List of Titles

A framework for processing cumulative frequency queries over medical data streams

- Al-Shammari, Ahmed, Zhou, Rui, Liu, Chengfei, Naseriparsa, Mehdi, Vo, Bao

Authors: Al-Shammari, Ahmed , Zhou, Rui , Liu, Chengfei , Naseriparsa, Mehdi , Vo, Bao
Date: 2018
Type: Text , Conference paper
Relation: 19th International Conference on Web Information Systems Engineering, WISE 2018 Vol. 11234 LNCS, p. 121-131
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Description: Medical data streams processing becomes increasingly important since it extracts critical information from a continuous flow of patient data. Various types of problems have been studied on medical data streams, such as classification, clustering, anomaly detection, etc.; however, efficient evaluation of cumulative frequency queries has not been well studied. The cumulative frequency of patients’ status can play an instrumental role in monitoring the patients’ health conditions. Up to now, efficiently processing cumulative frequency queries on medical data streams is still a challenging task due to the large size of the incoming data. Therefore, in this paper, we propose a novel framework for processing the cumulative frequency queries over medical data streams to support the online medical decision. The proposed framework includes two components: data summarisation and dynamic maintenance. For data summarisation, we propose a hybrid approach that combines two data structures and exploits a classification algorithm to select the more efficient data structure for computing the cumulative frequency. For dynamic maintenance, we propose an incremental maintenance approach for updating the cumulative frequencies when new data arrive. The experimental results on a real dataset demonstrate the efficiency of the proposed approach. © Springer Nature Switzerland AG 2018.

A framework for clustering and dynamic maintenance of xml documents

- Al-Shammari, Ahmed, Liu, Chengfei, Naseriparsa, Mehdi, Vo, Bao, Anwar, Tarique, Zhou, Rrui

Authors: Al-Shammari, Ahmed , Liu, Chengfei , Naseriparsa, Mehdi , Vo, Bao , Anwar, Tarique , Zhou, Rrui
Date: 2017
Type: Text , Conference paper
Relation: 13th International Conference on Advanced Data Mining and Applications, ADMA 2017 Vol. 10604 LNAI, p. 399-412
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Description: Web data clustering has been widely studied in the data mining communities. However, dynamic maintenance of the web data clusters is still a challenging task. In this paper, we propose a novel framework called XClusterMaint which serves for both clustering and maintenance of the XML documents. For clustering, we take both structure and content into account and propose an efficient solution for grouping the documents based on the combination of structure and content similarity. For maintenance, we propose an incremental approach for maintaining the existing clusters dynamically when we receive new incoming XML documents. Since the dynamic maintenance of the clusters is computationally expensive, we also propose an improved approach which uses a lazy maintenance scheme to improve the performance of the clusters maintenance. The experimental results on real datasets verify the efficiency of the proposed clustering and maintenance model. © Springer International Publishing AG 2017.

An effective density-based clustering and dynamic maintenance framework for evolving medical data streams

- Al-Shammari, Ahmed, Zhou, Rui, Naseriparsaa, Mehdi, Liu, Chengfei

Authors: Al-Shammari, Ahmed , Zhou, Rui , Naseriparsaa, Mehdi , Liu, Chengfei
Date: 2019
Type: Text , Journal article
Relation: International Journal of Medical Informatics Vol. 126, no. (2019), p. 176-186
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Description: Background: Medical data stream clustering has become an integral part of medical decision systems since it extracts highly-sensitive information from a tremendous flow of medical data. However, clustering and maintaining of medical data streams is still a challenging task. That is because the evolving of medical data streams imposes various challenges for clustering such as the ability to discover the arbitrary shape of a cluster, the ability to group data streams without a predefined number of clusters, and the ability to maintain the data clusters dynamically. Objective: To support the online medical decisions, there is a need to address the clustering challenges. Therefore, in this paper, we propose an effective density-based clustering and dynamic maintenance framework for grouping the patients with similar symptoms into meaningful clusters and monitoring the patients’ status frequently. Methods: For clustering, we generate a set of initial medical data clusters based on the combination of Piece-wise Aggregate Approximation and the density-based spatial clustering of applications with noise called (PAA+DBSCAN) algorithm. For maintenance, when new medical data streams arrive, we maintain the initially generated medical data clusters dynamically. Since the incremental cluster maintenance is time-consuming, we further propose an Advanced Cluster Maintenance (ACM) approach to improve the performance of the dynamic cluster maintenance. Results: The experimental results on real-world medical datasets demonstrate the effectiveness and efficiency of our proposed approaches. The PAA+DBSCAN algorithm is more efficient and effective than the exact DBSCAN algorithm. Moreover, the ACM approach requires less running time in comparison with the Baseline Cluster Maintenance (BCM) approach using different tuning parameter values in all datasets. That is because the BCM approach tracks all the data points in the cluster. Conclusion: The proposed framework is capable of clustering and maintaining the medical data streams effectively by means of grouping the patients who share similar symptoms and tracking the patients status that naturally tends to be changing over time. © 2019 Elsevier B.V.

