Optimization of blasting design in open pit limestone mines with the aim of reducing ground vibration using robust techniques
- Authors: Rezaeineshat, Afsaneh , Monjezi, Masoud , Mehrdanesh, Amirhossein , Khandelwal, Manoj
- Date: 2020
- Type: Text , Journal article
- Relation: Geomechanics and Geophysics for Geo-Energy and Geo-Resources Vol. 6, no. 2 (2020), p.
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- Description: Blasting operations create significant problems to residential and other structures located in the close proximity of the mines. Blast vibration is one of the most crucial nuisances of blasting, which should be accurately estimated to minimize its effect. In this paper, an attempt has been made to apply various models to predict ground vibrations due to mine blasting. To fulfill this aim, 112 blast operations were precisely measured and collected in one the limestone mines of Iran. These blast operation data were utilized to construct the artificial neural network (ANN) model to predict the peak particle velocity (PPV). The input parameters used in this study were burden, spacing, maximum charge per delay, distance from blast face to monitoring point and rock quality designation and output parameter was the PPV. The conventional empirical predictors and multivariate regression analysis were also performed on the same data sets to study the PPV. Accordingly, it was observed that the ANN model is more accurate as compared to the other employed predictors. Moreover, it was also revealed that the most influential parameters on the ground vibration are distance from the blast and maximum charge per delay, whereas the least effective parameters are burden, spacing and rock quality designation. Finally, in order to minimize PPV, the developed ANN model was used as an objective function for imperialist competitive algorithm (ICA). Eventually, it was found that the ICA algorithm is able to decrease PPV up to 59% by considering burden of 2.9 m, spacing of 4.4 m and charge per delay of 627 Kg. © 2020, Springer Nature Switzerland AG.
Polytopes close to being simple
- Authors: Pineda-Villavicencio, Guillermo , Ugon, Julien , Yost, David
- Date: 2020
- Type: Text , Journal article
- Relation: Discrete and Computational Geometry Vol. 64, no. 1 (2020), p. 200-215
- Relation: http://purl.org/au-research/grants/arc/DP180100602
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- Description: It is known that polytopes with at most two nonsimple vertices are reconstructible from their graphs, and that d-polytopes with at most d- 2 nonsimple vertices are reconstructible from their 2-skeletons. Here we close the gap between 2 and d- 2 , showing that certain polytopes with more than two nonsimple vertices are reconstructible from their graphs. In particular, we prove that reconstructibility from graphs also holds for d-polytopes with d+ k vertices and at most d- k+ 3 nonsimple vertices, provided k
Pre-service teacher perceptions of LANTITE : complexity theory in action?
- Authors: Burke, Jenene , Sellings, Peter , Nelson, Naomi
- Date: 2020
- Type: Text , Book chapter
- Relation: Teacher Education in Globalised Times Chapter 8 p. 139-157
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Projected changes in ENSO-driven regional tropical cyclone tracks
- Authors: Bell, Samuel , Chand, Savin , Turville, Christopher
- Date: 2020
- Type: Text , Journal article
- Relation: Climate Dynamics Vol. 54, no. 3-4 (Feb 2020), p. 2533-2559
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- Description: Simulations and projections of the El Nino Southern Oscillation's (ENSO's) influence on TC track variability was analysed globally using Coupled Model Intercomparison project Phase 5 (CMIP5) models. The ability of these models to simulate the historical (1970-2000) ENSO-TC track relationship and inform us of the likely projected changes resulting from high carbon emissions (RCP8.5) in a climate projection (2070-2100) was determined through cluster analysis. The number of seasonal TC occurrences during traditional ENSO events ("El Nino" and "La Nina") in each cluster were used to determine whether each cluster was "El Nino dominant", "La Nina dominant" or "neither". Only seven out of a combined total of 28 clusters across all basins were found to disagree in terms of "ENSO dominance" between the observed records and historical model simulations. This suggests that models can simulate the ENSO and TC track relationship reasonably well. Under sustained high carbon emissions, La Nina TCs were projected to become dominant over El Nino TCs in the central South Indian Ocean ( 60-100 degrees E), the southern Bay of Bengal and over straight-moving TCs in the South China Sea. El Nino TCs were projected to increase and become dominant over La Nina TCs in a larger area of the western South Pacific ( 160 degrees E-165 degrees W) and central North Pacific ( 160 degrees E-145 degrees W) Oceans. Projections of track directions and lifetimes, while less robust, indicated that El Nino TCs would track westward more often in the Coral Sea (150-165 degrees E), while El Nino TCs that took an eastward track here would have longer lifetimes ( 3 days).
