The use of temporal speech and lip information for multi-modal speaker identification via multi-stream HMMs

Investigates the use of temporal lip information, in conjunction with speech information, for robust, text-dependent speaker identification. We propose that significant speaker-dependent information can be obtained from moving lips, enabling speaker recognition systems to be highly robust in the presence of noise. The fusion structure for the audio and visual information is based around the use of multi-stream hidden Markov models (MSHMM), with audio and visual features forming two independent data streams. Recent work with multi-modal MSHMMs has been performed successfully for the task of speech recognition. The use of temporal lip information for speaker identification has been performed previously (T.J. Wark et al., 1998), however this has been restricted to output fusion via single-stream HMMs. We present an extension to this previous work, and show that a MSHMM is a valid structure for multi-modal speaker identification

Antiretroviral therapy (ART) adherence among people living with HIV/AIDS (PLHIV) in the north of Vietnam : a multi-method approach

The antiretroviral therapy (ART) program for People Living with HIV/AIDS (PLHIV) in Vietnam has been scaled up rapidly in recent years (from 50 clients in 2003 to almost 38,000 in 2009). ART success is highly dependent on the ability of the patients to fully adhere to the prescribed treatment regimen. Despite the remarkable extension of ART programs in Vietnam, HIV/AIDS program managers still have little reliable data on levels of ART adherence and factors that might promote or reduce adherence. Several previous studies in Vietnam estimated extremely high levels of ART adherence among their samples, although there are reasons to question the veracity of the conclusion that adherence is nearly perfect. Further, no study has quantitatively assessed the factors influencing ART adherence. In order to reduce these gaps, this study was designed to include several phases and used a multi-method approach to examine levels of ART non-adherence and its relationship to a range of demographic, clinical, social and psychological factors. The study began with an exploratory qualitative phase employing four focus group discussions and 30 in-depth interviews with PLHIV, peer educators, carers and health care providers (HCPs). Survey interviews were completed with 615 PLHIV in five rural and urban out-patient clinics in northern Vietnam using an Audio Computer Assisted Self-Interview (ACASI) and clinical records extraction. The survey instrument was carefully developed through a systematic procedure to ensure its reliability and validity. Cultural appropriateness was considered in the design and implementation of both the qualitative study and the cross sectional survey. The qualitative study uncovered several contrary perceptions between health care providers and HIV/AIDS patients regarding the true levels of ART adherence. Health care providers often stated that most of their patients closely adhered to their regimens, while PLHIV and their peers reported that “it is not easy” to do so. The quantitative survey findings supported the PLHIV and their peers’ point of view in the qualitative study, because non-adherence to ART was relatively common among the study sample. Using the ACASI technique, the estimated prevalence of onemonth non-adherence measured by the Visual Analogue Scale (VAS) was 24.9% and the prevalence of four-day not-on-time-adherence using the modified Adult AIDS Clinical Trials Group (AACTG) instrument was 29%. Observed agreement between the two measures was 84% and kappa coefficient was 0.60 (SE=0.04 and p<0.0001). The good agreement between the two measures in the current study is consistent with those found in previous research and provides evidence of cross-validation of the estimated adherence levels. The qualitative study was also valuable in suggesting important variables for the survey conceptual framework and instrument development. The survey confirmed significant correlations between two measures of ART adherence (i.e. dose adherence and time adherence) and many factors identified in the qualitative study, but failed to find evidence of significant correlations of some other factors and ART adherence. Non-adherence to ART was significantly associated with untreated depression, heavy alcohol use, illicit drug use, experiences with medication side-effects, chance health locus of control, low quality of information from HCPs, low satisfaction with received support and poor social connectedness. No multivariate association was observed between ART adherence and age, gender, education, duration of ART, the use of adherence aids, disclosure of ART, patients’ ability to initiate communication with HCPs or distance between clinic and patients’ residence. This is the largest study yet reported in Asia to examine non-adherence to ART and its possible determinants. The evidence strongly supports recent calls from other developing nations for HIV/AIDS services to provide screening, counseling and treatment for patients with depressive symptoms, heavy use of alcohol and substance use. Counseling should also address fatalistic beliefs about chance or luck determining health outcomes. The data suggest that adherence could be enhanced by regularly providing information on ART and assisting patients to maintain social connectedness with their family and the community. This study highlights the benefits of using a multi-method approach in examining complex barriers and facilitators of medication adherence. It also demonstrated the utility of the ACASI interview method to enhance open disclosure by people living with HIV/AIDS and thus, increase the veracity of self-reported data.

