Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Disclosure, conservatism and the cost of equity capital : a review of the foundation literature

In this review piece, we survey the literature on the cost of equity capital implications of corporate disclosure and conservative accounting policy choice decisions with the principle objective of providing insights into the design and methodological issues, which underlie the empirical investigations. We begin with a review of the analytical studies most typically cited in the empirical research as providing a theoretical foundation. We then turn to consider literature that offers insights into the selection of proxies for each of our points of interest, cost of equity capital, disclosure quality and accounting conservatism. As a final step, we review selected empirical studies to illustrate the relevant evidence found within the literature. Based on our review, we interpret the literature as providing the researcher with only limited direct guidance on the appropriate choice of measure for each of the constructs of interest. Further, we view the literature as raising questions about both the interpretation of empirical findings in the face of measurement concerns and the suitability of certain theoretical arguments to the research setting. Overall, perhaps the message which is most clear is that one of the most controversial and fundamental issues underlying the literature is the issue of the diversifiability or nondiversifiability of information effects.

The cultural and creative industries : a literature review [2nd ed.]

This is a short book which gives an introduction and overview of the literature on the cultural and creative industries. This is a revised version of the 2007 edition, with a new conclusion.

Job satisfaction, stress and burnout associated with haemodialysis nursing : a review of literature

Job dissatisfaction, stress and burnout are linked to high rates of nurses leaving the profession, poor morale and poor patient outcomes. Haemodialysis (HD) nursing is uniquely characterised by the intense-prolonged interaction with patients who require complex technological care. A review of nine papers found that factors affecting job satisfaction were aspects of nursing care, organisational factors and length of time that a nurse has been working in nephrology nursing. Factors affecting job stress and burnout were due to interpersonal relationships with physicians, patient care activities, violence and abuse from patients, organisational factors and a lack of access to ongoing education.

Factors contributing to nurse job satisfaction in the acute hospital setting : a review of recent literature

Aim  To explore and discuss from recent literature the common factors contributing to nurse job satisfaction in the acute hospital setting. Background  Nursing dissatisfaction is linked to high rates of nurses leaving the profession, poor morale, poor patient outcomes and increased financial expenditure. Understanding factors that contribute to job satisfaction could increase nurse retention. Evaluation  A literature search from January 2004 to March 2009 was conducted using the keywords nursing, (dis)satisfaction, job (dis)satisfaction to identify factors contributing to satisfaction for nurses working in acute hospital settings. Key issues  This review identified 44 factors in three clusters (intra-, inter- and extra-personal). Job satisfaction for nurses in acute hospitals can be influenced by a combination of any or all of these factors. Important factors included coping strategies, autonomy, co-worker interaction, direct patient care, organizational policies, resource adequacy and educational opportunities. Conclusions  Research suggests that job satisfaction is a complex and multifactorial phenomenon. Collaboration between individual nurses, their managers and others is crucial to increase nursing satisfaction with their job. Implications for nursing management  Recognition and regular reviewing by nurse managers of factors that contribute to job satisfaction for nurses working in acute care areas is pivotal to the retention of valued staff.

Drug law enforcement : a review of the evaluation literature

This article describes the results of a systematic review of drug law enforcement evaluations. The authors describe the search procedures and document the results in five main categories: international/national interventions (e.g., interdiction and drug seizure), reactive/ directed interventions (e.g., crackdowns, raids, buy-busts, saturation patrol, etc.), proactive/ partnership interventions (e.g., third-party policing, problem-oriented policing, community policing, drug nuisance abatement, etc.), individualized interventions (e.g., arrest referral and diversion), or interventions that used a combination of reactive/directed and proactive/ partnership strategies. Results indicate that proactive interventions involving partnerships between the police and third parties and/or community entities appear to be more effective at reducing both drug and nondrug problems in drug problem places than are reactive/ directed approaches. But the general quality of research in drug law enforcement is poor, the range of interventions that have been evaluated is limited, and more high-quality research is needed across a greater variety of drug interventions.

Learning object dynamics for smooth tracking of moving lip contours

A new technique is proposed for learning the dynamic characteristics of a deformable object, applied in particular to the problem of lip-tracking. Experimental results are given which demonstrate that the use of dynamic models allows the system to track more robustly under adverse conditions and to correct spurious, poorly tracked frames

Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.