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Dual-channel based energy efficient event clustering and data gathering in WSNs

- 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. 241-246
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  • Description: Wireless sensor networks (WSNs), now-a-days, are deployed in environmental data collection as well as in critical event monitoring. Successful data collection requires reliability while reliable event detection necessitates timeliness. Simultaneous data gathering and event monitoring is not well studied in literature. In this paper, we propose a system model that works on homogeneous data gathering WSNs. When an event occurs, an event cluster with a different transmission channel is formed and both data gathering and event monitoring are performed at the same time. The proposed model has a novel routing strategy with a built-in congestion control technique to provide timely delivery of event data. Experimental results show that the proposed method performs better than known similar techniques in terms of reliable data gathering and reliable timely event monitoring. It also enhances the network lifetime significantly compared to other existing methods.

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.

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

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

  • Authors: Ulhaq, Anwaar , Yin, Xiaoxia , Zhang, Yunchan , Gondal, Iqbal
  • Date: 2016
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016; Lecce, Italy; 24th-27th October 2016; published in Advanced Conepts for Intelligent Vision Systems (Lecture Notes in Computer Science series) Vol. 10016 LNCS, 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. © Springer International Publishing AG 2016.
  • Description: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A Cultural Competence Organizational Review for community health services : Insights from a participatory approach

- Truong, Mandy, Gibbs, Lisa, Pradel, Veronika, Morris, Michal, Gwatirisa, Pauline, Tadic, Maryanne, De Silva, Andrea, Hall, Martin, Young, Dana, Riggs, Elisha, Calache, Hanny, Gussy, Mark, Watt, Richard, Gondal, Iqbal, Waters, Elizabeth

  • Authors: Truong, Mandy , Gibbs, Lisa , Pradel, Veronika , Morris, Michal , Gwatirisa, Pauline , Tadic, Maryanne , De Silva, Andrea , Hall, Martin , Young, Dana , Riggs, Elisha , Calache, Hanny , Gussy, Mark , Watt, Richard , Gondal, Iqbal , Waters, Elizabeth
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Health Promotion Practice Vol. 18, no. 3 (2017), p. 466-475
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  • Description: Cultural competence is an important aspect of health service access and delivery in health promotion and community health. Although a number of frameworks and tools are available to assist health service organizations improve their services to diverse communities, there are few published studies describing organizational cultural competence assessments and the extent to which these tools facilitate cultural competence. This article addresses this gap by describing the development of a cultural competence assessment, intervention, and evaluation tool called the Cultural Competence Organizational Review (CORe) and its implementation in three community sector organizations. Baseline and follow-up staff surveys and document audits were conducted at each participating organization. Process data and organizational documentation were used to evaluate and monitor the experience of CORe within the organizations. Results at follow-up indicated an overall positive trend in organizational cultural competence at each organization in terms of both policy and practice. Organizations that are able to embed actions to improve organizational cultural competence within broader organizational plans increase the likelihood of sustainable changes to policies, procedures, and practice within the organization. The benefits and lessons learned from the implementation of CORe are discussed. © 2017, Society for Public Health Education.

A patient agent to manage blockchains for remote patient monitoring

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

  • Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: 7th International Conference on Global Telehealth, GT 2018; Colombo, Sri Lanka; 10th-11th October 2018; published in Studies in Health Technology and Informatics Vol. 254, p. 105-115
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  • Description: Continuous monitoring of patient's physiological signs has the potential to augment traditional medical practice, particularly in developing countries that have a shortage of healthcare professionals. However, continuously streamed data presents additional security, storage and retrieval challenges and further inhibits initiatives to integrate data to form electronic health record systems. Blockchain technologies enable data to be stored securely and inexpensively without recourse to a trusted authority. Blockchain technologies also promise to provide architectures for electronic health records that do not require huge government expenditure that challenge developing nations. However, Blockchain deployment, particularly with streamed data challenges existing Blockchain algorithms that take too long to place data in a block, and have no mechanism to determine whether every data point in every stream should be stored in such a secure way. This article presents an architecture that involves a Patient Agent, coordinating the insertion of continuous data streams into Blockchains to form an electronic health record.
  • Description: Studies in Health Technology and Informatics

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

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

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 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).

