Small businesses, Institutions, and Regional Incomes
- Authors: Mardaneh, Karim , O'Malley, Tony
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 59th ISCB World Conference, Entrepreneurship and sustainability, Dublin, 11th June, 2014
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- Description: Regional small businesses may rely on customers who earn income in local and global markets. Small business must transact with suppliers of knowledge and resources, transform those resources into innovative and saleable products or services, and transact with customers. Transformation, transaction and social activities, and the institutions which support them, are necessary for successful small businesses. Regional income and small businesses depend on innovation and trade provided by social and transaction institutions. In this paper we demonstrate this proposition empirically using a model and by investigating the relationship between regional income, transaction institutions, transformation institutions, and social institutions for 140 functional economic regions (FERs) in Australia. The model suggests that social institutions create a macro-environment in which transaction institutions and the transformation and trading activities of businesses can thrive, and help to generate regional income and prosperity. We follow others (Cooke et al., 2007) in arguing that strong transaction institutions are a necessary condition for regional innovation. Social institutions complement transaction institutions by providing education and training, arts and recreation, health care and social services. In the studies reported in this paper the capacity for search and intermediation of exchanges of all kinds (goods, services, knowledge etc.) is measured by the share of transaction institutions in regional employment. The capacity of social institutions is measured by the share of employment in social institutions. We argue that the market failures which cause regional failures to thrive may be made solvable by mobilising market making services to extend and provide governance for regional transactions with faraway markets.
The importance of mandatory data breach notification to identity crime
- Authors: Holm, Eric , Mackenzie, Geraldine
- Date: 2014
- Type: Text , Conference proceedings
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- Description: The relationship between data breaches and identity crime has been scarcely explored in current literature. However, there is an important relationship between the misuse of personal identification information and identity crime as the former is in many respects the catalyst for the latter. Data breaches are one of the ways in which this personal identification information is obtained by identity criminals, and thereby any response to data breaches is likely to impact the incidence of identity crime. Initiatives around data breach notification have become increasingly prevalent and are now seen in many State legislatures in the United States and overseas. The Australian Government is currently in the process of introducing mandatory data breach notification laws. This paper explores the introduction of mandatory data breach notification in Australia, and lessons learned from the experience in the US, particularly noting the link between data breaches and identity crime. The paper proposes that through the introduction of such laws, identity crimes are likely to be reduced.
A review on chemical diagnosis techniques for transformer paper insulation degradation
- Authors: Abu Bakar, Norazhar , Abu Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
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- Description: Energized parts within power transformer are isolated using paper insulation and are immersed in insulating oil. Hence, transformer oil and paper insulation are essential sources to detect incipient and fast developing power transformer faults. Several chemical diagnoses techniques are developed to examine the condition of paper insulation such as degree of polymerization, carbon oxides, furanic compounds and methanol. The principle and limitation of these diagnoses are discussed and compared in this paper.
An improved building detection in complex sites using the LIDAR height variation and point density
- Authors: Siddiqui, Fasahat , Teng, Shyh , Lu, Guojun , Awrangjeb, Mohammad
- Date: 2013
- Type: Text , Conference proceedings
- Relation: 2013 28th International Conference on Image and Vision Computing New Zealand, IVCNZ 2013; Wellington; New Zealand; 27th-29th November 2013; published in International Conference Image and Vision Computing New Zealand p. 471-476
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- Description: In this paper, the height variation in LIDAR (Light Detection And Ranging) point cloud data and point density are analyzed to remove the false building detection in highly vegetation and hilly sites. In general, the LIDAR points in a tree area have higher height variations than those in a building area. Moreover, the density of points having similar height values is lower in a tree area than in a building area. The proposed method uses such information as an improvement to a current state-of-the-art building detection method. The qualitative and object-based quantitative analyzes have been performed to verify the effectiveness of the proposed building detection method as compared with a current method. The analysis shows that proposed building detection method successfully reduces false building detection (i.e. trees in high complex sites of Australia and Germany), and the average correctness and quality have been improved by 6.36% and 6.16% respectively.
Estimation of induction motor parameters using hybrid algorithms for power system dynamic studies
- Authors: Susanto, Julius , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
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- Description: This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.
