Green IT segment analysis : an academic literature review

Research on Green Information Technology (IT) is becoming a prevalent research theme in Green Information Systems (IS) research. This article provides a review of 98 papers published on Green IT between 2007−2013 to facilitate future research and to provide a retrospective analysis of existing knowledge and gaps thereof. While some researchers have discussed phenomena such as Green IT, motivation of Green IT and the Green IT adoption lifecycle, others have researched the importance of Green IT implementation within the organisational and individual level. Throughout the literature, scholars are trying to portray a constructive relationship between IT and the environment. Through our analysis, we can provide an assessment of the status of information systems literature on Green IT and, we provide taxonomy of segments of Green IT publications. Future research opportunities are identified based on the review.

Promiscuity, pheromones and pathogenicity : why all Enterococci are not created equal

Enterococcus faecalis is a Gram-positive, coccus shaped, lactic acid bacterium, with demonstrated ubiquity across multiple anatomical sites. Enterococcus faecalis isolates have been isolated from clinical samples as the etiological agent in patients with overt infections, and from body sites previously thought to be sterile but absent of signs and symptoms of infection. E. faecalis is implicated in both human health and disease, recognized as a commensal, a probiotic and an opportunistic multiply resistant pathogen. E. faecalis has emerged as a key pathogen in nosocomial infections. E. faecalis is well equipped to avert recognition by host cell immune mediators. Antigenic cell wall components including lipotechoic acids are concealed from immune detection by capsular polysaccharides produced by some strains. Thereby preventing complement activation, the pro-inflammatory response, opsonisation and phagocytosis. E. faecalis also produces a suite of enzymes including gelatinase and cytolysin, which aid in both virulence and host immune evasion. The ability of enterococci to form biofilms in vivo further increases virulence, whilst simultaneously preventing detection by host cells. E. faecalis exhibits high levels of both intrinsic and acquired antimicrobial resistance. The mobility of the E. faecalis genome is a significant contributor to antimicrobial resistance, with this species also transferring resistance to other Gram-positive bacteria. Whilst E. faecalis is of increasing concern in nosocomial infections, its role as a member of the endogenous microbiota cannot be underestimated. As a commensal and probiotic, E. faecalis plays an integral role in modulating the immune response, and in providing endogenous antimicrobial activity to enhance exclusion or inhibition of opportunistic pathogens in certain anatomical niches. In this chapter we will review possible mediators of enterococcal transition from commensal microbe to opportunistic pathogen, considering isolates obtained from patients diagnosed with pathogenic infections and those obtained from asymptomatic patients.

Market segmentation : insights for changing children's physical activity behaviour

Market segmentation has received relatively limited attention in social marketing, particularly within the context of changing children’s physical activity behaviour. This is an important area of investigation given growing concern over childhood obesity globally. The present research aims to extend current understanding of the applicability of market segmentation within this context. The results of a two-step cluster analysis on data from 512 respondents of an online survey show three distinct segments of caregivers, each with unique beliefs about their primary school children walking to/from school. The results demonstrate the validity of employing the process of market segmentation within this social context and provide further insights for targeting the identified segments through tailored social marketing programs.

Optimizing preventative maintenance strategies for linear assets

Linear assets are engineering infrastructure, such as pipelines, railway lines, and electricity cables, which span long distances and can be divided into different segments. Optimal management of such assets is critical for asset owners as they normally involve significant capital investment. Currently, Time Based Preventive Maintenance (TBPM) strategies are commonly used in industry to improve the reliability of such assets, as they are easy to implement compared with reliability or risk-based preventive maintenance strategies. Linear assets are normally of large scale and thus their preventive maintenance is costly. Their owners and maintainers are always seeking to optimize their TBPM outcomes in terms of minimizing total expected costs over a long term involving multiple maintenance cycles. These costs include repair costs, preventive maintenance costs, and production losses. A TBPM strategy defines when Preventive Maintenance (PM) starts, how frequently the PM is conducted and which segments of a linear asset are operated on in each PM action. A number of factors such as required minimal mission time, customer satisfaction, human resources, and acceptable risk levels need to be considered when planning such a strategy. However, in current practice, TBPM decisions are often made based on decision makers’ expertise or industrial historical practice, and lack a systematic analysis of the effects of these factors. To address this issue, here we investigate the characteristics of TBPM of linear assets, and develop an effective multiple criteria decision making approach for determining an optimal TBPM strategy. We develop a recursive optimization equation which makes it possible to evaluate the effect of different maintenance options for linear assets, such as the best partitioning of the asset into segments and the maintenance cost per segment.

Complete-linkage clustering for voice activity detection in audio and visual speech

We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

Identifying vulnerable carotid plaques in vivo using high resolution magnetic resonance imaging-based finite element analysis

Object. Individuals with carotid atherosclerosis develop symptoms following rupture of vulnerable plaques. Biomechanical stresses within this plaque may increase vulnerability to rupture. In this report the authors describe the use of in vivo carotid plaque imaging and computational mechanics to document the magnitude and distribution of intrinsic plaque stresses. Methods. Ten (five symptomatic and five asymptomatic) individuals underwent plaque characterization magnetic resonance (MR) imaging. Plaque geometry and composition were determined by multisequence review. Intrinsic plaque stress profiles were generated from 3D meshes by using finite element computational analysis. Differences in principal (shear) stress between normal and diseased sections of the carotid artery and between symptomatic and asymptomatic plaques were noted. Results. There was a significant difference in peak principal stress between diseased and nondiseased segments of the artery (mean difference 537.65 kPa, p < 0.05). Symptomatic plaques had higher mean stresses than asymptomatic plaques (627.6 kPa compared with 370.2 kPa, p = 0.05), which were independent of luminal stenosis and plaque composition. Conclusions. Significant differences in plaque stress exist between plaques from symptomatic individuals and those from asymptomatic individuals. The MR imaging-based computational analysis may therefore be a useful aid to identification of vulnerable plaques in vivo.