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Priority based expansion of neighbourhood size for heterogeneous traffic routing in WSN

- Rizal, Muhammad Nur, Gondal, Iqbal, Delir Haghighi, Pari, Qiu, Bin

Selective adversarial learning for mobile malware

- Khoda, Mahbub, Imam, Tasadduq, Kamruzzaman, Joarder, Gondal, Iqbal, Rahman, Ashfaqur

  • Authors: Khoda, Mahbub , Imam, Tasadduq , Kamruzzaman, Joarder , Gondal, Iqbal , Rahman, Ashfaqur
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 272-279
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  • Description: Machine learning models, including deep neural networks, have been shown to be vulnerable to adversarial attacks. Adversarial samples are crafted from legitimate inputs by carefully introducing small perturbation to the input so that the classifier is fooled. Adversarial retraining, which involves retraining the classifier using adversarial samples, has been shown to improve the robustness of the classifier against adversarial attacks. However, it has been also shown that retraining with too many samples can lead to performance degradation. Hence, a careful selection of the adversarial samples that are used to retrain the classifier is necessary, yet existing works select these samples in a randomized fashion. In our work, we propose two novel approaches for selecting adversarial samples: based on the distance from cluster center of malware and based on the probability derived from a kernel based learning (KBL). Our experiment results show that both of our selective mechanisms for adversarial retraining outperform the random selection technique and significantly improve the classifier performance against adversarial attacks. In particular, selection with KBL delivers above 6% improvement in detection accuracy compared to random selection. The method proposed here has greater impact in designing robust machine learning system for security applications. © 2019 IEEE.
  • Description: E1

A cross-layer approach for using multiple radio channels with directional beams in a suburban Ad Hoc network

- Rokonuzzaman, S. K., Pose, Ronald, Gondal, Iqbal

  • Authors: Rokonuzzaman, S. K. , Pose, Ronald , Gondal, Iqbal
  • Date: 2008
  • Type: Text , Conference paper
  • Relation: Australasian Telecommunication Networks and Applications Conference
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  • Description: The capacity of wireless ad hoc networks can be increased by using multiple radio channels. But due to interference the capacity is still not fully utilized. This is caused by the limited number of available radio channels. The interference problem can be reduced using directional beams instead of omni-directional beams. This paper presents a novel cross-layer approach to use multiple radio channels with directional antennas. We are using three different radio channels. Each node has three fixed directional beams having fixed beamwidth and with different radio frequency. Two nodes can communicate when both the sending and receiving beams are pointing towards each other using the same frequency channel. In this study the directions of beams cannot be changed dynamically. A modified version of Ad hoc On-demand Distance Vector (AODV) routing protocol has been used. Simulation results show that our approach outperforms other methods using three different radio channels with omni-directional antennas

Complex anomaly for enhanced machine independent condition monitoring

- Amar, Muhammad, Gondal, Iqbal, Wilson, Campbell

  • Authors: Amar, Muhammad , Gondal, Iqbal , Wilson, Campbell
  • Date: 2015
  • Type: Text , Conference proceedings
  • Relation: 9th International Conference on Open Source Systems and Technologies, ICOSST 2015; Lahore, Pakistan; 17th-19th December 2015
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  • Description: Safety in machine applications requires tracking machine health during the time of operations. Anomaly detection techniques are used to model normal behavior of the machines and raise an alarm if any anomaly is observed. But traditional anomaly detection techniques do not identify type and severity of aberrance in terms of amplitude, pattern or both. Once the anomalous behavior is observed then fault detection techniques are applied to diagnose faults. For machine independent condition monitoring (MICM) a range of features transforms are needed for autonomous learning of the fault classifiers for different parameters to identify variety of fault types which requires huge amount of time. In this paper a novel complex anomaly plan (CAP) representation has been proposed with amplitude anomalies on real and pattern anomalies on imaginary axis. To plot amplitude and pattern anomalies in the CAP, normal state vibrations frequency features are used to train Gaussian models for each of the frequency. The dynamic location of the anomaly plotted in the CAP gives a measure of the intensity of the anomaly, where real and imaginary axis components help the fault classifier to make an appropriate selection of the transform and thus enhances the efficiency of MICM framework. © 2015 IEEE.
  • Description: ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings

