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Texture based vein biometrics for human identification : A comparative study

  • Authors: Bashar, Khayrul , Murshed, Manzur
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: 42nd IEEE Computer Software and Applications Conference, COMPSAC 2018; Tokyo, Japan; 23rd-27th July 2018 Vol. 2, p. 571-576
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  • Description: Hand vein biometric is an important modality for human authentication and liveness detection in many applications. Reliable feature extraction is vital to any biometric system. Over the past years, two major categories of vein features, namely vein structures and vein image textures, were proposed for hand dorsal vein based biometric identification. Of them, texture features seem important as it can combine skin micro-textures along with vein properties. In this study, we have performed a comparative study to identify potential texture features and feature-classifier combination that produce efficient vein biometric systems. Seven texture features (HOG, GABOR, GLCM, SSF, DWT, WPT, and LBP) and three multiclass classifiers (LDA, ESVM, and KNN) were explored towards the supervised identification of human from vein images. An experiment with 400 infrared (IR) hand images from 40 adults indicates the superior performance of the histogram of oriented gradients (HOG) and simple local statistical feature (SSF) with LDA and ESVM classifiers in terms of average accuracy (> 90%), average Fscore (> 58%) and average specificity (>93%). The decision-level fusion of the LDA and ESVM classifier with single texture features showed improved performances (by 2.2 to 13.2% of average Fscore) over individual classifier for human identification with IR hand vein images.
  • Description: Proceedings - International Computer Software and Applications Conference

Model of ICT adoption: A framework for value creation in East Java SME agribusiness enterprise (EJ-SMAES)

  • Authors: Sudaryanto, Yanto , Courvisanos, Jerry , Soekartawi, IR
  • Date: 2007
  • Type: Text , Conference proceedings
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  • Description: The aim of this paper is to demonstrate the importance of technological investment as an innovation creates benefits either in macro and micro economics. In particular, adopting information and communication technology (ICT) for East Java's SMAES can create value within the agribusiness sub-systems by digitalized coordination.

Adaptive sliding-mode dynamic controller for nonholonomic mobile robots

  • Authors: Amer, Ahmed , Sallam, Elsayed , Sultan, Ibrahim
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: ICENCO 2016 : 12th International Computer Engineering Conference (ICENCO) "Boundless smart societies" ; 2016, Egypt; 28th-29th Dec. 2016 p. 230-235
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  • Description: This paper presents a proposed adaptive technique for nonholonomic wheeled mobile robot (NWMR) using the sliding-mode control (SMC) method. The proposed control system based on the backstepping kinematic controller and PI sliding mode dynamic control. With an adaptive fuzzy logic to adjust adaptation gain of SMC for trajectory tracking control of nonholonomic mobile robot. Parametric and nonparametric uncertainties of mobile robot can be solved by using the proposed control which take advantages of stability and robustness in sliding mode control. The adaptation gain of SMC is adjusted by using Mamdani type inference system with adaptive tuning algorithm, which improves the adaptability for uncertainness and eliminate input chattering of the SMC. The stability and convergence of the control system are proved using Lypanouve criteria, and the comparison of the proposed controller with the other controllers ensures the validity and superiority of my own controller

Modeling the particle breakage by using combined DEM and SBFEM

  • Authors: Luo, Tao , Ooi, Ean Hin , Chan, Andrew , Fu, Shaojun
  • Date: 2017
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 7th International Conference on Discrete Element Methods, DEM7 2016; Dalian, China; 1st-4th August 2016; published in Springer Proceedings in Physics Vol. 188, p. 281-288
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  • Description: A novel computational method is developed in this study through the coupling of the discrete element method (DEM) and the scaled boundary finite element method (SBFEM). The objective of the developed technique is to model the particle breakage phenomenon in granular materials. This method models individual grains as single star-convex arbitrary sided polygons. The DEM is used to resolve the dynamics of each grain whereas the SBFEM is used to determine its corresponding stress state after a DEM analysis. The flexibility of both the SBFEM and DEM enable the grains to be formulated on arbitrary sided polygons so that the morphology of each grain to be replicated using only a single polygon. Grain breakage condition is determined if the stress state in a polygon satisfies a mechanically driven criterion e.g. the Hoek-Brown criterion is used. Once the breakage condition is detected, the resulting grain is split into two separate polygons. The resulting new polygons are directly modelled by the DEM and SBFEM without any change to the formulation. The feasibility of the developed method is demonstrated using a numerical example. © Springer Science+Business Media Singapore 2017.
  • Description: Springer Proceedings in Physics