Scaled boundary finite element method for compressible and nearly incompressible elasticity over arbitrary polytopes

- Aladurthi, Lakshmi, Natarajan, Sundararajan, Ooi, Ean Tat, Song, Chongmin

Authors: Aladurthi, Lakshmi , Natarajan, Sundararajan , Ooi, Ean Tat , Song, Chongmin
Date: 2019
Type: Text , Journal article
Relation: International Journal for Numerical Methods in Engineering Vol. 119, no. 13 (2019), p. 1379-1394
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Description: In this paper, a purely displacement-based formulation is presented within the framework of the scaled boundary finite element method to model compressible and nearly incompressible materials. A selective reduced integration technique combined with an analytical treatment in the nearly incompressible limit is employed to alleviate volumetric locking. The stiffness matrix is computed by solving the scaled boundary finite element equation. The salient feature of the proposed technique is that it neither requires a stabilization parameter nor adds additional degrees of freedom to handle volumetric locking. The efficiency and the robustness of the proposed approach is demonstrated by solving various numerical examples in two and three dimensions.

On-road and wind tunnel aerodynamic study of human powered vehicles

- Alam, Firoz, Chowdhury, Harun, Guillaume, Erika, Yang, Jie, Zimmer, Gary

Authors: Alam, Firoz , Chowdhury, Harun , Guillaume, Erika , Yang, Jie , Zimmer, Gary
Date: 2013
Type: Text , Conference proceedings
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Description: The aim of the Royal Automotive Club of Victoria (RACV) Energy Breakthrough annual event is to provide an opportunity to school students to design and develop human powered vehicles (HPVs) and race a nonstop 24 hours event that requires energy conservation, endurance and reliability. The event involves primary and secondary school students, teachers, parents and local industry to work together on the design and use of energy efficient vehicles. The key areas with interest of HPVs are the significance of aerodynamic design and ways to improve overall aerodynamics as most HPVs are designed with minimal or no aerodynamic consideration. Therefore, the primary objective of this study is to examine the aerodynamic behaviour of two production HPVs of variable designs using on-road, wind tunnel experimentations and Computational Fluid Dynamics (CFD) modelling. The study shows that the aerodynamic efficiency of vehicle largely depends on external shape especially the extrusion, gaps and bumps. The useful data can be obtained and utilized using wind tunnel and on-road tests for HPVs if a close replica along is used. Â© 2013 The Authors.

Aerodynamics of ribbed bicycle racing helmets

- Alam, Firoz, Chowdhury, Harun, Wei, Hozhi, Mustary, Israt, Zimmer, Gary

Authors: Alam, Firoz , Chowdhury, Harun , Wei, Hozhi , Mustary, Israt , Zimmer, Gary
Date: 2014
Type: Text , Conference paper
Relation: 2014 Conference of the International Sports Engineering Association p. 691-696
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Description: In competitive cycling, aero-helmets have been used around since 1980 to reduce aerodynamic resistance. Considerable design effort has been made to improve the aerodynamic efficiency of racing bicycle helmets over the years. However, the demand for further improvement has forced helmet manufacturers and designers to introduce new designs progressively. Recently several helmet manufacturers (e.g., LG, Lazer and Giro) have introduced dimples on the outer shell of helmet mimicking the so called 'Golf-ball' dimple effects with a view to further reduce aerodynamic drag of the helmet. However, no independently verifiable research so far has been reported in the public domain about the aerodynamic performance of ribbed bicycle helmets compared to smooth surfaced helmets. Hence, the primary objective of this work was to undertake an experimental study on four smooth aero-helmets including two latest model ribbed aero-helmets to understand their aerodynamic performance and the effect of dimples on helmets. The investigation was undertaken in an wind tunnel environment over a range of wind speeds, pitch and yaw angles. The experimental data indicate no measurable advantage between the smooth and ribbed helmets under varied pitch angles and at zero yaw angle.

