GLOA : a new job scheduling algorithm for grid computing

The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed) algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA), to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

The influence of organisational commitment, job involvement and utility perceptions on trainees’ motivation to improve work through learning

Workplace training is a key strategy often used by organisations to optimise performance. Further, trainee motivation is a key determinant of the degree to which the material learned in a training programme will be transferred to the workplace, enhancing the performance of the trainee. This study investigates the relationship between several components of the Revised Human Resource Development (HRD) Evaluation and Research Model. This model provides a framework for diagnosing and understanding the causal influences of HRD intervention outcomes on training effectiveness. Data were obtained from an online questionnaire completed by 105 employees of various organisations. Findings revealed that affective organisational commitment, job involvement and utility perceptions are predictors of motivation to learn and transfer learning. An interaction effect was found, with increased affective organisational commitment predicting greater motivation to learn when training was of lower perceived utility. These findings suggest that the design and delivery of training should emphasise the relevance and utility of the programme in order to encourage greater trainee motivation and maximise return on investment. Additionally, implementing strategies aimed at promoting organisational commitment would appear beneficial.

Job strain — attributable depression in a sample of working Australians: assessing the contribution to health inequalities

Background The broad aim of this study was to assess the contribution of job strain to mental health inequalities by (a) estimating the proportion of depression attributable to job strain (low control and high demand jobs), (b) assessing variation in attributable risk by occupational skill level, and (c) comparing numbers of job strain–attributable depression cases to numbers of compensated 'mental stress' claims. Methods Standard population attributable risk (PAR) methods were used to estimate the proportion of depression attributable to job strain. An adjusted Odds Ratio (OR) of 1.82 for job strain in relation to depression was obtained from a recently published meta-analysis and combined with exposure prevalence data from the Australian state of Victoria. Job strain exposure prevalence was determined from a 2003 population-based telephone survey of working Victorians (n = 1101, 66% response rate) using validated measures of job control (9 items, Cronbach's alpha = 0.80) and psychological demands (3 items, Cronbach's alpha = 0.66). Estimates of absolute numbers of prevalent cases of depression and successful stress-related workers' compensation claims were obtained from publicly available Australian government sources. Results Overall job strain-population attributable risk (PAR) for depression was 13.2% for males [95% CI 1.1, 28.1] and 17.2% [95% CI 1.5, 34.9] for females. There was a clear gradient of increasing PAR with decreasing occupational skill level. Estimation of job strain–attributable cases (21,437) versus "mental stress" compensation claims (696) suggest that claims statistics underestimate job strain–attributable depression by roughly 30-fold. Conclusion Job strain and associated depression risks represent a substantial, preventable, and inequitably distributed public health problem. The social patterning of job strain-attributable depression parallels the social patterning of mental illness, suggesting that job strain is an important contributor to mental health inequalities. The numbers of compensated 'mental stress' claims compared to job strain-attributable depression cases suggest that there is substantial under-recognition and under-compensation of job strain-attributable depression. Primary, secondary, and tertiary intervention efforts should be substantially expanded, with intervention priorities based on hazard and associated health outcome data as an essential complement to claims statistics.

Cost of reproduction in the Queensland fruit fly: Y-model versus lethal protein hypothesis

The trade-off between lifespan and reproduction is commonly explained by differential allocation of limited resources. Recent research has shown that the ratio of protein to carbohydrate (P : C) of a fly's diet mediates the lifespan–reproduction trade-off, with higher P : C diets increasing egg production but decreasing lifespan. To test whether this P : C effect is because of changing allocation strategies (Y-model hypothesis) or detrimental effects of protein ingestion on lifespan (lethal protein hypothesis), we measured lifespan and egg production in Queensland fruit flies varying in reproductive status (mated, virgin and sterilized females, virgin males) that were fed one of 18 diets varying in protein and carbohydrate amounts. The Y-model predicts that for sterilized females and for males, which require little protein for reproduction, there will be no effect of P : C ratio on lifespan; the lethal protein hypothesis predicts that the effect of P : C ratio should be similar in all groups. In support of the lethal protein hypothesis, and counter to the Y-model, the P : C ratio of the ingested diets had similar effects for all groups. We conclude that the trade-off between lifespan and reproduction is mediated by the detrimental side-effects of protein ingestion on lifespan.