Sensor selection for tracking multiple groups of targets

- Armaghani, Farzaneh, Gondal, Iqbal, Kamruzzaman, Joarder, Green, David

  • Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder , Green, David
  • Date: 2014
  • Type: Text , Journal article
  • Relation: Journal of Network and Computer Applications Vol. 46, no. (2014), p. 36-47
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  • Description: Group target tracking is a challenge for sensor networks. It occurs where large numbers of closely spaced targets move together in different groups. In these applications, the sensor selection scheme plays a vital role in extending network lifetime while providing high tracking accuracy. Existing schemes cause an extreme imbalance between energy usages and tracking accuracy. They are capable of tracking only individual groups and without using prior knowledge about the groups. These problems make them impractical for group target tracking. With the aim of balancing the trade-off between lifetime and accuracy, we present a novel Multi-Sensor Group Tracking (MSGT) scheme. MSGT comprises the following steps to accomplish concurrent tracking of multiple groups: (1) Clustering to capture changes in the behavioural properties of groups, such as formation, merging, and splitting; (2) Sensor selection to activate the contributory sensors for the estimated group regions; and (3) Group tracking using the activated sensors. We develop a probabilistic decision-making strategy that triggers the clustering step adaptively with any detected change in group behavioural patterns. The sensor selection step coordinates periodic selection of leader and tracking sensor nodes in a distributed manner. We introduce cost metrics that include sensor′s energy parameters in the selection of active sensors that fully cover the group regions. The tracking step is a Bayesian modelling of the target groups which uses particle filtering algorithm to estimate the group locations. Simulation results show that our scheme achieves substantial improvements over existing approaches in terms of network lifetime and tracking accuracy.

Action-02MCF : A robust space-time correlation filter for action recognition in clutter and adverse lighting conditions

- lhaq, Anwaar, Yin, Xiaoxia, Zhang, Yunchan, Gondal, Iqbal

  • Authors: lhaq, Anwaar , Yin, Xiaoxia , Zhang, Yunchan , Gondal, Iqbal
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 17th International Conference, ACIVS 2016 p. 465-476
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  • Description: Human actions are spatio-temporal visual events and recognizing human actions in different conditions is still a challenging computer vision problem. In this paper, we introduce a robust feature based space-time correlation filter, called Action-02MCF (0’zero-aliasing’ 2M’ Maximum Margin’) for recognizing human actions in video sequences. This filter combines (i) the sparsity of spatio-temporal feature space, (ii) generalization of maximum margin criteria, (iii) enhanced aliasing free localization performance of correlation filtering using (iv) rich context of maximally stable space-time interest points into a single classifier. Its rich multi-objective function provides robustness, generalization and recognition as a single package. Action-02MCF can simultaneously localize and classify actions of interest even in clutter and adverse imaging conditions. We evaluate the performance of our proposed filter for challenging human action datasets. Experimental results verify the performance potential of our action-filter compared to other correlation filtering based action recognition approaches.

Carry me if you can : A utility based forwarding scheme for content sharing in tourist destinations

- Kaisar, Shahriar, Kamruzzaman, Joarder, Karmakar, Gour, Gondal, Iqbal

  • Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: 22nd Asia-Pacific Conference on Communications, APCC 2016; Yogyakarta, Indonesia; 25th-27th August 2016 p. 261-267
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  • Description: Message forwarding is an integral part of the decentralized content sharing process as the content delivery success highly depends on it. Existing literature employs spatio-temporal regularity of human movement pattern and pre-existing social relationship to take message forwarding decisions. However, such approaches are ineffectual in environments where those information are unavailable such as a tourist spot or camping site. In this study, we explore the message forwarding techniques in such environments considering the information that are readily available and can be gathered on the fly. We propose a utility based forwarding scheme to select the appropriate forwarder node based on co-location stay time, connectivity and available resources. A higher co-location stay time reflects that the forwarder and the destination node is likely to have more opportunistic contacts, while the connectivity and available resource ensure that the selected forwarder has sufficient neighbours and resources to carry the message forward. Simulation results suggest that the proposed approach attains high hit and success rate and low latency for successful content delivery, which is comparable to those proposed for work-place type scenarios with regular movement pattern and pre-existing relationships. © 2016 IEEE.