Refining Parkinson’s neurological disorder identification through deep transfer learning
- Authors: Naseer, Amina , Rani, Monai , Naz, Saeeda , Razzak, Muhammad , Imran, Muhammad , Xu, Guandong
- Date: 2020
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 32, no. 3 (2020), p. 839-854
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- Description: Parkinson’s disease (PD), a multi-system neurodegenerative disorder which affects the brain slowly, is characterized by symptoms such as muscle stiffness, tremor in the limbs and impaired balance, all of which tend to worsen with the passage of time. Available treatments target its symptoms, aiming to improve the quality of life. However, automatic diagnosis at early stages is still a challenging medicine-related task to date, since a patient may have an identical behavior to that of a healthy individual at the very early stage of the disease. Parkinson’s disease detection through handwriting data is a significant classification problem for identification of PD at the infancy stage. In this paper, a PD identification is realized with help of handwriting images that help as one of the earliest indicators for PD. For this purpose, we proposed a deep convolutional neural network classifier with transfer learning and data augmentation techniques to improve the identification. Two approaches like freeze and fine-tuning of transfer learning are investigated using ImageNet and MNIST dataset as source task independently. A trained network achieved 98.28% accuracy using fine-tuning-based approach using ImageNet and PaHaW dataset. Experimental results on benchmark dataset reveal that the proposed approach provides better detection of Parkinson’s disease as compared to state-of-the-art work. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Reusing artifact-centric business process models : a behavioral consistent specialization approach
- Authors: Yongchareon, Sira , Liu, Chengfei , Zhao, Xiaohui
- Date: 2020
- Type: Text , Journal article
- Relation: Computing Vol. 102, no. 8 (2020), p. 1843-1879
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- Description: Process reuse is one of the important research areas that address efficiency issues in business process modeling. Similar to software reuse, business processes should be able to be componentized and specialized in order to enable flexible process expansion and customization. Current activity/control-flow centric workflow modeling approaches face difficulty in supporting highly flexible process reuse, limited by their procedural nature. In comparison, the emerging artifact-centric workflow modeling approach well fits into these reuse requirements. Beyond the classic class level reuse in existing object-oriented approaches, process reuse faces the challenge of handling synchronization dependencies among artifact lifecycles as parts of a business process. In this article, we propose a theoretical framework for business process specialization that comprises an artifact-centric business process model, a set of methods to design and construct a specialized business process model from a base model, and a set of behavioral consistency criteria to help check the consistency between the two process models. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature.
Sequential sampling models without random between-trial variability : the racing diffusion model of speeded decision making
- Authors: Tillman, Gabriel , Van Zandt, Trish , Logan, Gordon
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Psychonomic Bulletin and Review Vol. 27, no. 5 (2020), p. 911-936
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- Description: Most current sequential sampling models have random between-trial variability in their parameters. These sources of variability make the models more complex in order to fit response time data, do not provide any further explanation to how the data were generated, and have recently been criticised for allowing infinite flexibility in the models. To explore and test the need of between-trial variability parameters we develop a simple sequential sampling model of N-choice speeded decision making: the racing diffusion model. The model makes speeded decisions from a race of evidence accumulators that integrate information in a noisy fashion within a trial. The racing diffusion does not assume that any evidence accumulation process varies between trial, and so, the model provides alternative explanations of key response time phenomena, such as fast and slow error response times relative to correct response times. Overall, our paper gives good reason to rethink including between-trial variability parameters in sequential sampling models. © 2020, The Psychonomic Society, Inc.
