337 research outputs found

    Investigation of Jordanian pre-service teachers' beliefs about learning and teaching of mathematics

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    Title from PDF of title page, viewed on July 26th, 2013Dissertation advisor: Rita BargerVitaIncludes bibliographic references (pages 105-112)Thesis (Ph.D.)--School of Education and School of Computing and Engineering. University of Missouri--Kansas City, 2013This study investigated Jordanian pre-service teachers' beliefs about the learning and teaching of mathematics. One aim of the study was to identify possible explanations for why Jordanian students score much lower than many of their global counterparts on international mathematics tests. On the 2007 Trends in International Mathematics and Science Study (TIMSS), Jordanian eighth-graders' average score was 427, far below the TIMSS scale average of 500. Jordan ranked 31st out of the 48 participating countries. On the 2011 TIMSS, Jordanian eighth-graders' average dropped to 406, and Jordan's overall ranking was 49th out of 56 participating countries and education systems. In addition to investigating Jordanian pre-service teachers' beliefs, the findings were compared to the findings from a similar study in South Korea (Kim, 2009), the top performing country in mathematics in 2011 and second overall in 2007 on the TIMSS assessments. The participants in this study were 441 pre-service teachers enrolled in 5 universities in Jordan, four public and one private. Participants' data were collected using a questionnaire survey, the same instrument that was used in the Korean study of 2009. Nearly 95% of the Jordanian participants believed in the existence of a mathematical mind indicating that they view mathematics ability as fixed or stable. Other strong beliefs were about the importance of memorization, gender, and mathematics ability. Specifically, 65% of the participants believed that the best way to learn mathematics was to memorize all the formulas, and nearly 70% believed that math ability was not associated with a specific gender. The comparison between Jordanian and Korean pre-service teachers produced significant results about the necessity for memorization and the belief in multiple methods for doing mathematics. Jordanian pre-service teachers believed strongly in the need to memorize in mathematics and in the existence of a single correct way to do mathematics. These are beliefs are not held by Korean pre-service teachers.Introduction -- Review of literature -- Methodology -- Results -- Discussion -- Appendix A. Mathematics beliefs instrument -- Appendix B. Background information instrument -- Appendix C. Yarmouk University results on mathematics belief instrument -- Appendix D. Mu'Tah University results on mathematics beliefs instrument -- Appendix E. Al-Bayt University results on mathematics beliefs instrument -- Appendix F. Jordan University results on mathematics beliefs instrument -- Appendix G. Jadara University results on mathematics beliefs instrument -- Appendix H. Researchers and researched belief

    A New Multi-threaded and Interleaving Approach to Enhance String Matching for Intrusion Detection Systems

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    String matching algorithms are computationally intensive operations in computer science. The algorithms find the occurrences of one or more strings patterns in a larger string or text. String matching algorithms are important for network security, biomedical applications, Web search, and social networks. Nowadays, the high network speeds and large storage capacity put a high requirement on string matching methods to perform the task in a short time. Traditionally, Aho-Corasick algorithm, which is used to find the string matches, is executed sequentially. In this paper, a new multi-threaded and interleaving approach of Aho-Corasick using graphics processing units (GPUs) is designed and implemented to achieve high-speed string matching. Compute Unified Device Architecture (CUDA) programming language is used to implement the proposed parallel version. Experimental results show that our approach achieves more than 5X speedup over the sequential and other parallel implementations. Hence, a wide range of applications can benefit from our solution to perform string matching faster than ever before

    A Mathematical Framework for Agent Based Models of Complex Biological Networks

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    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis.Comment: To appear in Bulletin of Mathematical Biolog

    In Defence of Absolutes: The Evolution of Aphra Behns Political Views

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    The evolution of Aphra Behns political views is a point of scholarly contention. The analysis of her dramatic works starts with her early tragicomedies, like The Young King and The Amorous Prince, and continues through her well- known Exclusion Crisiss sexual comedies, like The Roundheads and Sir Patient Fancy. This paper argues that Behns on- stage royalism was considerably diverse, reflecting various degrees of support for the monarchy. Behn altered her political positions in response to the development of the fierce rivalry between different political parties. Following her concerns and discontent about the kings ability to rule the country in her early plays, Behn developed a remarkable tendency for supporting Charles II and created an image of an impeccable king beyond any criticism. The results suggest that Behn’s Toryism did not reflect an unwavering and unchanging support for the newly restored monarchy, as was assumed previously

