A reasoning community perspective on deliberate democracy
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2011
- Type: Text , Book chapter
- Relation: Technologies for supporting reasoning communities and collaborative decision making: Cooperative approaches p.237-246
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- Description: This chapter describes some of the current approaches to delibertative democracy and the considers them from the perspective of a reasoning community framework. This approach highlights important tasks, process and structures that can be used to enhance the process of groups engaging in deliberative democracy approaches. In particular it focuses attention on the potential for technologies to support groups in achieving broad agreed structured reasoning bases that capture the scope of an issue from multiple perspectives.
A reasoning framework for decision making in water allocation: a tree for water
- Authors: Graymore, Michelle , Mays, Heather , Stranieri, Andrew , Lehmann, La Vergne , McRae-Williams, Pamela , Thoms, Gavin , Yearwood, John
- Date: 2011
- Type: Text , Conference paper
- Relation: Paper presented at International Conference on Integrated Water Management 2011
- Full Text: false
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A reinforcement learning approach with spline-fit object tracking for AIBO Robot's high level decision making
- Authors: Mukherjee, Subhasis , Huda, Shamsul , Yearwood, John
- Date: 2011
- Type: Text , Book chapter
- Relation: Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing p. 169-183
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- Description: Robocup is a popular test bed for AI programs around the world. Robosoccer is one of the two major parts of Robocup, in which AIBO entertainment robots take part in the middle sized soccer event. The three key challenges that robots need to face in this event are manoeuvrability, image recognition and decision making skills. This paper focuses on the decision making problem in Robosoccer-The goal keeper problem. We investigate whether reinforcement learning (RL) as a form of semi-supervised learning can effectively contribute to the goal keeper's decision making process when penalty shot and two attacker problem are considered. Currently, the decision making process in Robosoccer is carried out using rule-base system. RL also is used for quadruped locomotion and navigation purpose in Robosoccer using AIBO. Moreover the ball distance is being calculated using IR sensors available at the nose of the robot. In this paper, we propose a reinforcement learning based approach that uses a dynamic state-action mapping using back propagation of reward and Q-learning along with spline fit (QLSF) for the final choice of high level functions in order to save the goal. The novelty of our approach is that the agent learns while playing and can take independent decision which overcomes the limitations of rule-base system due to fixed and limited predefined decision rules. The spline fit method used with the nose camera was also able to find out the location and the ball distance more accurately compare to the IR sensors. The noise source and near and far sensor dilemma problem with IR sensor was neutralized using the proposed spline fit method. Performance of the proposed method has been verified against the bench mark data set made with Upenn'03 code logic and a base line experiment with IR sensors. It was found that the efficiency of our QLSF approach in goalkeeping was better than the rule based approach in conjunction with the IR sensors. The QLSF develops a semi-supervised learning process over the rule-base system's input-output mapping process, given in the Upenn'03 code. © 2011 Springer-Verlag Berlin Heidelberg.
An application of novel clustering technique for information security
- Authors: Beliakov, Gleb , Yearwood, John , Kelarev, Andrei
- Date: 2011
- Type: Text , Conference paper
- Relation: Applications and Techniques in Information Security Workshop p. 5-11
- Full Text: false
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- Description: This article presents experimental results devoted to a new application of the novel clustering technique introduced by the authors recently. Our aim is to facilitate the application of robust and stable consensus functions in information security, where it is often necessary to process large data sets and monitor outcomes in real time, as it is required, for example, for intrusion detection. Here we concentrate on the particular case of application to profiling of phishing websites. First, we apply several independent clustering algorithms to a randomized sample of data to obtain independent initial clusterings. Silhouette index is used to determine the number of clusters. Second, we use a consensus function to combine these independent clusterings into one consensus clustering . Feature ranking is used to select a subset of features for the consensus function. Third, we train fast supervised classification algorithms on the resulting consensus clustering in order to enable them to process the whole large data set as well as new data. The precision and recall of classifiers at the final stage of this scheme are critical for effectiveness of the whole procedure. We investigated various combinations of three consensus functions, Cluster-Based Graph Formulation (CBGF), Hybrid Bipartite Graph Formulation (HBGF), and Instance-Based Graph Formulation (IBGF) and a variety of supervised classification algorithms. The best precision and recall have been obtained by the combination of the HBGF consensus function and the SMO classifier with the polynomial kernel.