OFFER: A Motif Dimensional Framework for Network Representation Learning

  • Authors: Yu, Shuo , Xia, Feng , Xu, Jin , Chen, Zhikui , Lee, Ivan
  • Date: 2020
  • Type: Text , Conference proceedings
  • Relation: 29th ACM International Conference on Information and Knowledge Management, CIKM 2020 p. 3349-3352
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  • Description: Aiming at better representing multivariate relationships, this paper investigates a motif dimensional framework for higher-order graph learning. The graph learning effectiveness can be improved through OFFER. The proposed framework mainly aims at accelerating and improving higher-order graph learning results. We apply the acceleration procedure from the dimensional of network motifs. Specifically, the refined degree for nodes and edges are conducted in two stages: (1) employ motif degree of nodes to refine the adjacency matrix of the network; and (2) employ motif degree of edges to refine the transition probability matrix in the learning process. In order to assess the efficiency of the proposed framework, four popular network representation algorithms are modified and examined. By evaluating the performance of OFFER, both link prediction results and clustering results demonstrate that the graph representation learning algorithms enhanced with OFFER consistently outperform the original algorithms with higher efficiency. © 2020 ACM.

Supporting pre-service teachers through intercultural experiences: a pathway to socially and culturally inclusive teaching

  • Authors: Johnstone, Carolyn , Cooper, Maxine
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: 10th International Technology, Education and Development Conference (INTED2016) Proceedings, Valencia, Spain. 7-9 March, 2016
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  • Description: In the classrooms of tomorrow, beginning teachers encounter a wide array of students from diverse linguistic, cultural, religious and socio-economic backgrounds. The global community is reflected in the classroom and teachers are expected to prepare their students for global citizenship. Practising and pre-service teachers studying education programs at open access regional universities in Australia often have limited experience of travel and few opportunities to develop global mindedness. Drawing on Bourdieu’s work on social and cultural capital, this qualitative research explores how intercultural experiences contribute to the individual’s developing teacher identity and, in particular, whether unfamiliar professional experience settings promote socially and culturally inclusive teaching in a global context. The study examines whether pre-service teachers develop intercultural empathy, improve intercultural communication and assemble values that reflect membership of a global community. Critical pedagogy principles have been applied to the research and participants are encouraged to critically reflect on their professional experience and their personal journeys as they build their teacher identities. Participant stories, collected through interviews and reflective writing, are examined through narrative inquiry. Additionally, questionnaires are used to provide observer evaluation of the extent to which participants are being and becoming socially and culturally inclusive teachers in a global context. This paper reports on the experiences of the first cohort in the study who have travelled from Federation University Australia to complete professional experience placements in China, Timor-Leste and Papua New Guinea in 2015. Initial findings indicate that these experiences may increase the individual’s cross-cultural empathy, understandings and communication skills, thus enhancing their capacity for socially and culturally inclusive teaching. In addition university mentoring and guidance through the reflection process can increase the learning that occurs including understanding cultural diversity in the classroom, becoming responsible and globally informed teachers and deeply reflective practitioners.

On unified modeling, theory, and method for solving multi-scale global optimization problems

An efficient cooperative lane-changing algorithm for sensor- and communication-enabled automated vehicles