Soil chemical markers distinguishing human and pig decomposition islands : a preliminary study
- Authors: Barton, Philip , Reboldi, Anna , Dawson, Blake , Ueland, Maiken , Strong, Craig , Wallman, James
- Date: 2020
- Type: Text , Journal article
- Relation: Forensic Science, Medicine, and Pathology Vol. 16, no. 4 (2020), p. 605-612
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- Description: The decomposition of vertebrate cadavers on the soil surface produces nutrient-rich fluids that enter the soil profile, leaving clear evidence of the presence of a cadaver decomposition island. Few studies, however, have described soil physicochemistry under human cadavers, or compared the soil between human and non-human animal models. In this study, we sampled soil to 5 cm depth at distances of 0 cm and 30 cm from cadavers, as well as from control sites 90 cm distant, from five human and three pig cadavers at the Australian Facility for Taphonomic Experimental Research (AFTER). We found that soil moisture, electrical conductivity, nitrate, ammonium, and total phosphorus were higher in soil directly under cadavers (0 cm), with very limited lateral spread beyond 30 cm. These patterns lasted up to 700 days, indicating that key soil nutrients might be useful markers of the location of the decomposition island for up to 2 years. Soil phosphorus was always higher under pigs than humans, suggesting a possible difference in the decomposition and soil processes under these two cadaver types. Our preliminary study highlights the need for further experimental and replicated research to quantify variability in soil properties, and to identify when non-human animals are suitable analogues. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Some new characterizations of intrinsic transversality in hilbert spaces
- Authors: Thao, Nguyen , Bui, Hoa , Cuong, Nguyen , Verhaegen, Michel
- Date: 2020
- Type: Text , Journal article
- Relation: Set-Valued and Variational Analysis Vol. 28, no. 1 (2020), p. 5-39
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- Description: Motivated by a number of questions concerning transversality-type properties of pairs of sets recently raised by Ioffe and Kruger, this paper reports several new characterizations of the intrinsic transversality property in Hilbert spaces. New results in terms of normal vectors clarify the picture of intrinsic transversality, its variants and sufficient conditions for subtransversality, and unify several of them. For the first time, intrinsic transversality is characterized by an equivalent condition which does not involve normal vectors. This characterization offers another perspective on intrinsic transversality. As a consequence, the obtained results allow us to answer a number of important questions about transversality-type properties. © 2020, The Author(s).
Stability analysis for parameterized variational systems with implicit constraints
- Authors: Benko, Matus , Gfrerer, Helmut , Outrata, Jiri
- Date: 2020
- Type: Text , Journal article
- Relation: Set-Valued and Variational Analysis Vol. 28, no. 1 (2020), p. 167-193
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- Description: In the paper we provide new conditions ensuring the isolated calmness property and the Aubin property of parameterized variational systems with constraints depending, apart from the parameter, also on the solution itself. Such systems include, e.g., quasi-variational inequalities and implicit complementarity problems. Concerning the Aubin property, possible restrictions imposed on the parameter are also admitted. Throughout the paper, tools from the directional limiting generalized differential calculus are employed enabling us to impose only rather weak (non- restrictive) qualification conditions. Despite the very general problem setting, the resulting conditions are workable as documented by some academic examples. © 2019, The Author(s).
Stability prediction of Himalayan residual soil slope using artificial neural network
- Authors: Ray, Arunava , Kumar, Vikash , Kumar, Amit , Rai, Rajesh , Khandelwal, Manoj , Singh, T.
- Date: 2020
- Type: Text , Journal article
- Relation: Natural Hazards Vol. 103, no. 3 (2020), p. 3523-3540
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- Description: In the past decade, advances in machine learning (ML) techniques have resulted in developing sophisticated models that are capable of modelling extremely complex multi-factorial problems like slope stability analysis. The literature review indicates that considerable works have been done in slope stability using ML, but none of them covers the analysis of residual soil slope. The present study aims to develop an artificial neural network (ANN) model that can be employed for evaluating the factor of safety of Shiwalik Slopes in the Himalayan Region. Data obtained from numerical analysis of a residual soil slope were used to develop two ANN models (ANN1 and ANN2 utilising eleven input parameters, and scaled-down number of parameters based on correlation coefficient, respectively). A four-layer, feed-forward back-propagation neural network having the optimum number of hidden neurons is developed based on trial-and-error method. The results derived from ANN models were compared with those achieved from numerical analysis. Additionally, several performance indices such as coefficient of determination (R2), root mean square error, variance account for, and residual error were employed to evaluate the predictive performance of the developed ANN models. Both the ANN models have shown good prediction performance; however, the overall performance of the ANN2 model is better than the ANN1 model. It is concluded that the ANN models are reliable, valid, and straightforward computational tools that can be employed for slope stability analysis during the preliminary stage of designing infrastructure projects in residual soil slope. © 2020, Springer Nature B.V.
