CONTEXTUALIZING LEARNING OBJECTS USING ONTOLOGIES

Educational research over the past three years has intensified such that the context of learning resources needs to be properly modeled. Many researchers have described and even mandated the use of ontologies in the research being conducted, yet the process of actually connecting one or more ontologies to a learning object has not been extensively discussed. This paper describes a practical model for associating multiple ontologies with learning objects while making full use of the IEEE LOM specification. The model categorizes these ontologies according to five major categories of context based on the most popular fields of study actively being pursued by the educational research community: Thematic context, Pedagogical context, Learner context, Organizational context, and Historical/Statistical context.     

Cornea stress test--evaluation of corneal endothelial function in vivo by contact lens induced stress

Changes in the NHS have supported the idea of targeting health services to those in greatest need. This has meant that health visitors are increasingly having to identify 'vulnerable' families in need of increased health visiting intervention. This paper reports on a qualitative study undertaken in order to explore the ways in which health visitors plan and organize their work in relation to the concept of vulnerability. Focus groups and semi-structured interviews were carried out with health visitors from two separate geographical areas, one an inner city area and the other suburban, in order to explore the criteria by which health visitors define vulnerability and decide to increase their levels of intervention to particular families. It was found that vulnerability was extremely difficult to define but that the health visitors used criteria which were appropriate to the particular localities in which they worked to identify vulnerable families and to increase their levels of intervention to those families. Health visitors were targeting their services within a framework of a basic minimum service to all and were assessing the health needs of individuals or families rather than planning their work on the basis of community or practice profiles.     

Mutual information based registration of multimodal stereo videos for person tracking

Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and robustly for relatively close range surveillance applications. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we employ maximization of mutual information in sliding correspondence windows that inform a disparity voting algorithm to demonstrate successful registration of objects in color and thermal imagery. Extensive evaluation of scenes with multiple objects at different depths and levels of occlusion shows high rates of successful registration. Ground truth experiments demonstrate the utility of the disparity voting techniques for multimodal registration by yielding qualitative and quantitative results that outperform approaches that do not consider occlusions. A basic framework for multimodal stereo tracking is investigated and promising experimental studies show the viability of using registration disparity estimates as a tracking feature.     

Thermal stability and high-temperature wear of Ti–TiN and TiN–CrN nanomultilayer coatings under self-mated conditions

Ti–TiN and TiN–CrN nanomultilayers were thermally stable retaining uniform and sharp layer interfaces up to 24 h at 773 K, without any oxidation or phase transformation accompanying each individual layer. Decreasing the multilayer spacing resulted in an increase in the hardness in both cases. The coating hardness was found to be independent of the substrate type, when applied on HS718, Ti64 and HCHCr substrates. In scratch testing, the multilayers displayed a better resistance to the onset of failure, as compared to the monolayer TiN. The substrate plasticity played an important role in determining the coating failure mode. Self-mated wear tests revealed the CrN–TiN system to exhibit the best wear behaviour, both at room temperature and at 773 K. The Ti–TiN coatings are more accommodative with all three substrates, as compared to TiN–CrN and TiN.     

Treatment with the oral growth hormone secretagogue MK-677 increases markers of bone formation and bone resorption in obese young males

The effect of 2 months of treatment with the oral growth hormone (GH) secretagogue MK-677 on markers of bone metabolism was determined in healthy obese male subjects. This was a randomized, double-blind, parallel, placebo-controlled study. Twenty-four healthy obese males, 19-49 years of age, with body mass index > 30 kg/m2 were treated with MK-677 (25 mg/day; n = 12) or placebo (n = 12) for 8 weeks. MK-677 increased markers of bone formation; a 23% increase in the carboxy-terminal propeptide of type I procollagen levels and a 28% increase in procollagen III peptide levels were seen with as little as 2 weeks of MK-677 treatment (p < 0.01 and p = 0.001 vs. placebo, respectively) while a 15% increase in serum levels of osteocalcin was not detected until 8 weeks of treatment (p < 0.01 vs. placebo). Markers of bone resorption were induced within 2 weeks of treatment with MK-677; serum levels of the carboxy-terminal cross-linked telopeptide of type I collagen were increased 26% at 8 weeks (p = 0.001 vs. placebo), and urine hydroxyproline/creatinine and calcium/creatinine ratios at 8 weeks were increased by 23% (p < 0.05 vs. placebo) and 46% (p < 0.05 vs placebo), respectively, MK-677 increased serum insulin-like growth factor binding protein-5 (IGFBP-5) by 43-44% after 2-8 weeks of treatment (p < 0.01 vs. placebo). Serum IGFBP-4 was increased by 25% after 2 weeks of treatment (p < 0.001 vs. placebo) but no significant change from baseline was observed after 8 weeks of treatment. Plasma interleukin-6 was not significantly changed by active treatment. In conclusion, short-term treatment of healthy obese male volunteers with the GH secretagogue MK-677 increases markers of both bone resorption and formation. Large increases in serum levels of IGF-1 and IGFBP-5 and a transient increase in serum IGFBP-4 were found. Future long-term studies are needed to investigate if prolonged treatment with MK-677 increases bone mass.     

Towards an effective integration of cellular users to the structured Peer-to-Peer network

Integration of cellular users into the peer-to-peer (P2P) network is still in limbo due to limitations caused by heterogeneity, mobility and time-varying capacities of the wireless channel. If traditional Chord is employed to include users from the cellular networks, users under the same base station scatter in logical topology randomly. In this paper, we present a novel cellular Chord (C-Chord) P2P system that integrates the cellular users into the well-established structured P2P network in a topology-aware fashion. C-Chord offers the cellular users a choice of downloading contents either from the Internet peers at a faster rate or from other cellular users from the same base station avoiding the Internet data penalty. We also incorporate the peer selection module based on stable marriage problem that chooses the appropriate candidate from the discovered potential senders. We conduct extensive simulations to evaluate the performance of the proposed C-Chord P2P system and the peer selection module. Simulation results show that the path-length per lookup query is smaller than that of the traditional Chord system. Overhead due to renewal of routing information is also smaller for the cellular users in the C-Chord system. We also measure the throughput at the cellular receivers to analyze the effects of selecting peers either from same base station or from outside the Internet gateway. Throughput also increases dramatically due to an intelligent selection of peers among the potential senders.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.