  • Authors: Awal, Tanveer , Murshed, Manzur , Ali, Mortuza
  • Date: 2015
  • Type: Text , Conference proceedings
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  • Description: A key goal in transportation system is to attain efficient road traffic through minimization of trip time, fuel consumption and pollutant-emission without compromising safety. In dense traffic lane-changes and merging are often key ingredients to cause safety hazards, traffic breakdowns and travel delays. In this paper, we propose an efficient cooperative lane-changing algorithm CLA for sensor- and communication-enabled automated vehicles to reduce the lane-changing bottlenecks. For discretionary lane-changing, we consider the advantages of the subject vehicle, the follower in the current lane and k (an integer) lag vehicles in the target lane to maximize speed gains. Our algorithm simultaneously minimizes the impact of lane-change on traffic flow and the overall trip time, fuel-consumption and pollutant-emission. For mandatory lane-changing CLA dissociates the decision-making point from the actual mandatory lane-changing point and computes a suitable lane-changing slot in order to minimize lane-changing (merging) time. Our algorithm outperforms the potential cooperative lane-changing algorithm MOBIL proposed by Kesting et al. [1] in terms of merging time and rate, waiting time, fuel consumption, average velocity and flow (especially at the point in front of the merging point) at the cost of slightly increased average trip time for the mainroad vehicles compared to MOBIL. We also highlight important directions for further research. © 2015 IEEE.

Localising runtime Anomalies in Service-Oriented Systems

  • Authors: He, Qiang , Xie, Xiaoyuan , Wang, Yanchun , Ye, Dayong , Chen, Feifei , Jin, Hai , Yang, Yun
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: IEEE Transactions on Services Computing ( Volume: 10, Issue: 1, Jan.-Feb. 1 2017 ) Vol. 10, p. 94-106
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  • Description: In a distributed, dynamic and volatile operating environment, runtime anomalies occurring in service-oriented systems (SOSs) must be located and fixed in a timely manner in order to guarantee successful delivery of outcomes in response to user requests. Monitoring all component services constantly and inspecting the entire SOS upon a runtime anomaly are impractical due to excessive resource and time consumption required, especially in large-scale scenarios. We present a spectrum-based approach that goes through a five-phase process to quickly localize runtime anomalies occurring in SOSs based on end-to-end system delays. Upon runtime anomalies, our approach calculates the similarity coefficient for each basic component (BC) of the SOS to evaluate their suspiciousness of being faulty. Our approach also calculates the delay coefficients to evaluate each BC's contribution to the severity of the end-to-end system delays. Finally, the BCs are ranked by their similarity coefficient scores and delay coefficient scores to determine the order of them being inspected. Extensive experiments are conducted to evaluate the effectiveness and efficiency of the proposed approach. The results indicate that our approach significantly outperforms random inspection and the popular Ochiai-based inspection in localizing single and multiple runtime anomalies effectively. Thus, our approach can help save time and effort for localizing runtime anomalies occuring in SOSs.

Evolved similarity techniques in malware analysis

  • Authors: Black, Paul , Gondal, Iqbal , Vamplew, Peter , Lakhotia, Arun
  • Date: 2019
  • Type: Text , Conference proceedings
  • Relation: 2019 18th IEEE International Conference On Trust, Security And Privacy; published in In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 5-8th Aug, 2019 p. 404-410
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  • Description: Malware authors are known to reuse existing code, this development process results in software evolution and a sequence of versions of a malware family containing functions that show a divergence from the initial version. This paper proposes the term evolved similarity to account for this gradual divergence of similarity across the version history of a malware family. While existing techniques are able to match functions in different versions of malware, these techniques work best when the version changes are relatively small. This paper introduces the concept of evolved similarity and presents automated Evolved Similarity Techniques (EST). EST differs from existing malware function similarity techniques by focusing on the identification of significantly modified functions in adjacent malware versions and may also be used to identify function similarity in malware samples that differ by several versions. The challenge in identifying evolved malware function pairs lies in identifying features that are relatively invariant across evolved code. The research in this paper makes use of the function call graph to establish these features and then demonstrates the use of these techniques using Zeus malware.

Empirical study of decision trees and ensemble classifiers for monitoring of diabetes patients in pervasive healthcare