Dynamic adjustment of sensing range for event coverage in wireless sensor networks

- Alam, Kh Mahmudul, Kamruzzaman, Joarder, Karmakar, Gour, Murhsed, Manzur

Authors: Alam, Kh Mahmudul , Kamruzzaman, Joarder , Karmakar, Gour , Murhsed, Manzur
Date: 2014
Type: Text , Journal article
Relation: Journal of Network and Computer Applications Vol. 46, no. (2014), p. 139-153
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Description: One primary goal of sensor networks is to guarantee robust and accurate event detection while reducing energy consumption for extended lifetime. To increase detection fidelity, recent literature introduces redundancy in the sensor field either by maintaining fixed k-coverage throughout lifetime or by providing dynamic k-coverage using mobile sensors after an event is detected. The former requires a large number of sensor nodes and the latter is costly and sometimes infeasible as mobile node deployment in inaccessible areas is difficult. Exploiting recent advances that allow adjustable sensing and transmission radius for sensors, we propose a scheme that ensures 1-coverage at deployment time, but on detection, extends to k-coverage to increase accuracy and robustness. Using an adjustable sensing model through power adjustment, we formulate an optimization problem that determines the optimal sensor set whose sensing and transmission radius are to be adjusted to provide expected coverage degree, through minimizing a cost function comprising energy consumption and achievable accuracy in detection. For a given sensing adjustability, a guideline for deterministic and random deployment is presented to ensure initial coverage. Detection performance and network lifetime are analyzed both theoretically and through simulation. Our approach avoids over-provisioning in sensor network, increases lifetime and scalability, and maintains detection performance in a cost effective way.

Dynamic event coverage in hybrid wireless sensor networks

- Alam, Kh Mahmudul, Kamruzzaman, Joarder, Karmakar, Gour, Murhsed, Manzur

Authors: Alam, Kh Mahmudul , Kamruzzaman, Joarder , Karmakar, Gour , Murhsed, Manzur
Date: 2011
Type: Text , Conference paper
Relation: 10th IEEE International Symposium on Network Computing and Applications, NCA 2011; Cambridge, United States; 25th-27th August 2011 p. 348-353
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Description: For cost effective deployment and implementation, mobility is introduced in sensor networks to provide dynamic event coverage. A hybrid network of static and mobile nodes, can yield the same desired accuracy and robustness of a static k-coverage detection model with fewer nodes. Since node movement is a costly operation and the movement strategy has to be decided instantly after event occurrence, it is desirable to have a lightweight distributed node selection and movement scheme. In this work, we propose a game theoretic model to provide dynamic event coverage that achieves the desired detection accuracy with significantly fewer number of nodes while balancing the energy consumption due to mobility and keeping the travelling distance minimum. We address and exploit the spatial clustering nature of events to maximize the overall detection performance over the network lifetime.

Priority sensitive event detection in hybrid wireless sensor networks

- Alam, Kh Mahmudul, Kamruzzaman, Joarder, Karmakar, Gour, Murhsed, Manzur

Authors: Alam, Kh Mahmudul , Kamruzzaman, Joarder , Karmakar, Gour , Murhsed, Manzur
Date: 2012
Type: Text , Conference paper
Relation: 2012 21st International Conference on Computer Communications and Networks, ICCCN 2012; Munich, Germany; 30th July-2nd August 2012 p. 1-7
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Description: Traditionally, event centric Wireless Sensor Network (WSN) applications treat all events with equal importance, implicitly assuming that all events have same priority. However, in real world applications events may have different level of severity and sensitivity based on their cost of potential damage, occurrence location and frequency. Such applications demand that a detection scheme adopt differentiated treatment of events considering above criteria. Recent works proposed multi-modal sensor nodes for detection of different types of event in a single sensor network and mobile nodes for on-demand attendance of events. When a multi- modal WSN is deployed to monitor events of varied priority, major challenges lies to allocate resources and mobilize mobile nodes in an optimized way to maximize detection performance. We introduce the concept of varied priority and cost of mis-detection of events, and propose a detection scheme for multiple simultaneous events in a hybrid sensor network. Mobile nodes are mobilized through formulation of an optimization problem that maximizes the prioritized accuracy while minimizing detection delay. Theoretical and simulation results demonstrate that our scheme significantly outperforms other scheme that treats all events equally.