- Description: 2003009195
Case based web services
- Authors: Sun, Zhaohao , Finnie, Gavin , Yearwood, John
- Date: 2011
- Type: Text , Book chapter
- Relation: Encyclopedia of E-Business Development and Management in the Global Economy p. 871-882
- Full Text: false
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- Description: Web services are Internet-based application components published using standard interface description languages and universally available via uniform communication protocols (Singh & Huhns, 2005). Web services can be also considered the provision of services over electronic networks such as the Internet and wireless networks (Rust & Kannan, 2003). Web services is a new computing paradigm that has drawn increasing attention in information technology (Deitel, et al, 2004, p.13), information systems, and is playing a pivotal role in service computing and service intelligence (Singh & Huhns, 2005). Web services is a new business paradigm that is playing an important role in e-business, ecommerce and business intelligence (Wang, et al, 2006). The key motive for the rapid development of web services is the ability to discover services that fulfil users’ demands, negotiate service contracts and have the services delivered where and when the users request them (Tang, et al, 2007). The current research trend is to add intelligent techniques to web services to facilitate discovery, invocation, composition, and recommendation of web services (Wang, et al, 2006)
Child face detection using age specific luminance invariant geometric descriptor
- Authors: Islam, Mofakharul , Watters, Paul , Yearwood, John
- Date: 2011
- Type: Text , Conference proceedings
- Full Text: false
- Description: While considerable research have been conducted on age-wise age estimation using skin detection most often with other visual cues, relatively little research has looked closely at the subject. In this paper, we present a new framework for interpreting facial image patterns that can be employed in categorical age estimation. The aim is to propose a novel approach to investigate and implement a child face detection technique that is able to estimate age categorically adult or child based on a new hybrid feature descriptor. The novel hybrid feature descriptor LIGD (the luminance invariant geometric descriptor) is composed of some low and high level features, which are found to be effective in characterizing the local appearance. In local appearance estimation, chromaticity, texture, and positional information of few facial visual cues can be employed simultaneously. Compared to the results published in a recent work, our proposed approach yields the highest precision and recall, and overall accuracy in recognition. © 2011 IEEE.
Demand driven web services
- Authors: Sun, Zhaohao , Dong, Dong , Yearwood, John
- Date: 2011
- Type: Text , Book chapter
- Relation: Service intelligence and service science: Evolutionary technologies and challenges p. 35-55
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- Description: Web services are playing a pivotal role in e-business, service intelligence, and service science. Demand-driven web services are becoming important for web services and service computing. However, many fundamental issues are still ignored to some extent. For example, what is the demand theory for web services, what is a demand-driven architecture for web services and what is a demand-driven web service lifecycle remain open. This chapter addresses these issues by examining fundamentals for demand analysis in web services, and proposing a demand-driven architecture for web services. It also proposes a demand-driven web service lifecycle for the main players in web services: Service providers, service requestors and service brokers, respectively. It then provides a unified perspective on demand-driven web service lifecycles. The proposed approaches will facilitate research and development of web services, e-services, service intelligence, service science and service computing.
- Description: 2003009207
Detection of child exploiting chatsfrom a mixed chat dataset as a text classification task
- Authors: Yearwood, John , Miah, Md Waliur Rahman , Kulkarni, Siddhivinayak
- Date: 2011
- Type: Text , Conference paper
- Relation: Proceedings of Australasian Language Technology Association Workshop
- Full Text: false
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- Description: There is a rapidly growing body of work in the use of Embodied Conversational Agents (ECA) to convey complex contextual relationships through verbal and non-verbal communication, in domains ranging from military C2 to e-learning. In these applications the subject matter expert in often naive to the technical requirements of ECAs. ENGAGE (the Extensible Natural Gesture Animation Generation Engine) is desgined to automatically generate appropriate and 'realistic' animation for ECAs based on the content provided to them. It employs syntactic analysis of the surface text and uses predefined behaviours for the ECA. We discuss the design of this system, its current applications and plans for its future development.