Principles for use of ball projection machines in elite and developmental sport programmes

Use of ball projection machines in the acquisition of interceptive skill has recently been questioned. The use of projection machines in developmental and elite fast ball sports programmes is not a trivial issue, since they play a crucial role in reducing injury incidence in players and coaches. A compelling challenge for sports science is to provide theoretical principles to guide how and when projection machines might be used for acquisition of ball skills and preparation for competition in developmental and elite sport performance programmes. Here, we propose how principles from an ecological dynamics theoretical framework could be adopted by sports scientists, pedagogues and coaches to underpin the design of interventions, practice and training tasks, including the use of hybrid video-projection technologies. The assessment of representative learning design during practice may provide ways to optimize developmental programmes in fast ball sports and inform the principled use of ball projection machines.

Determining operational measures from multi-camera surveillance systems using soft biometrics

CCTV and surveillance networks are increasingly being used for operational as well as security tasks. One emerging area of technology that lends itself to operational analytics is soft biometrics. Soft biometrics can be used to describe a person and detect them throughout a sparse multi-camera network. This enables them to be used to perform tasks such as determining the time taken to get from point to point, and the paths taken through an environment by detecting and matching people across disjoint views. However, in a busy environment where there are 100's if not 1000's of people such as an airport, attempting to monitor everyone is highly unrealistic. In this paper we propose an average soft biometric, that can be used to identity people who look distinct, and are thus suitable for monitoring through a large, sparse camera network. We demonstrate how an average soft biometric can be used to identify unique people to calculate operational measures such as the time taken to travel from point to point.

Aircraft emission reduction through multi-disciplinary flight path optimisation

There is worldwide interest in reducing aircraft emissions. The difficulty of reducing emissions including water vapour, carbon dioxide (CO2) and oxides of nitrogen (NOx) is mainly due from the fact that a commercial aircraft is usually designed for a particular optimal cruise altitude but may be requested or required to operate and deviate at different altitude and speeds to archive a desired or commanded flight plan, resulting in increased emissions. This is a multi- disciplinary problem with multiple trade-offs such as optimising engine efficiency, minimising fuel burnt, minimise emissions while maintaining aircraft separation and air safety. This project presents the coupling of an advanced optimisation technique with mathematical models and algorithms for aircraft emission reduction through flight optimisation. Numerical results show that the method is able to capture a set of useful trade-offs between aircraft range and NOx, and mission fuel consumption and NOx. In addition, alternative cruise operating conditions including Mach and altitude that produce minimum NOx and CO2 (minimum mission fuel weight) are suggested.

A study on acoustic emission signal propagation of a small size multi-cylinder diesel engine

Acoustic emission has been found effective in offering earlier fault detection and improving identification capabilities of faults. However, the sensors are inherently uncalibrated. This paper presents a source to sensor paths calibration technique which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time domain, time-frequency domain, and the root mean square (RMS) energy. The results reveal how the RMS energy of a source propagates to the adjacent sensors. The findings lead to allocate the source and estimate its inferences to the adjacent sensor, and finally help to diagnose the small size diesel engines by minimising the crosstalk from multiple cylinders.

A Krylov-based finite state projection algorithm for solving the chemical master equation arising in the discrete modelling of biological systems

Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically difficult to solve, since the state-space involved can be very large or even countably infinite. Recently a finite state projection method (FSP) that truncates the state-space was suggested and shown to be effective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the final time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger final times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was first demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is significantly faster and extendable to larger biological models.

An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation

This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.