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Utilising visual attention cues for vehicle detection and tracking
No full textAdvanced Driver-Assistance Systems (ADAS) have been attracting attention from many researchers. Vision-based sensors are the closest way to emulate human driver visual behaviour while driving. In this paper, we explore possible ways to use visual attention (saliency) for object detection and tracking. We investigate: 1) How a visual attention map such as a subjectness attention or saliency map and an objectness attention map can facilitate region proposal generation in a 2- stage object detector; 2) How a visual attention map can be used for tracking multiple objects. We propose a neural network that can simultaneously detect objects as and generate objectness and subjectness maps to save computational power. We further exploit the visual attention map during tracking using a sequential Monte Carlo probability hypothesis density (PHD) filter. The experiments are conducted on KITTI and DETRAC datasets. The use of visual attention and hierarchical features has shown a considerable improvement of ≈8% in object detection which effectively increased tracking performance by ≈4% on KITTI dataset
Radiotherapy, immunotherapy, and the tumour microenvironment: Turning an immunosuppressive milieu into a therapeutic opportunity
No full textImmune checkpoint blockade (ICB) has revolutionised the treatment of solid tumours, yet most patients do not derive a clinical benefit. Resistance to ICB is often contingent on the tumour microenvironment (TME) and modulating aspects of this immunosuppressive milieu is a goal of combination treatment approaches. Radiation has been used for over a century in the management of cancer with more than half of all cancer patients receiving radiotherapy. Here, we outline the rationale behind combining radiotherapy with ICB, a potential synergy through mutually beneficial remodelling of the TME. We discuss the pleiotropic effects radiation has on the TME including immunogenic cell death, activation of cytosolic DNA sensors, remodelling the stroma and vasculature, and paradoxical infiltration of both anti-tumour and suppressive immune cell populations. These events depend on the radiation dose and fractionation and optimising these parameters will be key to develop safe and effective combination regimens. Finally, we highlight ongoing efforts that combine radiation, immunotherapy and inhibitors of DNA damage response, which can help achieve a favourable equilibrium between the immunogenic and tolerogenic effects of radiation on the immune microenvironment
An evaluation of a proposed approach for overcoming the environmental and economic challenges of anaerobic digestion process through the production of more bio-products
No full textThe transformation to renewable energy has become a requirement nowadays. Thermoplastic starch (TPS) is a type of bio-plastic. Its quality and properties are examined by employing mechanical, physical, and other tests. Despite the proven advantages of using anaerobic digestion (AD) for the conversion of biomass into biogas and the developments on it, there still exist some environmental and economical challenges limiting prosperity and sustainability of AD. Economically, compared to fossil fuel market, biogas, which is the only major product of AD, is not competitive enough compared to the prices of its counterparts.
With the aid of Design Expert software, the present study mainly aims to design and implement an integrated approach so as to potentially overcome these challenges and to make the AD more desirable. The approach incorporates the AD process with the process of producing TPS to form; biogas, bio-slurry and TPS/mango fibre bio-plastic sheet, from the residues of three starchy biomass: potato, mango and avocado. A Hollander Beater was employed as a multi-functional device, to: pre-treat the biomass, isolate the starch and to process mango seed coats. The study found that, the highest energy gain per gram of volatile solids of potato residues was 62.9% at 35 ⁰C, 1.62 g-VS organic concentration and 50% sludge concentration, which yielded a maximum CH4% of 72.4%. While, the highest energy gain by the gram of volatile solids of mango and avocado residues were 65% and 16.5% which yielded a maximum CH4% of 62.4% and 60.9% respectively. The production of a bioplastic sheet with a dimension of 2440*1220*3.2 mm has the same specifications of the optimal bio-plastic sheet produced, resulting in a cost efficiency of up to 65%. To achieve this approximately 353.7 kg potato, 89.9 kg mango and 173.7 kg avocado requires processing.
