Is the public healthcare sector a more strenuous working environment than the private sector for a physician?

Aims: The present study examined the differences between physicians working in public and private health care in strenuous working environments (presence of occupational hazards, physical violence, and presenteeism) and health behaviours (alcohol consumption, body mass index, and physical activity). In addition, we examined whether gender or age moderated these potential differences. Methods: Cross-sectional survey data were compiled on 1422 female and 948 male randomly selected physicians aged 25-65 years from The Finnish Health Care Professionals Study. Logistic regression and linear regression analyses were used with adjustment for gender, age, specialisation status, working time, managerial position, and on-call duty. Results: Occupational hazards, physical violence, and presenteeism were more commonly reported by physicians working in the public sector than by their counterparts in the private sector. Among physicians aged 50 years or younger, those who worked in the public sector consumed more alcohol than those who worked in the private sector, whereas in those aged 50 or more the reverse was true. In addition, working in the private sector was most strongly associated with lower levels of physical violence in those who were older than 50 years, and with lower levels of presenteeism among those aged 40-50 years. Conclusions: The present study found evidence for the public sector being a more strenuous work environment for physicians than the private sector. Our results suggest that public healthcare organisations should pay more attention to the working conditions of their employees.

A collaborative working environment for a large scale environmental model

Large scientific applications are usually developed, tested and used by a group of geographically dispersed scientists. The problems associated with the remote development and data sharing could be tackled by using collaborative working environments. There are various tools and software to create collaborative working environments. Some software frameworks, currently available, use these tools and software to enable remote job submission and file transfer on top of existing grid infrastructures. However, for many large scientific applications, further efforts need to be put to prepare a framework which offers application-centric facilities. Unified Air Pollution Model (UNI-DEM), developed by Danish Environmental Research Institute, is an example of a large scientific application which is in a continuous development and experimenting process by different institutes in Europe. This paper intends to design a collaborative distributed computing environment for UNI-DEM in particular but the framework proposed may also fit to many large scientific applications as well.

Assessing pragmatic interoperability for process alignment in collaborative working environment

This paper is an extension of our previous study on pragmatic interoperability assessment for process alignment. In this study, we conduct four case studies in industrial companies and hospitals in order to gather their viewpoints regarding the concerns when condensing process alignment in a collaborative working environment. Used techniques include interview, observation, and documentation. The collected results firstly are summarised into three layers based on our previous developed pragmatic assessment model, and then are transformed into the elements which constitutes the purposed method, and finally based on the summarised results we purpose a method for assessing pragmatic interoperability for process alignment in collaborative working environment. The method contains two parts: one gives all the elements of pragmatic interoperability that should be concerned when considering process alignment in collaborative working environment, and the other one is a supplementary method for dealing with technical concerns.

Adaptive speech enhancement with varying noise backgrounds

We present a new approach for speech enhancement in the presence of non-stationary and rapidly changing background noise. A distributed microphone system is used to capture the acoustic characteristics of the environment. The input of each microphone is then classified either as speech or one of the predetermined noise types. Further enhancement of speech in respective microphones is carried out using a modified spectral subtraction algorithm that incorporates multiple noise models to quickly adapt to rapid background noise changes. Tests on real world speech captured under diverse conditions demonstrate the effectiveness of this method.

Spatial activity recognition in a smart home environment using a chemotactic model

Spatial activity recognition is challenging due to the amount of noise incorporated during video tracking in everyday environments. We address the spatial recognition problem with a biologically-inspired chemotactic model that is capable of handling noisy data. The model is based on bacterial chemotaxis, a process that allows bacteria to change motile behaviour in relation to environmental gradients. Through adoption of chemotactic principles, we propose the chemotactic model and evaluate its performance in a smart house environment. The model exhibits greater than 99% recognition performance with a diverse six class dataset and outperforms the Hidden Markov Model (HMM). The approach also maintains high accuracy (90-99%) with small training sets of one to five sequences. Importantly, unlike other low-level spatial activity recognition models, we show that the chemotactic model is capable of recognising simple interwoven activities.

Generating Awareness from Collaborative Working Environment using Social Data

Nowadays, Internet is a place where social networks have reached an important impact in collaboration among people over the world in different ways. This article proposes a new paradigm for building CSCW business tools following the novel ideas provided by the social web to collaborate and generate awareness. An implementation of these concepts is described, including the components we provide to collaborate in workspaces, (such as videoconference, chat, desktop sharing, forums or temporal events), and the way we generate awareness from these complex social data structures. Figures and validation results are also presented to stress that this architecture has been defined to support awareness generation via joining current and future social data from business and social networks worlds, based on the idea of using social data stored in the cloud.