Image processing-based on-line technique to detect power transformer winding faults
- Authors: Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013; Vienna, Austria; 10th-14th November 2013 p. 1-6
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- Description: Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
Impact of axial displacement on power transformer FRA signature
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 IEEE Power and Energy Society General Meeting, PES 2013; Vancouver, Canada; 21st-25th July 2013 p. 1-4
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- Description: Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a singlephase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model’s parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer.
Local n-grams for author identification: Notebook for PAN at CLEF 2013 C3 - CEUR Workshop Proceedings
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Conference proceedings
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- Description: Our approach to the author identification task uses existing authorship attribution methods using local n-grams (LNG) and performs a weighted ensemble. This approach came in third for this year's competition, using a relatively simple scheme of weights by training set accuracy. LNG models create profiles, consisting of a list of character n-grams that best represent a particular author's writing. The use of a weighted ensemble improved upon the accuracy of the method without reducing the speed of the algorithm; the submitted solution was not only near the top of the leaderboard in terms of accuracy, but it was also one of the faster algorithms submitted.
A new hybrid method combining genetic algorithm and coordinate search method
- Authors: Long, Qiang , Huang, Junjian
- Date: 2012
- Type: Text , Conference proceedings
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- Description: This paper proposed a new hybrid method combining genetic algorithm(GA) and coordinate search method (CSM). Genetic algorithm is good at global exploration but bad at accuracy and local search. Whereas, coordinate search method is good at local exploitation, and its accuracy is reliable when searching in a local area. Thus we combine those two methods in this paper to design a hybrid method called genetic algorithm with coordinate search (GACS). Experimental tests shows that this method are good at both global search and local accuracy. © 2012 IEEE.
- Description: 2003010808
A surrogate model for evaluation of maximum normalized dynamic load factor in moving load model for pipeline spanning due to slug flow
- Authors: Sultan, Ibrahim , Reda, Ahmed , Forbes, Gareth
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Understanding the problem of slug-flow-induced fatigue damage is of particular importance to the reliable operation of pipelines. Slug flow, across unsupported pipeline spans, produces dynamic vibrations in the pipeline resulting in cyclical fatigue stresses. These dynamic effects will cause the pipeline to fail at a point of stress concentration if proper design procedure is not followed. The response of a pipeline span, under the passage of slug flow, can be represented by dynamic load factors that are functions of the speed ratio and damping characteristics of the span. The aspects of these functional relationships are investigated, in this paper by conducting multiple simulations at different speed ratios and damping factors. The data obtained from the steady state Fourier expansion will, consequently, be used to produce a surrogate model with a level of accuracy that adequately qualifies it for use in determining dynamic loading of pipelines. The closed-form surrogate model can be used to eliminate the need to employ costly mathematical procedures or finite element packages for the analysis. The model will also provide a solid ground for optimization studies and help designers gain an insight into how various model parameters impact the system response. This paper will demonstrate the aspects of a proposed surrogate model and endeavor to obtain parameter domains within which the model's reliability is ensured. A numerical example will be demonstrated to prove the concepts presented in the paper and confirm the validity of the proposed model. Copyright © 2012 by ASME.
- Description: C1
Colour image annotation using hybrid intelligent techniques for image retrieval
- Authors: Kulkarni, Siddhivinayak , Kulkarni, Pradnya
- Date: 2012
- Type: Text , Conference proceedings
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- Description: This paper presents a novel technique for colour image annotation based on neural networks and fuzzy logic. Neural network is proposed for classifying the images based on their contents and fuzzy logic is proposed for interpreting the content of an image in terms of natural language. One of the main aspects of this research is to avoid re-training of the neural networks by training the content of the image. Neural network is not trained on database of images; therefore image can be added or deleted from image database without affecting the training. The proposed hybrid technique is tested on real world colour image dataset and promising results are obtained. © 2012 IEEE.