Does the Delphi process lead to increased accuracy in group-based judgmental forecasts or does it simply induce consensus amongst judgmental forecasters?
- Authors: Bolger, Fergus , Stranieri, Andrew , Wright, George , Yearwood, John
- Date: 2011
- Type: Text , Journal article
- Relation: Technological Forecasting and Social Change Vol. , no. (2011), p.
- Full Text: false
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- Description: We investigate the relative impact of internal Delphi process factors - including panelists' degree of confidence, expertise, majority/minority positioning - and an external factor, richness of feedback - on opinion change and subsequent accuracy of judgmental forecasts. We found that panelists who had low confidence in their judgmental forecast and/or who were in a minority were more likely to change their opinion than those who were more confident and/or in a majority. The addition of rationales, or reasons, to the numeric feedback had little impact upon panelists' final forecasts, despite the quality of panelists' rationales being significantly positively correlated with accurate forecasts and thus of potential use to aid forecast improvement over Delphi rounds. Rather, the effect of rationales was similar to that of confidence: to pull panelists towards the majority opinion regardless of its correctness. We conclude that majority opinion is the strongest influence on panelists' opinion change in both the 'standard' Delphi, and Delphi-with-reasons. We make some suggestions for improved variants of the Delphi-with-reasons technique that should help reduce majority influence and thereby permit reasoned arguments to exert their proper pull on opinion change, resulting in forecast accuracy improvements over Delphi rounds. © 2011.
ICT change agents: Global actors in financial services technology projects
- Authors: Jagodick, Jana , Courvisanos, Jerry , Yearwood, John
- Date: 2011
- Type: Text , Journal article
- Relation: Asia Pacific Management Review Vol. 16, no. 2 (2011), p. 165-180
- Full Text: false
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- Description: The global demand for web-based applications regarding financial products and services drives the financial sector to innovate through Information and Communication Technology (ICT) projects. The ICT projects are launched for the diffusion (spread) and implementation of new software or hardware by using web-based platforms in order to offer innovative financial products and services across the branch bank system. These projects are initiated, diffused, managed and implemented by global actors, so-called ICT change agents. Despite the increased recruitment of ICT change agents, there is relatively little research available regarding ICT change agents in financial services projects. Specifically, little consideration is given to the interaction process between formal and informal ICT change agents' roles. Based on a case study methodology in Australia and Germany, this research indicates that deadline-oriented projects drive ICT change agents to play various formal and informal roles. Their formal roles are performed in accordance with organisational settings and project management standards, whereas their informal operations are due to the rapid-changing and global nature of ICT technologies. The findings are summed up in a new framework which indicates that both types of roles impact on the outcomes of financial services technology projects.
Optimization and matrix constructions for classification of data
- Authors: Kelarev, Andrei , Yearwood, John , Vamplew, Peter , Abawajy, Jemal , Chowdhury, Morshed
- Date: 2011
- Type: Journal article
- Relation: New Zealand Journal of Mathematics Vol. 41, no. 2011 (2011), p. 65-73
- Full Text:
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- Description: Max-plus alegbras and more general semirings have many useful applications and have been actively investigated. On the other hand, structural matrix rings are also well known and have been considered by many authors. The main theorem of this article completely describes all optimal ideas in the more general structural matrix semirings. Originally, our investigation of these ideals was motivated by applications in data mining for the design of multiple classification systems combining several individual classifiers.
Optimization of classifiers for data mining based on combinatorial semigroups
- Authors: Kelarev, Andrei , Yearwood, John , Watters, Paul
- Date: 2011
- Type: Text , Journal article
- Relation: Semigroup Forum Vol. 82, no. 2 (2011), p. 1-10
- Full Text:
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- Description: The aim of the present article is to obtain a theoretical result essential for applications of combinatorial semigroups for the design of multiple classification systems in data mining. We consider a novel construction of multiple classification systems, or classifiers, combining several binary classifiers. The construction is based on combinatorial Rees matrix semigroups without any restrictions on the sandwich-matrix. Our main theorem gives a complete description of all optimal classifiers in this novel construction. © 2011 Springer Science+Business Media, LLC.