Metal concentrations in rice and pulses of Samta Village, Bangladesh

- Alam, M. G. M., Allinson, Graeme, Stagnitti, Frank, Tanaka, A., Westbrooke, Martin

Authors: Alam, M. G. M. , Allinson, Graeme , Stagnitti, Frank , Tanaka, A. , Westbrooke, Martin
Date: 2002
Type: Text , Journal article
Relation: Bulletin of Environmental Contamination and Toxicology Vol. 69, no. 3 (2002), p. 323-329
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Description: 2003000169

Arsenic contamination in Bangladesh groundwater : A major environmental and social disaster

- Alam, M. G. M., Allinson, Graeme, Stagnitti, Frank, Tanaka, A., Westbrooke, Martin

Authors: Alam, M. G. M. , Allinson, Graeme , Stagnitti, Frank , Tanaka, A. , Westbrooke, Martin
Date: 2002
Type: Text , Journal article
Relation: International Journal of Environmental Health Research Vol. 12, no. 3 (2002), p. 236-253
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Description: In attempting to eliminate disease caused by drinking polluted surface water, millions of shallow surface wells were drilled into the Ganges delta alluvium in Bangladesh. The latest statistics indicate that 80% of Bangladesh and an estimated 40 million people are at risk of arsenic poisoning-related diseases because the ground water in these wells is contaminated with arsenic. The clinical manifestations of arsenic poisoning are myriad, and the correct diagnosis depends largely on awareness of the problem. Patients with melanosis, leuco-melanosis, keratosis, hyperkeratosis, dorsum, non-petting edema, gangrene and skin cancer have been identified. The present article reviews the current arsenic contamination of ground water, hydrological systems, groundwater potential and utilization and environmental pollution in Bangladesh. This paper concludes by clarifying the main actions required to ensure the sustainable development of water resources in Bangladesh.
Description: 2003000124

An optimal transportation routing approach using GIS-based dynamic traffic flows

- Alazab, Ammar, Venkatraman, Sitalakshmi, Abawajy, Jemal, Alazab, Mamoun

Authors: Alazab, Ammar , Venkatraman, Sitalakshmi , Abawajy, Jemal , Alazab, Mamoun
Date: 2010
Type: Text , Conference proceedings
Full Text: false
Description: This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively.

Malware detection and prevention system based on multi-stage rules

- Alazab, Ammar, Hobbs, Michael, Abawajy, Jemal, Khraisat, Ansam

Authors: Alazab, Ammar , Hobbs, Michael , Abawajy, Jemal , Khraisat, Ansam
Date: 2013
Type: Text , Journal article
Relation: International Journal of Information Security and Privacy Vol. 7, no. 2 (2013), p. 29-43
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Description: The continuously rising Internet attacks pose severe challenges to develop an effective Intrusion Detection System (IDS) to detect known and unknown malicious attack. In order to address the problem of detecting known, unknown attacks and identify an attack grouped, the authors provide a new multi stage rules for detecting anomalies in multi-stage rules. The authors used the RIPPER for rule generation, which is capable to create rule sets more quickly and can determine the attack types with smaller numbers of rules. These rules would be efficient to apply for Signature Intrusion Detection System (SIDS) and Anomaly Intrusion Detection System (AIDS). Copyright © 2013, IGI Global.

Crime toolkits: The productisation of cybercrime

- Alazab, Ammar, Abawajy, Jemal, Hobbs, Michael, Layton, Robert, Khraisat, Ansam

Authors: Alazab, Ammar , Abawajy, Jemal , Hobbs, Michael , Layton, Robert , Khraisat, Ansam
Date: 2013
Type: Text , Conference paper
Relation: Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013 p. 1626-1632
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Maximising competitive advantage on e-Business websites : A data mining approach

