Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.

A cluster operating system supporting parallel computing

The single factor limiting the harnessing of the enormous computing power of clusters for parallel computing is the lack of appropriate software. Present cluster operating systems are not built to support parallel computing – they do not provide services to manage parallelism. The cluster operating environments that are used to assist the execution of parallel applications do not provide support for both Message Passing (MP) or Distributed Shared Memory (DSM) paradigms. They are only offered as separate components implemented at the user level as library and independent servers. Due to poor operating systems users must deal with computers of a cluster rather than to see this cluster as a single powerful computer. A Single System Image of the cluster is not offered to users. There is a need for an operating system for clusters. We claim and demonstrate that it is possible to develop a cluster operating system that is
able to efficiently manage parallelism, support Message Passing and DSM and offer the Single System Image. In order to substantiate the claim the first version of a cluster operating system, called GENESIS, that manages parallelism and offers the Single System Image has been developed.

Comparing alternate teaching styles to teach computing skills to girls in their English classes

Low female participation rates in computing are a current concern of the education sector. To address this problem an intervention was developed — computing skills were introduced to girls in their English classes using three different teaching styles: peer tutoring, cross-age tutoring and teacher instruction (control). The sample comprised 136 girls from Years 8 and 10 from a single-sex government school. A pre-test post-test quantitative design was used. To describe the students perspectives, qualitative data were collected from six focus groups conducted with 8–10 students — one from each of the six classes. It was predicted that cross-age tutoring would yield more positive effects than peer tutoring which, in turn, would yield more positive effects than traditional teacher instruction as assessed by achievement on class tasks and attitudes towards computing. The hypothesis was not supported by the quantitative analysis, however in the qualitative data cross-age tutoring was appraised more favourably than peer tutoring or teacher instruction. The latter was the least preferred condition due to: (1) inefficiency; (2) difficulty understanding teachers' explanations; and (3) lack of teacher knowledge. Problems with the implementation of the intervention identified in the focus groups were teacher differences, system failures, missed classes, lack of communication, and selection of computing activities. Practical suggestions were provided relevant to the introduction of cross-age tutoring and the use of computers within secondary level English classes.

Intelligent agent technology within information warfare

Research into Intelligent Agent (IA) technology and how it can assist computer systems in the autonomous completion of common office and home computing tasks is extremely widespread. The use oflA's is becoming more feasible as the functionality moves Into line with what users require for their everyday computing needs. However, this does not mean that IA technology cannot be exploited or developed for use in a malicious manner, such as within an Information Waifare (IW) scenario, where systems may be attacked autonomously by agent system implem-entations. This paper will discuss tne cilrrenlStcite Ofmalicious use of lA's as well as focusing on attack techniques, the difficulties brought about by such attacks as well as security methods, both proactive and reactive, that could be instated within compromised or sensitive systems.

Experiential learning in social science theory: an investigation of the relationship between student enjoyment and learning

This paper provides an analysis of student experiences of an approach to teaching theory that integrates the teaching of theory and data analysis. The argument that supports this approach is that theory is most effectively taught by using empirical data in order to generate and test propositions and hypotheses, thereby emphasising the dialectic relationship between theory and data through experiential learning. Bachelor of Commerce students in two second-year substantive organisational theory subjects were introduced to this method of learning at a large, multi-campus Australian university. In this paper, we present a model that posits a relationship between students' perceptions of their learning, the enjoyment of the experience and expected future outcomes. The results of our evaluation reveal that a majority of students:

•enjoyed this way of learning;
•believed that the exercise assisted their learning of substantive theory, computing applications and the nature of survey data; and
•felt that what they have learned could be applied elsewhere.

We argue that this approach presents the potential to improve the way theory is taught by integrating theory, theory testing and theory development; moving away from teaching theory and analysis in discrete subjects; and, introducing iterative experiences in substantive subjects.

Dusting off the epidemiological triad: could it work with obesity

The search for effective ways of dealing with obesity has centred on biological research and clinical management. However, obesity needs to be conceptualized more broadly if the modern pandemic is to be arrested. The epidemiological triad (hosts, agent/vectors and environments) has served us well in dealing with epidemics in the past, and may be worth re-evaluating to this end. Education, behaviour change and clinical practices deal predominantly with the host, although multidisciplinary practices such as shared-care might also be expected to impact on other corners of the triad. Technology deals best with the agent of obesity (energy imbalance) and it's vectors (excessive energy intake and/or inadequate energy expenditure), and policy and social change are needed to cope with the environment. The value of a broad model like this, rather than specific isolated approaches, is that the key players such as legislators, health professionals, governments and industry can see their roles in attenuating and eventually reversing the epidemic. It also highlights the need to intervene at all levels in obesity control and reduces the relevance of arguments about nature vs. nurture.