Smart phone based vehicle condition monitoring

- Yaqub, Muhammad Farrukh, Gondal, Iqbal

  • Authors: Yaqub, Muhammad Farrukh , Gondal, Iqbal
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 8th IEEE Conference on Industrial Electronics and Applications (ICIEA) p. 267-271
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  • Description: Condition monitoring (CM) of the industrial equipment is growing auspiciously since the last decade or so. Whereas, very little efforts have been exerted on monitoring the vehicles that we ride every day. One of the main reasons is the actual cost of the CM equipment. Today an average level vibration based condition monitoring unit costs around the total price of the vehicle. Thanks to the advancement in the smart phone technology which provides a broad range of sensors and remarkable computational power in a small handheld devices. Owing to the capability of the smartphones to capture the vibrations using an internal built-in accelerometer, this paper proposes a cost effective vibration condition monitoring unit for the motor vehicles. The accelerometer in the smart phone has very limited capacity in terms sampling rate for the data acquisition. This paper proposes an enhanced sampling rate (ESR) technique for capturing the data at an improved sampling rate in spite of device limitation. Though a lot needs to be done both in terms of hardware optimization and fault diagnosis, the focus of this paper is to achieve an efficient data acquisition using smartphone. Experimental results are presented both for the simulated as well actual vibration datasets which validate the practicality and suitability of the proposed technique.

Content exchange among mobile tourists using users' interest and place-centric activities

- Kaisar, Shahriar, Kamruzzaman, Joarder, Karmakar, Gour, Gondal, Iqbal

  • Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
  • Date: 2015
  • Type: Text , Conference paper
  • Relation: 2015 10th International Conference on Information, Communications and Signal Processing (Icics); Singapore, Singapore; 2nd-4th December 2015 p. 1-5
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  • Description: In this work we investigate decentralized content exchange among tourists who are mostly strangers, depicts irregular movement patterns and most likely not to have any prior social relationship or difficult to establish any in a tourist spot. We incorporate user's interest, trustworthy online recommendations, and place-centric information to facilitate content exchange in such tourist destinations. The proposed administrator selection policy considers stay probability in activities, connectivity among nodes and their available resources. We have done extensive simulation using network simulator NS3 on a popular tourist spot in Australia that provides a number of activities. Our proposed approach shows promising results in exchanging contents among users measured in terms of content hit and delivery success rate as well as latency. The success rate is comparable to those reported in the literature for cases where social relationship exist and nodes follow regular predictable movement patterns.

Blockchain leveraged task migration in body area sensor networks

- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki

  • Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 25th Asia-Pacific Conference on Communications, APCC 2019 p. 177-184
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  • Description: Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.
  • Description: E1

Dynamic dwell timer for hybrid vertical handover in 4G coupled networks

- Haider, Ammar, Gondal, Iqbal, Kamruzzaman, Joarder

Multi-dimensional adaptive SINR based vertical handoff for heterogeneous wireless networks

- Yang, Kemeng, Gondal, Iqbal, Qiu, Bin

  • Authors: Yang, Kemeng , Gondal, Iqbal , Qiu, Bin
  • Date: 2008
  • Type: Text , Journal article
  • Relation: IEEE Communications Letters Vol. 12, no. 6 (2008), p. 438-440
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  • Description: Vertical handoff in next generation heterogeneous wireless networks is a multi-dimensional issue. In this article we propose a multi-dimensional adaptive SINR based vertical handoff algorithm (MASVH) which uses the combined effects of SINR, user required bandwidth, user traffic cost and utilization from participating access networks to make handoff decisions for multi-attribute QoS consideration. Simulation results confirm that the new MASVH algorithm improves the system performance in terms of higher throughput and lower dropping probability, as well as reduces the user traffic cost for accessing the integrated wireless networks.

