The normative structure of mathematization in systematic biology.

PubMed

Sterner, Beckett; Lidgard, Scott

2014-06-01

We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to formalize the work of classification, but Mayr introduced a qualitative formalism based on human judgment for determining the taxonomic rank of populations, while the numerical taxonomists introduced a quantitative formalism based on automated procedures for computing classifications. The key contrast between Mayr and the numerical taxonomists is how they conceptualized the temporal structure of the workflow of classification, specifically where they allowed meta-level discourse about difficulties in producing the classification. Copyright © 2014. Published by Elsevier Ltd.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

Omnidirectional Learning - A New Paradigm for Learning to Predict Any Set of Variables from Any Other Set

DTIC Science & Technology

2016-05-06

ABSTRACT Awards: Best Paper Honorable Mention Award at the SIAM (Society for Industrial and Applied Mathematics Conference on Data Mining (SDM...magnitude in computation time over the state of the art. 15. SUBJECT TERMS Data Mining 16. SECURITY CLASSIFICATION OF: 17...International Conference on Data Mining and received Best Paper Honorable mention. To ensure broad use and uptake of the outcomes of this research

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

PubMed

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

PubMed Central

Pham, Tuan D.

2014-01-01

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

BOOK REVIEW: Symmetry and the Monster: One of the Greatest Quests of Mathematics

NASA Astrophysics Data System (ADS)

Szabo, R. J.

2007-04-01

The book Symmetry and the Monster: One of the Greatest Quests of Mathematics describes historical events leading up to the discovery of the Monster sporadic group, the largest simple sporadic group. It also expounds the significance and deep relationships between this group and other areas of mathematics and theoretical physics. It begins, in the prologue, with a nice overview of some of the mathematical drama surrounding the discovery of the Monster and its subsequent relationship to number theory (the so-called Moonshine conjectures). From a historical perspective, the book traces back to the roots of group theory, Galois theory, and steadily runs through time through the many famous mathematicians who contributed to group theory, including Lie, Killing and Cartan. Throughout, the author has provided a very nice and deep insight into the sociological and scientific problems at the time, and gives the reader a very prominent inside view of the real people behind the mathematics. The book should be an enjoyable read to anyone with an interest in the history of mathematics. For the non-mathematician the book makes a good, and mostly successful, attempt at being non-technical. Technical mathematical jargon is replaced with more heuristic, intuitive terminology, making the mathematical descriptions in the book fairly easy going. A glossary\\hspace{0.25pc} of\\hspace{0.25pc} terminology for noindent the more scientifically inclined is included in various footnotes throughout the book and in a comprehensive listing at the end of the book. Some more technical material is also included in the form of appendices at the end of the book. Some aspects of physics are also explained in a simple, intuitive way. The author further attempts at various places to give the non-specialist a glimpse into what mathematical proof is all about, and explains the difficulties and technicalities involved in this very nicely (for instance, he mentions the various 100+ page articles that appeared in the hey-day of finite group theory, indicating the enormous technical nature of the subject). The book nicely paints a dramatic landscape leading up to the discovery of the Monster group, and the problems that remain to this day in trying to understand its significance. One can really take from this book a feel of the mathematics leading up to its appearance, and the importance of the classification problem which was responsible for this. One also really gets an appreciation of the efforts and commitments of the mathematicians who contributed to the subject. All in all, this book achieves a nice balance between providing a beautiful historical account of group theory, and explaining the classification problem for finite groups in a way that is accessible to non-scientists. This should prove to be a good read for both the layperson interested in mathematics or mathematical physics, and also both mathematicians and physicists alike.

On the Equidecomposability of a Regular Triangle and A Square of Equal Areas.

DTIC Science & Technology

1984-01-01

Hogo Steinhaus OMathematical Snapshots , is not correct. ANS (MOS) Subject Classifications: 51-01, 51N20 Key Words: Equidecomposability of plane...It is shown that the solution of the problem of the title, as given in the first snapshot of H. Steinhaus ’ "Mathematical Snapshots" is not correct...490985 This accuracy should be sufficient for the realization of the ingenious linkage of four polygons (1) as described by Steinhaus (See (2, Figure 1.3

A Likelihood Ratio Test Regarding Two Nested But Oblique Order Restricted Hypotheses.

DTIC Science & Technology

1982-11-01

Report #90 DIC JAN 2 411 ISMO. H American Mathematical Society 1979 subject classification Primary 62F03 Secondary 62E15 Key words and phrases: Order...model. A likelihood ratio test for these two restrictions is studied . Asa *a .on . r 373 RA&J *iii - ,sa~m muwod [] v~ -F: :.v"’. os "- 1...investigation was stimulated partly by a problem encountered in psychiatric research. [Winokur et al., 1971] studied data on psychiatric illnesses afflicting

Development of a methodology for classifying software errors

NASA Technical Reports Server (NTRS)

Gerhart, S. L.

1976-01-01

A mathematical formalization of the intuition behind classification of software errors is devised and then extended to a classification discipline: Every classification scheme should have an easily discernible mathematical structure and certain properties of the scheme should be decidable (although whether or not these properties hold is relative to the intended use of the scheme). Classification of errors then becomes an iterative process of generalization from actual errors to terms defining the errors together with adjustment of definitions according to the classification discipline. Alternatively, whenever possible, small scale models may be built to give more substance to the definitions. The classification discipline and the difficulties of definition are illustrated by examples of classification schemes from the literature and a new study of observed errors in published papers of programming methodologies.

Verification and classification bias interactions in diagnostic test accuracy studies for fine-needle aspiration biopsy.

PubMed

Schmidt, Robert L; Walker, Brandon S; Cohen, Michael B

2015-03-01

Reliable estimates of accuracy are important for any diagnostic test. Diagnostic accuracy studies are subject to unique sources of bias. Verification bias and classification bias are 2 sources of bias that commonly occur in diagnostic accuracy studies. Statistical methods are available to estimate the impact of these sources of bias when they occur alone. The impact of interactions when these types of bias occur together has not been investigated. We developed mathematical relationships to show the combined effect of verification bias and classification bias. A wide range of case scenarios were generated to assess the impact of bias components and interactions on total bias. Interactions between verification bias and classification bias caused overestimation of sensitivity and underestimation of specificity. Interactions had more effect on sensitivity than specificity. Sensitivity was overestimated by at least 7% in approximately 6% of the tested scenarios. Specificity was underestimated by at least 7% in less than 0.1% of the scenarios. Interactions between verification bias and classification bias create distortions in accuracy estimates that are greater than would be predicted from each source of bias acting independently. © 2014 American Cancer Society.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Engineering Design Handbook. Development Guide for Reliability. Part 6. Mathematical Appendix and Glossary

DTIC Science & Technology

1976-01-08

Corps, nonmilitary Government agencies, contractors, private industry, individuals, universities , and others must purchase these Handbooks from...verified by an official Department of Army representative and processed from Defense Documentation Center ( DDC ), ATTN: DDC -TSR, Cameron Station...tell, by looking at a failed item, what classification of failure is involved. Some of the classifications are for mathematical conven- ience only

Neuromuscular disease classification system

NASA Astrophysics Data System (ADS)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Subject design and factors affecting achievement in mathematics for biomedical science

NASA Astrophysics Data System (ADS)

Carnie, Steven; Morphett, Anthony

2017-01-01

Reports such as Bio2010 emphasize the importance of integrating mathematical modelling skills into undergraduate biology and life science programmes, to ensure students have the skills and knowledge needed for biological research in the twenty-first century. One way to do this is by developing a dedicated mathematics subject to teach modelling and mathematical concepts in biological contexts. We describe such a subject at a research-intensive Australian university, and discuss the considerations informing its design. We also present an investigation into the effect of mathematical and biological background, prior mathematical achievement, and gender, on student achievement in the subject. The investigation shows that several factors known to predict performance in standard calculus subjects apply also to specialized discipline-specific mathematics subjects, and give some insight into the relative importance of mathematical versus biological background for a biology-focused mathematics subject.

[Executive functioning and motivation in preschool children at risk for learning difficulties in mathematics].

PubMed

Presentación-Herrero, M Jesús; Mercader-Ruiz, Jessica; Siegenthaler-Hierro, Rebeca; Fernández-Andrés, Inmaculada; Miranda-Casas, Ana

2015-02-25

Early identification of the factors involved in the development of learning difficulties in mathematics is essential to be able to understand their origin and implement successful interventions. This study analyses the capacity of executive functioning and of variables from the motivational belief system to differentiate and classify preschool children with and without risk of having difficulties in mathematics. A total of 146 subjects from the third year of preschool education took part in the study, divided into risk/no risk according to the score obtained on the operations subtest of the TEDI-MATH test. Working memory (verbal and visuospatial) and inhibition (with auditory and visual stimuli) neuropsychological tasks were applied. Teachers filled in a questionnaire on the children's motivation with regard to learning. Significant differences were found between the two groups on the working memory and inhibition-auditory factors, as well as on all the motivation variables. The results also show a similar power of classification, with percentages above 80%, for both groups of variables. The implications of these findings for educational practice are discussed.

Teaching Mathematical Modeling in Mathematics Education

ERIC Educational Resources Information Center

Saxena, Ritu; Shrivastava, Keerty; Bhardwaj, Ramakant

2016-01-01

Mathematics is not only a subject but it is also a language consisting of many different symbols and relations. Taught as a compulsory subject up the 10th class, students are then able to choose whether or not to study mathematics as a main subject. The present paper discusses mathematical modeling in mathematics education. The article provides…

Profiling Student Use of Calculators in the Learning of High School Mathematics

ERIC Educational Resources Information Center

Crowe, Cheryll E.; Ma, Xin

2010-01-01

Using data from the 2005 National Assessment of Educational Progress, students' use of calculators in the learning of high school mathematics was profiled based on their family background, curriculum background, and advanced mathematics coursework. A statistical method new to educational research--classification and regression trees--was applied…

Computer Classification of Triangles and Quadrilaterals--A Challenging Application

ERIC Educational Resources Information Center

Dennis, J. Richard

1978-01-01

Two computer exercises involving the classification of geometric figures are given. The mathematics required is relatively simple but comes from several areas--synthetic geometry, analytic geometry, and linear algebra. (MN)

Crisis in Cataloging Revisited: The Year's Work in Subject Analysis, 1990.

ERIC Educational Resources Information Center

Young, James Bradford

1991-01-01

Reviews the 1990 literature that concerns subject analysis. Issues addressed include subject cataloging, including Library of Congress Subject Headings (LCSH); classification, including Dewey Decimal Classification (DDC), Library of Congress Classification, and classification in online systems; subject access, including the online use of…

Teachers' Choice of Using Practical Activities--A Hierarchical Classification Attempt

ERIC Educational Resources Information Center

Haara, Frode Olav

2015-01-01

From a system theoretically grounded point of view, a hierarchy of primary and secondary impact factors influencing the mathematics teacher's choice to use practical activities in mathematics teaching is suggested initially in the article. A study, based on qualitative responses from mathematics teachers, then gives grounds for suggesting that a…

Classification of microscopic images of breast tissue

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Franzen, Lennart

2004-05-01

Breast cancer is the most common form of cancer among women. The diagnosis is usually performed by the pathologist, that subjectively evaluates tissue samples. The aim of our research is to develop techniques for the automatic classification of cancerous tissue, by analyzing histological samples of intact tissue taken with a biopsy. In our study, we considered 200 images presenting four different conditions: normal tissue, fibroadenosis, ductal cancer and lobular cancer. Methods to extract features have been investigated and described. One method is based on granulometries, which are size-shape descriptors widely used in mathematical morphology. Applications of granulometries lead to distribution functions whose moments are used as features. A second method is based on fractal geometry, that seems very suitable to quantify biological structures. The fractal dimension of binary images has been computed using the euclidean distance mapping. Image classification has then been performed using the extracted features as input of a back-propagation neural network. A new method that combines genetic algorithms and morphological filters has been also investigated. In this case, the classification is based on a correlation measure. Very encouraging results have been obtained with pilot experiments using a small subset of images as training set. Experimental results indicate the effectiveness of the proposed methods. Cancerous tissue was correctly classified in 92.5% of the cases.

What Software to Use in the Teaching of Mathematical Subjects?

ERIC Educational Resources Information Center

Berežný, Štefan

2015-01-01

We can consider two basic views, when using mathematical software in the teaching of mathematical subjects. First: How to learn to use specific software for the specific tasks, e. g., software Statistica for the subjects of Applied statistics, probability and mathematical statistics, or financial mathematics. Second: How to learn to use the…

Incremental Validity of Multidimensional Proficiency Scores from Diagnostic Classification Models: An Illustration for Elementary School Mathematics

ERIC Educational Resources Information Center

Kunina-Habenicht, Olga; Rupp, André A.; Wilhelm, Oliver

2017-01-01

Diagnostic classification models (DCMs) hold great potential for applications in summative and formative assessment by providing discrete multivariate proficiency scores that yield statistically driven classifications of students. Using data from a newly developed diagnostic arithmetic assessment that was administered to 2032 fourth-grade students…

A Taxonomy-Based Approach to Shed Light on the Babel of Mathematical Models for Rice Simulation

NASA Technical Reports Server (NTRS)

Confalonieri, Roberto; Bregaglio, Simone; Adam, Myriam; Ruget, Francoise; Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Buis, Samuel;

Modelling the influence of noise of the image sensor for blood cells recognition in computer microscopy

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.; Nagornov, O. V.; Pronichev, A. N.; Polyakov, E. V.; Dmitrieva, V. V.

2017-12-01

The first stage of diagnostics of blood cancer is the analysis of blood smears. The application of decision-making support systems would reduce the subjectivity of the diagnostic process and avoid errors, resulting in often irreversible changes in the patient's condition. In this regard, the solution of this problem requires the use of modern technology. One of the tools of the program classification of blood cells are texture features, and the task of finding informative among them is promising. The paper investigates the effect of noise of the image sensor to informative texture features with application of methods of mathematical modelling.

IDEAS.

ERIC Educational Resources Information Center

Young, Sharon L.

1991-01-01

Presented are activities that focus on gathering, using, and interpreting data about fingerprints as a basis for integrating mathematics and science. Patterns, classification, logical reasoning, and mathematical relationships are explored by making graphs, classifying fingerprints, and matching identical fingerprints. A parent-involvement activity…

Preservice Teachers' Reconciliation of an Epistemological Issue in an Integrated Mathematics/Science Methods Course

ERIC Educational Resources Information Center

Cormas, Peter C.

2017-01-01

Preservice teachers in six sections (n = 87) of a sequenced, methodological and process-integrated elementary mathematics/science methods course were able to reconcile an issue centered on a similar area of epistemology. Preservice teachers participated in a science inquiry lesson on biological classification and a mathematics problem-solving…

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

DTIC Science & Technology

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

The effect of mathematics games to the student perception of mathematics subject: A case study in Sekolah Kebangsaan Bukit Kuda, Klang

NASA Astrophysics Data System (ADS)

Abdul Hadi, Normi; Mohd Noor, Norlenda; Abd Halim, Suhaila; Alwadood, Zuraida; Khairol Azmi, Nurul Nisa'

2013-04-01

Mathematics is a basic subject in primary and secondary schools. Early exposure to mathematics is very important since it will affect the student perception towards this subject for their entire life. Therefore, a program called 'Mini Hari Matematik' was conducted to expose the basic mathematics concept through some games which fit the knowledge of Standard four and five students. A questionnaire regarding student perception towards this subject was distributed before and after the program. From the analysis, the program has positively changed the student's perception towards mathematics.

Non-Routine Problems in Primary Mathematics Workbooks from Romania

ERIC Educational Resources Information Center

Marchis, Iuliana

2012-01-01

The aim of this paper is to present a research on Hungarian 3th grade primary school textbooks from Romania. These textbooks are analyzed using two classifications. The first classification is based on how much creativity and problem solving skills pupils need to solve a given task. In this classification problems are gouped in three categories:…

Students attitude towards calculus subject: Bumiputera case-study

NASA Astrophysics Data System (ADS)

Awang, Noorehan; Ilias, Mohd Rijal; Che Hussain, Wan Siti Esah; Mokhtar, Siti Fairus

2013-04-01

Mathematics has always become the most dislike subject among other subjects in school. Study showed that attitudes of students in science subjects such as mathematics were closely related to how they solve problems, accessing ideas and making a right decision. According to another study on mathematics achievement of eighth grade students in Malaysia, mathematics grades among bumiputera students was lower when compared to other races such as Chinese and Indians. The poor performance was due to their attitude and pre-conceived ideas towards the subject. Therefore, this study was designed todetermine the criteria and subcriteria that were considered important in measuring students' attitude toward mathematics among the bumiputeras. Factor analysis was carried out to identify the groups among criterion. Instrument used to measure mathematics attitude was Test of Mathematics Related Attitude (TOMRA) which measured student attitudes in four criteria: normality of mathematics, attitudes towards mathematics inquiry, adoption of mathematics attitude and enjoyment of mathematics lessons. The target population of this study was all computer science and quantitative science students who enrolled Calculus subject in UiTM Kedah. Findings shows that there are two criteria that influenced students attitude toward mathematics namely normality of mathematics with eleven subcriteria and enjoyment of mathematics with eight subcriteria. From the analysis it shows that the total percentage of variation explained is 35.071% with 0.837 Cronbach's alpha reliability test. The findings will help the lecturers, parents and society to consider what action should be taken to install interest and positive attitude of bumiputera students towards mathematics and thus improve their achievement.

Data fusion and classification using a hybrid intrinsic cellular inference network

NASA Astrophysics Data System (ADS)

Woodley, Robert; Walenz, Brett; Seiffertt, John; Robinette, Paul; Wunsch, Donald

2010-04-01

Hybrid Intrinsic Cellular Inference Network (HICIN) is designed for battlespace decision support applications. We developed an automatic method of generating hypotheses for an entity-attribute classifier. The capability and effectiveness of a domain specific ontology was used to generate automatic categories for data classification. Heterogeneous data is clustered using an Adaptive Resonance Theory (ART) inference engine on a sample (unclassified) data set. The data set is the Lahman baseball database. The actual data is immaterial to the architecture, however, parallels in the data can be easily drawn (i.e., "Team" maps to organization, "Runs scored/allowed" to Measure of organization performance (positive/negative), "Payroll" to organization resources, etc.). Results show that HICIN classifiers create known inferences from the heterogonous data. These inferences are not explicitly stated in the ontological description of the domain and are strictly data driven. HICIN uses data uncertainty handling to reduce errors in the classification. The uncertainty handling is based on subjective logic. The belief mass allows evidence from multiple sources to be mathematically combined to increase or discount an assertion. In military operations the ability to reduce uncertainty will be vital in the data fusion operation.

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Re/Writing the Subject: A Contribution to Post-Structuralist Theory in Mathematics Education

ERIC Educational Resources Information Center

Roth, Wolff-Michael

2012-01-01

This text, occasioned by a critical reading of "Mathematics Education and Subjectivity" (Brown, "2011") and constituting a response to the book, aims at contributing to the building of (post-structuralist) theory in mathematics education. Its purpose was to re/write two major positions that "Mathematics Education and Subjectivity" articulates:…

Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis.

PubMed

Stephan, Klaas E; Bach, Dominik R; Fletcher, Paul C; Flint, Jonathan; Frank, Michael J; Friston, Karl J; Heinz, Andreas; Huys, Quentin J M; Owen, Michael J; Binder, Elisabeth B; Dayan, Peter; Johnstone, Eve C; Meyer-Lindenberg, Andreas; Montague, P Read; Schnyder, Ulrich; Wang, Xiao-Jing; Breakspear, Michael

2016-01-01

Contemporary psychiatry faces major challenges. Its syndrome-based disease classification is not based on mechanisms and does not guide treatment, which largely depends on trial and error. The development of therapies is hindered by ignorance of potential beneficiary patient subgroups. Neuroscientific and genetics research have yet to affect disease definitions or contribute to clinical decision making. In this challenging setting, what should psychiatric research focus on? In two companion papers, we present a list of problems nominated by clinicians and researchers from different disciplines as candidates for future scientific investigation of mental disorders. These problems are loosely grouped into challenges concerning nosology and diagnosis (this Personal View) and problems related to pathogenesis and aetiology (in the companion Personal View). Motivated by successful examples in other disciplines, particularly the list of Hilbert's problems in mathematics, this subjective and eclectic list of priority problems is intended for psychiatric researchers, helping to re-focus existing research and providing perspectives for future psychiatric science. Copyright © 2016 Elsevier Ltd. All rights reserved.

Digital techniques for processing Landsat imagery

NASA Technical Reports Server (NTRS)

Green, W. B.

1978-01-01

An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

Classification, Seriation, and Counting in Grades 1, 2, and 3 as Two-Year Longitudinal Predictors for Low Achieving in Numerical Facility and Arithmetical Achievement?

ERIC Educational Resources Information Center

Desoete, Annemie; Stock, Pieter; Schepens, Annemie; Baeyens, Dieter; Roeyers, Herbert

2009-01-01

Previous research stresses the importance of seriation, classification, and counting abilities that should be assessed in kindergarten, when looking for crucial predictors of mathematical learning disabilities in Grade 1. This study examines (n = 158) two-year-long predictive relationships between children's seriation, classification, procedural…

Teacher Judgment and Mastery Score Setting for Nebraska's Local Assessment Reporting System: Efficacy and Appropriateness.

ERIC Educational Resources Information Center

Giraud, Gerald T.; Buckendahl, Chad; Lucas, Mike

This study examined the efficacy of teacher judgment in the process of setting mastery scores (cut scores) for fourth-grade mathematics in local school districts in Nebraska in terms of agreement between teacher classification of students and classification by the cut score obtained by this classification. The study also examined cut scores in…

Implementation of several mathematical algorithms to breast tissue density classification

NASA Astrophysics Data System (ADS)

Quintana, C.; Redondo, M.; Tirao, G.

2014-02-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

Reproducibility of neuroimaging analyses across operating systems

PubMed Central

Glatard, Tristan; Lewis, Lindsay B.; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C.

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed. PMID:25964757

Reproducibility of neuroimaging analyses across operating systems.

PubMed

Glatard, Tristan; Lewis, Lindsay B; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed.

Study of the Factors Affecting the Mathematics Achievement of Turkish Students According to Data from the Programme for International Student Assessment (PISA) 2012

ERIC Educational Resources Information Center

Güzeller, Cem Oktay; Eser, Mehmet Taha; Aksu, Gökhan

2016-01-01

This study attempts to determine the factors affecting the mathematics achievement of students in Turkey based on data from the Programme for International Student Assessment 2012 and the correct classification ratio of the established model. The study used mathematics achievement as a dependent variable while sex, having a study room, preparation…

Enhancing student engagement to positively impact mathematics anxiety, confidence and achievement for interdisciplinary science subjects

NASA Astrophysics Data System (ADS)

Everingham, Yvette L.; Gyuris, Emma; Connolly, Sean R.

2017-11-01

Contemporary science educators must equip their students with the knowledge and practical know-how to connect multiple disciplines like mathematics, computing and the natural sciences to gain a richer and deeper understanding of a scientific problem. However, many biology and earth science students are prejudiced against mathematics due to negative emotions like high mathematical anxiety and low mathematical confidence. Here, we present a theoretical framework that investigates linkages between student engagement, mathematical anxiety, mathematical confidence, student achievement and subject mastery. We implement this framework in a large, first-year interdisciplinary science subject and monitor its impact over several years from 2010 to 2015. The implementation of the framework coincided with an easing of anxiety and enhanced confidence, as well as higher student satisfaction, retention and achievement. The framework offers interdisciplinary science educators greater flexibility and confidence in their approach to designing and delivering subjects that rely on mathematical concepts and practices.

Mathematical model of blasting schemes management in mining operations in presence of random disturbances

NASA Astrophysics Data System (ADS)

Kazakova, E. I.; Medvedev, A. N.; Kolomytseva, A. O.; Demina, M. I.

2017-11-01

The paper presents a mathematical model of blasting schemes management in presence of random disturbances. Based on the lemmas and theorems proved, a control functional is formulated, which is stable. A universal classification of blasting schemes is developed. The main classification attributes are suggested: the orientation in plan the charging wells rows relatively the block of rocks; the presence of cuts in the blasting schemes; the separation of the wells series onto elements; the sequence of the blasting. The periodic regularity of transition from one Short-delayed scheme of blasting to another is proved.

Comparison of the performance of first-grade and mentally retarded students on the Peabody Mathematics Readiness Test.

PubMed

Richardson, L I; Thurman, R L; Bassler, O C

1978-07-01

The Peabody Mathematics Readiness Test was developed to assess mathematics readiness and identify children who would encounter difficulty in first-grade mathematics. In the present study, we compared performances of mentally retarded subjects and first-grade subjects on this test. Retarded subjects' mean scores were significantly lower than those of the nonretarded subjects on the drawing test; however, there were no significant differences between the mean scores of the groups on the other five subscales.

Unveiling the South African Official Primary Mathematics Teacher Pedagogic Identity

ERIC Educational Resources Information Center

Pausigere, Peter; Graven, Mellony

2013-01-01

This article is theoretically informed by Bernstein's (2000) notion of pedagogic identity, supplemented by Tyler's (1999) elaboration of Bernstein's theory into an analytical framework that describes four possible identity positions relating to classification and framing properties. The article analyses key primary mathematics curriculum policy…

Classification and disease prediction via mathematical programming

NASA Astrophysics Data System (ADS)

Lee, Eva K.; Wu, Tsung-Lin

2007-11-01

In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80% to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Differentiation chronic post traumatic stress disorder patients from healthy subjects using objective and subjective sleep-related parameters.

PubMed

Tahmasian, Masoud; Jamalabadi, Hamidreza; Abedini, Mina; Ghadami, Mohammad R; Sepehry, Amir A; Knight, David C; Khazaie, Habibolah

2017-05-22

Sleep disturbance is common in chronic post-traumatic stress disorder (PTSD). However, prior work has demonstrated that there are inconsistencies between subjective and objective assessments of sleep disturbance in PTSD. Therefore, we investigated whether subjective or objective sleep assessment has greater clinical utility to differentiate PTSD patients from healthy subjects. Further, we evaluated whether the combination of subjective and objective methods improves the accuracy of classification into patient versus healthy groups, which has important diagnostic implications. We recruited 32 chronic war-induced PTSD patients and 32 age- and gender-matched healthy subjects to participate in this study. Subjective (i.e. from three self-reported sleep questionnaires) and objective sleep-related data (i.e. from actigraphy scores) were collected from each participant. Subjective, objective, and combined (subjective and objective) sleep data were then analyzed using support vector machine classification. The classification accuracy, sensitivity, and specificity for subjective variables were 89.2%, 89.3%, and 89%, respectively. The classification accuracy, sensitivity, and specificity for objective variables were 65%, 62.3%, and 67.8%, respectively. The classification accuracy, sensitivity, and specificity for the aggregate variables (combination of subjective and objective variables) were 91.6%, 93.0%, and 90.3%, respectively. Our findings indicate that classification accuracy using subjective measurements is superior to objective measurements and the combination of both assessments appears to improve the classification accuracy for differentiating PTSD patients from healthy individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

Towards a Bernsteinian Language of Description for Mathematics Classroom Discourse

ERIC Educational Resources Information Center

Straehler-Pohl, Hauke; Gellert, Uwe

2013-01-01

This article aims at developing an external language of description to investigate the problem of why particular groups of students are systematically not provided access to school mathematical knowledge. Based on Basil Bernstein's conceptualisation of power in classification, we develop a three-dimensional model that operationalises the…

Dedication: Major M. Goodman, Maize Breeder and Geneticist

USDA-ARS?s Scientific Manuscript database

Major M. Goodman is the leading expert on the classification and use of the diverse genetic resources of maize. He pioneered the development and use of mathematical approaches to classification of diverse plant materials; had a primary role in the development of one of the first comprehensive plant ...

Harmonic oscillator states in aberration optics

NASA Technical Reports Server (NTRS)

Wolf, Kurt Bernardo

1993-01-01

The states of the three-dimensional quantum harmonic oscillator classify optical aberrations of axis-symmetric systems due to the isomorphism between the two mathematical structures. Cartesian quanta and angular momentum classifications have their corresponding aberration classifications. The operation of concatenation of optical elements introduces a new operation between harmonic oscillator states.

Analogical Reasoning in Geometry Education

ERIC Educational Resources Information Center

Magdas, Ioana

2015-01-01

The analogical reasoning isn't used only in mathematics but also in everyday life. In this article we approach the analogical reasoning in Geometry Education. The novelty of this article is a classification of geometrical analogies by reasoning type and their exemplification. Our classification includes: analogies for understanding and setting a…

Circulation Type Classifications and their nexus to Van Bebber's storm track Vb

NASA Astrophysics Data System (ADS)

Hofstätter, M.; Chimani, B.

2012-04-01

Circulation Type Classifications (CTCs) are tools to identify repetitive and predominantly stationary patterns of the atmospheric circulation over a certain area, with the purpose to enable the recognition of specific characteristics in surface climate variables. On the other hand storm tracks can be used to identify similar types of synoptic events from a non-stationary, kinematic perspective. Such a storm track classification for Europe has been done in the late 19th century by Van Bebber (1882, 1891), from which the famous type Vb and Vc/d remained up to the present day because of to their association with major flooding events like in August 2002 in Europe. In this work a systematic tracking procedure has been developed, to determine storm track types and their characteristics especially for the Eastern Alpine Region in the period 1961-2002, using ERA40 and ERAinterim reanalysis. The focus thereby is on cyclone tracks of type V as suggested by van Bebber and congeneric types. This new catalogue is used as a reference to verify the hypothesis of a certain coherence of storm track Vb with certain circulation types (e.g. Fricke and Kaminski, 2002). Selected objective and subjective classification schemes from the COST733 action (http://cost733.met.no/, Phillip et al. 2010) are used therefore, as well as the manual classification from ZAMG (Lauscher 1972 and 1985), in which storm track Vb has been classified explicitly on a daily base since 1948. The latter scheme should prove itself as a valuable and unique data source in that issue. Results show that not less than 146 storm tracks are identified as Vb between 1961 and 2002, whereas only three events could be found from literature, pointing to big subjectivity and preconception in the issue of Vb storm tracks. The annual number of Vb storm tracks do not show any significant trend over the last 42 years, but large variations from year to year. Circulation type classification CAP27 (Cluster Analysis of Principal Components) is the best performing, fully objective scheme tested herein, showing the power to discriminate Vb events. Most of the other fully objective schemes do by far not perform as well. Largest skill in that issue can be seen from the subjective/manual CTCs, proving themselves to enhance relevant synoptic phenomena instead of emphasizing mathematic criteria in the classification. The hypothesis of Fricke and Kaminsky can definitely be supported by this work: Vb storm tracks are included in one or the other stationary circulation pattern, but to which extent depends on the specific characteristics of the CTC in question.

Students' perception and relationship between confidence and anxiety in teaching and learning mathematics: A case study in Sekolah Kebangsaan Bukit Kuda, Klang

NASA Astrophysics Data System (ADS)

Mohd Nordin, Noraimi Azlin; Md Tahir, Herniza; Kamis, Nor Hanimah; Khairul Azmi, Nurul Nisa'

2013-04-01

In general, Mathematics is one of the core subjects need to be learned by students regardless they are in primary and secondary schools. Different students might have different views and interests on Mathematics subjects. This is due to different level of thinking for each student. Students' acceptance and confidence level in learning Mathematics will depend on various factors among them. A program named "Mini Hari Matematik" was conducted in Sekolah Rendah Kebangsaan Bukit Kuda, Klang exclusively for 49 students of standard four, five and six to identify the students' perception and correlation between their confidence and anxiety in learning Mathematics. This program was intended to give exposure to the students on the importance of Mathematics in life and hence, develop their interest in learning Mathematics. We measure the students' perception on teaching and learning Mathematics using statistical approach based on SPSS. The analysis includes mean, variance, observations, correlation and so on. Based on the results obtained, it is found that there is a positive correlation between students' confidence and anxiety in learning Mathematics in their daily life. In addition, students are more attracted to Mathematics if this subject is blended with game elements in their teaching and learning process. As a conclusion, we can see that there are three basic foundations need to be developed in each of the students about Mathematics which are firstly, their early understanding on the subject itself, ability to communicate regarding this subject and how they apply this subject in decision making and problem solving. This program gives high benefit to the students in preparing them towards the science and technology era.

Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.

PubMed

Gurbaxani, Brian M; Jones, James F; Goertzel, Benjamin N; Maloney, Elizabeth M

2006-04-01

To provide a mathematical introduction to the Wichita (KS, USA) clinical dataset, which is all of the nongenetic data (no microarray or single nucleotide polymorphism data) from the 2-day clinical evaluation, and show the preliminary findings and limitations, of popular, matrix algebra-based data mining techniques. An initial matrix of 440 variables by 227 human subjects was reduced to 183 variables by 164 subjects. Variables were excluded that strongly correlated with chronic fatigue syndrome (CFS) case classification by design (for example, the multidimensional fatigue inventory [MFI] data), that were otherwise self reporting in nature and also tended to correlate strongly with CFS classification, or were sparse or nonvarying between case and control. Subjects were excluded if they did not clearly fall into well-defined CFS classifications, had comorbid depression with melancholic features, or other medical or psychiatric exclusions. The popular data mining techniques, principle components analysis (PCA) and linear discriminant analysis (LDA), were used to determine how well the data separated into groups. Two different feature selection methods helped identify the most discriminating parameters. Although purely biological features (variables) were found to separate CFS cases from controls, including many allostatic load and sleep-related variables, most parameters were not statistically significant individually. However, biological correlates of CFS, such as heart rate and heart rate variability, require further investigation. Feature selection of a limited number of variables from the purely biological dataset produced better separation between groups than a PCA of the entire dataset. Feature selection highlighted the importance of many of the allostatic load variables studied in more detail by Maloney and colleagues in this issue [1] , as well as some sleep-related variables. Nonetheless, matrix linear algebra-based data mining approaches appeared to be of limited utility when compared with more sophisticated nonlinear analyses on richer data types, such as those found in Maloney and colleagues [1] and Goertzel and colleagues [2] in this issue.

Language Issues in Teaching and Learning of Mathematics

ERIC Educational Resources Information Center

Nath, Baiju. K.; V., Vineesha

2009-01-01

Today as in the past, many students struggle with mathematics and become affected as they continually encounter obstacles to engagement. Mathematics is generally seen as a difficult subject and how this subject is communicated to pupils will influence how pupils learn the subject. Classroom routines play an important role in developing students'…

Topological Classification of Crystalline Insulators through Band Structure Combinatorics

NASA Astrophysics Data System (ADS)

Kruthoff, Jorrit; de Boer, Jan; van Wezel, Jasper; Kane, Charles L.; Slager, Robert-Jan

2017-10-01

We present a method for efficiently enumerating all allowed, topologically distinct, electronic band structures within a given crystal structure in all physically relevant dimensions. The algorithm applies to crystals without time-reversal, particle-hole, chiral, or any other anticommuting or anti-unitary symmetries. The results presented match the mathematical structure underlying the topological classification of these crystals in terms of K -theory and therefore elucidate this abstract mathematical framework from a simple combinatorial perspective. Using a straightforward counting procedure, we classify all allowed topological phases of spinless particles in crystals in class A . Employing this classification, we study transitions between topological phases within class A that are driven by band inversions at high-symmetry points in the first Brillouin zone. This enables us to list all possible types of phase transitions within a given crystal structure and to identify whether or not they give rise to intermediate Weyl semimetallic phases.

Classification of self-assembling protein nanoparticle architectures for applications in vaccine design

NASA Astrophysics Data System (ADS)

Indelicato, G.; Burkhard, P.; Twarock, R.

2017-04-01

We introduce here a mathematical procedure for the structural classification of a specific class of self-assembling protein nanoparticles (SAPNs) that are used as a platform for repetitive antigen display systems. These SAPNs have distinctive geometries as a consequence of the fact that their peptide building blocks are formed from two linked coiled coils that are designed to assemble into trimeric and pentameric clusters. This allows a mathematical description of particle architectures in terms of bipartite (3,5)-regular graphs. Exploiting the relation with fullerene graphs, we provide a complete atlas of SAPN morphologies. The classification enables a detailed understanding of the spectrum of possible particle geometries that can arise in the self-assembly process. Moreover, it provides a toolkit for a systematic exploitation of SAPNs in bioengineering in the context of vaccine design, predicting the density of B-cell epitopes on the SAPN surface, which is critical for a strong humoral immune response.

Host - HIF- 1alpha Pathway And Hypoxia: In Vitro Studies And Mathematical Model

DTIC Science & Technology

2016-08-30

TERMS mathematical model, signaling pathways, hypoxia, immunohistochemistry, ELISA , inhalation chamber 16. SECURITY CLASSIFICATION OF: U 17...B. HIF-1α ELISA Procedure ........................................................................................27 Appendix C. HIF-1α Model...Quantifying Induction of HIF-1α Expression using ELISA .........................................15 Figure 10. Simulation Outputs from HIF-1α Kinetic

Analysis and Classification of Entering Freshmen Mathematic Students Using Multiple Discriminate Function Analysis.

ERIC Educational Resources Information Center

Ahrens, Steve

Predictor variables that could be used effectively to place entering freshmen methematics students into courses of instruction in mathematics were investigated at West Virginia University. Multiple discriminant analysis was used with nearly 6,000 student records collected over a three-year period, and a series of predictive equations were…

75 FR 7272 - Agency Information Collection Activities; Submission for Office of Management and Budget Review...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-18

...,880). This is a one-time cost for a computer or mathematic employees to design and prepare a report... Occupational Classification 15-0000, computer and mathematics occupations, all industries; we add 40 percent to... believes that manufacturers of animal drugs already possess the computers, software, and additional...

Matched field localization based on CS-MUSIC algorithm

NASA Astrophysics Data System (ADS)

Guo, Shuangle; Tang, Ruichun; Peng, Linhui; Ji, Xiaopeng

2016-04-01

The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered. A matched field localization algorithm based on CS-MUSIC (Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning. The signal matrix is calculated through the SVD (Singular Value Decomposition) of the observation matrix. The observation matrix in the sparse mathematical model is replaced by the signal matrix, and a new concise sparse mathematical model is obtained, which means not only the scale of the localization problem but also the noise level is reduced; then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS (Compressive Sensing) method and MUSIC (Multiple Signal Classification) method. The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots, and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large, which will be proved in this paper.