Therefore the proposed study has achieved its main aim. Economically, this was achieved as a result of an excess amount of the bio-energy been produced (approximately 29%) of the total bio-energy produced. Regarding the environmental challenges which mainly depend on the accumulation of large amounts of the generated digestate, the study has confirmed the biofertiliser potential of the digestate with a suggestion to carry out more tests to confirm its quality and increase the reliability. Countries such as Saudi Arabia which is emerging in this field, can greatly benefit from this study via identifying the obstacles, tackling and avoiding them to improve profitability
Community-based exercise rehabilitation in a diverse chronic disease population
No full textThe effectiveness of physical activity (PA) for reducing the morbidity and mortality in individuals with chronic disease (CD) has been widely established. CD populations participate in lower levels of PA than their healthy counterparts. Currently research has focused on individual disease cohorts and limited evidence exists investigating levels of PA and SB in a mixed CD population. Study I used a cross-sectional study design to evaluate total daily PA and SB in men and women (62.98 ± 10.99 yr and 50.6% men) with a variety of CDs and examined the association between these behaviours and selected health indices. Participants spent 9.5 h.day-1, 4.1 h.day-1, 1.4 h.day-1, and 0.3 h.day-1 sedentary, standing, in light intensity PA (LIPA) and moderate to vigorous intensity PA (MVPA), respectively and on average took 6713 steps per day. The majority of SB was accumulated in bouts lasting ≥ 30 min. A higher daily step count was associated with more favourable measures of body composition, aerobic fitness and self-rated health. Increased daily sedentary time was associated with less favourable lower body strength. These findings highlighted that individuals with CD, regardless of specific condition, are a target cohort for intervention. Community-based exercise rehabilitation (CBER) programs have the potential to improve health outcomes in CD groups by increasing PA levels and reducing sedentary behaviour (SB). Historically such programs have involved single CDs. Given the similar programme design and the growing prevalence of multimorbidity (MM), an integrated model may be more suitable. MedEx Wellness is a novel CBER service in Ireland, which offers a shared programme to a range of CDs. In study II a quasi-experimental design was used to investigate the effects of a CBER program on levels of PA, SB and selected health indices, in men and women with a variety of CDs. There were significant improvements in LIPA, patterns of SB, physical function, body composition and psychological health following participation in a CBER program. A higher attendance to the CBER program was associated with improvements in measures of LIPA, MVPA, step count, time in sedentary bouts > 60 min, physical function, body composition and psychological health and psychosocial determinants of PA. These findings demonstrate that CBER is an effective approach to increasing PA and improving health related outcomes for individuals with CD, however statistically significant findings often mask the range of inter-individual variability that exists within response to CBER. In study III factors associated with an effective response to participation in a CBER, in terms of a measurable change, in men and women with a variety of CDs were explored. For measures of LIPA, strength, body composition and psychological health, a lower baseline (BL) value increased the likelihood of achieving a measurable change. A higher cardiorespiratory fitness (CRF) level at BL, increased the likelihood of achieving a measurable change. Individuals with cancer were more likely to improve measures lower body strength. Individuals with metabolic disease and respiratory disease were less likely to improve measures of LIPA and psychological health, respectively. Individuals with CD participate in low levels of PA and accumulate high levels of SB. A shared CBER program is an effective approach to inducing change in PA, SB, physical function and psychological health in a CD cohort. Identifying factors associated with a non-response to CBER could optimise program design and delivery
Broadband RF-Input Continuous-Mode Load-Modulated Balanced Power Amplifier With Input Phase Adjustment
No full textThis article presents the theory and design methodology of broadband RF-input continuous-mode load-modulated balanced power amplifier (CM-LMBA) by introducing the CM output-matching networks in the LMBA architecture. It is illustrated that the CM impedance condition can be achieved by properly adjusting the phase difference between the different PA branches in the proposed CM-LMBA during the entire load modulation process. An RF-input CM-LMBA with 1.45-2.45-GHz bandwidth using commercial GaN transistors is designed and implemented to validate the proposed architecture. The fabricated CM-LMBA attains a measured 11.2-13.4-dB gain and around 40-W saturated power. Power-added efficiency (PAE) of 46.4%-56.5% and 43.2%-50.3% is achieved at 6- and 8-dB output power back-offs throughout the designed band. When driven by a 100-MHz OFDM signal with an 8-dB peak-to-average power ratio (PAPR), the proposed CM-LMBA achieves better than -46-dBc adjacent channel leakage ratio (ACLR) and higher than 45% average PAE after digital predistortion at 1.8 and 2.1 GHz.Science Foundation IrelandTrinity College Dublin (TCD
A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
No full textThe 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), Online, 5-10 July 2020Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation. However, there is a lack of datasets that realistically address such use cases at a scale large enough for training supervised models for this task. This work presents a new dataset for MDS that is large both in the total number of document clusters and in the size of individual clusters. We build this dataset by leveraging the Wikipedia Current Events Portal (WCEP), which provides concise and neutral human-written summaries of news events, with links to external source articles. We also automatically extend these source articles by looking for related articles in the Common Crawl archive. We provide a quantitative analysis of the dataset and empirical results for several state-of-the-art MDS techniques.Irish Research CouncilScience Foundation IrelandAylien Ltd
