Using zero-norm constraint for sparse probability density function estimation

A new sparse kernel probability density function (pdf) estimator based on zero-norm constraint is constructed using the classical Parzen window (PW) estimate as the target function. The so-called zero-norm of the parameters is used in order to achieve enhanced model sparsity, and it is suggested to minimize an approximate function of the zero-norm. It is shown that under certain condition, the kernel weights of the proposed pdf estimator based on the zero-norm approximation can be updated using the multiplicative nonnegative quadratic programming algorithm. Numerical examples are employed to demonstrate the efficacy of the proposed approach.

Scope and constraint in the diagnosis of cluttering: combining two perspectives

A chapter outlining a theoretical position on the definition of the speech language disorder, cluttering.

Kinematical analysis of redundant drive wire mechanisms with velocity constraint

In this paper, we propose a new velocity constraint type for Redundant Drive Wire Mechanisms. The purpose of this paper is to demonstrate that the proposed velocity constraint module can fix the orientation of the movable part and to use the kinematical analysis method to obtain the moving direction of the movable part. First, we discuss the necessity of using this velocity constraint type and the possible applications of the proposed mechanism. Second, we derive the basic equations of a wire mechanism with this constraint type. Next, we present a method of motion analysis on active and passive constraint spaces, which is used to find the moving direction of a movable part. Finally, we apply the above analysis method on a wire mechanism with a velocity constraint module and on a wire mechanism with four double actuator modules. By evaluating the results, we prove the validity of the proposed constraint type.

The angular momentum constraint on climate sensitivity and downward influence in the middle atmosphere

It is shown that under reasonable assumptions, conservation of angular momentum provides a strong constraint on gravity wave drag feedbacks to radiative perturbations in the middle atmosphere. In the time mean, radiatively induced temperature perturbations above a given altitude z cannot induce changes in zonal mean wind and temperature below z through feedbacks in gravity wave drag alone (assuming an unchanged gravity wave source spectrum). Thus, despite the many uncertainties in the parameterization of gravity wave drag, the role of gravity wave drag in middle-atmosphere climate perturbations may be much more limited than its role in climate itself. This constraint limits the possibilities for downward influence from the mesosphere. In order for a gravity wave drag parameterization to respect the momentum constraint and avoid spurious downward influence, any nonzero parameterized momentum flux at a model lid must be deposited within the model domain, and there must be no zonal mean sponge layer. Examples are provided of how violation of these conditions leads to spurious downward influence. For planetary waves, the momentum constraint does not prohibit downward influence, but it limits the mechanisms by which it can occur: in the time mean, downward influence from a radiative perturbation can only arise through changes in reflection and meridional propagation properties of planetary waves.

Pesticide-handling practices of smallholder coffee farmers in Eastern Jamaica

Pesticide use among smallholder coffee producers in Jamaica has been associated with significant occupational health effects. Research on pesticide handling practices, however, has been scarce, especially in eastern Jamaica. This explorative study aims at filling this gap and provides a first basis to develop effective interventions to promote a safer pesticide use. A random sample of 81 coffee farmers was surveyed. The majority of farmers reported to suffer from at least one health symptom associated with pesticide handling, but safety practices were scarcely adopted. There was also the risk that other household members and the wider local community are exposed to pesticides. The lack of training on pesticide management, the role of health services and the cost for protective equipment seemed to be the most significant factors that influence current pesticide handling practices in eastern Jamaica. Further research is recommended to develop a systemic understanding of farmer’s behaviour to provide a more solid basis for the development of future intervention programmes.

The Copenhagen principles on the handling of detainees: implications for the procedural regulation of internment

The Copenhagen Principles on the Handling of Detainees in International Military Operations were released in October 2012 after a five-year long process involving states and certain organizations. The Principles address a number of issues concerning the handling and transfer of detainees. They apply in military operations conducted by states abroad in the context of non-international armed conflicts and peace operations. This article focuses on those principles that address the procedural regulation of internment (ie preventive, security detention), as it is here that the current law is particularly unclear. On the one hand, the treaty provisions applicable in non-international armed conflicts contain no rules on the procedural regulation of internment, in comparison with the law of international armed conflict. On the other hand, the relevant rules under international human rights law (IHRL) appear derogable in such situations. This article demonstrates that the approach taken to this issue in the Copenhagen Principles is one which essentially draws on the procedural rules applicable to civilian internment in the international armed conflicts. These rules adopt standards that are lower than those under IHRL. Reference is then made to other recent practice, which illustrates that the Copenhagen Principles do not apply in a legal vacuum. In particular, two recent judicial developments highlight the continued relevance of human rights law and domestic law, respectively, in regulating detention operations in the context of international military operations. Compliance with the Copenhagen Principles may not, therefore, be sufficient for detention to be lawful.

Conditioning of the weak-constraint variational data assimilation problem for numerical weather prediction

4-Dimensional Variational Data Assimilation (4DVAR) assimilates observations through the minimisation of a least-squares objective function, which is constrained by the model flow. We refer to 4DVAR as strong-constraint 4DVAR (sc4DVAR) in this thesis as it assumes the model is perfect. Relaxing this assumption gives rise to weak-constraint 4DVAR (wc4DVAR), leading to a different minimisation problem with more degrees of freedom. We consider two wc4DVAR formulations in this thesis, the model error formulation and state estimation formulation. The 4DVAR objective function is traditionally solved using gradient-based iterative methods. The principle method used in Numerical Weather Prediction today is the Gauss-Newton approach. This method introduces a linearised `inner-loop' objective function, which upon convergence, updates the solution of the non-linear `outer-loop' objective function. This requires many evaluations of the objective function and its gradient, which emphasises the importance of the Hessian. The eigenvalues and eigenvectors of the Hessian provide insight into the degree of convexity of the objective function, while also indicating the difficulty one may encounter while iterative solving 4DVAR. The condition number of the Hessian is an appropriate measure for the sensitivity of the problem to input data. The condition number can also indicate the rate of convergence and solution accuracy of the minimisation algorithm. This thesis investigates the sensitivity of the solution process minimising both wc4DVAR objective functions to the internal assimilation parameters composing the problem. We gain insight into these sensitivities by bounding the condition number of the Hessians of both objective functions. We also precondition the model error objective function and show improved convergence. We show that both formulations' sensitivities are related to error variance balance, assimilation window length and correlation length-scales using the bounds. We further demonstrate this through numerical experiments on the condition number and data assimilation experiments using linear and non-linear chaotic toy models.