Gender classification under extended operating conditions

NASA Astrophysics Data System (ADS)

Rude, Howard N.; Rizki, Mateen

2014-06-01

Gender classification is a critical component of a robust image security system. Many techniques exist to perform gender classification using facial features. In contrast, this paper explores gender classification using body features extracted from clothed subjects. Several of the most effective types of features for gender classification identified in literature were implemented and applied to the newly developed Seasonal Weather And Gender (SWAG) dataset. SWAG contains video clips of approximately 2000 samples of human subjects captured over a period of several months. The subjects are wearing casual business attire and outer garments appropriate for the specific weather conditions observed in the Midwest. The results from a series of experiments are presented that compare the classification accuracy of systems that incorporate various types and combinations of features applied to multiple looks at subjects at different image resolutions to determine a baseline performance for gender classification.

The Cognitive Differences According to Regionality and Mathematical Minds

NASA Astrophysics Data System (ADS)

Park, Inchan; Igarashi, Hiroya; Yamanaka, Toshimasa

The purpose of this research is to explore factors that create cognitive diversity. We studied two different ways of recognizing images in our preliminary experiment: attribute-oriented thoughts and relationship-oriented thoughts. We examined whether we could observe the divergences in recognition processes between Asian and European cultures. From the result, we found that European (Dutch and British) subjects had stronger tendencies in attribute-oriented thoughts than the Korean subjects. However, in spite of their regional similarity, the Japanese subjects had greater tendencies in attribute-oriented thoughts than Korean subjects when comparing two Asian countries. This result made us question if there would be any other factors that could create the cognitive differences. Through the consideration of the participants' educational background, we found a possibility that the mathematical thoughts of the European and Japanese subjects were greater than the Korean subjects. Furthermore, in our subsequent study, we discovered that mathematical minds (skill and interest) effected on creating attribute-oriented thoughts as factors. We found the interesting discovery of the Japanese male participants, who had different cognitive tendencies with their mathematical skills and interests; the male subjects who had high-leveled mathematical skills, and who liked mathematics showed stronger tendencies of Attribute-oriented thoughts than those who did not. Based on the result, a possibility was suggested that the Japanese males' strong mathematical minds might be one of the factors that create the cognitive difference between Japanese and Korean subjects in the preliminary experiment.

Modeling the Time-Varying Nature of Student Exceptionality Classification on Achievement Growth

ERIC Educational Resources Information Center

Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N.

2017-01-01

Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…

The written mathematical communication profile of prospective math teacher in mathematical proving

NASA Astrophysics Data System (ADS)

Pantaleon, K. V.; Juniati, D.; Lukito, A.; Mandur, K.

2018-01-01

Written mathematical communication is the process of expressing mathematical ideas and understanding in writing. It is one of the important aspects that must be mastered by the prospective math teacher as tool of knowledge transfer. This research was a qualitative research that aimed to describe the mathematical communication profile of the prospective mathematics teacher in mathematical proving. This research involved 48 students of Mathematics Education Study Program; one of them with moderate math skills was chosen as the main subject. Data were collected through tests, assignments, and task-based interviews. The results of this study point out that in the proof of geometry, the subject explains what is understood, presents the idea in the form of drawing and symbols, and explains the content/meaning of a representation accurately and clearly, but the subject can not convey the argument systematically and logically. Whereas in the proof of algebra, the subject describes what is understood, explains the method used, and describes the content/meaning of a symbolic representation accurately, systematically, logically, but the argument presented is not clear because it is insufficient detailed and complete.

Mathematics deficits in adolescents with bipolar I disorder.

PubMed

Lagace, Diane C; Kutcher, Stanley P; Robertson, Heather A

2003-01-01

This study examined mathematical ability in adolescents with bipolar I disorder, compared to adolescents with major depressive disorder and psychiatrically healthy comparison subjects. Participants (N=119) included adolescents in remission from bipolar disorder (N=44) or major depressive disorder (N=30), as well as comparison subjects (N=45) with no psychiatric history. Participants were assessed with the following measures: the Wide-Range Achievement Test, Revised 2 (WRAT-R2), Peabody Individual Achievement Test, Bay Area Functional Performance Evaluation Task-Oriented Assessment (functional mathematics subtest), Test of Nonverbal Intellegence-2, and a self-report of mathematics performance. WRAT-R2 and Peabody Individual Achievement Test scores for spelling, mathematics, and reading revealed that adolescents with bipolar disorder had significantly lower achievement in mathematics, compared to subjects with major depressive disorder and comparison subjects. Results for the Test of Nonverbal Intellegence-2 were not significantly different between groups. Adolescents with bipolar disorder took significantly longer to complete the Bay Area Functional Performance Evaluation mathematics task. Significantly fewer adolescents with bipolar disorder (9%) reported above-average mathematics performance, compared with the other groups. Adolescents with remitted bipolar disorder have a specific profile of mathematics difficulties that differentiates them from both adolescents with unipolar depression and psychiatrically healthy comparison subjects. These mathematics deficits may not derive simply from more global deficits in nonverbal intelligence or executive functioning, but may be associated with neuroanatomical abnormalities that result in cognitive deficits, including a slowed response time. These deficits suggest the need for specialized assessment of mathematics as part of a comprehensive clinical follow-up treatment plan.

Analysis of a Bibliographic Database Enhanced with a Library Classification.

ERIC Educational Resources Information Center

Drabenstott, Karen Markey; And Others

1990-01-01

Describes a project that examined the effects of incorporating subject terms from the Dewey Decimal Classification (DDC) into a bibliographic database. It is concluded that the incorporation of DDC and possibly other library classifications into online catalogs can enhance subject access and provide additional subject searching strategies. (11…

Children thinking mathematically beyond authoritative identities

NASA Astrophysics Data System (ADS)

MacMillan, Agnes

1995-10-01

A study into the mathematics-related interactions and developing attitudes of young children during the transition period between pre-school and school is reported. Transcripts of interactions during a six-week observation period in one of two preschool sites are coded according to the classifications defined within a theoretical framework. Two separate episodes of construction play were analysed and one of these is used to examine the mathematical nature of the children's interactions within an emerging model of autonomous learning. The results of the analysis indicate that access to self-regulatory social relations is very closely linked to the accessibility of mathematical meanings.

Does CAS Use Disadvantage Girls in VCE Mathematics?

ERIC Educational Resources Information Center

Forgasz, Helen; Tan, Hazel

2010-01-01

In 2009, four mathematics subjects were offered at the year 12 level in the Victorian Certificate of Education (VCE). The two subjects at the intermediate level--Mathematical Methods and Mathematical Methods CAS--run in parallel, that is, a student can be enrolled in only one or the other, the choice being made at the school level. The curricular…

Bayesian classification theory

NASA Technical Reports Server (NTRS)

Hanson, Robin; Stutz, John; Cheeseman, Peter

1991-01-01

The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework and using various mathematical and algorithmic approximations, the AutoClass system searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit or share model parameters though a class hierarchy. We summarize the mathematical foundations of AutoClass.

Technical Subjects. Mathematics. Science. Curriculum RP-27.

ERIC Educational Resources Information Center

Ontario Dept. of Education, Toronto.

GRADES OR AGES: Grades 9-12. SUBJECT MATTER: Technical subjects and special mathematics and science courses for technical students. Technical subjects include air conditioning, auto mechanics, carpentry, drafting, applied electronics, masonry, painting, plumbing, service station operation, welding, and woodworking. ORGANIZATION AND PHYSICAL…

Accountability as a Design for Teacher Learning: Sensemaking about Mathematics and Equity in the NCLB Era

ERIC Educational Resources Information Center

Horn, Ilana Seidel

2018-01-01

Using a learning design perspective on No Child Left Behind (NCLB), I examine how accountability policy shaped urban educators' instructional sensemaking. Focusing on the role of policy-rooted classifications, I examine conversations from a middle school mathematics teacher team as a "best case" because they worked diligently to comply…

Improving of prospective elementary teachers' reasoning: Learning geometry through mathematical investigation

NASA Astrophysics Data System (ADS)

Sumarna, Nana; Sentryo, Izlan

2017-08-01

This research applies mathematical investigation approach in teaching geometry to improve mathematical reasoning abilities of prospective elementary teachers. Mathematical investigation in this study involved non-routine tasks through a mathematical investigation process, namely through a series of activities as an attribute of mathematical investigation. Developing the ability of mathematical reasoning of research subjects obtained through capability of research subjects in the analysis, generalization, synthesis, justify, and resolve non-routine, which is operationally constructed as an indicator of research and is used as a criterion for measuring the ability of mathematical reasoning. Research design using Quasi-Experimental design. Based on this type, the researchers apply a pre-and posttest design, which is divided into two study groups: control group and the treatment group. The number of research subjects were 111 students consisting of 56 students in the experimental group and 55 students in the control group. The conclusion of this study stated that (1) Investigation of mathematics as an approach to learning is able to give a positive response to the increasing ability of mathematical reasoning, and (2) There is no interaction effect of the factors of learning and prior knowledge of mathematics to the increased ability of mathematical reasoning.

Pharmacy students' perceptions of natural science and mathematics subjects.

PubMed

Prescott, Julie; Wilson, Sarah Ellen; Wan, Kai-Wai

2014-08-15

To determine the level of importance pharmacy students placed on science and mathematics subjects for pursuing a career in pharmacy. Two hundred fifty-four students completed a survey instrument developed to investigate students' perceptions of the relevance of science and mathematics subjects to a career in pharmacy. Pharmacy students in all 4 years of a master of pharmacy (MPharm) degree program were invited to complete the survey instrument. Students viewed chemistry-based and biology-based subjects as relevant to a pharmacy career, whereas mathematics subjects such as physics, logarithms, statistics, and algebra were not viewed important to a career in pharmacy. Students' experience in pharmacy and year of study influenced their perceptions of subjects relevant to a pharmacy career. Pharmacy educators need to consider how they can help students recognize the importance of scientific knowledge earlier in the pharmacy curriculum.

Exploring the Impact of a Standards-Based Mathematics and Pedagogy Class on Preservice Teachers' Beliefs and Subject Matter Knowledge

ERIC Educational Resources Information Center

Stohlmann, Micah Stephen

2012-01-01

This case study explored the impact of a standards-based mathematics and pedagogy class on preservice elementary teachers' beliefs and conceptual subject matter knowledge of linear functions. The framework for the standards-based mathematics and pedagogy class in this study involved the National Council of Teachers of Mathematics Standards,…

Investigating adaptive reasoning and strategic competence: Difference male and female

NASA Astrophysics Data System (ADS)

Syukriani, Andi; Juniati, Dwi; Siswono, Tatag Yuli Eko

2017-08-01

The series of adaptive reasoning and strategic competencies represent the five components of mathematical proficiency to describe the students' mathematics learning success. Gender contribute to the problem-solving process. This qualitative research approach investigated the adaptive reasoning and strategic competence aspects of a male student and a female student when they solved mathematical problem. They were in the eleventh grade of high school in Makassar. Both also had similar mathematics ability and were in the highest category. The researcher as the main instrument used secondary instrument to obtain the appropriate subject and to investigate the aspects of adaptive reasoning and strategic competence. Test of mathematical ability was used to locate the subjects with similar mathematical ability. The unstructured guideline interview was used to investigate aspects of adaptive reasoning and strategic competence when the subject completed the task of mathematical problem. The task of mathematical problem involves several concepts as the right solution, such as the circle concept, triangle concept, trigonometry concept, and Pythagoras concept. The results showed that male and female subjects differed in applying a strategy to understand, formulate and represent the problem situation. Furthermore, both also differed in explaining the strategy used and the relationship between concepts and problem situations.

The Implementation of APIQ Creative Mathematics Game Method in the Subject Matter of Greatest Common Factor and Least Common Multiple in Elementary School

NASA Astrophysics Data System (ADS)

Rahman, Abdul; Saleh Ahmar, Ansari; Arifin, A. Nurani M.; Upu, Hamzah; Mulbar, Usman; Alimuddin; Arsyad, Nurdin; Ruslan; Rusli; Djadir; Sutamrin; Hamda; Minggi, Ilham; Awi; Zaki, Ahmad; Ahmad, Asdar; Ihsan, Hisyam

2018-01-01

One of causal factors for uninterested feeling of the students in learning mathematics is a monotonous learning method, like in traditional learning method. One of the ways for motivating students to learn mathematics is by implementing APIQ (Aritmetika Plus Intelegensi Quantum) creative mathematics game method. The purposes of this research are (1) to describe students’ responses toward the implementation of APIQ creative mathematics game method on the subject matter of Greatest Common Factor (GCF) and Least Common Multiple (LCM) and (2) to find out whether by implementing this method, the student’s learning completeness will improve or not. Based on the results of this research, it is shown that the responses of the students toward the implementation of APIQ creative mathematics game method in the subject matters of GCF and LCM were good. It is seen in the percentage of the responses were between 76-100%. (2) The implementation of APIQ creative mathematics game method on the subject matters of GCF and LCM improved the students’ learning.

Mathematical visualization process of junior high school students in solving a contextual problem based on cognitive style

NASA Astrophysics Data System (ADS)

Utomo, Edy Setiyo; Juniati, Dwi; Siswono, Tatag Yuli Eko

2017-08-01

The aim of this research was to describe the mathematical visualization process of Junior High School students in solving contextual problems based on cognitive style. Mathematical visualization process in this research was seen from aspects of image generation, image inspection, image scanning, and image transformation. The research subject was the students in the eighth grade based on GEFT test (Group Embedded Figures Test) adopted from Within to determining the category of cognitive style owned by the students namely field independent or field dependent and communicative. The data collection was through visualization test in contextual problem and interview. The validity was seen through time triangulation. The data analysis referred to the aspect of mathematical visualization through steps of categorization, reduction, discussion, and conclusion. The results showed that field-independent and field-dependent subjects were difference in responding to contextual problems. The field-independent subject presented in the form of 2D and 3D, while the field-dependent subject presented in the form of 3D. Both of the subjects had different perception to see the swimming pool. The field-independent subject saw from the top, while the field-dependent subject from the side. The field-independent subject chose to use partition-object strategy, while the field-dependent subject chose to use general-object strategy. Both the subjects did transformation in an object rotation to get the solution. This research is reference to mathematical curriculum developers of Junior High School in Indonesia. Besides, teacher could develop the students' mathematical visualization by using technology media or software, such as geogebra, portable cabri in learning.

A Cryptological Way of Teaching Mathematics

ERIC Educational Resources Information Center

Caballero-Gil, Pino; Bruno-Castaneda, Carlos

2007-01-01

This work addresses the subject of mathematics education at secondary schools from a current and stimulating point of view intimately related to computational science. Cryptology is a captivating way of introducing into the classroom different mathematical subjects such as functions, matrices, modular arithmetic, combinatorics, equations,…

Pharmacy Students’ Perceptions of Natural Science and Mathematics Subjects

PubMed Central

Wilson, Sarah Ellen; Wan, Kai-Wai

2014-01-01

Objective. To determine the level of importance pharmacy students placed on science and mathematics subjects for pursuing a career in pharmacy. Method. Two hundred fifty-four students completed a survey instrument developed to investigate students’ perceptions of the relevance of science and mathematics subjects to a career in pharmacy. Pharmacy students in all 4 years of a master of pharmacy (MPharm) degree program were invited to complete the survey instrument. Results. Students viewed chemistry-based and biology-based subjects as relevant to a pharmacy career, whereas mathematics subjects such as physics, logarithms, statistics, and algebra were not viewed important to a career in pharmacy. Conclusion. Students’ experience in pharmacy and year of study influenced their perceptions of subjects relevant to a pharmacy career. Pharmacy educators need to consider how they can help students recognize the importance of scientific knowledge earlier in the pharmacy curriculum. PMID:25147390

Gender Difference Added? Institutional Variations in the Gender Gap in First Class Degree Awards in Mathematical Sciences

ERIC Educational Resources Information Center

Simonite, Vanessa

2005-01-01

This article shows how multilevel modelling can be used to study institutional variations in the gender differences in achievement. The results presented are from analyses of the degree classifications of 22,433 individuals who graduated in mathematical sciences, from universities in the UK, between 1994/95 and 1999/2000. The analyses were…

Problem-Posing Strategies Used by Years 8 and 9 Students

ERIC Educational Resources Information Center

Stoyanova, Elena

2005-01-01

According to Kilpatrick (1987), in the mathematics classrooms problem posing can be applied as a "goal" or as a means of instruction. Using problem posing as a goal of instruction involves asking students to respond to a range of problem-posing prompts. The main goal of this article is a classification of mathematics questions created by Years 8…

Computational Typologies of Multidimensional End-of-Primary-School Performance Profiles from an Educational Perspective of Large-Scale TIMSS and PIRLS Surveys

ERIC Educational Resources Information Center

Unlu, Ali; Schurig, Michael

2015-01-01

Recently, performance profiles in reading, mathematics and science were created using the data collectively available in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS) 2011. In addition, a classification of children to the end of their primary school years was…

A mathematical analysis of the ABCD criteria for diagnosing malignant melanoma

NASA Astrophysics Data System (ADS)

Lee, Hyunju; Kwon, Kiwoon

2017-03-01

The medical community currently employs the ABCD (asymmetry, border irregularity, color variegation, and diameter of the lesion) criteria in the early diagnosis of a malignant melanoma. Although many image segmentation and classification methods are used to analyze the ABCD criteria, it is rare to see a study containing mathematical justification of the parameters that are used to quantify the ABCD criteria. In this paper, we suggest new parameters to assess asymmetry, border irregularity, and color variegation, and explain the mathematical meaning of the parameters. The suggested parameters are then tested with 24 skin samples. The parameters suggested for the 24 skin samples are displayed in three-dimensional coordinates and are compared to those presented in other studies (Ercal et al 1994 IEEE Trans. Biomed. Eng. 41 837-45, Cheerla and Frazier 2014 Int. J. Innovative Res. Sci., Eng. Technol. 3 9164-83) in terms of Pearson correlation coefficient and classification accuracy in determining the malignancy of the lesions.

Victorian Certificate of Education: Mathematics, Science and Gender

ERIC Educational Resources Information Center

Cox, Peter J.; Leder, Gilah C.; Forgasz, Helen J.

2004-01-01

Gender differences in participation and performance at "high stakes" examinations have received much public attention, which has often focused on mathematics and science subjects. This paper describes the innovative forms of assessment introduced into mathematics and science subjects within the Victorian Certificate of Education (VCE)…

75 FR 18170 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-09

... subject areas, such as mathematics, reading, writing, science, U.S. history, civics, geography, economics... 4, 8, and 12 core (demographic) and subject-specific (reading (4, 8), mathematics (4, 8), science (8..., reading, mathematics, and science components); and grades 4 and 8 school questionnaires (core, reading...

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Data-driven heterogeneity in mathematical learning disabilities based on the triple code model.

PubMed

Peake, Christian; Jiménez, Juan E; Rodríguez, Cristina

2017-12-01

Many classifications of heterogeneity in mathematical learning disabilities (MLD) have been proposed over the past four decades, however no empirical research has been conducted until recently, and none of the classifications are derived from Triple Code Model (TCM) postulates. The TCM proposes MLD as a heterogeneous disorder, with two distinguishable profiles: a representational subtype and a verbal subtype. A sample of elementary school 3rd to 6th graders was divided into two age cohorts (3rd - 4th grades, and 5th - 6th grades). Using data-driven strategies, based on the cognitive classification variables predicted by the TCM, our sample of children with MLD clustered as expected: a group with representational deficits and a group with number-fact retrieval deficits. In the younger group, a spatial subtype also emerged, while in both cohorts a non-specific cluster was produced whose profile could not be explained by this theoretical approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Landscape classification: research progress and development trend].

PubMed

Liang, Fa-Chao; Liu, Li-Ming

2011-06-01

Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

The number of reduced alignments between two DNA sequences

PubMed Central

2014-01-01

Background In this study we consider DNA sequences as mathematical strings. Total and reduced alignments between two DNA sequences have been considered in the literature to measure their similarity. Results for explicit representations of some alignments have been already obtained. Results We present exact, explicit and computable formulas for the number of different possible alignments between two DNA sequences and a new formula for a class of reduced alignments. Conclusions A unified approach for a wide class of alignments between two DNA sequences has been provided. The formula is computable and, if complemented by software development, will provide a deeper insight into the theory of sequence alignment and give rise to new comparison methods. AMS Subject Classification Primary 92B05, 33C20, secondary 39A14, 65Q30 PMID:24684679

[Impacts of multicomponent environment on solubility of puerarin in biopharmaceutics classification system of Chinese materia medica].

PubMed

Hou, Cheng-Bo; Wang, Guo-Peng; Zhang, Qiang; Yang, Wen-Ning; Lv, Bei-Ran; Wei, Li; Dong, Ling

2014-12-01

To illustrate the solubility involved in biopharmaceutics classification system of Chinese materia medica (CMMBCS) , the influences of artificial multicomponent environment on solubility were investigated in this study. Mathematical model was built to describe the variation trend of their influence on the solubility of puerarin. Carried out with progressive levels, single component environment: baicalin, berberine and glycyrrhizic acid; double-component environment: baicalin and glycyrrhizic acid, baicalin and berberine and glycyrrhizic acid and berberine; and treble-component environment: baicalin, berberin, glycyrrhizic acid were used to describe the variation tendency of their influences on the solubility of puerarin, respectively. And then, the mathematical regression equation model was established to characterize the solubility of puerarin under multicomponent environment.

Autoclass: An automatic classification system

NASA Technical Reports Server (NTRS)

Stutz, John; Cheeseman, Peter; Hanson, Robin

1991-01-01

The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework, and using various mathematical and algorithmic approximations, the AutoClass System searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit, or share, model parameters through a class hierarchy. The mathematical foundations of AutoClass are summarized.

Adaptive sleep-wake discrimination for wearable devices.

PubMed

Karlen, Walter; Floreano, Dario

2011-04-01

Sleep/wake classification systems that rely on physiological signals suffer from intersubject differences that make accurate classification with a single, subject-independent model difficult. To overcome the limitations of intersubject variability, we suggest a novel online adaptation technique that updates the sleep/wake classifier in real time. The objective of the present study was to evaluate the performance of a newly developed adaptive classification algorithm that was embedded on a wearable sleep/wake classification system called SleePic. The algorithm processed ECG and respiratory effort signals for the classification task and applied behavioral measurements (obtained from accelerometer and press-button data) for the automatic adaptation task. When trained as a subject-independent classifier algorithm, the SleePic device was only able to correctly classify 74.94 ± 6.76% of the human-rated sleep/wake data. By using the suggested automatic adaptation method, the mean classification accuracy could be significantly improved to 92.98 ± 3.19%. A subject-independent classifier based on activity data only showed a comparable accuracy of 90.44 ± 3.57%. We demonstrated that subject-independent models used for online sleep-wake classification can successfully be adapted to previously unseen subjects without the intervention of human experts or off-line calibration.

"Being Good" at Maths: Fabricating Gender Subjectivity

ERIC Educational Resources Information Center

Chronaki, Anna; Pechtelidis, Yannis

2012-01-01

Current research in mathematics education places emphasis on the analysis of men and women's accounts about their life trajectories and choices for studying, working and developing a career that involves the learning and teaching of mathematics. Within this realm, the present study aims to highlight how mathematics, gender and subjectivity become…

A Protocol-Analytic Study of Metacognition in Mathematical Problem Solving.

ERIC Educational Resources Information Center

Cai, Jinfa

1994-01-01

Metacognitive behaviors of subjects having high (n=2) and low (n=2) levels of mathematical experience were compared across four cognitive processes in mathematical problem solving: orientation, organization, execution, and verification. High-experience subjects engaged in self-regulation and spent more time on orientation and organization. (36…

Discrete Mathematics and Its Applications

ERIC Educational Resources Information Center

Oxley, Alan

2010-01-01

The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…

Categorization and analysis of explanatory writing in mathematics

NASA Astrophysics Data System (ADS)

Craig, Tracy S.

2011-10-01

The aim of this article is to present a scheme for coding and categorizing students' written explanations of mathematical problem-solving activities. The scheme was used successfully within a study project carried out to determine whether student problem-solving behaviour could be positively affected by writing explanatory strategies to mathematical problem-solving processes. The rationale for the study was the recognized importance of mathematical problem-solving, the widely acknowledged challenge of teaching problem-solving skills directly and the evidence in the literature that writing in mathematics provides a tool for learning. The study was carried out in a first-year mathematics course at the University of Cape Town, South Africa. Students' written submissions were categorized and analysed through use of an adaptation of a journal entry classification scheme. The scheme successfully observed positive changes over the experimental period in students' level of engagement with the mathematical material and with their stance towards knowledge.

Girls and Mathematics: Parental Variables.

ERIC Educational Resources Information Center

Stamp, Peggy

1979-01-01

Girls taking A-level mathematics were compared with girls taking A-level French on masculinity/femininity, parental identification, and attitudes toward their school subjects. Subject choice was related to both parents' attitudes, but subject attitudes related only to the mothers' attitudes. (Editor/SJL)

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals

PubMed Central

Rana, Mohit; Prasad, Vinod A.; Guan, Cuntai; Birbaumer, Niels; Sitaram, Ranganatha

2016-01-01

Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain–Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM), so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity. PMID:27467528

NASA Scope and Subject Category Guide

NASA Technical Reports Server (NTRS)

2011-01-01

This guide provides a simple, effective tool to assist aerospace information analysts and database builders in the high-level subject classification of technical materials. Each of the 76 subject categories comprising the classification scheme is presented with a description of category scope, a listing of subtopics, cross references, and an indication of particular areas of NASA interest. The guide also includes an index of nearly 3,000 specific research topics cross referenced to the subject categories. The portable document format (PDF) version of the guide contains links in the index from each input subject to its corresponding categories. In addition to subject classification, the guide can serve as an aid to searching databases that use the classification scheme, and is also an excellent selection guide for those involved in the acquisition of aerospace literature. The CD-ROM contains both HTML and PDF versions.

Classification in Astronomy: Past and Present

NASA Astrophysics Data System (ADS)

Feigelson, Eric

2012-03-01

Astronomers have always classified celestial objects. The ancient Greeks distinguished between asteros, the fixed stars, and planetos, the roving stars. The latter were associated with the Gods and, starting with Plato in his dialog Timaeus, provided the first mathematical models of celestial phenomena. Giovanni Hodierna classified nebulous objects, seen with a Galilean refractor telescope in the mid-seventeenth century into three classes: "Luminosae," "Nebulosae," and "Occultae." A century later, Charles Messier compiled a larger list of nebulae, star clusters and galaxies, but did not attempt a classification. Classification of comets was a significant enterprise in the 19th century: Alexander (1850) considered two groups based on orbit sizes, Lardner (1853) proposed three groups of orbits, and Barnard (1891) divided them into two classes based on morphology. Aside from the segmentation of the bright stars into constellations, most stellar classifications were based on colors and spectral properties. During the 1860s, the pioneering spectroscopist Angelo Secchi classified stars into five classes: white, yellow, orange, carbon stars, and emission line stars. After many debates, the stellar spectral sequence was refined by the group at Harvard into the familiar OBAFGKM spectral types, later found to be a sequence on surface temperature (Cannon 1926). The spectral classification is still being extended with recent additions of O2 hot stars (Walborn et al. 2002) and L and T brown dwarfs (Kirkpatrick 2005). Townley (1913) reviews 30 years of variable star classification, emerging with six classes with five subclasses. The modern classification of variable stars has about 80 (sub)classes, and is still under debate (Samus 2009). Shortly after his confirmation that some nebulae are external galaxies, Edwin Hubble (1926) proposed his famous bifurcated classification of galaxy morphologies with three classes: ellipticals, spirals, and irregulars. These classes are still used today with many refinements by Gerard de Vaucouleurs and others. Supernovae, nearly all of which are found in external galaxies, have a complicated classification scheme:Type I with subtypes Ia, Ib, Ic, Ib/c pec and Type II with subtypes IIb, IIL, IIP, and IIn (Turatto 2003). The classification is based on elemental abundances in optical spectra and on optical light curve shapes. Tadhunter (2009) presents a three-dimensional classification of active galactic nuclei involving radio power, emission line width, and nuclear luminosity. These taxonomies have played enormously important roles in the development of astronomy, yet all were developed using heuristic methods. Many are based on qualitative and subjective assessments of spatial, temporal, or spectral properties. A qualitative, morphological approach to astronomical studies was explicitly promoted by Zwicky (1957). Other classifications are based on quantitative criteria, but these criteria were developed by subjective examination of training datasets. For example, starburst galaxies are discriminated from narrow-line Seyfert galaxies by a curved line in a diagramof the ratios of four emission lines (Veilleux and Osterbrock 1987). Class II young stellar objects have been defined by a rectangular region in a mid-infrared color-color diagram (Allen et al. 2004). Short and hard gamma-ray bursts are discriminated by a dip in the distribution of burst durations (Kouveliotou et al. 2000). In no case was a statistical or algorithmic procedure used to define the classes.

Developing a Theoretical Framework for Classifying Levels of Context Use for Mathematical Problems

ERIC Educational Resources Information Center

Almuna Salgado, Felipe

2016-01-01

This paper aims to revisit and clarify the term problem context and to develop a theoretical classification of the construct of levels of context use (LCU) to analyse how the context of a problem is used to formulate a problem in mathematical terms and to interpret the answer in relation to the context of a given problem. Two criteria and six…

Reflective thinking in solving an algebra problem: a case study of field independent-prospective teacher

NASA Astrophysics Data System (ADS)

Agustan, S.; Juniati, Dwi; Yuli Eko Siswono, Tatag

2017-10-01

Nowadays, reflective thinking is one of the important things which become a concern in learning mathematics, especially in solving a mathematical problem. The purpose of this paper is to describe how the student used reflective thinking when solved an algebra problem. The subject of this research is one female student who has field independent cognitive style. This research is a descriptive exploratory study with data analysis using qualitative approach to describe in depth reflective thinking of prospective teacher in solving an algebra problem. Four main categories are used to analyse the reflective thinking in solving an algebra problem: (1) formulation and synthesis of experience, (2) orderliness of experience, (3) evaluating the experience and (4) testing the selected solution based on the experience. The results showed that the subject described the problem by using another word and the subject also found the difficulties in making mathematical modelling. The subject analysed two concepts used in solving problem. For instance, geometry related to point and line while algebra is related to algebra arithmetic operation. The subject stated that solution must have four aspect to get effective solution, specifically the ability to (a) understand the meaning of every words; (b) make mathematical modelling; (c) calculate mathematically; (d) interpret solution obtained logically. To test the internal consistency or error in solution, the subject checked and looked back related procedures and operations used. Moreover, the subject tried to resolve the problem in a different way to compare the answers which had been obtained before. The findings supported the assertion that reflective thinking provides an opportunity for the students in improving their weakness in mathematical problem solving. It can make a grow accuracy and concentration in solving a mathematical problem. Consequently, the students will get the right and logic answer by reflective thinking.

Mathematics for the Elementary School, Unit 15, Addition and Linear Translations.

ERIC Educational Resources Information Center

Clark, Julia, Ed.; Myers, Donald E., Ed.

The Minnesota School Mathematics and Science Teaching (MINNEMAST) Project is characterized by its emphasis on the coordination of mathematics and science in the elementary school curriculum. Units are planned to provide children with activities in which they learn various concepts from both subject areas. Each subject is used to support and…

Preparing Middle Level Preservice Teachers to Integrate Mathematics and Science: Problems and Possibilities

ERIC Educational Resources Information Center

Koirala, Hari P.; Bowman, Jacqueline K.

2003-01-01

Many members of the mathematics and science education community believe that the integration of mathematics and science enhances students' understanding of both subjects. Despite this belief, attempts to integrate these subjects have frequently been unsuccessful. This study examines the development and implementation of a team-taught integrated…

The Ability of Students’ Mathematical Proof in Determining the Validity of Argument Reviewed from Gender Differences

NASA Astrophysics Data System (ADS)

Feriyanto

2018-01-01

This research aims to describe the ability of students’ mathematical proof in determining the validity of argument reviewed from gender differences. The subjects of this research were one male and one female student of the fifth semester of Mathematic Education study program. The subjects were selected based on the highest mathematics ability which was assesed from their previous assignments and tests. In addition, the communication ability of the subjects was also considered in order to facilitate the researcher in conducting interviews. Based on the result of the test with direct and indirect proof, it could be concluded that the subjects were able to: 1) mention all facts/premises and write about what should be shown (conclusion) in direct proof and write additional premise in indirect proof; 2) connect facts/premises to concepts which must be mastered; 3) use equivalent concept to manipulate and organize the proof; 4) use the concept of syllogism and tollens mode to obtain the desired conclusion; 5) construct mathematical evidence systematically, and logically; 6) complement the reason for each step appropriately. The difference was that the male subject wrote the final conclusion, while the female subject did not write the final conclusion on the proof.

Mathematics Underground

ERIC Educational Resources Information Center

Luther, Kenneth H.

2012-01-01

Mathematical modeling of groundwater flow is a topic at the intersection of mathematics and geohydrology and is rarely encountered in undergraduate mathematics. However, this subject is full of interesting and meaningful examples of truly "applied" mathematics accessible to undergraduates, from the pre-calculus to advanced mathematics levels. This…

A Classification of Designated Logic Systems

DTIC Science & Technology

1988-02-01

Introduction to Logic. New York: Macmillan Publishing, 1972. Grimaldi , Ralph P . Discrete and Combinatorial Mathematics. Reading: Addison-Wesley...sound basis for understanding non-classical logic systems. I would like to thank the Air Force Institute of Technology for funding this research. vi p ...6 p ILLUSTRATIONS Figure Page 1. Two Classifications of Designated Logic Systems 13 2. Two Partitions of Two-valued Logic Systems 14 3. Two

Early Childhood: Geologist for a Day.

ERIC Educational Resources Information Center

Lind, Karen K.

1989-01-01

Outlines a lesson on the study of rocks including classification, identification, and observation techniques. Provides a listing of activities which integrate rocks with art, mathematics, and language arts. (RT)

Single-trial EEG RSVP classification using convolutional neural networks

NASA Astrophysics Data System (ADS)

Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

2016-05-01

Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

Analysis the Competences and Contents of "Mathematics and Environmental Exploration" Subject Syllabus for Preparatory Grade

ERIC Educational Resources Information Center

Dulama, Maria Eliza; Magda?, Ioana

2014-01-01

In this paper, we analyze some aspects related to "Mathematics and Environmental Exploration" subject syllabus for preparatory grade approved by Minister of National Education of Romania. The analysis aim the place of the subject syllabus into the Framework Plan; the syllabus structure and the argumentation of studying this subject; the…

Application of Decision Making and Team Training Research to Operational Training. A Translative Technique.

DTIC Science & Technology

DECISION MAKING , * GROUP DYNAMICS, NAVAL TRAINING, TRANSFER OF TRAINING, SCIENTIFIC RESEARCH, CLASSIFICATION, PROBLEM SOLVING, MATHEMATICAL MODELS, SUBMARINES, SIMULATORS, PERFORMANCE(HUMAN), UNDERSEA WARFARE.

Meaningful Statistics in Professional Practices as a Bridge between Mathematics and Science: An Evaluation of a Design Research Project

ERIC Educational Resources Information Center

Dierdorp, Adri; Bakker, Arthur; van Maanen, Jan A.; Eijkelhof, Harrie M. C.

2014-01-01

Background: Creating coherence between school subjects mathematics and science and making these school subjects meaningful are still topical challenges. This study investigates how students make meaningful connections between mathematics, statistics, science and applications when they engage in a specially developed unit that is based on…

How Mathematical Literacy Teachers Facilitate Mathematisation in Modelling Situations

ERIC Educational Resources Information Center

Botha, Hanlie; van Putten, Sonja

2018-01-01

Mathematical literacy (ML) is a compulsory subject in South Africa for those learners who choose not to do mathematics to Grade 12 level. ML is designed to enable a learner to become a self-managing person by providing opportunities to analyse and solve real-life problems through the mathematisation of contextual situations. The subject thus lends…

On the Importance of Subject Matter in Mathematics Education: A Conversation with Erich Christian Wittmann

ERIC Educational Resources Information Center

Akinwunmi, Kathrin; Höveler, Karina; Schnell, Susanne

2014-01-01

Erich Christian Wittmann is one of the primary founders of mathematics education research as an autonomous field of work and research in Germany. The interview presented here reflects on his role in promoting mathematics education as a design science. The interview addresses the following topics: (1) The importance of subject matter in…

Subject Design and Factors Affecting Achievement in Mathematics for Biomedical Science

ERIC Educational Resources Information Center

Carnie, Steven; Morphett, Anthony

2017-01-01

Reports such as Bio2010 emphasize the importance of integrating mathematical modelling skills into undergraduate biology and life science programmes, to ensure students have the skills and knowledge needed for biological research in the twenty-first century. One way to do this is by developing a dedicated mathematics subject to teach modelling and…

Subject Classification.