- Description: 2003010700
Empirical investigation of multi-tier ensembles for the detection of cardiac autonomic neuropathy using subsets of the Ewing features
- Authors: Abawajy, Jemal , Kelarev, Andrei , Stranieri, Andrew , Jelinek, Herbert
- Date: 2012
- Type: Text , Conference proceedings
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- Description: This article is devoted to an empirical investigation of performance of several new large multi-tier ensembles for the detection of cardiac autonomic neuropathy (CAN) in diabetes patients using sub-sets of the Ewing features. We used new data collected by the diabetes screening research initiative (DiScRi) project, which is more than ten times larger than the data set originally used by Ewing in the investigation of CAN. The results show that new multi-tier ensembles achieved better performance compared with the outcomes published in the literature previously. The best accuracy 97.74% of the detection of CAN has been achieved by the novel multi-tier combination of AdaBoost and Bagging, where AdaBoost is used at the top tier and Bagging is used at the middle tier, for the set consisting of the following four Ewing features: the deep breathing heart rate change, the Valsalva manoeuvre heart rate change, the hand grip blood pressure change and the lying to standing blood pressure change.
High definition 3D telemedicine: The next frontier?
- Authors: Stranieri, Andrew , Collmann, Richard , Borda, Ann
- Date: 2012
- Type: Text , Conference proceedings
- Relation: Studies in Health Technology and Informatics, 182, p.133-41.
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- Description: Evidence from the literature indicates that the degree of immersion often referred to as the "sense of being there" experienced by clinicians and patients is a factor in the success of tele-health installations. High definition and 3D telemedicine offers a compelling mechanism to achieve a sense of immersion and contribute to an enhanced quality of use. This article surveys HD3D trials in tele-health and concludes that the way HD3D is integrated into telemedicine depends on the clinical, organisational and technological context. In some settings real time HD3D is not so desirable whereas asynchronous transmission of HD3D images and videos is highly desirable. © 2012 The authors and IOS Press.
Hybrid technique for colour image classification and efficient retrieval based on fuzzy logic and neural networks
- Authors: Fernando, Ranisha , Kulkarni, Siddhivinayak
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Developments in the technology and the Internet have led to increase in number of digital images and videos. Thousands of images are added to WWW every day. To retrieve the specific images efficiently from database or from Internet is becoming a challenge now a day. As a result, the necessity of retrieving images has emerged to be important to various professional areas. This paper proposes a novel fuzzy approach to classify the colour images based on their content, to pose a query in terms of natural language and fuse the queries based on neural networks for fast and efficient retrieval. Number of experiments was conducted for classification and retrieval of images on sets of images and promising results were obtained. The results were analysed and compared with other similar image retrieval system. © 2012 IEEE.
Identity crime : The challenges in the regulation of identity crime
- Authors: Holm, Eric
- Date: 2012
- Type: Text , Conference proceedings
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- Description: This paper discusses the unique challenges of regulating identity crime. Identity crime involves the use of personal identification information to perpetrate crimes of fraud. As such, the identity crime involves using personal and private information to perpetrate crime. This article considers the two significant issues that obstruct responses to this crime; firstly, the reporting of crime. Secondly the paper considers the issue of jurisdiction. Finally, the paper explores some responses to this crime. The paper then explores some of the current responses to identity crime. © 2012 IEEE.
Integrating online social networks with e-Commerce : A CBR approach
- Authors: Sun, Zhaohao , Firmin, Sally , Yearwood, John
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Integrating online social networks (OSN) with e-commerce is a part of Enterprise 2.0 and social media and is of significance for development of e-commerce and online social networking services. However, how to integrate online social networks including Facebook with e-commerce is still a big issue for companies. Case based reasoning (CBR) has a number of successful applications in e-commerce and web services. This article examines how to integrate OSN with e-commerce, how to integrate CBR with e-commerce and how to integrate CBR with OSN. This article also proposes a CBR architecture for integrating online social networks with e-commerce using CBR as an intelligent intermediary. One of the research findings indicates that the principle of CBR is a useful marketing strategy for integrating e-commerce and OSN. The approach proposed in this research will facilitate the development of e-commerce, Enterprise 3.0 and online social networking services. Sun, Firmin, & Yearwood © 2012.