Multiple-points fault signature's dynamics modeling for bearing defect frequencies

- Yaqub, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder

Vibration spectrum imaging : A novel bearing fault classification approach

- Amar, Muhammad, Gondal, Iqbal, Wilson, Campbell

  • Authors: Amar, Muhammad , Gondal, Iqbal , Wilson, Campbell
  • Date: 2015
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Electronics Vol. 62, no. 1 (2015), p. 494-502
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  • Description: Incipient fault detection in low signal-to-noise ratio (SNR) conditions requires robust features for accurate condition-based machine health monitoring. Accurate fault classification is positively linked to the quality of features of the faults. Therefore, there is a need to enhance the quality of the features before classification. This paper presents a novel vibration spectrum imaging (VSI) feature enhancement procedure for low SNR conditions. An artificial neural network (ANN) has been used as a fault classifier using these enhanced features of the faults. The normalized amplitudes of spectral contents of the quasi-stationary time vibration signals are transformed into spectral images. A 2-D averaging filter and binary image conversion, with appropriate threshold selection, are used to filter and enhance the images for the training and testing of the ANN classifier. The proposed novel VSI augments and provides the visual representation of the characteristic vibration spectral features in an image form. This provides enhanced spectral images for ANN training and thus leads to a highly robust fault classifier.

Machine fault severity estimation based on adaptive wavelet nodes selection and SVM

- Yaqub, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: IEEE International Conference on Mechatronics and Automation (ICMA),Beijing 7 August 2011 to 10 August 2011) p. 1951-1956
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  • Description: The study is focused on estimating the severity level of the bearing faults which helps in determining the residual life of the equipment and planned maintenance. A novel technique, adaptive severity estimation model (ASEM) is proposed based on adaptive selection of wavelet decomposition nodes and support vector machines. Vibration data from multiple severity levels are used to build the fault estimation model. An adaptive criterion for wavelet decomposition node selection is developed which helps ASEM to achieve robustness in estimating fault severity under varying signal to noise ratio (SNR), a key demand in industrial environment. The simulated data with known severity level is used to parameterize the estimation model. The fault severity estimation performance of ASEM is also validated for the real vibration data and its robustness is gauged under varying SNR conditions.

I-MAC: energy efficient intelligent MAC protocol for wireless sensor networks

- Bhuiyan, Mohammad, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Bhuiyan, Mohammad , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 17th Asia Pacific Conference on Communications, APCC 2011; Sabah, Malaysia; 2nd-5th October 2011 p. 133-138
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  • Description: Energy efficiency is a vital aspect of resource constrained wireless sensor networks (WSNs). All protocols designed for WSNs must be energy aware in order to prolong the network lifetime. In this paper, we have designed a novel MAC layer protocol (I-MAC: Intelligent MAC) for WSNs. By exercising intelligent sleep and wake-up schedule, I-MAC saves energy of the resource constrained sensor nodes greatly. At the same time, I-MAC does not compromise its operational performances. Both analytical study and simulation prove that I-MAC is not only highly energy efficient but also its operational performances are better than similar protocols.

An adaptive self-configuration scheme for severity invariant machine fault diagnosis

- Yaqub, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2013
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Reliability Vol. 62, no. 1 (2013), p. 116-126
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  • Description: Vibration signals, used for abnormality detection in machine health monitoring (MHM), exhibit significant variation with varying fault severity. This signal variation causes overlap among the features characterizing different types of faults, which results in severe performance degradation of the fault diagnostic model. In this paper, a wavelet based adaptive training set and feature selection (WATF) self-configuration scheme is presented, which selects the optimum wavelet decomposition level, and employs adaptive selection of the training set and features. Optimal wavelet decomposition level selection is such that the maximum fault signature-signal energy bands are achieved. The severity variant features, which could cause detrimental class overlap for MHM, are avoided using adaptive selection of the training set and features based on the location of a test data in feature space. WATF uses Support Vector Machines (SVM) to build the fault diagnostic model, and its performance and robustness has been tested with data having different severity levels. Comparative studies of WATF with eight existing fault diagnosis schemes show that, for publicly available data sets, WATF achieves higher fault detection accuracy, even when training and testing data sets belong to different severity levels.

