Modeling as a bridge between real world problems and school mathematics

This article argues for an interdisciplinary approach to mathematical problem solving at the elementary school, one that draws upon the engineering domain. A modeling approach, using engineering model eliciting activities, might provide a rich source of meaningful situations that capitalize on and extend students’ existing mathematical learning. The study reports on the developments of 48 twelve-year old students who worked on the Bridge Design activity. Results revealed that young students, even before formal instruction, have the capacity to deal with complex interdisciplinary problems. A number of students created quite appropriate models by developing the necessary mathematical constructs to solve the problem. Students’ difficulties in mathematizing the problem, and in revising and documenting their models are presented and analysed, followed by a discussion on the appropriateness of a modeling approach as a means for introducing complex problems to elementary school students.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

Porohyperelastic analysis to explore mechanical properties of chondrocytes using numerical modeling and experiments : a finite element study

There are many continuum mechanical models have been developed such as liquid drop models, solid models, and so on for single living cell biomechanics studies. However, these models do not give a fully approach to exhibit a clear understanding of the behaviour of single living cells such as swelling behaviour, drag effect, etc. Hence, the porohyperelastic (PHE) model which can capture those aspects would be a good candidature to study cells behaviour (e.g. chondrocytes in this study). In this research, an FEM model of single chondrocyte cell will be developed by using this PHE model to simulate Atomic Force Microscopy (AFM) experimental results with the variation of strain rate. This material model will be compared with viscoelastic model to demonstrate the advantages of PHE model. The results have shown that the maximum value of force applied of PHE model is lower at lower strain rates. This is because the mobile fluid does not have enough time to exude in case of very high strain rate and also due to the lower permeability of the membrane than that of the protoplasm of chondrocyte. This behavior is barely observed in viscoelastic model. Thus, PHE model is the better model for cell biomechanics studies.

Design and modeling of collaboration architecture for security

Threats against computer networks evolve very fast and require more and more complex measures. We argue that teams respectively groups with a common purpose for intrusion detection and prevention improve the measures against rapid propagating attacks similar to the concept of teams solving complex tasks known from field of work sociology. Collaboration in this sense is not easy task especially for heterarchical environments. We propose CIMD (collaborative intrusion and malware detection) as a security overlay framework to enable cooperative intrusion detection approaches. Objectives and associated interests are used to create detection groups for exchange of security-related data. In this work, we contribute a tree-oriented data model for device representation in the scope of security. We introduce an algorithm for the formation of detection groups, show realization strategies for the system and conduct vulnerability analysis. We evaluate the benefit of CIMD by simulation and probabilistic analysis.

Modeling destination brand equity in an emerging long haul market

The destination branding literature emerged as recently as 1998, and there remains a dearth of empirical data that tests the effectiveness of brand campaigns over time. This paper reports the results of an investigation into consumer-based brand equity for Australia as a long haul destination in an emerging South American market. In spite of the high level of academic interest in the measurement of perceptions of destinations since the 1970s, few previous studies have examined perceptions held by South American consumers. Findings suggest that destination brand awareness, brand image, and brand value are positively related to brand loyalty for a long-haul destination. The results also indicate that Australia is a more compelling destination brand for previous visitors compared to non-visitors.

Modeling as a means for making powerful ideas accessible to children at an early age

The SimCalc Vision and Contributions Advances in Mathematics Education 2013, pp 419-436 Modeling as a Means for Making Powerful Ideas Accessible to Children at an Early Age Richard Lesh, Lyn English, Serife Sevis, Chanda Riggs … show all 4 hide » Look Inside » Get Access Abstract In modern societies in the 21st century, significant changes have been occurring in the kinds of “mathematical thinking” that are needed outside of school. Even in the case of primary school children (grades K-2), children not only encounter situations where numbers refer to sets of discrete objects that can be counted. Numbers also are used to describe situations that involve continuous quantities (inches, feet, pounds, etc.), signed quantities, quantities that have both magnitude and direction, locations (coordinates, or ordinal quantities), transformations (actions), accumulating quantities, continually changing quantities, and other kinds of mathematical objects. Furthermore, if we ask, what kind of situations can children use numbers to describe? rather than restricting attention to situations where children should be able to calculate correctly, then this study shows that average ability children in grades K-2 are (and need to be) able to productively mathematize situations that involve far more than simple counts. Similarly, whereas nearly the entire K-16 mathematics curriculum is restricted to situations that can be mathematized using a single input-output rule going in one direction, even the lives of primary school children are filled with situations that involve several interacting actions—and which involve feedback loops, second-order effects, and issues such as maximization, minimization, or stabilizations (which, many years ago, needed to be postponed until students had been introduced to calculus). …This brief paper demonstrates that, if children’s stories are used to introduce simulations of “real life” problem solving situations, then average ability primary school children are quite capable of dealing productively with 60-minute problems that involve (a) many kinds of quantities in addition to “counts,” (b) integrated collections of concepts associated with a variety of textbook topic areas, (c) interactions among several different actors, and (d) issues such as maximization, minimization, and stabilization.

Proteomic and bioinformatics tools to understand virulence mechanisms in Staphylococcus aureus

Staphylococcus aureus, one of the major pathogenic bacteria, is associated with substantial morbidity and mortality. The disease burden of staphylococcal infections is significant, which is primarily attributed to its adaptability and resistance to environmental stresses. S. aureus has the ability to develop multiple resistances to antimicrobial agents. These high resistances make pathogenicity of S. aureus one of the most complex mechanisms to understand and manage. Proteomic and bioinformatics approaches show great potential in exploring microbial adaptation strategies, ability to cause disease by pathogenic bacteria and the development of diagnostic tools. A summary of the latest developments in the application of ‘omics’ technologies to understand resistance mechanisms in S. aureus and their future role in antistaphylococcal vaccine and/or drug discovery is given here.

