An efficient data extraction framework for mining wireless sensor networks
- 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.
Carry me if you can : A utility based forwarding scheme for content sharing in tourist destinations
- 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.
Child oral health in migrant families : A cross-sectional study of caries in 1-4 year old children from migrant backgrounds residing in Melbourne, Australia
- Authors: Gibbs, Lisa , De Silva, Andrea , Christian, Bradley , Gold, Lisa , Gussy, Mark , Moore, Laurence , Calache, Hanny , Young, Dana , Riggs, Elisha , Tadic, Maryanne , Watt, Richard , Gondal, Iqbal , Waters, Elizabeth
- Date: 2016
- Type: Text , Journal article
- Relation: Community Dental Health Vol. 33, no. 2 (2016), p. 100-106
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- Description: Early Childhood Caries (ECC) is the most common, preventable disease of childhood. It can affect children’s health and wellbeing and children from migrant families may be at greater risk of developing ECC. Objective: To describe ECC in children from migrant families, and explore possible influences. Basic research design: Cross-sectional analysis of caries data collected as baseline data for an oral health promotion study. Participants: The analysis sample included 630 1-4 year-old children clustered within 481 Iraqi, Lebanese and Pakistani families in Melbourne, Australia. Method: Child participants received a community-based visual dental examination. Parents completed a self-administered questionnaire on demographics, ethnicity, and oral health knowledge, behaviour and attitudes. Main outcome measure: Child caries experience. Bivariate associations between oral health behaviours and ethnicity were tested for significance using chi-square. Multivariate logistic regression analyses were performed to identify associations with ECC, adjusting for demographic variables and accounting for clustering by family. Results: Overall, 34% of children in the sample experienced caries (both non-cavitated and cavitated). For all caries lesions, parent’ length of residence in Australia, consumption of sweet drinks and parental education remained as independent predictors of child caries experience. Adding sugar to drinks was an additional risk factor for cavitation. Ethnicity was associated with some individual oral health behaviours suggesting cultural influences on health, however the relationship was not independent of other predictors. Conclusion: Culturally competent oral health promotion interventions should aim to support migrant families with young children, and focus on reducing sweet drink consumption. © BASCD 2016.
Online romance scam: Expensive e-living for romantic happiness
- Authors: Kopp, Christian , Sillitoe, James , Gondal, Iqbal , Layton, Robert
- Date: 2016
- Type: Text , Conference proceedings
- Relation: Proceedings of the 29th Bled eConference: Digital Economy (BLED 2016), Slovenia, pp.175-189 p. 15
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- Description: The Online Romance Scam is a very successful scam which causes considerable financial and emotional damage to its victims. It is based on building a relationship which establishes a deep trust that causes victims to voluntarily transfer funds to the scammer. The aim of this research is to explore online dating scams as a type of e-Living which initially creates happiness for the victim in a virtual romantic relationship, but tragically then causes the victim to be separated from his or her savings. Using narrative research methodology, this research will establish a model of the romance scam structure and its variations regarding human romantic attitudes, and will develop a theory which explains how the victim is moved through the phases of the scam. Findings of this research will contribute to the knowledge of the Online Romance Scam as e-Crime and provide information about the structure and the development of the modus operandi which can be used to identify an online relationship as a scam at an early phase in order to prevent significant harm to the victim.
The role of love stories in Romance Scams : A qualitative analysis of fraudulent profiles
- Authors: Kopp, Christian , Layton, Robert , Sillitoe, Jim , Gondal, Iqbal
- Date: 2016
- Type: Text , Journal article
- Relation: International Journal of Cyber Criminology Vol. 9, no. 2 (2016), p. 205-216
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- Description: The Online Romance Scam is a very successful scam which causes considerable financial and emotional damage to its victims. In this paper, we provide a perspective that might be helpful to explain the success of this scam. In a similar way to the "The Nigerian letter", we propose that the scam techniques appeal to strong emotions, which are clearly involved in Romantic relationships. We also assume that the same success factors found in normal relationships contribute to the success of the romance scam. In an exploratory study using a qualitative analysis of fraudulent profiles from an international dating website, we examined this assumption. The findings show that personal affinities related to personal romantic imaginations, which are described by personal love stories, play an important role in the success of a romance scam. © 2016 International Journal of Cyber Criminology (IJCC).
