Big-five personality factors affecting driving behaviours

The factors affecting driving behaviors are various and interact simultaneously. Therefore, study of their correlations affecting on driving behaviors is of interest. This paper reports a questionnaire survey in China, focusing on the effect of Big-Five factors on speeding, drink driving, and distracted driving while Akers' social learning theory and Homel's deterrence theory were applied. The results showed that personalities had significant effect on speeding and drink driving; social factors had significant effect on speeding and distracted driving; deterrence had significant effect on speeding and drink driving; however, social learning theory did not contribute to drink driving; deterrence did not affect distracted driving. The results were discussed along with the limitation of this study.

Spectrum sensing using two-stage detection to compensate for reduced primary user duty cycle

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. One of the common assumption among current spectrum sensing detectors is the full presence or complete absence of the primary user within the sensing period. In reality, there are many situations where the primary user signal only occupies a portion of the observed signal and the assumption of primary user duty cycle not necessarily fulfilled. In this paper we show that the true detection performance can degrade from the assumed achievable values when the observed primary user exhibits a certain duty cycle. Therefore, a two-stage detection method incorporating primary user duty cycle that enhances the detection performance is proposed. The proposed detector can improve the probability of detection under low duty cycle at the expense of a small decrease in performance at high duty cycle.

Activity analysis in complicated scenes using DFT coefficients of particle trajectories

Modelling activities in crowded scenes is very challenging as object tracking is not robust in complicated scenes and optical flow does not capture long range motion. We propose a novel approach to analyse activities in crowded scenes using a “bag of particle trajectories”. Particle trajectories are extracted from foreground regions within short video clips using particle video, which estimates long range motion in contrast to optical flow which is only concerned with inter-frame motion. Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes. We show that our approaches achieve state-of-the-art performance for both tasks.

Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

Recognising the capacities of dynamic reconfiguration for the QoS assurance of running systems in concurrent and parallel environments

Recognizing the impact of reconfiguration on the QoS of running systems is especially necessary for choosing an appropriate approach to dealing with dynamic evolution of mission-critical or non-stop business systems. The rationale is that the impaired QoS caused by inappropriate use of dynamic approaches is unacceptable for such running systems. To predict in advance the impact, the challenge is two-fold. First, a unified benchmark is necessary to expose QoS problems of existing dynamic approaches. Second, an abstract representation is necessary to provide a basis for modeling and comparing the QoS of existing and new dynamic reconfiguration approaches. Our previous work [8] has successfully evaluated the QoS assurance capabilities of existing dynamic approaches and provided guidance of appropriate use of particular approaches. This paper reinvestigates our evaluations, extending them into concurrent and parallel environments by abstracting hardware and software conditions to design an evaluation context. We report the new evaluation results and conclude with updated impact analysis and guidance.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

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.

Experimental evaluation of MCDTK, the Monte Carlo DICOM Tool-Kit

The Monte Carlo DICOM Tool-Kit (MCDTK) is a software suite designed for treatment plan dose verification, using the BEAMnrc and DOSXYZnrc Monte Carlo codes. MCDTK converts DICOM-format treatment plan information into Monte Carlo input files and compares the results of Monte Carlo treatment simulations with conventional treatment planning dose calculations. In this study, a treatment is planned using a commercial treatment planning system, delivered to a pelvis phantom containing ten thermoluminescent dosimeters and simulated using BEAMnrc and DOSXYZnrc using inputs derived from MCDTK. The dosimetric accuracy of the Monte Carlo data is then evaluated via comparisons with the dose distribution obtained from the treatment planning system as well as the in-phantom point dose measurements. The simulated beam arrangement produced by MCDTK is found to be in geometric agreement with the planned treatment. An isodose display generated from the Monte Carlo data by MCDTK shows general agreement with the isodose display obtained from the treatment planning system, except for small regions around density heterogeneities in the phantom, where the pencil-beam dose calculation performed by the treatment planning systemis likely to be less accurate. All point dose measurements agree with the Monte Carlo data obtained using MCDTK, within confidence limits, and all except one of these point dose measurements show closer agreement with theMonte Carlo data than with the doses calculated by the treatment planning system. This study provides a simple demonstration of the geometric and dosimetric accuracy ofMonte Carlo simulations based on information from MCDTK.

Monte Carlo evaluation of collapsed-cone convolution calculations in head and neck radiotherapy treatment plans

The presence of air and bone interfaces makes the dose distribution for head and neck cancer treatments difficult to accurately predict. This study compared planning system dose calculations using the collapsed-cone convolution algorithm with EGSnrcMonte Carlo simulation results obtained using the Monte Carlo DICOMToolKit software, for one oropharynx, two paranasal sinus and three nodal treatment plans. The difference between median doses obtained from the treatment planning and Monte Carlo calculations was found to be greatest in two bilateral treatments: 4.8%for a retropharyngeal node irradiation and 6.7% for an ethmoid paranasal sinus treatment. These deviations in median dose were smaller for two unilateral treatments: 0.8% for an infraclavicular node irradiation and 2.8% for a cervical node treatment. Examination of isodose distributions indicated that the largest deviations between Monte Carlo simulation and collapsed-cone convolution calculations were seen in the bilateral treatments, where the increase in calculated dose beyond air cavities was most significant.

The creative cities discourse : production and/or consumption?

The already considerable debate about what constitutes a 'creative' city becomes ever more critical as the world urbanizes at a rapid pace. In this chapter the author argues that the key tensions in discussions over what makes cities more conducive to and supportive of creativity revolve around perspectives that are either production-centric or consumption-centric. Scholars are increasing prepared to claim priority for the city-region over the nation-state as an economic and cultural agent in the contemporary world, but are they ready to deal with major changes in the nature of cultural production and consumption themselves? A number of examples of new challenges for the creative cities 'discourse' rounds out the chapter.

Culture, technology and the city

The 21st century has been described as the “century of cities”. By 2030, 70 per cent of the world’s population will live in cities, with the most rapid urbanization occurring in the developing world. This paper will draw up geographer Ed Soja’s concept of the “spatial turn” in social theory to consider how the culture of cities can act as a catalyst to innovation and the development of new technologies. In doing so, the paper will develop a three-layered approach to culture as: the arts; the way of life of people and communities; and the embedded structure underpinning socio-economic relations. It will also consider technology at a three-layered element, including devices, practices and ‘logics’ of technology, or what the Greeks termed techne. The paper will consider recent approaches to urban cultural policy, including cluster development and creative cities, and suggest some alternatives, noting that a problem with current approaches is that they focus excessively upon production (clusters) or consumption (creative cities). It will also consider the development of digital creative industries such as games, and the strategies of different cities to develop an innovation culture.