Data transformations in custom digital workflows : property graphs as a data model for user-defined mappings

This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

Attitudes of future special education teachers toward gifted students and their education

Saudi Arabian education is undergoing substantial reform in the context of a nation transitioning from a resource-rich economy to a knowledge economy. Gifted students are important human resources for such developing countries. However, there are some concerns emanating from the international literature that gifted students have been neglected in many schools due to teachers’ attitudes toward them. The literature shows that future teachers also hold similar negative attitudes, especially those in Special Education courses who, as practicing teachers, are often responsible for supporting the gifted education process. The purpose of this study was to explore whether these attitudes are held by future special education teachers in Saudi Arabia, and how the standard gifted education course, delivered as part of their program, impacts on their attitudes toward gifted students. The study was strongly influenced by the Theory of Reasoned Action (Ajzen, 1980, 2012) and the Theory of Personal Knowledge (Polanyi, 1966), which both suggest that attitudes are related to people’s (i.e. teachers’) beliefs. A mixed methods design was used to collect quantitative and qualitative data from a cohort of students enrolled in a teacher education program at a Saudi Arabian university. The program was designed for students majoring in special education. The quantitative component of the study involved an investigation of a cohort of future special education teachers taking a semester-long course in gifted education. The data were primarily sourced from a standard questionnaire instrument modified in the Arabic language, and supplemented with questions that probed the future teachers’ attitudes toward gifted children. The participants, 90 special education future teachers, were enrolled in an introductory course about gifted education. The questionnaire contained 34 items from the "Opinions about the Gifted and Their Education" (Gagné, 1991) questionnaire, utilising a five-point Likert scale. The quantitative data were analysed through the use of descriptive statistics, Spearman correlation Coefficients, Paired Samples t-test, and Multiple Linear Regression. The qualitative component focussed on eight participants enrolled in the gifted education course. The primary source of the qualitative data was informed by individual semi-structured interviews with each of these participants. The findings, based on both the quantitative and qualitative data, indicated that the majority of future special education teachers held, overall, slightly positive attitudes toward gifted students and their education. However, the participants were resistant to offering special services for the gifted within the regular classroom, even when a comparison was made on equity grounds with disabled students. While the participants held ambivalent attitudes toward ability grouping, their attitudes were positive toward grade acceleration. Further, the majority agreed that gifted students are likely to be rejected by their teachers. Despite such judgments, they considered the gifted to be a valuable resource for Saudi society. Differences within the cohort were found when two variables emerged as potential predictors of attitude: age, experience, and participants’ hometown. The younger (under 25 years old) future special education teachers, with no internship or school practice experience, held more positive attitudes toward the gifted students, with respect to their general needs, than did the older participants with previous school experiences. Additionally, participants from a rural region were more resistant toward gifted education than future teachers from urban areas. The findings also indicated that the attitudes of most of the participants were significantly improved, as a result of the course, toward ability grouping such as special classes and schools, but remained highly concerned about differentiation within regular classrooms with either elitism or time pressure. From the findings, it can be confirmed that a lectured-based course can serve as a starting point from which to focus future teachers’ attention on the varied needs of the gifted, and as a conduit for learning about special services for the gifted. However, by itself, the course appears to have minimal influence on attitudes toward differentiation. As a consequence, there is merit in its redevelopment, and the incorporation of more practical opportunities for future teachers to experience the teaching of the gifted.

Mechanical properties of bioinspired bicontinuous nanocomposites

Inspired by the wonderful properties of some biological composites in nature, we performed molecular dynamics simulations to investigate the mechanical behavior of bicontinuous nanocomposites. Three representative types of bicontinuous composites, which have regular network, random network, and nacre inspired microstructures respectively, were studied and the results were compared with those of a honeycomb nanocomposite with only one continuous phase. It was found that the mechanical strength of nanocomposites in a given direction strongly depends on the connectivity of microstructure in that direction. Directional isotropy in mechanical strength and easy manufacturability favor the random network nanocomposites as a potentially great bioinspired composite with balanced performances. In addition, the tensile strength of random network nanocomposites is less sensitive to the interfacial failure, owing to its super high interface-to-volume ratio and random distribution of internal interfaces. The results provide a useful guideline for design and optimization of advanced nanocomposites with superior mechanical properties.

Flexible design of decoupling and matching networks for two strongly coupled antennas

The flexible design of decoupling and matching networks for coupled antennas is introduced. The network includes three parts: circuits for impedance transformation, an element for odd-mode decoupling and conventional matching networks. It is found that all three parts are determined by one parameter of the ABCD matrix of the impedance transformation circuit. Thus a large variety of circuits with different element values can be used for decoupling which relaxes the practical design constraints.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active nearstream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.