Wake-up timer and binary exponential backoff for ZigBee-based wireless sensor network for flexible movement control system of a self-lifting scaffold
- Authors: Liang, Hua , Yang, Guangxiang , Xu, Ye , Gondal, Iqbal , Wu, Chao
- Date: 2016
- Type: Text , Journal article
- Relation: International Journal of Distributed Sensor Networks Vol. 12, no. 9 (2016), p. 1-12
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- Description: Synchronous movement of attached self-lifting scaffolds is traditionally monitored with wired sensors in high-rise building construction, which limits their flexibility of movements. A ZigBee-based wireless sensor system has been suggested in this article to prove the effectiveness of wireless sensor networks in actual implementation. Two optoelectronic sensors are integrated into a ZigBee node for measuring the displacement of attached self-lifting scaffolds. The proposed wireless sensor network combines an end device and a coordinator to allow easy replacement of sensors as compared to a wired network. A wake-up timer algorithm is proposed to reduce the transmitting power during continuous wireless data communication in the wireless sensor network. Furthermore, a variant binary exponential backoff transmission algorithm for data loss avoidance is proposed. The variant binary exponential backoff algorithm reduces packet collisions during simultaneous access by increasing the randomizing moments at nodes attempting to access the wireless channels. The performance of three of the proposed modules - a cable sensor, a 315-MHz sensor, and a ZigBee sensor - is evaluated in terms of packet delivery ratio and the end-to-end delay of a ZigBee-based wireless sensor network. The experimental results show that the proposed variant binary exponential backoff transmission algorithm achieves a higher packet delivery ratio at the cost of higher delays. The average cost of the developed ZigBee-based wireless sensor network decreased by 24% compared with the cable sensor. The power consumption of ZigBee is approximately 53.75% of the 315-MHz sensor. The average current consumption is reduced by approximately 1.5 mA with the wake-up timer algorithm at the same sampling rate. © The Author(s) 2016.
A mapreduce based technique for mining behavioral patterns from sensor data
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Conference paper
- Relation: 22nd International Conference on Neural Information Processing, ICONIP 2015; Istanbul, Turkey; 9th-12th November 2015 Vol. 9492, p. 145-153
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- Description: WSNs generate a large amount of data in the form of streams, and temporal regularity in occurrence behavior is considered as an important measure for assessing the importance of patterns in WSN data. A frequent sensor pattern that occurs after regular intervals in WSNs is called regularly frequent sensor patterns (RFSPs). Existing RFSPs techniques assume that the data structure of the mining task is small enough to fit in the main memory of a processor. However, given the emergence of the Internet of Things (IoT), WSNs in future will generate huge volume of data, which means such an assumption does not hold any longer. To overcome this, a distributed solution using MapReduce model has not yet been explored extensively. Since MapReduce is becoming the de-facto model for computation on large data, an efficient RFSPs mining algorithm on this model is likely to provide a highly effective solution. In this work, we propose a regularly frequent sensor patterns mining algorithm called RFSP-H which uses MapReduce based framework. Extensive performance analyses show that our technique is significantly time efficient in finding regularly frequent sensor patterns. © Springer International Publishing Switzerland 2015.
Complex anomaly for enhanced machine independent condition monitoring
- 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
Condition monitoring through mining fault frequency from machine vibration data
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Conference paper
- Relation: International Joint Conference on Neural Networks, IJCNN 2015; Killarney; Ireland; 12th-17th July 2015 p. 1-8
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- Description: In machine health monitoring, fault frequency identification of potential bearing faults is very important and necessary when it comes to reliable operation of a given system. In this paper, we proposed a data mining based scheme for fault frequency identification from the bearing data. In this scheme, we propose a compact tree called SAP-tree (sliding window associated frequency pattern tree) which is built upon the analysis of frequency domain characteristics of machine vibration data. Using this tree we devised a sliding window-based associated frequency pattern mining technique, called SAP algorithm, that mines for the frequencies relevant to machine fault. Our SAP algorithm can mine associated frequency patterns in the current window with frequent pattern (FP)-growth like pattern-growth method and used these patterns to identify the fault frequency. Extensive experimental analyses show that our technique is very efficient in identifying fault frequency over vibration data stream.
Content exchange among mobile tourists using users' interest and place-centric activities
- 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.