Background Knowledge Injection for Interpretable Sequence Classification
No full textThe 8th International New Frontiers in Mining Complex Patterns Workshop 2019, Wùzburg, Germany, 16 September 2019Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols. Although accuracy is paramount, in certain scenarios interpretability is a must. Unfortunately, such trade-off is often hard to achieve since we lack human-independent interpretability metrics. We introduce a novel sequence learning algorithm, that combines (i) linear classifiers - which are known to strike a good balance between predictive power and interpretability, and (ii) background knowledge embeddings. We extend the classic subsequence feature space with groups of symbols which are generated by background knowledge injected via word or graph embeddings, and use this new feature space to learn a linear classifier. We also present a new measure to evaluate the interpretability of a set of symbolic features based on the symbol embeddings. Experiments on human activity recognition from wearables and amino acid sequence classification show that our classification approach preserves predictive power, while delivering more interpretable models.Science Foundation Irelan
Adaptive multi-band negative-group-delay RF circuits with low reflection
No full textTwo classes of frequency-reconfigurable multi-band negative-group-delay (NGD) circuit networks that feature low-input-power-reflection capabilities are reported. They consist of lossy-complementary-diplexer architectures, in which the NGD properties are obtained within the stopband regions of their lossy multi-band bandstop-filter (BSF) channel. Their complementary lossy multi-band bandpass-filter (BPF) branch absorbs in its terminating resistor the RF-input-signal energy that is not transmitted by the lossy multi-band BSF channel within its stopbands. In this manner, the input-reflectionless/absorptive behavior is realized. The theoretical foundations of the devised lossy-multi-band-BSF-based NGD structures using a coupling-routing-diagram formalism and single-to-multi-band admittance transformations are described. For the first-order case as illustration, guidelines for the synthesis in the bandpass frequency domain are provided. Furthermore, the extension of these multi-band NGD approaches to higher-order and in-series-cascade multi-stage realizations for more-general and wider-band NGD patterning, as well as to two-port/symmetrical designs, is shown. In addition, the conception of multi-functional passive components with NGD characteristics, such as wide-band BPFs and power directional couplers with embedded NGD regions, is also addressed. For experimental-demonstration purposes, an electronically-reconfigurable microstrip prototype of a two-stage-in-series-cascade dual-band NGD circuit is manufactured and measured
Drive-by Bridge Health Monitoring Using Multiple Passes and Machine Learning
No full textThis paper studies a machine learning algorithm for bridge damage detection using the responses measured on a passing vehicle. A finite element (FE) model of vehicle bridge interaction (VBI) is employed for simulating the vehicle responses. Several vehicle passes are simulated over a healthy bridge using random vehicle speeds. An artificial neural network (ANN) is trained using the frequency spectrum of the responses measured on multiple vehicle passes over a healthy bridge where the vehicle speed is available. The ANN can predict the frequency spectrum of any passes using the vehicle speed. The prediction error is then calculated using the differences between the predicated and measured spectrums for each passage. Finally, a damage indicator is defined using the changes in the distribution of the prediction errors versus vehicle speeds. It is shown that the distribution of the prediction errors is low when the bridge condition is healthy. However, in presence of a damage on the bridge, a recognisable change in the distribution will be observed. Several data sets are generated using the healthy and damaged bridges to evaluate the performance of the algorithm in presence of road roughness profile and measurement noise. In addition, the impacts of the training set size and frequency range to the performance of the algorithm are investigated
Design considerations for composite cylindrical shells on elastic foundations subject to compression buckling
No full textElastic boundary conditions play an important role in the buckling analysis of cylinders under compressive
loading. These structures are used widely in aerospace applications and are highly sensitive to geometrical,
material, loading, and boundary imperfections. In fact, the presence of these imperfections can lead to catastrophic failure. In 1968, NASA reported relations for obtaining the Knockdown Factor (KDF) based on an
empirical method that is valid for isotropic and orthotropic materials; however, these relations do not consider
the effect of elastic boundaries that can lead to highly conservative values of KDF. In design practice, a universal KDF of 0.65 has been used for recent designs by NASA, which may not be applicable to new types of structural configuration with different loading and boundary conditions. Therefore, there is a need for robust design
factors for future designs which reduce the dependency on testing during preliminary design phases and speeds
up the product development process. The availability of up‐to‐date and different KDF expressions for different
structural configurations would help engineers to design lighter structures with improved load carrying capacity and reliability. The main objective of this work is to identify the buckling load sensitivity of cylindrical
shells due to their boundary conditions and develop KDF relations considering elastic boundaries. To achieve
this goal, the effect of axial, radial and tangential support stiffness on a quasi‐isotropic cylinder under axial
compression is investigated. A data‐driven design approach is used to develop new KDF empirical relations
for a quasi‐isotropic cylinder on different elastic foundations. The accuracy of these relations is within 5%
for any elastic foundation considered