Technological barriers to learning : designing hybrid pedagogy to minimise cognitive load and maximise understanding

Information and Communication Technologies (ICTs) provide great promise for the future of education. In the Asia-Pacific region, many nations have started working towards the comprehensive development of infrastructure to enable the development of strong networked educational systems. In Queensland there have been significant initiatives in the past decade to support the integration of technology in classrooms and to set the conditions for the enhancement of teaching and learning with technology. One of the great challenges is to develop our classrooms to make the most of these technologies for the benefit of student learning. Recent research and theory into cognitive load, suggests that complex information environments may well impose a barrier on student learning. Further, it suggests that teachers have the capacity to mitigate against cognitive load through the way they prepare and support students engaging with complex information environments. This chapter compares student learning at different levels of cognitive load to show that learning is enhanced when integrating pedagogies are employed to mitigate against high-load information environments. This suggests that a mature policy framework for ICTs in education needs to consider carefully the development of professional capacities to effectively design and integrate technologies for learning.

Static load modelling and voltage stability indices

This paper analyzes the performance of some of the widely used voltage stability indices, namely, singular value, eigenvalue, and loading margin with different static load models. Well-known ZIP model is used to represent loads having components with different power to voltage sensitivities. Studies are carried out on a 10-bus power system and the New England 39-bus power system models. The effects of variation of load model on the performance of the voltage stability indices are discussed. The choice of voltage stability index in the context of load modelling is also suggested in this paper.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

Load during prosthetic gait : is direct measurement better than inverse dynamics?

The knee forces and moments estimated by inverse dynamics and directly measured by a multiaxial transducer were compared during the gait of a transfemoral amputee. The estimated and directly measured forces and moments were relatively close. However, 3D inverse dynamics estimated only partially the forces and moments associated with the deformation of the prosthetic foot and locking of knee mechanism.

Twisted Edwards curves revisited

This paper introduces fast algorithms for performing group operations on twisted Edwards curves, pushing the recent speed limits of Elliptic Curve Cryptography (ECC) forward in a wide range of applications. Notably, the new addition algorithm uses for suitably selected curve constants. In comparison, the fastest point addition algorithms for (twisted) Edwards curves stated in the literature use . It is also shown that the new addition algorithm can be implemented with four processors dropping the effective cost to . This implies an effective speed increase by the full factor of 4 over the sequential case. Our results allow faster implementation of elliptic curve scalar multiplication. In addition, the new point addition algorithm can be used to provide a natural protection from side channel attacks based on simple power analysis (SPA).

Jacobi quartic curves revisited

This paper provides new results about efficient arithmetic on Jacobi quartic form elliptic curves, y 2 = d x 4 + 2 a x 2 + 1. With recent bandwidth-efficient proposals, the arithmetic on Jacobi quartic curves became solidly faster than that of Weierstrass curves. These proposals use up to 7 coordinates to represent a single point. However, fast scalar multiplication algorithms based on windowing techniques, precompute and store several points which require more space than what it takes with 3 coordinates. Also note that some of these proposals require d = 1 for full speed. Unfortunately, elliptic curves having 2-times-a-prime number of points, cannot be written in Jacobi quartic form if d = 1. Even worse the contemporary formulae may fail to output correct coordinates for some inputs. This paper provides improved speeds using fewer coordinates without causing the above mentioned problems. For instance, our proposed point doubling algorithm takes only 2 multiplications, 5 squarings, and no multiplication with curve constants when d is arbitrary and a = ±1/2.

Faster group operations on elliptic curves

This paper improves implementation techniques of Elliptic Curve Cryptography. We introduce new formulae and algorithms for the group law on Jacobi quartic, Jacobi intersection, Edwards, and Hessian curves. The proposed formulae and algorithms can save time in suitable point representations. To support our claims, a cost comparison is made with classic scalar multiplication algorithms using previous and current operation counts. Most notably, the best speeds are obtained from Jacobi quartic curves which provide the fastest timings for most scalar multiplication strategies benefiting from the proposed 12M + 5S + 1D point doubling and 7M + 3S + 1D point addition algorithms. Furthermore, the new addition algorithm provides an efficient way to protect against side channel attacks which are based on simple power analysis (SPA). Keywords: Efficient elliptic curve arithmetic,unified addition, side channel attack.

Faster pairings on special Weierstrass curves

This paper presents efficient formulas for computing cryptographic pairings on the curve y 2 = c x 3 + 1 over fields of large characteristic. We provide examples of pairing-friendly elliptic curves of this form which are of interest for efficient pairing implementations.

Application of system dynamics for evaluating truck load regulations in Anhui, China

In the critical situation of prevailing overweight transportation and crag-fast enforcement in Chinese highway networks, this paper develops a methodological framework for truck weight regulation (TWR) evaluation using System Dynamics (SD). Composed of five interrelated subsystems, the framework is able to capture the highway, vehicle and freight variables that influence the effect of TWR and transportation efficiency over time. It specifically describes the development and use of the Truck Weight Regulation Evaluating Model (TWREM) for the highway freight system in Anhui province, China. Three policy alternatives are analyzed: 1) tolerant policy approach, which allows heavy-duty freight activity to continue in its current state, and is shown to lead to nearly catastrophic results; 2) rigid policy approach, which would terminate all heavy-duty freight activities immediately, and is shown to be economically infeasible; and 3) moderate policy approach, which advocates a gradual reduction of heavy-duty freight activities to a moderate state. The simulation results shows that the moderate policy approach is the most appropriate option to solve the social and economic problems arising from the activities of the heavy-duty freight transportation in Anhui. In addition, some suggestions of TWR policy in China are also made in this paper.

Adaptive load shedding and regional protection

The requirement for improved efficiency whilst maintaining system security necessitates the development of improved system analysis approaches and the development of advanced emergency control technologies. Load shedding is a type of emergency control that is designed to ensure system stability by curtailing system load to match generation supply. This paper presents a new adaptive load shedding scheme that provides emergency protection against excess frequency decline, whilst minimizing the risk of line overloading. The proposed load shedding scheme uses the local frequency rate information to adapt the load shedding behaviour to suit the size and location of the experienced disturbance. The proposed scheme is tested in simulation on a 3-region, 10-generator sample system and shows good performance.

Assessment of Speech Dialog Systems using Multi-Modal Cognitive Load Analysis and Driving Performance Metrics

In this paper, cognitive load analysis via acoustic- and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.

Utilizing robustness of positive buck-boost converter against input voltage and load current disturbances

A Positive Buck- Boost (PBB) converter is a known DC-DC converter that can operate in step up and step down modes. Unlike Buck, Boost, and Inverting Buck Boost converters, the inductor current of a PBB can be controlled independently of its voltage conversion ratio. In other words, the inductor of PBB can be utilised as an energy storage unit in addition to its main function of energy transfer. In this paper, the capability of PBB to store energy has been utilised to achieve robustness against input voltage fluctuations and output current changes. The control strategy has been developed to keep accuracy, affordability, and simplicity acceptable. To improve the efficiency of the system a Smart Load Controller (SLC) has been suggested. Applying SLC extra current storage occurs when there is sudden loads change otherwise little extra current is stored.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm− 1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. This ex-vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.