UAV Aided Data Collection for Wildlife Monitoring using Cache-enabled Mobile Ad-hoc Wireless Sensor Nodes

Unmanned aerial vehicle (UAV) assisted data collection is not a new concept and has been used in various mobile ad hoc networks. In this paper, we propose a caching assisted scheme alternative to routing in MANETs for the purpose of wildlife monitoring. Rather than deploying a routing protocol, data is collected and transported to and from a base station using a UAV. Although some literature exists on such an approach, we propose the use of intermediate caching between the mobile nodes and compare it to a baseline scenario where no caching is used. The paper puts forward our communication design where we have simulated the movement of multiple mobile sensor nodes in a field that move according to the Levy walk model imitating wildlife animal foraging and a UAV that makes regular trips across the field to collect data from them. The unmanned aerial vehicle can collect data not only from the current node it is communicating with but also data of other nodes that this node came into contact with. Simulations show that exchanging cached data is highly advantages as the drone can indirectly communicate with many more mobile nodes

Methods and Apparatus for Determining a Path in a Communication Network

United States Patent Filing No:United States Patent Filing No:United States Patent Filing No:Typically paths are provisioned in a network with a margin which allows for component variations and failures in the network and so on. By providing more information about the requirements of the link in a path request, it is possible to more efficiently calculate a route for the path through the network. The efficiency gain allows greater network utilization which in turn saves costs for the network service provider

Proposals on Kaplan–Meier plots in medical research and a survey of stakeholder views: KMunicate

OBJECTIVES: To examine reactions to the proposed improvements to standard Kaplan–Meier plots, the standard way to present time-to-event data, and to understand which (if any) facilitated better depiction of (1) the state of patients over time, and (2) uncertainty over time in the estimates of survival. DESIGN: A survey of stakeholders’ opinions on the proposals. SETTING: A web-based survey, open to international participation, for those with an interest in visualisation of time-to-event data. PARTICIPANTS: 1174 people participated in the survey over a 6-week period. Participation was global (although primarily Europe and North America) and represented a wide range of researchers (primarily statisticians and clinicians). MAIN OUTCOME MEASURES: Two outcome measures were of principal importance: (1) participants’ opinions of each proposal compared with a ‘standard’ Kaplan–Meier plot; and (2) participants’ overall ranking of the proposals (including the standard). RESULTS: Most proposals were more popular than the standard Kaplan–Meier plot. The most popular proposals in the two categories, respectively, were an extended table beneath the plot depicting the numbers at risk, censored and having experienced an event at periodic timepoints, and CIs around each Kaplan–Meier curve. CONCLUSION: This study produced a high response number, reflecting the importance of graphics for time-to-event data. Those producing and publishing Kaplan–Meier plots—both authors and journals—should, as a starting point, consider using the combination of the two favoured proposals

World TB Day 2016: an interview with leading experts in tuberculosis research.

In this interview, we talk to leading tuberculosis (TB) experts from University College London and the London School of Hygiene and Tropical Medicine about the current challenges in TB research. The video of this interview is available here: https://www.youtube.com/watch?v=75Die7MQBec&feature=youtu.be . The video can also be downloaded via Additional file 1

Exploiting Delay Budget Flexibility for Efficient Group Delivery in the Internet of Things

Further accelerated by the Internet of Things (IoT) concept, various devices are being continuously introduced into diverse application scenarios. To achieve unattended updates of IoT smart object(s), there remains a challenging problem concerning how to efficiently deliver messages to specific groups of target nodes, especially considering node mobility. In this paper, the relay selection problem is investigated on the basis of directional movement with randomness (e.g. typically associated with the searching or migrating behaviour of animals). Unlike numerous works tackling one-to-one communication, we focus on efficient group delivery (one-to-many). A two-level delay budget model is considered to reflect the flexibility of delay tolerance, which brings potential efficiency gains for group delivery compared with using a single budget boundary. Following the description of the system model, a combinatorial bi-objective optimisation problem is formulated and solutions are proposed. Simulation results show that the greedy algorithm can achieve comparable performance to an evolutionary algorithm when the delivery satisfaction outweighs efficiency. Furthermore, we show that our proposed greedy scheme can outperform the state-of-theart when the delivery efficiency becomes increasingly important

Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion

How to democratize Internet of Things devices. A participatory design research

The global introduction of affordable Internet of Things (IoT) devices offers an opportunity to empower a large variety of users with different needs. However, many off-the-shelf digital products are still not widely adopted by people who are hesitant technology users or by older adults, notwithstanding that the design and user-interaction of these devices is recognized to be user-friendly. In view of the potential of IoT-based devices, how can we reduce the obstacles of a cohort with low digital literacy and technology anxiety and enable them to be equal participants in the digitalized world? This article shows the method and results achieved in a community-stakeholder workshop, developed through the participatory design methodology, aiming at brainstorming problems and scenarios through a focus group and a structured survey. The research activity focused on understanding factors to increase the usability of off-the-shelf IoT devices for hesitant users and identify strategies for improving digital literacy and reducing technology anxiety. A notable result was a series of feedback items pointing to the importance of creating learning resources to support individuals with different abilities, age, gender expression, to better adopt off-the-shelf IoT-based solutions.Comment: 8 pages, 5 figure

Effect of Changes in Body Mass Index on the Risk of Cardiovascular Disease and Diabetes Mellitus in HIV-Positive Individuals: Results From the D:A:D Study

BACKGROUND: Weight gain is common among people with HIV once antiretroviral treatment (ART) is commenced. We assess the effect of changes in body mass index (BMI), from different baseline BMI levels, on the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). METHODS: D:A:D participants receiving ART were followed from their first BMI measurement to the first of either CVD or DM event, or earliest of 1/2/2016 or 6 months after last follow-up. Participants were stratified according to their baseline BMI, and changes from baseline BMI were calculated for each participant. Poisson regression models were used to assess the effects of changes on BMI on CVD or DM events. RESULTS: There were 2,104 CVD and 1,583 DM events over 365,287 and 354,898 person years (rate: CVD 5.8/1000 (95% CI 5.5-6.0); DM 4.5/1000 (95% CI 4.2 - 4.7)). Participants were largely male (74%), baseline mean age of 40 years and median BMI of 23.0 (IQR: 21.0-25.3). Risk of CVD by change in BMI from baseline, stratified by baseline BMI strata showed little evidence of an increased risk of CVD with an increased BMI in any baseline BMI strata. An increase in BMI was associated with an increased risk of DM across all baseline BMI strata. CONCLUSIONS: While increases in BMI across all levels of baseline BMI were not associated with an increased risk of CVD, such changes were consistently associated with increased risk of DM. There was also some evidence of an increased risk of CVD with a decrease in BMI