The density connectivity information bottleneck

Clustering with the agglomerative Information Bottleneck (aIB) algorithm suffers from the sub-optimality problem, which cannot guarantee to preserve as much relative information as possible. To handle this problem, we introduce a density connectivity chain, by which we consider not only the information between two data elements, but also the information among the neighbors of a data element. Based on this idea, we propose DCIB, a Density Connectivity Information Bottleneck algorithm that applies the Information Bottleneck method to quantify the relative information during the clustering procedure. As a hierarchical algorithm, the DCIB algorithm produces a pruned clustering tree-structure and gets clustering results in different sizes in a single execution. The experiment results in the documentation clustering indicate that the DCIB algorithm can preserve more relative information and achieve higher precision than the aIB algorithm.

Development of an exposure database and surveillance system for use by practicing OSH professionals

This report summarizes the development of an occupational exposure database and surveillance system for use by health and safety professionals at Rocky Flats Environmental Technology Site (RFETS), a former nuclear weapons production facility. The site itself is currently in the cleanup stage with work expected to continue into 2006. The system was developed with the intent of helping health and safety personnel not only to manage and analyze exposure monitoring data, but also to identify exposure determinants during the highly variable cleanup work. Utilizing a series of focused meetings with health and safety personnel from two of the major contractors at RFETS, core data elements were established. These data elements were selected based on their utility for analysis and identification of exposure determinants. A task-based coding scheme was employed to better define the highly variable work. The coding scheme consisted of a two-tiered hierarchical list with a total of 34 possible combinations of work type and task. The data elements were incorporated into a Microsoft Access database with built-in data entry features to both promote consistency and limit entry choices to enable stratified analyses. In designing the system, emphasis was placed on the ability of end users to perform complex analyses and multiparameter queries to identify trends in their exposure data. A very flexible and user-friendly report generator was built into the system. This report generator allowed users to perform multiparameter queries using an intuitive system with very little training. In addition, a number of automated graphical analyses were built into the system, including ex posure levels by any combination of building, date, employee, job classification, type of contaminant, work type or task, exposure levels over time, exposure levels relative to the permissible exposure limit (PELS), and distributions of exposure levels. Both of these interfaces, allow the user to ''drill down'' or gradually narrow query criteria to identify specific exposure determinants. A number of other industrial hygiene processes were automated by the use of this database. Exposure calculations were coded into the system to allow automatic calculation of time-weighted averages and sample volumes. In addition, a table containing all the PELs and other relevant occupational exposure limits was built into the system to allow automatic comparisons with the current standards. Finally, the process of generating reports for employee notification was automated. The implementation of this system demonstrates that an integrated database system can save time for a practicing hygienist as well as provide useful and more importantly, timely information to guide primary prevention efforts.

Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

A conceptual matrix model for biological data processing

This paper proposes a conceptual matrix model with algorithms for biological data processing. The required elements for constructing a matrix model are discussed. The representative matrix-based methods and algorithms which have potentials in biological data processing are presented / proposed. Some application cases of the model in biological data processing are studied, which show the applicability of this model in various kinds of biological data processing. This conceptual model established a framework within which biological data processing and mining could be conducted. The model is also heuristic to other applications.

Interactive dance performance : movement data and the 'materiality' of the system

This paper describes a recent performance work I made using dance and live feed video
processing, 1 + x: mid-range projections, commissioned by the Seoul Contemporary Dance
Company and first performed in Melbourne in July 2005. This work forms a basis for discussing
my interest in creating performance images that reveal 'interiority'. I am interested in how you
embed the 'feel' of the human systematically in an interactive structure, and how that process
can produce a poetic that arises from the detailed and nuanced play between real and virtual
images on the same screen. How do you abstract and play with a performer's movement, play
with it in real and virtual time, so that it gives the work an emotional charge? Its like playing with
the process of 'becoming virtual' - and I'm being deliberately Deleuzian about that - how do you
'become virtual' in the sense of melding performer and image so that the meaning exists
between - in the connection between the two?

This quest to get the energy, the 'lived', 'felt' quality of the movement into the imagery gives rise
to research questions about how 'presence' is perceived in movement. What elements of the
raw movement data do you need to keep and what can you throwaway, and still keep the
personality, the emotion, the 'life' of that movement? How do you make a virtual, interactive
performance system that has its own 'materiality'?

