Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners’ needs or serve organization’s quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach.     

Coherency Hub Design for Multisocket Sun Servers with CoolThreads Technology

CoHub, a coherency hub ASIC, provides a cost-effective way to extend a glueless two-node chip-multithreading system to a four-node system without changes to the processor. The four-node, 256-thread system achieves near-linear scaling of performance with thread count on transaction-processing workloads. Time-to-market pressure, 800-MHz operation, and a six-stage pipeline were among the constraints that shaped CoHub's design.     

An investigation of multiphase CFD modelling of a lateral sloshing tank

A near-resonant, sway-induced sloshing flow in a rectangular tank is used to compare a homogeneous and inhomogeneous multiphase approach for fluid density and viscosity in a commercial CFD code. Dimensional analysis of the relative motion between the phases suggests the application of an inhomogeneous multiphase model whereas previous published work has used the computationally cheaper homogeneous (or average property) approach. The comparison between the computational and experimental results shows that the homogeneous model tends to underestimate the experimental peak pressures by up to 50%. The inhomogeneous multiphase model gives good agreement with the experimental pressure data. Examination of the relative velocity at the fluid interface confirms that the inhomogeneous model is the appropriate model to use for the simulation of a violent sloshing flow.     

Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain

Practical and financial constraints associated with traditional field-based lithological mapping are often responsible for the generation of maps with insufficient detail and inaccurately located contacts. In arid areas with well exposed rocks and soils, high-resolution multi- and hyperspectral imagery is a valuable mapping aid as lithological units can be readily discriminated and mapped by automatically matching image pixel spectra to a set of reference spectra. However, the use of spectral imagery in all but the most barren terrain is problematic because just small amounts of vegetation cover can obscure or mask the spectra of underlying geological substrates. The use of ancillary information may help to improve lithological discrimination, especially where geobotanical relationships are absent or where distinct lithologies exhibit inherent spectral similarity. This study assesses the efficacy of airborne multispectral imagery for detailed lithological mapping in a vegetated section of the Troodos ophiolite (Cyprus), and investigates whether the mapping performance can be enhanced through the integration of LiDAR-derived topographic data. In each case, a number of algorithms involving different combinations of input variables and classification routine were employed to maximise the mapping performance. Despite the potential problems posed by vegetation cover, geobotanical associations aided the generation of a lithological map - with a satisfactory overall accuracy of 65.5% and Kappa of 0.54 - using only spectral information. Moreover, owing to the correlation between topography and lithology in the study area, the integration of LiDAR-derived topographic variables led to significant improvements of up to 22.5% in the overall mapping accuracy compared to spectral-only approaches. The improvements were found to be considerably greater for algorithms involving classification with an artificial neural network (the Kohonen Self-Organizing Map) than the parametric Maximum Likelihood Classifier. The results of this study demonstrate the enhanced capability of data integration for detailed lithological mapping in areas where spectral discrimination is complicated by the presence of vegetation or inherent spectral similarities.     

Proactive Use of Shared L3 Caches to Enhance Cache Communications in Multi-Core Processors

The software and hardware techniques to exploit the potential of multi-core processors are falling behind, even though the number of cores and cache levels per chip is increasing rapidly. There is no explicit communications support available, and hence inter-core communications depend on cache coherence protocols, resulting in demand-based cache line transfers with their inherent latency and overhead. In this paper, we present Software Controlled Eviction (SCE) to improve the performance of multithreaded applications running on multi-core processors by moving shared data to shared cache levels before it is demanded from remote private caches. Simulation results show that SCE offers significant performance improvement (8-28%) and reduces L3 cache misses by 88-98%.     

A well-based reverse-phase protein array applicable to extracts from formalin-fixed paraffin-embedded tissue

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue offers significant diagnostic utility but is complicated due to the high level of covalently crosslinked proteins arising from formalin fixation. To address these challenges, we developed a reliable protein extraction method for FFPE tissue, based on heat-induced antigen retrieval within a pressure cooker. The protein extraction yield from archival FFPE tissue section is approximately 90% of that recovered from frozen tissue. This method demonstrates preservation of immunoreactivity and recovery of full-length proteins by Western blotting. Additionally, we developed a well-based RP protein array platform utilizing an electrochemiluminescence detection system. Protein samples derived from FFPE tissue by means of laser capture dissection, with as few as 500 shots demonstrate measurable signal differences for different proteins. The lysates coated to the array plate, remain stable over 1?month at room temperature. Theses data suggest that this new protein-profiling platform coupled with the protein extraction method can be used for molecular profiling analysis in FFPE tissue, and contribute to the validation and development of biomarkers in clinical studies.     

Adventure tourism and adventure sports injury: the New Zealand experience

The primary aims of this study were to establish a client injury baseline for the New Zealand adventure tourism and adventure sport sector, and to examine patterns and trends in claims for injury during participation in adventure activities. Content analysis of narrative text data for compensated injuries occurring in a place for recreation and sport over a 12-month period produced over 15,000 cases involving adventure tourism and adventure sport. As found in previous studies in New Zealand, highest claim counts were observed for activities that are often undertaken independently, rather than commercially. Horse riding, tramping, surfing and mountain biking were found to have highest claim counts, while hang gliding/paragliding/parasailing and jet boating injuries had highest claim costs, suggesting greatest injury severity. Highest claim incidence was observed for horse riding, with female claimants over-represented for this activity. Younger male claimants comprised the largest proportion of adventure injuries, and falls were the most common injury mechanism.     

Feature subset selection and ranking for data dimensionality reduction

A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one at a time, by estimating the capability of each specified candidate feature subset to represent the overall features in the measurement space. A squared correlation function is employed as the criterion to measure the dependency between features and this makes the new algorithm easy to implement. The forward orthogonalization strategy, which combines good effectiveness with high efficiency, enables the new algorithm to produce efficient feature subsets with a clear physical interpretation     

The importance of different timings of excitatory and inhibitory pathways in neural field models

In this paper, we consider a neural field model comprised of two distinct populations of neurons, excitatory and inhibitory, for which both the velocities of action potential propagation and the time courses of synaptic processing are different. Using recently-developed techniques, we construct the Evans function characterising the stability of both stationary and travelling wave solutions, under the assumption that the firing rate function is the Heaviside step. We find that these differences in timing for the two populations can cause instabilities of these solutions, leading to, for example, stationary breathers. We also analyse "anti-pulses", a novel type of pattern for which all but a small interval of the domain (in moving coordinates) is active. These results extend previous work on neural fields with space-dependent delays, and demonstrate the importance of considering the effects of the different time-courses of excitatory and inhibitory neural activity.