Optimization of matrix semirings for classification systems
- Authors: Gao, David , Kelarev, Andrei , Yearwood, John
- Date: 2011
- Type: Text , Journal article
- Relation: Bulletin of the Australian Mathematical Society Vol. 84, no. 3 (2011), p. 492-503
- Full Text:
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- Description: The max-plus algebra is well known and has useful applications in the investigation of discrete event systems and affine equations. Structural matrix rings have been considered by many authors too. This article introduces more general structural matrix semirings, which include all matrix semirings over the max-plus algebra. We investigate properties of ideals in this construction motivated by applications to the design of centroid-based classification systems, or classifiers, as well as multiple classifiers combining several initial classifiers. The first main theorem of this paper shows that structural matrix semirings possess convenient visible generating sets for ideals. Our second main theorem uses two special sets to determine the weights of all ideals and describe all matrix ideals with the largest possible weight, which are optimal for the design of classification systems. © Copyright Australian Mathematical Publishing Association Inc. 2011.
- Description: 2003009498
Real-time detection of children's skin on social networking sites using Markov random field modelling
- Authors: Islam, Mofakharul , Watters, Paul , Yearwood, John
- Date: 2011
- Type: Text , Journal article
- Relation: Information Security Technical Report Vol. 16, no. 2 (2011), p. 51-58
- Full Text: false
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- Description: Social networking sites are increasingly being used as the source for paedophiles to search for, download and exchange child exploitation images. Law Enforcement Agencies (LEAs) around the world face a difficult challenge to combat technologically-savvy paedophiles. In this paper, we propose a framework for detecting images containing children's pictures in different poses, with the ultimate view of identifying and classifying images as corresponding to the COPINE scale. To achieve the goal of automatic detection, we present a novel stochastic vision model based on a Markov Random Fields (MRF) prior, which will employ a skin model and human affine-invariant geometric descriptor to detect and identify skin regions containing pornographic contexts. © 2011 Published by Elsevier Ltd.
Reinforcement learning approach to AIBO robot's decision making process in Robosoccer's goal keeper problem
- Authors: Mukherjee, Subhasis , Yearwood, John , Vamplew, Peter , Huda, Shamsul
- Date: 2011
- Type: Text , Conference proceedings
- Full Text: false
- Description: Robocup is a popular test bed for AI programs around the world. Robosoccer is one of the two major parts of Robocup, in which AIBO entertainment robots take part in the middle sized soccer event. The three key challenges that robots need to face in this event are manoeuvrability, image recognition and decision making skills. This paper focuses on the decision making problem in Robosoccer - The goal keeper problem. We investigate whether reinforcement learning (RL) as a form of semi-supervised learning can effectively contribute to the goal keeper's decision making process when penalty shot and two attacker problem are considered. Currently, the decision making process in Robosoccer is carried out using rule-base system. RL also is used for quadruped locomotion and navigation purpose in Robosoccer using AIBO. In this paper, we propose a reinforcement learning based approach that uses a dynamic state-action mapping using back propagation of reward and space quantized Q-learning (SQQL) for the choice of high level functions in order to save the goal. The novelty of our approach is that the agent learns while playing and can take independent decision which overcomes the limitations of rule-base system due to fixed and limited predefined decision rules. Performance of the proposed method has been verified against the bench mark data set made with Upenn'03 code logic. It was found that the efficiency of our SQQL approach in goalkeeping was better than the rule based approach. The SQQL develops a semi-supervised learning process over the rule-base system's input-output mapping process, given in the Upenn'03 code. © 2011 IEEE.
Technologies for supporting reasoning communities and collaborative decision making: Cooperative approaches
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2011
- Type: Text , Book
- Full Text: false
- Reviewed:
- Description: The information age has enabled unprecedented levels of data to be collected and stored. At the same time, society and organizations have become increasingly complex. Consequently, decisions in many facets have become increasingly complex but have the potential to be better informed. Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches includes chapters from diverse fields of enquiry including decision science, political science, argumentation, knowledge management, cognitive psychology and business intelligence. Each chapter illustrates a perspective on group reasoning that ultimately aims to lead to a greater understanding of reasoning communities and inform technological developments.