Decentralized content sharing among tourists in visiting hotspots

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

  • Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Journal of Network and Computer Applications Vol. 79, no. (2017), p. 25-40
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  • Description: Content sharing with smart mobile devices using decentralized approach enables users to share contents without the use of any fixed infrastructure, and thereby offers a free-of-cost platform that does not add to Internet traffic which, in its current state, is approaching bottleneck in its capacity. Most of the existing decentralized approaches in the literature consider spatio-temporal regularity in human movement patterns and pre-existing social relationship for the sharing scheme to work. However, such predictable movement patterns and social relationship information are not available in places like tourist spots where people visit only for a short period of time and usually meet strangers. No works exist in literature that deals with content sharing in such environment. In this work, we propose a content sharing approach for such environments. The group formation mechanism is based on users' interest score and stay probability in the individual region of interest (ROI) as well as on the availability and delivery probabilities of contents in the group. The administrator of each group is selected by taking into account its probability of stay in the ROI, connectivity with other nodes, its trustworthiness and computing and energy resources to serve the group. We have also adopted an incentive mechanism as encouragement that awards nodes for sharing and forwarding contents. We have used network simulator NS3 to perform extensive simulation on a popular tourist spot in Australia which facilitates a number of activities. The proposed approach shows promising results in sharing contents among tourists, measured in terms of content hit, delivery success rate and latency.
  • Description: Content sharing with smart mobile devices using decentralized approach enables users to share contents without the use of any fixed infrastructure, and thereby offers a free-of-cost platform that does not add to Internet traffic which, in its current state, is approaching bottleneck in its capacity. Most of the existing decentralized approaches in the literature consider spatio-temporal regularity in human movement patterns and pre-existing social relationship for the sharing scheme to work. However, such predictable movement patterns and social relationship information are not available in places like tourist spots where people visit only for a short period of time and usually meet strangers. No works exist in literature that deals with content sharing in such environment. In this work, we propose a content sharing approach for such environments. The group formation mechanism is based on users' interest score and stay probability in the individual region of interest (ROI) as well as on the availability and delivery probabilities of contents in the group. The administrator of each group is selected by taking into account its probability of stay in the ROI, connectivity with other nodes, its trustworthiness and computing and energy resources to serve the group. We have also adopted an incentive mechanism as encouragement that awards nodes for sharing and forwarding contents. We have used network simulator NS3 to perform extensive simulation on a popular tourist spot in Australia which facilitates a number of activities. The proposed approach shows promising results in sharing contents among tourists, measured in terms of content hit, delivery success rate and latency. © 2016

Dynamic sensor selection for target tracking in wireless sensor networks

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

  • Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: IEEE 74th Vehicular Technology Conference, VTC Fall 2011; San Francisco, United States; 5th-8th September 2011 p. 1-6
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  • Description: Optimum selection of sensors in target tracking applications has a great potential to maintain right trade-off between energy consumption and quality of tracking. In this paper, we propose a dynamic sensor selection scheme to achieve energy efficiency while ensuring the required quality of tracking. To this end, relative information utility projection of a target on sensors' observation is used in niche overlap measurements. Niche overlap measures are used to assess the similarity in information utilities where information utility is inversely proportional to error in target's state estimation based on prior distribution. The proposed scheme is a greedy approach in which sensor nodes are selected such that the overall niche overlap of all the selected nodes is maximized until the required level of accuracy is achieved. Our simulation results show significant improvement in tracking accuracy and network's lifetime over the existing methods.

Multi-source cyber-attacks detection using machine learning

- Taheri, Sona, Gondal, Iqbal, Bagirov, Adil, Harkness, Greg, Brown, Simon, Chi, Chihung

  • Authors: Taheri, Sona , Gondal, Iqbal , Bagirov, Adil , Harkness, Greg , Brown, Simon , Chi, Chihung
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne, Australia; 13th-15th February 2019 Vol. 2019-February, p. 1167-1172
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  • Description: The Internet of Things (IoT) has significantly increased the number of devices connected to the Internet ranging from sensors to multi-source data information. As the IoT continues to evolve with new technologies number of threats and attacks against IoT devices are on the increase. Analyzing and detecting these attacks originating from different sources needs machine learning models. These models provide proactive solutions for detecting attacks and their sources. In this paper, we propose to apply a supervised machine learning classification technique to identify cyber-attacks from each source. More precisely, we apply the incremental piecewise linear classifier that constructs boundary between sources/classes incrementally starting with one hyperplane and adding more hyperplanes at each iteration. The algorithm terminates when no further significant improvement of the separation of sources/classes is possible. The construction and usage of piecewise linear boundaries allows us to avoid any possible overfitting. We apply the incremental piecewise linear classifier on the multi-source real world cyber security data set to identify cyber-attacks and their sources.
  • Description: Proceedings of the IEEE International Conference on Industrial Technology

An efficient data extraction framework for mining wireless sensor networks

- Rashid, Md. Mamunur, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 23rd International Conference, ICONIP 2016; Kyoto, Japan; 16th-21st October 2016; published in Neural Information Processing, Part III (Lecture Notes in Computer Science series) Vol. 9949, p. 491-498
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  • Description: Behavioral patterns for sensors have received a great deal of attention recently due to their usefulness in capturing the temporal relations between sensors in wireless sensor networks. To discover these patterns, we need to collect the behavioral data that represents the sensor's activities over time from the sensor database that attached with a well-equipped central node called sink for further analysis. However, given the limited resources of sensor nodes, an effective data collection method is required for collecting the behavioral data efficiently. In this paper, we introduce a new framework for behavioral patterns called associated-correlated sensor patterns and also propose a MapReduce based new paradigm for extract data from the wireless sensor network by distributed away. Extensive performance study shows that the proposed method is capable to reduce the data size almost 50% compared to the centralized model.