Inferencing design styles using Baysian Networks

Reasoning with uncertain knowledge and belief has long been recognized as an important research issue in Artificial Intelligence (AI). Several methodologies have been proposed in the past, including knowledge-based systems, fuzzy sets, and probability theory. The probabilistic approach became popular mainly due to a knowledge representation framework called Bayesian networks. Bayesian networks have earned reputation of being powerful tools for modeling complex problem involving uncertain knowledge. Uncertain knowledge exists in domains such as medicine, law, geographical information systems and design as it is difficult to retrieve all knowledge and experience from experts. In design domain, experts believe that design style is an intangible concept and that its knowledge is difficult to be presented in a formal way. The aim of the research is to find ways to represent design style knowledge in Bayesian net works. We showed that these networks can be used for diagnosis (inferences) and classification of design style. The furniture design style is selected as an example domain, however the method can be used for any other domain.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Dynamic modeling for construction innovation

Previous research on construction innovation has commonly recognized the importance of the organizational climate and key individuals, often called “champions,” for the success of innovation. However, it rarely focuses on the role of participants at the project level and addresses the dynamics of construction innovation. This paper therefore presents a dynamic innovation model that has been developed using the concept of system dynamics. The model incorporates the influence of several individual and situational factors and highlights two critical elements that drive construction innovations: (1) normative pressure created by project managers through their championing behavior, and (2) instrumental motivation of team members facilitated by a supportive organizational climate. The model is qualified empirically, using the results of a survey of project managers and their project team members working for general contractors in Singapore, by assessing casual relationships for key model variables. Finally, the paper discusses the implications of the model structure for fostering construction innovations.

Daylighting design and simulation : ease of use analysis of digital tools for architects

Good daylighting design in buildings not only provides a comfortable luminous environment, but also delivers energy savings and comfortable and healthy environments for building occupants. Yet, there is still no consensus on how to assess what constitutes good daylighting design. Currently amongst building performance guidelines, Daylighting factors (DF) or minimum illuminance values are the standard; however, previous research has shown the shortcomings of these metrics. New computer software for daylighting analysis contains new more advanced metrics for daylighting (Climate Base Daylight Metrics-CBDM). Yet, these tools (new metrics or simulation tools) are not currently understood by architects and are not used within architectural firms in Australia. A survey of architectural firms in Brisbane showed the most relevant tools used by industry. The purpose of this paper is to assess and compare these computer simulation tools and new tools available architects and designers for daylighting. The tools are assessed in terms of their ease of use (e.g. previous knowledge required, complexity of geometry input, etc.), efficiency (e.g. speed, render capabilities, etc.) and outcomes (e.g. presentation of results, etc. The study shows tools that are most accessible for architects, are those that import a wide variety of files, or can be integrated into the current 3d modelling software or package. These software’s need to be able to calculate for point in times simulations, and annual analysis. There is a current need in these software solutions for an open source program able to read raw data (in the form of spreadsheets) and show that graphically within a 3D medium. Currently, development into plug-in based software’s are trying to solve this need through third party analysis, however some of these packages are heavily reliant and their host program. These programs however which allow dynamic daylighting simulation, which will make it easier to calculate accurate daylighting no matter which modelling platform the designer uses, while producing more tangible analysis today, without the need to process raw data.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

Electronic functionality in graphene-based nanoarchitectures : discovery and design via first-principles modeling

Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.

Towards tacit knowledge sharing over social web tools

Purpose - Researchers debate whether tacit knowledge sharing through Information Technology (IT) is actually possible. However, with the advent of social web tools, it has been argued that most shortcomings of tacit knowledge sharing are likely to disappear. This paper has two purposes: firstly, to demonstrate the existing debates in the literature regarding tacit knowledge sharing using IT, and secondly, to identify key research gaps that lay the foundations for future research into tacit knowledge sharing using social web. Design/methodology/approach - This paper reviews current literature on IT-mediated tacit knowledge sharing and opens a discussion on tacit knowledge sharing through the use of social web. Findings - First, the existing schools of thoughts in regards to IT ability for tacit knowledge sharing are introduced. Next, difficulties of sharing tacit knowledge through the use of IT are discussed. Then, potentials and pitfalls of social web tools are presented. Finally, the paper concludes that whilst there are significant theoretical arguments supporting that the social web facilitates tacit knowledge sharing there is a lack of empirical evidence to support these arguments and further work is required. Research limitations/implications - The limitations of the review includes: covering only papers that were published in English, issues of access to full texts of some resources, possibility of missing some resources due to search strings used or limited coverage of databases searched. Originality/value - The paper contributes to the fast growing literature on the intersection of KM and IT particularly by focusing on tacit knowledge sharing in social media space. The paper highlights the need for further studies in this area by discussing the current situation in the literature and disclosing the emerging questions and gaps for future studies.

Conceptual modeling - an epistemological foundation

The success of contemporary organizations depends on their ability to make appropriate decisions. Making appropriate decisions is inevitably bound to the availability and provision of relevant information. Information systems should be able to provide information in an efficient way. Thus, within information systems development a detailed analysis of information supply and information demands has to prevail. Based on Syperski’s information set and subset-model we will give an epistemological foundation of information modeling in general and show, why conceptual modeling in particular is capable of specifying effective and efficient information systems. Furthermore, we derive conceptual modeling requirements based on our findings. A short example illustrates the usefulness of a conceptual data modeling technique for the specification of information systems.