Social signal processing for pain monitoring using a hidden conditional random field

utomatic pain monitoring has the potential to greatly improve patient diagnosis and outcomes by providing a continuous objective measure. One of the most promising methods is to do this via automatically detecting facial expressions. However, current approaches have failed due to their inability to: 1) integrate the rigid and non-rigid head motion into a single feature representation, and 2) incorporate the salient temporal patterns into the classification stage. In this paper, we tackle the first problem by developing a “histogram of facial action units” representation using Active Appearance Model (AAM) face features, and then utilize a Hidden Conditional Random Field (HCRF) to overcome the second issue. We show that both of these methods improve the performance on the task of pain detection in sequence level compared to current state-of-the-art-methods on the UNBC-McMaster Shoulder Pain Archive.

Rogue flows : trans-Asian cultural traffic

"Rogue Flows brings together some of the best and most knowledgeable writers on consumption and cultural theory to chart the under-explored field of cultural flows and consumption across different regions in Asia, and the importance of these flows in creating contemporary Asian national identities. It offers innovative possibilities for envisioning how the transfer of popular and consumer culture (such as TV, music, film, advertising and commodities) across Asian countries has produced a new form of cross-cultural fertilisation within Asian societies, which does not merely copy Western counterparts." "Rogue Flows is unique in its investigation of how "Asianness" is being exploited by Asian transnational cultural industries and how it is involved in the new power relations of the region. It is an important contribution to the literature of Asian cultural studies."--BOOK JACKET.

Reducing alcohol-related driving on China's roads : Traffic police officers' perceptions and practice

Alcohol-related driving is a longstanding, serious problem in China (Li, Xie, Nie, & Zhang, 2012). On 1st May, 2011 a national law was introduced to criminalize drunk driving, and imposed serious penalties including jail for driving with a blood alcohol level of above 80mg/100ml. This pilot study, undertaken a year after introduction of the law, sought traffic police officers’ perceptions of drink driving and the practice of breath alcohol testing (BAT) in a large city in Guangdong Province, southern China. A questionnaire survey and semi-structured interviews were used to gain an in-depth understanding of issues relevant to alcohol-related driving. Fifty-five traffic police officers were recruited for the survey and six traffic police officers with a variety of working experience including roadside alcohol breath testing, traffic crash investigation and police resourcing were interviewed individually. The officers were recruited by the first author with the assistance of the staff from Guangdong Institute of Public Health, Centre for Disease Control and Prevention (CDC). Interview participants reported three primary reasons why people drink and drive: 1) being prepared to take the chance of not being apprehended by police; 2) the strong traditional Chinese drinking culture; and 3) insufficient public awareness about the harmfulness of drink driving. Problems associated with the process of breath alcohol testing (BAT) were described and fit broadly into two categories: resourcing and avoiding detection. It was reported that there were insufficient traffic police officers to conduct routine traffic policing, including alcohol testing. Police BAT equipment was considered sufficient for routine traffic situations but not highway traffic operations. Local media and posters are used by the Public Security Bureau which is responsible for education about safe driving but participants thought that the education campaigns are limited in scope. Participants also described detection avoidance strategies used by drivers including: changing route; ignoring a police instruction to stop; staying inside the vehicle with windows and doors locked to avoid being tested; intentionally not performing breath tests correctly; and arguing with officers. This pilot study provided important insights from traffic police in one Chinese city which suggest there may be potential unintended effects of introducing more severe penalties including a range of strategies reportedly used by drivers to avoid detection. Recommendations for future research include a larger study to confirm these findings and examine the training and education of drivers; the focus and reach of publicity; and possible resource needs to support police enforcement.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

Assessing the Impact of Sensor Accuracy and Sensor Choice on Air Traffic Conflict Risk Estimation using Risk-Ratio Concepts

One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.

A wide area monitoring system based load restoration method

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Risk modelling in quality clinical registries : Monitoring lesion treatment failure rate in percutaneous coronary interventions

Aims: This paper describes the development of a risk adjustment (RA) model predictive of individual lesion treatment failure in percutaneous coronary interventions (PCI) for use in a quality monitoring and improvement program. Methods and results: Prospectively collected data for 3972 consecutive revascularisation procedures (5601 lesions) performed between January 2003 and September 2011 were studied. Data on procedures to September 2009 (n = 3100) were used to identify factors predictive of lesion treatment failure. Factors identified included lesion risk class (p < 0.001), occlusion type (p < 0.001), patient age (p = 0.001), vessel system (p < 0.04), vessel diameter (p < 0.001), unstable angina (p = 0.003) and presence of major cardiac risk factors (p = 0.01). A Bayesian RA model was built using these factors with predictive performance of the model tested on the remaining procedures (area under the receiver operating curve: 0.765, Hosmer–Lemeshow p value: 0.11). Cumulative sum, exponentially weighted moving average and funnel plots were constructed using the RA model and subjectively evaluated. Conclusion: A RA model was developed and applied to SPC monitoring for lesion failure in a PCI database. If linked to appropriate quality improvement governance response protocols, SPC using this RA tool might improve quality control and risk management by identifying variation in performance based on a comparison of observed and expected outcomes.

