limitations of electronic imaging systems. Applications of face SR include video surveillance, in which the individual of interest is often far from cameras. A two-step method is proposed to infer a high-quality and HR face image from a low-quality and LR observation. First, we establish the nonlinear relationship between LR face images and HR ones, according to radial basis function and partial least squares (RBF-PLS) regression, to transform the LR face into the global face space. Then, a locality-induced sparse representation (LiSR) approach is presented to enhance the local facial details once all the global faces for each LR training face are constructed. A comparison of some state-of-the-art SR methods shows the superiority of the proposed two-step approach, RBF-PLS global face regression followed by LiSR-based local patch reconstruction. Experiments also demonstrate the effectiveness under both simulation conditions and some real conditions.