  • Authors: Kelarev, Andrei , Stranieri, Andrew , Yearwood, John , Jelinek, Herbert
  • Date: 2012
  • Type: Text , Conference proceedings
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  • Description: Diabetes is a condition requiring continuous everyday monitoring of health related tests. To monitor specific clinical complications one has to find a small set of features to be collected from the sensors and efficient resource-aware algorithms for their processing. This article is concerned with the detection and monitoring of cardiovascular autonomic neuropathy, CAN, in diabetes patients. Using a small set of features identified previously, we carry out an empirical investigation and comparison of several ensemble methods based on decision trees for a novel application of the processing of sensor data from diabetes patients for pervasive health monitoring of CAN. Our experiments relied on an extensive database collected by the Diabetes Complications Screening Research Initiative at Charles Sturt University and concentrated on the particular task of the detection and monitoring of cardiovascular autonomic neuropathy. Most of the features in the database can now be collected using wearable sensors. Our experiments included several essential ensemble methods, a few more advanced and recent techniques, and a novel consensus function. The results show that our novel application of the decision trees in ensemble classifiers for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the outcomes obtained previously in the literature. © 2012 IEEE.
  • Description: 2003009675

Cluster based rule discovery model for enhancement of government's tobacco control strategy

  • Authors: Huda, Shamsul , Yearwood, John , Borland, Ron
  • Date: 2010
  • Type: Text , Conference proceedings
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  • Description: Discovery of interesting rules describing the behavioural patterns of smokers' quitting intentions is an important task in the determination of an effective tobacco control strategy. In this paper, we investigate a compact and simplified rule discovery process for predicting smokers' quitting behaviour that can provide feedback to build an scientific evidence-based adaptive tobacco control policy. Standard decision tree (SDT) based rule discovery depends on decision boundaries in the feature space which are orthogonal to the axis of the feature of a particular decision node. This may limit the ability of SDT to learn intermediate concepts for high dimensional large datasets such as tobacco control. In this paper, we propose a cluster based rule discovery model (CRDM) for generation of more compact and simplified rules for the enhancement of tobacco control policy. The clusterbased approach builds conceptual groups from which a set of decision trees (a decision forest) are constructed. Experimental results on the tobacco control data set show that decision rules from the decision forest constructed by CRDM are simpler and can predict smokers' quitting intention more accurately than a single decision tree. © 2010 IEEE.

Framework for sustainability performance assessment for manufacturing processes- A Review

  • Authors: Singh, Karmjit , Sultan, Ibrahim
  • Date: 2017
  • Type: Text , Conference proceedings
  • Relation: IOP Conference Series: Earth and Environmental Science, Volume 73; International Conference on Sustainable Energy Engineering 12–14 June 2017; Perth, Australia Vol. 73
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  • Description: Manufacturing industries are facing tough competition due to increasing raw material cost and depleting natural resources. There is great pressure on the industry to produce environmental friendly products using environmental friendly processes. To address these issues modern manufacturing industries are focusing on sustainable manufacturing. To develop more sustainable societies, industries need to better understand how to respond to environmental, economic and social challenges. This paper proposed some framework and tools that accelerate the transition towards a sustainable system. The developed framework will be beneficial for sustainability assessment comparing different plans alongside material properties, ultimately helping the manufacturing industries to reduce the carbon emissions and material waste, besides improving energy efficiency. It is expected that this would be highly beneficial for determination of environmental impact of a process at early design stages. Therefore, it would greatly help the manufacturing industries for selection of process plan based on sustainable indices. Overall objective of this paper would have good impact on reducing air emissions and protecting environment. We expect this work to contribute to the development of a standard reference methodology to help further sustainability in the manufacturing sector.

Characterisation of permanent deformation behaviour of unbound granular materials using repeated load triaxial testing

  • Authors: Zhalehjoo, Negin , Tolooiyan, Ali , Mackay, Rae , Bodin, Didier
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields, BCRRA 2017; Athens, Greece; 28th-30th June 2017; published in Bearing Capacity of Roads, Railways and Airfields p. 159-166
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  • Description: Unbound Granular Material (UGM) used in the base/subbase layers of a flexible pavement structure constitutes the vast majority of the material found in roads around the world. The permanent deformation of a compacted UGM layer due to cyclic deviatoric loading has a significant effect on the performance of the pavement structure. The accurate prediction of the magnitude of accumulated permanent strain at varying load cycles and stress levels plays an important role in improving the design and maintenance of flexible pavements. In this study, samples of two road base UGMs are tested to evaluate the characteristics of permanent deformation using the laboratory Repeated Load Triaxial (RLT) test. Three permanent deformation models are used to predict the magnitude of strain accumulation of the studied UGMs. The permanent strain results predicted by the models are compared against those measured by laboratory RLT tests to evaluate the prediction ability of each model.
  • Description: Bearing Capacity of Roads, Railways and Airfields - Proceedings of the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields, BCRRA 2017