Subdifferential of the supremum via compactification of the index set
- Authors: Correa, Rafael , Hantoute, Abderrahim , López, Marco
- Date: 2020
- Type: Text , Journal article
- Relation: Vietnam Journal of Mathematics Vol. 48, no. 3 (2020), p. 569-588, http://purl.org/au-research/grants/arc/DP180100602
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- Description: We give new characterizations for the subdifferential of the supremum of an arbitrary family of convex functions, dropping out the standard assumptions of compactness of the index set and upper semi-continuity of the functions with respect to the index (J. Convex Anal. 26, 299–324, 2019). We develop an approach based on the compactification of the index set, giving rise to an appropriate enlargement of the original family. Moreover, in contrast to the previous results in the literature, our characterizations are formulated exclusively in terms of exact subdifferentials at the nominal point. Fritz–John and KKT conditions are derived for convex semi-infinite programming. © 2020, Vietnam Academy of Science and Technology (VAST) and Springer Nature Singapore Pte Ltd.
- Description: Funding details: Fondo Nacional de Desarrollo CientÃfico, Tecnológico y de Innovación Tecnológica, FONDECYT, PIA AFB-170001, 1190110, 1190012 Funding details: Universidad de Alicante, BEA- GAL 18/00205, PGC2018-097960-B-C21 Funding details: Australian Research Council, ARC, DP 180100602 Funding details: Comisión Nacional de Investigación CientÃfica y Tecnológica, CONICYT Funding details: Ministerio de Ciencia e Innovación, MICINN Funding text 1: Research supported by CONICYT (Fondecyt 1190012 and 1190110), Proyecto/Grant PIA AFB-170001, MICIU of Spain and Universidad de Alicante (Grant Beatriz Galindo BEA- GAL 18/00205), and Research Project PGC2018-097960-B-C21 from MICINN, Spain. The research of the third author is also supported by the Australian ARC - Discovery Projects DP 180100602
Subdifferentials and stability analysis of feasible set and pareto front mappings in linear multiobjective optimization
- Authors: Cánovas, Maria , López, Marco , Mordukhovich, Boris , Parra, Juan
- Date: 2020
- Type: Text , Journal article
- Relation: Vietnam Journal of Mathematics Vol. 48, no. 2 (2020), p. 315-334
- Relation: http://purl.org/au-research/grants/arc/DP180100602
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- Description: The paper concerns multiobjective linear optimization problems in
- Description: Funding details: European Commission, EC Funding details: European Regional Development Fund, FEDER Funding details: Australian Research Council, ARC Funding details: Australian Research Council, ARC, DP180100602 Funding details: Australian Research Council, ARC, DP-190100555 Funding details: Air Force Office of Scientific Research, AFOSR, 15RT04 Funding details: DMS-1512846, DMS-1808978 Funding text 1: This research has been partially supported by grants MTM2014-59179-C2-(1,2)-P and PGC2018-097960-B-C2(1,2) from MINECO/MICINN, Spain, and ERDF, “A way to make Europe”, European Union. Funding text 2: Research of the second author is also partially supported by the Australian Research Council (ARC) Discovery Grants Scheme (Project Grant # DP180100602). Funding text 3: Research of third author was partially supported by the USA National Science Foundation under grants DMS-1512846 and DMS-1808978, by the USA Air Force Office of Scientific Research grant #15RT04, and by Australian Research Council under grant DP-190100555.
