Subsea cable tracking in an uncertain environment using particle filters

Localization of subsea cables is a demanding and challenging task. Among the few methods reported in the literature, magnetic field detection is the most promising one, as the cable does not require to be seen visually. Magnetic noise and a quick attenuation of the magnetic field propagating in sea water often make available methods unreliable. The authors propose a novel method of using particle filters for estimating the position of a subsea cable in a highly uncertain environment. The method was tested on data collected from a buried cable in the Baltic Sea, Denmark and shown to have a close approximation to the true location of the subsea cable. The method can be used to localize a subsea cable in an offshore noisy and uncertain environment and provides an inexpensive alternative to the use of a diver or a remotely operated platform

Application of artificial neural networks to weighted interval Kalman filtering

The interval Kalman filter is a variant of the traditional Kalman filter for systems with bounded parametric uncertainty. For such systems, modelled in terms of intervals, the interval Kalman filter provides estimates of the system state also in the form of intervals, guaranteed to contain the Kalman filter estimates of all point-valued systems contained in the interval model. However, for practical purposes, a single, point-valued estimate of the system state is often required. This point value can be seen as a weighted average of the interval bounds provided by the interval Kalman filter. This article proposes a methodology based on the application of artificial neural networks by which an adequate weight can be computed at each time step, whereby the weighted average of the interval bounds approximates the optimal estimate or estimate which would be obtained using a Kalman filter if no parametric uncertainty was present in the system model, even when this is not the case. The practical applicability and robustness of the method are demonstrated through its application to the navigation of an uninhabited surface vehicle. © IMechE 2014

Non-linear control algorithms for an unmanned surface vehicle

Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design. © 2014 IMechE

Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle

Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possible to retrieve its six-degrees of freedom relative-pose in an easy way. To compensate interruption in the marker’s observations, an extended Kalman filter (EKF) estimates the current USV’s position with reference to the last known position. Validation experiments have been performed in a simulated environment under various marine conditions. The results confirmed that the EKF provides estimates accurate enough to direct the UAV in proximity of the autonomous vessel such that the marker becomes visible again. Using only the odometry and the inertial measurements for the estimation, this method is found to be applicable even under adverse weather conditions in the absence of the global positioning system

Subsea cable tracking by an unmanned surface vehicle

Subsea cable localisation is a demanding task that requires a lot of time, effort and expense. In the present paper the authors propose a methodology that is automated and inexpensive, based on magnetic detection from a small unmanned surface vehicle (USV) and the use of a batch particle filter (BPF) algorithm. A dynamic path planning algorithm for the USV is also developed so that adequate samples of the magnetic field readings can be gathered for processing by the BPF. All of these elements work together online as the cable is tracked, which was demonstrated in a simulated mission

Augmenting the 6-3-5 method with design information

This paper describes a comparative study between the 6-3-5 Method and the ICR Grid. The ICR Grid is an evolved variant of 6-3-5 intended to better integrate information into the concept generation process. Unlike a conventional 6-3-5 process where participants continually sketch concepts, using the ICR Grid (the name derived from its Inform, Create, Reflect activities and structured, grid-like output) participants are additionally required to undertake information search tasks, use specific information items for concept development, and reflect on the merit of concepts as the session progresses. The results indicate that although the quantity of concepts was lower, the use of information had a positive effect in a number of areas, principally the quality and variety of output. Although grounded in the area of product development, this research is applicable to any organisation undertaking idea generation and problem solving. As well as providing insights on the transference of information to concepts, it holds additional interest for studies on the composition and use of digital libraries

Multi-channel Transformers for Multi-articulatory Sign Language Translation

Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore. In this paper we tackle the multi-articulatory sign language translation task and propose a novel multi-channel transformer architecture. The proposed architecture allows both the inter and intra contextual relationships between different sign articulators to be modelled within the transformer network itself, while also maintaining channel specific information. We evaluate our approach on the RWTH-PHOENIX-Weather-2014T dataset and report competitive translation performance. Importantly, we overcome the reliance on gloss annotations which underpin other state-of-the-art approaches, thereby removing future need for expensive curated datasets

