Comparison of word-, sentence, and phoneme-based training strategies in improving the perception of spectrally-distorted speech

Purpose: To compare the effectiveness of three self-administered strategies for auditory training that might improve speech perception by adult users of cochlear implants. The strategies are based, respectively, on discriminating isolated words, words in sentences, and phonemes in nonsense syllables. Method: Participants were 18 normally-hearing adults who listened to speech processed by a noise-excited vocoder to simulate the information provided by a cochlear implant. They were assigned randomly to word-, sentence-, or phoneme-based training and underwent nine 20-minute training sessions on separate days over a 2-3-week period. The effectiveness of training was assessed as the improvement in accuracy of discriminating vowels and consonants, and identifying words in sentences, relative to participants’ best performance in repeated tests prior to training. Results: Word- and sentence-based training led to significant improvements in the ability to identify words in sentences that were significantly larger than the improvements produced by phoneme-based training. There were no significant differences between the effectiveness of word- and sentence-based training. No significant improvements in consonant or vowel discrimination were found for the sentence- or phoneme-based training groups, but some improvements were found for the word-based training group. Conclusions: The word- and sentence-based training strategies were more effective than the phoneme-based strategy at improving the perception of spectrally-distorted speech

Auditory training strategies for adult users of cochlear implants

There has been growing interest recently in whether computer-based training can improve speech perception among users of cochlear implants (Fu et al., 2005; Oba et al., 2011; Ingvalson et al., 2013). This paper reports a series of experiments which first evaluated the effectiveness of different training strategies with normal-hearing participants who listened to noise-vocoded speech, before conducting a small-scale study with users of cochlear implants. Our vocoder studies revealed (1) that ‘High-Variability’ training led to greater generalisation to new talkers than training with a single talker, and (2) that word-and sentence-based training materials led to greater improvements than an approach based on phonemes in nonsense syllables. Informed by these findings, we evaluated the effectiveness of a computer-based training package that included word-and sentence-based tasks, with materials recorded by 20 talkers. We found good compliance with the training protocol, with 8 out of the 11 participants completing 15 hours of training as instructed. Following training, there was a significant improvement on a consonant test, but in general the improvements were small, highly variable, and not statistically significant. A large-scale randomised controlled trial is needed before we can be confident that computer-based auditory training is worthwhile for users of cochlear implants

Adaptive enterprise architecture drivenagiledevelopment

Agile development practices focus on developing and delivering working software systems in small iterations with minimal documentation. However, locally project focused agile practices overlook the need for holistic enterprise architecture. Lack of enterprise architecture in agile, especially in the large agile environments, may lead to a number of problems such as technical debt, unnecessary re-work, inconsistent communication, locally focused isolated architecture, design and implementation. There is a missing link between the enterprise architecture and agile development. Enterprise architecture is a strategic capability that should enable and enhance agility of agile development. However, organisations are not sure how best to approach strategic enterprise architecture capability for supporting agile development. This paper proposes and demonstrate the applicability of an integrated adaptive enterprise architecture driven agile development approach for large agile environments

Towards the Development of an Adaptive Enterprise Service System Model.

The continuous adaptation of modern enterprises is largely dependent on their underlying adaptive enterprise architecture capability. However, the establishment of an adaptive enterprise architecture capability requires defining the enterprise context before actually commissioning any enterprise architecture or adaptation work. This paper presents the adaptive enterprise service system (AESS) model based on the “Design Science” research method and “Theory Triangulation” approach. The AESS integrates the enterprise context perspectives from three well-known theories of agility, (agent) system, and service science. The AESS model, as a part of the large adaptive enterprise architecture toolkit, defines a modern enterprise as an adaptive enterprise service system. The adaptive enterprise service system is a multi-agent system of service systems that exhibits agility and focuses on the emerging service-centric view as opposed to a traditional product-centric view. The service-centric view of an enterprise is critical for establishing the adaptive enterprise architecture capability for handling complex enterprise transformations

Computational intelligence for measuring macro-knowledge competitiveness

The aim of this research is to investigate the utilisation of Computational Intelligence methods for constructing Synthetic Composite Indicators (SCI). In particular for delivering a Unified Macro-Knowledge Competitiveness Indicator (UKCI) to enable consistent and transparent assessments and forecasting of the progress and competitiveness of Knowledge Based Economy (KBE). SCI are assessment tools usually constructed to evaluate and contrast entities performance by aggregating intangible measures in many areas such as economy, education, technology and innovation. SCI key value is inhibited in its capacity to aggregate complex and multi-dimensional variables into a single meaningful value. As a result, SCIs have been considered as one of the most important tools for macro-level and strategic decision making. Considering the shortcomings of the existing SCI, this study is proposing an alternative approach to develop Intelligent Synthetic Composite Indicators (iSCI). The suggested approach utilizes Fuzzy Proximity Knowledge Mining technique to build the qualitative taxonomy initially, and Fuzzy c-mean is employed to form the new composite indicators

Elevated PAI-1 is associated with poor clinical outcomes in pediatric patients with acute lung injury.

