Fog computing: a cloud to the ground support for smart things and machine-to-machine networks

Cloud services to smart things face latency and intermittent connectivity issues. Fog devices are positioned between cloud and smart devices. Their high speed Internet connection to the cloud, and physical proximity to users, enable real time applications and location based services, and mobility support. Cisco promoted fog computing concept in the areas of smart grid, connected vehicles and wireless sensor and actuator networks. This survey article expands this concept to the decentralized smart building control, recognizes cloudlets as special case of fog computing, and relates it to the software defined networks (SDN) scenarios. Our literature review identifies a handful number of articles. Cooperative data scheduling and adaptive traffic light problems in SDN based vehicular networks, and demand response management in macro station and micro-grid based smart grids are discussed. Security, privacy and trust issues, control information overhead and network control policies do not seem to be studied so far within the fog computing concept.

Neurocognitive effects of multivitamin supplementation on the steady state visually evoked potential (SSVEP) measure of brain activity in elderly women

OBJECTIVE: Growing evidence suggests that dietary supplementation with selected micronutrients and nutraceuticals may have the potential to improve cognition in older adults. Fewer studies have investigated the effects of these substances on brain activity. METHODS: This study was a randomised, double-blind, placebo-controlled trial, conducted to explore the effects of 16 weeks supplementation with a combined multivitamin, mineral and herbal formula on the steady state visually evoked potential (SSVEP) measure of brain electrical activity. Participants were elderly women aged between 64 and 79 years, with subjective memory complaints. Baseline and post-treatment SSVEP data was obtained for 22 participants in the multivitamin group and 19 in the placebo group. A spatial working memory delayed response task (DRT) was performed during the recording of the SSVEP. RESULTS: The results revealed that when compared to placebo, multivitamin supplementation delayed SSVEP latency during retrieval, interpreted as an increase in inhibitory neural processes. Behavioural performance on the DRT was not improved by the multivitamin, however improved performance accuracy was associated with increased midline central SSVEP latency. There were no multivitamin-related effects on SSVEP amplitude. CONCLUSION: These findings indicate that in the elderly, multivitamin supplementation may enhance neural efficiency during memory retrieval.

Does angling technique selectively target fishes based on their behavioural type?

Recently, there has been growing recognition that fish harvesting practices can have important impacts on the phenotypic distributions and diversity of natural populations through a phenomenon known as fisheries-induced evolution. Here we experimentally show that two common recreational angling techniques (active crank baits versus passive soft plastics) differentially target wild largemouth bass (Micropterus salmoides) and rock bass (Ambloplites rupestris) based on variation in their behavioural tendencies. Fish were first angled in the wild using both techniques and then brought back to the laboratory and tested for individual-level differences in common estimates of personality (refuge emergence, flight-initiation-distance, latency-to-recapture and with a net, and general activity) in an in-lake experimental arena. We found that different angling techniques appear to selectively target these species based on their boldness (as characterized by refuge emergence, a standard measure of boldness in fishes) but not other assays of personality. We also observed that body size was independently a significant predictor of personality in both species, though this varied between traits and species. Our results suggest a context-dependency for vulnerability to capture relative to behaviour in these fish species. Ascertaining the selective pressures angling practices exert on natural populations is an important area of fisheries research with significant implications for ecology, evolution, and resource management.

Motor cortex excitability is not differentially modulated following skill and strength training

AIM: A single session of skill or strength training can modulate the primary motor cortex (M1), which manifests as increased corticospinal excitability (CSE) and decreased short-latency intra-cortical inhibition (SICI). We tested the hypothesis that both skill and strength training can propagate the neural mechanisms mediating cross-transfer and modulate the ipsilateral M1 (iM1). METHODS: Transcranial magnetic stimulation (TMS) measured baseline CSE and SICI in the contralateral motor cortex (cM1) and iM1. Participants completed 4 sets of unilateral training with their dominant arm, either visuomotor tracking, metronome-paced strength training (MPST), self-paced strength training (SPST) or control. Immediately post training, TMS was repeated in both M1s. RESULTS: Motor-evoked potentials (MEPs) increased and inhibition was reduced for skill and MPST training from baseline in both M1s. Self-paced strength training and control did not produce changes in CSE and SICI when compared to baseline in both M1s. After training, skill and MPST increased CSE and decreased SICI in cM1 compared to SPST and control. Skill and MPST training decreased SICI in iM1 compared to SPST and control post intervention; however, CSE in iM1 was not different across groups post training. CONCLUSION: Both skill training and MPST facilitated an increase in CSE and released SICI in iM1 and cM1 compared to baseline. Our results suggest that synchronizing to an auditory or a visual cue promotes neural adaptations within the iM1, which is thought to mediate cross transfer.

Information discovery in multi-dimensional autonomous wireless sensor networks

 The thesis proposed four novel algorithms of information discovery for Multidimensional Autonomous Wireless Sensor Networks (WSNs) that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service improvements that are of immense benefit to Multidimensional Autonomous WSNs are deployed in complex environments (e.g., mission-critical applications).

