145 research outputs found
Map-aided navigation for emergency searches
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordReal-time positioning of emergency personnel has
been an active research topic for many years. However, studies on
how to improve navigation accuracy by using prior information
on the idiosyncratic motion characteristics of firefighters are
scarce. This paper presents an algorithm for generating pseudo
observations of position and orientation based on standard search
patterns used by firefighters. The iterative closest point algorithm
is used to compare walking trajectories estimated from inertial
odometry with search patterns generated from digital maps. The
resulting fitting errors are then used to integrate the pseudo
observations into a map-aided navigation filter. Specifically, we
present a sequential Monte Carlo solution where the pattern
comparison is used to both update particle weights and create
new particle samples. Experimental results involving professional
firefighters demonstrate that the proposed pseudo observations
can achieve a stable localization error of about one meter, and
offer increased robustness in the presence of map errors
3D Object reconstruction from a single depth view with adversarial learning
In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial networks. Unlike the existing work which typically requires multiple views of the same object or class labels to recover the full 3D geometry, the proposed 3D-RecGAN only takes the voxel grid representation of a depth view of the object as input, and is able to generate the complete 3D occupancy grid by filling in the occluded/missing regions. The key idea is to combine the generative capabilities of autoencoders and the conditional Generative Adversarial Networks (GAN) framework, to infer accurate and fine-grained 3D structures of objects in high-dimensional voxel space. Extensive experiments on large synthetic datasets show that the proposed 3D-RecGAN significantly outperforms the state of the art in single view 3D object reconstruction, and is able to reconstruct unseen types of objects. Our code and data are available at: https://github.com/Yang7879/3D-RecGAN
DeepTIO: a deep thermal-inertial odometry with visual hallucination
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordVisual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fail. Thermal cameras are commonly used for perception and inspection when the environment has low visibility. However, their use in odometry estimation is hampered by the lack of robust visual features. In part, this is as a result of the sensor measuring the ambient temperature profile rather than scene appearance and geometry. To overcome this issue, we propose a Deep Neural Network model for thermal-inertial odometry (DeepTIO) by incorporating a visual hallucination network to provide the thermal network with complementary information. The hallucination network is taught to predict fake visual features from thermal images by using Huber loss. We also employ selective fusion to attentively fuse the features from three different modalities, i.e thermal, hallucination, and inertial features. Extensive experiments are performed in hand-held and mobile robot data in benign and smoke-filled environments, showing the efficacy of the proposed model
Rancang Bangun Alat Pereduksi Particulate Matter (PM) Gas Buang Mesin Diesel Dengan Metode Cyclone
Gas buang dari hasil proses pembakaran berpengaruh terhadap pencemaran udara dan lingkungan khususnya motor diesel. Proses pembakaran bahan bakar pada motor bakar menghasilkan gas buang yang mengandung unsur Nitrogen Oksida (NOx), Sulfur Oksida (SOx), Particulate Matter (PM), Karbon Monoksida (CO), dan Hidrokarbon (HC) yang bersifat mencemari udara. Agar motor diesel yang digunakan tidak mengakibatkan pencemaran udara berlebih, perlu dilakukan suatu penelitian menurunkan emisi gas buang motor diesel dengan pemilihan teknologi dan metode yang tepat. Penelitian cylone separator ini berdasarkan prinsip kerja separator yang memanfaatkan gaya sentrifugal dan perbedaan massa jenis. Karena massa jenis PM lebih besar dari pada massa jenis gas buang, PM akan terpisah dari gas buang karena gaya sentrifugal dan adanya perbedaan massa jenis. Pada tahap awal penelitian ini yaitu dibuat desain dan kemudian dilakukan CFD analisis untuk dicari yang paling efisien dari segi kecepatan dan jenis aliran. Pada hasil analisa CFD disimpulkan bahwa metode Perry lebih efisien dibanding 3 metode yang lain. Setelah didapat desain yang efisien maka dilanjutkan dengan pembuatan prototipe, untuk selanjutnya dilakukan uji ekperimen. Berdasar uji eksperimen, cyclone separator dapar mereduksi PM gas Buang motor diesel pada beban 2000 watt sebesar 8,71%. Sedangkan pada beban 2500 watt, cylone separator dapat mereduksi PM sebesar 34,49%
Mammography screening: views from women and primary care physicians in Crete
Background: Breast cancer is the most commonly diagnosed cancer among women and a leading cause of death from cancer in women in Europe. Although breast cancer incidence is on the rise worldwide, breast cancer mortality over the past 25 years has been stable or decreasing in some countries and a fall in breast cancer mortality rates in most European countries in the 1990s was reported by several studies, in contrast, in Greece have not reported these favourable trends. In Greece, the age-standardised incidence and mortality rate for breast cancer per 100.000 in 2006 was 81,8 and 21,7 and although it is lower than most other countries in Europe, the fall in breast cancer mortality that observed has not been as great as in other European countries. There is no national strategy for screening in this country. This study reports on the use of mammography among middleaged women in rural Crete and investigates barriers to mammography screening encountered by women and their primary care physicians.