Content sharing among visitors with irregular movement patterns in visiting hotspots
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 IEEE 14th International Symposium on Network Computing and Applications (NCA); Cambridge, United States; 28th - 30th September 2015; published in Proceedings - 2015 IEEE 14th International Symposium on Network Computing and Applications, NCA 2015 p. 230-234
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- Description: Smart mobile devices have become immensely popular among the people worldwide and provide a new platform for generating and sharing contents. The centralized and hybrid architectures for content sharing require constant Internet connection, increase traffic and incur costs. To address these issues several content sharing approaches have been proposed using the decentralized architecture. Most of the proposed approaches use spatio-temporal regularity and pre-existing social relationships of the users to predict their movements and facilitate content sharing. However, there are scenarios such as visiting hotspots where regular movement patterns or established social relationships among people might not exist. Content sharing in such scenarios has not been addressed yet in literature and existing prediction based approaches are ineffectual. This study focuses on facilitating content sharing in the afore-mentioned scenarios. We take account of user interests, recommendations from on-line social networks, hotspot specific activities and other relevant information to construct communities which facilitate content sharing. For each community an administrator, who maintains content and member lists and render directory services, is selected based on stay probability, interest score, battery lifetime and device configuration. Simulation results show that our proposed approach attains high content hit and success rate and low latency in delivery which is nearly comparable to those proposed for scenarios with regular predictable movement patterns reported in literature.
Ethical considerations when using online datasets for research purposes
- Authors: Kopp, Christian , Layton, Robert , Gondal, Iqbal , Sillitoe, Jim
- Date: 2015
- Type: Text , Book chapter
- Relation: Automating Open Source Intelligence: Algorithms for OSINT p. 131-157
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- Description: The Internet has become an important community communications platform, supporting a range of programs and virtual environments. While there are many ways in which people choose to develop personal interactions over the Internet, one of the most popular manifestations is the creation and maintenance of social relationships using social and dating websites. In this chapter, the collection and use of data from such sites is assessed from an ethical frame, and key concepts such as informed consent, information, comprehension, and voluntariness are outlined.
Mining associated patterns from wireless sensor networks
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Computers Vol. 64, no. 7 (2015), p. 1998-2011
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- Description: Mining of sensor data for useful knowledge extraction is a very challenging task. Existing works generate sensor association rules using occurrence frequency of patterns to extract the knowledge. These techniques often generate huge number of rules, most of which are non-informative or fail to reflect true correlation among sensor data. In this paper, we propose a new type of behavioral pattern called associated sensor patterns which capture association-like co-occurrences as well as temporal correlations which are linked with such co-occurrences. To capture such patterns a compact tree structure, called associated sensor pattern tree (ASP-tree) and a mining algorithm (ASP) are proposed which use pattern growth-based approach to generate all associated patterns with only one scan over dataset. Moreover, when data stream flows through, old information may lose significance for the current time. To capture significance of recent data, ASP-tree is further enhanced to SWASP-tree by adopting sliding observation window and updating the tree structure accordingly. Finally, window size is made dynamically adaptive to ensure efficient resource usage. Different characteristics of the proposed techniques and their computational complexity are presented. Experimental results show that our approach is very efficient in discovering associated sensor patterns and outperforms existing techniques.
Share-frequent sensor patterns mining from wireless sensor network data
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Parallel and Distributed Systems Vol. 26, no. 12 (2015), p. 3471-3484
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- Description: Mining interesting knowledge from the huge amount of data gathered from WSNs is a challenge. Works reported in literature use support metric-based sensor association rules which employ the occurrence frequency of patterns as criteria. However, consideration of the binary frequency of a pattern is not a sufficient indicator for finding meaningful patterns because it only reflects the number of epochs which contain that pattern in the dataset. The share measure of sensorsets could discover useful knowledge about trigger values associated with a sensor. Here, we propose a new type of behavioral pattern called share-frequent sensor patterns (SFSPs) by considering the non-binary frequency values of sensors in epochs. SFSPs can find a correlation among a set of sensors and hence can improve the performance of WSNs in a resource management process. In this paper, a share-frequent sensor pattern tree (ShrFSP-Tree) has been proposed to facilitate a pattern growth mining technique to discover SFSPs from WSN data. We also present a parallel and distributed method where the ShrFSP-Tree is enhanced into PShrFSP-Tree and its performance is investigated for both homogeneous and heterogeneous systems. Results show that our method is time and memory efficient in finding SFSPs than the existing most efficient algorithms.