ERIC Educational Resources Information Center

Thompson, Gayle; And Others

Three newspaper librarians described how they manage the files of newspaper clippings which are a necessary part of their collections. The development of a new subject classification system for the clippings files was outlined. The new subject headings were based on standard subject heading lists and on local need. It was decided to use a computer…

Mathematics Self-Efficacy and Flow in Developmental Mathematics Students

ERIC Educational Resources Information Center

Golnabi, Laura

2017-01-01

This study examined mathematics self-efficacy and the characteristics of flow in the context of performing mathematical tasks. In particular, it explored the subjective experiences of 113 undergraduate students enrolled in a developmental mathematics course while they were independently solving certain mathematical problems. This study…

Defining the Relationship of Student Achievement Between STEM Subjects Through Canonical Correlation Analysis of 2011 Trends in International Mathematics and Science Study (TIMSS) Data

NASA Astrophysics Data System (ADS)

O'Neal, Melissa Jean

Canonical correlation analysis was used to analyze data from Trends in International Mathematics and Science Study (TIMSS) 2011 achievement databases encompassing information from fourth/eighth grades. Student achievement in life science/biology was correlated with achievement in mathematics and other sciences across three analytical areas: mathematics and science student performance, achievement in cognitive domains, and achievement in content domains. Strong correlations between student achievement in life science/biology with achievement in mathematics and overall science occurred for both high- and low-performing education systems. Hence, partial emphases on the inter-subject connections did not always lead to a better student learning outcome in STEM education. In addition, student achievement in life science/biology was positively correlated with achievement in mathematics and science cognitive domains; these patterns held true for correlations of life science/biology with mathematics as well as other sciences. The importance of linking student learning experiences between and within STEM domains to support high performance on TIMSS assessments was indicated by correlations of moderate strength (57 TIMSS assessments was indicated by correlations of moderate strength (57 < r < 85) stronger correlations (73 < r < 97) between life science/biology and other science domains. Results demonstrated the foundational nature of STEM knowledge at the fourth grade level, and established the importance of strong interconnections among life science/biology, mathematics, and other sciences. At the eighth grade level, students who built increasing levels of cognitive complexity upon firm foundations were prepared for successful learning throughout their educational careers. The results from this investigation promote a holistic design of school learning opportunities to improve student achievement in life science/biology and other science, technology, engineering, and mathematics (STEM) subjects at the elementary and middle school levels. While the curriculum can vary from combined STEM subjects to separated mathematics or science courses, both professional learning communities (PLC) for teachers and problem-based learning (PBL) for learners can be strengthened through new knowledge construction beyond the traditional boundaries of each subject. It is the knowledge transfer across subjects that breaks barriers of future STEM discoveries to improve STEM education outcomes.

Quantitative computed tomography applied to interstitial lung diseases.

PubMed

Obert, Martin; Kampschulte, Marian; Limburg, Rebekka; Barańczuk, Stefan; Krombach, Gabriele A

2018-03-01

To evaluate a new image marker that retrieves information from computed tomography (CT) density histograms, with respect to classification properties between different lung parenchyma groups. Furthermore, to conduct a comparison of the new image marker with conventional markers. Density histograms from 220 different subjects (normal = 71; emphysema = 73; fibrotic = 76) were used to compare the conventionally applied emphysema index (EI), 15 th percentile value (PV), mean value (MV), variance (V), skewness (S), kurtosis (K), with a new histogram's functional shape (HFS) method. Multinomial logistic regression (MLR) analyses was performed to calculate predictions of different lung parenchyma group membership using the individual methods, as well as combinations thereof, as covariates. Overall correct assigned subjects (OCA), sensitivity (sens), specificity (spec), and Nagelkerke's pseudo R 2 (NR 2 ) effect size were estimated. NR 2 was used to set up a ranking list of the different methods. MLR indicates the highest classification power (OCA of 92%; sens 0.95; spec 0.89; NR 2 0.95) when all histogram analyses methods were applied together in the MLR. Highest classification power among individually applied methods was found using the HFS concept (OCA 86%; sens 0.93; spec 0.79; NR 2 0.80). Conventional methods achieved lower classification potential on their own: EI (OCA 69%; sens 0.95; spec 0.26; NR 2 0.52); PV (OCA 69%; sens 0.90; spec 0.37; NR 2 0.57); MV (OCA 65%; sens 0.71; spec 0.58; NR 2 0.61); V (OCA 66%; sens 0.72; spec 0.53; NR 2 0.66); S (OCA 65%; sens 0.88; spec 0.26; NR 2 0.55); and K (OCA 63%; sens 0.90; spec 0.16; NR 2 0.48). The HFS method, which was so far applied to a CT bone density curve analysis, is also a remarkable information extraction tool for lung density histograms. Presumably, being a principle mathematical approach, the HFS method can extract valuable health related information also from histograms from complete different areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

An Investigation of Mental Coding Mechanisms and Heuristics Used in Electronics Troubleshooting.

DTIC Science & Technology

1980-04-01

that is, the particular program to be used for the decision making or problem solving exercise at hand. The relationships between LTM, the processor...stimulus input according to previously learned classifications. Norman continued by writing that the encoded information is the material which is stored...the manipulation of algebraic or other mathematical symbols according to the rules embodied in mathematical logic. Once these essentially content free

A Cross-Validation of easyCBM Mathematics Cut Scores in Washington State: 2009-2010 Test. Technical Report #1105

ERIC Educational Resources Information Center

Anderson, Daniel; Alonzo, Julie; Tindal, Gerald

2011-01-01

In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in the state of Washington. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Washington state…

A Cross-Validation of easyCBM[R] Mathematics Cut Scores in Oregon: 2009-2010. Technical Report #1104

ERIC Educational Resources Information Center

Anderson, Daniel; Alonzo, Julie; Tindal, Gerald

2011-01-01

In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in Oregon. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Oregon state test was used as the…

Lacan, Subjectivity and the Task of Mathematics Education Research

ERIC Educational Resources Information Center

Brown, Tony

2008-01-01

This paper addresses the issue of subjectivity in the context of mathematics education research. It introduces the psychoanalyst and theorist Jacques Lacan whose work on subjectivity combined Freud's psychoanalytic theory with processes of signification as developed in the work of de Saussure and Peirce. The paper positions Lacan's subjectivity…

"This compendious language": mathematics in the world of Augustus De Morgan.

PubMed

Richards, Joan L

2011-09-01

Mathematics is the most chameleon of subjects, whose meaning is differently defined in different circumstances. This essay considers the mathematics of Augustus De Morgan as an illustration of the ways that the essence of the subject, the very objects that are included within it, has been adjusted in response to cultural factors. Since these cultural factors are the same ones that shape scientific development, the argument is that the history of mathematics and the history of science are always inextricably bound to one another.

Motivation of men and women in mathematics and language.

PubMed

Vrugt, Anneke; Oort, Frans J; Waardenburg, Lydeke

2009-10-01

Based on the multiple goal perspective it is argued that mastery and performance goals contribute to different motivational variables-mastery goals to self-efficacy and performance goals to social comparison-that contribute through affect to achievement. The first aim of this study was to determine whether this model is applicable irrespective of sex and subject. The expected relationships occurred for female students studying Dutch and mathematics, and for male students studying Dutch. The second aim was to test a model in which the perceived gender appropriateness of the subject affects the pursued achievement goal. We expected that subjects perceived as gender-appropriate--Dutch for female and mathematics for male students--would result in strong relationships between mastery goals, self-efficacy, affect, and achievement, and that less gender-appropriate subjects--mathematics for women and Dutch for men--would result in strong relationships between performance goals, social comparison, affect, and achievement. Several of the expected relationships occurred for female and males students studying Dutch and mathematics. Furthermore, female students obtained higher course grades in Dutch than male students, while male students studying mathematics scored higher on self-efficacy and affect than female students.

Mathematical modelling in developmental biology.

PubMed

Vasieva, Olga; Rasolonjanahary, Manan'Iarivo; Vasiev, Bakhtier

2013-06-01

In recent decades, molecular and cellular biology has benefited from numerous fascinating developments in experimental technique, generating an overwhelming amount of data on various biological objects and processes. This, in turn, has led biologists to look for appropriate tools to facilitate systematic analysis of data. Thus, the need for mathematical techniques, which can be used to aid the classification and understanding of this ever-growing body of experimental data, is more profound now than ever before. Mathematical modelling is becoming increasingly integrated into biological studies in general and into developmental biology particularly. This review outlines some achievements of mathematics as applied to developmental biology and demonstrates the mathematical formulation of basic principles driving morphogenesis. We begin by describing a mathematical formalism used to analyse the formation and scaling of morphogen gradients. Then we address a problem of interplay between the dynamics of morphogen gradients and movement of cells, referring to mathematical models of gastrulation in the chick embryo. In the last section, we give an overview of various mathematical models used in the study of the developmental cycle of Dictyostelium discoideum, which is probably the best example of successful mathematical modelling in developmental biology.

Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?

PubMed

Rossini, Paolo M; Buscema, Massimo; Capriotti, Massimiliano; Grossi, Enzo; Rodriguez, Guido; Del Percio, Claudio; Babiloni, Claudio

2008-07-01

It has been shown that a new procedure (implicit function as squashing time, IFAST) based on artificial neural networks (ANNs) is able to compress eyes-closed resting electroencephalographic (EEG) data into spatial invariants of the instant voltage distributions for an automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects with classification accuracy of individual subjects higher than 92%. Here we tested the hypothesis that this is the case also for the classification of individual normal elderly (Nold) vs. MCI subjects, an important issue for the screening of large populations at high risk of AD. Eyes-closed resting EEG data (10-20 electrode montage) were recorded in 171 Nold and in 115 amnesic MCI subjects. The data inputs for the classification by IFAST were the weights of the connections within a nonlinear auto-associative ANN trained to generate the instant voltage distributions of 60-s artifact-free EEG data. The most relevant features were selected and coincidently the dataset was split into two halves for the final binary classification (training and testing) performed by a supervised ANN. The classification of the individual Nold and MCI subjects reached 95.87% of sensitivity and 91.06% of specificity (93.46% of accuracy). These results indicate that IFAST can reliably distinguish eyes-closed resting EEG in individual Nold and MCI subjects. IFAST may be used for large-scale periodic screening of large populations at risk of AD and personalized care.

Pre-Service Accounting Teachers' Attitudes to Mathematics

ERIC Educational Resources Information Center

Mkhize, Msizi Vitalis; Maistry, Suriamurthee Moonsamy

2017-01-01

Mathematics proficiency has an acknowledged impact on students' accounting grades. Success in this core business subject is dependent on students' mathematical aptitude, attitude and type of secondary schooling. Our study investigated accounting students' attitudes to mathematics on domains of the Fennema-Sherman Mathematics Attitudes Scales…

Using Mathematics in Science: Working with Your Mathematics Department

ERIC Educational Resources Information Center

Lyon, Steve

2014-01-01

Changes to the mathematics and science curriculums are designed to increase rigour in mathematics, and place greater emphasis on mathematical content in science subjects at key stages 3, 4 and 5 (ages 11-18). One way to meet the growing challenge of providing increased emphasis on mathematics in the science curriculum is greater collaboration…

Teachers' Beliefs about School Mathematics and Mathematicians' Mathematics and Their Relationship to Practice

ERIC Educational Resources Information Center

Beswick, Kim

2012-01-01

There is broad acceptance that mathematics teachers' beliefs about the nature of mathematics influence the ways in which they teach the subject. It is also recognised that mathematics as practised in typical school classrooms is different from the mathematical activity of mathematicians. This paper presents case studies of two secondary…

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

PubMed Central

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B.; Bringas-Vega, Maria L.; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A.

2018-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented. PMID:29379411

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

PubMed

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

The problem-solving approach in the teaching of number theory

NASA Astrophysics Data System (ADS)

Toh, Pee Choon; Hoong Leong, Yew; Toh, Tin Lam; Dindyal, Jaguthsing; Quek, Khiok Seng; Guan Tay, Eng; Him Ho, Foo

2014-02-01

Mathematical problem solving is the mainstay of the mathematics curriculum for Singapore schools. In the preparation of prospective mathematics teachers, the authors, who are mathematics teacher educators, deem it important that pre-service mathematics teachers experience non-routine problem solving and acquire an attitude that predisposes them to adopt a Pólya-style approach in learning mathematics. The Practical Worksheet is an instructional scaffold we adopted to help our pre-service mathematics teachers develop problem-solving dispositions alongside the learning of the subject matter. The Worksheet was initially used in a design experiment aimed at teaching problem solving in a secondary school. In this paper, we describe an application and adaptation of the MProSE (Mathematical Problem Solving for Everyone) design experiment to a university level number theory course for pre-service mathematics teachers. The goal of the enterprise was to help the pre-service mathematics teachers develop problem-solving dispositions alongside the learning of the subject matter. Our analysis of the pre-service mathematics teachers' work shows that the MProSE design holds promise for mathematics courses at the tertiary level.

Elevate or Relegate? The Relative Importance of Mathematics

ERIC Educational Resources Information Center

Huckstep, Peter

2007-01-01

The value of any subject on a crowded, contested and compulsory curriculum is, or at least should be, open to debate. More importantly, when different subjects are prioritized over others, the justification for the ranking of such subjects should also be submitted to sustained enquiry. Mathematics enjoys a prestigious place in the English National…

The Erroneous Derivative Examples of Eleventh Grade Students

ERIC Educational Resources Information Center

Gur, Hulya; Barak, Basak

2007-01-01

The derivative is not only an important subject for mathematics but also is an important subject for engineering, physics, economy, chemistry, and statistics. Especially, mathematics depends on strongly preceding learning and the subject of derivative will be used in university education by all students. Therefore, it is one of the most important…

Desert plains classification based on Geomorphometrical parameters (Case study: Aghda, Yazd)

NASA Astrophysics Data System (ADS)

Tazeh, mahdi; Kalantari, Saeideh

2013-04-01

This research focuses on plains. There are several tremendous methods and classification which presented for plain classification. One of The natural resource based classification which is mostly using in Iran, classified plains into three types, Erosional Pediment, Denudation Pediment Aggradational Piedmont. The qualitative and quantitative factors to differentiate them from each other are also used appropriately. In this study effective Geomorphometrical parameters in differentiate landforms were applied for plain. Geomorphometrical parameters are calculable and can be extracted using mathematical equations and the corresponding relations on digital elevation model. Geomorphometrical parameters used in this study included Percent of Slope, Plan Curvature, Profile Curvature, Minimum Curvature, the Maximum Curvature, Cross sectional Curvature, Longitudinal Curvature and Gaussian Curvature. The results indicated that the most important affecting Geomorphometrical parameters for plain and desert classifications includes: Percent of Slope, Minimum Curvature, Profile Curvature, and Longitudinal Curvature. Key Words: Plain, Geomorphometry, Classification, Biophysical, Yazd Khezarabad.

Exploring simple, transparent, interpretable and predictive QSAR models for classification and quantitative prediction of rat toxicity of ionic liquids using OECD recommended guidelines.

PubMed

Das, Rudra Narayan; Roy, Kunal; Popelier, Paul L A

2015-11-01

The present study explores the chemical attributes of diverse ionic liquids responsible for their cytotoxicity in a rat leukemia cell line (IPC-81) by developing predictive classification as well as regression-based mathematical models. Simple and interpretable descriptors derived from a two-dimensional representation of the chemical structures along with quantum topological molecular similarity indices have been used for model development, employing unambiguous modeling strategies that strictly obey the guidelines of the Organization for Economic Co-operation and Development (OECD) for quantitative structure-activity relationship (QSAR) analysis. The structure-toxicity relationships that emerged from both classification and regression-based models were in accordance with the findings of some previous studies. The models suggested that the cytotoxicity of ionic liquids is dependent on the cationic surfactant action, long alkyl side chains, cationic lipophilicity as well as aromaticity, the presence of a dialkylamino substituent at the 4-position of the pyridinium nucleus and a bulky anionic moiety. The models have been transparently presented in the form of equations, thus allowing their easy transferability in accordance with the OECD guidelines. The models have also been subjected to rigorous validation tests proving their predictive potential and can hence be used for designing novel and "greener" ionic liquids. The major strength of the present study lies in the use of a diverse and large dataset, use of simple reproducible descriptors and compliance with the OECD norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pancreatic abnormalities detected by endoscopic ultrasound (EUS) in patients without clinical signs of pancreatic disease: any difference between standard and Rosemont classification scoring?

PubMed

Petrone, Maria Chiara; Terracciano, Fulvia; Perri, Francesco; Carrara, Silvia; Cavestro, Giulia Martina; Mariani, Alberto; Testoni, Pier Alberto; Arcidiacono, Paolo Giorgio

2014-01-01

The prevalence of nine EUS features of chronic pancreatitis (CP) according to the standard Wiersema classification has been investigated in 489 patients undergoing EUS for an indication not related to pancreatico-biliary disease. We showed that 82 subjects (16.8%) had at least one ductular or parenchymal abnormality. Among them, 18 (3.7% of study population) had ≥3 Wiersema criteria suggestive of CP. Recently, a new classification (Rosemont) of EUS findings consistent, suggestive or indeterminate for CP has been proposed. To stratify healthy subjects into different subgroups on the basis of EUS features of CP according to the Wiersema and Rosemont classifications and to evaluate the agreement in the diagnosis of CP with the two scoring systems. Weighted kappa statistics was computed to evaluate the strength of agreement between the two scoring systems. Univariate and multivariate analysis between any EUS abnormality and habits were performed. Eighty-two EUS videos were reviewed. Using the Wiersema classification, 18 subjects showed ≥3 EUS features suggestive of CP. The EUS diagnosis of CP in these 18 subjects was considered as consistent in only one patient, according to Rosemont classification. Weighted Kappa statistics was 0.34 showing that the strength of agreement was 'fair'. Alcohol use and smoking were identified as risk factors for having pancreatic abnormalities on EUS. The prevalence of EUS features consistent or suggestive of CP in healthy subjects according to the Rosemont classification is lower than that assessed by Wiersema criteria. In that regard the Rosemont classification seems to be more accurate in excluding clinically relevant CP. Overall agreement between the two classifications is fair. Copyright © 2014 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Enhancement of force patterns classification based on Gaussian distributions.

PubMed

Ertelt, Thomas; Solomonovs, Ilja; Gronwald, Thomas

2018-01-23

Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clinical diagnostics. Here, the knowledge and experience of the diagnostician is relevant for its assessment. For an objective and valid discrimination of the ground reaction force pattern, a generic method, especially in the medical field, is absolutely necessary to describe the qualities of the time-course. The aim of the presented method was to combine the approaches of two existing procedures from the fields of machine learning and the Gauss approximation in order to take advantages of both methods for the classification of ground reaction force patterns. The current limitations of both methods could be eliminated by an overarching method. Twenty-nine male athletes from different sports were examined. Each participant was given the task of performing a one-legged stopping maneuver on a force plate from the maximum possible starting speed. The individual time course of the ground reaction force of each subject was registered and approximated on the basis of eight Gaussian distributions. The descriptive coefficients were then classified using Bayesian regulated neural networks. The different sports served as the distinguishing feature. Although the athletes were all given the same task, all sports referred to a different quality in the time course of ground reaction force. Meanwhile within each sport, the athletes were homogeneous. With an overall prediction (R = 0.938) all subjects/sports were classified correctly with 94.29% accuracy. The combination of the two methods: the mathematical description of the time course of ground reaction forces on the basis of Gaussian distributions and their classification by means of Bayesian regulated neural networks, seems an adequate and promising method to discriminate the ground reaction forces without any loss of information. Copyright © 2017 Elsevier Ltd. All rights reserved.

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

PubMed

Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (p<0.001) for predicting the task being performed within each scan using artifact-cleaned components. The NMF algorithms, which suppressed negative BOLD signal, had the poorest accuracy compared to the ICA and sparse coding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (p<0.001). Lower classification accuracy occurred when the extracted spatial maps contained more CSF regions (p<0.001). The success of sparse coding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

"My math and me": Nursing students' previous experiences in learning mathematics.

PubMed

Røykenes, Kari

2016-01-01

In this paper, 11 narratives about former experiences in learning of mathematics written by nursing students are thematically analyzed. Most students had a positive relationship with the subject in primary school, when they found mathematics fun and were able to master the subject. For some, a change occurred in the transition to lower secondary school. The reasons for this change was found in the subject (increased difficulty), the teachers (movement of teachers, numerous substitute teachers), the class environment and size (many pupils, noise), and the student him- or herself (silent and anonymous pupil). This change was also found in the transition from lower to higher secondary school. By contrast, some students had experienced changes that were positive, and their mathematics teacher was a significant factor in this positive change. The paper emphasizes the importance of previous experiences in learning mathematics to nursing students when learning about drug calculation. Copyright © 2015. Published by Elsevier Ltd.

Refractive Thinking Profile In Solving Mathematical Problem Reviewed from Students Math Capability

NASA Astrophysics Data System (ADS)

Maslukha, M.; Lukito, A.; Ekawati, R.

2018-01-01

Refraction is a mental activity experienced by a person to make a decision through reflective thinking and critical thinking. Differences in mathematical capability have an influence on the difference of student’s refractive thinking processes in solving math problems. This descriptive research aims to generate a picture of refractive thinking of students in solving mathematical problems in terms of students’ math skill. Subjects in this study consisted of three students, namely students with high, medium, and low math skills based on mathematics capability test. Data collection methods used are test-based methods and interviews. After collected data is analyzed through three stages that are, condensing and displaying data, data display, and drawing and verifying conclusion. Results showed refractive thinking profiles of three subjects is different. This difference occurs at the planning and execution stage of the problem. This difference is influenced by mathematical capability and experience of each subject.

The Effects of Constructivist Learning Environment on Prospective Mathematics Teachers' Opinions

ERIC Educational Resources Information Center

Narli, Serkan; Baser, Nes'e

2010-01-01

To explore the effects of constructivist learning environment on prospective teachers' opinions about "mathematics, department of mathematics, discrete mathematics, countable and uncountable infinity" taught under the subject of Cantorian Set Theory in discrete mathematics class, 60 first-year students in the Division of Mathematics…

Wyoming Mathematics Curriculum Guide, Grades 7-12.

ERIC Educational Resources Information Center

Wyoming State Dept. of Education, Cheyenne.

GRADES OR AGES: 7-12; SUBJECT MATTER: Mathematics. ORGANIZATION AND PHYSICAL APPEARANCE: The guide has an introduction and four chapters: 1) A Sample Mathematics Curriculum; 2) The Exceptional Student in Mathematics; 3) Mathematics Components for Comprehensive Occupational Education; 4) Reference Materials. The guide is printed and spiral bound…

Mechanization of Library Procedures in the Medium-Sized Medical Library: XIV. Correlations between National Library of Medicine Classification Numbers and MeSH Headings *

PubMed Central

Fenske, Ruth E.

1972-01-01

The purpose of this study was to determine the amount of correlation between National Library of Medicine classification numbers and MeSH headings in a body of cataloging which had already been done and then to find out which of two alternative methods of utilizing the correlation would be best. There was a correlation of 44.5% between classification numbers and subject headings in the data base studied, cataloging data covering 8,137 books. The results indicate that a subject heading index showing classification numbers would be the preferred method of utilization, because it would be more accurate than the alternative considered, an arrangement by classification numbers which would be consulted to obtain subject headings. PMID:16017607

A domain-knowledge-inspired mathematical framework for the description and classification of H&E stained histopathology images.

PubMed

Massar, Melody L; Bhagavatula, Ramamurthy; Ozolek, John A; Castro, Carlos A; Fickus, Matthew; Kovačević, Jelena

2011-10-19

We present the current state of our work on a mathematical framework for identification and delineation of histopathology images-local histograms and occlusion models. Local histograms are histograms computed over defined spatial neighborhoods whose purpose is to characterize an image locally. This unit of description is augmented by our occlusion models that describe a methodology for image formation. In the context of this image formation model, the power of local histograms with respect to appropriate families of images will be shown through various proved statements about expected performance. We conclude by presenting a preliminary study to demonstrate the power of the framework in the context of histopathology image classification tasks that, while differing greatly in application, both originate from what is considered an appropriate class of images for this framework.

Discrete mathematics for spatial data classification and understanding

NASA Astrophysics Data System (ADS)

Mussio, Luigi; Nocera, Rossella; Poli, Daniela

1998-12-01

Data processing, in the field of information technology, requires new tools, involving discrete mathematics, like data compression, signal enhancement, data classification and understanding, hypertexts and multimedia (considering educational aspects too), because the mass of data implies automatic data management and doesn't permit any a priori knowledge. The methodologies and procedures used in this class of problems concern different kinds of segmentation techniques and relational strategies, like clustering, parsing, vectorization, formalization, fitting and matching. On the other hand, the complexity of this approach imposes to perform optimal sampling and outlier detection just at the beginning, in order to define the set of data to be processed: rough data supply very poor information. For these reasons, no hypotheses about the distribution behavior of the data can be generally done and a judgment should be acquired by distribution-free inference only.

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

A subject-independent pattern-based Brain-Computer Interface

PubMed Central

Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio

2015-01-01

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089

AMOEBA clustering revisited. [cluster analysis, classification, and image display program

NASA Technical Reports Server (NTRS)

Bryant, Jack

1990-01-01

A description of the clustering, classification, and image display program AMOEBA is presented. Using a difficult high resolution aircraft-acquired MSS image, the steps the program takes in forming clusters are traced. A number of new features are described here for the first time. Usage of the program is discussed. The theoretical foundation (the underlying mathematical model) is briefly presented. The program can handle images of any size and dimensionality.

Classification and Subject Cataloguing Section. Bibliographic Control Division. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations, The Hague (Netherlands).

Papers on classification and subject cataloging which were presented at the 1983 International Federation of Library Associations (IFLA) conference include: (1) "PRECIS: Basic Principles, Function, and Use," in which Derek Austin (United Kingdom) describes the automated subject indexing system developed for use in the "British…

Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes

PubMed Central

Bayo-Monton, Jose-Luis; Argente-Pla, María; Fernandez-Llatas, Carlos; Merino-Torres, Juan Francisco

2017-01-01

Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of type 2 diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. Prospective research has been driven on large groups of the population to build risk scores that aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently, there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and integrated into a clinical application for decision support. In this paper, we present a novel system architecture based on service choreography and hybrid modeling, which enables a distributed integration of clinical databases, statistical and mathematical engines and web interfaces to be deployed in a clinical setting. The system was assessed during an eight-week continuous period with eight endocrinologists of a hospital who evaluated up to 8080 patients with seven different type 2 diabetes risk models implemented in two mathematical engines. Throughput was assessed as a matter of technical key performance indicators, confirming the reliability and efficiency of the proposed architecture to integrate hybrid artificial intelligence tools into daily clinical routine to identify high risk subjects. PMID:29286314

Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes.

PubMed

Martinez-Millana, Antonio; Bayo-Monton, Jose-Luis; Argente-Pla, María; Fernandez-Llatas, Carlos; Merino-Torres, Juan Francisco; Traver-Salcedo, Vicente

2017-12-29

Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of type 2 diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. Prospective research has been driven on large groups of the population to build risk scores that aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently, there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and integrated into a clinical application for decision support. In this paper, we present a novel system architecture based on service choreography and hybrid modeling, which enables a distributed integration of clinical databases, statistical and mathematical engines and web interfaces to be deployed in a clinical setting. The system was assessed during an eight-week continuous period with eight endocrinologists of a hospital who evaluated up to 8080 patients with seven different type 2 diabetes risk models implemented in two mathematical engines. Throughput was assessed as a matter of technical key performance indicators, confirming the reliability and efficiency of the proposed architecture to integrate hybrid artificial intelligence tools into daily clinical routine to identify high risk subjects.

How Well Does A-Level Mathematics Prepare Students for the Mathematical Demands of Chemistry Degrees?

ERIC Educational Resources Information Center

Darlington, Ellie; Bowyer, Jessica

2016-01-01

332 undergraduate chemistry students were surveyed in order to establish whether they had found A-level Mathematics and/or Further Mathematics to be good preparation for their degree. Perceptions of both subjects were found to be positive, with more than 80% of participants describing Mathematics or Further Mathematics as good preparation. In…

Connecting Mathematics across the Curriculum. 1995 Yearbook.

ERIC Educational Resources Information Center

House, Peggy A., Ed.; Coxford, Arthur F., Ed.

One of the four cornerstones of the National Council of Teachers of Mathematics (NCTM) "Curriculum and Evaluation Standards for School Mathematics" asserts that connecting mathematics to other subjects in the curriculum and to the everyday world is an important goal of school mathematics. This yearbook is designed to help classroom…

Graphing Calculator Exposure of Mathematics Learning in a Partially Technology Incorporated Environment

ERIC Educational Resources Information Center

Kharuddin, Azrul Fazwan; Ismail, Noor Azina

2017-01-01

Integrating technology in the mathematics curriculum has become a necessary task for curriculum developers as well as mathematics practitioners across the world and time. In general research studies seeking a better understanding of how best to integrate mathematics analysis tools with mathematics subject matter normally observe mathematics…

Mathematical Modelling at Secondary School: The MACSI-Clongowes Wood College Experience

ERIC Educational Resources Information Center

Charpin, J. P. F.; O'Hara, S.; Mackey, D.

2013-01-01

In Ireland, to encourage the study of STEM (science, technology, engineering and mathematics) subjects and particularly mathematics, the Mathematics Applications Consortium for Science and Industry (MACSI) and Clongowes Wood College (County Kildare, Ireland) organized a mathematical modelling workshop for senior cycle secondary school students.…

Teacher Qualification and Students' Academic Performance in Science Mathematics and Technology Subjects in Kenya

ERIC Educational Resources Information Center

Musau, Lydia M.; Abere, Migosi Joash

2015-01-01

Performance in Science, Mathematics and Technology (SMT) subjects among students in Kitui County, Kenya has perpetually been unsatisfactory. The aim of this study was to look into the extent to which teacher qualification influenced students' academic performance in SMT subjects. The study applied ex-post-facto survey research design. Random…

Subjectivity and Cultural Adjustment in Mathematics Education: A Response to Wolff-Michael Roth

ERIC Educational Resources Information Center

Brown, Tony

2012-01-01

In this volume, Wolff-Michael Roth provides a critical but partial reading of Tony Brown's book "Mathematics Education and Subjectivity". The reading contrasts Brown's approach with Roth's own conception of subjectivity as derived from the work of Vygotsky, in which Roth aims to "reunite" psychology and sociology. Brown's book, however, focuses on…

A hybrid model of mathematics support for science students emphasizing basic skills and discipline relevance

NASA Astrophysics Data System (ADS)

Jackson, Deborah C.; Johnson, Elizabeth D.

2013-09-01

The problem of students entering university lacking basic mathematical skills is a critical issue in the Australian higher-education sector and relevant globally. The Maths Skills programme at La Trobe University has been developed to address under preparation in the first-year science cohort in the absence of an institutional mathematics support centre. The programme was delivered through first-year science and statistics subjects with large enrolments and focused on basic mathematical skills relevant to each science discipline. The programme offered a new approach to the traditional mathematical support centre or class. It was designed through close collaboration between science subject coordinators and the project leader, a mathematician, and includes resources relevant to science and mathematics questions written in context. Evaluation of the programme showed it improved the confidence of the participating students who found it helpful and relevant. The programme was delivered through three learning modes to allow students to select activities most suitable for them, which was appreciated by students. Mathematics skills appeared to increase following completion of the programme and student participation in the programme correlated positively and highly with academic grades in their relevant science subjects. This programme offers an alternative model for mathematics support tailored to science disciplines.

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

PubMed

Hilbert, Kevin; Lueken, Ulrike; Muehlhan, Markus; Beesdo-Baum, Katja

2017-03-01

Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral data from a sample of GAD, MD and healthy subjects to differentiate subjects with a disorder from healthy subjects (case-classification) and to differentiate GAD from MD (disorder-classification). Subjects with GAD ( n  = 19), MD without GAD ( n  = 14), and healthy comparison subjects ( n  = 24) were included. The sample was matched regarding age, sex, handedness and education and free of psychopharmacological medication. Binary support vector machines were used within a nested leave-one-out cross-validation framework. Clinical questionnaires, cortisol release, gray matter (GM), and white matter (WM) volumes were used as input data separately and in combination. Questionnaire data were well-suited for case-classification but not disorder-classification (accuracies: 96.40%, p  < .001; 56.58%, p  > .22). The opposite pattern was found for imaging data (case-classification GM/WM: 58.71%, p  = .09/43.18%, p  > .66; disorder-classification GM/WM: 68.05%, p  = .034/58.27%, p  > .15) and for cortisol data (38.02%, p  = .84; 74.60%, p  = .009). All data combined achieved 90.10% accuracy ( p  < .001) for case-classification and 67.46% accuracy ( p  = .0268) for disorder-classification. In line with previous evidence, classification of GAD was difficult using clinical questionnaire data alone. Particularly cortisol and GM volume data were able to provide incremental value for the classification of GAD. Findings suggest that neurobiological biomarkers are a useful target for further research to delineate their potential contribution to diagnostic processes.

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification.

PubMed

Dai, Mengxi; Zheng, Dezhi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

PubMed Central

Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

Students’ Mathematical Literacy in Solving PISA Problems Based on Keirsey Personality Theory

NASA Astrophysics Data System (ADS)

Masriyah; Firmansyah, M. H.

2018-01-01

This research is descriptive-qualitative research. The purpose is to describe students’ mathematical literacy in solving PISA on space and shape content based on Keirsey personality theory. The subjects are four junior high school students grade eight with guardian, artisan, rational or idealist personality. Data collecting methods used test and interview. Data of Keirsey Personality test, PISA test, and interview were analysed. Profile of mathematical literacy of each subject are described as follows. In formulating, guardian subject identified mathematical aspects are formula of rectangle area and sides length; significant variables are terms/conditions in problem and formula of ever encountered question; translated into mathematical language those are measurement and arithmetic operations. In employing, he devised and implemented strategies using ease of calculation on area-subtraction principle; declared truth of result but the reason was less correct; didn’t use and switch between different representations. In interpreting, he declared result as area of house floor; declared reasonableness according measurement estimation. In formulating, artisan subject identified mathematical aspects are plane and sides length; significant variables are solution procedure on both of daily problem and ever encountered question; translated into mathematical language those are measurement, variables, and arithmetic operations as well as symbol representation. In employing, he devised and implemented strategies using two design comparison; declared truth of result without reason; used symbol representation only. In interpreting, he expressed result as floor area of house; declared reasonableness according measurement estimation. In formulating, rational subject identified mathematical aspects are scale and sides length; significant variables are solution strategy on ever encountered question; translated into mathematical language those are measurement, variable, arithmetic operation as well as symbol and graphic representation. In employing, he devised and implemented strategies using additional plane forming on area-subtraction principle; declared truth of result according calculation process; used and switched between symbol and graphic representation. In interpreting, he declared result as house area within terrace and wall; declared reasonableness according measurement estimation. In formulating, idealist subject identified mathematical aspects are sides length; significant variables are terms/condition in problem; translated into mathematical language those are measurement, variables, arithmetic operations as well as symbol and graphic representation. In employing, he devised and implemented strategies using trial and error and two design in process of finding solutions; declared truth of result according the use of two design of solution; used and switched between symbol and graphic representation. In interpreting, he declared result as floor area of house; declared reasonableness according measurement estimation.

Learning Mathematics for Teaching Mathematics: Non-Specialist Teachers' Mathematics Teacher Identity

ERIC Educational Resources Information Center

Crisan, Cosette; Rodd, Melissa

2017-01-01

A non-specialist teacher of mathematics is a school teacher who qualified to teach in a subject other than mathematics yet teaches mathematics to students in secondary school. There is an emerging interest internationally in this population, a brief report of which is given in the paper. Because of concerns about the quality of non-specialists'…

Building a Multi-Discipline Digital Library Through Extending the Dienst Protocol

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

1997-01-01

The purpose of this project is to establish multi-discipline capability for a unified, canonical digital library service for scientific and technical information (STI). This is accomplished by extending the Dienst Protocol to be aware of subject classification of a servers holdings. We propose a hierarchical, general, and extendible subject classification that can encapsulate existing classification systems.

Classification of change detection and change blindness from near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Tanaka, Hirokazu; Katura, Takusige

2011-08-01

Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

Student’s rigorous mathematical thinking based on cognitive style

NASA Astrophysics Data System (ADS)

Fitriyani, H.; Khasanah, U.

2017-12-01

The purpose of this research was to determine the rigorous mathematical thinking (RMT) of mathematics education students in solving math problems in terms of reflective and impulsive cognitive styles. The research used descriptive qualitative approach. Subjects in this research were 4 students of the reflective and impulsive cognitive style which was each consisting male and female subjects. Data collection techniques used problem-solving test and interview. Analysis of research data used Miles and Huberman model that was reduction of data, presentation of data, and conclusion. The results showed that impulsive male subjects used three levels of the cognitive function required for RMT that were qualitative thinking, quantitative thinking with precision, and relational thinking completely while the other three subjects were only able to use cognitive function at qualitative thinking level of RMT. Therefore the subject of impulsive male has a better RMT ability than the other three research subjects.

Discrete Mathematics and the Secondary Mathematics Curriculum.

ERIC Educational Resources Information Center

Dossey, John

Discrete mathematics, the mathematics of decision making for finite settings, is a topic of great interest in mathematics education at all levels. Attention is being focused on resolving the diversity of opinion concerning the exact nature of the subject, what content the curriculum should contain, who should study that material, and how that…

TDmat--Mathematics Diagnosis Evaluation Test for Engineering Sciences Students

ERIC Educational Resources Information Center

Pinto, J. S.; Oliveira, M. P.; Anjo, A. B.; Pais, S. I. Vieira; Isidro, R. O.; Silva, M. H.

2007-01-01

Since 1989, the Mathematics Education Project (PmatE--Projecto Matematica Ensino) has developed several strategies to improve the success of students in Mathematics. The most important of these are mathematical games for all grades above primary school. The online evaluation of Mathematics subjects is one of PmatE's goals. The implementation of an…

Managing Cognitive Load in the Mathematics Classroom

ERIC Educational Resources Information Center

Chinnappan, Mohan; Chandler, Paul

2010-01-01

Contemporary debates on effective pedagogies for K-12 mathematics have called for shifts in the way teachers and teacher educators conceptualise mathematics as a subject and how it should be taught. This is reflected by changes in the curriculum including the inclusion of a strand called Working Mathematically within K-12 mathematics curriculum…

Effect of Gender, Achievement in Mathematics, and Grade Level on Attitudes toward Mathematics.

ERIC Educational Resources Information Center

Tapia, Martha; Marsh, George E., II

The effects of gender, math achievement, and grade level on attitudes toward mathematics were examined by use of an inventory, Attitudes Toward Mathematics Instrument. Subjects were 803 bilingual, middle and high school students. The data were analyzed using a multivariate factorial model with four factors of Mathematics Attitudes as dependent…

Studies in Mathematics Education. Volume 6. Out-of-School Mathematics Education.

ERIC Educational Resources Information Center

Morris, Robert, Ed.