Methods: Design: Semi-structured individual interviews. Setting and participants: Thirty women between 45â65
years of age, with a mean age of 54,6 years, and standard deviation 6,8 from rural areas of Crete and 28 qualified
primary care physicians, with a mean age of 44,7 years and standard deviation 7,0 serving this rural population.
Main outcome measure: Qualitative thematic analysis.
Results: Most women identified several reasons for not using mammography. These included poor knowledge
of the benefits and indications for mammography screening, fear of pain during the procedure, fear of a serious
diagnosis, embarrassment, stress while anticipating the results, cost and lack of physician recommendation.
Physicians identified difficulties in scheduling an appointment as one reason women did not use mammography
and both women and physicians identified distance from the screening site, transportation problems and the
absence of symptoms as reasons for non-use.
Conclusion: Women are inhibited from participating in mammography screening in rural Crete. The provision
of more accessible screening services may improve this. However physician recommendation is important in
overcoming women's inhibitions. Primary care physicians serving rural areas need to be aware of barriers
preventing women from attending mammography screening and provide women with information and advice in a sensitive way so women can make informed decisions regarding breast caner screening
An active-radio-frequency-identification system capable of identifying co-locations and social-structure: Validation with a wild free-ranging animal
Abstract
Behavioural events that are important for understanding sociobiology and movement ecology are often rare, transient and localised, but can occur at spatially distant sites e.g. territorial incursions and coâlocating individuals. Existing animal tracking technologies, capable of detecting such events, are limited by one or more of: battery life; data resolution; location accuracy; data security; ability to coâlocate individuals both spatially and temporally. Technology that at least partly resolves these limitations would be advantageous. European badgers (Meles meles L.), present a challenging testâbed, with extraâgroup paternity (apparent from genotyping) contradicting established views on rigid group territoriality with little socialâgroup mixing.
In a proof of concept study we assess the utility of a fully automated activeâradioâfrequencyâidentification (aRFID) system combining badgerâborne aRFIDâtags with static, wirelesslyânetworked, aRFIDâdetector baseâstations to record badger coâlocations at setts (burrows) and near notional border latrines. We summarise the time badgers spent coâlocating within and between socialâgroups, applying network analysis to provide evidence of coâlocation based community structure, at both these scales.
The aRFID system coâlocated animals within 31.5Â m (adjustable) of baseâstations. Efficient radio transmission between aRFIDs and baseâstations enables a 20Â g tag to last for 2â5Â years (depending on transmission interval). Data security was high (data stored off tag), with remote access capability. Badgers spent most coâlocation time with members of their own socialâgroups at setts; remaining coâlocation time was divided evenly between intraâ and interâsocialâgroup coâlocations near latrines and interâsocialâgroup coâlocations at setts. Network analysis showed that 20â100% of tracked badgers engaged in interâsocialâgroup mixing per week, with evidence of transâborder superâgroups, that is, badgers frequently transgressed notional territorial borders.
aRFID occupies a distinct niche amongst established tracking technologies. We validated the utility of aRFID to identify coâlocations, socialâstructure and interâgroup mixing within a wild badger population, leading us to refute the conventional view that badgers (socialâgroups) are territorial and to question management strategies, for controlling bovine TB, based on this model. Ultimately aRFID proved a versatile system capable of identifying socialâstructure at the landscape scale, operating for years and suitable for use with a range of species.
EPSRC WILDSENSING projec
Efficient Data Propagation in Traffic-Monitoring Vehicular Networks.
Road congestion and traffic-related pollution have a large negative social and economic impact on several economies worldwide. We believe that investment in the monitoring, distribution, and processing of traffic information should enable better strategic planning and encourage better use of public transport, both of which would help cut pollution and congestion. This paper investigates the problem of efficiently collecting and disseminating traffic information in an urban setting. We formulate the traffic data acquisition problem and explore solutions in the mobile sensor network domain while considering realistic application requirements. By leveraging existing infrastructure such as traveling vehicles in the city, we propose traffic data dissemination schemes that operate on both the routing and the application layer; our schemes are frugal in the use of the wireless medium, rendering our system interoperable with the proliferation of competing applications. We introduce the following two routing algorithms for vehicular networks that aim at minimizing communication and, at the same time, adhering to a delay threshold set by the application: 1) delay-bounded greedy forwarding and 2) delay-bounded minimum-cost forwarding. We propose a framework that jointly optimizes the two key processes associated with monitoring traffic, i.e., data acquisition and data delivery, and provide a thorough experimental evaluation based on realistic vehicular traces on a real city map. © 2006 IEEE
Delay-bounded routing in vehicular ad-hoc networks.
Ad hoc networks formed by traveling vehicles are envisaged to become a common platform that will support a wide variety of applications, ranging from road safety to advertising and entertainment. The multitude of vehicular applications calls for routing schemes that satisfy user-defined delay requirements while at the same time maintaining a low level of channel utilization to allow their coexistence. This paper focuses on the development of carry-and-forward schemes that attempt to deliver data from vehicles to fixed infrastructure nodes in an urban setting. The proposed algorithms leverage local or global knowledge of traffic statistics to carefully alternate between the Data Muling and Multihop Forwarding strategies, in order to minimize communication overhead while adhering to delay constraints imposed by the application. We provide an extensive evaluation of our schemes using realistic vehicular traces on a real city map. Copyright 2008 ACM
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