Mobile malware detection - An analysis of the impact of feature categories

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

Weighted ANN input layer for adaptive features selection for robust fault classification

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

  • Authors: Amar, Muhammad , Gondal, Iqbal , Wilson, Campbell
  • Date: 2015
  • Type: Text , Conference proceedings
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  • Description: Model based feature selection for identification of diverse faults in rotary machines can significantly cost time and money and it is nearly impossible to model all faults under different operating environments. In this paper, feedforward ANN input-layer-weights have been used for the adaptive selection of the least number of features, without fault model information, reducing the computations significantly but assuring the required accuracy by mitigating the noise. In the proposed approach, under the assumption that presented features should be translation invariant, ANN uses entire set of spectral features from raw input vibration signal for training. Dominant features are then selected using input-layer-weights relative to a threshold value vector. Different instances of ANN are then trained and tested to calculate F1_score with the reduced dominant features at different SNRs for each threshold value. Trained ANN with best average classification accuracy among all ANN instances gives us required number of dominant features. © Springer International Publishing Switzerland 2015.

Mining associated sensor patterns for data stream of wireless sensor networks

- Rashid, Md. Mamunur, Gondal, Iqbal, Kamruzzaman, Joarder

  • Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2013
  • Type: Text , Conference proceedings
  • Relation: 8th ACM International Workshop on Performance Monitoring, Measurement, and Evaluation of Heterogeneous Wireless and Wired Networks, PM2HW2N 2013, Barcelona; Spain; 3rd-8th November 2013 p. 91-98
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  • Description: WSNs generate a large amount of data in the form of data stream; and mining these streams to extract useful knowledge is a highly challenging task. Existing works proposed in literature use sensor association rules measured in terms of occurrence frequency of patterns. However, these rules often generate a huge number of rules, most of which are non-informative or fail to reflect the true correlation among data objects. Additionally mining associated sensor patterns from sensor stream data, which is vital for real-time applications, has not been addressed yet in literature. In this paper, we address these problems and propose a new type of sensor behavioral pattern called associated sensor patterns which capture simultaneously association-like co-occurrence as well as substantial temporal correlations implied by such co-occurrences in sensor data. We propose a novel tree structure, called associated sensor pattern stream tree (ASPS-tree) and a new technique, called associated sensor pattern mining of data stream (ASPMS), using sliding window-based associated sensor pattern mining for WSNs. By capturing the useful knowledge of the data stream into an ASPS-tree, our ASPMS algorithm can mine associated sensor patterns in the current window with frequent pattern (FP)-growth like pattern-growth method. Extensive experimental analyses show that our technique is very efficient in discovering associated sensor patterns over sensor data stream.

Improving authorship attribution in twitter through topic-based sampling

- Pan, Luoxi, Gondal, Iqbal, Layton, Robert

  • Authors: Pan, Luoxi , Gondal, Iqbal , Layton, Robert
  • Date: 2017
  • Type: Text , Conference proceedings
  • Relation: 30th Australasian Joint Conference on Artificial Intelligence, AI 2017 : Advances in Artificial Intelligence; Melbourne, Australia; 19th-20th August 2017; published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10400 LNAI, p. 250-261
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  • Description: Aliases are used as a means of anonymity on the Internet in environments such as IRC (internet relay chat), forums and micro-blogging websites such as Twitter. While there are genuine reasons for the use of aliases, such as journalists operating in politically oppressive countries, they are increasingly being used by cybercriminals and extremist organisations. In recent years, we have seen increased research on authorship attribution of Twitter messages, including authorship analysis of aliases. Previous studies have shown that anti-aliasing of randomly generated sub-aliases yields high accuracies when linking the sub-aliases, but become much less accurate when topic-based sub-aliases are used. N-gram methods have previously been demonstrated to perform better than other methods in this situation. This paper investigates the effect of topic-based sampling on authorship attribution accuracy for the popular micro-blogging website Twitter. Features are extracted using character n-grams, which accurately capture differences in authorship style. These features are analysed using support vector machines using a one-versus-all classifier. The predictive performance of the algorithm is then evaluated using two different sampling methodologies - authors that were sampled through a context-sensitive topic-based search and authors that were sampled randomly. Topic-based sampling of authors is found to produce more accurate authorship predictions. This paper presents several theories as to why this might be the case. © Springer International Publishing AG 2017.