Area-level unemployment and perceived job insecurity: evidence from a longitudinal survey conducted in the Australian working-age population

Research significance: Job insecurity, the subjective individual anticipation of involuntary job loss, negatively affects employees’ health and their engagement. Although the relationship between job insecurity and health has been extensively studied, job insecurity as an ‘exposure’ has received far less attention, with little known about the upstream determinants of job insecurity in particular. This research sought to identify the relationship between self-rated job insecurity and area-level unemployment using a longitudinal, nationally representative study of Australian households. Methods: Mixed-effect multi-level regression models were used to assess the relationship between area-based unemployment rates and self-reported job insecurity using data from a longitudinal, nationally representative survey running since 2001. Interaction terms were included to test the hypotheses that the relationship between area-level unemployment and job insecurity differed between occupational skill-level groups and by employment arrangement. Marginal effects were computed to visually depict differences in job insecurity across areas with different levels of unemployment. Results: Results indicated that areas with the lowest unemployment rates had significantly lower job insecurity (predicted value 2.74; 95% confidence interval (CI) 2.71–2.78, P < 0.001) than areas with higher unemployment (predicted value 2.81; 95% CI 2.79–2.84, P < 0.001). There was a stronger relationship between area-level unemployment and job insecurity among precariously and fixed-term employed workers than permanent workers. Conclusion: These findings demonstrate the independent influences of prevailing economic conditions, individual- and job-level factors on job insecurity. Persons working on a casual basis or on a fixed-term contract in areas with higher levels of unemployment are more susceptible to feelings of job insecurity than those working permanently.

Does privatisation drive innovation? Business model innovation through stakeholder viewpoints: the case of Sydney Airport 10 years post-privatisation

Broad economic and social reform, rapid technological change and increasing global competition have meant that organisations must consider all aspects of their business model in order to successfully create and capture ongoing customer value. In this study it is proposed that business model innovation must always consider and incorporate the symbiotic and interdependent relationship that stakeholders have with an organisation. One particular aspect of economic reform, privatisation, has become an important driver of economic growth in many economies, particularly when linked with the rapid growth of air travel. Privatisation of an airport can generate a radical change in the overall business model for the airport owner and the various stakeholders involved in the operation of the airport. Sydney Airport has restructured its overarching business model to meet the demands of stakeholders. Using feedback from key stakeholders, this research examines the generally accepted view that airport privatisation leads to an improvement in airport performance. Chesbrough's Business Model Framework provides a lens to assist the analysis of Sydney Airport operations before and after privatisation, and provides valuable insights into the impact of privatisation on business model innovation. © Cambridge University Press and Australian and New Zealand Academy of Management 2014.

Deferentially private tagging recommendation based on topic model

Tagging recommender system allows Internet users to annotate resources with personalized tags and provides users the freedom to obtain recommendations. However, It is usually confronted with serious privacy concerns, because adversaries may re-identify a user and her/his sensitive tags with only a little background information. This paper proposes a privacy preserving tagging release algorithm, PriTop, which is designed to protect users under the notion of differential privacy. The proposed PriTop algorithm includes three privacy preserving operations: Private Topic Model Generation structures the uncontrolled tags, Private Weight Perturbation adds Laplace noise into the weights to hide the numbers of tags; while Private Tag Selection finally finds the most suitable replacement tags for the original tags. We present extensive experimental results on four real world datasets and results suggest the proposed PriTop algorithm can successfully retain the utility of the datasets while preserving privacy. © 2014 Springer International Publishing.

