Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Agency problems of corporate philanthropy

Evaluating agency theory and optimal contracting theory views of corporate philanthropy, we find that as corporate giving increases, shareholders reduce their valuation of firm cash holdings. Dividend increases following the 2003 Tax Reform Act are associated with reduced corporate giving. Using a natural experiment, we find that corporate giving is positively (negatively) associated with CEO charity preferences (CEO shareholdings and corporate governance quality). Evidence from CEO-affiliated charity donations, market reactions to insider-affiliated donations, its relation to CEO compensation, and firm contributions to director-affiliated charities indicates that corporate donations advance CEO interests and suggests misuses of corporate resources that reduce firm value.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

Comparisons between youth of a parent with MS and a control group on adjustment, caregiving, attachment and family functioning

Few studies have examined the effects of parental MS on children, and those that have suffered from numerous methodological weaknesses, some of which are addressed in this study. This study investigated the effects of parental MS on children by comparing youth of a parent with MS to youth who have no family member with a serious health condition on adjustment outcomes, caregiving, attachment and family functioning. A questionnaire survey methodology was used. Measures included youth somatisation, health, pro-social behaviour, behavioural-social difficulties, caregiving, attachment and family functioning. A total of 126 youth of a parent with MS were recruited from MS Societies in Australia and, were matched one-to-one with youth who had no family member with a health condition drawn from a large community sample. Comparisons showed that youth of a parent with MS did not differ on any of the outcomes except for peer relationship problems: adolescent youth of a parent with MS reported lower peer relationship problems than control adolescents. Overall, results did not support prior research findings suggesting adverse impacts of parental MS on youth.

Rough Fuzzy Control of SVC for Power System Stability Enhancement

Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

Optimal eradication: When to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter. © 2006 Blackwell Publishing Ltd/CNRS.

Automatic camera exposure control

It is commonplace to use digital video cameras in robotic applications. These cameras have built-in exposure control but they do not have any knowledge of the environment, the lens being used, the important areas of the image and do not always produce optimal image exposure. Therefore, it is desirable and often necessary to control the exposure off the camera. In this paper we present a scheme for exposure control which enables the user application to determine the area of interest. The proposed scheme introduces an intermediate transparent layer between the camera and the user application which combines the information from these for optimal exposure production. We present results from indoor and outdoor scenarios using directional and fish-eye lenses showing the performance and advantages of this framework.

Vision-based control for mining automation

The mining industry is highly suitable for the application of robotics and automation technology since the work is both arduous and dangerous. Visual servoing is a means of integrating noncontact visual sensing with machine control to augment or replace operator based control. This article describes two of our current mining automation projects in order to demonstrate some, perhaps unusual, applications of visual servoing, and also to illustrate some very real problems with robust computer vision

Is comfort important for optimal use of child restraints?

Suboptimal restraint use, particularly the incorrect use of restraints, is a significant and widespread problem among child vehicle occupants, and increases the risk of injury. Previous research has identified comfort as a potential factor influencing suboptimal restraint use. Both the real comfort experienced by the child and the parent’s perception of the child’s comfort are reported to influence the optimal use of restraints. Problems with real comfort may lead the child to misuse the restraint in their attempt to achieve better comfort whilst parent-perceived discomfort has been reported as a driver for premature graduation and inappropriate restraint choice. However, this work has largely been qualitative. There has been no research that objectively studies either the association between real and parental perceived comfort, or any association between comfort and suboptimal restraint use. One barrier to such studies is the absence of validated tools for quantifying real comfort in children. We aimed to develop methods to examine both real and parent-perceived comfort and examine their effects on suboptimal restraint use. We conducted online parent surveys (n=470) to explore what drives parental perceptions of their child’s comfort in restraint systems (study 1) and used data from field observation studies (n=497) to examine parent-perceived comfort and its relationship with observed restraint use (study 2). We developed methods to measure comfort in children in a laboratory setting (n=14) using video analysis to estimate a Discomfort Avoidance Behaviour (DAB) score, pressure mapping and adapted survey tools to differentiate between comfortable and induced discomfort conditions (study 3). Preliminary analysis of our recent online survey of Australian parents (study 1) indicates that 23% of parents report comfort as a consideration when making a decision to change restraints. Logistic regression modelling of data collected during the field observation study (study 2) revealed that parent-perceived discomfort was not significantly associated with premature graduation. Contrary to expectation, children of parents who reported that their child was comfortable were almost twice as likely to have been incorrectly restrained (p<0.01, 95% CI 1.24 - 2.77). In the laboratory study (study 3) we found our adapted survey tools did not provide a reliable measurement of real comfort among children. However our DAB score was able to differentiate between comfortable and induced discomfort conditions and correlated well with pressure mapping. Our results suggest that while some parents report concern about their child’s comfort, parent-reported comfort levels were not associated with restraint choice. If comfort is important for optimal restraint use, it is likely to be the real comfort of the child rather than that reported by the parent. The method we have developed for studying real comfort can be used in naturalistic studies involving child occupants to further understand this relationship. This work will be of interest to vehicle and child restraint manufacturers interested in improving restraint design for young occupants as well as researchers and other stakeholders interested in reducing the incidence of restraint misuse among children.

