'Tacitus' project: identifying multi-sensory perceptions in creative 3D practice for the development of a haptic computing system for applied artists

This paper outlines the major motivating factors concerning a novel collaborative project between Edinburgh College of Art and Edinburgh Virtual Environment Centre. The Tacitus project will investigate the use of multi-modal virtual environments, specifically, the haptic (touch) modality, with regards to the creative processes employed by designers working within the field of applied arts. The salient areas of research are described, and the methods by which information regarding these areas will be obtained are considered. Initial investigations have revealed a strong need to mimic the traditional applied artists' workspaces, with co-location of visual and haptic cues a priority.     

Examining teacher growth in professional learning groups for in‐service teachers of mathematics

Abstract

Teachers may face important challenges when encouraged to improve their mathematics teaching. Their personal beliefs, knowledge, confidence and personal intentions towards growth and change are all complex factors which may influence teachers’ capacity, and their decisions about personal change in their teaching. In this study, intermediate teachers and the conversations that took place during their monthly Professional Learning Group meetings over a one‐year period were examined in order to better understand issues teachers face in their growth and development as teachers of mathematics. We critically examine the notion and meaning of success to different stakeholders.     

The effect of handle friction and inward or outward torque on maximum axial push force

OBJECTIVE: To investigate the relationship among friction, applied torque, and axial push force on cylindrical handles. BACKGROUND: We have earlier demonstrated that participants can exert greater contact force and torque in an "inward" movement of the hand about the long axis of a gripped cylinder (wrist flexion/forearm supination) than they can in an "outward" hand movement. METHOD: Twelve healthy participants exerted anteriorly directed maximum push forces along the long axis of aluminum and rubber handles while applying deliberate inward or outward torques, no torque (straight), and an unspecified (preferred) torque. RESULTS: Axial push force was 12% greater for the rubber handle than for the aluminum handle. Participants exerted mean torques of 1.1, 0.3, 2.5, and -2.0 Nm and axial push forces of 94, 85, 75, and 65 N for the preferred, straight, inward, and outward trials, respectively. Left to decide for themselves, participants tended to apply inward torques, which were associated with increased axial push forces. CONCLUSION: Axial push force was limited by hand-handle coupling--not the whole body's push strength. Participants appeared to intuitively know that the application of an inward torque would improve their maximum axial push force. Axial push forces were least when a deliberate torque was requested, probably because high levels of torque exertions interfered with the push. APPLICATION: A low-friction handle decreases maximum axial push force. It should be anticipated that people will apply inward torque during maximum axial push.     

Performance enhancement of TCP in high-speed networks

GridFTP is a secure and reliable high-performance parallel data transfer protocol used for transferring massive amounts of widely distributed data. Currently it allows users to configure the number of parallel streams and socket buffer size. However, its tuning procedure for optimal combination is a time consuming task. The socket handlers and buffers are important system resources and must therefore be carefully managed. In this paper, we propose a scheme to achieve high throughput even with a smaller buffer size, and also derive a regression equation to predict the optimal combination of resources for a connection. To improve the performance, the TCP based on our scheme obtains higher throughput and spends less memory for the same throughput than the original TCP scheme. In addition, the regression equation is verified by comparing measured and predicted values, and we apply the equation to an actual experiment on the KOrea advanced REsearch Network (KOREN). The result demonstrates that the equation provides excellent predictions with only an 8% error boundary.     

Column and batch reactive transport experiment parameter estimation using a genetic algorithm

This paper focuses on the application of a genetic algorithm (GA) in estimating the fate and transport parameters of a reacting solute from the column and batch experiments involving a saturated porous medium. A program is developed using C++ to model the column and batch data using kinetically controlled one- or two-site sorption models including linear and/or nonlinear forms. The objective of the algorithm is to minimize the sum of squared differences between the measured and modeled solute concentration data associated with column effluent (i.e., “breakthrough curves”). The GA is capable of estimating transport and reactions parameters such as forward and reverse reaction rates and parameters of the nonlinear reaction models, from a given set of measured data. Further simulations have been performed to estimate the appropriate configurations of the GA, which assist the method in estimating the fate and transport parameters more efficiently. It is shown that a wide range of the GA parameters can lead to convergence to appropriate estimations. The results obtained from this study show that the capability of GAs to fit the column and batch experiment data is promising.     

Approximate factorization of multivariate polynomials using singular value decomposition

We describe the design, implementation and experimental evaluation of new algorithms for computing the approximate factorization of multivariate polynomials with complex coefficients that contain numerical noise. Our algorithms are based on a generalization of the differential forms introduced by W. Ruppert and S. Gao to many variables, and use singular value decomposition or structured total least squares approximation and Gauss–Newton optimization to numerically compute the approximate multivariate factors. We demonstrate on a large set of benchmark polynomials that our algorithms efficiently yield approximate factorizations within the coefficient noise even when the relative error in the input is substantial (10⁻³).     

Perfect forward secure identity-based authenticated key agreement protocol in the escrow mode

The majority of existing escrowable identity-based key agreement protocols only provide partial forward secrecy. Such protocols are, arguably, not suitable for many real-word applications, as the latter tends to require a stronger sense of forward secrecy—perfect forward secrecy. In this paper, we propose an efficient perfect forward-secure identity-based key agreement protocol in the escrow mode. We prove the security of our protocol in the random oracle model, assuming the intractability of the Gap Biline...     

The movement patterns and the experiential components of virtual environments

Human movement in virtual environments (VEs) is a largely unstudied area, and there are no well-established methods of measuring it in VEs. Consequently, it is unclear how movement affects the experiential side of VEs. We introduce a novel method of measuring and modelling human movement. A specific information entropy-based modelling method enabled us to identify different movement patterns and analyse the experiential components related to them. The data was collected by registering the movement patterns of 68 participants who were in a virtual house doing a search task. The experiential side of the VE was measured with the Experimental Virtual Environment Questionnaire (EVEQ). Four movement patterns were identified. In addition, fluent movement in VEs was related to a high sense of presence. Moreover, the participants who moved fluently in the environment assessed their skills high. The results show how movement is related the way in which people experience the VE. The movement analysis method introduced here is applicable to other related research areas as well.     

Prediction of urban stormwater quality using artificial neural networks

There are a vast number of complex, interrelated processes influencing urban stormwater quality. However, the lack of measured fundamental variables prevents the construction of process-based models. Furthermore, hybrid models such as the buildup-washoff models are generally crude simplifications of reality. This has created the need for statistical models, capable of making use of the readily accessible data. In this paper, artificial neural networks (ANN) were used to predict stormwater quality at urbanized catchments located throughout the United States. Five constituents were analysed: chemical oxygen demand (COD), lead (Pb), suspended solids (SS), total Kjeldhal nitrogen (TKN) and total phosphorus (TP). Multiple linear regression equations were initially constructed upon logarithmically transformed data. Input variables were primarily selected using a stepwise regression approach, combined with process knowledge. Variables found significant in the regression models were then used to construct ANN models. Other important network parameters such as learning rate, momentum and the number of hidden nodes were optimized using a trial and error approach. The final ANN models were then compared with the multiple linear regression models. In summary, ANN models were generally less accurate than the regression models and more time consuming to construct. This infers that ANN models are not more applicable than regression models when predicting urban stormwater quality.