A shadow-like task migration model based on context semantics for mobile and pervasive environments

Pervasive computing is a user-centric mobile computing paradigm, in which tasks should be migrated over different platforms in a shadow-like way when users move around. In this paper, we propose a context-sensitive task migration model that recovers program states and rebinds resources for task migrations based on context semantics through inserting resource description and state description sections in source programs. Based on our model, we design and develop a task migration framework xMozart which extends the Mozart platform in terms of context awareness. Our approach can recover task states and rebind resources in the context-aware way, as well as support multi- modality I/O interactions. The extensive experiments demonstrate that our approach can migrate tasks by resuming them from the last broken points like shadows moving along with the users.

Cardiovascular prevention model from Kenyan slums to migrants in the Netherlands

Cardiovascular diseases (CVD) are the main cause of morbidity and mortality worldwide. As prevention and treatment of CVD often requires active screening and lifelong follow up it is a challenge for health systems both in high-income and low and middle-income countries to deliver adequate care to those in need, with efficient use of resources.We developed a health service model for primary prevention of CVD suitable for implementation in the Nairobi slums, based on best practices from public health and the private sectors. The model consists of four key intervention elements focusing on increasing awareness, incentives for promoting access to screening and treatment, and improvement of long-term adherence to prescribed medications. More than 5,000 slum dwellers aged ≥35 years and above have been screened in the study resulting in more than 1000 diagnosed with hypertension and referred to the clinic.Some marginalized groups in high-income countries like African migrants in the Netherlands also have low rates of awareness, treatment and control of hypertension as the slum population in Nairobi. The parallel between both groups is that they have a combination of risky lifestyle, are prone to chronic diseases such as hypertension, have limited knowledge about hypertension and its complications, and a tendency to stay away from clinics partly due to cultural beliefs in alternative forms of treatment, and lack of trust in health providers. Based on these similarities it was suggested by several policymakers that the model from Nairobi can be applied to other vulnerable populations such as African migrants in high-income countries. The model can be contextualized to the local situation by adapting the key steps of the model to the local settings.The involvement and support of African communities' infrastructures and health care staff is crucial, and the most important enabler for successful implementation of the model in migrant communities in high-income countries. Once these stakeholders have expressed their interest, the impact of the adapted intervention can be measured through an implementation research approach including collection of costs from health care providers' perspective and health effects in the target population, similar to the study design for Nairobi.

Rebound or resignation: developing a predictive model of return to subjective wellbeing set-point

Though subjective wellbeing (SWB) is generally stable and consistent over time, it can fall below its set-point in response to adverse life events. However, deviations from set-point levels are usually only temporary, as homeostatic processes operate to return SWB to its normal state. Given that income and close interpersonal relationships have been proposed as powerful external resources that are coincident with higher SWB, access to these resources may be an important predictor of whether or not a person is likely to recover their SWB following a departure from their set-point. Under the guiding framework of SWB Homeostasis Theory, this study considers whether access to a higher income and a committed partner can predict whether people who score lower than normal for SWB at baseline will return to normal set-point levels of SWB (rebound) or remain below the normal range (resigned) at follow-up. Participants were 733 people (53.3 % female) from the Australian Unity Longitudinal Wellbeing Study who ranged in age from 20 to 92 years (M = 59.65 years; SD = 13.15). Logistic regression analyses revealed that participants’ demographic characteristics were poor predictors of whether they rebounded or resigned. Consistent with homeostasis theory, the extent of departure from the proposed normal SWB set-point at baseline was significantly associated with rebound or resignation at time 2. These findings have implications for the way that SWB measures can be used in professional practice to identify people who are particularly vulnerable to depression and to guide the provision of appropriate and effective therapeutic interventions.

Individual differences in intention to fake job interviews: Personality, self-monitoring, and the theory of planned behaviour

When job applicants lie in job interviews, they can deprive a more honest candidate of a job and deprive an organisation of the best employees. To better understand job interview faking, the present study examined the effect of general dispositions and domain-specific beliefs on the intention to fake job interviews. A community sample of 313 participants completed measures of personality (i.e., extraversion, neuroticism, conscientiousness) and self-monitoring, and a domain-specific measure of beliefs about faking job interviews based on the theory of planned behaviour, which measured attitudes, subjective norms, and perceived behavioural control. Results indicated that the measure of attitudes was the strongest predictor of intention to fake. In line with the compatibility principle, the domain-specific measures based on the theory of planned behaviour correlated much more strongly with intentions to fake job interviews than did the general measures of personality or self-monitoring. Of the dispositional measures, lower conscientiousness, higher neuroticism, and higher self-monitoring was associated with greater intention to fake job interviews. The findings support a model whereby the effect of personality on intentions is partially mediated by domain-specific beliefs.