Countryside elements and the conservation of birds in agricultural environments

Throughout the world, many native species inhabit agricultural landscapes. While natural habitats will form the cornerstone of conservation efforts in production-oriented environments, the success of these efforts will be enhanced by a greater understanding of the potential contribution of the increasingly modified countryside (‘matrix’) elements in these landscapes. Here, we investigate the relative occurrence of birds in some landscape elements (i.e. land-uses, vegetation types) common to agricultural environments around the world. Twenty-seven study mosaics (1 km × 1 km in size), selected to incorporate variation in the cover of native vegetation and the richness of different landscape elements, were sampled in Gippsland, south-eastern Australia. Birds were surveyed in five main types of elements: native vegetation, linear vegetation, plantation, scattered trees and pasture. The greatest number of species was recorded in native vegetation, the most important element for the majority of birds in Australian agricultural landscapes. Nevertheless, most countryside elements had value for many species; particularly structurally complex elements. Ordination analyses (based on presence/absence data for 81 species) showed that the composition of bird communities differed between elements. The number of mosaics in which ‘all species’ and ‘woodland species’ were recorded was positively related to the breadth of elements they used; thus species using a greater number of elements occurred more frequently in the study region. Correlation analyses identified that the richness of woodland species (those of increased conservation concern in Australia) in different elements was influenced by features of the mosaic in which they occurred. Notably, the richness of woodland bird species recorded in scattered trees and pasture increased with local native vegetation cover. Key implications for conservation in Australian agricultural environments include: (1) native vegetation is vital for the persistence of birds in these landscapes, and thus is the primary element on which conservation efforts in agricultural landscapes depend; (2) countryside elements can enhance the conservation value of agricultural landscapes by (a) increasing structural complexity in largely cleared areas and (b) increasing the heterogeneity of the entire landscape; and (3) patches of different elements cannot be managed in isolation from their surroundings, as landscape properties affect the richness of bird assemblages in different elements.

Decentralized mobility models for data collection in wireless sensor networks

Controlled mobility in wireless sensor networks provides many benefits towards enhancing the network performance and prolonging its lifetime. Mobile elements, acting as mechanical data carriers, traverse the network collecting data using single-hop communication, instead of the more energy demanding multi-hop routing to the sink. Scaling up from single to multiple mobiles is based more on the mobility models and the coordination methodology rather than increasing the number of mobile elements in the network. This work addresses the problem of designing and coordinating decentralized mobile elements for scheduling data collection in wireless sensor networks, while preserving some performance measures, such as latency and amount of data collected. We propose two mobility models governing the behaviour of the mobile element, where the incoming data collection requests are scheduled to service according to bidding strategies to determine the winner element. Simulations are run to measure the performance of the proposed mobility models subject to the network size and the number of mobile elements.

Reconstruction of in vivo time-evolving neuroendocrine dose - response properties unveils admixed deterministic and stochastic elements

Homeostasis in the intact organism is achieved implicitly by repeated incremental feedback (inhibitory) and feedforward (stimulatory) adjustments enforced via intermittent signal exchange. In separated systems, neurohormone signals act deterministically on target cells via quantifiable effector-response functions. On the other hand, in vivo interglandular signaling dynamics have not been estimable to date. Indeed, experimentally isolating components of an interactive network definitionally disrupts time-sensitive linkages. We implement and validate analytical reconstruction of endogenous effector-response properties via a composite model comprising (i) a deterministic basic feedback and feedforward ensemble structure; (ii) judicious statistical allowance for possible stochastic variability in individual biologically interpretable dose–response properties; and (iii) the sole data requirement of serially observed concentrations of a paired signal (input) and response (output). Application of this analytical strategy to a prototypical neuroendocrine axis in the conscious uninjected horse, sheep, and human (i) illustrates probabilistic estimation of endogenous effector dose–response properties; and (ii) unmasks statistically vivid (2- to 5-fold) random fluctuations in inferred target-gland responsivity within any given pulse train. In conclusion, balanced mathematical formalism allows one to (i) reconstruct deterministic properties of interglandular signaling in the intact mammal and (ii) quantify apparent signal-response variability over short time scales in vivo. The present proof-of-principle experiments introduce a previously undescribed means to estimate time-evolving signal-response relationships without isotope infusion or pathway disruption.

Dynamic request-driven scheme for data collectors in sensor networks

Wireless sensor networks lifetime is prolonged through a dynamic scheme for collecting sensory information using intelligent mobile elements. The data collection routes are optimised for fast and reliable delivery. The scheme minimises high levels of energy consumption to extend the network operational time.