The radius of metric subregularity
- Authors: Dontchev, Asen , Gfrerer, Helmut , Kruger, Alexander , Outrata, Jiri
- Date: 2020
- Type: Text , Journal article
- Relation: Set-Valued and Variational Analysis Vol. 28, no. 3 (2020), p. 451-473, http://purl.org/au-research/grants/arc/DP160100854
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- Description: There is a basic paradigm, called here the radius of well-posedness, which quantifies the “distance” from a given well-posed problem to the set of ill-posed problems of the same kind. In variational analysis, well-posedness is often understood as a regularity property, which is usually employed to measure the effect of perturbations and approximations of a problem on its solutions. In this paper we focus on evaluating the radius of the property of metric subregularity which, in contrast to its siblings, metric regularity, strong regularity and strong subregularity, exhibits a more complicated behavior under various perturbations. We consider three kinds of perturbations: by Lipschitz continuous functions, by semismooth functions, and by smooth functions, obtaining different expressions/bounds for the radius of subregularity, which involve generalized derivatives of set-valued mappings. We also obtain different expressions when using either Frobenius or Euclidean norm to measure the radius. As an application, we evaluate the radius of subregularity of a general constraint system. Examples illustrate the theoretical findings. © 2019, Springer Nature B.V.
- Description: Funding details: Austrian Science Fund, FWF, P26132-N25, P26640-N25, P29190-N32 Funding details: National Science Foundation, NSF Funding details: Australian Research Council, ARC Funding details: Australian Research Council, ARC, DP160100854 Funding details: Austrian Science Fund, FWF Funding details: Universiteit Stellenbosch, US, P26640-N25 P26132-N25, BodyRef/PDF/11228_2019_Article_523.pdf Funding details: Grantová Agentura
Thermal fragmentation as a possible, viable, alternative mining method in narrow vein mining?
- Authors: Bouwmeester, Patrick , Tuck, Michael , Koroznikova, Larissa , Durkin, Steve
- Date: 2020
- Type: Text , Journal article
- Relation: Mining, Metallurgy and Exploration Vol. 37, no. 2 (2020), p. 605-618
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- Description: In currently used mining methods, blasting techniques often causes dilution of valuable ore and results in costly processing requirements. In the context of narrow vein mining of thin and highly concentrated orebodies there is a need of a mining method that can reduce dilution in order to remain economically viable. This research project explored the viability of a new mining technology, thermal fragmentation, in narrow vein mining. Thermal fragmentation technology uses a flame jet to produce extreme heat that spalls the surrounding rock to a strategically located drill hole, as an alternative to traditional blasting. This paper creates a net present value (NPV) model of a mining method using thermal fragmentation, as well as for an existing method used for narrow vein mining; comparisons and evaluations were made regarding the feasibility of the new technology. It was found that while overall costs for thermal fragmentation were relatively high, reductions in wages, haulage and processing costs, as well as increased productivity and ore recovery, meant that the new method would improve the financial performance of any operation. These results identify that there is an opportunity to introduce the thermal fragmentation technology to narrow vein mines within Australia, in order to lower costs and increase profit. © 2019, Society for Mining, Metallurgy & Exploration Inc.
Thinking dispositions for teaching : enabling and supporting resilience in context
- Authors: McDonough, Sharon , McGraw, Amanda
- Date: 2020
- Type: Text , Book chapter
- Relation: Cultivating Teacher Resilience: International Approaches, Applications and Impact Chapter 5 p. 69-83
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- Description: Preparing pre-teachers for an increasingly challenging teaching profession is a complex work and requires teacher educators to engage in the careful design of both programmes and professional learning opportunities. This chapter explores how an explicit focus on thinking dispositions that enable effective teaching are developed in a Master of Teaching (Secondary) programme. This programme, delivered on-site at a secondary school, included carefully constructed teaching opportunities to support development of thinking dispositions. Ways of thinking and the impact they have on feelings, actions and beliefs will be examined along with how the implementation of our thinking dispositions framework supports the development of resilience in challenging teaching and learning contexts.