Severity invariant machine fault diagnosis

- Yaqub, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 6th IEEE Conference on Industrial Electronics and Applications p. 21-26
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  • Description: Vibration signals used for abnormality detection in machine health monitoring (MHM) suffer from significant variation with fault severity. This variation causes overlap among the features belonging to different types of faults resulting in severe degradation of fault detection accuracy. This paper identifies a new problem due to severity variant features and proposes a novel adaptive training set and feature selection (ATSFS) scheme based upon the orientation of the test data. In order to build ATSFS and validate its performance, training and testing data are obtained from different severity levels. To capture the non-stationary behavior of vibration signal, robust tools such as wavelet transform (WT) for time-frequency analysis are employed. Simulation studies show that ATSFS attains high classification accuracy even if training and testing data belong to different severity levels.

An exploratory trial implementing a community-based child oral health promotion intervention for Australian families from refugee and migrant backgrounds : A protocol paper for Teeth Tales

- Gibbs, Lisa, Waters, Elizabeth, De Silva, Andrea, Riggs, Elisha, Moore, Laurence, Armit, Christine, Johnson, Britt, Morris, Michal, Calache, Hanny, Gussy, Mark, Young, Dana, Tadic, Maryanne, Christian, Bradley, Gondal, Iqbal, Watt, Richard, Pradel, Veronika, Truong, Mandy, Gold, Lisa

  • Authors: Gibbs, Lisa , Waters, Elizabeth , De Silva, Andrea , Riggs, Elisha , Moore, Laurence , Armit, Christine , Johnson, Britt , Morris, Michal , Calache, Hanny , Gussy, Mark , Young, Dana , Tadic, Maryanne , Christian, Bradley , Gondal, Iqbal , Watt, Richard , Pradel, Veronika , Truong, Mandy , Gold, Lisa
  • Date: 2014
  • Type: Text , Journal article
  • Relation: BMJ Open Vol. 4, no. 3 (2014), p. 1-14
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  • Description: Introduction: Inequalities are evident in early childhood caries rates with the socially disadvantaged experiencing greater burden of disease. This study builds on formative qualitative research, conducted in the Moreland/Hume local government areas of Melbourne, Victoria 2006-2009, in response to community concerns for oral health of children from refugee and migrant backgrounds. Development of the community-based intervention described here extends the partnership approach to cogeneration of contemporary evidence with continued and meaningful involvement of investigators, community, cultural and government partners. This trial aims to establish a model for child oral health promotion for culturally diverse communities in Australia. Methods and analysis: This is an exploratory trial implementing a community-based child oral health promotion intervention for Australian families from refugee and migrant backgrounds. Families from an Iraqi, Lebanese or Pakistani background with children aged 1-4 years, residing in metropolitan Melbourne, were invited to participate in the trial by peer educators from their respective communities using snowball and purposive sampling techniques. Target sample size was 600. Moreland, a culturally diverse, inner-urban metropolitan area of Melbourne, was chosen as the intervention site. The intervention comprised peer educator led community oral health education sessions and reorienting of dental health and family services through cultural Competency Organisational Review (CORe). Ethics and dissemination: Ethics approval for this trial was granted by the University of Melbourne Human Research Ethics Committee and the Department of Education and Early Childhood Development Research Committee. Study progress and output will be disseminated via periodic newsletters, peer-reviewed research papers, reports, community seminars and at National and International conferences. Trial registration number: Australian New Zealand Clinical Trials Registry (ACTRN12611000532909).

LACAR : Location aided congestion aware routing in wireless sensor networks

- Bhuiyan, Mohammad, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Bhuiyan, Mohammad , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2010
  • Type: Text , Conference paper
  • Relation: Wireless Communications and Networking Conference (WCNC), p. 1-6
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  • Description: Trade-off between energy-efficiency and reliability in wireless sensor networks is application dependent. Without the reliability, the extended lifetime of a network is of limited use. Due to the inherent correlation between reliability and congestion, it is necessary to reduce congestion to improve reliability. Existing congestion control algorithms in wireless sensor networks are reactive. They attempt to reduce the congestion only after its detection. In this paper, we present Location Aided Congestion Aware Routing (LACAR) protocol that proactively avoids congestion formation and improves data delivery success rate in data gathering wireless sensor networks. Location, energy and congestion information of neighbours together with the location information of the base station determine appropriate routes. Simulation results show that LACAR achieves high packet success rate in an energy-efficient way.