A new supervised term ranking method for text categorization
- Authors: Mammadov, Musa , Yearwood, John , Zhao, Lei
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at 23rd Australasian Joint Conference on Artificial Intelligence, AI 2010 Vol. 6464 LNAI, p. 102-111
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- Description: In text categorization, different supervised term weighting methods have been applied to improve classification performance by weighting terms with respect to different categories, for example, Information Gain, χ2 statistic, and Odds Ratio. From the literature there are three term ranking methods to summarize term weights of different categories for multi-class text categorization. They are Summation, Average, and Maximum methods. In this paper we present a new term ranking method to summarize term weights, i.e. Maximum Gap. Using two different methods of information gain and χ2 statistic, we setup controlled experiments for different term ranking methods. Reuter-21578 text corpus is used as the dataset. Two popular classification algorithms SVM and Boostexter are adopted to evaluate the performance of different term ranking methods. Experimental results show that the new term ranking method performs better. © 2010 Springer-Verlag.
Adaptive clustering with feature ranking for DDoS attacks detection
- Authors: Zi, Lifang , Yearwood, John , Wu, Xin
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Distributed Denial of Service (DDoS) attacks pose an increasing threat to the current internet. The detection of such attacks plays an important role in maintaining the security of networks. In this paper, we propose a novel adaptive clustering method combined with feature ranking for DDoS attacks detection. First, based on the analysis of network traffic, preliminary variables are selected. Second, the Modified Global K-means algorithm (MGKM) is used as the basic incremental clustering algorithm to identify the cluster structure of the target data. Third, the linear correlation coefficient is used for feature ranking. Lastly, the feature ranking result is used to inform and recalculate the clusters. This adaptive process can make worthwhile adjustments to the working feature vector according to different patterns of DDoS attacks, and can improve the quality of the clusters and the effectiveness of the clustering algorithm. The experimental results demonstrate that our method is effective and adaptive in detecting the separate phases of DDoS attacks. © 2010 IEEE.
An application of consensus clustering for DDoS attacks detection
- Authors: Zi, Lifang , Yearwood, John , Kelarev, Andrei
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: The detection of Distributed Denial of Service (DDos) attacks is very important for maintaining the security of networks and the Internet. This paper introduces a novel iterative consensus process based on Hybrid Bipartite Graph Formulation (HGBF) consensus function for DDos attacks detection. First, the features are extracted during feature extraction process based on the analysis of network traffic. Second, several clustering algorithms are applied in combination with the silhouette index to obtain a collection of independent initial clusterings. Third, the HGBF consensus function and silhouette index are used to find an appropriate consensus clustering of the initial clusterings. Fourth, this new consensus clustering is added to the pool of initial clusterings replacing another clustering with the worst Silhouette index. Fifth, the process continues iteratively until the Silhouette index of the resulting consensus clusterings stabilizes. This iterative consensus clustering process can improve the quality of the clusters. The experimental results demonstrate that our iterative consensus process is effective and can be used in practice for detecting the separate phased of DDos attacks.
Automated opinion detection : Implications of the level of agreement between human raters
- Authors: Osman, Deanna , Yearwood, John , Vamplew, Peter
- Date: 2010
- Type: Text , Journal article
- Relation: Information Processing and Management Vol. 46, no. 3 (2010), p. 331-342
- Full Text: false
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- Description: The ability to agree with the TREC Blog06 opinion assessments was measured for seven human assessors and compared with the submitted results of the Blog06 participants. The assessors achieved a fair level of agreement between their assessments, although the range between the assessors was large. It is recommended that multiple assessors are used to assess opinion data, or a pre-test of assessors is completed to remove the most dissenting assessors from a pool of assessors prior to the assessment process. The possibility of inconsistent assessments in a corpus also raises concerns about training data for an automated opinion detection system (AODS), so a further recommendation is that AODS training data be assembled from a variety of sources. This paper establishes an aspirational value for an AODS by determining the level of agreement achievable by human assessors when assessing the existence of an opinion on a given topic. Knowing the level of agreement amongst humans is important because it sets an upper bound on the expected performance of AODS. While the AODSs surveyed achieved satisfactory results, none achieved a result close to the upper bound. © 2009 Elsevier Ltd. All rights reserved.