Autonomous adaptation to climate-driven change in marine biodiversity in a global marine hotspot
- Authors: Pecl, Gretta , Ogier, Emily , Jennings, Sarah , van Putten, Ingrid , Crawford, Christine , Fogarty, Hannah , Frusher, Stewart , Hobday, Alistair , Keane, John , Lee, Emma , MacLeod, Catriona , Mundy, Craig , Stuart-Smith, Jemima , Tracey, Sean
- Date: 2019
- Type: Text , Journal article
- Relation: Ambio Vol. 48, no. 12 (2019), p. 1498-1515
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- Description: While governments and natural resource managers grapple with how to respond to climatic changes, many marine-dependent individuals, organisations and user-groups in fast-changing regions of the world are already adjusting their behaviour to accommodate these. However, we have little information on the nature of these autonomous adaptations that are being initiated by resource user-groups. The east coast of Tasmania, Australia, is one of the world’s fastest warming marine regions with extensive climate-driven changes in biodiversity already observed. We present and compare examples of autonomous adaptations from marine users of the region to provide insights into factors that may have constrained or facilitated the available range of autonomous adaptation options and discuss potential interactions with governmental planned adaptations. We aim to support effective adaptation by identifying the suite of changes that marine users are making largely without government or management intervention, i.e. autonomous adaptations, to better understand these and their potential interactions with formal adaptation strategies. © 2019, Royal Swedish Academy of Sciences.
Calculus for directional limiting normal cones and subdifferentials
- Authors: Benko, Matúš , Gfrerer, Helmut , Outrata, Jiri
- Date: 2019
- Type: Text , Journal article
- Relation: Set-Valued and Variational Analysis Vol. 27, no. 3 (2019), p. 713-745
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- Description: The paper is devoted to the development of a comprehensive calculus for directional limiting normal cones, subdifferentials and coderivatives in finite dimensions. This calculus encompasses the whole range of the standard generalized differential calculus for (non-directional) limiting notions and relies on very weak (non-restrictive) qualification conditions having also a directional character. The derived rules facilitate the application of tools exploiting the directional limiting notions to difficult problems of variational analysis including, for instance, various stability and sensitivity issues. This is illustrated by some selected applications in the last part of the paper.
DINE : a framework for deep incomplete network embedding
- Authors: Hou, Ke , Liu, Jiaying , Peng, Yin , Xu, Bo , Lee, Ivan , Xia, Feng
- Date: 2019
- Type: Text , Conference paper
- Relation: 32nd Australasian Joint Conference on Artificial Intelligence, AI 2019 Vol. 11919 LNAI, p. 165-176
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- Description: Network representation learning (NRL) plays a vital role in a variety of tasks such as node classification and link prediction. It aims to learn low-dimensional vector representations for nodes based on network structures or node attributes. While embedding techniques on complete networks have been intensively studied, in real-world applications, it is still a challenging task to collect complete networks. To bridge the gap, in this paper, we propose a Deep Incomplete Network Embedding method, namely DINE. Specifically, we first complete the missing part including both nodes and edges in a partially observable network by using the expectation-maximization framework. To improve the embedding performance, we consider both network structures and node attributes to learn node representations. Empirically, we evaluate DINE over three networks on multi-label classification and link prediction tasks. The results demonstrate the superiority of our proposed approach compared against state-of-the-art baselines. © 2019, Springer Nature Switzerland AG.
- Description: E1
Hierarchical colour image segmentation by leveraging RGB channels independently
- Authors: Tania, Sheikh , Murshed, Manzur , Teng, Shyh , Karmakar, Gour
- Date: 2019
- Type: Text , Conference paper
- Relation: 9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019 Vol. 11854 LNCS, p. 197-210
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- Description: In this paper, we introduce a hierarchical colour image segmentation based on cuboid partitioning using simple statistical features of the pixel intensities in the RGB channels. Estimating the difference between any two colours is a challenging task. As most of the colour models are not perceptually uniform, investigation of an alternative strategy is highly demanding. To address this issue, for our proposed technique, we present a new concept for colour distance measure based on the inconsistency of pixel intensities of an image which is more compliant to human perception. Constructing a reliable set of superpixels from an image is fundamental for further merging. As cuboid partitioning is a superior candidate to produce superpixels, we use the agglomerative merging to yield the final segmentation results exploiting the outcome of our proposed cuboid partitioning. The proposed cuboid segmentation based algorithm significantly outperforms not only the quadtree-based segmentation but also existing state-of-the-art segmentation algorithms in terms of quality of segmentation for the benchmark datasets used in image segmentation. © 2019, Springer Nature Switzerland AG.