146 resultados para 080301 Bioinformatics Software


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This article reports on the development of an iPhone-based brain-exercise tool for seniors involving a series of focus groups (FGs) and field trials (FTs). Four FGs with 34 participants were conducted aimed at understanding the underlying motivational and de-motivational factors influencing seniors’ engagement with mobile brain-exercise software. As part of the FGs, participants had approximately 40 minutes hands-on experience with commercially available brain-exercise software. A content analysis was conducted on the data resulting in a ranking of 19 motivational factors, of which the top three were challenge, usefulness and familiarity and 15 de-motivational factors, of which the top-three were usability issues, poor communication and games that were too fast. Findings were used to inform the design of three prototype brain-exercise games for the iPhone contained within one overall application, named Brain jog. Subsequently, two FTs were conducted using Brain jog to investigate the part that time exposure has to play in shaping the factors influencing engagement. New factors arose with respect to the initial FGs including the motivational factor feedback and the de-motivational factor boring. The results of this research provide valuable guidelines for the design and evaluation of mobile brain-exercise software for seniors.

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In essence, optimal software engineering means creating the right product, through the right process, to the overall satisfaction of everyone involved. Adopting the agile approach to software development appears to have helped many companies make substantial progress towards that goal. The purpose of this paper is to clarify that contribution from comparative survey information gathered in 2010 and 2012. The surveys were undertaken in software development companies across Northern Ireland. The paper describes the design of the surveys and discusses optimality in relation to the results obtained. Both surveys aimed to achieve comprehensive coverage of a single region rather than rely on a voluntary sample. The main outcome from the work is a collection of insights into the nature and advantages of agile development, suggesting how further progress towards optimality might be achieved.

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The agile model of software development has been mainstream for several years, and is now in a phase where its principles and practices are maturing. The purpose of this paper is to describe the results of an industry survey aimed at understanding how maturation is progressing. The survey was taken across 40 software development companies in Northern Ireland at the beginning of 2012. The paper describes the design of the survey and examines maturity by comparing the results obtained in 2012 with those from a study of agile adoption in the same region in 2010. Both surveys aimed to achieve comprehensive coverage of a single area rather than rely on a voluntary sample. The main outcome from the work is a collection of ‘insights’ into the nature and practice of agile development, the main two of which are reported in this paper.

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Software is patentable in Europe so long as there is sufficient ‘technical contribution’ under the decades-long interpretation of the European Patent Convention made by the Boards of Appeal of the European Patent Office. Despite the failure of the proposed Directive on Computer Implemented Inventions, opponents of software patents have failed to have any affect upon this technical contrivance. Yet, while national courts find the Boards of Appeal decisions persuasive, ‘technical contribution’ remains a difficult test for these various courts to apply. In this article I outline that the test is difficult to utilise in national litigation (it is an engineering approach, rather than a legal one) and suggest that as the Boards of Appeal become less important (and thus less persuasive) should the proposed Unified Patent Court come to fruition, the ‘technical contribution’ test is unlikely to last. This may again make the whole issue of what/whether/how software should be patentable open to debate, hopefully in a less aggressive environment than has existed to date.

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Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

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Software Product-Line Engineering has emerged in recent years, as an important strategy for maximising reuse within the context of a family of related products. In current approaches to software product-lines, there is general agreement that the definition of a reference-architecture for the product-line is an important step in the software engineering process. In this paper we introduce ADLARS, a new form of architecture Description language that places emphasis on the capture of architectural relationships. ADLARS is designed for use within a product-line engineering process. The language supports both the definition of architectural structure, and of important architectural relationships. In particular it supports capture of the relationships between product features, component and task architectures, interfaces and parameter requirements.

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Optimizing and editing enterprise software systems, after the implementation process has started, is widely recognized to be an expensive process. This has led to increasing emphasis on locating mistakes within software systems at the design stage, to help minimize development costs. There is increasing interest in the field of architecture evaluation techniques that can identify problems at the design stage, either within complete, or partially complete architectures. Most current techniques rely on manual review-based evaluation methods that require advanced skills from architects and evaluators. We are currently considering what a formal Architecture Description Language (ADL) can contribute to the process of architecture evaluation and validation. Our investigation is considering the inter-relationships between the activities performed during the architecture evaluation process, the characteristics an ADL should possess to support these activities, and the tools needed to provide convenient access to, and presentation of architectural information.

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Often the modification and enhancement of large scientific software systems are severely hampered because many components of the system are written in an implementation dependent fashion, they are inadequately documented, and their functionalities are not precisely known. In this paper we consider how mathematics may be employed to alleviate some of these problems. In particular, we illustrate how the formal specification notation VDM-SL is being used to specify precisely abstract data types for use in the development of scientific software.