PurposeDeposition of fibrin in the alveolar space is a hallmark of acute lung injury (ALI). Plasminogen activator inhibitor-1 (PAI-1) is an antifibrinolytic agent that is activated during inflammation. Increased plasma and pulmonary edema fluid levels of PAI-1 are associated with increased mortality in adults with ALI. This relationship has not been examined in children. The objective of this study was to test whether increased plasma PAI-1 levels are associated with worse clinical outcomes in pediatric patients with ALI.Design/methodsWe measured plasma PAI-1 levels on the first day of ALI among 94 pediatric patients enrolled in two separate prospective, multicenter investigations and followed them for clinical outcomes. All patients met American European Consensus Conference criteria for ALI.ResultsA total of 94 patients were included. The median age was 3.2 years (range 16 days-18 years), the PaO(2)/F(i)O(2) was 141 +/- 72 (mean +/- SD), and overall mortality was 14/94 (15%). PAI-1 levels were significantly higher in nonsurvivors compared to survivors (P < 0.01). The adjusted odds of mortality doubled for every log increase in the level of plasma PAI-1 after adjustment for age and severity of illness.ConclusionsHigher PAI-1 levels are associated with increased mortality and fewer ventilator-free days among pediatric patients with ALI. These findings suggest that impaired fibrinolysis may play a role in the pathogenesis of ALI in pediatric patients and suggest that PAI-1 may serve as a useful biomarker of prognosis in patients with ALI

Spectral and temporal processing in human auditory cortex

Hierarchical processing suggests that spectrally and temporally complex stimuli will evoke more activation than do simple stimuli, particularly in non-primary auditory fields. This hypothesis was tested using two tones, a single frequency tone and a harmonic tone, that were either static or frequency modulated to create four stimuli. We interpret the location of differences in activation by drawing comparisons between fMRI and human cytoarchitectonic data, reported in the same brain space. Harmonic tones produced more activation than single tones in right Heschl's gyrus (HG) and bilaterally in the lateral supratemporal plane (STP). Activation was also greater to frequency-modulated tones than to static tones in these areas, plus in left HG and bilaterally in an anterolateral part of the STP and the superior temporal sulcus. An elevated response magnitude to both frequency-modulated tones was found in the lateral portion of the primary area, and putatively in three surrounding non-primary regions on the lateral STP (one anterior and two posterior to HG). A focal site on the posterolateral STP showed an especially high response to the frequency-modulated harmonic tone. Our data highlight the involvement of both primary and lateral non-primary auditory regions

An agile enterprise architecture driven model for geographically distributed agile development

Agile development is a highly collaborative environment, which requires active communication (i.e. effective and efficient communication) among stakeholders. The active communication in geographically distributed agile development (GDAD) environment is difficult to achieve due to many challenges. Literature has reported that active communication play critical role in enhancing GDAD performance through reducing the cost and time of a project. However, little empirical evidence is known about how to study and establish active communication construct in GDAD in terms of its dimensions, determinants and effects on GDAD performance. To address this knowledge gap, this paper describes an enterprise architecture (EA) driven research model to identify and empirically examine the GDAD active communication construct. This model can be used by researchers and practitioners to examine the relationships among two dimensions of GDAD active communication (effectiveness and efficiency), one antecedent that can be controlled (agile EA), and four dimensions of GDAD performance (on-Time completion, on-budget completion, software functionality and software quality)

Crowd sourcing challenges assessment index for disaster management

Emergency agencies (EA) rely on inter-agency approaches to information management during disasters. EA have shown a significant interest in the use of cloud-based social media such as Twitter and Facebook for crowd-sourcing and distribution of disaster information. While the intentions are clear, the question of what are its major challenges are not. EA have a need to recognise the challenges in the use of social media under their local circumstances. This paper analysed the recent literature, 2010 Haiti earthquake and 2010-11 Queensland flood cases and developed a crowd sourcing challenges assessment index construct specific to EA areas of interest. We argue that, this assessment index, as a part of our large conceptual framework of context aware cloud adaptation (CACA), can be useful for the facilitation of citizens, NGOs and government agencies in a strategy for use of social media for crowd sourcing, in preventing, preparing for, responding to and recovering from disasters. © (2012) by the AIS/ICIS Administrative Office All rights reserved