- Alazab, Ammar, Bevinakoppa, Savitri, Khraisat, Ansam

Authors: Alazab, Ammar , Bevinakoppa, Savitri , Khraisat, Ansam
Date: 2018
Type: Text , Conference proceedings , Conference paper
Relation: 2018 IEEE Conference on Big Data and Analytics, ICBDA 2018; Langkawi, Malaysia; 21st-22nd November 2018 p. 111-116
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Description: Many organizations are interested in analyzing and evaluating the web data for their websites because websites are a very important platform to carry out their business. However, website evaluations face many challenges in using analytics, especially with the huge amount of data that the websites are collecting from various sources. This explosive growth in data requires a complex tool for analyzing and automatically convert the data into valuable information. However, without using a proper analysis tool, it is very difficult to understand the user's behaviour, user's interaction patterns on the website and how users involve in the site. This paper explains methods to examine, understand and visualize the huge amounts of stored data collected from the websites. In this paper, a framework is developed for identifying user's behaviours on websites. Firstly, the attributes are extracted from different websites using Google Analytics and other API tools. Secondly, data mining techniques such as clustering, classification and information gain are applied to build this framework. The findings of these study can be used to evaluate the website and provide some guidelines for the web team to increase user engagement on the website and understand the influence of user behaviour. In addition, this framework is able to identify which behaviour features influence user decisions. Our proposed framework for identifying user's behaviours on websites is tested on a large dataset that contains a variety of individual users from different websites. © 2018 IEEE.

Effective digital forensic analysis of the NTFS disk image

- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul

Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
Date: 2009
Type: Text , Journal article
Relation: Ubiquitous Computing and Communication Journal Vol. 4, no. 3 (Special issue on ICIT 2009 Conference - Applied Computing) (2009), p. 551-558
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Description: Forensic analysis of the Windows NT File System (NTFS) could provide useful information leading towards malware detection and presentation of digital evidence for the court of law. Since NTFS records every event of the system, forensic tools are required to process an enormous amount of information related to user / kernel environment, buffer overflows, trace conditions, network stack, etc. This has led to imperfect forensic tools that are practical for implementation and hence become popular, but are not comprehensive and effective. Many existing techniques have failed to identify malicious code in hidden data of the NTFS disk image. This research discusses the analysis technique we have adopted to successfully detect maliciousness in hidden data, by investigating the NTFS boot sector. We have conducted experimental studies with some of the existing popular forensics tools and have identified their limitations. Further, through our proposed three-stage forensic analysis process, our experimental investigation attempts to unearth the vulnerabilities of NTFS disk image and the weaknesses of the current forensic techniques.
Description: 2003007525

Information security governance: The art of detecting hidden malware

- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul

Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
Date: 2013
Type: Text , Book chapter
Relation: IT Security governance innovations: Theory and research p. 293-315
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Description: Detecting malicious software or malware is one of the major concerns in information security governance as malware authors pose a major challenge to digital forensics by using a variety of highly sophisticated stealth techniques to hide malicious code in computing systems, including smartphones. The current detection techniques are futile, as forensic analysis of infected devices is unable to identify all the hidden malware, thereby resulting in zero day attacks. This chapter takes a key step forward to address this issue and lays foundation for deeper investigations in digital forensics. The goal of this chapter is, firstly, to unearth the recent obfuscation strategies employed to hide malware. Secondly, this chapter proposes innovative techniques that are implemented as a fully-automated tool, and experimentally tested to exhaustively detect hidden malware that leverage on system vulnerabilities. Based on these research investigations, the chapter also arrives at an information security governance plan that would aid in addressing the current and future cybercrime situations.

Malware detection based on structural and behavioural features of API calls

- Alazab, Mamoun, Layton, Robert, Venkatraman, Sitalakshmi, Watters, Paul

Authors: Alazab, Mamoun , Layton, Robert , Venkatraman, Sitalakshmi , Watters, Paul
Date: 2010
Type: Text , Conference proceedings
Full Text: false
Description: In this paper, we propose a five-step approach to detect obfuscated malware by investigating the structural and behavioural features of API calls. We have developed a fully automated system to disassemble and extract API call features effectively from executables. Using n-gram statistical analysis of binary content, we are able to classify if an executable file is malicious or benign. Our experimental results with a dataset of 242 malwares and 72 benign files have shown a promising accuracy of 96.5% for the unigram model. We also provide a preliminary analysis by our approach using support vector machine (SVM) and by varying n-values from 1 to 5, we have analysed the performance that include accuracy, false positives and false negatives. By applying SVM, we propose to train the classifier and derive an optimum n-gram model for detecting both known and unknown malware efficiently.

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