This is the sixth volume in a series designed to improve mathematics instruction by providing resource materials for those responsible for mathematics teaching. Focusing on out-of-school mathematics education, this volume presents a panorama of current practices around the world and suggests future trends. Subjects considered include: (1)…

Development Mathematic Assessment to Increase Mathematical Prerequisite Ability on The Student with Learning Disabilities in Inclusive Elementary School

NASA Astrophysics Data System (ADS)

Robiansyah, S. T. U.; Nanang, F.; Hidayat

2018-01-01

The purpose of this study was to introduce about mathematic assessment is a process of obtaining data or information about the mastery of a student's mathematical skills as an ingredient in preparing a learning program. With this mathematics assessment can be known obstacles, difficulties and needs of students especially in the field of mathematic, so that the learning program will be in accordance with the potential students because it is tailored to what is required of students. This research study was conducted at elementary school of inclusive precisely at SDN Sukagalih I Bandung City based learning in setting of inclusive education. This research study is motivated by the existence of a first-grade student who has disabilities learning in mathematics, the ability of the mathematical prerequisite mastery of the classification of objects by color. The results of the research can provide a profile picture of student data information, the data obtained from the results of the development of systematic and formal mathematical assessment. After doing the development of mathematics assessment then the teacher gets important related information: 1. process the analysis of students’ learning needs, especially in the field of mathematics, 2. preparing the learning program planning according to student learning needs, 3. Designing procedural of method remedial program.

Determinants of Girls' Performance in Science, Mathematics and Technology Subjects in Public Secondary Schools in Kenya

ERIC Educational Resources Information Center

Musau, Lydia Mbaki; Migosi, Joash; Muola, James Matee

2013-01-01

There has been incessant low academic performance in Science, Mathematics and Technology (SMT) subjects especially among girls at form four level in Kitui Central District over the years. The aim of this study was to investigate the determinants of girls' performance in SMT subjects in public secondary schools. Using ex-post-facto survey research…

Classification of quantum groups and Belavin–Drinfeld cohomologies for orthogonal and symplectic Lie algebras

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadets, Boris; Karolinsky, Eugene; Pop, Iulia

2016-05-15

In this paper we continue to study Belavin–Drinfeld cohomology introduced in Kadets et al., Commun. Math. Phys. 344(1), 1-24 (2016) and related to the classification of quantum groups whose quasi-classical limit is a given simple complex Lie algebra #Mathematical Fraktur Small G#. Here we compute Belavin–Drinfeld cohomology for all non-skewsymmetric r-matrices on the Belavin–Drinfeld list for simple Lie algebras of type B, C, and D.

Teachers mathematical communication profile in explaining subject matter

NASA Astrophysics Data System (ADS)

Umami, Rohmatul; Budayasa, I. Ketut; Suwarsono, St.

2017-12-01

This study aimed to see a teachers mathematical communication profile in explaining a subject matter. It is a qualitative research. A high-school junior teacher (i.e., a teacher with 1- to 5-year experience) teaching mathematics at X-Social Class was selected as the subject of this study. The data was collected by observing the teachers mathematical communication in explaining a given material (i.e., the rule of sine) in class and an in-depth interview would be organized respectively. The result showed that the junior teacher explained the subject matter in systematic, complete, fluent, and centered manner. In this case, she began with reminding students on the previous material related to the current material to be learned, informing the current learning objectives, and finally delivering the subject matter. To support her explanation, the teacher also provided some related information, led the students attention into the given material by asking them particular related questions, and did not use any confusing terms. However, the study found that some of high-school teachers still used less appropriate language in explaining materials.

A Mathematical Diet Model

ERIC Educational Resources Information Center

Toumasis, Charalampos

2004-01-01

Emphasis on problem solving and mathematical modeling has gained considerable attention in the last few years. Connecting mathematics to other subjects and to the real world outside the classroom has received increased attention in mathematics programs. This article describes an application of simple differential equations in the field of…

Making Mathematics Phenomenal

ERIC Educational Resources Information Center

Pratt, Dave

2012-01-01

Mathematics is often portrayed as an "abstract" cerebral subject, beyond the reach of many. In response, research with digital technology has led to innovative design in which mathematics can be experienced much like everyday phenomena. This lecture examines how careful design can "phenomenalise" mathematics and support not only engagement but…

Students' perceptions of the relevance of mathematics in engineering

NASA Astrophysics Data System (ADS)

Flegg, Jennifer; Mallet, Dann; Lupton, Mandy

2012-09-01

In this article, we report on the findings of an exploratory study into the experience of students as they learn first year engineering mathematics. Here we define engineering as the application of mathematics and sciences to the building and design of projects for the use of society [M. Kirschenman and B. Brenner, Education for Civil Engineering: A Profession of Practice, Leader. Manag. Eng. 10 (2010), p. 54]. Qualitative and quantitative data on students' views of the relevance of their mathematics study to their engineering studies and future careers in engineering was collected. The students described using a range of mathematics techniques (mathematics skills developed, mathematics concepts applied to engineering and skills developed relevant for engineering) for various usages (as a subject of study, a tool for other subjects or a tool for real world problems). We found a number of themes relating to the design of engineering mathematics curriculum emerged from the data. These included the relevance of mathematics within different engineering majors, the relevance of mathematics to future studies, the relevance of learning mathematical rigour and the effectiveness of problem-solving tasks in conveying the relevance of mathematics more effectively than other forms of assessment. We make recommendations for the design of engineering mathematics curriculum based on our findings.

Subject-Specific Characteristics of Instructional Quality in Mathematics Education

ERIC Educational Resources Information Center

Schlesinger, Lena; Jentsch, Armin; Kaiser, Gabriele; König, Johannes; Blömeke, Sigrid

2018-01-01

Instructional research in German-speaking countries has conceptualized teaching quality recently according to three generic dimensions, namely, classroom management, student support and cognitive activation. However, as these dimensions are mainly regarded as generic, subject-specific aspects of mathematics instruction, e.g., the mathematical…

The errors of metacognitive evaluation on metacognitive failure of students in mathematical problem solving

NASA Astrophysics Data System (ADS)

Huda, Nizlel; Sutawidjaja, Akbar; Subanji; Rahardjo, Swasono

2018-04-01

Metacognitive activity is very important in mathematical problems solving. Metacognitive activity consists of metacognitive awareness, metacognitive evaluation and metacognitive regulation. This study aimed to reveal the errors of metacognitive evaluation in students’ metacognitive failure in solving mathematical problems. 20 students taken as research subjects were grouped into three groups: the first group was students who experienced one metacognitive failure, the second group was students who experienced two metacognitive failures and the third group was students who experienced three metacognitive failures. One person was taken from each group as the reasearch subject. The research data was collected from worksheets done using think aload then followed by interviewing the research subjects based on the results’ of subject work. The findings in this study were students who experienced metacognitive failure in solving mathematical problems tends to miscalculate metacognitive evaluation in considering the effectiveness and limitations of their thinking and the effectiveness of their chosen strategy of completion.

How Manipulatives Affect the Mathematics Achievement of Students in Nigerian Schools

ERIC Educational Resources Information Center

Aburime, F. Ehi.

2007-01-01

Mathematics is a very important subject in Nigeria. Yet, for more than twenty years, mathematics education in Nigeria has been in a sorry state. Mathematics achievement has been very low and frustrating. So far, every effort made to save Nigerian education from the devastating effect of persistent poor mathematics achievement has failed. An…

A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades

NASA Astrophysics Data System (ADS)

Murtagh, Fionn; Kurtz, Michael J.

2016-04-01

The Classification Literature Automated Search Service, an annual bibliography based on citation of one or more of a set of around 80 book or journal publications, ran from 1972 to 2012. We analyze here the years 1994 to 2011. The Classification Society's Service, as it was termed, has been produced by the Classification Society. In earlier decades it was distributed as a diskette or CD with the Journal of Classification. Among our findings are the following: an enormous increase in scholarly production post approximately 2000; a very major increase in quantity, coupled with work in different disciplines, from approximately 2004; and a major shift also from cluster analysis in earlier times having mathematics and psychology as disciplines of the journals published in, and affiliations of authors, contrasted with, in more recent times, a "centre of gravity" in management and engineering.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Index of NACA Technical Publications: 1915-1949

NASA Technical Reports Server (NTRS)

1949-01-01

The Index of NACA Technical Publications covers reports issued from the date of origin of the Committee in 1915 until approximately September 1949. Because omissions were noted after publication of the Index issued in 1947, and since many new reports have been released since that time, it was decided to issue a new volume to supersede completely the 1947 Index, with supplements to be issued regularly in the future. Commencing with all publications issued after September 1, 1949, subject classifications were revised, the most important change involving the transfer of aircraft loads reports from the Aerodynamics classification to Structures. For those maintaining a file of NACA index cards, it is recommended that cards issued for reports dated prior to September 1, 1949 be removed from the file. This volume includes the same index information. Supplements covering periods following September 1, 1949, will be arranged according to the revised subject classifications. On the pages immediately following, the subject classifications are indexed in order of breakdown. There is included in the back of this volume an alphabetical arrangement of the subject classifications.

Massive Symbolic Mathematical Computations and Their Applications

DTIC Science & Technology

1988-08-16

NUMBER ORGANIZATION (if appi cable) AFOSR I A_ /__ I F49620-87- C -0113 Bc. ADDRESS (City, Stare, and ZIP Code) %. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT...TASK WORK UNIT - < ’/I/ "//ELEMENT NO. NO. NO. ACCESSION NO. /,, AF,; c 9r ;- 6 (4/tL’ " ’ ’! /K’, 11 TITLE (Incoue Secuirty Classification) Massive...DARPA R & D Status Report AFOSR.m. 8 8-1 12Contract No. F49620-87- C -0113 MASSIVE SYMBOLIC MATHEMATICAL COMPUTATIONS AND THEIR APPLICATIONS Quarterly

Integrating First-Year Technology and Finite Mathematics Courses

ERIC Educational Resources Information Center

Shafii-Mousavi, Morteza; Kochanowski, Paul

2006-01-01

This paper describes an interdisciplinary project-based mathematics course linked to a computer technology course. The linkage encourages an appreciation of mathematics and technology as students see an immediate use for these skills in completing actual real-world projects. Linking mathematics and technology integrates subjects taught in…

Mathematics Intervention for Prevention of Neurocognitive Deficits in Childhood Leukemia

PubMed Central

Moore (Ki), Ida M.; Hockenberry, Marilyn J.; Anhalt, Cynthia; McCarthy, Kathy; Krull, Kevin R.

2011-01-01

Background Despite evidence that CNS treatment is associated with cognitive and academic impairment, interventions to prevent or mitigate these problems are limited. The purpose was to determine if early intervention can prevent declines in mathematics abilities. Procedures Fifty-seven children with ALL were enrolled and randomized to a Mathematics Intervention or Standard Care. Subjects completed neurocognitive assessments prior to the intervention, post intervention, and one year later. Parents received written results and recommendations for use with their school. The Mathematics Intervention was based on Multiple Representation Theory and delivered individually over one year. Results Thirty-two of 57 subjects completed the study and were included in data analyses. These 32 subjects completed all neurocognitive assessments and, for those in the intervention group, 40–50 hours of the mathematics intervention. There were no group differences on relevant demographic variables; risk stratification; number of intrathecal methotrexate injections or high dose systemic methotrexate. Significant improvements in calculation and applied mathematics from baseline to post-intervention (p = 0.003 and 0.002, respectively) and in visual working memory from baseline to one year follow-up (p = 0.02) were observed in the Intervention but not the Standard Care group. Results from repeated measures ANOVA demonstrated significant between group differences for applied mathematics (F[2, 29] 12.47, p<0.001) and visual working memory (F[2 29]= 5.53, p=0.009). Conclusions The Mathematics Intervention improved mathematics abilities and visual working memory compared to standard care. Future studies are needed to translate the Mathematics Intervention into a “virtual” delivery method more readily available to parents and children. PMID:21938763

Mathematics intervention for prevention of neurocognitive deficits in childhood leukemia.

PubMed

Moore, Ida M; Hockenberry, Marilyn J; Anhalt, Cynthia; McCarthy, Kathy; Krull, Kevin R

2012-08-01

Despite evidence that CNS treatment is associated with cognitive and academic impairment, interventions to prevent or mitigate these problems are limited. The purpose was to determine if early intervention can prevent declines in mathematics abilities. Fifty-seven children with ALL were enrolled and randomized to a Mathematics Intervention or Standard Care. Subjects completed neurocognitive assessments prior to the intervention, post-intervention, and 1 year later. Parents received written results and recommendations for use with their school. The Mathematics Intervention was based on Multiple Representation Theory and delivered individually over 1 year. Thirty-two of 57 subjects completed the study and were included in data analyses. These 32 subjects completed all neurocognitive assessments and, for those in the Intervention Group, 40-50 hours of the Mathematics Intervention. There were no group differences on relevant demographic variables; risk stratification; number of intrathecal methotrexate injections; or high dose systemic methotrexate. Significant improvements in calculation and applied mathematics from Baseline to Post-Intervention (P = 0.003 and 0.002, respectively) and in visual working memory from Baseline to 1 year Follow-up (P = 0.02) were observed in the Intervention but not the Standard Care Group. Results from repeated measures ANOVA demonstrated significant between group differences for applied mathematics [F(2,29) = 12.47, P < 0.001] and visual working memory [F(2,29) = 5.53, P = 0.009]. The Mathematics Intervention improved mathematics abilities and visual working memory compared to standard care. Future studies are needed to translate the Mathematics Intervention into a "virtual" delivery method more readily available to parents and children. Copyright © 2011 Wiley Periodicals, Inc.

Dewey Decimal Classification Online Project: Evaluation of a Library Schedule and Index Integrated into the Subject Searching Capabilities of an Online Catalog. Final Report.

ERIC Educational Resources Information Center

Markey, Karen; Demeyer, Anh N.

In this research project, subject terms from the Dewey Decimal Classification (DDC) Schedules and Relative Index were incorporated into an online catalog as searcher's tools for subject access, browsing, and display. Four features of the DDC were employed to help searchers browse for and match their own subject terms with the online catalog's…

Astronomy and Mathematics Education

NASA Astrophysics Data System (ADS)

Ros, Rosa M.

There are many European countries where Astronomy does not appear as a specific course on the secondary school. In these cases Astronomy content can be introduced by means of other subjects. There are some astronomical topics within the subject of Physics but this talk concerns introducing Astronomy in Mathematics classes. Teaching Astronomy through Mathematics would result in more exposure than through Physics as Mathematics is more prevalent in the curriculum. Generally it is not easy to motivate students in Mathematics but they are motivated to find out more about the universe and Astronomy current events than appears in the media. This situation can be an excellent introduction to several mathematics topics. The teachers in secondary and high school can use this idea in order to present more attractive mathematics courses. In particular some different examples will be offered regarding * Angles and spherical coordinates considering star traces * Logarithms and visual magnitudes * Plane trigonometry related orbital movements * Spherical trigonometry in connection with ecliptic obliquity * Conic curves related to sundial at several latitudes Some students do not enjoy studying Mathematics but they can be attracted by practical situations using Applied Mathematics: Astronomy is always very attractive to teenagers.

An Attempt of Making Program-Generated Animation in a Beginners’ Programming Class

NASA Astrophysics Data System (ADS)

Matsuyama, Chieko; Nakashima, Toyoshiro; Ishii, Naohiro

In general, mathematical subjects are used for programming education in universities. In this case, many students lose the interest in the programming because the students have the preconception that is difficult to program by using the mathematical expressions. Especially beginners of the programming are a tendency to lose the interest. Therefore it is pointed out to use the subjects which do not need mathematical knowledge as much as possible. In this paper the authors have tried to make animation that are generated by programs instead of the mathematical subjects in a beginners’ programming class using C language used in a wide-ranging field. The authors discuss about improvements of the interest of students for programming by the try that is to make animation by programs in a programming class and refer to its effects.

Female and male adolescents' subjective orientations to mathematics and the influence of those orientations on postsecondary majors.

PubMed

Perez-Felkner, Lara; McDonald, Sarah-Kathryn; Schneider, Barbara; Grogan, Erin

2012-11-01

Although important strides toward gender parity have been made in several scientific fields, women remain underrepresented in the physical sciences, engineering, mathematics, and computer sciences (PEMCs). This study examines the effects of adolescents' subjective orientations, course taking, and academic performance on the likelihood of majoring in PEMC in college. Results indicate that racial-ethnic and gender underrepresentation in science, technology, engineering, and mathematics (STEM) fields are interrelated and should be examined with attention to the intersecting factors influencing female and racial-ethnic minority adolescents' pathways toward careers in these fields. Among those who major in PEMC fields, women closely resemble men with respect to their subjective orientations. The effects of subjective orientations on women's chances of majoring in PEMC vary by their secondary school mathematics course completion levels. Women who take more mathematics courses are more likely to major in PEMC; however, course taking alone does not attenuate gender disparities in declaring these majors. High mathematics ability (as measured by standardized test scores in the 10th grade) appears to be positively associated with women's selection of social, behavioral, clinical, and health science majors. This association is less robust (and slightly negative) for women in PEMC. While advanced course taking appears to assist women in selecting PEMC majors, women who enter these fields may not be as strong as those who select other, less male-dominated scientific fields.

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy.

PubMed

Karamzadeh, Nader; Amyot, Franck; Kenney, Kimbra; Anderson, Afrouz; Chowdhry, Fatima; Dashtestani, Hadis; Wassermann, Eric M; Chernomordik, Victor; Boccara, Claude; Wegman, Edward; Diaz-Arrastia, Ramon; Gandjbakhche, Amir H

2016-11-01

We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

EPA Releases Guidance on a Voluntary Pilot Program to Reduce Animal Testing

EPA Pesticide Factsheets

EPA is announcing the start of a voluntary pilot program to evaluate the usefulness and acceptability of a mathematical tool that estimates the toxicological classification of a chemical, which is used in the GHS.

Mixtures Equation Pilot Program to Reduce Animal Testing

EPA Pesticide Factsheets

EPA is announcing the start of a pilot program to evaluate the usefulness and acceptability of a mathematical tool (the GHS Mixtures Equation), which is used in the Globally Harmonized System of Classification and Labeling of Chemicals (GHS).

Enhancing Math through Literature.

ERIC Educational Resources Information Center

O'Banion, Carie

1997-01-01

Provides a bibliography of children's literature exploring mathematical concepts: classification; place value and numeration systems; counting, addition, and subtraction; multiplication and division; fractions; estimation; big numbers; geometry; measurement; and games and puzzles. Highlights one book for each concept, suggests class activities,…

Mathematical Geology

ERIC Educational Resources Information Center

Merriam, Daniel F.

1978-01-01

Geomathematics is a developing field that is being used in practical applications. Classification is an important element and the dynamic-cluster method (DCM), a nonhierarchial procedure, was introduced this past year. A method for testing the degree of cluster distinctness was developed also. (MA)

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

Mathematical disposition of junior high school students viewed from learning styles

NASA Astrophysics Data System (ADS)

Putra, Arief Karunia; Budiyono, Slamet, Isnandar

2017-08-01

The relevance of this study is the growth of character values for students in Indonesia. Mathematics is a subject that builds the character values for students. It can be seen from the students' confidence in answering mathematics problems, their persistent and resilience in mathematics task. In addition, students have a curiosity in mathematics and appreciate the usefulness of mathematics. In mathematics, it is called a mathematical disposition. One of the factors that can affect students' mathematical disposition is learning style. Each student has a dominant learning style. Three of the most popular ones are visual, auditory, and kinesthetic. The most important uses of learning styles is that it makes it easy for teachers to incorporate them into their teaching. The purpose of this study was to determine which one that gives better mathematical dispositions among students with learning styles of visual, auditory, or kinesthetic. The subjects were 150 students in Sleman regency. Data obtained through questionnaires. Based on data analysis that has been done with benchmark assessment method, it can be concluded that students with visual learning style has a mathematical disposition better than students with auditory and kinesthetic learning styles, while students with kinesthetic learning style has a mathematical disposition better than students with auditory learning style. These results can be used as a reference for students with individual learning styles to improve the mathematical positive disposition in the learning process of mathematics.

Emotion, Confidence, Perception and Expectation Case of Mathematics

ERIC Educational Resources Information Center

Dogan, Hamide

2012-01-01

Students' concerns about mathematics can significantly affect their ability to learn the subject. In particular, their anxieties and attitudes can greatly affect how they perceive their own mathematical competence, and in return, this may make them reluctant to pursue mathematical studies. Many researchers believe in the role of active learning…

The Use of GBL to Teach Mathematics in Higher Education

ERIC Educational Resources Information Center

Naik, Nitin

2017-01-01

Innovation in learning and teaching is an everyday requirement in contemporary higher education (HE), especially in challenging subjects such as mathematics. Teaching mathematics to students with limited experience of formal mathematical instruction is a good example of a demanding pedagogical undertaking where innovatory practice can help HE…

Enriching the Teaching of Biology with Mathematical Concepts

ERIC Educational Resources Information Center

Andersen, Janet

2007-01-01

Secondary school educators are told to teach more mathematics and science to their students to help them become more proficient in the two subjects. Coordination of mathematics and science teaching is recognized as another means of improving proficiency. The National Science Foundation has funded the "Mathematics, Science and Technology…

Mathematical Problem Solving Ability of Eleventh Standard Students

ERIC Educational Resources Information Center

Priya, J. Johnsi

2017-01-01

There is a general assertion among mathematics instructors that learners need to acquire problem solving expertise, figure out how to communicate using mathematics knowledge and aptitude, create numerical reasoning and thinking, to see the interconnectedness amongst mathematics and other subjects. Based on this perspective, the present study aims…

Symbolising the Real of Mathematics Education

ERIC Educational Resources Information Center

Pais, Alexandre

2015-01-01

This text, occasioned by a critical reading of Tony Brown's new book "Mathematics Education and Subjectivity," aims at contributing to the building of a sociopolitical approach to mathematics education based on Lacanian psychoanalysis and Slavoj Žižek's philosophy. Brown has been bringing into the field of mathematics education the work…

Mathematical Difficulty: Does Early Intervention Enhance Mathematical Performance?

ERIC Educational Resources Information Center

Graham, Jennifer

2008-01-01

The need to ask educators about their opinions on the subject to what extent early intervention methods enhance mathematical performance is long overdue. The purpose of this quantitative research is to examine the extent to which teachers agree that early intervention methods enhance the mathematical performance of students with mathematical…

From Mathematical Reading to Mathematical Literacy

ERIC Educational Resources Information Center

Beaudine, Gregory

2018-01-01

If teachers have a deeper comprehension of their students' reading ability, it may lead to students' improved literacy and understanding of the subject. The account presented in this article of the author's growing interest in mathematical literacy specifically involves mathematical reading. This shift in interest began with a six-week…

Mathematizing Process of Junior High School Students to Improve Mathematics Literacy Refers PISA on RCP Learning

NASA Astrophysics Data System (ADS)

Wardono; Mariani, S.; Hendikawati, P.; Ikayani

2017-04-01

Mathematizing process (MP) is the process of modeling a phenomenon mathematically or establish the concept of a phenomenon. There are two mathematizing that is Mathematizing Horizontal (MH) and Mathematizing Vertical (MV). MH as events changes contextual problems into mathematical problems, while MV is the process of formulation of the problem into a variety of settlement mathematics by using some appropriate rules. Mathematics Literacy (ML) is the ability to formulate, implement and interpret mathematics in various contexts, including the capacity to perform reasoning mathematically and using the concepts, procedures, and facts to describe, explain or predict phenomena incident. If junior high school students are conditioned continuously to conduct mathematizing activities on RCP (RME-Card Problem) learning, it will be able to improve ML that refers PISA. The purpose of this research is to know the capability of the MP grade VIII on ML content shape and space with the matter of the cube and beams with RCP learning better than the scientific learning, upgrade MP grade VIII in the issue of the cube and beams with RCP learning better than the scientific learning in terms of cognitive styles reflective and impulsive the MP grade VIII with the approach of the RCP learning in terms of cognitive styles reflective and impulsive This research is the mixed methods model concurrent embedded. The population in this study, i.e., class VIII SMPN 1 Batang with sample two class. Data were taken with the observation, interviews, and tests and analyzed with a different test average of one party the right qualitative and descriptive. The results of this study demonstrate the capability of the MP student with RCP learning better than the scientific learning, upgrade MP with RCP learning better compare with scientific learning in term cognitive style of reflective and impulsive. The subject of the reflective group top, middle, and bottom can meet all the process of MH indicators are then the subject of the reflective upper and intermediate group can meet all the MV indicators but to lower groups can only fulfill some MV indicators. The subject is impulsive upper and middle group can meet all the MH indicators but to lower groups can only meet some MH indicator, then the subject is impulsive group can meet all the MV indicators but for middle and the bottom group can only fulfill some MV indicators.

U.S. Geological Survey Library classification system

USGS Publications Warehouse

Sasscer, R. Scott

2000-01-01

The U.S. Geological Survey Library classification system has been designed for earth science libraries. It is a tool for assigning call numbers to earth science and allied pure science materials in order to collect these materials into related subject groups on the library shelves and arrange them alphabetically by author and title. The classification can be used as a retrieval system to access materials through the subject and geographic numbers.The classification scheme has been developed over the years since 1904 to meet the ever-changing needs of increased specialization and the development of new areas of research in the earth sciences. The system contains seven schedules: Subject scheduleGeological survey schedule Earth science periodical scheduleGovernment document periodical scheduleGeneral science periodical schedule Earth science map schedule Geographic schedule Introduction provides detailed instructions on the construction of call numbers for works falling into the framework of the classification schedules.The tables following the introduction can be quickly accessed through the use of the newly expanded subject index.The purpose of this publication is to provide the earth science community with a classification and retrieval system for earth science materials, to offer sufficient explanation of its structure and use, and to enable library staff and clientele to classify or access research materials in a library collection.

Long-publishing Astronomers, or the Problem of Classification

NASA Astrophysics Data System (ADS)

Tenn, Joseph S.

2012-01-01

In response to several discussions among astronomers and historians of astronomy, I started out to prepare a paper on long-publishing astronomers--those who published for 70, 75, or even 80 years. However, I soon ran into a number of questions of classification, and that turned out to be at least as interesting. How do we decide on classifications? Every time we choose classes, such as asteroids, planets and stars, we run into objects that seem to be in between. In the present case a number of questions arise: Who is an astronomer? Several of those with the longest publication runs started out as physicists, published for years in that subject only, and later took up astrophysics, eventually publishing a few (or even no) papers in astronomy journals. What is a publication? Should we count publications in physics, chemistry, or mathematics? What about philosophy of science or history of science? What about the elderly retired astronomer presenting a memoir of his or her own work? Abstracts of oral presentations? Textbooks? Monographs? Book reviews? Obituaries? Then there is the problem of posthumous publications. Probably most would include papers in the pipeline when the astronomer dies, but what about the case where the coauthor finally publishes the paper eight years after the death of the person of interest? I eventually decided to make two lists, one which would include most of the above, and one restricted to papers that make contributions to physical science. Note that I do not say "refereed,” as that presents its own problems, especially when applied to periods before the twentieth century.

Mathematics and the Flight from the Feminine: The Discursive Construction of Gendered Subjectivity in Mathematics Textbooks

ERIC Educational Resources Information Center

Hottinger, Sara

2010-01-01

There is a widespread awareness in the American culture that women do not pursue careers in mathematics-related fields in equal numbers to men. Efforts to address this disparity by reforming mathematics education have met with some success; recent research shows that girls' achievements in mathematics stay on par with those of boys through…

Values Education in the Mathematics Classroom: Subject Values, Educational Values and One Teacher's Articulation of Her Practice

ERIC Educational Resources Information Center

Bills, Liz; Husbands, Chris

2005-01-01

The issue of values has been a longstanding concern of mathematics education research. Attempts have been made to analyze the specifically mathematical values which characterize the practice of mathematics teachers. In this paper we draw on one teacher's articulation of her practice to explore values issues in the teaching of mathematics, drawing…

Mathematics Teachers as Moral Educators: The Implications of Conceiving of Mathematics as a Technology

ERIC Educational Resources Information Center

Warnick, Bryan R.; Stemhagen, Kurt

2007-01-01

Mathematics educators often fail to see that their subject has social and ethical dimensions. If anything, mathematics is seen as a neutral tool that has a social dimension only because it can be used to solve social problems. This study critically examines this idea by arguing that, although school mathematics is indeed a technology, technology…

The Effect of a Pre-University Mathematics Bridging Course on Adult Learners' Self-Efficacy and Retention Rates in STEM Subjects

ERIC Educational Resources Information Center

Johnson, Patrick; O'Keeffe, Lisa

2016-01-01

In August 2008, the Mathematics Learning Centre at the University of Limerick initiated a mathematics bridging course, entitled "Head Start Maths", to provide mathematics revision for adult learners about to embark on science or technology degree programmes. The aim of Head Start Maths was to revise mathematics fundamentals before the…

Students’ Representation in Mathematical Word Problem-Solving: Exploring Students’ Self-efficacy

NASA Astrophysics Data System (ADS)

Sahendra, A.; Budiarto, M. T.; Fuad, Y.

2018-01-01

This descriptive qualitative research aims at investigating student represented in mathematical word problem solving based on self-efficacy. The research subjects are two eighth graders at a school in Surabaya with equal mathematical ability consisting of two female students with high and low self-efficacy. The subjects were chosen based on the results of test of mathematical ability, documentation of the result of middle test in even semester of 2016/2017 academic year, and results of questionnaire of mathematics word problem in terms of self-efficacy scale. The selected students were asked to do mathematical word problem solving and be interviewed. The result of this study shows that students with high self-efficacy tend to use multiple representations of sketches and mathematical models, whereas students with low self-efficacy tend to use single representation of sketches or mathematical models only in mathematical word problem-solving. This study emphasizes that teachers should pay attention of student’s representation as a consideration of designing innovative learning in order to increase the self-efficacy of each student to achieve maximum mathematical achievement although it still requires adjustment to the school situation and condition.

Global similarity predicts dissociation of classification and recognition: evidence questioning the implicit-explicit learning distinction in amnesia.

PubMed

Jamieson, Randall K; Holmes, Signy; Mewhort, D J K

2010-11-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort unstudied grammatical exemplars from lures, whereas in recognition, they sort studied grammatical exemplars from lures. Hence, global similarity is necessarily greater in recognition than in classification. Moreover, a grammatical exemplar's similarity to studied exemplars is a nonlinear function of the integrity of the data in memory. Assuming that data integrity is better for control subjects than for subjects with amnesia, the nonlinear relation combined with the advantage for recognition over classification predicts the dissociation of recognition and classification. To illustrate the dissociation of recognition and classification in healthy undergraduates, we manipulated study time to vary the integrity of the data in memory and brought the dissociation under experimental control. We argue that the dissociation reflects a general cost in memory rather than a selective impairment of separate procedural and episodic systems. (c) 2010 APA, all rights reserved

Math Organization Attempts to Bring Focus to Subject

ERIC Educational Resources Information Center

Cavanagh, Sean

2006-01-01

More than 15 years after its publication of influential national standards in mathematics, a leading professional organization has unveiled new and more focused guidelines that describe the crucial skills and content students should master in that subject in elementary and middle school. The National Council of Teachers of Mathematics released…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carpenter, J.A.

This report is a sequel to ORNL/CSD-46: KWIC Index For Numerical Algebra (March 1980) and in turn the both of these ae sequels to Professor A.S. Householer's report of the same name: ORNL-4778 Revised (June 1975). The area covered remains nearly the same as Professor Householder's guidelines, roughly delineated by the American Mathematical Society classification 15, 65F and 65H together with their secondary categories, but with little coverage of infinite matrices, matrices over fields of positive characteristic, operator theory, optimization and those facets of matrix theory primarily combinatorial in nature. The period covered by this report is roughly July 1979more » through December 1980, as measured by the appearance of the articles in the American Mathematical Society's Contents of Mathematical Publications. The review citations are limited to the Mathematical Reviews (MR) and Das Zentralblatt fur Mathematik Und Ihre Grenzgebiete (ZBL).« less

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

PubMed Central

Luo, Gang; Min, Wanli

2007-01-01

Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Mathematical Methods of Subjective Modeling in Scientific Research: I. The Mathematical and Empirical Basis

NASA Astrophysics Data System (ADS)

Pyt'ev, Yu. P.

2018-01-01

mathematical formalism for subjective modeling, based on modelling of uncertainty, reflecting unreliability of subjective information and fuzziness that is common for its content. The model of subjective judgments on values of an unknown parameter x ∈ X of the model M( x) of a research object is defined by the researcher-modeler as a space1 ( X, p( X), P{I^{\\bar x}}, Be{l^{\\bar x}}) with plausibility P{I^{\\bar x}} and believability Be{l^{\\bar x}} measures, where x is an uncertain element taking values in X that models researcher—modeler's uncertain propositions about an unknown x ∈ X, measures P{I^{\\bar x}}, Be{l^{\\bar x}} model modalities of a researcher-modeler's subjective judgments on the validity of each x ∈ X: the value of P{I^{\\bar x}}(\\tilde x = x) determines how relatively plausible, in his opinion, the equality (\\tilde x = x) is, while the value of Be{l^{\\bar x}}(\\tilde x = x) determines how the inequality (\\tilde x = x) should be relatively believed in. Versions of plausibility Pl and believability Bel measures and pl- and bel-integrals that inherit some traits of probabilities, psychophysics and take into account interests of researcher-modeler groups are considered. It is shown that the mathematical formalism of subjective modeling, unlike "standard" mathematical modeling, •enables a researcher-modeler to model both precise formalized knowledge and non-formalized unreliable knowledge, from complete ignorance to precise knowledge of the model of a research object, to calculate relative plausibilities and believabilities of any features of a research object that are specified by its subjective model M(\\tilde x), and if the data on observations of a research object is available, then it: •enables him to estimate the adequacy of subjective model to the research objective, to correct it by combining subjective ideas and the observation data after testing their consistency, and, finally, to empirically recover the model of a research object.

A Mathematical Model to Predict and Maintain the Neutral Buoyancy of Suited Astronauts

NASA Technical Reports Server (NTRS)

Clowers, Kurt; Jaramillo, Marcos; Nguyen, Daniel; Sweet, Robert; Rajulu, Sudhakar

2006-01-01

A previous study reported that inadequate weigh outs of suited subjects contribute to fatigue and the risk of injury during training in the Neutral Buoyancy Laboratory (NBL). Another study suggested that shoulder injuries observed in suited subjects who train in the NBL may be attributed to excessive righting moments caused by a non-optimal weigh out. The purpose of this study was to develop a mathematical model to predict and maintain the neutral buoyancy of suited subjects during training operations at the NBL. Due to time constraints, one certified NBL support diver served as a subject (height: 66.54 in; weight: 182 lbs) for this study and only one complete test was conducted. The study was divided into two runs for which the first run required the NBL divers to perform a weigh out similar to a suited astronaut on a scuba diver wearing a mock Portable Life Support System and a Displays and Control Module. For the second run, the same subject and equipment were weighed out according to the mathematical model. The objective of each run was to achieve a neutrally buoyant subject floating 450 to the pool floor. Motion data was collected using two underwater cameras and analyzed using Dartfish video analysis software while force and moment data were recorded using an AMTI force plate. The results from the NBL divers visual run indicate that the subject was floating at an angle of 29.50 while the resultant force and moment data were 1.139 lb and 1.125 ft-lb respectively. The mathematical model s weigh out resulted in the subject floating at an angle of 37.40 and a resultant force of 0.765 lb and resultant moment of 1.248 ft-lb. The mathematical model was better able to orient the subject and reduce resultant moment and force as compared to the NBL divers.

Impact of Growth in the Universe of Subjects on Classification.

ERIC Educational Resources Information Center

Ranganathan, Shiyali Ramamritam

The development of the removal of rigidity in library classification is traced from the Enumerative Classification of DC (1876) through the Nearly-Faceted Classification of UDC (1896), the rigidly, though fully faceted version of CC (1933), the generalized faceted structure of version 2 of CC (1949), down to the Freely Faceted Classification of…

The composite sequential clustering technique for analysis of multispectral scanner data

NASA Technical Reports Server (NTRS)

Su, M. Y.

1972-01-01

The clustering technique consists of two parts: (1) a sequential statistical clustering which is essentially a sequential variance analysis, and (2) a generalized K-means clustering. In this composite clustering technique, the output of (1) is a set of initial clusters which are input to (2) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum likelihood classification techniques. The mathematical algorithms for the composite sequential clustering program and a detailed computer program description with job setup are given.

Mathematical psychology.

PubMed

Batchelder, William H

2010-09-01

Mathematical psychology is a sub-field of psychology that started in the 1950s and has continued to grow as an important contributor to formal psychological theory, especially in the cognitive areas of psychology such as learning, memory, classification, choice response time, decision making, attention, and problem solving. In addition, there are several scientific sub-areas that were originated by mathematical psychologists such as the foundations of measurement, stochastic memory models, and psychologically motivated reformulations of expected utility theory. Mathematical psychology does not include all uses of mathematics and statistics in psychology, and indeed there is a long history of such uses especially in the areas of perception and psychometrics. What is most unique about mathematical psychology is its approach to theory construction. While accepting the behaviorist dictum that the data in psychology must be observable and replicable, mathematical models are specified in terms of unobservable formal constructs that can predict detailed aspects of data across multiple experimental and natural settings. By now almost all the substantive areas of cognitive and experimental psychology have formal mathematical models and theories, and many of these are due to researchers that identify with mathematical psychology. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

Mathematics Anxiety and Preservice Elementary Teachers' Confidence to Teach Mathematics and Science

ERIC Educational Resources Information Center

Bursal, Murat; Paznokas, Lynda

2006-01-01

Sixty-five preservice elementary teachers' math anxiety levels and confidence levels to teach elementary mathematics and science were measured. The confidence scores of subjects in different math anxiety groups were compared and the relationships between their math anxiety levels and confidence levels to teach mathematics and science were…

Beauty as Fit: A Metaphor in Mathematics?

ERIC Educational Resources Information Center

Raman, Manya; Öhman, Lars-Daniel

2013-01-01

Beauty, which plays a central role in the practice of mathematics (Sinclair 2002), is almost absent in discussions of school mathematics (Dreyfus and Eisenberg 1986). This is problematic, because students will decide whether or not to continue their studies in mathematics without having an accurate picture of what the subject is about. In order to…

Actitud Hacia las Matematicas: Revision Bibliografica (Attitudes Toward Mathematics: Revised Bibliography). Publication No. 39.