The optimal frequency of aquatic physiotherapy for individuals with chronic musculoskeletal pain: a randomised controlled trial

Purpose: To establish whether there was a difference in health-related quality of life (HRQoL) in people with chronic musculoskeletal disorders (PwCMSKD) after participating in a multimodal physiotherapy program (MPP) either two or three sessions a week. Methods: Total of 114 PwCMSKD participated in this prospective randomised controlled trial. An individualised MPP, consisting of exercises for mobility, motor-control, muscle strengthening, cardiovascular training, and health education, was implemented either twice a week (G2: n = 58) or three times a week) (G3: n = 56) for 1 year. Outcomes: HRQoL physical and mental health state (PHS/MHS), Roland Morris disability Questionnaire (RMQ), Neck-Disability-Index (NDI) and Western Ontario and McMaster Universities’ Arthritis Index (WOMAC) were used to measure outcomes of MPP for people with chronic low back pain, chronic neck pain and osteoarthritis, respectively. Measures were taken at baseline, 8 weeks (8 w), 6 months (6 m), and 1 year (1 y) after starting the programme. Results: No statistically significant differences were found between the two groups (G2 and G3), except in NDI at 8 w (−3.34, (CI 95%: −6.94/0.84, p = 0.025 (scale 0–50)). All variables showed improvement reaching the following values (from baseline to 1 y) G2: PHS: 57.72 (baseline: 41.17; (improvement: 16.55%), MHS: 74.51 (baseline: 47.46, 27.05%), HRQoL 0.90 (baseline: 0.72, 18%)), HRQoL-VAS 84.29 (baseline: 58.04, 26.25%), RMQ 4.15 (baseline: 7.85, 15.42%), NDI 3.96 (baseline: 21.87, 35.82%), WOMAC 7.17 (baseline: 25.51, 19.10%). G3: PHS: 58.64 (baseline: 39.75, 18.89%), MHS: 75.50 (baseline: 45.45, (30.05%), HRQoL 0.67 (baseline: 0.88, 21%), HRQoL-VAS 86.91 (baseline: 52.64, 34.27%), RMQ 4.83 (baseline: 8.93, 17.08%), NDI 4.91 (baseline: 23.82, 37.82%), WOMAC 6.35 (baseline: 15.30, 9.32%). Conclusions: No significant differences between the two groups were found in the outcomes of a MPP except in the NDI at 8 weeks, but both groups improved in all variables during the course of 1 year under study.

Experimental studies on the performance of rail joints with modified wheel/railhead contact

Rail joints are provided with a gap to account for thermal movement and to maintain electrical insulation for the control of signals and/or broken rail detection circuits. The gap in the rail joint is regarded as a source of significant problems for the rail industry since it leads to a very short rail service life compared with other track components due to the various, and difficult to predict, failure modes – thus increasing the risk for train operations. Many attempts to improve the life of rail joints have led to a large number of patents around the world; notable attempts include strengthening through larger-sized joint bars, an increased number of bolts and the use of high yield materials. Unfortunately, no design to date has shown the ability to prolong the life of the rail joints to values close to those for continuously welded rail (CWR). This paper reports the results of a fundamental study that has revealed that the wheel contact at the free edge of the railhead is a major problem since it generates a singularity in the contact pressure and railhead stresses. A design was therefore developed using an optimisation framework that prevents wheel contact at the railhead edge. Finite element modelling of the design has shown that the contact pressure and railhead stress singularities are eliminated, thus increasing the potential to work as effectively as a CWR that does not have a geometric gap. An experimental validation of the finite element results is presented through an innovative non-contact measurement of strains. Some practical issues related to grinding rails to the optimal design are also discussed.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Electronic Control of Facial Selection in Additions to Sterically Unbiased Ketones and Olefins

By definition, the two faces of a pi bond are equivalent.1 However, they are rendered nonequivalent in most molecules because of the absence of a plane of symmetry encompassing the double bond and the adjacent substituents. As a result, additions to trigonal centers from the two faces need not be equally facile. Exploiting this stereodifferentiation in a controlled manner represents one of the core problems in organic synthesis. Evidently, the factors which determine such diastereoselection need to be delineated in as much detail as possible.

Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.