Exploring spatiotemporal trends in commercial fishing effort of an abalone fishing zone: a GIS-based hotspot model

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100's of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics.

The impact of participative leadership on job performance and organizational citizenship behavior: distinguishing between the mediating effects of affective and cognitive trust

This study examines the mediating effects of cognitive trust and affective trust on the relationship between supervisors' participative leadership behavior and subordinate work outcomes, using data obtained from 247 dyads in a manufacturing organization located in mainland China. Structural equation modeling revealed that while affective trust fully mediated the relationships between participative leadership of supervisor and subordinate job performance and organizational citizenship behavior, cognitive trust had non-significant effects. These findings underscore the importance of interpersonal interactions between the supervisor and subordinate for engendering subordinate work outcomes. They also lend support to the exchange (relationship)-based explanation as to how trust enhances the response of subordinates to the participative leadership behavior of their immediate supervisor, given that affective trust involves a process of social exchange between both parties over an extended period of time. © 2014 © 2014 Taylor & Francis.

Adaptable, model-driven security engineering for SaaS cloud-based applications

Software-as-a-service (SaaS) multi-tenancy in cloud-based applications helps service providers to save cost, improve resource utilization, and reduce service customization and maintenance time. This is achieved by sharing of resources and service instances among multiple "tenants" of the cloud-hosted application. However, supporting multi-tenancy adds more complexity to SaaS applications required capabilities. Security is one of these key requirements that must be addressed when engineering multi-tenant SaaS applications. The sharing of resources among tenants - i.e. multi-tenancy - increases tenants' concerns about the security of their cloud-hosted assets. Compounding this, existing traditional security engineering approaches do not fit well with the multi-tenancy application model where tenants and their security requirements often emerge after the applications and services were first developed. The resultant applications do not usually support diverse security capabilities based on different tenants' needs, some of which may change at run-time i.e. after cloud application deployment. We introduce a novel model-driven security engineering approach for multi-tenant, cloud-hosted SaaS applications. Our approach is based on externalizing security from the underlying SaaS application, allowing both application/service and security to evolve at runtime. Multiple security sets can be enforced on the same application instance based on different tenants' security requirements. We use abstract models to capture service provider and multiple tenants' security requirements and then generate security integration and configurations at runtime. We use dependency injection and dynamic weaving via Aspect-Oriented Programming (AOP) to integrate security within critical application/service entities at runtime. We explain our approach, architecture and implementation details, discuss a usage example, and present an evaluation of our approach on a set of open source web applications.

A decentralized cloud firewall framework with resources provisioning cost optimization

Cloud computing is becoming popular as the next infrastructure of computing platform. Despite the promising model and hype surrounding, security has become the major concern that people hesitate to transfer their applications to clouds. Concretely, cloud platform is under numerous attacks. As a result, it is definitely expected to establish a firewall to protect cloud from these attacks. However, setting up a centralized firewall for a whole cloud data center is infeasible from both performance and financial aspects. In this paper, we propose a decentralized cloud firewall framework for individual cloud customers. We investigate how to dynamically allocate resources to optimize resources provisioning cost, while satisfying QoS requirement specified by individual customers simultaneously. Moreover, we establish novel queuing theory based model M/Geo/1 and M/Geo/m for quantitative system analysis, where the service times follow a geometric distribution. By employing Z-transform and embedded Markov chain techniques, we obtain a closed-form expression of mean packet response time. Through extensive simulations and experiments, we conclude that an M/Geo/1 model reflects the cloud firewall real system much better than a traditional M/M/1 model. Our numerical results also indicate that we are able to set up cloud firewall with affordable cost to cloud customers.