ERIC Educational Resources Information Center

Rodriguez Feijoo, Nelida

Investigations about attitudes toward mathematics carried out in the past decade were revised. The instruments used to measure attitudes toward mathematics were analysed as well as the attitudes toward different aspects of mathematics, their relation with other school subjects and their stability through time. Opinions about the influence of…

Research on Mathematical Animation Using Pascal Animation as an Example

ERIC Educational Resources Information Center

Weng, Ting-Sheng; Yang, Der-Ching

2017-01-01

Most students thinking mathematics is a difficult subject. This study aims to enhance students' motivation and efficiency in learning mathematics. This study developed 3D animation on the binomial theorem with historical stories of mathematics as the plot. It also examined the effect of animation on students' learning willingness and…

Identity and Ethnomathematics Projects in Papua New Guinea

ERIC Educational Resources Information Center

Owens, Kay

2012-01-01

Indigenous students may find mathematics in schools difficult because there is discontinuity between cultural mathematics and school mathematics. One of the reasons for this is that their teacher's identity as a mathematical thinker may not link to their cultural ways of thinking. In Papua New Guinea, there is a subject to assist student teachers…

The Factors Influencing Mathematics Students to Choose Teaching as a Career

ERIC Educational Resources Information Center

du Preez, Michelle

2018-01-01

Prompted by the poor state of mathematics education in South Africa and the shortage of competent mathematics teachers, this study sought to identify what factors influenced 40 Postgraduate Certificate in Education (PGCE) students at three universities in the Western Cape Province, with Mathematics as a major subject, to choose teaching as a…

Group by Subject or by Ability? Tertiary Mathematics for Engineering Students

ERIC Educational Resources Information Center

Plank, Michael; James, Alex; Hannah, John

2011-01-01

The mathematics topics taught to engineering students at university are ostensibly no different to those taught to mathematics majors, so should these students be taught together or separately? Should engineering students be segregated by ability in their mathematics classes? This study analyses the grades of over 1000 engineering students, and…

The Art of Teaching the Art of Applying Mathematics

ERIC Educational Resources Information Center

Lighthill, M. J.

1971-01-01

This article (the 1971 Presidential Address to the Mathematical Association of U. K.) makes a plea that college teachers of mathematics should be better aware of the applications of mathematics in other subjects. As an example, the author describes the use of differential equations to solve certain vibrational problems in mechanical engineering.…

The Origins of Liberal Arts Mathematics

ERIC Educational Resources Information Center

George, Michael

2010-01-01

"Liberal arts mathematics" differs from traditional mathematics courses in that it consists of a disparate collection of topics, rather than being organized around a single mathematical subject. As a result, the educational rationale for and purpose of the course may be vague both to instructors and students. The purpose of this study is to…

Practicing Engineers' Perspective on Mathematics and Mathematics Education in College

ERIC Educational Resources Information Center

Tosmur-Bayazit, Nermin; Ubuz, Behiye

2013-01-01

This paper reports on a qualitative study focusing on engineers' point of view in regard to university mathematics and mathematics education. An individual interview was conducted with three electrical and two mechanical engineers between the ages of 25-40, all engaged in successful careers. The subjects were requested to reflect upon themselves…

Enhancing Self-Efficacy of Elementary School Students to Learn Mathematics

ERIC Educational Resources Information Center

Katz, Sara

2015-01-01

Mathematics is a key to all scientific subjects. Learning mathematics requires cognitive and meta-cognitive effort. Many students suffer from mathematics anxiety that very often leads to physiological symptoms. Self-efficacy is defined as people's beliefs about their capabilities to produce designated levels of performance that affect their lives.…

Loving and Loathing: Portrayals of School Mathematics in Young Adult Fiction

ERIC Educational Resources Information Center

Darragh, Lisa

2018-01-01

Images of mathematics and mathematicians are often negative and stereotyped. These portrayals may work to construct our impressions of mathematics and influence students' identity with and future participation in the subject. This study examined young adult fiction as a context in which school mathematics is portrayed and constructed. I used…

Promoting Students' Self-Directed Learning Ability through Teaching Mathematics for Social Justice

ERIC Educational Resources Information Center

Voss, Richard; Rickards, Tony

2016-01-01

Mathematics is a subject which is often taught using abstract methods and processes. These methods by their very nature may for students alienate the relationship between Mathematics and real life situations. Further, these abstract methods and processes may disenfranchise students from becoming self-directed learners of Mathematics. A solution to…

Infrared differential-absorption Mueller matrix spectroscopy and neural network-based data fusion for biological aerosol standoff detection.

PubMed

Carrieri, Arthur H; Copper, Jack; Owens, David J; Roese, Erik S; Bottiger, Jerold R; Everly, Robert D; Hung, Kevin C

2010-01-20

An active spectrophotopolarimeter sensor and support system were developed for a military/civilian defense feasibility study concerning the identification and standoff detection of biological aerosols. Plumes of warfare agent surrogates gamma-irradiated Bacillus subtilis and chicken egg white albumen (analytes), Arizona road dust (terrestrial interferent), water mist (atmospheric interferent), and talcum powders (experiment controls) were dispersed inside windowless chambers and interrogated by multiple CO(2) laser beams spanning 9.1-12.0 microm wavelengths (lambda). Molecular vibration and vibration-rotation activities by the subject analyte are fundamentally strong within this "fingerprint" middle infrared spectral region. Distinct polarization-modulations of incident irradiance and backscatter radiance of tuned beams generate the Mueller matrix (M) of subject aerosol. Strings of all 15 normalized elements {M(ij)(lambda)/M(11)(lambda)}, which completely describe physical and geometric attributes of the aerosol particles, are input fields for training hybrid Kohonen self-organizing map feed-forward artificial neural networks (ANNs). The properly trained and validated ANN model performs pattern recognition and type-classification tasks via internal mappings. A typical ANN that mathematically clusters analyte, interferent, and control aerosols with nil overlap of species is illustrated, including sensitivity analysis of performance.

Effects of Experiential Learning Approach on Students' Mathematical Creativity among Secondary School Students of Kericho East Sub-County, Kenya

ERIC Educational Resources Information Center

Chesimet, M. C.; Githua, B. N.; Ng'eno, J. K.

2016-01-01

Mathematics is a subject which seeks to understand patterns that permeate both the world around us and the mind within us. There are many ways of thinking and the kind of thinking one learns in mathematics is an ability to handle abstraction and solve problems that require knowledge of mathematics. Mathematical creativity is essential for…

`I'm a natural and I do it for love!': exploring students' accounts of studying mathematics

NASA Astrophysics Data System (ADS)

Bartholomew, Hannah; Darragh, Lisa; Ell, Fiona; Saunders, Jeanette

2011-10-01

Drawing on in-depth interviews with the third year students at a New Zealand university, we explore the ways in which students speak about studying mathematics, their relationship with the subject and how this has developed over time. These interviews were conducted as part of a project looking at undergraduate mathematics from the perspective of lecturers, students, and interactions in lectures, and funded by the Teaching and Learning Research Initiative in New Zealand. We use the work of Gee [Identity as an analytic lens for research in education, Rev. Res. Educ. 25 (2000), pp. 99-125] to tease out some discourses of mathematics that frame students' participation in the subject, and show that notions of 'natural ability', and of being passionate about the study of mathematics for its own sake, dominate the narratives of mathematics students. In developing this position, we turn to psycho-social theorists such as Hollway and Jefferson [Doing Qualitative Research Differently: Free Association, Narrative and the Interview Method, Sage, London, 1997] so as to question the 'face-value' meanings of these narratives and to argue that students' choices have less to do with rational decision making than with constructing identities that protect vulnerable aspects of themselves. Finally, we develop the metaphor of a 'maths club', which we feel captures something of the culture of mathematics and students' orientations towards the subject. This metaphor also allows us to raise questions about widening participation in mathematics.

Mathematics Fitness.

ERIC Educational Resources Information Center

Trezise, Kathleen A.

1998-01-01

Students receiving mathematics instruction relevant to life will understand that mathematics is part of the real world and not just another school subject. Presents an activity that integrates rational numbers with health-related science content as students collect data and engage in decision making. (ASK)

The analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference

NASA Astrophysics Data System (ADS)

Ma'rufi, Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

The aim of this study was to describe the analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference. The purpose of this study is to describe the analysis of mathematics teacher's learning on limit algebraic functions in terms of the differences of teaching experience. Learning analysis focused on Pedagogical Content Knowledge (PCK) of teachers in mathematics on limit algebraic functions related to the knowledge of pedagogy. PCK of teachers on limit algebraic function is a type of specialized knowledge for teachers on how to teach limit algebraic function that can be understood by students. Subjects are two high school mathematics teacher who has difference of teaching experience they are one Novice Teacher (NP) and one Experienced Teacher (ET). Data are collected through observation of learning in the class, videos of learning, and then analyzed using qualitative analysis. Teacher's knowledge of Pedagogic defined as a knowledge and understanding of teacher about planning and organizing of learning, and application of learning strategy. The research results showed that the Knowledge of Pedagogy on subject NT in mathematics learning on the material of limit function algebra showed that the subject NT tended to describe procedurally, without explaining the reasons why such steps were used, asking questions which tended to be monotonous not be guiding and digging deeper, and less varied in the use of learning strategies while subject ET gave limited guidance and opportunities to the students to find their own answers, exploit the potential of students to answer questions, provide an opportunity for students to interact and work in groups, and subject ET tended to combine conceptual and procedural explanation.

77 FR 17463 - Notice of Submission for OMB Review; Institute of Education Sciences; National Assessment of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-26

..., 8, and 12 in various subject areas, such as mathematics, reading, writing, science, U.S. history, civics, geography, economics, and the arts. DATES: Interested persons are invited to submit comments on... various subject areas, such as mathematics, reading, writing, science, U.S. history, civics, geography...

The True Growth Rate and the Inflation Balancing Principle.

ERIC Educational Resources Information Center

Thompson, Robert C.

1983-01-01

The demise of mathematics of finance as a subject is discussed and a resurgence is seen as possible, but the traditional instructional presentation is seen as in need of modernization. Financial mathematics is referred to as a beautiful subject when inflation is incorporated, provided that calculators are used in computations. (Author/MP)

Is Knowing Another Language as Important as Knowing "Core" Subjects Like Mathematics or Science

ERIC Educational Resources Information Center

Kouritzin, Sandra G.

2012-01-01

This article explores, through interview data with 125 respondents in Canada, whether the study of foreign languages can be considered as important as the study of the "core" STEMM (science, technology, engineering, mathematics, medicine) subjects in school and university curricula. Five categories of interviewees, including those…

Qualified, but Not Choosing STEM at University: Unconscious Influences on Choice of Study

ERIC Educational Resources Information Center

Rodd, Melissa; Reiss, Michael; Mujtaba, Tamjid

2014-01-01

This article offers explanations as to why good candidates for mathematics or physics degrees might opt to study subjects other than STEM (science, technology, engineering, mathematics) subjects at university. Results come from analysis, informed by psychoanalytic theory and practice, of narrative-style interviews conducted with first-year…

Female and Male Adolescents' Subjective Orientations to Mathematics and the Influence of Those Orientations on Postsecondary Majors

ERIC Educational Resources Information Center

Perez-Felkner, Lara; McDonald, Sarah-Kathryn; Schneider, Barbara; Grogan, Erin

2012-01-01

Although important strides toward gender parity have been made in several scientific fields, women remain underrepresented in the physical sciences, engineering, mathematics, and computer sciences (PEMCs). This study examines the effects of adolescents' subjective orientations, course taking, and academic performance on the likelihood of majoring…

Project-Based Activity: Root of Research and Creative Thinking

ERIC Educational Resources Information Center

Rambely, A. S.; Ahmad, R. R.; Majid, N.; M-Suradi, N. R.; Din, U. K. S.; A-Rahman, I.; Mohamed, F.; Rahim, F.; Abu-Hanifah, S.

2013-01-01

Decreasing of interest in mathematics and science subjects among students in Malaysia has been discussed lately. Applications of mathematics and science in real world settings might be able to facilitate increased interests in the subjects, especially in doing research. Therefore, the aim of this paper is to manifest that learning mathematics…

With an Eye on the Mathematical Horizon: Dilemmas of Teaching Elementary School Mathematics. Craft Paper 90-3.

ERIC Educational Resources Information Center

Ball, Deborah Loewenberg

Much educational discourse centers on the importance of teachers' subject matter knowledge. Complementing concerns for subject matter knowledge is interest in developing and studying alternative pedagogies that emphasize active learning and meaningful engagement. Teaching and learning would be improved, so the argument goes, if classrooms were…

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Sex-related Differences in the Determinants and Process of Science and Mathematics Choice in Pre-university Education

NASA Astrophysics Data System (ADS)

van Langen, Annemarie; Rekers-Mombarg, Lyset; Dekkers, Hetty

2006-01-01

The more science and mathematics subjects that pupils in pre-university education include in their final examination package, the more future academic routes are available to them. Equality of educational opportunity is thus threatened when groups of pupils, distinguished by sex and family background but otherwise of equal capacities and achievement, are found to differ in their choices. This proposition is examined using data from a large Dutch cohort. Multilevel analyses show that the choice of science and mathematics subjects by girls is influenced by their family background while the choice by boys is not. The influence of various pupil and family variables on the subject selection process is explored via path analyses. The results confirm the importance of viewing subject choice as a chronological process that progresses differently for boys and girls.

Mathematical modeling for novel cancer drug discovery and development.

PubMed

Zhang, Ping; Brusic, Vladimir

2014-10-01

Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

Behavioral Variability, Learning Processes, and Creativity

DTIC Science & Technology

1990-09-01

Nursery Schools . ~ 9-10 y.o. subjects, at the concrete operative stage and coming from Primary Schools . - 14-15 y.o. subjects, at the formal thought...stage and coming from General Secondary Schools (no Technical School subject has been considered). - Adults, students at the University. Cognitive...classifications combine in a single situation, the operations of seiation and of classification, as approached in the classical Piaget’s procedures

10 CFR 1045.15 - Classification and declassification presumptions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... criteria in § 1045.16 indicates otherwise: (1) Basic science: mathematics, chemistry, theoretical and experimental physics, engineering, materials science, biology and medicine; (2) Magnetic confinement fusion...); (5) Fact of use of safety features (e.g., insensitive high explosives, fire resistant pits) to lower...

10 CFR 1045.15 - Classification and declassification presumptions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... criteria in § 1045.16 indicates otherwise: (1) Basic science: mathematics, chemistry, theoretical and experimental physics, engineering, materials science, biology and medicine; (2) Magnetic confinement fusion...); (5) Fact of use of safety features (e.g., insensitive high explosives, fire resistant pits) to lower...

Formalization of the classification pattern: survey of classification modeling in information systems engineering.

PubMed

Partridge, Chris; de Cesare, Sergio; Mitchell, Andrew; Odell, James

2018-01-01

Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the "one and the many." Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor's work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus to the ISE literature. The literature survey follows the evolution of ISE's understanding of how to formalize the classification pattern. The various proposals are assessed using the classical example of classification; the Linnaean taxonomy formalized using powersets as a benchmark for formal expressiveness. The broad conclusion of the survey is that (1) the ISE community is currently in the early stages of the process of understanding how to formalize the classification pattern, particularly in the requirements for expressiveness exemplified by powersets, and (2) that there is an opportunity to intervene and speed up the process of adoption by clarifying this expressiveness. Given the central place that the classification pattern has in domain modeling, this intervention has the potential to lead to significant improvements.

Limits of Constructivism: Kant, Piaget and Peirce

NASA Astrophysics Data System (ADS)

Otte, M.

The paradox of mathematical knowledge that mathematics cannot be conceived of as completely separated from empirical experience and yet cannot be explained by empiricist epistemology (for a slightly different and more elaborate formulation cf. Blackwell Companion to Epistemology, 270f), can only be resolved if one accepts that the causal interactions between knower and environment have themselves a generalizing tendency, a sort of continuity, rather than consisting just of singular events. Kant resolves the schism between the continous and the distinct in a constructivist manner. He assumes that all our knowledge-extending cognitions are synthetic. This synthesis does not lie in the matter of experience but springs from the function of cognizant consciousness. Piaget adhered to a Kantianism where the categories are not there at the outset. He conceives of the subject as constructing itself as well as of the emerging subject's structure as the source of the apprehension of the wo rld and believes in a Kantianism which emphasizes man's active being and potential for unlimited self-development. But he has no use for the Kantian idea of space and time as forms of mathematical intuition.Kantian thought is also central to Peirce's philosophy and conception of mathematics. But Peirce emphasizes the role of perception and analysis as its prerequisites. Peirce's and Piaget's origins in Kantianism are exhibited when both try to replace the Aristotelian notion of abstraction and generalization by something more suitable for mathematical epistemology. Peirce proposes that hypostatic abstraction is the chief explanation for the power of mathematical reasoning and explains: This operation is performed when something, that one has thought about any subject, is itself made a subject of thought. Piaget speaks of reflective abstraction in this context, making it the basis of mathematical knowledge; but separating it completely from empirical abstraction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Honorio, J.; Goldstein, R.; Honorio, J.

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statisticalmore » theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.« less

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

IFLA General Conference, 1986. Bibliographic Control Division. Section: Classification and Indexing. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations and Institutions, The Hague (Netherlands).

Papers on classification and indexing presented at the 1986 International Federation of Library Associations (IFLA) conference include: (1) "Profile on Chinese Cataloguing and Subject Cataloguing" (Yan Lizhong, China); (2) "The Trend of Classification in Japan" (Hiroshi Ishiyama, Japan); (3) "Classification in Online…

Automated classification of Acid Rock Drainage potential from Corescan drill core imagery

NASA Astrophysics Data System (ADS)

Cracknell, M. J.; Jackson, L.; Parbhakar-Fox, A.; Savinova, K.

2017-12-01

Classification of the acid forming potential of waste rock is important for managing environmental hazards associated with mining operations. Current methods for the classification of acid rock drainage (ARD) potential usually involve labour intensive and subjective assessment of drill core and/or hand specimens. Manual methods are subject to operator bias, human error and the amount of material that can be assessed within a given time frame is limited. The automated classification of ARD potential documented here is based on the ARD Index developed by Parbhakar-Fox et al. (2011). This ARD Index involves the combination of five indicators: A - sulphide content; B - sulphide alteration; C - sulphide morphology; D - primary neutraliser content; and E - sulphide mineral association. Several components of the ARD Index require accurate identification of sulphide minerals. This is achieved by classifying Corescan Red-Green-Blue true colour images into the presence or absence of sulphide minerals using supervised classification. Subsequently, sulphide classification images are processed and combined with Corescan SWIR-based mineral classifications to obtain information on sulphide content, indices representing sulphide textures (disseminated versus massive and degree of veining), and spatially associated minerals. This information is combined to calculate ARD Index indicator values that feed into the classification of ARD potential. Automated ARD potential classifications of drill core samples associated with a porphyry Cu-Au deposit are compared to manually derived classifications and those obtained by standard static geochemical testing and X-ray diffractometry analyses. Results indicate a high degree of similarity between automated and manual ARD potential classifications. Major differences between approaches are observed in sulphide and neutraliser mineral percentages, likely due to the subjective nature of manual estimates of mineral content. The automated approach presented here for the classification of ARD potential offers rapid, repeatable and accurate outcomes comparable to manually derived classifications. Methods for automated ARD classifications from digital drill core data represent a step-change for geoenvironmental management practices in the mining industry.

AVNM: A Voting based Novel Mathematical Rule for Image Classification.

PubMed

Vidyarthi, Ankit; Mittal, Namita

2016-12-01

In machine learning, the accuracy of the system depends upon classification result. Classification accuracy plays an imperative role in various domains. Non-parametric classifier like K-Nearest Neighbor (KNN) is the most widely used classifier for pattern analysis. Besides its easiness, simplicity and effectiveness characteristics, the main problem associated with KNN classifier is the selection of a number of nearest neighbors i.e. "k" for computation. At present, it is hard to find the optimal value of "k" using any statistical algorithm, which gives perfect accuracy in terms of low misclassification error rate. Motivated by the prescribed problem, a new sample space reduction weighted voting mathematical rule (AVNM) is proposed for classification in machine learning. The proposed AVNM rule is also non-parametric in nature like KNN. AVNM uses the weighted voting mechanism with sample space reduction to learn and examine the predicted class label for unidentified sample. AVNM is free from any initial selection of predefined variable and neighbor selection as found in KNN algorithm. The proposed classifier also reduces the effect of outliers. To verify the performance of the proposed AVNM classifier, experiments are made on 10 standard datasets taken from UCI database and one manually created dataset. The experimental result shows that the proposed AVNM rule outperforms the KNN classifier and its variants. Experimentation results based on confusion matrix accuracy parameter proves higher accuracy value with AVNM rule. The proposed AVNM rule is based on sample space reduction mechanism for identification of an optimal number of nearest neighbor selections. AVNM results in better classification accuracy and minimum error rate as compared with the state-of-art algorithm, KNN, and its variants. The proposed rule automates the selection of nearest neighbor selection and improves classification rate for UCI dataset and manually created dataset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Who Succeeds in Mathematics? Caribbean Perspectives on the Mix of Schools and Mathematics

ERIC Educational Resources Information Center

George, Patricia

2012-01-01

Within the Caribbean, there has been a perception that students are underachieving in mathematics. This assessment has seemingly been based amongst other things upon the proportion of students who are successful in mathematics compared to other subjects in external examinations. This notion was investigated in a case study of secondary schools in…

Loving and Hating Mathematics: Challenging the Myths of Mathematical Life

ERIC Educational Resources Information Center

Hersh, Reuben; John-Steiner, Vera

2010-01-01

Mathematics is often thought of as the coldest expression of pure reason. But few subjects provoke hotter emotions--and inspire more love and hatred--than mathematics. And although math is frequently idealized as floating above the messiness of human life, its story is nothing if not human; often, it is all too human. "Loving and Hating…

Investigation of Problems of Implementing Curriculum in Primary Schools in Somalia. African Studies in Curriculum Development & Evaluation.

ERIC Educational Resources Information Center

Mohamed, Ibrahim Jeylani

The aim of this study was to investigate the implementation of modern mathematics in the primary schools of Somalia. In particular, three concerns were addressed: (1) teachers' confidence and ability in teaching mathematics; (2) students' interest in mathematics; and (3) students' examination performance in mathematics. Subjects were 30 teachers…

How Talented Rural Students Experience School Mathematics. Working Paper No. 29

ERIC Educational Resources Information Center

Howley, Aimee; Gholson, Melissa; Pendarvis, Edwina

2006-01-01

The purpose of this paper is to examine how mathematically talented children in a disadvantaged rural community experience mathematics, both as a discipline and as a school subject. The aim is to find answers to questions such as: "What do these children think mathematics is?" "What value do they attach to the study of…

Engineering Undergraduates' Views of A-Level Mathematics and Further Mathematics as Preparation for Their Degree

ERIC Educational Resources Information Center

Darlington, Ellie; Bowyer, Jessica

2017-01-01

An ongoing reform programme of the post-16 Advanced "A"-level qualifications in England and Wales means that pre-university mathematics content and assessment will change from 2017. Undergraduate engineering is a subject that relies heavily on mathematics, and applicants to engineering degree programmes in the UK are required to have…

Automated Decision Tree Classification of Corneal Shape

PubMed Central

Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

2011-01-01

Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification problems. PMID:16357645

Efficacy and efficiency in formative assessment: an informed reflection on the value of partial marking

NASA Astrophysics Data System (ADS)

Seaton, Katherine A.

2013-10-01

This article presents an informed reflection on the evolution of teacher-to-learner feedback provided on written assignments in first-year university mathematics subjects. The feedback provided addresses not only mathematical accuracy and skills, but also the development of graduate attributes, such as discipline-appropriate written communication. Effective and efficient practices that have been collectively refined and enhanced, for more than a decade, are described and examined. This model for formative assessment in mathematics subjects is critiqued in the light of the scholarly literature on feedback and assessment.

Railroad Classification Yard Technology Manual: Volume II : Yard Computer Systems

DOT National Transportation Integrated Search

1981-08-01

This volume (Volume II) of the Railroad Classification Yard Technology Manual documents the railroad classification yard computer systems methodology. The subjects covered are: functional description of process control and inventory computer systems,...

32 CFR 2001.14 - Classification challenges.

Code of Federal Regulations, 2010 CFR

2010-07-01

... any more specific than to question why information is or is not classified, or is classified at a... a classification challenge to information that has been the subject of a challenge within the past two years, or that is the subject of pending litigation, the agency is not required to process the...

Estimation and Q-Matrix Validation for Diagnostic Classification Models

ERIC Educational Resources Information Center

Feng, Yuling

2013-01-01

Diagnostic classification models (DCMs) are structured latent class models widely discussed in the field of psychometrics. They model subjects' underlying attribute patterns and classify subjects into unobservable groups based on their mastery of attributes required to answer the items correctly. The effective implementation of DCMs depends…

The Future for Mathematics Subject Associations

ERIC Educational Resources Information Center

Pope, Sue

2012-01-01

Subject associations have developed, over the years, to serve the interests of the mathematics education community. We live in changing times, and education is often at the forefront of such change. So, to remain contemporary, relevant, and to have a regard for the future in a world influenced by technology, it is suggested that there is a need…

Why Mechanics Should Be Integral to Secondary School Mathematics

ERIC Educational Resources Information Center

Rowlands, Stuart

2008-01-01

Mechanics has never been the most popular subject in A-level mathematics, the UK's public examination for 16-18-year olds, either with students, teachers or educators. The attempts to popularize mechanics have failed and it is conceivable that the subject will be dropped from the A-level syllabus in the foreseeable future. This article argues the…

Subject-Matter Experts in Urban Schools: Journeys of Enacted Identities in Science and Mathematics Classrooms

ERIC Educational Resources Information Center

Ye, Li; Varelas, Maria; Guajardo, Raphael

2011-01-01

This study explored how two mathematics/science subject-matter experts (Fellows) conceptualized urban classrooms and the students they worked with for a year, how they negotiated academic achievement with cultural and sociopolitical competence, and how their identities as educators were co-constructed and enacted. Using grounded theory, Fellows'…

Cross National Comparisons of Excellence in University Mathematics Instructors

ERIC Educational Resources Information Center

Grant, Frida

2014-01-01

Mathematicians have, historically, not been overly successful in their approach to teaching and much research has looked in to why this is so. Teaching mathematics is based on a solid understanding of the subject; however, instructors also need to be able to efficiently communicate the subject to their students. The purpose of this study was to…

The Diagnosis and Remediation of Mathematical Skills for Prospective Elementary School Teachers. Final Report.

ERIC Educational Resources Information Center

Schwartz, Lita L.; And Others

Investigated was the development of a diagnostic and individualized remedial program for prospective elementary teachers in the area of mathematical skills. Subjects were 120 students in the pre-methods course on number systems during the Winter and Spring 1971 terms at the Ogontz Campus, Pennsylvania State University. All subjects were given a…

The Role of Subject-Matter Content in Teacher Preparation: An International Perspective for Mathematics

ERIC Educational Resources Information Center

Schmidt, William H.; Burroughs, Nathan A.; Cogan, Leland S.; Houang, Richard T.

2017-01-01

International comparative studies in education provide a fresh perspective on K-12 education policy by enabling countries to learn from each other's approaches. The recently conducted Teacher Education and Development Study--Mathematics provides a worldwide lens by which to examine the role of subject-matter in the preparation of US teachers of…

Investigating the Differences between Girls and Boys Regarding the Factors of Frustration, Boredom and Insecurity They Experience during Science Lessons

ERIC Educational Resources Information Center

Wegner, Claas; Strehlke, Friederike; Weber, Phillip

2014-01-01

Science, technology, engineering and mathematics (STEM) are subjects comprising knowledge whose schooling is essential for every country striving after long-term economic success. Despite the already existing shortage of skilled labour within the mathematic-technical-scientific professional field, men still dominate the respective subjects and…

Boundary crossing and brokering between disciplines in pre-service mathematics teacher education

NASA Astrophysics Data System (ADS)

Goos, Merrilyn; Bennison, Anne

2017-12-01

In many countries, pre-service teacher education programs are structured so that mathematics content is taught in the university's mathematics department and mathematics pedagogy in the education department. Such program structures make it difficult to authentically interweave content with pedagogy in ways that acknowledge the roles of both mathematicians and mathematics educators in preparing future teachers. This article reports on a project that deliberately fostered collaboration between mathematicians and mathematics educators in six Australian universities in order to investigate the potential for learning at the boundaries between the two disciplinary communities. Data sources included two rounds of interviews with mathematicians and mathematics educators and annual reports prepared by each participating university over the three years of the project. The study identified interdisciplinary boundary practices that led to integration of content and pedagogy through new courses co-developed and co-taught by mathematicians and mathematics educators, and new approaches to building communities of pre-service teachers. It also developed an evidence-based classification of conditions that enable or hinder sustained collaboration across disciplinary boundaries, together with an empirical grounding for Akkerman and Bakker's conceptualisation of transformation as a mechanism for learning at the boundary between communities. The study additionally highlighted the ambiguous nature of boundaries and implications for brokers who work there to connect disciplinary paradigms.

Refining Landsat classification results using digital terrain data

USGS Publications Warehouse

Miller, Wayne A.; Shasby, Mark

1982-01-01

 Scientists at the U.S. Geological Survey's Earth Resources Observation systems (EROS) Data Center have recently completed two land-cover mapping projects in which digital terrain data were used to refine Landsat classification results. Digital ter rain data were incorporated into the Landsat classification process using two different procedures that required developing decision criteria either subjectively or quantitatively. The subjective procedure was used in a vegetation mapping project in Arizona, and the quantitative procedure was used in a forest-fuels mapping project in Montana. By incorporating digital terrain data into the Landsat classification process, more spatially accurate landcover maps were produced for both projects.

Interactive Tax Reform: Simulating Impacts of Legislative Proposals.

ERIC Educational Resources Information Center

Downing, Roger H.; And Others

1985-01-01

Pennsylvania's mathematical modeling technique to evaluate tax reform proposals requires the following data: personal income at the local level and measures of the breakdown of property tax payment by land use classification. The simulation technique could be readily adapted in reorganizing educational finance systems. (MLF)

Forestry 101.

ERIC Educational Resources Information Center

Markham, Mary T.

2000-01-01

Introduces a unit on forest management in which students manage the school forest. Involves students in tree identification, determining the size or volume and height of trees, and evaluation of the forest for management decisions. Integrates mathematics, writing, and social studies with plant classification, plant reproduction, and the use of…

Validation of a systems-actuarial computer process for multidimensional classification of child psychopathology.

PubMed

McDermott, P A; Hale, R L

1982-07-01

Tested diagnostic classifications of child psychopathology produced by a computerized technique known as multidimensional actuarial classification (MAC) against the criterion of expert psychological opinion. The MAC program applies series of statistical decision rules to assess the importance of and relationships among several dimensions of classification, i.e., intellectual functioning, academic achievement, adaptive behavior, and social and behavioral adjustment, to perform differential diagnosis of children's mental retardation, specific learning disabilities, behavioral and emotional disturbance, possible communication or perceptual-motor impairment, and academic under- and overachievement in reading and mathematics. Classifications rendered by MAC are compared to those offered by two expert child psychologists for cases of 73 children referred for psychological services. Experts' agreement with MAC was significant for all classification areas, as was MAC's agreement with the experts held as a conjoint reference standard. Whereas the experts' agreement with MAC averaged 86.0% above chance, their agreement with one another averaged 76.5% above chance. Implications of the findings are explored and potential advantages of the systems-actuarial approach are discussed.

Two notions of conspicuity and the classification of phyllotaxis.

PubMed

Reick, Christian H

2002-04-07

Invoking cylindrical Bravais lattices, Adler (1974, 1977) proposed a mathematically precise definition for the botanical classification of phyllotaxis. It is based on opposed pairs of parastichy families, that are conspicuous and visible. Jean (1988) generalized this concept to non-opposed pairs of parastichy families. In the present paper it is shown that this generalization implies a notion of conspicuity different from Adler's. This is made obvious by redefining the key terms of the two approaches. Both classifications are well defined. For Adler's, this is shown by presenting a general proof for his conjecture that conspicuous (in the sense of Adler) opposed pairs of parastichy families are visible. There are indications that in applications to models of phyllotaxis (van Iterson model, inhibitor models) their solutions are better characterized by Jean's classification. The differences between Adler's and Jean's classification show up only in very rare cases, so that the practice of pattern determination is only insignificantly touched by the present results. It turns out that the widely used contact parastichy method to determine phyllotactic patterns gives results according to Jean's classification rather than Adler's. Copyright 2002 Elsevier Science Ltd. All rights reserved.

Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.

NASA Astrophysics Data System (ADS)

Campo, D.; Quintero, O. L.; Bastidas, M.

2016-04-01

We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.

Gesture analysis of students' majoring mathematics education in micro teaching process

NASA Astrophysics Data System (ADS)

Maldini, Agnesya; Usodo, Budi; Subanti, Sri

2017-08-01

In the process of learning, especially math learning, process of interaction between teachers and students is certainly a noteworthy thing. In these interactions appear gestures or other body spontaneously. Gesture is an important source of information, because it supports oral communication and reduce the ambiguity of understanding the concept/meaning of the material and improve posture. This research which is particularly suitable for an exploratory research design to provide an initial illustration of the phenomenon. The goal of the research in this article is to describe the gesture of S1 and S2 students of mathematics education at the micro teaching process. To analyze gesture subjects, researchers used McNeil clarification. The result is two subjects using 238 gesture in the process of micro teaching as a means of conveying ideas and concepts in mathematics learning. During the process of micro teaching, subjects using the four types of gesture that is iconic gestures, deictic gesture, regulator gesturesand adapter gesture as a means to facilitate the delivery of the intent of the material being taught and communication to the listener. Variance gesture that appear on the subject due to the subject using a different gesture patterns to communicate mathematical ideas of their own so that the intensity of gesture that appeared too different.

Comparison of subjective and fully automated methods for measuring mammographic density.

PubMed

Moshina, Nataliia; Roman, Marta; Sebuødegård, Sofie; Waade, Gunvor G; Ursin, Giske; Hofvind, Solveig

2018-02-01

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (k w ). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend < 0.001 for both subjective classifications). The agreement between BI-RADS and volumetric breast density categories was k w  = 0.5 (95% CI = 0.47-0.53; P < 0.001). Conclusion Mean values of volumetric breast density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.

Physical exertion and immediate mental performance of sixth-grade children.

PubMed

McNaughten, D; Gabbard, C

1993-12-01

The intent of this investigation was to examine the potential influence of varying durations of physical exertion at different times of the day on immediate mathematical performance by 120 sixth-grade boys and girls. Subjects were assigned to two control and two treatment groups (Solomon Four-group Design), with treated subjects administered physical exertion (paced walking at controlled moderate intensity) for durations of 20, 30, and 40 min. at three different times of the school day [8:30 a.m., 11:50 a.m. (before lunch), 2:20 p.m.] over 3 weeks. After each exertion session, subjects were immediately administered a 90-sec. mathematical computation test. Analysis indicated no significant differences in mathematical performance at any duration in the morning, but scores were significantly higher at 11:50 a.m. and 2:20 p.m. at 30- and 40-min. durations in comparison to the 20-min. duration. There were no differences by gender of subject.

Bernhard Riemann, a(rche)typical mathematical-physicist?

NASA Astrophysics Data System (ADS)

Elizalde, Emilio

2013-09-01

The work of Bernhard Riemann is discussed under the perspective of present day mathematics and physics, and with a prospective view towards the future, too. Against the (unfortunately rather widespread) trend---which predominantly dominated national scientific societies in Europe during the last Century---of strictly classifying the work of scientists with the aim to constrain them to separated domains of knowledge, without any possible interaction among those and often even fighting against each other (and which, no doubt, was in part responsible for the decline of European in favor of American science), it will be here argued, using Riemann as a model, archetypical example, that good research transcends any classification. Its uses and applications arguably permeate all domains, subjects and disciplines one can possibly define, to the point that it can be considered to be universally useful. After providing a very concise review of the main publications of Bernhard Riemann on physical problems, some connections between Riemann's papers and contemporary physics will be considered: (i) the uses of Riemann's work on the zeta function for devising applications to the regularization of quantum field theories in curved space-time, in particular, of quantum vacuum fluctuations; (ii) the uses of the Riemann tensor in general relativity and in recent generalizations of this theory, which aim at understanding the presently observed acceleration of the universe expansion (the dark energy issue). Finally, it will be argued that mathematical physics, which was yet not long ago a model paradigm for interdisciplinary activity---and had a very important pioneering role in this sense---is now quickly being surpassed by the extraordinarily fruitful interconnections which seem to pop up from nothing every day and simultaneously involve several disciplines, in the classical sense, including genetics, combinatorics, nanoelectronics, biochemistry, medicine, and even ps

Comparing Features for Classification of MEG Responses to Motor Imagery.

PubMed

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio-spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system.

Mathematics Efficacy and Professional Development Needs of Wyoming Agricultural Education Teachers

ERIC Educational Resources Information Center

Haynes, J. Chris; Stripling, Christopher T.

2014-01-01

School-based agricultural education programs provide contextualized learning environments for the teaching of core academic subject matter. This study sought to examine the mathematics efficacy and professional development needs of Wyoming agricultural education teachers related to teaching contextualized mathematics. Wyoming agricultural…

Prognostic modelling options for remaining useful life estimation by industry

NASA Astrophysics Data System (ADS)

Sikorska, J. Z.; Hodkiewicz, M.; Ma, L.

2011-07-01

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

Cross-Lagged Cross-Subject Bidirectional Predictions among Achievements in Mathematics, English Language and Chinese Language of School Children

ERIC Educational Resources Information Center

Mok, Magdalena Mo Ching; Zhu, Jinxin; Law, Cecilia Lai Kwan

2017-01-01

This study aimed to explore the cross-lagged association of achievements in mathematics and languages. While the effect of language on achievements in mathematics is well-documented, few studies have examined the reciprocal relationships among mathematics, the Chinese language and the English language in the same study. This study conducted a…

The Changing Profile of Entrants to Mathematics at A Level and to Mathematical Subjects in Higher Education.

ERIC Educational Resources Information Center

Kitchen, Ann

1999-01-01

Analyzes the characteristics of the British student population in mathematics at both the interface between the General Certificate of Secondary Education (GCSE) and A level and between A level and high education. Focuses on the changes in GCSE and A level mathematics, entry standards in higher education, and gender balance issues. (CMK)

What Would the Mathematics Curriculum Look Like if Values Were the Focus?