Students' perceptions of the value of the elements of an online learning environment : looking back in moving forward

In 2003, Deakin University implemented a centralised learning management system (LMS) under the banner of Deakin Studies Online (DSO), as well as implementing policies requiring all its units of study to have at least a basic online presence from 2004. Given the scope of the university's commitment to online education, it was considered essential to evaluate the effectiveness of this investment. Based on more than 5400 responses obtained from students in 2004 and 2005 as part of the DSO evaluation survey, the analysis presented here identifies those elements of the online learning environment (OLE) that are most used and valued by students, those elements of the OLE that students most want to see improved, and, those factors that most contribute to students' perceptions that use of the OLE enhanced their learning experience. The most used and valued elements were core LMS functions, including accessing unit information, accessing lecture/tute/lab notes, interacting with unit learning resources, reading online discussions, contacting lecturers/tutors and submitting assignments online. The OLE elements identified as most needing attention were receiving feedback on assignments; viewing my marks; and reviewing unit progress. Students felt that using DSO enhanced their learning experience when they were adequately supported by unit teachers and technical support services; when they were able to find and use unit information; and when they were able to read the online contributions of other unit members. The retrospective analysis of data collected in the period 2004-2005 has been shaped by a forward-looking agenda. The array of elements available within, and in association with, traditional LMSs which has emerged since that time raises the future challenge of how to maximise and evidence educational value through the optimal combination of elements from the portfolio of e-learning technologies increasingly available to educators.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper presents a new study on the application of the framework of Computational Media Aesthetics to the problem of automated understanding of film. Leveraging Film Grammar as the means to closing the "semantic gap" in media analysis, we examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and enhance its lyrical quality experientially. The novelty of this paper lies in the specification and investigation of the rhythmic elements that are present in two cinematic devices; namely motion and editing patterns, and their potential usefulness to automated content annotation and management systems. In our rhythm model, motion behavior is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighborhoods in movies are then grouped by proportional makeup of these motion behavioral classes to yield seven high-level rhythmic arrangements that prove to be adept at indicating likely scene content (e.g. dialogue or chase sequence) in our experiments. The second part of our investigation presents a computational model to detect editing patterns as either metric, accelerated, decelerated or free. Details of the algorithm for the extraction of these classes are presented, along with experimental results on real movie data. We show with an investigation of combined rhythmic patterns that, while detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/editing rhythms can allow us to determine that the content has changed and hypothesize as to why this is so. We present three such categories of change and demonstrate their efficacy for capturing useful film elements (e.g. scene change precipitated by plot event), by providing data support from five motion pictures.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper forms a continuation of our work focused on exploiting film grammar for the task of automated film understanding. We examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and to enhance its lyrical quality experientially. Of the many, often complex, cinematic devices contributing to film rhythm, this paper investigates the rhythmic elements that are present in edited sequences of shots, and presents a novel computational model to detect shot structural rhythm as either metric, accelerated, decelerated, or free. Details of the algorithm for the extraction of these editing rhythm classes are presented, along with experimental results on real movie data. Following this we study the usefulness of combining the rhythmic patterns induced through both motion and editing in film. We show that, whilst detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/shot rhythm can allow us to determine that the content has changed and hypothesize as to why this is so. We present 3 such categories of change and demonstrate their efficacy for capturing useful film elements (e.g., scene change precipitated by plot event), by providing data support from 5 motion pictures.

Associations between fruit and vegetable intake, leisure-time physical activity, sitting time and self-rated health among older adults : cross-sectional data from the WELL study

Background
Lifestyle behaviours, such as healthy diet, physical activity and sedentary behaviour, are key elements of healthy ageing and important modifiable risk factors in the prevention of chronic diseases. Little is known about the relationship between these behaviours in older adults. The purpose of this study was to explore the relationship between fruit and vegetable (F&V) intake, leisure-time physical activity (LTPA) and sitting time (ST), and their association with self-rated health in older adults.

Methods
This cross-sectional study comprised 3,644 older adults (48% men) aged 55-65 years, who participated in the Wellbeing, Eating and Exercise for a Long Life ("WELL") study. Respondents completed a postal survey about their health and their eating and physical activity behaviours in 2010 (38% response rate). Spearman's coefficient (rho) was used to evaluate the relationship between F&V intake, LTPA and ST. Their individual and shared associations with self-rated health were examined using ordinal logistic regression models, stratified by sex and adjusted for confounders (BMI, smoking, long-term illness and socio-demographic characteristics).