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Fault detection service architecture for grid computing systems

The ability to tolerate failures while effectively exploiting the grid computing resources in an scalable and transparent manner must be an integral part of grid computing infrastructure. Hence, fault-detection service is a necessary prerequisite to fault tolerance and fault recovery in grid computing. To this end, we present an scalable fault detection service architecture. The proposed fault-detection system provides services that monitors user applications, grid middlewares and the dynamically changing state of a collection of distributed resources. It reports summaries of this information to the appropriate agents on demand or instantaneously in the event of failures.

Dynamic parallel job scheduling in multi-cluster computing systems

Job scheduling is a complex problem, yet it is fundamental to sustaining and improving the performance of parallel processing systems. In this paper, we address an on-line parallel job scheduling problem in heterogeneous multi-cluster computing systems. We propose a new space-sharing scheduling policy and show that it performs substantially better than the conventional policies.

Large-scale biological sequence assembly and alignment by using computing grid

Large-scale sequence assembly and alignment are fundamental parts of biological computing. However, most of the large-scale sequence assembly and alignment require intensive computing power and normally take very long time to complete. To speedup the assembly and alignment process, this paper parallelizes the Euler sequence assembly and pair-wise/multiple sequence assembly, two important sequence assembly methods, and takes advantage of Computing Grid which has a colossal computing capacity to meet the large-scale biological computing demand.

"I could see, and yet, mon, I could na` see" : William Macewen, the agnosias, and brain surgery

Two little noticed cases in which William Macewen used symptoms of visual agnosia to plan brain surgery on the angular gyrus are reviewed and evaluated. Following a head injury, Macewen’s first patient had an immediate and severe visual object agnosia that lasted for about 2 weeks. After that he gradually became homicidal and depressed and it was for those symptoms that Macewen first saw him, some 11 months after the accident. From his examination, Macewen concluded that the agnosia clearly indicated a lesion in “the posterior portion of the operculum or in the angular gyrus.” When he removed parts of the internal table that had penetrated those structures the homicidal impulses disappeared. Macewen’s second patient was seen for a chronic middle ear infection and, although neither aphasic nor deaf, was ‘word deaf.’ Slightly later he became ‘psychically blind’ as well. Macewen suspected a cerebral abscess pressing on both the angular gyrus and the first temporal convolution. A large subdural abscess was found there and the symptoms disappeared after it was treated. The patients are discussed and Macewen’s positive results analysed in the historical context of the dispute over the proposed role of the angular gyrus as the visual centre.

Autonomic job scheduling policy for grid computing

Autonomic middleware services will play an important role in the management of resources and distributed workloads in emerging distributed computing environments. In this paper, we address the problem of autonomic grid resource scheduling and propose a scheduling infrastructure that is capable of self-management in the face of dynamic behavior inherent to this kind of systems.

Job scheduling policy for high throughput grid computing

The growing computational power requirements of grand challenge applications has promoted the need for merging high throughput computing and grid computing principles to harness computational resources distributed across multiple organisations. This paper identifies the issues in resource management and scheduling in the emerging high throughput grid computing context. We also survey and study the performance of several space-sharing and time-sharing opportunistic scheduling policies that have been developed for high throughput computing.

Robust parallel job scheduling infrastructure for service-oriented grid computing systems

Recent trends in grid computing development is moving towards a service-oriented architecture. With the momentum gaining for the service-oriented grid computing systems, the issue of deploying support for integrated scheduling and fault-tolerant approaches becomes paramount importance. To this end, we propose a scalable framework that loosely couples the dynamic job scheduling approach with the hybrid replications approach to schedule jobs efficiently while at the same time providing fault-tolerance. The novelty of the proposed framework is that it uses passive replication approach under high system load and active replication approach under low system loads. The switch between these two replication methods is also done dynamically and transparently.

Grid accounting service infrastructure for service-oriented grid computing systems

In this paper, we propose an architecture of accounting and payment services for service-oriented grid computing systems. The proposed accounting and payment services provide the mechanisms for service providers to be paid for authorized use of their resources. It supports the recording of usage data, secure storage of that data, analysis of that data for purposes of billing and so forth. It allows a variety of payment methods, it is scalable, secure, convenient, and reduce the overall cost of payment processing while taking into account requirements of Grid computing systems.