ERIC Educational Resources Information Center

Seah, Wee Tiong; Andersson, Annica; Bishop, Alan; Clarkson, Philip

2016-01-01

The crucial reason for the common dislike, fear, and even hatred of mathematics by students and others is probably not the nature of mathematics itself, but the way the subject is portrayed and taught. We propose that instead of a mathematics curriculum that focuses on concepts and techniques (which is often seen), it might be more productive if…

The Evolvement of Numeracy and Mathematical Literacy Curricula and the Construction of Hierarchies of Numerate or Mathematically Literate Subjects

ERIC Educational Resources Information Center

Jablonka, Eva

2015-01-01

This contribution briefly sketches the evolvement of numeracy or mathematical literacy as models for mathematics curricula, which will be described as driven by a weakening of the insulation between discourses, that is, as a process of "declassification". The question then arises as to whether and how coherence of new forms of initially…

Expanding your horizons in science and mathematics

NASA Technical Reports Server (NTRS)

Palmer, Cynthia E. A.

1995-01-01

The purpose of the 'Expanding Your Horizons in Science and Mathematics' program is to interest young women in grades six through twelve in a variety of careers where mathematics and science are important. Progress in encouraging young women to take courses in mathematics, science, and technological subjects is discussed. Also included are adult, student, and organizational information packets used for 'Expanding Your Horizons' conferences.

The Nuances and Complexities of Teaching Mathematics for Cultural Relevance and Social Justice

ERIC Educational Resources Information Center

Leonard, Jacqueline; Brooks, Wanda; Barnes-Johnson, Joy; Berry, Robert Q., III.

2010-01-01

Mathematics is not a race-neutral subject. Access and opportunity in mathematics for students of color in the United States continue to be limited. While a great deal of attention has been given to increasing the number of underrepresented minority students in the mathematics pipeline, there is little consideration of who they are as learners or…

Students' Intentions to Study Non-Compulsory Mathematics: The Importance of How Good You Think You Are

ERIC Educational Resources Information Center

Sheldrake, Richard; Mujtaba, Tamjid; Reiss, Michael J.

2015-01-01

Increasing the number of students who study mathematics once it is no longer compulsory remains a priority for England. A longitudinal cohort from England (1085 students) was surveyed at Years 10 and 12. Students' self-beliefs of ability influenced their GCSE mathematics grades and their intended and actual mathematics subject-choices; the degree…

CFD Analysis of the SBXC Glider Airframe

DTIC Science & Technology

2016-06-01

mathematically on finite element methods. To validate and verify the methodology developed, a mathematical comparison was made with the previous research data...greater than 15 m/s. 14. SUBJECT TERMS finite element method, computational fluid dynamics, Y Plus, mesh element quality, aerodynamic data, fluid...based mathematically on finite element methods. To validate and verify the methodology developed, a mathematical comparison was made with the

The Application of Contextual Approach in Learning Mathematics to Improve Students Motivation at SMPN 1 Kupang

ERIC Educational Resources Information Center

Ekowati, Ch. Krisnandari; Darwis, Muhammad; Upa, H. M. D. Pua; Tahmir, Suradi

2015-01-01

This research is an action research which aims to implement contextual teaching and learning (CTL) approach to learn mathematics, focus on the integration subjects. The approach utilizes the use of mathematics manipulative so that students can understand a mathematical concept to construct their own. The method which used in this research are…

ADHD classification using bag of words approach on network features

NASA Astrophysics Data System (ADS)

Solmaz, Berkan; Dey, Soumyabrata; Rao, A. Ravishankar; Shah, Mubarak

2012-02-01

Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.

Single-gender mathematics and science classes and the effects on urban middle school boys and girls

NASA Astrophysics Data System (ADS)

Sudler, Dawn M.

This study compared the differences in the Criterion-Referenced Competency Test (CRCT) mathematics and science achievement scores of boys and girls in Grade 7 at two urban middle schools. The data allowed the researcher to determine to what degree boys and girls in Grade 7 differ in their mathematics and science achievements within a single-gender environment versus a coeducational learning environment. The study compared any differences between boys and girls in Grade 7 within a single-gender environment in the subjects of mathematics and science, as measured by the CRCT assessments. The study also compared differences between boys and girls in Grade 7 within a coeducational environment in the subjects of mathematics and science, as measured by the CRCT assessments. Two middle schools were used within the study. One middle school was identified as a single-gender school (Middle School A); the other was identified as a coeducational school (Middle School B). This quantitative study applied the use of a descriptive research design. In addition, CRCT scores for the subjects of mathematics and science were taken during the spring of 2008 from both middle schools. Data were measured using descriptive statistics and independent t test calculations. The frequency statistics proceeded to compare each sample performance levels. The data were described in means, standard deviations, standard error means, frequency, and percentages. This method provided an excellent description of a sample scored on the spring 2008 CRCT mathematics and science assessments.

"They're gonna explain to us what makes a cube a cube?" Geometrical properties as contingent achievement of sequentially ordered child-centered mathematics lessons

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael; Gardener, Rod

2012-09-01

In mathematics education, there is a continuing debate about the nature of mathematics, which some claim to be an objective science, whereas others note its socially and individually constructed nature. From a strict cultural-historical perspective, the objective and subjective sides of mathematics are but manifestations of a higher-order phenomenon that may be summarized by the aphorism that mind is in society to the extent that society is in the mind. In this study, we show, drawing on exemplifying materials from a second-grade unit on three-dimensional geometry, how mathematics manifests itself both as objective science all the while being subjectively produced. A particular three-turn interactional sequence comes to play a central role. We conclude by re-assigning a positive role to a much-maligned sequentially ordered conversational routine.

40 CFR 51.904 - How do the classification and attainment date provisions in section 172(a) of subpart 1 of the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b)? (a) Classification. The Administrator may classify an area subject to § 51.902(b) as an overwhelming...

40 CFR 51.904 - How do the classification and attainment date provisions in section 172(a) of subpart 1 of the...

Code of Federal Regulations, 2014 CFR

2014-07-01

... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b)? (a) Classification. The Administrator may classify an area subject to § 51.902(b) as an overwhelming...

40 CFR 51.904 - How do the classification and attainment date provisions in section 172(a) of subpart 1 of the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b)? (a) Classification. The Administrator may classify an area subject to § 51.902(b) as an overwhelming...

40 CFR 51.904 - How do the classification and attainment date provisions in section 172(a) of subpart 1 of the...

Code of Federal Regulations, 2013 CFR

2013-07-01

... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b)? (a) Classification. The Administrator may classify an area subject to § 51.902(b) as an overwhelming...

40 CFR 51.904 - How do the classification and attainment date provisions in section 172(a) of subpart 1 of the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b... attainment date provisions in section 172(a) of subpart 1 of the CAA apply to areas subject to § 51.902(b)? (a) Classification. The Administrator may classify an area subject to § 51.902(b) as an overwhelming...

Mathematical Caring Relations: A Challenging Case

ERIC Educational Resources Information Center

Hackenberg, Amy

2010-01-01

Developed from Noddings's (2002) care theory, von Glasersfeld's (1995) constructivism, and Ryan and Frederick's (1997) notion of subjective vitality, a mathematical caring relation (MCR) is a quality of interaction between a student and a mathematics teacher that conjoins affective and cognitive realms in the process of aiming for mathematical…

A Mathematical Mystery Tour: Higher-Thinking Math Tasks.

ERIC Educational Resources Information Center

Wahl, Mark

This book contains mathematics activities based upon the concepts of Fibonacci numbers and the Golden Ratio. The activities include higher order thinking skills, calculation practice, integration with different subject areas, mathematics history, extensions and home tasks, teaching notes, and questions for thought and comprehension. A visual map…

The Preschool Rating Instrument for Science and Mathematics (PRISM)

ERIC Educational Resources Information Center

Brenneman, Kimberly; Stevenson-Garcia, Judi; Jung, Kwanghee; Frede, Ellen

2011-01-01

Until recently, few valid and reliable assessments were available to measure young children's mathematics and science learning in a "comprehensive" way. Now, a number of mathematics assessments have been developed and subjected to testing (Klein, Starkey, & Wakeley, 2000; Ginsburg, 2008; Clements & Sarama, 2008), and progress has…

Structuring students’ analogical reasoning in solving algebra problem

NASA Astrophysics Data System (ADS)

Lailiyah, S.; Nusantara, T.; Sa'dijah, C.; Irawan, E. B.; Kusaeri; Asyhar, A. H.

2018-01-01

The average achievement of Indonesian students’ mathematics skills according to Benchmark International Trends in Mathematics and Science Study (TIMSS) is ranked at the 38th out of 42 countries and according to the survey result in Program for International Student Assessment (PISA) is ranked at the 64th out of 65 countries. The low mathematics skill of Indonesian student has become an important reason to research more deeply about reasoning and algebra in mathematics. Analogical reasoning is a very important component in mathematics because it is the key to creativity and it can make the learning process in the classroom become effective. The major part of the analogical reasoning is about structuring including the processes of inferencing and decision-making happens. Those processes involve base domain and target domain. Methodologically, the subjects of this research were 42 students from class XII. The sources of data were derived from the results of thinks aloud, the transcribed interviews, and the videos taken while the subject working on the instruments and interviews. The collected data were analyzed using qualitative techniques. The result of this study described the structuring characteristics of students’ analogical reasoning in solving algebra problems from all the research subjects.

Changes in How Prospective Teachers Anticipate Secondary Students' Answers

ERIC Educational Resources Information Center

Llinares, Salvador; Fernández, Ceneida; Sánchez-Matamoros, Gloria

2016-01-01

This study focuses on how prospective teachers learn about students' mathematical thinking when (1) anticipating secondary students' answers reflecting different characteristics of understanding, and (2) propose new activities in relation to the classification of quadrilaterals. The data were collected from forty-eight prospective secondary school…

Epidemic classification of phytosanitary situations on cereal crops using mathematical modeling

USDA-ARS?s Scientific Manuscript database

Most plant protection researchers and experts divide emerging phytosanitary situations into three classes: epidemic, moderate development of disease, and yield depression. The known principles and methods for estimating these situations (Van der Plank J.E., Kranz J. et al.) do not fully describe th...

Reliability of McConnell's classification of patellar orientation in symptomatic and asymptomatic subjects.

PubMed

Watson, C J; Propps, M; Galt, W; Redding, A; Dobbs, D

1999-07-01

Test-retest reliability study with blinded testers. To determine the intratester reliability of the McConnell classification system and to determine whether the intertester reliability of this system would be improved by one-on-one training of the testers, increasing the variability and numbers of subjects, blinding the testers to the absence or presence of patellofemoral pain syndrome, and adhering to the McConnell classification system as it is taught in the "McConnell Patellofemoral Treatment Plan" continuing education course. The McConnell classification system is currently used by physical therapy clinicians to quantify static patellar orientation. The measurements generated from this system purportedly guide the therapist in the application of patellofemoral tape and in assessment of the efficacy of treatment interventions on changing patellar orientation. Fifty-six subjects (age range, 21-65 years) provided a total of 101 knees for assessment. Seventy-six knees did not produce symptoms. A researcher who did not participate in the measuring process determined that 17 subjects had patellofemoral pain syndrome in 25 knees. Two testers concurrently measured static patellar orientation (anterior/posterior and medial/lateral tilt, medial/lateral glide, and patellar rotation) on subjects, using the McConnell classification system. Repeat measures were performed 3-7 days later. A kappa (kappa) statistic was used to assess the degree of agreement within each tester and between testers. The kappa coefficients for intratester reliability varied from -0.06 to 0.35. Intertester reliability ranged from -0.03 to 0.19. The McConnell classification system, in its current form, does not appear to be very reliable. Intratester reliability ranged from poor to fair, and intertester reliability was poor to slight. This system should not be used as a measurement tool or as a basis for treatment decisions.

Perceptual-motor skill learning in Gilles de la Tourette syndrome. Evidence for multiple procedural learning and memory systems.

PubMed

Marsh, Rachel; Alexander, Gerianne M; Packard, Mark G; Zhu, Hongtu; Peterson, Bradley S

2005-01-01

Procedural learning and memory systems likely comprise several skills that are differentially affected by various illnesses of the central nervous system, suggesting their relative functional independence and reliance on differing neural circuits. Gilles de la Tourette syndrome (GTS) is a movement disorder that involves disturbances in the structure and function of the striatum and related circuitry. Recent studies suggest that patients with GTS are impaired in performance of a probabilistic classification task that putatively involves the acquisition of stimulus-response (S-R)-based habits. Assessing the learning of perceptual-motor skills and probabilistic classification in the same samples of GTS and healthy control subjects may help to determine whether these various forms of procedural (habit) learning rely on the same or differing neuroanatomical substrates and whether those substrates are differentially affected in persons with GTS. Therefore, we assessed perceptual-motor skill learning using the pursuit-rotor and mirror tracing tasks in 50 patients with GTS and 55 control subjects who had previously been compared at learning a task of probabilistic classifications. The GTS subjects did not differ from the control subjects in performance of either the pursuit rotor or mirror-tracing tasks, although they were significantly impaired in the acquisition of a probabilistic classification task. In addition, learning on the perceptual-motor tasks was not correlated with habit learning on the classification task in either the GTS or healthy control subjects. These findings suggest that the differing forms of procedural learning are dissociable both functionally and neuroanatomically. The specific deficits in the probabilistic classification form of habit learning in persons with GTS are likely to be a consequence of disturbances in specific corticostriatal circuits, but not the same circuits that subserve the perceptual-motor form of habit learning.

14 CFR 1203.405 - Proprietary information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... PROGRAM Guides for Original Classification § 1203.405 Proprietary information. Proprietary information made available to NASA is subject to examination for classification purposes under the criteria set... the proposal but believes that security classification would be appropriate under the criteria of...

Do Biology Students Really Hate Math? Empirical Insights into Undergraduate Life Science Majors' Emotions about Mathematics

ERIC Educational Resources Information Center

Wachsmuth, Lucas P.; Runyon, Christopher R.; Drake, John M.; Dolan, Erin L.

2017-01-01

Undergraduate life science majors are reputed to have negative emotions toward mathematics, yet little empirical evidence supports this. We sought to compare emotions of majors in the life sciences versus other natural sciences and math. We adapted the Attitudes toward the Subject of Chemistry Inventory to create an Attitudes toward the Subject of…

Dealing with Maths Anxiety: How "Do" You Teach Mathematics in a Geography Department?

ERIC Educational Resources Information Center

Chapman, Lee

2010-01-01

Mathematics is often taught covertly as a "service" subject in geography departments, but can often be a cause of fear for students who may not have studied the subject post-GCSE. Negative attitudes are common and many students show signs of maths anxiety. This paper details how students' attitudes were changed by a new foundation mathematics…

Tracing the Impact: A Case of a Professional Development Programme in Mathematical Literacy

ERIC Educational Resources Information Center

Bansilal, S.; Goba, B.; Webb, L.; James, A.; Khuzwayo, H.

2012-01-01

The introduction of the subject Mathematical Literacy (ML) as part of the education reform process, led to the development of many large scale in-service programmes designed to train practising teachers to teach the new subject. The purpose of the study is to examine the challenges associated with providing in-service training for teachers of ML,…

Emotion recognition based on physiological changes in music listening.

PubMed

Kim, Jonghwa; André, Elisabeth

2008-12-01

Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper investigates the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an automatic recognition system are discussed, from the recording of a physiological dataset to a feature-based multiclass classification. In order to collect a physiological dataset from multiple subjects over many weeks, we used a musical induction method which spontaneously leads subjects to real emotional states, without any deliberate lab setting. Four-channel biosensors were used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to find the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by classification results. Classification of four musical emotions (positive/high arousal, negative/high arousal, negative/low arousal, positive/low arousal) is performed by using an extended linear discriminant analysis (pLDA). Furthermore, by exploiting a dichotomic property of the 2D emotion model, we develop a novel scheme of emotion-specific multilevel dichotomous classification (EMDC) and compare its performance with direct multiclass classification using the pLDA. Improved recognition accuracy of 95\\% and 70\\% for subject-dependent and subject-independent classification, respectively, is achieved by using the EMDC scheme.

Long-publishing astronomers, or the problem of classification

NASA Astrophysics Data System (ADS)

Tenn, Joseph S.

2012-03-01

In response to several discussions among astronomers and historians of astronomy, I started out to prepare a paper on long-publishing astronomers-those who published for 70, 75, or even 80 years. However, I soon ran into a number of questions of classification, and that turned out to be at least as interesting. How do we decide on classifications? Every time we choose classes, such as asteroids, planets and stars, we run into objects that seem to be in between. In the present case a number of questions arise: Who is an astronomer? Several of those with the longest publication runs started out as physicists, published for years in that subject only, and later took up astrophysics, eventually publishing a few papers in astronomy journals. What is a publication? Should we count publications in physics, chemistry, or mathematics? What about philosophy of science or history of science? What about the elderly retired astronomer presenting a memoir of his or her own work? Abstracts of oral presentations? Monographs? Textbooks? Book reviews? Obituaries? Then there is the problem of posthumous publications. Probably most would include papers in the pipeline when the astronomer dies, but what about the case where the coauthor finally publishes the paper as much as twenty-two years after the death of the person of interest? I eventually decided to make two lists, one which would include most of the above, and one restricted to papers that make contributions to physical science. Note that I do not say 'refereed', as that presents its own problems, especially when applied to periods before the twentieth century. I present a list of astronomers who have published for periods of 68 to 80 years and discuss the problems of defining such terms as astronomer and publication.

Automatic detection and classification of artifacts in single-channel EEG.

PubMed

Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W; Sorensen, Helge B D

2014-01-01

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated. The detection algorithm yield an average sensitivity and specificity above 95% for both the subject-specific and generic models. The classification algorithm show a mean accuracy of 78 and 64% for the subject-specific and generic model, respectively. The classification model was additionally validated on a reference dataset with similar results.

Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase

NASA Astrophysics Data System (ADS)

Zink, Rob; Hunyadi, Borbála; Van Huffel, Sabine; De Vos, Maarten

2016-04-01

Objective. One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a supervised calibration phase, new users could potentially explore a BCI faster. In this work we aim to remove this subject-specific calibration phase and allow direct classification. Approach. We explore canonical polyadic decompositions and block term decompositions of the EEG. These methods exploit structure in higher dimensional data arrays called tensors. The BCI tensors are constructed by concatenating ERP templates from other subjects to a target and non-target trial and the inherent structure guides a decomposition that allows accurate classification. We illustrate the new method on data from a three-class auditory oddball paradigm. Main results. The presented approach leads to a fast and intuitive classification with accuracies competitive with a supervised and cross-validated LDA approach. Significance. The described methods are a promising new way of classifying BCI data with a forthright link to the original P300 ERP signal over the conventional and widely used supervised approaches.

Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase.

PubMed

Zink, Rob; Hunyadi, Borbála; Huffel, Sabine Van; Vos, Maarten De

2016-04-01

One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a supervised calibration phase, new users could potentially explore a BCI faster. In this work we aim to remove this subject-specific calibration phase and allow direct classification. We explore canonical polyadic decompositions and block term decompositions of the EEG. These methods exploit structure in higher dimensional data arrays called tensors. The BCI tensors are constructed by concatenating ERP templates from other subjects to a target and non-target trial and the inherent structure guides a decomposition that allows accurate classification. We illustrate the new method on data from a three-class auditory oddball paradigm. The presented approach leads to a fast and intuitive classification with accuracies competitive with a supervised and cross-validated LDA approach. The described methods are a promising new way of classifying BCI data with a forthright link to the original P300 ERP signal over the conventional and widely used supervised approaches.

Single-trial classification of auditory event-related potentials elicited by stimuli from different spatial directions.

PubMed

Cabrera, Alvaro Fuentes; Hoffmann, Pablo Faundez

2010-01-01

This study is focused on the single-trial classification of auditory event-related potentials elicited by sound stimuli from different spatial directions. Five naϊve subjects were asked to localize a sound stimulus reproduced over one of 8 loudspeakers placed in a circular array, equally spaced by 45°. The subject was seating in the center of the circular array. Due to the complexity of an eight classes classification, our approach consisted on feeding our classifier with two classes, or spatial directions, at the time. The seven chosen pairs were 0°, which was the loudspeaker directly in front of the subject, with all the other seven directions. The discrete wavelet transform was used to extract features in the time-frequency domain and a support vector machine performed the classification procedure. The average accuracy over all subjects and all pair of spatial directions was 76.5%, σ = 3.6. The results of this study provide evidence that the direction of a sound is encoded in single-trial auditory event-related potentials.

U.S. Geological Survey Library classification system

USGS Publications Warehouse

Sasscer, R. Scott

1992-01-01

The U.S. Geological Survey library classification system has been designed for an earth science library. It is a tool for assigning classification numbers to earth science and allied pure science library materials in order to collect these materials into related subject groups on the library shelves and arrange them alphabetically by author and title. It can also be used as a retrieval system to access these materials through the subject and visible geographic classification numbers.The classification scheme has been developed over the years since 1904 to meet the ever-changing needs of increased specialization and new areas of study in the earth sciences.This system contains seven schedules:Subject scheduleGeological survey scheduleEarth science periodical scheduleGovernment documents periodical scheduleGeneral science periodical scheduleEarth science maps scheduleGeographic scheduleA geographic number, from the geographic schedule, is distinguished from other numbers in the system in that it is always enclosed in parentheses; for example, (200) is the geographic number for the United States.The geographic number is used in conjunction with the six other previously listed schedules, and it represents slightly different nuances of meanings, in respect to geographic locale, for each schedule.When used with a subject number, the geographic number indicates the country, state, province, or region in which the research was made. The subject number, 203, geology, when combined with the geographic number, (200), for example 203(200), is the classification number for library materials on the geology of the United States.The geographic number, combined with the capital letter G, for example, G(211), is the classification number for an earth science periodical issued by a geological association or university geology department in the State of Maine.When the letter S is combined with a geographic number, for example, S(276), it represents a general science periodical for a university or association in California.When the letter P is combined with a geographic number, for example, P(200), it represents a governmental periodical issued by the United States Federal Government.Geographic numbers standing alone represent classification numbers for the publications of geological surveys; for example, (200) represents publications of the U.S. Geological Survey.Map call numbers have a geographic number preceded by the capital letter M, followed by an abbreviated subject number.For example:M(200)2where:M = Map(200) = Geographic region of the United States2 = Abbreviation for the subject number 203— geology.The introduction, which follows this abstract, provides detailed procedures on the construction of complete call numbers for works falling into the framework of the aforesaid classification schedules.The tables following the introduction can be quickly accessed through the use of the newly expanded subject index.The purpose of this publication is to provide the earth science community with a classification and retrieval system for earth science materials, to provide sufficient explanation of its structure and use, and to enable library staff and clientele to classify or access research materials in a library collection.

The Role of Cooperative Learning Type Team Assisted Individualization to Improve the Students' Mathematics Communication Ability in the Subject of Probability Theory

ERIC Educational Resources Information Center

Tinungki, Georgina Maria

2015-01-01

The importance of learning mathematics can not be separated from its role in all aspects of life. Communicating ideas by using mathematics language is even more practical, systematic, and efficient. In order to overcome the difficulties of students who have insufficient understanding of mathematics material, good communications should be built in…

"They [The Lecturers] Have to Get through a Certain Amount in an Hour": First Year Students' Problems with Service Mathematics Lectures

ERIC Educational Resources Information Center

Harris, Diane; Pampaka, Maria

2016-01-01

Drawing on large-scale survey data and interviews with students during their first year at university, and case studies in their institutions, we explore the problems faced by students taking mathematically demanding courses, e.g. physics and engineering. These students are often taught mathematics as a service subject by lecturers of mathematics.…

Open-Ended Approach: An Effort in Cultivating Students' Mathematical Creative Thinking Ability and Self-Esteem in Mathematics

ERIC Educational Resources Information Center

Fatah, Abdul; Suryadi, Didi; Sabandar, Jozua; Turmudi

2016-01-01

The present study aims at examining the use of open-ended approach in cultivating senior high school students' mathematical creative thinking ability (MCTA) and self-esteem (SE) in mathematics viewed from school category. The subjects of this research were the students grade XI at three schools; high, middle and low category in Kota Serang, Banten…

Students' Critical Mathematical Thinking Skills and Character: Experiments for Junior High School Students through Realistic Mathematics Education Culture-Based

ERIC Educational Resources Information Center

Palinussa, Anderson L.

2013-01-01

This paper presents the findings of a quasi-experimental with pre-test-post-test design and control group that aims to assess students' critical mathematical thinking skills and character through realistic mathematics education (RME) culture-based. Subjects of this study were 106 junior high school students from two low and medium schools level in…

Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.

PubMed

Cho, Youngsang; Seong, Joon-Kyung; Jeong, Yong; Shin, Sung Yong

2012-02-01

Patterns of brain atrophy measured by magnetic resonance structural imaging have been utilized as significant biomarkers for diagnosis of Alzheimer's disease (AD). However, brain atrophy is variable across patients and is non-specific for AD in general. Thus, automatic methods for AD classification require a large number of structural data due to complex and variable patterns of brain atrophy. In this paper, we propose an incremental method for AD classification using cortical thickness data. We represent the cortical thickness data of a subject in terms of their spatial frequency components, employing the manifold harmonic transform. The basis functions for this transform are obtained from the eigenfunctions of the Laplace-Beltrami operator, which are dependent only on the geometry of a cortical surface but not on the cortical thickness defined on it. This facilitates individual subject classification based on incremental learning. In general, methods based on region-wise features poorly reflect the detailed spatial variation of cortical thickness, and those based on vertex-wise features are sensitive to noise. Adopting a vertex-wise cortical thickness representation, our method can still achieve robustness to noise by filtering out high frequency components of the cortical thickness data while reflecting their spatial variation. This compromise leads to high accuracy in AD classification. We utilized MR volumes provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) to validate the performance of the method. Our method discriminated AD patients from Healthy Control (HC) subjects with 82% sensitivity and 93% specificity. It also discriminated Mild Cognitive Impairment (MCI) patients, who converted to AD within 18 months, from non-converted MCI subjects with 63% sensitivity and 76% specificity. Moreover, it showed that the entorhinal cortex was the most discriminative region for classification, which is consistent with previous pathological findings. In comparison with other classification methods, our method demonstrated high classification performance in both categories, which supports the discriminative power of our method in both AD diagnosis and AD prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Socio-Emotional Orientations and Teacher Change

ERIC Educational Resources Information Center

Kaasila, Raimo; Hannula, Markku S.; Laine, Anu; Pehkonen, Erkki

2008-01-01

In this article we consider how elementary education students' views of mathematics changed during their mathematics methods course. We focus on four female students: two started the course with mainly positive views of mathematics and a task orientation, two with negative views of the subject and an ego-defensive orientation. The biggest change…

Swedish Upper Secondary Students' Perspectives on the Typical Mathematics Lesson

ERIC Educational Resources Information Center

Andrews, Paul; Larson, Niclas

2017-01-01

This paper presents a group interview study of Swedish upper secondary students' perspectives on the typical mathematics lesson. Students, from four demographically different schools, constructed a collective synthesis of their many years' experience of mathematics classrooms. Transcriptions were subjected to a constant comparison analysis, which…

Keystone Method: A Learning Paradigm in Mathematics

ERIC Educational Resources Information Center

Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram

2008-01-01

This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…

Improving Intuition Skills with Realistic Mathematics Education

ERIC Educational Resources Information Center

Hirza, Bonita; Kusumah, Yaya S.; Darhim; Zulkardi

2014-01-01

The intention of the present study was to see the improvement of students' intuitive skills. This improvement was seen by comparing the Realistic Mathematics Education (RME)-based instruction with the conventional mathematics instruction. The subject of this study was 164 fifth graders of elementary school in Palembang. The design of this study…

Making Connections

ERIC Educational Resources Information Center

Turner, Paul

2015-01-01

This article aims to illustrate a process of making connections, not between mathematics and other activities, but within mathematics itself--between diverse parts of the subject. Novel connections are still possible in previously explored mathematics when the material happens to be unfamiliar, as may be the case for a learner at any career stage.…

Helping Your Child Learn Mathematics

ERIC Educational Resources Information Center

US Department of Education, 2004

2004-01-01

An increasingly technological world demands strong mathematical skills for the workforce and everyday life, and these demands will increase in the future. Research has shown that children are more likely to be successful in mathematics and other academic subjects when parents actively support their learning. To ensure that children are on track…

The Use of Design Practice to Teach Mathematics and Science

ERIC Educational Resources Information Center

Norton, Stephen John

2008-01-01

Relatively low participation in the hard sciences (mathematics, science, engineering and technology) has become a concern with respect to the capacity of Australia to meet critical infrastructure projects. This problem has its roots in poor student attitudes towards and perceptions about the study of prerequisite subjects including mathematics and…

VDOE :: Standards of Learning (SOL) and Testing

Science.gov Websites

Health History & Social Science Family Life Fine Arts Foreign Language Mathematics Physical Education the end of each grade or course in English, mathematics, science, history/social science and other subjects. SOL tests in reading, writing, mathematics, science and history/social science measure the

The Early Childhood Mathematics Education Revolution

ERIC Educational Resources Information Center

Hachey, Alyse C.

2013-01-01

Research Findings: We are in the midst of a revolution. Prior to the onset of the 21st century, mathematics education in the United States was deemphasized (Geary, 1996), and mathematics as an instructional subject has traditionally been considered above the preschool and kindergarten levels. However, the old regime--the knowledge and philosophies…

Synopses for Modern Secondary School Mathematics.

ERIC Educational Resources Information Center

Organisation for Economic Cooperation and Development, Paris (France). Directorate for Scientific Affairs.

The 1959 Royaumont seminar "New Thinking in School Mathematics," having agreed on the need for modernization, recommended that a second group of experts work out detailed synopses of the entire subject matter of secondary school mathematics. This book is the report of the second seminar and contains the Dubrovnik Program which stimulated…

Seventies, Eighties, Nineties, Noughties.... a Sequence of Concerns

ERIC Educational Resources Information Center

Jackson, Elizabeth

2007-01-01

This paper outlines small scale research regarding mathematics anxiety and potential links to confidence and mathematics subject knowledge for primary teacher education (QTS) students in a HE institution, where the author is a Senior Lecturer in Primary Mathematics Education. The purpose is to establish the existence of such anxiety and related…

Students' Exploratory Thinking about a Nonroutine Calculus Task

ERIC Educational Resources Information Center

Nabb, Keith

2013-01-01

In this article on introductory calculus, intriguing questions are generated that can ignite an appreciation for the subject of mathematics. These questions open doors to advanced mathematical thinking and harness many elements of research-oriented mathematics. Such questions also offer greater incentives for students to think and reflect.…

Mathematics and Academic Diversity in Japan

ERIC Educational Resources Information Center

Woodward, J.; Ono, Y.

2004-01-01

Japanese education has been the subject of considerable research and educational commentary in the United States over the last 20 years. Since the early 1990s, there has been increased interest in Japanese methods for teaching mathematics, and the Third International Mathematics and Science Study has accelerated American interest in Japanese…

A hybrid three-class brain-computer interface system utilizing SSSEPs and transient ERPs

NASA Astrophysics Data System (ADS)

Breitwieser, Christian; Pokorny, Christoph; Müller-Putz, Gernot R.

2016-12-01

Objective. This paper investigates the fusion of steady-state somatosensory evoked potentials (SSSEPs) and transient event-related potentials (tERPs), evoked through tactile simulation on the left and right-hand fingertips, in a three-class EEG based hybrid brain-computer interface. It was hypothesized, that fusing the input signals leads to higher classification rates than classifying tERP and SSSEP individually. Approach. Fourteen subjects participated in the studies, consisting of a screening paradigm to determine person dependent resonance-like frequencies and a subsequent online paradigm. The whole setup of the BCI system was based on open interfaces, following suggestions for a common implementation platform. During the online experiment, subjects were instructed to focus their attention on the stimulated fingertips as indicated by a visual cue. The recorded data were classified during runtime using a multi-class shrinkage LDA classifier and the outputs were fused together applying a posterior probability based fusion. Data were further analyzed offline, involving a combined classification of SSSEP and tERP features as a second fusion principle. The final results were tested for statistical significance applying a repeated measures ANOVA. Main results. A significant classification increase was achieved when fusing the results with a combined classification compared to performing an individual classification. Furthermore, the SSSEP classifier was significantly better in detecting a non-control state, whereas the tERP classifier was significantly better in detecting control states. Subjects who had a higher relative band power increase during the screening session also achieved significantly higher classification results than subjects with lower relative band power increase. Significance. It could be shown that utilizing SSSEP and tERP for hBCIs increases the classification accuracy and also that tERP and SSSEP are not classifying control- and non-control states with the same level of accuracy.

Analysis of swallowing sounds using hidden Markov models.

PubMed

Aboofazeli, Mohammad; Moussavi, Zahra

2008-04-01

In recent years, acoustical analysis of the swallowing mechanism has received considerable attention due to its diagnostic potentials. This paper presents a hidden Markov model (HMM) based method for the swallowing sound segmentation and classification. Swallowing sound signals of 15 healthy and 11 dysphagic subjects were studied. The signals were divided into sequences of 25 ms segments each of which were represented by seven features. The sequences of features were modeled by HMMs. Trained HMMs were used for segmentation of the swallowing sounds into three distinct phases, i.e., initial quiet period, initial discrete sounds (IDS) and bolus transit sounds (BTS). Among the seven features, accuracy of segmentation by the HMM based on multi-scale product of wavelet coefficients was higher than that of the other HMMs and the linear prediction coefficient (LPC)-based HMM showed the weakest performance. In addition, HMMs were used for classification of the swallowing sounds of healthy subjects and dysphagic patients. Classification accuracy of different HMM configurations was investigated. When we increased the number of states of the HMMs from 4 to 8, the classification error gradually decreased. In most cases, classification error for N=9 was higher than that of N=8. Among the seven features used, root mean square (RMS) and waveform fractal dimension (WFD) showed the best performance in the HMM-based classification of swallowing sounds. When the sequences of the features of IDS segment were modeled separately, the accuracy reached up to 85.5%. As a second stage classification, a screening algorithm was used which correctly classified all the subjects but one healthy subject when RMS was used as characteristic feature of the swallowing sounds and the number of states was set to N=8.

Determining aspects of ethnicity amongst persons of South Asian origin: the use of a surname-classification programme (Nam Pehchan).

PubMed

Macfarlane, Gary J; Lunt, Mark; Palmer, Benedict; Afzal, Cara; Silman, Alan J; Esmail, Aneez

2007-03-01

Name-based classification systems are potentially useful in identifying study samples based on probable ethnic minority group. The aim of the current study was to assess the validity of the Nam Pehchan name classification programme of religion and language against subject self-report. A population-based cross-sectional survey conducted in areas of the North-West and West Midland regions of England with a relatively high density of South Asian ethnic minority groups. The sampling frame was age-sex registers of selected general practices and subjects were classified according to language and religion using the Nam Pehchan programme. These were compared with responses by subjects on a self-complete postal questionnaire. One thousand nine hundred and forty-nine subjects who participated, classified themselves as South Asian. Sensitivity in identifying religion was high amongst Muslims (92%) and Sikhs (86%), and somewhat lower in Hindus (62%). Specificity exceeded 95% for all ethnic groups. The vast majority of subjects assigned Punjabi or Gujarati as their main South Asian language indicated that they did in fact speak these languages (97% and 94%, respectively). Subjects assigned Urdu or Bengali, however, were less likely to do so (61% and 35%, respectively). The name-based classification system Nam Pehchan has demonstrated high levels of accuracy in some sub-groups of the South Asian population in determining subjects likely language spoken and religion-and is likely to be a useful additional tool when information on ethnicity is not already available.

Large Deviations for Nonlocal Stochastic Neural Fields

PubMed Central

2014-01-01

We study the effect of additive noise on integro-differential neural field equations. In particular, we analyze an Amari-type model driven by a Q-Wiener process, and focus on noise-induced transitions and escape. We argue that proving a sharp Kramers’ law for neural fields poses substantial difficulties, but that one may transfer techniques from stochastic partial differential equations to establish a large deviation principle (LDP). Then we demonstrate that an efficient finite-dimensional approximation of the stochastic neural field equation can be achieved using a Galerkin method and that the resulting finite-dimensional rate function for the LDP can have a multiscale structure in certain cases. These results form the starting point for an efficient practical computation of the LDP. Our approach also provides the technical basis for further rigorous study of noise-induced transitions in neural fields based on Galerkin approximations. Mathematics Subject Classification (2000): 60F10, 60H15, 65M60, 92C20. PMID:24742297

Mathematical and Statistical Software Index.

DTIC Science & Technology

1986-08-01

geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis

Disentangling Mathematics Target and Access Skills: Implications for Accommodation Assignment Practices

ERIC Educational Resources Information Center

Ketterlin-Geller, Leanne R.; Jamgochian, Elisa M.; Nelson-Walker, Nancy J.; Geller, Joshua P.

2012-01-01

Appropriate assignment of accommodations is predicated on a clear distinction between target skills and access skills. In this study, we examine the agreement between test developer/researchers' and educators' classification of target and access skills as a possible explanatory mechanism for assigning accommodations. Findings indicate that…

A Multidimensional Model for the Identification of Dual-Exceptional Learners

ERIC Educational Resources Information Center

Al-Hroub, Anies

2013-01-01

This research takes mathematics as a model for investigating the definitions, identification, classification and characteristics of a group of gifted student related to the notion of "dual-exceptionality". An extensive process using qualitative and quantitative methods was conducted by a multidisciplinary team to develop and implement a…

Interactions between Defining, Explaining and Classifying: The Case of Increasing and Decreasing Sequences

ERIC Educational Resources Information Center

Alcock, Lara; Simpson, Adrian

2017-01-01

This paper describes a study in which we investigated relationships between defining mathematical concepts--increasing and decreasing infinite sequences--explaining their meanings and classifying consistently with formal definitions. We explored the effect of defining, explaining or studying a definition on subsequent classification, and the…

Teaching ESL Content through Kite Making for Grades K-12.

ERIC Educational Resources Information Center

Alexander, N.