Results
The correlations between F&V intake, LTPA and ST were low. F&V intake and LTPA were positively associated with self-rated health. Each additional serving of F&V or MET-hour of LTPA were associated with approximately 10% higher likelihood of reporting health as good or better among women and men. The association between ST and self-rated health was not significant in the multivariate analysis. A significant interaction was found (ST*F&V intake). The effect of F&V intake on self-rated health increased with increasing ST in women, whereas the effect decreased with increasing ST in men.

Conclusion
This study contributes to the scarce literature related to lifestyle behaviours and their association with health indicators among older adults. The findings suggest that a modest increase in F&V intake, or LTPA could have a marked effect on the health of older adults. Further research is needed to fully understand the correlates and determinants of lifestyle behaviours, particularly sitting time, in this age group.

Critical pre-implementation elements in engendering change for sustainability in SMEs : insights from SME sustainability leaders

Despite the increased awareness surrounding sustainability issues and growing pressure on businesses to adopt sustainable business practices, there is little understanding of management processes and practices necessary for SMEs to implement environmental sustainable (ES) practices. Through qualitative in-depth interviews, this paper draws on the experiences and perspectives from twelve SME sustainability leaders to present answers to the 'what' and 'why' of critical pre-implementation elements in engendering change for sustainability within the SME context. The research questions examined in this study are: In the views of SME sustainability leaders: what pre-implementation elements are important in setting the foundations of ES success in SMEs; what are the most important elements in the decision to introduce and encourage improved ES practices; and how do SME sustainability leaders plan for ES change in their firms. We also examine how the pre-implementation elements identified in this study, fit with the steps of one of the most well-known sustainability change management frameworks by Dunphy et al (2003). The results show that elements playing a role in setting the foundations for ES success in participating firms include: the SME leader challenging the status quo, gathering of initial information; clarifying the internal know-how about ES, identifying who the ES leader(s) is, and what the associated roles are; creating a theme of environmental sustainability in the firm (what sustainability means to the firm); and the personal mindset of leaders regarding ES. In addition, it was evident from the interview data that apart from providing valuable data regarding what must change and why, the drivers and benefits of ES provide a strong rationale and motivation to the rest of the organisation why sustainability is important to the organisation. Furthermore, it is evident from the interview data that the most used strategic approach to planning by SME sustainability leaders, is a deliberate approach even though the emergent approach to planning has also featured in some SMEs. Furthermore, the CEOs are the main players in the strategic process, with the majority involving staff in planning for ES. The results also indicate that in matching the pre-implementation elements to Dunphy et al‘s (2003) sustainability change management steps, the execution of two of their steps may need adjustment to be fully applicable to SMEs. Several practical implications for other SMEs are outlined. In conclusion, the framework outlined in this paper provides an example of a critically reflective approach to a specific phase of the environmental sustainability puzzle in SMEs.

Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data

Recent advances in telemetry technology have created a wealth of tracking data available for many animal species moving over spatial scales from tens of meters to tens of thousands of kilometers. Increasingly, such data sets are being used for quantitative movement analyses aimed at extracting fundamental biological signals such as optimal searching behavior and scale-dependent foraging decisions. We show here that the location error inherent in various tracking technologies reduces the ability to detect patterns of behavior within movements. Our analyses endeavored to set out a series of initial ground rules for ecologists to help ensure that sampling noise is not misinterpreted as a real biological signal. We simulated animal movement tracks using specialized random walks known as Lévy flights at three spatial scales of investigation: 100-km, 10-km, and 1-km maximum daily step lengths. The locations generated in the simulations were then blurred using known error distributions associated with commonly applied tracking methods: the Global Positioning System (GPS), Argos polar-orbiting satellites, and light-level geolocation. Deviations from the idealized Lévy flight pattern were assessed for each track after incrementing levels of location error were applied at each spatial scale, with additional assessments of the effect of error on scale-dependent movement patterns measured using fractal mean dimension and first-passage time (FPT) analyses. The accuracy of parameter estimation (Lévy μ, fractal mean D, and variance in FPT) declined precipitously at threshold errors relative to each spatial scale. At 100-km maximum daily step lengths, error standard deviations of ≥10 km seriously eroded the biological patterns evident in the simulated tracks, with analogous thresholds at the 10-km and 1-km scales (error SD ≥ 1.3 km and 0.07 km, respectively). Temporal subsampling of the simulated tracks maintained some elements of the biological signals depending on error level and spatial scale. Failure to account for large errors relative to the scale of movement can produce substantial biases in the interpretation of movement patterns. This study provides researchers with a framework for understanding the limitations of their data and identifies how temporal subsampling can help to reduce the influence of spatial error on their conclusions.