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

- Rizal, Muhammad Nur, Gondal, Iqbal, Haghighi, P. Delir, Qiu, Bin

  • Authors: Rizal, Muhammad Nur , Gondal, Iqbal , Haghighi, P. Delir , Qiu, Bin
  • Date: 2012
  • Type: Text , Conference paper
  • Relation: 9th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks, PE-WASUN 2012 p. 101-106
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  • Description: This paper presents a new routing scheme that adapts to the requirements of heterogeneous traffic. The proposed scheme introduces further improvements to our developed ExtTeGAR algorithm. The aim of the scheme is to achieve low latency and to satisfy multiple quality of service (QoS) in various network conditions. In doing so, the proposed approach exploits multiple nodes’ attributes such as energy, distance to the base station (BS), history of hop delay of data to neighbors and probability of link availability to determine the best node for delivering different traffic requirements. The contribution of the scheme is its ability to differentiate the required data-related to each type of traffic and give different priorities to different data categories so that each type of traffic classification ensures to meet the demands of the application requirements. The proposed scheme uses a distance-based and a location-aware approach to create a shortest path for type of packets with given deadlines and it provides adaptability to increase the transmission range to expand the neighborhood sizes for data delivery continuation. The paper shows that the proposed scheme outperforms an existing QoS routing algorithm (SPEED) in various application scenarios and different network sizes.

Mobile agent based artificial immune system for machine condition monitoring

- Hua, Xue-Liang, Gondal, Iqbal, Yaqub, Farrukh

  • Authors: Hua, Xue-Liang , Gondal, Iqbal , Yaqub, Farrukh
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 8th IEEE Conference on Industrial Electronics and Applications (ICIEA) p. 108-113
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  • Description: Machine condition monitoring is a process of continuously observing the status of a machine to ensure that proactive measures are taken to prevent damage due to abnormal operating conditions. Generally, industrial units such as mining, oil and gas etc, are located in geographically remote areas, so a large amount of data need to be acquired for fault diagnosis and prognosis remotely. To achieve this, certain resources such as stable communication network and adequate bandwidth are required. Furthermore, it is not always feasible to dispatch human resources simultaneously over large areas of operation to perform on-site maintenance. To overcome these issues, a mobile agent based system architecture is proposed for machine condition monitoring by imitating human immune system (ACMIS), which is also known as artificial immune system. The experiment results are presented to evaluate the performance of the proposed system in terms of fault detection accuracy and bandwidth allocation. Overall performance evaluation of the proposed framework suggests that our proposed scheme not only provides excellent fault detection accuracy but also a flexible and reliable machine condition monitoring system with reduced network and computational resources. Further our approach provides cost effective solution in building a practical machine condition monitoring system.

Optimally parameterized wavelet packet transform for incipient machine fault diagnosis

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

  • Authors: Yaqub, Muhammad Farrukh , Gondal, Iqbal , Kamruzzaman, Joarder
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 6th International Conference on Leading Edge Manufacturing in 21st Century, LEM 2011
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  • Description: Vibration signals used for abnormality detection in machine health monitoring (MHM) are non-stationary in nature. Wavelet packet transform is extensively used in the literature for comprehensive analysis of non-stationary vibration signal but these techniques work only for a specific application lacking in some generalized methodology for selecting appropriate wavelet decomposition level and nodes for optimal performance. This study proposes a framework for inchoate fault detection by selecting the optimal wavelet decomposition level and nodes, named Optimally Parameterized Wavelet Packet Transform (OPWPT). OPWPT uses support vector machine to build the fault diagnostic model. Results in comparison with the existing schemes validate that OPWPT enhances the fault detection accuracy significantly in case of incipient faults when vibration signatures are very weak and overall signal to noise ratio is very poor.

Dynamic content distribution for decentralized sharing in tourist spots using demand and supply

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

  • Authors: Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal , Kaisar, Shahriar
  • Date: 2017
  • Type: Text , Conference proceedings
  • Relation: 13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017; Valencia, Spain; 26th-30th June 2016 p. 2121-2126
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  • Description: Decentralized content sharing (DCS) is emerging as an important platform for sharing contents among smart mobile device users, where devices form an ad-hoc network and communicate opportunistically. Existing DCS approaches for tourist spot like scenarios achieve low delivery success rate and high latency as they do not focus on dynamic demand for contents which usually vary considerably with the number of visitors present or occurrence of some influencing events. The amount of available supply also changes because of the nodes leaving the area. Only way to improve content delivery service is to distribute the contents in strategic positions based on dynamic demand and supply. In this paper, we propose a dynamic content distribution (DCD) method considering dynamic demand and supply for contents in tourist spots. Simulation results validate the improvement of the proposed approach. © 2017 IEEE.
  • Description: 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017