Teeth Tales : A community-based child oral health promotion trial with migrant families in Australia
- Authors: Gibbs, Lisa , Waters, Elizabeth , Christian, Bradley , Gold, Lisa , Young, Dana , De Silva, Andrea , Calache, Hanny , Gussy, Mark , Watt, Richard , Riggs, Elisha , Tadic, Maryanne , Hall, Martin , Gondal, Iqbal , Pradel, Veronika , Moore, Laurence
- Date: 2015
- Type: Text , Journal article
- Relation: BMJ Open Vol. 5, no. 6 (2015), p. 1-13
- Relation: http://purl.org/au-research/grants/arc/LP100100223
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- Description: Objectives: The Teeth Tales trial aimed to establish a model for child oral health promotion for culturally diverse communities in Australia. Design: An exploratory trial implementing a communitybased child oral health promotion intervention for Australian families from migrant backgrounds. Mixed method, longitudinal evaluation. Setting: The intervention was based in Moreland, a culturally diverse locality in Melbourne, Australia. Participants: Families with 1-4-year-old children, self-identified as being from Iraqi, Lebanese or Pakistani backgrounds residing in Melbourne. Participants residing close to the intervention site were allocated to intervention. Intervention: The intervention was conducted over 5 months and comprised community oral health education sessions led by peer educators and follow-up health messages. Outcome measures: This paper reports on the intervention impacts, process evaluation and descriptive analysis of health, knowledge and behavioural changes 18 months after baseline data collection. Results: Significant differences in the Debris Index (OR=0.44 (0.22 to 0.88)) and the Modified Gingival Index (OR=0.34 (0.19 to 0.61)) indicated increased tooth brushing and/or improved toothbrushing technique in the intervention group. An increased proportion of intervention parents, compared to those in the comparison group reported that they had been shown how to brush their child's teeth (OR=2.65 (1.49 to 4.69)). Process evaluation results highlighted the problems with recruitment and retention of the study sample (275 complete case families). The child dental screening encouraged involvement in the study, as did linking attendance with other community/cultural activities. Conclusions: The Teeth Tales intervention was promising in terms of improving oral hygiene and parent knowledge of tooth brushing technique. Adaptations to delivery of the intervention are required to increase uptake and likely impact. A future cluster randomised controlled trial would provide strongest evidence of effectiveness if appropriate to the community, cultural and economic context.
Vibration spectrum imaging : A novel bearing fault classification approach
- 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.
Weighted ANN input layer for adaptive features selection for robust fault classification
- 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.
A novel algorithm for mining behavioral patterns from wireless sensor networks
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2014
- Type: Text , Conference paper
- Relation: 2014 International Joint Conference on Neural Networks, IJCNN 2014; Beijing, China; 6th-11th July 2014 p. 1-7
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- Description: Due to recent advances in wireless sensor networks (WSNs) and their ability to generate huge amount of data in the form of streams, knowledge discovery techniques have received a great deal of attention to extract useful knowledge regarding the underlying network. Traditionally sensor association rules measure 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. In this paper, we propose a new type of sensor behavioral pattern called associated sensor patterns that captures association-like co-occurrences and the strong temporal correlations implied by such co-occurrences in the sensor data. We also propose a novel tree structure called as associated sensor pattern tree (ASPT) and a mining algorithm, associated sensor pattern (ASP) which facilitates frequent pattern (FP) growth-based technique to generate all associated sensor patterns from WSN data with only one scan over the sensor database. Extensive performance study shows that our algorithm is very efficient in finding associated sensor patterns than the existing significant algorithms.
A technique for parallel share-frequent sensor pattern mining from wireless sensor networks
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2014
- Type: Text , Conference paper
- Relation: 14th Annual International Conference on Computational Science, ICCS 2014; Cairns, Australia; 10th-12th June 2014; published in Procedia Computer Science p. 124-133
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- Description: WSNs generate huge amount of data in the form of streams and mining useful knowledge from these streams is a challenging task. Existing works generate sensor association rules using occurrence frequency of patterns with binary frequency (either absent or present) or support of a pattern as a criterion. However, considering the binary frequency or support of a pattern may not be a sufficient indicator for finding meaningful patterns from WSN data because it only reflects the number of epochs in the sensor data which contain that pattern. The share measure of sensorsets could discover useful knowledge about numerical values associated with sensor in a sensor database. Therefore, in this paper, we propose a new type of behavioral pattern called share-frequent sensor patterns by considering the non-binary frequency values of sensors in epochs. To discover share-frequent sensor patterns from sensor dataset, we propose a novel parallel technique. In this technique, we develop a novel tree structure, called parallel share-frequent sensor pattern tree (PShrFSP-tree) that is constructed at each local node independently, by capturing the database contents to generate the candidate patterns using a pattern growth technique with a single scan and then merges the locally generated candidate patterns at the final stage to generate global share-frequent sensor patterns. Comprehensive experimental results show that our proposed model is very efficient for mining share-frequent patterns from WSN data in terms of time and scalability.
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
- 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).