    Protein contact map prediction using multi-stage hybrid intelligence inference systems

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    AbstractProteins are one of the most important molecules in organisms. Protein function can be inferred from its 3D structure. The gap between the number of discovered protein sequences and the number of structures determined by the experimental methods is increasing. Accurate prediction of protein contact map is an important step toward the reconstruction of the protein’s 3D structure. In spite of continuous progress in developing contact map predictors, highly accurate prediction is still unresolved problem. In this paper, we introduce a new predictor, JUSTcon, which consists of multiple parallel stages that are based on adaptive neuro-fuzzy inference System (ANFIS) and K nearest neighbors (KNNs) classifier. A smart filtering operation is performed on the final outputs to ensure normal connectivity behaviors of amino acids pairs. The window size of the filter is selected by a simple expert system. The dataset was divided into testing dataset of 50 proteins and training dataset of 450 proteins. The system produced an average accuracy of 45.2% for the sequence separation of six amino acids. In addition, JUSTcon outperformed SVMcon and PROFcon predictors in the cases of large separation distances. JUSTcon produced an average accuracy of 15% for the sequence separation of 24 amino acids after applying it on CASP9 targets

    Experimental study on bendway weirs

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    River morphodynamics and sediment transportBank erosion and protectio

    Using Bayesian Networks to Provide Educational Implications: Mobile Learning and Ethnomathematics to Improve Sustainability in Mathematics Education

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    There are many Western apps that help students strengthen their mathematics skills through learning and game apps. A research project was designed to create an IOS Math App to provide Grade 6 Emirati students with the opportunity to explore mathematics, then, using Bayesian Networks, to examine the educational implications. The learning app was developed using ethnomathematics modules based on the Emirati culture. Students were required to navigate through several modules to examine various mathematical concepts in algebra and geometry. The survey was written for Grade 6 English language learners. Based on the Bayesian Networks, the findings suggested that if students are allowed to explore mathematics based on familiar cultural norms and practices, students with grades A and C would get higher grades. However, if students are not allowed to explore mathematics in line with their local culture, more students would receive an F grade, while some students with an A grade would get lower grades. Additionally, the findings showed that incorporating cultural elements had a positive change in students’ liking and learning mathematics, even without a mobile device. However, not allowing a mobile device and not allowing culture had an increased negative impact on students’ liking and learning mathematics. The last finding suggested that students valued ethnomathematics examples over a mobile device to learn mathematics. The research findings could help to improve sustainability in mathematics education by promoting ethnomathematics and mobile learning

    A recurrent neural network and a discrete wavelet transform to predict the Saudi stock price trends

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    Stock markets can be characterised as being complex, dynamic and chaotic environments, making the prediction of stock prices very tough. In this research work, we attempt to predict the Saudi stock price trends with regards to its earlier price history by combining a discrete wavelet transform (DWT) and a recurrent neural network (RNN). The DWT technique helped to remove the noises pertaining to the data gathered from the Saudi stock market based on a few chosen samples of companies. Then, a designed RNN has trained via the Back Propagation Through Time (BPTT) method to aid in predicting the Saudi market's stock prices for the next seven days' closing price pertaining to the chosen sample of companies. Then, analysis of the obtained results was carried out to make a comparison with the results from those employing the traditional prediction algorithms like the auto regressive integrated moving average (ARIMA). Based on the comparison, it was found that the put forward method (DWT+RNN) allowed more accurate prediction of the day's closing price versus the ARIMA method employing the mean squared error (MSE), mean absolute error (MAE) and root mean squared error (RMSE) criterion

    Parallel Implementation of Systolic Array Design for Developing Medical Image Rotation

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    Many image-processing algorithms are particularly suited to parallel computing, as they process images that are difficult and time consuming to analyse. In particular, medical images of tissues tend to be very complex with great irregularity and variability in shapes. Furthermore, existing algorithms contain explicit parallelism, which can be efficiently exploited by processing arrays. A good example of an image processing operation is the geometric rotation of a rectangular bitmap. This paper presents a set of systolic array designs for implementing the geometric rotation algorithms of images on VLSI processing arrays. The examined algorithm performs a trigonometric transformation on each pixel in an image.  The design is implemented as a distributed computing system of networked computers using Parallel Virtual Machine (PVM) model. Each node (computer) in the network takes part in the task in hand – such as image processing – using message passing. Comments and conclusions about the implementation of the design as a distributed computing system are discussed. Keywords: parallel computing, distributed computing. PVM, image rotation, systolic array
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