Ozone-initiated particle formation, particle aging, and precursors in a laser printer

An increasing number of researchers have hypothesized that ozone may be involved in the particle formation processes that occur during printing, however no studies have investigated this further. In the current study, this hypothesis was tested in a chamber study by adding supplemental ozone to the chamber after a print job without measurable ozone emissions. Subsequent particle number concentration and size distribution measurements showed that new particles were formed minutes after the addition of ozone. The results demonstrated that ozone did react with printer-generated volatile organic compounds (VOCs) to form secondary organic aerosols (SOAs). The hypothesis was further confirmed by the observation of correlations among VOCs, ozone, and particles concentrations during a print job with measurable ozone emissions. The potential particle precursors were identified by a number of furnace tests, which suggested that squalene and styrene were the most likely SOA precursors with respect to ozone. Overall, this study significantly improved scientific understanding of the formation mechanisms of printer-generated particles, and highlighted the possible SOA formation potential of unsaturated nonterpene organic compounds by ozone-initiated reactions in the indoor environment. © 2011 American Chemical Society.

Efficient safety information retrieval on construction sites: a preliminary methodology

IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports.

Automated support for versioning compliance checking between workflow management and product lifecycle management (in Chinese)

With the development of enterprise informatisation, Product Lifecycle Management (PLM) systems have been widely deployed and applied in enterprises. This paper analyzes the requirement that conducting version operations on business objects as specified in process models should be compliant with the versioning policies imposed by product lifecycles. This leads to the introduction of the concept of versioning compliance, and the approach of compliance checking that we proposed in our earlier work, which comprises both syntactical compatibility and behavioural compatibility checking. The paper then focuses on the tool implementation for providing automated support to the versioning compliance checking. An empirical evaluation of the tool was also performed with industrial partners using the well-known questionnaire-based method. The evaluation and feedback from practitioners further evidence the practical significance of this research question in the PLM field and demonstrate that the proposed solution with its automated tool support possesses a high application potential.

Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.