Estimating health related costs and savings from balcony acoustic design for road traffic noise

A multi-faceted study is conducted with the objective of estimating the potential fiscal savings in annoyance and sleep disturbance related health costs due to providing improved building acoustic design standards. This study uses balcony acoustic treatments in response to road traffic noise as an example. The study area is the State of Queensland in Australia, where regional road traffic noise mapping data is used in conjunction with standard dose–response curves to estimate the population exposure levels. The background and the importance of using the selected road traffic noise indicators are discussed. In order to achieve the objective, correlations between the mapping indicator (LA10 (18 hour)) and the dose response curve indicators (Lden and Lnight) are established via analysis on a large database of road traffic noise measurement data. The existing noise exposure of the study area is used to estimate the fiscal reductions in health related costs through the application of simple estimations of costs per person per year per degree of annoyance or sleep disturbance. The results demonstrate that balcony acoustic treatments may provide a significant benefit towards reducing the health related costs of road traffic noise in a community.

The significance of balcony acoustic treatments in mitigating urban road traffic noise

Urban road traffic noise in cities is an ongoing and increasing problem across much of the world. Consequently a large amount of effort is expended in attempts to address this problem, especially in the area of acoustic design of buildings. Acoustic design policies developed by government authorities will typically focus on required transport noise reductions through a building façade to meet a specified internal noise levels. The significance of balcony acoustic treatments has been highlighted in recent decades yet this area has potentially been considered less important than the need for acoustic isolation of building facades. This paper outlines recent research that has been conducted in determining the significance of balcony acoustic treatments in mitigating urban road traffic noise. It summarizes recent literature, some of which focuses on technological advances in the knowledge of balcony acoustic design and some literature discusses the overall aims and benefits of balcony acoustic design. The aim of this paper is to promote the use of balcony acoustic design as a significant element in the overall solution towards mitigating road traffic noise in modern cities.

Speech interference and transmission on residential balconies with road traffic noise

Balcony acoustic treatments can mitigate the effects of community road traffic noise. To further investigate, a theoretical study into the effects of balcony acoustic treatment combinations on speech interference and transmission is conducted for various street geometries. Nine different balcony types are investigated using a combined specular and diffuse reflection computer model. Diffusion in the model is calculated using the radiosity technique. The balcony types include a standard balcony with or without a ceiling and with various combinations of parapet, ceiling absorption and ceiling shield. A total of 70 balcony and street geometrical configurations are analyzed with each balcony type, resulting in 630 scenarios. In each scenario the reverberation time, speech interference level (SIL) and speech transmission index (STI) are calculated. These indicators are compared to determine trends based on the effects of propagation path, inclusion of opposite buildings and difference with a reference position outside the balcony. The results demonstrate trends in SIL and STI with different balcony types. It is found that an acoustically treated balcony reduces speech interference. A parapet provides the largest improvement, followed by absorption on the ceiling. The largest reductions in speech interference arise when a combination of balcony acoustic treatments are applied.

A Systematic review of a statistical vacuum circuit breaker model for condition monitoring

Vacuum circuit breaker (VCB) overvoltage failure and its catastrophic failures during shunt reactor switching have been analyzed through computer simulations for multiple reignitions with a statistical VCB model found in the literature. However, a systematic review (SR) that is related to the multiple reignitions with a statistical VCB model does not yet exist. Therefore, this paper aims to analyze and explore the multiple reignitions with a statistical VCB model. It examines the salient points, research gaps and limitations of the multiple reignition phenomenon to assist with future investigations following the SR search. Based on the SR results, seven issues and two approaches to enhance the current statistical VCB model are identified. These results will be useful as an input to improve the computer modeling accuracy as well as the development of a reignition switch model with point-on-wave controlled switching for condition monitoring

School-based first aid training and the implications for traffic injury prevention : a randomised controlled trial

Adolescent injury remains a significant public health concern and is often the result of at-risk transport related behaviours. When a person is injured actions taken by bystanders are of crucial importance and timely first aid appears to reduce the severity of some injuries (Hussain & Redmond, 1994). Accordingly, researchers have suggested that first aid training should be more widely available as a potential strategy to reduce injury (Lynch et al., 2006). Further research has identified schools as an ideal setting for learning first aid skills as a means of injury prevention (Maitra, 1997). The current research examines the implications of school based first aid training for young adolescents on injury prevention, particularly relating to transport injuries. First aid training was integrated with peer protection and school connectedness within the Skills for Preventing Injury in Youth (SPIY) program (Buckley & Sheehan, 2009) and evaluated to determine if there was a reduction in the likelihood of transport related injuries at six months post-intervention. In Queensland, Australia, 35 high schools were recruited and randomly assigned to intervention and control conditions in early April 2012. A total of 2,000 Year nine students (mean age 13.5 years, 39% male) completed surveys six months post-intervention in November 2012. Analyses will compare the intervention students with control group students who self-reported i) first aid training with a teacher, professional or other adult and ii) no first aid in the preceding six months. Using the Extended Adolescent Injury Checklist (E-AIC) (Chapman, Buckley & Sheehan, 2011) the transport related injury experiences included being injured while “riding as a passenger in a car”, “driving a car off road” and “riding a bicycle”. It is expected that students taught first aid within SPIY will report significantly fewer transport related injuries in the previous three months, compared to the control groups described above. Analyses will be conducted separately for sex and socio-economic class of schools. Findings from this study will provide insight into the value of first aid in adolescent injury prevention and provide evidence as to whether teaching first aid skills within a school based health education curriculum has traffic safety implications.

A hybrid association rule mining approach for characterizing network traffic behaviour

Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.