Ideas for teaching elementary and secondary students of English as a Second Language (ESL) through a unit on kites and kite-making are offered. First, unit objectives are outlined. These include objectives for cognitive skill development (classification, comparison), psychomotor skills (constructing a kite), mathematical operations (measuring,…

High/Scope Preschool Key Experiences: Classification, Seriation, and Number.

ERIC Educational Resources Information Center

Koopmann, Linda

Noticing relationships between similar things and developing rules for treating things the same or differently, based on characteristics like color, size, shape, and texture provides the basis of beginning mathematics learning. Based on the view that teachers and parents of young children should provide children with age-appropriate words,…

Is a Scientific Classification of Educational (Behavioral) Objectives Possible?

ERIC Educational Resources Information Center

Stigliano, Tony

Robert M. W. Travers's 1980 essay is the focal point of this paper. He argues that evaluation research requires a scientific taxonomy of human behavior and learning. Such a taxonomy must be experimentally based, mathematically expressed, theoretically sound, and predictive. He bases such criteria on the development of scientifically successful…

Promoting Repeating Patterns with Young Children--More than Just Alternating Colours!

ERIC Educational Resources Information Center

Papic, Marina

2007-01-01

Patterning is an essential skill in early mathematics learning, particularly in the development of spatial awareness, sequencing and ordering, comparison, and classification. This includes the ability to identify and describe attributes of objects and similarities and differences between them. Patterning is also integral to the development of…

Real time workload classification from an ambulatory wireless EEG system using hybrid EEG electrodes.

PubMed

Matthews, R; Turner, P J; McDonald, N J; Ermolaev, K; Manus, T; Shelby, R A; Steindorf, M

2008-01-01

This paper describes a compact, lightweight and ultra-low power ambulatory wireless EEG system based upon QUASAR's innovative noninvasive bioelectric sensor technologies. The sensors operate through hair without skin preparation or conductive gels. Mechanical isolation built into the harness permits the recording of high quality EEG data during ambulation. Advanced algorithms developed for this system permit real time classification of workload during subject motion. Measurements made using the EEG system during ambulation are presented, including results for real time classification of subject workload.

Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qui

2009-01-01

Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

76 FR 33357 - Notice of Realty Action; Recreation and Public Purposes Act Classification; and Notice of Intent...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-08

.... 1715 (c), and thus made subject to BLM classification and planning requirements. The BLM Kingman RMP...] Notice of Realty Action; Recreation and Public Purposes Act Classification; and Notice of Intent To... classification approximately 1.31 acres of public land located in Mohave County, Arizona, and has found the...

XUV Frequency Comb Development for Precision Spectroscopy and Ultrafast Science

DTIC Science & Technology

2015-07-28

first time and provide insight to the underlying 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a...TERMS. Key words or phrases identifying major concepts in the report. 16. SECURITY CLASSIFICATION. Enter security classification in accordance with... security classification regulations, e.g. U, C, S, etc. If this form contains classified information, stamp classification level on the top and bottom

Classification of autism spectrum disorder using supervised learning of brain connectivity measures extracted from synchrostates

NASA Astrophysics Data System (ADS)

Jamal, Wasifa; Das, Saptarshi; Oprescu, Ioana-Anastasia; Maharatna, Koushik; Apicella, Fabio; Sicca, Federico

2014-08-01

Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perception tasks. Approach. Phase synchronized patterns from 128-channel EEG signals are obtained for typical children and children with autism spectrum disorder (ASD). The phase synchronized states or synchrostates temporally switch amongst themselves as an underlying process for the completion of a particular cognitive task. We used 12 subjects in each group (ASD and typical) for analyzing their EEG while processing fearful, happy and neutral faces. The minimal and maximally occurring synchrostates for each subject are chosen for extraction of brain connectivity features, which are used for classification between these two groups of subjects. Among different supervised learning techniques, we here explored the discriminant analysis and support vector machine both with polynomial kernels for the classification task. Main results. The leave one out cross-validation of the classification algorithm gives 94.7% accuracy as the best performance with corresponding sensitivity and specificity values as 85.7% and 100% respectively. Significance. The proposed method gives high classification accuracies and outperforms other contemporary research results. The effectiveness of the proposed method for classification of autistic and typical children suggests the possibility of using it on a larger population to validate it for clinical practice.

Multiparametric fat-water separation method for fast chemical-shift imaging guidance of thermal therapies.

PubMed

Lin, Jonathan S; Hwang, Ken-Pin; Jackson, Edward F; Hazle, John D; Stafford, R Jason; Taylor, Brian A

2013-10-01

A k-means-based classification algorithm is investigated to assess suitability for rapidly separating and classifying fat/water spectral peaks from a fast chemical shift imaging technique for magnetic resonance temperature imaging. Algorithm testing is performed in simulated mathematical phantoms and agar gel phantoms containing mixed fat/water regions. Proton resonance frequencies (PRFs), apparent spin-spin relaxation (T2*) times, and T1-weighted (T1-W) amplitude values were calculated for each voxel using a single-peak autoregressive moving average (ARMA) signal model. These parameters were then used as criteria for k-means sorting, with the results used to determine PRF ranges of each chemical species cluster for further classification. To detect the presence of secondary chemical species, spectral parameters were recalculated when needed using a two-peak ARMA signal model during the subsequent classification steps. Mathematical phantom simulations involved the modulation of signal-to-noise ratios (SNR), maximum PRF shift (MPS) values, analysis window sizes, and frequency expansion factor sizes in order to characterize the algorithm performance across a variety of conditions. In agar, images were collected on a 1.5T clinical MR scanner using acquisition parameters close to simulation, and algorithm performance was assessed by comparing classification results to manually segmented maps of the fat/water regions. Performance was characterized quantitatively using the Dice Similarity Coefficient (DSC), sensitivity, and specificity. The simulated mathematical phantom experiments demonstrated good fat/water separation depending on conditions, specifically high SNR, moderate MPS value, small analysis window size, and low but nonzero frequency expansion factor size. Physical phantom results demonstrated good identification for both water (0.997 ± 0.001, 0.999 ± 0.001, and 0.986 ± 0.001 for DSC, sensitivity, and specificity, respectively) and fat (0.763 ± 0.006, 0.980 ± 0.004, and 0.941 ± 0.002 for DSC, sensitivity, and specificity, respectively). Temperature uncertainties, based on PRF uncertainties from a 5 × 5-voxel ROI, were 0.342 and 0.351°C for pure and mixed fat/water regions, respectively. Algorithm speed was tested using 25 × 25-voxel and whole image ROIs containing both fat and water, resulting in average processing times per acquisition of 2.00 ± 0.07 s and 146 ± 1 s, respectively, using uncompiled MATLAB scripts running on a shared CPU server with eight Intel Xeon(TM) E5640 quad-core processors (2.66 GHz, 12 MB cache) and 12 GB RAM. Results from both the mathematical and physical phantom suggest the k-means-based classification algorithm could be useful for rapid, dynamic imaging in an ROI for thermal interventions. Successful separation of fat/water information would aid in reducing errors from the nontemperature sensitive fat PRF, as well as potentially facilitate using fat as an internal reference for PRF shift thermometry when appropriate. Additionally, the T1-W or R2* signals may be used for monitoring temperature in surrounding adipose tissue.

Persistence and withdrawal by students in a preservice science and mathematics teacher education course

NASA Astrophysics Data System (ADS)

Tulip, David F.; Lucas, Keith B.

1991-12-01

At a time when recruitment into preservice teacher education courses in mathematics and science is difficult, one strategy to increase the number of graduates is to minimise the number of students who fail to complete their university courses. This study sought to determine factors which distinguish withdrawers from persisters in the first semester of a B.Ed course. Discriminant analysis was employed; a discriminant function employing seven factors resulted in correct classification in 81% of cases. Further analysis distinguishing between dropouts and transferees resulted in two discriminant functions with some common variables.

Developing Distinct Mathematical and Scientific Pedagogical Content Knowledge in an Early Childhood Dual-Content Methods Course: An Alternative to Integration

ERIC Educational Resources Information Center

Kalchman, Mindy; Kozoll, Richard H.

2017-01-01

Methods for teaching early childhood mathematics and science are often addressed in a single, dual-content course. Approaches to teaching this type of course include integrating the content and the pedagogy of both subjects, or keeping the subject areas distinct. In this article, the authors discuss and illustrate their approach to such a combined…

The Effects of CLIL Education on the Subject Matter (Mathematics) and the Target Language (English)

ERIC Educational Resources Information Center

Ouazizi, Khalid

2016-01-01

This paper investigates the effects of Content and Language Integrated Learning, CLIL for short, on both the attainment of the subject matter, mathematics in our case, hence the content aspect of CLIL. The second axes of research focuses on the effect of CLIL on the learners' proficiency vis-à-vis the language of instruction, epitomized here by…

A study of competence in mathematics and mechanics in an engineering curriculum

NASA Astrophysics Data System (ADS)

Munns, Andrew

2017-11-01

Professional bodies expect engineers to show competence in both mathematics and engineering topics such as mechanics, using their abilities in both of these to solve problems. Yet within engineering programmes there is a phenomenon known as 'The Mathematics Problem', with students not demonstrating understanding of the subject. This paper will suggest that students are constructing different concept images in engineering and mathematics, based on their perception of either the use or exchange-value for the topics. Using a mixed methods approach, the paper compares 10 different types of concept image constructed by students, which suggests that familiar procedural images are preferred in mathematics. In contrast strategic and conceptual images develop for mechanics throughout the years of the programme, implying that different forms of competence are being constructed by students between the two subjects. The paper argues that this difference is attributed to the perceived use-value of mechanics in the career of the engineer, compared to the exchange-value associated with mathematics. Questions are raised about the relevance of current definitions of competence given that some routine mathematical operations previously performed by engineers are now being replaced by technology, in the new world of work.

The Increase of Critical Thinking Skills through Mathematical Investigation Approach

NASA Astrophysics Data System (ADS)

Sumarna, N.; Wahyudin; Herman, T.

2017-02-01

Some research findings on critical thinking skills of prospective elementary teachers, showed a response that is not optimal. On the other hand, critical thinking skills will lead a student in the process of analysis, evaluation and synthesis in solving a mathematical problem. This study attempts to perform an alternative solution with a focus on mathematics learning conditions that is held in the lecture room through mathematical investigation approach. This research method was Quasi-Experimental design with pre-test post-test design. Data analysis using a mixed method with Embedded design. Subjects were regular students enrolled in 2014 at the study program of education of primary school teachers. The number of research subjects were 111 students consisting of 56 students in the experimental group and 55 students in the control group. The results of the study showed that (1) there is a significant difference in the improvement of critical thinking ability of students who receive learning through mathematical investigation approach when compared with students studying through expository approach, and (2) there is no interaction effect between prior knowledge of mathematics and learning factors (mathematical investigation and expository) to increase of critical thinking skills of students.

High profile students’ growth of mathematical understanding in solving linier programing problems

NASA Astrophysics Data System (ADS)

Utomo; Kusmayadi, TA; Pramudya, I.

2018-04-01

Linear program has an important role in human’s life. This linear program is learned in senior high school and college levels. This material is applied in economy, transportation, military and others. Therefore, mastering linear program is useful for provision of life. This research describes a growth of mathematical understanding in solving linear programming problems based on the growth of understanding by the Piere-Kieren model. Thus, this research used qualitative approach. The subjects were students of grade XI in Salatiga city. The subjects of this study were two students who had high profiles. The researcher generally chose the subjects based on the growth of understanding from a test result in the classroom; the mark from the prerequisite material was ≥ 75. Both of the subjects were interviewed by the researcher to know the students’ growth of mathematical understanding in solving linear programming problems. The finding of this research showed that the subjects often folding back to the primitive knowing level to go forward to the next level. It happened because the subjects’ primitive understanding was not comprehensive.

Students' Attitudes towards Mathematics in Single-Sex and Coeducational Schools.

ERIC Educational Resources Information Center

Norton, Stephen J.; Rennie, Leonie J.

1998-01-01

Discusses part of study stimulated by the continuing debate over differences between boys and girls in their attitudes towards mathematics and their participation and performance in this subject at school. Concludes that there were clear differences between boys and girls on the Mathematics as a Male Domain scale with girls being less stereotyped…

What Is Discrete Mathematics?

ERIC Educational Resources Information Center

Sharp, Karen Tobey

This paper cites information received from a number of sources, e.g., mathematics teachers in two-year colleges, publishers, and convention speakers, about the nature of discrete mathematics and about what topics a course in this subject should contain. Note is taken of the book edited by Ralston and Young which discusses the future of college…

Measurement Characteristics of the MAA Math Placement Tests.

ERIC Educational Resources Information Center

Melancon, Janet G.; Thompson, Bruce

This paper presents analyses of score reliability for a mathematics placement test developed by the Mathematical Association of America in 1984 for use with undergraduate college students. Subjects included all 589 students seeking admission to the college mathematics curricula at a private university in the South during the course of the study.…

Do Advanced Mathematics Skills Predict Success in Biology and Chemistry Degrees?

ERIC Educational Resources Information Center

Adkins, Michael; Noyes, Andrew

2018-01-01

The mathematical preparedness of science undergraduates has been a subject of debate for some time. This paper investigates the relationship between school mathematics attainment and degree outcomes in biology and chemistry across England, a much larger scale of analysis than has hitherto been reported in the literature. A unique dataset which…

Constructive Metacognitive Activity Shift in Mathematical Problem Solving

ERIC Educational Resources Information Center

Hastuti, Intan Dwi; Nusantara, Toto; Subanji; Susanto, Hery

2016-01-01

This study aims to describe the constructive metacognitive activity shift of eleventh graders in solving a mathematical problem. Subjects in this study were 10 students in grade 11 of SMAN 1 Malang. They were divided into 4 groups. Three types of metacognitive activity undertaken by students when completing mathematical problem are awareness,…

Experiences of Visually Impaired Students in Community College Math Courses

ERIC Educational Resources Information Center

Swan, S. Tomeka

2017-01-01

Blind and visually impaired students who attend community colleges face challenges in learning mathematics (Forrest, 2010). Scoy, McLaughlin, Walls, and Zuppuhaur (2006) claim these students are at a disadvantage in studying mathematics due to the visual and interactive nature of the subject, and by the way mathematics is taught. In this…

Learning Style Preferences and Mathematics Achievement of Secondary School Learners

ERIC Educational Resources Information Center

Bosman, Anne; Schulze, Salome

2018-01-01

Mathematics is a key subject necessary to the promotion of economic development, particularly in developing countries; however, South African learners perform poorly in Mathematics when benchmarked against their counterparts in other countries. One way to address this issue is by taking cognisance of the learners' learning styles when teaching.…

Understanding Mathematics: Some Key Factors

ERIC Educational Resources Information Center

Ali, Asma Amanat; Reid, Norman

2012-01-01

Mathematics is well known as a subject area where there can be problems in terms of understanding as well as retaining positive attitudes. In a large study involving 813 school students (ages approximately 10-12) drawn from two different school systems in Pakistan, the effect of limited working memory capacity on performance in mathematics was…

Mathematical Inqu[ee]ry: Beyond "Add-Queers-and-Stir" Elementary Mathematics Education

ERIC Educational Resources Information Center

Rands, Kathleen

2009-01-01

While elementary educators have developed queer pedagogies and perspectives in many subjects from reading to music, science to English as a second language, queer perspectives on elementary mathematics education are remarkably absent. This article differentiates between two common uses of the term "queer" and delineates two sets of approaches…

Effects of Teaching Strategies on Student Motivation to Learn in High School Mathematics Classes

ERIC Educational Resources Information Center

Toles, Ann

2010-01-01

To succeed in an increasing technological and global society, students need to develop strong mathematical and problem-solving skills. This qualitative grounded theory study examined student perceptions of the ways in which teaching strategies in high school mathematics classes affect student motivation to learn the subject. Study participants…

Primary Mathematics Teacher Education Encountering Difficult Terrain: A Personal Perspective

ERIC Educational Resources Information Center

Norton, Stephen

2016-01-01

This paper is a case study in preparing prospective primary teachers to teach mathematics at one Australian university. The paper describes the content knowledge of prospective teachers, pre and post a final mathematics curriculum subject. The teaching approach which attempts to account for both content and pedagogical content knowledge is…

The Transmission of Mathematics into Greek Education, 1800-1840: From Individual Initiatives to Institutionalization

ERIC Educational Resources Information Center

Kastanis, Iason; Kastanis, Nikos

2006-01-01

In the early nineteenth century, a number of Greek communities developed a remarkable education in mathematics. The subject matter for this instruction was drawn mainly from French textbooks, although some teachers displayed a preference for Prussian mathematical sources. These efforts, however, were thwarted by the religious conservatism of the…

The Enhancement of Students' Teacher Mathematical Reasoning Ability through Reflective Learning

ERIC Educational Resources Information Center

Rohana

2015-01-01

This study aims to examine the enhancement of mathematical reasoning ability through reflective learning. This study used quasi-experimental method with nonequivalent pretest and posttest control group design. The subject of this study were students of Mathematics Education Program in one of private universities in Palembang, South Sumatera,…

Ethno-Mathema-tics of Basotho

ERIC Educational Resources Information Center

Narayanan, Ajayagosh

2011-01-01

Mathematics as a subject is indispensable in the development of Lesotho with respect to science, technology or any other field of knowledge. It is also a mirror to our past. In this case, Lesotho's indigenous mathematics is not fully explored and understood by Basotho. This author aims to present ethno mathematics of Basotho as compared to…

Investigating the Effects of a Math-Enhanced Agricultural Teaching Methods Course

ERIC Educational Resources Information Center

Stripling, Christopher T.; Roberts, T. Grady

2013-01-01

Numerous calls have been made for agricultural education to support core academic subject matter including mathematics. Previous research has shown that the incorporation of mathematics content into a teaching methods course had a positive effect on preservice teachers' mathematics content knowledge. The purpose of this study was to investigate…

Culture Points: Engaging Students outside the Classroom

ERIC Educational Resources Information Center

Fraboni, Michael; Hartshorn, Kevin

2007-01-01

In the typical first-year mathematics course--whether it be calculus or a general education quantitative proficiency course--we struggle to help students see the relevance of mathematics to their own lives. Particularly in a focused course such as calculus, there is a danger that students see mathematics as an isolated subject, with applications…

Identification of Student- and Teacher-Level Variables in Modeling Variation of Mathematics Achievement Data

ERIC Educational Resources Information Center

Tarr, James E.; Ross, Daniel J.; McNaught, Melissa D.; Chavez, Oscar; Grouws, Douglas A.; Reys, Robert E.; Sears, Ruthmae; Taylan, R. Didem

2010-01-01

The Comparing Options in Secondary Mathematics: Investigating Curriculum (COSMIC) project is a longitudinal study of student learning from two types of mathematics curricula: integrated and subject-specific. Previous large-scale research studies such as the National Assessment of Educational Progress (NAEP) indicate that numerous variables are…

Virtual and Concrete Manipulatives: A Comparison of Approaches for Solving Mathematics Problems for Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Bouck, Emily C.; Satsangi, Rajiv; Doughty, Teresa Taber; Courtney, William T.

2014-01-01

Students with autism spectrum disorder (ASD) are included in general education classes and expected to participate in general education content, such as mathematics. Yet, little research explores academically-based mathematics instruction for this population. This single subject alternating treatment design study explored the effectiveness of…

Cognitive Activities in Solving Mathematical Tasks: The Role of a Cognitive Obstacle

ERIC Educational Resources Information Center

Antonijevic, Radovan

2016-01-01

In the process of learning mathematics, students practice various forms of thinking activities aimed to substantially contribute to the development of their different cognitive structures. In this paper, the subject matter is a "cognitive obstacle", a phenomenon that occurs in the procedures of solving mathematical tasks. Each task in…

A Study of Competence in Mathematics and Mechanics in an Engineering Curriculum

ERIC Educational Resources Information Center

Munns, Andrew

2017-01-01

Professional bodies expect engineers to show competence in both mathematics and engineering topics such as mechanics, using their abilities in both of these to solve problems. Yet within engineering programmes there is a phenomenon known as "The Mathematics Problem", with students not demonstrating understanding of the subject. This…

Making Visible and Acting on Issues of Racism and Racialization in School Mathematics

ERIC Educational Resources Information Center

Morvan, Jhonel A.

2017-01-01

Schools, as social systems, may knowingly or unintentionally perpetuate inequities through unchallenged oppressive systems. This paper focuses on mathematics as a subject area in school practices in which inequities seem to be considered normal. Issues of racism and racialization in the discipline of mathematics are predominantly lived through the…

The Differences in Scores and Self-Efficacy by Student Gender in Mathematics and Science

ERIC Educational Resources Information Center

Louis, Rachel A.; Mistele, Jean M.

2012-01-01

Typically, mathematics and science are seen as linked together, where both subjects involve numbers, critical thinking, and problem solving. Our study aims to develop a better understanding of the connections between student's achievement scores in mathematics and science, student gender, and self-efficacy. We used the Trends in International…

Mathematics and Social Justice: A Symbiotic Pedagogy

ERIC Educational Resources Information Center

Bond, Gareth; Chernoff, Egan J.

2015-01-01

Mathematics can be defined as "the science of pattern and order" (Van de Walle, Folk, Karp, & Bay-Williams, 2009, p. 10). But because there is often a perceived spectrum of approachability to mathematics (based on common misconceptions that envision the subject as a sort of elitist wizardry) it is important to bear in mind different…

Roots of Mathematics Anxiety in College Students

ERIC Educational Resources Information Center

Quan-Lorey, Stephanie

2017-01-01

A majority of college students exhibit feelings of fear and discomfort when put into situations that require the use of mathematics. These students are characterized to be mathematics-anxious and tend to overlook the idea that one can gain many benefits from learning the subject. This paper investigates the various factors that have led to and…

Teachers' Perspectives Regarding the Decline in Boys' Participation in Post-Compulsory Rigorous Mathematics Subjects

ERIC Educational Resources Information Center

Easey, Michael

2013-01-01

This paper explores the decline in boys' participation in post-compulsory rigorous mathematics using the perspectives of eight experienced teachers at an independent, boys' College located in Brisbane, Queensland. This study coincides with concerns regarding the decline in suitably qualified tertiary graduates with requisite mathematical skills…

Mathematical models of behavior of individual animals.

PubMed

Tsibulsky, Vladimir L; Norman, Andrew B

2007-01-01

This review is focused on mathematical modeling of behaviors of a whole organism with special emphasis on models with a clearly scientific approach to the problem that helps to understand the mechanisms underlying behavior. The aim is to provide an overview of old and contemporary mathematical models without complex mathematical details. Only deterministic and stochastic, but not statistical models are reviewed. All mathematical models of behavior can be divided into two main classes. First, models that are based on the principle of teleological determinism assume that subjects choose the behavior that will lead them to a better payoff in the future. Examples are game theories and operant behavior models both of which are based on the matching law. The second class of models are based on the principle of causal determinism, which assume that subjects do not choose from a set of possibilities but rather are compelled to perform a predetermined behavior in response to specific stimuli. Examples are perception and discrimination models, drug effects models and individual-based population models. A brief overview of the utility of each mathematical model is provided for each section.

Summary measures of agreement and association between many raters' ordinal classifications.

PubMed

Mitani, Aya A; Freer, Phoebe E; Nelson, Kerrie P

2017-10-01

Interpretation of screening tests such as mammograms usually require a radiologist's subjective visual assessment of images, often resulting in substantial discrepancies between radiologists' classifications of subjects' test results. In clinical screening studies to assess the strength of agreement between experts, multiple raters are often recruited to assess subjects' test results using an ordinal classification scale. However, using traditional measures of agreement in some studies is challenging because of the presence of many raters, the use of an ordinal classification scale, and unbalanced data. We assess and compare the performances of existing measures of agreement and association as well as a newly developed model-based measure of agreement to three large-scale clinical screening studies involving many raters' ordinal classifications. We also conduct a simulation study to demonstrate the key properties of the summary measures. The assessment of agreement and association varied according to the choice of summary measure. Some measures were influenced by the underlying prevalence of disease and raters' marginal distributions and/or were limited in use to balanced data sets where every rater classifies every subject. Our simulation study indicated that popular measures of agreement and association are prone to underlying disease prevalence. Model-based measures provide a flexible approach for calculating agreement and association and are robust to missing and unbalanced data as well as the underlying disease prevalence. Copyright © 2017 Elsevier Inc. All rights reserved.

Relationship between AOD and synoptic circulation over the Eastern Mediterranean: A comparison between subjective and objective classifications

NASA Astrophysics Data System (ADS)

Bodenheimer, Shalev; Nirel, Ronit; Lensky, Itamar M.; Dayan, Uri

2018-03-01

The Eastern Mediterranean (EM) Basin is strongly affected by dust originating from two of the largest world sources: The Sahara Desert and the Arabian Peninsula. Climatologically, the distribution pattern of aerosol optical depth (AOD), as proxy to particulate matter (PM), is known to be correlated with synoptic circulation. The climatological relationship between circulation type classifications (CTCs) and AOD levels over the EM Basin ("synoptic skill") was examined for the years 2000-2014. We compared the association between subjective (expert-based) and objective (fully automated) classifications and AOD using autoregressive models. After seasonal adjustment, the mean values of R2 for the different methods were similar. However, the distinct spatial pattern of the R2 values suggests that subjective classifications perform better in their area of expertise, specifically in the southeast region of the study area, while, objective CTCs had better synoptic skill over the northern part of the EM. This higher synoptic skill of subjective CTCs stem from their ability to identify distinct circulation types (e.g. Sharav lows and winter lows) that are infrequent but are highly correlated with AOD. Notably, a simple CTC based on seasonality rather than meteorological parameters predicted well AOD levels, especially over the south-eastern part of the domain. Synoptic classifications that are area-oriented are likely better predictors of AOD and possibly other environmental variables.

Low-back electromyography (EMG) data-driven load classification for dynamic lifting tasks.

PubMed

Totah, Deema; Ojeda, Lauro; Johnson, Daniel D; Gates, Deanna; Mower Provost, Emily; Barton, Kira

2018-01-01

Numerous devices have been designed to support the back during lifting tasks. To improve the utility of such devices, this research explores the use of preparatory muscle activity to classify muscle loading and initiate appropriate device activation. The goal of this study was to determine the earliest time window that enabled accurate load classification during a dynamic lifting task. Nine subjects performed thirty symmetrical lifts, split evenly across three weight conditions (no-weight, 10-lbs and 24-lbs), while low-back muscle activity data was collected. Seven descriptive statistics features were extracted from 100 ms windows of data. A multinomial logistic regression (MLR) classifier was trained and tested, employing leave-one subject out cross-validation, to classify lifted load values. Dimensionality reduction was achieved through feature cross-correlation analysis and greedy feedforward selection. The time of full load support by the subject was defined as load-onset. Regions of highest average classification accuracy started at 200 ms before until 200 ms after load-onset with average accuracies ranging from 80% (±10%) to 81% (±7%). The average recall for each class ranged from 69-92%. These inter-subject classification results indicate that preparatory muscle activity can be leveraged to identify the intent to lift a weight up to 100 ms prior to load-onset. The high accuracies shown indicate the potential to utilize intent classification for assistive device applications. Active assistive devices, e.g. exoskeletons, could prevent back injury by off-loading low-back muscles. Early intent classification allows more time for actuators to respond and integrate seamlessly with the user.

Mathematics education for social justice

NASA Astrophysics Data System (ADS)

Suhendra

2016-02-01

Mathematics often perceived as a difficult subject with many students failing to understand why they learn mathematics. This situation has been further aggravated by the teaching and learning processes used, which is mechanistic without considering students' needs. The learning of mathematics tends to be just a compulsory subject, in which all students have to attend its classes. Social justice framework facilitates individuals or groups as a whole and provides equitable approaches to achieving equitable outcomes by recognising disadvantage. Applying social justice principles in educational context is related to how the teachers treat their students, dictates that all students the right to equal treatment regardless of their background and completed with applying social justice issues integrated with the content of the subject in order to internalise the principles of social justice simultaneously the concepts of the subject. The study examined the usefulness of implementing the social justice framework as a means of improving the quality of mathematics teaching in Indonesia involved four teacher-participants and their mathematics classes. The study used action research as the research methodology in which the teachers implemented and evaluated their use of social justice framework in their teaching. The data were collected using multiple research methods while analysis and interpretation of the data were carried out throughout the study. The findings of the study indicated that there were a number of challengesrelated to the implementation of the social justice framework. The findings also indicated that, the teachers were provided with a comprehensive guide that they could draw on to make decisions about how they could improve their lessons. The interactions among students and between the teachers and the students improved, they became more involved in teaching and learning process. Using social justice framework helped the teachers to make mathematics more relevant to students. This increased relevance led to increasing students' engagement in the teaching and learning process and becoming more accessible to all students. Additionally, the findings have the potential to make a contribution to those seeking to reform mathematics teaching in Indonesia. The results could inform policy makers and professional development providers about how social justice framework might contribute to the educational reform in Indonesia.

Making instruction and assessment responsive to diverse students' progress: group-administered dynamic assessment in teaching mathematics.

PubMed

Jeltova, Ida; Birney, Damian; Fredine, Nancy; Jarvin, Linda; Sternberg, Robert J; Grigorenko, Elena L

2011-01-01

This study entailed a 3 (instructional intervention) × 2 (assessment-type) between-subjects experimental design employing a pretest-intervention-posttest methodology. The instructional interventions were administered between subjects in three conditions: (a) dynamic instruction, (b) triarchic or theory of successful intelligence-control instruction, and (c) standard-control instruction. The assessment-type consisted between subjects of either (a) a group-administered dynamic posttest or (b) the same group-administered posttest interspersed with a control filler activity. Performance in different mathematics content areas taught in fourth grade was investigated. In total, 1,332 students and 63 classroom teachers in 24 schools across six school districts participated in the study. The results indicate the advantages of using dynamic instruction and assessment in regular classrooms while teaching mathematics, especially when the student body is highly ethnically diverse.

34 CFR 300.10 - Core academic subjects.

Code of Federal Regulations, 2010 CFR

2010-07-01

... DISABILITIES General Definitions Used in This Part § 300.10 Core academic subjects. Core academic subjects means English, reading or language arts, mathematics, science, foreign languages, civics and government...

Former Spencer Artillery Range, Tennessee Classification Demonstration Open Field and Dynamic Areas

DTIC Science & Technology

2016-01-01

DEMONSTRATION REPORT Former Spencer Artillery Range, Tennessee Classification Demonstration Open Field and Dynamic Areas ESTCP...AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a. REPORT b. ABSTRACT c. THIS PAGE 17...2016 Technical Report N/A Former Spencer Artillery Range, Tennessee Classification Demonstration Open Field and Dynamic Areas Richard MacNeil, USA

Sequenced subjective accents for brain-computer interfaces

NASA Astrophysics Data System (ADS)

Vlek, R. J.; Schaefer, R. S.; Gielen, C. C. A. M.; Farquhar, J. D. R.; Desain, P.

2011-06-01

Subjective accenting is a cognitive process in which identical auditory pulses at an isochronous rate turn into the percept of an accenting pattern. This process can be voluntarily controlled, making it a candidate for communication from human user to machine in a brain-computer interface (BCI) system. In this study we investigated whether subjective accenting is a feasible paradigm for BCI and how its time-structured nature can be exploited for optimal decoding from non-invasive EEG data. Ten subjects perceived and imagined different metric patterns (two-, three- and four-beat) superimposed on a steady metronome. With an offline classification paradigm, we classified imagined accented from non-accented beats on a single trial (0.5 s) level with an average accuracy of 60.4% over all subjects. We show that decoding of imagined accents is also possible with a classifier trained on perception data. Cyclic patterns of accents and non-accents were successfully decoded with a sequence classification algorithm. Classification performances were compared by means of bit rate. Performance in the best scenario translates into an average bit rate of 4.4 bits min-1 over subjects, which makes subjective accenting a promising paradigm for an online auditory BCI.

Gender classification from video under challenging operating conditions

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Dong, Guozhu

2014-06-01

The literature is abundant with papers on gender classification research. However the majority of such research is based on the assumption that there is enough resolution so that the subject's face can be resolved. Hence the majority of the research is actually in the face recognition and facial feature area. A gap exists for gender classification under challenging operating conditions—different seasonal conditions, different clothing, etc.—and when the subject's face cannot be resolved due to lack of resolution. The Seasonal Weather and Gender (SWAG) Database is a novel database that contains subjects walking through a scene under operating conditions that span a calendar year. This paper exploits a subset of that database—the SWAG One dataset—using data mining techniques, traditional classifiers (ex. Naïve Bayes, Support Vector Machine, etc.) and traditional (canny edge detection, etc.) and non-traditional (height/width ratios, etc.) feature extractors to achieve high correct gender classification rates (greater than 85%). Another novelty includes exploiting frame differentials.

Mathematical thinking styles of undergraduate students and their achievement in mathematics

NASA Astrophysics Data System (ADS)

Risnanosanti

2017-08-01

The main purpose of this study is to analyze the role of mathematical thinking styles in students' achievement in mathematics. On the basis of this study, it is also to generate recommendation for classroom instruction. The two specific aims are; first to observe students' mathematical thinking styles during problem solving, the second to asses students' achievement in mathematics. The data were collected by using Mathematical Thinking Styles questionnaires and test of students' achievement in mathematics. The subject in this study was 35 students from third year at mathematics study program of Muhammadiyah University of Bengkulu in academic year 2016/2017. The result of this study was that the students have three mathematical thinking styles (analytic, visual, and integrated), and the students who have analytic styles have better achievement than those who have visual styles in mathematics.

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

PubMed

Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya; Gomez-Beldarrain, Marian; Fernandez-Ruanova, Begonya; Garcia-Monco, Juan Carlos

2017-04-13

Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (DTIs). In this study, feature selection and machine learning classification methods were tested for the purpose of automating diagnosis of migraines using both DTIs and questionnaire answers related to emotion and cognition - factors that influence of pain perceptions. We select 52 adult subjects for the study divided into three groups: control group (15), subjects with sporadic migraine (19) and subjects with chronic migraine and medication overuse (18). These subjects underwent magnetic resonance with diffusion tensor to see white matter pathway integrity of the regions of interest involved in pain and emotion. The tests also gather data about pathology. The DTI images and test results were then introduced into feature selection algorithms (Gradient Tree Boosting, L1-based, Random Forest and Univariate) to reduce features of the first dataset and classification algorithms (SVM (Support Vector Machine), Boosting (Adaboost) and Naive Bayes) to perform a classification of migraine group. Moreover we implement a committee method to improve the classification accuracy based on feature selection algorithms. When classifying the migraine group, the greatest improvements in accuracy were made using the proposed committee-based feature selection method. Using this approach, the accuracy of classification into three types improved from 67 to 93% when using the Naive Bayes classifier, from 90 to 95% with the support vector machine classifier, 93 to 94% in boosting. The features that were determined to be most useful for classification included are related with the pain, analgesics and left uncinate brain (connected with the pain and emotions). The proposed feature selection committee method improved the performance of migraine diagnosis classifiers compared to individual feature selection methods, producing a robust system that achieved over 90% accuracy in all classifiers. The results suggest that the proposed methods can be used to support specialists in the classification of migraines in patients undergoing magnetic resonance imaging.

Comparing Features for Classification of MEG Responses to Motor Imagery

PubMed Central

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Background Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. Methods MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio—spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. Results The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. Conclusions We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system. PMID:27992574

Finnish Primary and Secondary School Students' Interest in Music and Mathematics Relating to Enjoyment of the Subject and Perception of the Importance and Usefulness of the Subject

ERIC Educational Resources Information Center

Tossavainen, Timo; Juvonen, Antti

2015-01-01

Based on an expectancy-value theoretical framework and data (n = 1654) collected in 29 Finnish municipalities using a structured questionnaire, this study examines primary (grades 5-6), lower secondary (grades 7-9) and upper secondary (grades 10-12) students' motivation in music and mathematics. It explores in detail the students' interest in…

Creativity of Field-dependent and Field-independent Students in Posing Mathematical Problems

NASA Astrophysics Data System (ADS)

Azlina, N.; Amin, S. M.; Lukito, A.

2018-01-01

This study aims at describing the creativity of elementary school students with different cognitive styles in mathematical problem-posing. The posed problems were assessed based on three components of creativity, namely fluency, flexibility, and novelty. The free-type problem posing was used in this study. This study is a descriptive research with qualitative approach. Data collections were conducted through written task and task-based interviews. The subjects were two elementary students. One of them is Field Dependent (FD) and the other is Field Independent (FI) which were measured by GEFT (Group Embedded Figures Test). Further, the data were analyzed based on creativity components. The results show thatFD student’s posed problems have fulfilled the two components of creativity namely fluency, in which the subject posed at least 3 mathematical problems, and flexibility, in whichthe subject posed problems with at least 3 different categories/ideas. Meanwhile,FI student’s posed problems have fulfilled all three components of creativity, namely fluency, in which thesubject posed at least 3 mathematical problems, flexibility, in which thesubject posed problems with at least 3 different categories/ideas, and novelty, in which the subject posed problems that are purely the result of her own ideas and different from problems they have known.

Mathematical values in the processing of Chinese numeral classifiers and measure words.

PubMed

Her, One-Soon; Chen, Ying-Chun; Yen, Nai-Shing

2017-01-01

A numeral classifier is required between a numeral and a noun in Chinese, which comes in two varieties, sortal classifer (C) and measural classifier (M), also known as 'classifier' and 'measure word', respectively. Cs categorize objects based on semantic attributes and Cs and Ms both denote quantity in terms of mathematical values. The aim of this study was to conduct a psycholinguistic experiment to examine whether participants process C/Ms based on their mathematical values with a semantic distance comparison task, where participants judged which of the two C/M phrases was semantically closer to the target C/M. Results showed that participants performed more accurately and faster for C/Ms with fixed values than the ones with variable values. These results demonstrated that mathematical values do play an important role in the processing of C/Ms. This study may thus shed light on the influence of the linguistic system of C/Ms on magnitude cognition.

Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram.