Archaeal and bacterial glycerol dialkyl glycerol tetraether (GDGT) lipids in environmental samples by high temperature-gas chromatography with flame ionisation and time-of-flight mass spectrometry detection

Archaeal isoprenoidal glycerol dibiphytanyl glycerol tetraether lipids (iGDGTs) and their non-isoprenoidal branched bacterial analogues (brGDGTs) have widespread applications in biogeochemistry and paleothermometry. Analysis of GDGTs usually involves separation using high performance liquid chromatography, typically coupled via atmospheric pressure chemical ionisation to mass spectrometric detection in selected ion-monitoring mode (HPLC–APCI-MS). However, reliable determination of ratios and, in particular, quantification by this technique, can be challenging due to differences in ionisation efficiencies of the various compounds. Quantification of GDGTs also relies on external calibration of the relative response to an internal standard with authenticated GDGTs, which are often not readily accessible. Here, we tested the suitability of high temperature gas chromatography with flame ionisation detection (HTGC-FID) for the determination of concentrations and tetraether lipid-based ratios in marine and terrestrial samples. For this, we identified GDGTs in environmental samples using HTGC coupled to time-of-flight mass spectrometry (HTGC–MS). Using a purified GDGT standard, we show we can quantify GDGT-0 in environmental samples by GC-FID. Some GDGT-based ratios measured by HTGC-FID exhibited a linear correlation (1:1) with ratios derived from HPLC–MS and weight-based ratios of mixtures of purified standards. However, ratios relying on minor isomers, such as TEX86 and MBT/CBT have many unresolved challenges for determination by HTGC. Detection limits were higher than for HPLC–MS. However, the advantages of employing HTGC-based methods include: (1) the independence from MS tuning-related differences in ionisation energies; (2) the potential for direct comparison with other, non-GDGT based biomarkers; and (3) a more complete insight into biomarker distributions in environmental samples by the extension of the temperature range. Quantitative elution of GDGTs from a HTGC column as demonstrated herein, will also enable their analysis by compound-specific isotope ratio mass spectrometry

Outcomes of a randomized controlled trial assessing a smartphone Application to reduce unmet needs among people diagnosed with CancEr (ACE)

© 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. Background: Smartphone technology represents an opportunity to deliver practical solutions for people affected by cancer at a scale that was previously unimaginable, such as information, appointment monitoring, and improved access to cancer support services. This study aimed to determine whether a smartphone application (app) reduced the unmet needs among people newly diagnosed with cancer. Methods: A single blind, multisite randomized controlled trial to determine the impact of an app-based, 4-month intervention. Newly diagnosed cancer patients were approached at three health service treatment clinics. Results: Eighty-two people were randomized (intervention; n = 43 and control; n = 39), average age was 59.5 years (SD: 12.9); 71% female; 67% married or in a de facto relationship. At baseline, there were no differences in participants’ characteristics between the groups. No significant effects, in reducing unmet needs, were demonstrated at the end of intervention (4-month) or 12-month follow-up. Overall, 94% used the app in weeks 1-4, which decreased to 41% in weeks 13-16. Mean app use time per participant: Cancer Information, 6.9 (SD: 18.9) minutes; Appointment Schedule, 5.1 (SD: 9.6) minutes; Cancer Services 1.5 minutes (SD: 6.8); Hospital Navigation, 1.4 (SD: 2.8) minutes. Conclusions: Despite consumer involvement in the design of this smartphone technology, the app did not reduce unmet needs. This may have been due to the study being underpowered. To contribute to a meaningful understanding and improved implementation of smartphone technology to support people affected by cancer, practical considerations, such as recruitment issues and access to, and confidence with, apps, need to be considered. Australian New Zealand Clinical Trials Registration (ACTRN) Trial Registration: 12616001251415; WEF 7/9/2016