Reactive power/voltage control for unbalanced distribution system using genetic algorithms

  • Authors: Ulinuha, Agus , Masoum, Mohammad , Islam, Syed
  • Date: 2014
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Perth, Australia; 28th September-1st October 2014 p. 1-7
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  • Description: The unbalanced conditions are taken into account in the Reactive Power/Voltage control of distribution system. The aim of the control is to simultaneously minimize energy loss and improve voltage profile. The control is carried out by optimal dispatch of load tap changers (LTC) and shunt capacitors considering unbalanced conditions. A genetic algorithm (GA) is developed to determine the load curve partition for effective LTC scheduling and switching constraint satisfaction. GA is also appointed to determine the optimal dispatch schedule of the devices and to check the fulfillment of switching constraints prior to performing calculations. For power flow analyses under unbalanced conditions, a forward/backward propagation algorithm is developed. The optimization is implemented on the IEEE 34-bus unbalanced distribution system, and the presented system improvements are highlighted. The main contribution is inclusion of unbalanced system conditions into the optimal dispatch problem considering different daily load curves for the three phases of distribution system.

Interdisciplinary and cross-cultural approaches to design for healthy ageing

Multi-feature fusion for Crime Scene Investigation image retrieval

Development of ASTRI high-temperature solar receivers

Geoelectrical characterization of hydrological processes in a buried braided river system

  • Authors: Guinea, Ander , Hollins, Suzanne , Meredith, Karina , Hankin, Stuart , Cendón, Dioni
  • Date: 2016
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 22nd European Meeting of Environmental and Engineering Geophysics, Near Surface Geoscience 2016; Barcelona, Spain; 4th-8th September 2016
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  • Description: The Macquarie Marshes (NSW, Australia) cover approximately 200 square km of the Macquarie River flood-plains. The marshes are one of the largest remaining inland semi-permanent wetlands in southeastern Australia. Diversity of fauna and flora has decreased in the wetlands while the flood-drought cycles controlling these ecosystems have been affected by recent human activity. An Electrical Resistivity Tomography survey has been carried out to provide insight into the surface water/ groundwater interactions occurring at the north-western part of the marshes and to identify potential recharge areas of the aquifer systems. In the resistivity sections three main units can be identified: 1. A top unit of low-resistivity (1 to 6 ohm.m) with about 5 meter thick on average. 2. A middle unit of higher electrical resistivity (6 to 20 ohm.m) that continues to a depth of approximately 20 metres and is discontinuous laterally. 3. A bottom unit below a depth of 20 to 25 metres with resistivity decreasing to values similar to those of the top unit. The resistivity results has allowed to identify clay dominated and sand dominated materials. The groundwater is recharged from surface water following sandy windows in the clay created by modern channels on the surface of the marshes.
  • Description: 22nd European Meeting of Environmental and Engineering Geophysics, Near Surface Geoscience 2016

Industry type and business size on economic growth: Comparing Australia's Regional and Metropolitan areas

  • Authors: Mardaneh, Karim
  • Date: 2011
  • Type: Text , Conference proceedings
  • Relation: 56th Annual ICSB World Conference; Back to the Future - Changes in Perspectives of Global Entrepreneurship and Innovation,Stockholm, Sweden, 15-18 June, 2011
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  • Description: While the main body of literature regarding small-to-medium enterprises is focused on formation and growth, there is insufficient research about the role of both (a) firm size and (b) location on economic growth. The role of firm size and industrial structure on economic growth has been examined by some researchers. Pagano (2003) and Pagano and Schivardi (2000) identified a positive association between average firm size and growth and Carree and Thurik (1999) found evidence that the low number of large firms in an industry could lead to a higher value added growth. The current study attempts to investigate the impact of industry structure and businesses operating within these industries on economic growth. This paper uses “k-means” clustering algorithm to cluster Statistical Local Areas. Regression analysis is utilised to identify drivers of economic growth. Preliminary results suggest that size of business may act as a driver of economic growth but the impact could vary based on location.