PubMed

Urtnasan, Erdenebayar; Park, Jong-Uk; Lee, Kyoung-Joung

2018-05-24

In this paper, we propose a convolutional neural network (CNN)-based deep learning architecture for multiclass classification of obstructive sleep apnea and hypopnea (OSAH) using single-lead electrocardiogram (ECG) recordings. OSAH is the most common sleep-related breathing disorder. Many subjects who suffer from OSAH remain undiagnosed; thus, early detection of OSAH is important. In this study, automatic classification of three classes-normal, hypopnea, and apnea-based on a CNN is performed. An optimal six-layer CNN model is trained on a training dataset (45,096 events) and evaluated on a test dataset (11,274 events). The training set (69 subjects) and test set (17 subjects) were collected from 86 subjects with length of approximately 6 h and segmented into 10 s durations. The proposed CNN model reaches a mean -score of 93.0 for the training dataset and 87.0 for the test dataset. Thus, proposed deep learning architecture achieved a high performance for multiclass classification of OSAH using single-lead ECG recordings. The proposed method can be employed in screening of patients suspected of having OSAH. © 2018 Institute of Physics and Engineering in Medicine.

Pulmonary emphysema classification based on an improved texton learning model by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

2013-03-01

In this paper, we present a texture classification method based on texton learned via sparse representation (SR) with new feature histogram maps in the classification of emphysema. First, an overcomplete dictionary of textons is learned via KSVD learning on every class image patches in the training dataset. In this stage, high-pass filter is introduced to exclude patches in smooth area to speed up the dictionary learning process. Second, 3D joint-SR coefficients and intensity histograms of the test images are used for characterizing regions of interest (ROIs) instead of conventional feature histograms constructed from SR coefficients of the test images over the dictionary. Classification is then performed using a classifier with distance as a histogram dissimilarity measure. Four hundreds and seventy annotated ROIs extracted from 14 test subjects, including 6 paraseptal emphysema (PSE) subjects, 5 centrilobular emphysema (CLE) subjects and 3 panlobular emphysema (PLE) subjects, are used to evaluate the effectiveness and robustness of the proposed method. The proposed method is tested on 167 PSE, 240 CLE and 63 PLE ROIs consisting of mild, moderate and severe pulmonary emphysema. The accuracy of the proposed system is around 74%, 88% and 89% for PSE, CLE and PLE, respectively.

Single-accelerometer-based daily physical activity classification.

PubMed

Long, Xi; Yin, Bin; Aarts, Ronald M

2009-01-01

In this study, a single tri-axial accelerometer placed on the waist was used to record the acceleration data for human physical activity classification. The data collection involved 24 subjects performing daily real-life activities in a naturalistic environment without researchers' intervention. For the purpose of assessing customers' daily energy expenditure, walking, running, cycling, driving, and sports were chosen as target activities for classification. This study compared a Bayesian classification with that of a Decision Tree based approach. A Bayes classifier has the advantage to be more extensible, requiring little effort in classifier retraining and software update upon further expansion or modification of the target activities. Principal components analysis was applied to remove the correlation among features and to reduce the feature vector dimension. Experiments using leave-one-subject-out and 10-fold cross validation protocols revealed a classification accuracy of approximately 80%, which was comparable with that obtained by a Decision Tree classifier.

Critical Evaluation of Headache Classifications

PubMed Central

ÖZGE, Aynur

2013-01-01

Transforming a subjective sense like headache into an objective state and establishing a common language for this complaint which can be both a symptom and a disease all by itself have kept the investigators busy for years. Each recommendation proposed has brought along a set of patients who do not meet the criteria. While almost the most ideal and most comprehensive classification studies continued at this point, this time criticisims about withdrawing from daily practice came to the fore. In this article, the classification adventure of scientists who work in the area of headache will be summarized. More specifically, 2 classifications made by the International Headache Society (IHS) and the point reached in relation with the 3rd classification which is still being worked on will be discussed together with headache subtypes. It has been presented with the wish and belief that it will contribute to the readers and young investigators who are interested in this subject. PMID:28360577

Critical Evaluation of Headache Classifications.

PubMed

Özge, Aynur

2013-08-01

Transforming a subjective sense like headache into an objective state and establishing a common language for this complaint which can be both a symptom and a disease all by itself have kept the investigators busy for years. Each recommendation proposed has brought along a set of patients who do not meet the criteria. While almost the most ideal and most comprehensive classification studies continued at this point, this time criticisims about withdrawing from daily practice came to the fore. In this article, the classification adventure of scientists who work in the area of headache will be summarized. More specifically, 2 classifications made by the International Headache Society (IHS) and the point reached in relation with the 3rd classification which is still being worked on will be discussed together with headache subtypes. It has been presented with the wish and belief that it will contribute to the readers and young investigators who are interested in this subject.

From classroom environment to mathematics achievement: The mediating role of self-perceived ability and subject interest.

PubMed

Tosto, Maria G; Asbury, Kathryn; Mazzocco, Michèle M M; Petrill, Stephen A; Kovas, Yulia

2016-08-01

Drawing on Bandura's triadic reciprocal causation model, perceived classroom environment and three intrapersonal factors (mathematics self-efficacy, maths interest and academic self-concept) were considered as predictors of test performance in two correlated mathematics assessments: a public examination (GCSE) and an on-line test, both taken by UK pupils at age 16 (n = 6689). Intrapersonal factors were significantly associated with both test scores, even when the alternative score was taken into account. Classroom environment did not correlate with mathematics achievement once intrapersonal factors and alternative test performance were included in the model, but was associated with subject interest and academic self-concept. Perceptions of classroom environment may exercise an indirect influence on achievement by boosting interest and self-concept. In turn, these intrapersonal factors have direct relationships with achievement and were found to mediate the relationship between perceived classroom environment and maths performance. Findings and their implications for mathematics education are discussed.

76 FR 36095 - Notice of Submission for OMB Review

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-21

..., mathematics, and science literacy. It was first implemented by the National Center for Education Statistics..., mathematics will be the major subject domain. The field test will also include computer-based assessments in...

Working Memory in Students with Mathematical Difficulties

NASA Astrophysics Data System (ADS)

Nur, I. R. D.; Herman, T.; Ningsih, S.

2018-04-01

Learning process is the activities that has important role because this process is one of the all factors that establish students success in learning. oftentimes we find so many students get the difficulties when they study mathematics. This condition is not only because of the outside factor but also it comes from the inside. The purpose of this research is to analyze and give the representation how students working memory happened in physical education students for basic statistics subjects which have mathematical difficulties. The subjects are 4 students which have a mathematical difficulties. The research method is case study and when the describe about students working memory are explanated deeply with naturalistic observation. Based on this research, it was founded that 4 students have a working memory deficit in three components. The components are phonological loop, visuospatial sketchpad, dan episodic buffer.

EEG classification of emotions using emotion-specific brain functional network.

PubMed

Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

Activity recognition in planetary navigation field tests using classification algorithms applied to accelerometer data.

PubMed

Song, Wen; Ade, Carl; Broxterman, Ryan; Barstow, Thomas; Nelson, Thomas; Warren, Steve

2012-01-01

Accelerometer data provide useful information about subject activity in many different application scenarios. For this study, single-accelerometer data were acquired from subjects participating in field tests that mimic tasks that astronauts might encounter in reduced gravity environments. The primary goal of this effort was to apply classification algorithms that could identify these tasks based on features present in their corresponding accelerometer data, where the end goal is to establish methods to unobtrusively gauge subject well-being based on sensors that reside in their local environment. In this initial analysis, six different activities that involve leg movement are classified. The k-Nearest Neighbors (kNN) algorithm was found to be the most effective, with an overall classification success rate of 90.8%.

Amyloid positron emission tomography with (18)F-flutemetamol and structural magnetic resonance imaging in the classification of mild cognitive impairment and Alzheimer's disease.

PubMed

Duara, Ranjan; Loewenstein, David A; Shen, Qian; Barker, Warren; Potter, Elizabeth; Varon, Daniel; Heurlin, Kristen; Vandenberghe, Rik; Buckley, Christopher

2013-05-01

To evaluate the contributions of amyloid-positive (Am+) and medial temporal atrophy-positive (MTA+) scans to the diagnostic classification of prodromal and probable Alzheimer's disease (AD). (18)F-flutemetamol-labeled amyloid positron emission tomography (PET) and magnetic resonance imaging (MRI) were used to classify 10 young normal, 15 elderly normal, 20 amnestic mild cognitive impairment (aMCI), and 27 AD subjects. MTA+ status was determined using a cut point derived from a previous study, and Am+ status was determined using a conservative and liberal cut point. The rates of MRI scans with positive results among young normal, elderly normal, aMCI, and AD subjects were 0%, 20%, 75%, and 82%, respectively. Using conservative cut points, the rates of Am+ scans for these same groups of subjects were 0%, 7%, 50%, and 93%, respectively, with the aMCI group showing the largest discrepancy between Am+ and MTA+ scans. Among aMCI cases, 80% of Am+ subjects were also MTA+, and 70% of amyloid-negative (Am-) subjects were MTA+. The combination of amyloid PET and MTA data was additive, with an overall correct classification rate for aMCI of 86%, when a liberal cut point (standard uptake value ratio = 1.4) was used for amyloid positivity. (18)F-flutemetamol PET and structural MRI provided additive information in the diagnostic classification of aMCI subjects, suggesting an amyloid-independent neurodegenerative component among aMCI subjects in this sample. Copyright © 2013 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Core subjects at the end of primary school: identifying and explaining relative strengths of children with specific language impairment (SLI)

PubMed Central

Durkin, Kevin; Mok, Pearl L H; Conti-Ramsden, Gina

2015-01-01

Background In general, children with specific language impairment (SLI) tend to fall behind their typically developing (TD) peers in educational attainment. Less is known about how children with SLI fare in particular areas of the curriculum and what predicts their levels of performance. Aims To compare the distributions of performance of children with SLI in three core school subjects (English, Mathematics and Science); to test the possibility that performance would vary across the core subjects; and to examine the extent to which language impairment predicts performance. Methods & Procedures This study was conducted in England and reports historical data on educational attainments. Teacher assessment and test scores of 176 eleven-year-old children with SLI were examined in the three core subjects and compared with known national norms. Possible predictors of performance were measured, including language ability at ages 7 and 11, educational placement type, and performance IQ. Outcomes & Results Children with SLI, compared with national norms, were found to be at a disadvantage in core school subjects. Nevertheless, some children attained the levels expected of TD peers. Performance was poorest in English; relative strengths were indicated in Science and, to a lesser extent, in Mathematics. Language skills were significant predictors of performance in all three core subjects. PIQ was the strongest predictor for Mathematics. For Science, both early language skills at 7 years and PIQ made significant contributions. Conclusions & Implications Language impacts on the school performance of children with SLI, but differentially across subjects. English for these children is the most challenging of the core subjects, reflecting the high levels of language demand it incurs. Science is an area of relative strength and mathematics appears to be intermediate, arguably because some tasks in these subjects can be performed with less reliance on verbal processing. Many children with SLI do have the potential to reach or exceed educational targets that are set at national levels for TD children. PMID:25469890

A taxonomy-based approach to shed light on the babel of mathematical analogies for rice simulation

USDA-ARS?s Scientific Manuscript database

For most biophysical domains, different models are available and the extent to which their structures differ with respect to differences in outputs was never quantified. We use a taxonomy-based approach to address the question with thirteen rice models. Classification keys and binary attributes for ...

Undergraduate Research Experiences: Mentoring, Awareness, and Perceptions--A Case Study at a Hispanic-Serving Institution

ERIC Educational Resources Information Center

Rodríguez Amaya, Laura; Betancourt, Tania; Collins, Kristina Henry; Hinojosa, Orlando; Corona, Carlos

2018-01-01

Background: Undergraduate research experiences (UREs) have been proposed as means to increase the retention and engagement of minority--and more specifically Hispanic--college students in science, technology, engineering, and mathematics (STEM) majors. This study explores the impact of student characteristics such as gender, classification,…

MATHEMATICS OF SENSING, EXPLOITATION, AND EXECUTION (MSEE) Sensing, Exploitation, and Execution (SEE) on a Foundation for Representation, Inference, and Learning

DTIC Science & Technology

2016-07-01

reconstruction, video synchronization, multi - view tracking, action recognition, reasoning with uncertainty 16. SECURITY CLASSIFICATION OF: 17...3.4.2. Human action recognition across multi - views ......................................................................................... 44 3.4.3...68 4.2.1. Multi - view Multi -object Tracking with 3D cues

Assessment of functional defecation disorders using anorectal manometry.

PubMed

Seong, Moo-Kyung

2018-06-01

The aim was to evaluate the discriminating accuracy of anorectal manometry (ARM) between nonconstipated (NC) subjects and functionally constipated (FC) subjects, and between FC subjects with and without functional defecation disorder (FDD). Among female patients who visited anorectal physiology unit, those who could be grouped to following categories were included; FC group with FDD (+FDD subgroup), or without FDD (-FDD subgroup) and NC group. ARM was performed and interpreted not only with absolute pressure values, but also pattern classification and quantification of pressure changes in the rectum and anus during attempted defecation. There were 76 subjects in NC group and 75 in FC group. Among FC group, 63 subjects were in -FDD subgroup and 12 in +FDD subgroup. In pattern classification of pressure changes, type 0, as 'normal' response, was only slightly more prevalent in NC group than in FC group. When all 'abnormal' types (types 1-5) were considered together as positive findings, the sensitivity and specificity of pattern classification in diagnosing FC among all subjects were 89.3% and 22.7%. Those values in diagnosing FDD among FC group were 91.7% and 11.1%. Manometric defecation index (MDI) as a quantification parameter was significantly different between -FDD and +FDD subgroups. Other conventional absolute pressures were mostly comparable between the groups. Among all parameters of ARM, MDI was useful to diagnose FDD in FC patients. Other parameters including the pattern classification were questionable in their ability to diagnose FDD.

Assessment of functional defecation disorders using anorectal manometry

PubMed Central

2018-01-01

Purpose The aim was to evaluate the discriminating accuracy of anorectal manometry (ARM) between nonconstipated (NC) subjects and functionally constipated (FC) subjects, and between FC subjects with and without functional defecation disorder (FDD). Methods Among female patients who visited anorectal physiology unit, those who could be grouped to following categories were included; FC group with FDD (+FDD subgroup), or without FDD (−FDD subgroup) and NC group. ARM was performed and interpreted not only with absolute pressure values, but also pattern classification and quantification of pressure changes in the rectum and anus during attempted defecation. Results There were 76 subjects in NC group and 75 in FC group. Among FC group, 63 subjects were in −FDD subgroup and 12 in +FDD subgroup. In pattern classification of pressure changes, type 0, as ‘normal’ response, was only slightly more prevalent in NC group than in FC group. When all ‘abnormal’ types (types 1–5) were considered together as positive findings, the sensitivity and specificity of pattern classification in diagnosing FC among all subjects were 89.3% and 22.7%. Those values in diagnosing FDD among FC group were 91.7% and 11.1%. Manometric defecation index (MDI) as a quantification parameter was significantly different between −FDD and +FDD subgroups. Other conventional absolute pressures were mostly comparable between the groups. Conclusion Among all parameters of ARM, MDI was useful to diagnose FDD in FC patients. Other parameters including the pattern classification were questionable in their ability to diagnose FDD. PMID:29854711

A mathematical model of neuro-fuzzy approximation in image classification

NASA Astrophysics Data System (ADS)

Gopalan, Sasi; Pinto, Linu; Sheela, C.; Arun Kumar M., N.

2016-06-01

Image digitization and explosion of World Wide Web has made traditional search for image, an inefficient method for retrieval of required grassland image data from large database. For a given input query image Content-Based Image Retrieval (CBIR) system retrieves the similar images from a large database. Advances in technology has increased the use of grassland image data in diverse areas such has agriculture, art galleries, education, industry etc. In all the above mentioned diverse areas it is necessary to retrieve grassland image data efficiently from a large database to perform an assigned task and to make a suitable decision. A CBIR system based on grassland image properties and it uses the aid of a feed-forward back propagation neural network for an effective image retrieval is proposed in this paper. Fuzzy Memberships plays an important role in the input space of the proposed system which leads to a combined neural fuzzy approximation in image classification. The CBIR system with mathematical model in the proposed work gives more clarity about fuzzy-neuro approximation and the convergence of the image features in a grassland image.

The Impact of Problem-Based Learning Approach to Senior High School Students' Mathematics Critical Thinking Ability

ERIC Educational Resources Information Center

Widyatiningtyas, Reviandari; Kusumah, Yaya S.; Sumarmo, Utari; Sabandar, Jozua

2015-01-01

The study reported the findings of an only post-test control group research design and aims to analyze the influence of problem-based learning approach, school level, and students' prior mathematical ability to student's mathematics critical thinking ability. The research subjects were 140 grade ten senior high school students coming from…

The Impact of Tier 2 Mathematics Instruction on Second Graders with Mathematics Difficulties

ERIC Educational Resources Information Center

Dennis, Minyi Shih; Bryant, Brian R.; Drogan, Robin

2015-01-01

Although research on Tier 2 interventions for early mathematics is accumulating, such efforts remain far behind those for reading, especially regarding specific features such as the ideal time to begin an intervention. The present study investigated the effectiveness of a Tier 2 intervention using a single subject multiple baseline, across-groups…

Interest in Mathematics = Interest in Mathematics? What General Measures of Interest Reflect When the Object of Interest Changes

ERIC Educational Resources Information Center

Ufer, Stefan; Rach, Stefanie; Kosiol, Timo

2017-01-01

Students' motivational characteristics, e.g., subject-related interest, are considered important predictors for successful learning processes. However, few empirical studies provide evidence for the assumed chain of effects between high interest and high achievement in mathematics. One reason for this result might be that the applied measures of…

Some Applications of Mathematics for the Biology Classroom

ERIC Educational Resources Information Center

Horton, Robert M.; Leonard, William H.

2013-01-01

Biology and mathematics are inextricably linked. In this article, we show a few of the many areas in which this linkage might be made explicit. By doing so, teachers can deepen students' understanding and appreciation of both subjects. In this article, we explore some of these areas, providing brief explanations of the mathematics and some of the…

ESL through Content-Area Instruction: Mathematics, Science, Social Studies. Language in Education: Theory and Practice, No. 69.

ERIC Educational Resources Information Center

Crandall, JoAnn, Ed.; And Others

Three essays focus on integrating subject matter and the English used to communicate it as a technique for teaching limited-English-proficient students. "Integrating Language and Mathematics Learning," by Theresa Corasaniti Dale and Gilberto J. Cuevas, discusses the vocabulary, syntax, semantics, and discourse features of mathematics;…

International Comparisons of Foundation Phase Number Domain Mathematics Knowledge and Practice Standards

ERIC Educational Resources Information Center

Human, Anja; van der Walt, Marthie; Posthuma, Barbara

2015-01-01

Poor mathematics performance in schools is both a national and an international concern. Teachers ought to be equipped with relevant subject matter knowledge and pedagogical content knowledge as one way to address this problem. However, no mathematics knowledge and practice standards have as yet been defined for the preparation of Foundation Phase…

The Prevalent Rate of Problem-Solving Approach in Teaching Mathematics in Ghanaian Basic Schools

ERIC Educational Resources Information Center

Nyala, Joseph; Assuah, Charles; Ayebo, Abraham; Tse, Newel

2016-01-01

Stakeholders of mathematics education decry the rate at which students' performance are falling below expectation; they call for a shift to practical methods of teaching the subject in Ghanaian basic schools. The study explores the extent to which Ghanaian basic school mathematics teachers use problem-solving approach in their lessons. The…

Enhancing Student Engagement to Positively Impact Mathematics Anxiety, Confidence and Achievement for Interdisciplinary Science Subjects

ERIC Educational Resources Information Center

Everingham, Yvette L.; Gyuris, Emma; Connolly, Sean R.

2017-01-01

Contemporary science educators must equip their students with the knowledge and practical know-how to connect multiple disciplines like mathematics, computing and the natural sciences to gain a richer and deeper understanding of a scientific problem. However, many biology and earth science students are prejudiced against mathematics due to…

Influence of Instructional Practices on Secondary School Students' Achievement in Mathematics

ERIC Educational Resources Information Center

Nandwa, Odhiambo Marble; Wasike, Duncan Wekesa; Wanjala, Toili William

2015-01-01

Mathematics is a key subject which students cannot avoid if they have to lead a bright future. Despite the introduction and implementation of different teaching methods and strategies suggested by researchers the achievement of students in mathematics at school level has persistently been poor, hence the need to explore the influence of different…

Influence of Gender, Single-Sex and Co-Educational Schooling on Students' Enjoyment and Achievement in Mathematics

ERIC Educational Resources Information Center

Prendergast, Mark; O'Donoghue, John

2014-01-01

This research investigates the influence that gender, single-sex and co-educational schooling can have on students' mathematics education in second-level Irish classrooms. Although gender differences in mathematics education have been the subject of research for many years, recent results from PISA (Programme for International Student Assessment)…

Test Anxiety in Mathematics among Early Undergraduate Students in a British University in Malaysia

ERIC Educational Resources Information Center

Karjanto, Natanael; Yong, Su Ting

2013-01-01

The level of test anxiety in mathematics subjects among early undergraduate students at the University of Nottingham Malaysia Campus is studied in this article. The sample consists of 206 students taking several mathematics modules who completed the questionnaires on test anxiety just before they entered the venue for midterm examinations. The…

Using a Managerial Analogy for Making Mathematics More Attractive

ERIC Educational Resources Information Center

Hvorecký, Jozef

2010-01-01

In many countries, Mathematics is among the least popular school subjects. Educators are spending a lot of time in searching methods that could change this unfortunate situation. The author, a lecturer at a School of Management, discusses the issue as a managerial problem. First, the popularity of mathematics is analyzed as a marketing problem.…

Using Science to Promote Preservice Teacher Understanding of Problem Solving in Mathematics

ERIC Educational Resources Information Center

Tobias, Jennifer M.; Ortiz, Enrique

2007-01-01

Preservice elementary teachers need to be given the experiences of integrating mathematics with other subjects. They need to go into the classroom with the understanding that mathematics is not an isolated topic. This article describes a paper airplane activity that was presented in a class of preservice elementary education teachers to show how…

Modelling the Intention to Use Technology for Teaching Mathematics among Pre-Service Teachers in Serbia

ERIC Educational Resources Information Center

Teo, Timothy; Milutinovic, Verica

2015-01-01

This study aims to examine the variables that influence Serbian pre-service teachers' intention to use technology to teach mathematics. Using the technology acceptance model (TAM) as the framework, we developed a research model to include subjective norm, knowledge of mathematics, and facilitating conditions as external variables to the TAM. In…

Teacher Beliefs toward Using Alternative Teaching Approaches in Science and Mathematics Classes Related to Experience in Teaching

ERIC Educational Resources Information Center

Isiksal-Bostan, Mine; Sahin, Elvan; Ertepinar, Hamide

2015-01-01

The purpose of this study was to examine the relationships among Turkish classroom, science and mathematics teachers' beliefs toward using inquiry-based approaches, traditional teaching approaches, and technology in their mathematics and science classrooms; their efficacy beliefs in teaching those subjects; and years of experience in teaching in…

Ask Marilyn in the Mathematics Classroom: Probability Questions

ERIC Educational Resources Information Center

Vasko, Francis J.

2012-01-01

Since 1986, Marilyn Vos Savant, who is listed in the "Guinness Book of World Records Hall of Fame" for the highest IQ, has had a weekly column that is published in "Parade Magazine." In this column, she answers readers' questions on a wide variety of subjects including mathematics and particularly probability. Many of the mathematically oriented…

Understanding and Supporting Teacher Horizon Knowledge around Limits: A Framework for Evaluating Textbooks for Teachers

ERIC Educational Resources Information Center

Kajander, Ann; Lovric, Miroslav

2017-01-01

As part of recent scrutiny of teacher capacity, the question of teachers' content knowledge of higher level mathematics emerges as important to the field of mathematics education. Elementary teachers in North America and some other countries tend to be subject generalists, yet it appears that some higher level mathematics background may be…

An Archaeological/Genealogical Historical Analysis of The National Council of Teachers of Mathematics' Standards Documents

ERIC Educational Resources Information Center

Bullock, Erika Catherine

2013-01-01

Since the mid-20th century in the United States, there have been several reform movements within mathematics education; each movement has been subject to its own unique socio-cultural and -political forces. The National Council of Teachers of Mathematics' (NCTM) Standards documents--"Curriculum and Evaluation Standards for School…

Readin', Writin', an' 'Rithmetic: Literacy Strategies in High School Mathematics

ERIC Educational Resources Information Center

Principato, Angela M.

2017-01-01

Stagnant growth on national standardized tests in mathematics and reading and a focus on disciplinary literacy in the Common Core State Standards in ELA, history/social studies, science, and technical subjects has prompted a resurgence in utilizing literacy strategies in the content areas in high school. While literacy standards in mathematics are…

Implications from the Beginning Teacher Evaluation Study for the IEA Second Mathematics Study.

ERIC Educational Resources Information Center

Burstein, Leigh

The International Education Association plans for the Second Mathematics Study are deemed inadequate for the identification of the effects of instruction on mathematics education. Suggested modifications are based on the results of two studies. The first is a discussion of major methodological limitations of the Six Subjects Survey. The second is…

Kaspar Schott's "encyclopedia of all mathematical sciences"

PubMed

Knobloch, Eberhard

2011-06-01

In 1661, Kaspar Schott published his comprehensive textbook "Cursus mathematicus" in Würzburg for the first time, his "Encyclopedia of all mathematical sciences". It was so successful that it was published again in 1674 and 1677. In its 28 books, Schott gave an introduction for beginners in 22 mathematical disciplines by means of 533 figures and numerous tables. He wanted to avoid the shortness and the unintelligibility of his predecessors Alsted and Hérigone. He cited or recommended far more than hundred authors, among them Protestants like Michael Stifel and Johannes Kepler, but also Catholics like Nicolaus Copernicus. The paper gives a survey of this work and explains especially interesting aspects: The dedication to the German emperor Leopold I., Athanasius Kircher's letter of recommendation as well as Schott's classification of sciences, explanations regarding geometry, astronomy, and algebra.

A Study of Hierarchical Classification in Concrete and Formal Thought.

ERIC Educational Resources Information Center

Lowell, Walter E.

This researcher investigated the relationship of hierarchical classification processes in subjects categorized as to developmental level as defined by Piaget's theory, and explored the validity of the hierarchical model and test used in the study. A hierarchical classification test and a battery of four Piaget-type tasks were administered…

Hyaluronic Acid and Hyaluronidase in Prostate Cancer: Evaluation of Their Therapeutic and Prognostic Potential

DTIC Science & Technology

2005-01-01

PAGES No subject terms provided. 75 16. PRICE CODE 17. SECURITY CLASSIFICATION 18 . SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF...Prescribed by ANSI Std. Z39- 18 298-102 Lokeshwar, Vinata B Table of Contents Cover...1 Body ................................................................................................. 2- 18 Key Research

IFLA General Conference, 1984. Bibliographic Control Division. Sections on Bibliography, Cataloging, and Classification. Part 1. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations, The Hague (Netherlands).

Papers on bibliography, cataloging, and classification presented at the 1984 IFLA general conference include: (1) "Bibliographic Control: Zimbabwe's Present Practices and Hopes for the Future" (Angeline S. Kamba, Zimbabwe); (2) "Classification and Subject Cataloguing in Kenya" (Margaret N. Muriuki, Kenya); (3)…

Single-trial classification of motor imagery differing in task complexity: a functional near-infrared spectroscopy study

PubMed Central

2011-01-01

Background For brain computer interfaces (BCIs), which may be valuable in neurorehabilitation, brain signals derived from mental activation can be monitored by non-invasive methods, such as functional near-infrared spectroscopy (fNIRS). Single-trial classification is important for this purpose and this was the aim of the presented study. In particular, we aimed to investigate a combined approach: 1) offline single-trial classification of brain signals derived from a novel wireless fNIRS instrument; 2) to use motor imagery (MI) as mental task thereby discriminating between MI signals in response to different tasks complexities, i.e. simple and complex MI tasks. Methods 12 subjects were asked to imagine either a simple finger-tapping task using their right thumb or a complex sequential finger-tapping task using all fingers of their right hand. fNIRS was recorded over secondary motor areas of the contralateral hemisphere. Using Fisher's linear discriminant analysis (FLDA) and cross validation, we selected for each subject a best-performing feature combination consisting of 1) one out of three channel, 2) an analysis time interval ranging from 5-15 s after stimulation onset and 3) up to four Δ[O2Hb] signal features (Δ[O2Hb] mean signal amplitudes, variance, skewness and kurtosis). Results The results of our single-trial classification showed that using the simple combination set of channels, time intervals and up to four Δ[O2Hb] signal features comprising Δ[O2Hb] mean signal amplitudes, variance, skewness and kurtosis, it was possible to discriminate single-trials of MI tasks differing in complexity, i.e. simple versus complex tasks (inter-task paired t-test p ≤ 0.001), over secondary motor areas with an average classification accuracy of 81%. Conclusions Although the classification accuracies look promising they are nevertheless subject of considerable subject-to-subject variability. In the discussion we address each of these aspects, their limitations for future approaches in single-trial classification and their relevance for neurorehabilitation. PMID:21682906

Power System Transient Stability Based on Data Mining Theory

NASA Astrophysics Data System (ADS)

Cui, Zhen; Shi, Jia; Wu, Runsheng; Lu, Dan; Cui, Mingde

2018-01-01

In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Teaching Mathematics to Civil Engineers

ERIC Educational Resources Information Center

Sharp, J. J.; Moore, E.

1977-01-01

This paper outlines a technique for teaching a rigorous course in calculus and differential equations which stresses applicability of the mathematics to problems in civil engineering. The method involves integration of subject matter and team teaching. (SD)

75 FR 39922 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-13

...' capabilities in reading, mathematics, and science literacy. It was first implemented by the National Center for... study clearance in 2012. As in 2003, in PISA 2012, mathematics will be the major subject domain. The...

User intent prediction with a scaled conjugate gradient trained artificial neural network for lower limb amputees using a powered prosthesis.

PubMed

Woodward, Richard B; Spanias, John A; Hargrove, Levi J

2016-08-01

Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming. By using subject independent datasets, whereby a unique subject is tested against a pooled dataset of other subjects, we believe subject training time can be reduced while still achieving an accurate classification. We present here an intent recognition system using an artificial neural network (ANN) with a scaled conjugate gradient learning algorithm to classify gait intention with user-dependent and independent datasets for six unilateral lower limb amputees. We compare these results against a linear discriminant analysis (LDA) classifier. The ANN was found to have significantly lower classification error (P<;0.05) than LDA with all user-dependent step-types, as well as transitional steps for user-independent datasets. Both types of classifiers are capable of making fast decisions; 1.29 and 2.83 ms for the LDA and ANN respectively. These results suggest that ANNs can provide suitable and accurate offline classification in prosthesis gait prediction.

A cautionary note on the use of the Analysis of Covariance (ANCOVA) in classification designs with and without within-subject factors

PubMed Central

Schneider, Bruce A.; Avivi-Reich, Meital; Mozuraitis, Mindaugas

2015-01-01

A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, it is not generally recognized that serious problems of interpretation can arise when the design contains comparisons of participants sampled from different populations (classification designs). Designs that include a comparison of younger and older adults, or a comparison of musicians and non-musicians are examples of classification designs. In such cases, estimates of differences among groups can be contaminated by differences in the covariate population means across groups. A second problem of interpretation will arise if the experimenter fails to center the covariate measures (subtracting the mean covariate score from each covariate score) whenever the design contains within-subject factors. Unless the covariate measures on the participants are centered, estimates of within-subject factors are distorted, and significant increases in Type I error rates, and/or losses in power can occur when evaluating the effects of within-subject factors. This paper: (1) alerts potential users of ANCOVA of the need to center the covariate measures when the design contains within-subject factors, and (2) indicates how they can avoid biases when one cannot assume that the expected value of the covariate measure is the same for all of the groups in a classification design. PMID:25954230

Effect of synergetic implementation of inquiry activities across three subjects in comparison to more traditional approach to teaching

NASA Astrophysics Data System (ADS)

Balogová, Brigita; Ješková, Zuzana; Hančová, Martina; Kireš, Marián

2017-01-01

Science education standards for grammar schools (ISCED 3) urge more emphasis on students' investigations in order to develop understanding but also scientific process skills (inquiry skills). It is true for not only science, but also mathematics and informatics. This approach is promoted to increase scientific literacy and inquiry skills development, however, there has not been many studies carried out in Slovakia to show the effect on students' achievements. In cooperation with Institutes of mathematics and informatics there was a research designed in order to study the effect of synergetic implementation of inquiry activities across the three subjects of physics, mathematics and informatics. The effect was identified with the help of inquiry skills' test and results were compared to those achieved by students subjected to more traditional teaching. In the contribution there are results of the study analyzed and discussed in details.

Six to Ten Digits Multiplication Fun Learning Using Puppet Prototype

NASA Astrophysics Data System (ADS)

Islamiah Rosli, D.'oria; Ali, Azita; Peng, Lim Soo; Sujardi, Imam; Usodo, Budi; Adie Perdana, Fengky

2017-01-01

Logic and technical subjects require students to understand basic knowledge in mathematic. For instance, addition, minus, division and multiplication operations need to be mastered by students due to mathematic complexity as the learning mathematic grows higher. Weak foundation in mathematic also contribute to high failure rate in mathematic subjects in schools. In fact, students in primary schools are struggling to learn mathematic because they need to memorize formulas, multiplication or division operations. To date, this study will develop a puppet prototyping for learning mathematic for six to ten digits multiplication. Ten participants involved in the process of developing the prototype in this study. Students involved in the study were those from the intermediate class students whilst teachers were selected based on their vast knowledge and experiences and have more than five years of experience in teaching mathematic. Close participatory analysis will be used in the prototyping process as to fulfil the requirements of the students and teachers whom will use the puppet in learning six to ten digit multiplication in mathematic. Findings showed that, the students had a great time and fun learning experience in learning multiplication and they able to understand the concept of multiplication using puppet. Colour and materials of the puppet also help to attract student attention during learning. Additionally, students able to visualized and able to calculate accurate multiplication value and the puppet help them to recall in multiplying and adding the digits accordingly.

40 CFR 152.166 - Labeling of restricted use products.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152... formulation into other pesticide products) is not subject to the labeling requirements of this subpart. ...

40 CFR 152.166 - Labeling of restricted use products.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152... formulation into other pesticide products) is not subject to the labeling requirements of this subpart. ...

40 CFR 152.166 - Labeling of restricted use products.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152... formulation into other pesticide products) is not subject to the labeling requirements of this subpart. ...

40 CFR 152.166 - Labeling of restricted use products.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152... formulation into other pesticide products) is not subject to the labeling requirements of this subpart. ...

40 CFR 152.166 - Labeling of restricted use products.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152... formulation into other pesticide products) is not subject to the labeling requirements of this subpart. ...

Low-back electromyography (EMG) data-driven load classification for dynamic lifting tasks

PubMed Central

Ojeda, Lauro; Johnson, Daniel D.; Gates, Deanna; Mower Provost, Emily; Barton, Kira

2018-01-01

Objective Numerous devices have been designed to support the back during lifting tasks. To improve the utility of such devices, this research explores the use of preparatory muscle activity to classify muscle loading and initiate appropriate device activation. The goal of this study was to determine the earliest time window that enabled accurate load classification during a dynamic lifting task. Methods Nine subjects performed thirty symmetrical lifts, split evenly across three weight conditions (no-weight, 10-lbs and 24-lbs), while low-back muscle activity data was collected. Seven descriptive statistics features were extracted from 100 ms windows of data. A multinomial logistic regression (MLR) classifier was trained and tested, employing leave-one subject out cross-validation, to classify lifted load values. Dimensionality reduction was achieved through feature cross-correlation analysis and greedy feedforward selection. The time of full load support by the subject was defined as load-onset. Results Regions of highest average classification accuracy started at 200 ms before until 200 ms after load-onset with average accuracies ranging from 80% (±10%) to 81% (±7%). The average recall for each class ranged from 69–92%. Conclusion These inter-subject classification results indicate that preparatory muscle activity can be leveraged to identify the intent to lift a weight up to 100 ms prior to load-onset. The high accuracies shown indicate the potential to utilize intent classification for assistive device applications. Significance Active assistive devices, e.g. exoskeletons, could prevent back injury by off-loading low-back muscles. Early intent classification allows more time for actuators to respond and integrate seamlessly with the user. PMID:29447252

Machine processing of remotely sensed data; Proceedings of the Conference, Purdue University, West Lafayette, Ind., October 16-18, 1973

NASA Technical Reports Server (NTRS)

1973-01-01

Topics discussed include the management and processing of earth resources information, special-purpose processors for the machine processing of remotely sensed data, digital image registration by a mathematical programming technique, the use of remote-sensor data in land classification (in particular, the use of ERTS-1 multispectral scanning data), the use of remote-sensor data in geometrical transformations and mapping, earth resource measurement with the aid of ERTS-1 multispectral scanning data, the use of remote-sensor data in the classification of turbidity levels in coastal zones and in the identification of ecological anomalies, the problem of feature selection and the classification of objects in multispectral images, the estimation of proportions of certain categories of objects, and a number of special systems and techniques. Individual items are announced in this issue.

Functional Thinking Profile of Junior High School Student in Solving Mathematical Problem Observed by Differences of Sex

NASA Astrophysics Data System (ADS)

Siregar, A. P.; Juniati, D.; Sulaiman, R.

2018-01-01

This study involving 2 grade VIII students was taken place in SMPK Anak Bangsa Surabaya. Subjects were selected using equal mathematics ability criteria. Data was collected using provision of problem-solving tasks and followed by a task-based interview. Obtained data was analysed through the following steps, which are data reduction, data presentation, and conclusions. Meanwhile, to obtain a valid data, in this study, researchers used data triangulation. The results indicated that in the problem number 1 about identifying patterns, the subjects of male and female show a tendency of similarities in stating what is known and asked the question. However, the male students provided a more specific answer in explaining the magnitude of the difference between the first quantity and the increased differences in the other quantities. Related the activities in determining the relationship between two quantities, male subjects and women subject tended to have similarities in the sense of using trial and error on existing mathematical operations. It can be concluded that the functional way of thinking both subjects is relatively identic. Nevertheless, the male subject showed the more specific answer in finding the difference between the two quantities and finding the correspondence relationship between the quantities.