GeneGrid: Architecture, Implementation and Application

The emergence of Grid computing technology has opened up an unprecedented opportunity for biologists to share and access data, resources and tools in an integrated environment leading to a greater chance of knowledge discovery. GeneGrid is a Grid computing framework that seamlessly integrates a myriad of heterogeneous resources spanning multiple administrative domains and locations. It provides scientists an integrated environment for the streamlined access of a number of bioinformatics programs and databases through a simple and intuitive interface. It acts as a virtual bioinformatics laboratory by allowing scientists to create, execute and manage workflows that represent bioinformatics experiments. A number of cooperating Grid services interact in an orchestrated manner to provide this functionality. This paper gives insight into the details of the architecture, components and implementation of GeneGrid.

Fusion rules for merging uncertain information

In previous papers, we have presented a logic-based framework based on fusion rules for merging structured news reports. Structured news reports are XML documents, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume structured news reports do not require natural language processing. Fusion rules are a form of scripting language that define how structured news reports should be merged. The antecedent of a fusion rule is a call to investigate the information in the structured news reports and the background knowledge, and the consequent of a fusion rule is a formula specifying an action to be undertaken to form a merged report. It is expected that a set of fusion rules is defined for any given application. In this paper we extend the approach to handling probability values, degrees of beliefs, or necessity measures associated with textentries in the news reports. We present the formal definition for each of these types of uncertainty and explain how they can be handled using fusion rules. We also discuss the methods of detecting inconsistencies among sources.

Probabilistic program analysis for parallelizing compilers

Parallelizing compilers have difficulty analysing and optimising complex code. To address this, some analysis may be delayed until run-time, and techniques such as speculative execution used. Furthermore, to enhance performance, a feedback loop may be setup between the compile time and run-time analysis systems, as in iterative compilation. To extend this, it is proposed that the run-time analysis collects information about the values of variables not already determined, and estimates a probability measure for the sampled values. These measures may be used to guide optimisations in further analyses of the program. To address the problem of variables with measures as values, this paper also presents an outline of a novel combination of previous probabilistic denotational semantics models, applied to a simple imperative language.

A Novel Packet Marking Function for Real-Time Interactive MPEG-4 Video Applications in a Differentiated Services Network

The future convergence of voice, video and data applications on the Internet requires that next generation technology provides bandwidth and delay guarantees. Current technology trends are moving towards scalable aggregate-based systems where applications are grouped together and guarantees are provided at the aggregate level only. This solution alone is not enough for interactive video applications with sub-second delay bounds. This paper introduces a novel packet marking scheme that controls the end-to-end delay of an individual flow as it traverses a network enabled to supply aggregate- granularity Quality of Service (QoS). IPv6 Hop-by-Hop extension header fields are used to track the packet delay encountered at each network node and autonomous decisions are made on the best queuing strategy to employ. The results of network simulations are presented and it is shown that when the proposed mechanism is employed the requested delay bound is met with a 20% reduction in resource reservation and no packet loss in the network.

Lean software management case study: Timberline Inc.

This paper is believed to be the first documented account of a full adoption of lean by a software company. Lean techniques were devised by Toyota and other manufacturers over the last 50 years. The techniques are termed lean because they require less resource to produce more product and exceptional quality. Lean ideas have also been successful in service industries and product development. Applying lean to software has been advocated for over 10 years. Timberline, Inc started their lean initiative in Spring 2001 and this paper records their journey, results and lessons learned up to Fall 2003. This case study demonstrates that lean thinking can work successfully for software developers. It also indicates that the extensive lean literature is a valuable source of new ideas for software engineering.

Strasheela: Design and usage of a music composition environment based on the Oz programming model

Strasheela provides a means for the composer to create a symbolic score by formally describing it in a rule-based way. The environment defines a rich music representation for complex polyphonic scores. Strasheela enables the user to define expressive compositional rules and then to apply them to the score. Compositional rules can restrict many aspects of the music - including the rhythmic structure, the melodic structure and the harmonic structure - by constraining the parameters (e.g. duration or pitch) of musical events according to some numerical or logical relation. Strasheela combines this expressivity with efficient search strategies.

Towards an intelligent score following system: Handling of mistakes and jumps encountered during piano practicing

Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

Creating a spontaneous conversational speech corpus

Speech recognition and language analysis of spontaneous speech arising in naturally spoken conversations are becoming the subject of much research. However, there is a shortage of spontaneous speech corpora that are freely available for academics. We therefore undertook the building of a natural conversation speech database, recording over 200 hours of conversations in English by over 600 local university students. With few exceptions, the students used their own cell phones from their own rooms or homes to speak to one another, and they were permitted to speak on any topic they chose. Although they knew that they were being recorded and that they would receive a small payment, their conversations in the corpus are probably very close to being natural and spontaneous. This paper describes a detailed case study of the problems we faced and the methods we used to make the recordings and control the collection of these social science data on a limited budget.

Posting Incognito ... Males with Eating Problems: Online Emotional Expression and Support

Qualitative research in the area of eating disorders (eds) has predominantly focused on females,whilst the experiences of males’ remains poorly understood. due to the secretive nature of eating problems/eds it can be difficult to explore the experiences of males with these problems; however, online support groups/message boards, which are common and popular, provide a non-invasive
forum for researchers to conduct research. This study analyzed naturally occurring discussions on an internet message board dedicated to males and eating problems using content analysis. Two major overarching themes of emotional expression (sharing feelings of disturbed eating attitudes and emotions; being secretive) and support (informational and emotional) were identified. The message board provided a vital support system for this group, suggesting that online message boards may be an important avenue for health professionals to provide information, support, and advice.

Lightweight Risk Management in Agile projects

Risk management in software engineering has become a recognized project management practice but it seems that not all companies are systematically applying it. At the same time, agile methods have become popular, partly because proponents claim that agile methods implicitly reduce risks due
to, for example, more frequent and earlier feedback, shorter periods of development time and easier prediction of cost. Therefore, there is a need to investigate how risk management can be usable in iterative and evolutionary software development processes. This paper investigates the gathering of empirical data on risk management from the project environment and presents
a novel approach to manage risk in agile projects. Our approach is based on a prototype tool, Agile Risk Tool (ART). This tool reduces human effort in risk management by using software agents to identify, assess and monitor risk, based on input and data collected from the project environment and by applying
some designated rules. As validation, groups of student project data were used to provide evidence of the efficacy of this approach. We demonstrate the approach and the feasibility of using a lightweight risk management tool to alert, assess and monitor risk with reduced human effort.

Behavioral Model Generation from Use Cases Based on Ontology Mapping and GRASP Patterns

This paper contributes a new approach for developing UML software designs from Natural Language (NL), making use of a meta-domain oriented ontology, well established software design principles and Natural Language Processing (NLP) tools. In the approach described here, banks of grammatical rules are used to assign event flows from essential use cases. A domain specific ontology is also constructed, permitting semantic mapping between the NL input and the modeled domain. Rules based on the widely-used General Responsibility Assignment Software Principles (GRASP) are then applied to derive behavioral models.