- Description: 2003010901
MapReduce neural network framework for efficient content based image retrieval from large datasets in the cloud
- Authors: Venkatraman, Sitalakshmi , Kulkarni, Siddhivinayak
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Recently, content based image retrieval (CBIR) has gained active research focus due to wide applications such as crime prevention, medicine, historical research and digital libraries. With digital explosion, image collections in databases in distributed locations over the Internet pose a challenge to retrieve images that are relevant to user queries efficiently and accurately. It becomes increasingly important to develop new CBIR techniques that are effective and scalable for real-time processing of very large image collections. To address this, the paper proposes a novel MapReduce neural network framework for CBIR from large data collection in a cloud environment. We adopt natural language queries that use a fuzzy approach to classify the colour images based on their content and apply Map and Reduce functions that can operate in cloud clusters for arriving at accurate results in real-time. Preliminary experimental results for classifying and retrieving images from large data sets were quite convincing to carry out further experimental evaluations. © 2012 IEEE.
- Description: 2003010699
Performance evaluation of multi-tier ensemble classifiers for phishing websites
- Authors: Abawajy, Jemal , Beliakov, Gleb , Kelarev, Andrei , Yearwood, John
- Date: 2012
- Type: Text , Conference proceedings
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- Description: This article is devoted to large multi-tier ensemble classifiers generated as ensembles of ensembles and applied to phishing websites. Our new ensemble construction is a special case of the general and productive multi-tier approach well known in information security. Many efficient multi-tier classifiers have been considered in the literature. Our new contribution is in generating new large systems as ensembles of ensembles by linking a top-tier ensemble to another middletier ensemble instead of a base classifier so that the toptier ensemble can generate the whole system. This automatic generation capability includes many large ensemble classifiers in two tiers simultaneously and automatically combines them into one hierarchical unified system so that one ensemble is an integral part of another one. This new construction makes it easy to set up and run such large systems. The present article concentrates on the investigation of performance of these new multi-tier ensembles for the example of detection of phishing websites. We carried out systematic experiments evaluating several essential ensemble techniques as well as more recent approaches and studying their performance as parts of multi-level ensembles with three tiers. The results presented here demonstrate that new three-tier ensemble classifiers performed better than the base classifiers and standard ensembles included in the system. This example of application to the classification of phishing websites shows that the new method of combining diverse ensemble techniques into a unified hierarchical three-tier ensemble can be applied to increase the performance of classifiers in situations where data can be processed on a large computer.
Prudent fraud detection in internet banking
- Authors: Maruatona, Omaru , Vamplew, Peter , Dazeley, Richard
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Most commercial Fraud Detection components of Internet banking systems use some kind of hybrid setup usually comprising a Rule-Base and an Artificial Neural Network. Such rule bases have been criticised for a lack of innovation in their approach to Knowledge Acquisition and maintenance. Furthermore, the systems are brittle; they have no way of knowing when a previously unseen set of fraud patterns is beyond their current knowledge. This limitation may have far reaching consequences in an online banking system. This paper presents a viable alternative to brittleness in Knowledge Based Systems; a potential milestone in the rapid detection of unique and novel fraud patterns in Internet banking. The experiments conducted with real online banking transaction log files suggest that Prudent based fraud detection may be a worthy alternative in online banking. © 2012 IEEE.
- Description: 2003010883
State transition algorithm for traveling salesman problem
- Authors: Yang, Chunhua , Tang, Xiaolin , Zhou, Xiaojun , Gui, Weihua
- Date: 2012
- Type: Text , Conference proceedings
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- Description: Discrete version of state transition algorithm is proposed in order to solve the traveling salesman problem. Three special operators for discrete optimization problem named swap, shift and symmetry transformations are presented. Convergence analysis and time complexity of the algorithm are also considered. To make the algorithm simple and efficient, no parameter adjusting is suggested in current version. Experiments are carried out to test the performance of the strategy, and comparisons with simulated annealing and ant colony optimization have demonstrated the effectiveness of the proposed algorithm. The results also show that the discrete state transition algorithm consumes much less time and has better search ability than its counterparts, which indicates that state transition algorithm is with strong adaptability. © 2012 Chinese Assoc of Automati.