Novel approach for information discovery in autonomous wireless sensor networks

Autonomous Wireless sensor networks(WSNs) have sensors that are usually deployed randomly to monitor one or more phenomena. They are attractive for information discovery in large-scale data rich environments and can add value to mission–critical applications such as battlefield surveillance and emergency response systems. However, in order to fully exploit these networks for such applications, energy efficient, load balanced and scalable solutions for information discovery are essential. Multi-dimensional autonomous WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). Such networks present unique challenges to data dissemination, data storage of in-network information discovery. In this paper, we propose a novel method for information discovery for multi-dimensional autonomous WSNs which sensors are deployed randomly that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service (QoS) improvements that are of immense benefit to mission–critical applications. We present simulation results to show that the proposed approach to information discovery offers significant improvements on query resolution latency compared with current approaches.

Efficient consolidation-aware VCPU scheduling on multicore virtualization platform

Multicore processors are widely used in today's computer systems. Multicore virtualization technology provides an elastic solution to more efficiently utilize the multicore system. However, the Lock Holder Preemption (LHP) problem in the virtualized multicore systems causes significant CPU cycles wastes, which hurt virtual machine (VM) performance and reduces response latency. The system consolidates more VMs, the LHP problem becomes worse. In this paper, we propose an efficient consolidation-aware vCPU (CVS) scheduling scheme on multicore virtualization platform. Based on vCPU over-commitment rate, the CVS scheduling scheme adaptively selects one algorithm among three vCPU scheduling algorithms: co-scheduling, yield-to-head, and yield-to-tail based on the vCPU over-commitment rate because the actions of vCPU scheduling are split into many single steps such as scheduling vCPUs simultaneously or inserting one vCPU into the run-queue from the head or tail. The CVS scheme can effectively improve VM performance in the low, middle, and high VM consolidation scenarios. Using real-life parallel benchmarks, our experimental results show that the proposed CVS scheme improves the overall system performance while the optimization overhead remains low.

Modelling a helicopter training continuum to support system transformation

his study investigates the role of system dynamics (SD) modeling to support strategic decision making for an aviation training continuum that is going through major change. The Australian helicopter training continuum (HTC) is currently undergoing transformation, with restructure and consolidation of training schools and training platforms across multiple services. In this research, we introduce a novel SD-based HTC simulation architecture to facilitate the discovery of relationships between student and instructor development and flow dynamics. The proposed simulation architecture employs hybrid push – pull flow control to quantify transience and estimate recovery time after a policy change or disturbance. This architecture allows for multiple student and instructor types, and their respective intake levels and pass rates. Here the instructor variables include availability, specialization and experience. Enos (2011) successfully explored the application of SD modeling to understand the behavior for combat aviation training in an individual school. This research employs a similar modeling philosophy, but takes a higher level view of the system by looking across multiple training schools, which introduces complexity due to pooling, latency and the amplification of affects across the system. The ability to identify causal relationships allowed stakeholders to develop a deeper understanding of the underlying systemic problems, such as delayed transitions between schools and instructor shortages, whilst the hybrid “push-pull” design allowed us to quantify the pooling of students between schools.

Fast and energy efficient data storage for information discovery in multi-dimensional WSNs

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). An efficient information dis-covery for multi-dimensional WSNs deployed in mission–critical environments has become an essential research consideration. Timely and energy efficient information discovery is very impor-tant to maintain the QoS of such mission critical applications. An inefficient information discovery mechanism will result in high transmission of data packets over the network creating bottlenecks leading to unbalanced energy consumption over the network. High latency and inefficient energy consumption will have a direct effect on the QoS of mission-critical applications of particular importance in this regard is the minimization of hotspots.

Sleep quantity and quality is not compromised during planned burn shifts of less than 12 h

Planned burning is a preventative strategy aimed at decreasing fuel loads to reduce the severity of future wildfire events. During planned burn operations, firefighters can work long shifts. Furthermore, remote burning locations may require firefighters to sleep away from home between shifts. The existing evidence surrounding firefighters' sleep during such operations is exclusively anecdotal. The aims of the study were to describe firefighters' sleep during planned burn operations and evaluate the impact of the key operational factors (shift start time, shift length and sleeping location) that may contribute to inadequate sleep. Thirty-three salaried firefighters were recruited from Australia's fire agencies and sleep was measured objectively using wrist actigraphy for four weeks. All variables were examined in two conditions: (1) burn days, and (2) non-burn days. Time in bed, total sleep time, sleep latency and sleep efficiency were evaluated objectively. Subjective reports of pre- and post-sleep fatigue, sleep location, sleep quality, sleep quantity, number of times woken and sleep timing were also recorded. Analyses revealed no differences in measures of sleep quantity and quality when comparing non-burn and burn days. Total sleep time was less when planned burn shifts were >12 h. However, on burn days, work shift start time as well as sleeping location did not impact firefighters' sleep quantity. Self-reported levels of pre- and post-sleep fatigue were greater on burn days compared to non-burn days. These findings indicate that sleep quantity and quality are not compromised during planned burn operations <12 h in duration.