1,112 research outputs found

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

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    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

    Smart Data Harvesting in Cache-Enabled MANETs: UAVs, Future Position Prediction, and Autonomous Path Planning

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    The task of gathering data from nodes within mobile ad-hoc wireless sensor networks presents an enduring challenge. Conventional strategies employ customized routing protocols tailored to these environments, with research focused on refining them for improved efficiency in terms of throughput and energy utilization. However, these elements are interconnected, and enhancements in one often come at the expense of the other. An alternative data collection approach involves the use of Unmanned Aerial Vehicles (UAVs). In contrast to traditional methods, UAVs directly collect data from mobile nodes, bypassing the need for routing. While existing research predominantly addresses static nodes, this paper proposes an evolutionary based, innovative path selection approach based on future position prediction of caching enabled mobile ad-hoc wireless sensor network nodes for UAV data collection, aimed at maximizing node encounters and gathering the most valuable information in a single trip. The proposed technique is evaluated for different movement models and parameter configurations

    Methods and Apparatus for Determining a Path in a Communication Network

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    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

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    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.

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    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

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    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

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    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

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    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
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