How to strengthen any weakly unforgeable signature into a strongly unforgeable signature

Standard signature schemes are usually designed only to achieve weak unforgeability – i.e. preventing forgery of signatures on new messages not previously signed. However, most signature schemes are randomised and allow many possible signatures for a single message. In this case, it may be possible to produce a new signature on a previously signed message. Some applications require that this type of forgery also be prevented – this requirement is called strong unforgeability. At PKC2006, Boneh Shen and Waters presented an efficient transform based on any randomised trapdoor hash function which converts a weakly unforgeable signature into a strongly unforgeable signature and applied it to construct a strongly unforgeable signature based on the CDH problem. However, the transform of Boneh et al only applies to a class of so-called partitioned signatures. Although many schemes fall in this class, some do not, for example the DSA signature. Hence it is natural to ask whether one can obtain a truly generic efficient transform based on any randomised trapdoor hash function which converts any weakly unforgeable signature into a strongly unforgeable one. We answer this question in the positive by presenting a simple modification of the Boneh-Shen-Waters transform. Our modified transform uses two randomised trapdoor hash functions.

Effect of Coulomb blockade, gold resistance, and thermal expansion on the electrical resistance of ultrathin gold films

Controlling the electrical resistance of granular thin films is of great importance for many applications, yet a full understanding of electron transport in such films remains a major challenge. We have studied experimentally and by model calculations the temperature dependence of the electrical resistance of ultrathin gold films at temperatures between 2 K and 300 K. Using sputter deposition, the film morphology was varied from a discontinuous film of weakly coupled meandering islands to a continuous film of strongly coupled coalesced islands. In the weak-coupling regime, we compare the regular island array model, the cotunneling model, and the conduction percolation model with our experimental data. We show that the tunnel barriers and the Coulomb blockade energies are important at low temperatures and that the thermal expansion of the substrate and the island resistance affect the resistance at high temperatures. At low temperatures our experimental data show evidence for a transition from electron cotunneling to sequential tunneling but the data can also be interpreted in terms of conduction percolation. The resistivity and temperature coefficient of resistance of the meandering gold islands are found to resemble those of gold nanowires. We derive a simple expression for the temperature at which the resistance changes from non-metal-like behavior into metal-like behavior. In the case of strong island coupling, the total resistance is solely determined by the Ohmic island resistance.

Self-organized nanoarrays : plasma-related controls

The paper presents an investigation of self-organizational and -assembly processes of nanostructure growth on surfaces exposed to low-temperature plasmas. We have considered three main growth stages-initial, or sub-monolayer growth stage, separate nanostructure growth stage, and array growth stages with the characteristic sizes of several nm, several tens of nm, and several hundreds of nm, respectively, and have demonstrated, by the experimental data and hybrid multiscale numerical simulations, that the plasma parameters can strongly influence the surface processes and hence the kinetics of self-organization and -assembly. Our results show that plasma-controlled self-organization is a promising way to assemble large regular arrays of nanostructures. © 2008 IUPAC.

Surface waves in strongly irradiated dusty plasmas

High-frequency surface waves at the interface between two dusty plasmas subject to radiation are considered. Ultraviolet radiation with energy flux larger than the photoelectric work function of the dust surface causes photoemission of electrons. The dust charge and the overall charge balance of the plasma are thus modified. The dispersion properties of the surface waves are investigated for three parameter regimes distinguished by the charging mechanisms in the two plasmas. It is shown that photoemission can significantly affect the plasma and the surface waves.

Nanomorphology influence on the light conversion mechanisms in highly efficient diketopyrrolopyrrole based organic solar cells

In this work, diketopyrrolopyrrole-based polymer bulk heterojunction solar cells with inverted and regular architecture have been investigated. The influence of the polymer:fullerene ratio on the photoactive film nanomorphology has been studied in detail. Transmission Electron Microscopy and Atomic Force Microscopy reveal that the resulting film morphology strongly depends on the fullerene ratio. This fact determines the photocurrent generation and governs the transport of free charge carriers. Slight variations on the PCBM ratio respect to the polymer show great differences on the electrical behavior of the solar cell. Once the polymer:fullerene ratio is accurately adjusted, power conversion efficiencies of 4.7% and 4.9% are obtained for inverted and regular architectures respectively. Furthermore, by correlating the optical and morphological characterization of the polymer:fullerene films and the electrical behavior of solar cells, an ad hoc interpretation is proposed to explain the photovoltaic performance as a function of this polymer:blend composition.

Edge-weighting of gene expression graphs

In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed. Keywords: Edge-weighting; weighted graphs; gene expression; bi-clustering

Scaffolding understanding of tables and graphs

The literacy demands of tables and graphs are different from those of prose texts such as narrative. This paper draws from part of a qualitative case study which sought to investigate strategies that scaffold and enhance the teaching and learning of varied representations in text. As indicated in the paper, the method focused on the teaching and learning of tables and graphs with use of Freebody and Luke's (1990) four resources model from literacy education.

Towards strongly consistent online HMM parameter estimation using one-step Kerridge inaccuracy

In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on the new information-theoretic concept of one-step Kerridge inaccuracy (OKI). Under several regulatory conditions, we establish a convergence result (and some limited strong consistency results) for our proposed online OKI-based parameter estimator. In simulation studies, we illustrate the global convergence behaviour of our proposed estimator and provide a counter-example illustrating the local convergence of other popular HMM parameter estimators.