Diagnosing total quality management - Part 2

From extensive literature research a total quality management (TQM) model is developed. This model describes the basic elements of the concept of TQM. It also provides the way in which the basic elements can be made operational in practice. Based on this model a quality-diagnostical instrument is developed to establish the actual TQM-situation in an organization. The instrument has been tested in two cases in an existing company and the results look promising for purposes of using the instrument in the process of realizing TQM and 'measuring' and stimulating continuous quality improvement

Pick and Place Without Geometric Object Models

We propose a novel formulation of robotic pick and place as a deep reinforcement learning (RL) problem. Whereas most deep RL approaches to robotic manipulation frame the problem in terms of low level states and actions, we propose a more abstract formulation. In this formulation, actions are target reach poses for the hand and states are a history of such reaches. We show this approach can solve a challenging class of pick-place and regrasping problems where the exact geometry of the objects to be handled is unknown. The only information our method requires is: 1) the sensor perception available to the robot at test time; 2) prior knowledge of the general class of objects for which the system was trained. We evaluate our method using objects belonging to two different categories, mugs and bottles, both in simulation and on real hardware. Results show a major improvement relative to a shape primitives baseline

Molecular variation of Trypanosoma brucei subspecies as revealed by AFLP fingerprinting

Genetic analysis of Trypanosoma spp. depends on the detection of variation between strains. We have used the amplified fragment length polymorphism (AFLP) technique to develop a convenient and reliable method for genetic characterization of Trypanosome (sub)species. AFLP accesses multiple independent sites within the genome and would allow a better definition of the relatedness of different Trypanosome (sub)species. Nine isolates (3 from each T. brucei subspecies) were tested with 40 AFLP primer combinations to identify the most appropriate pairs of restriction endonucleases and selective primers. Primers based on the recognition sequences of EcoRI and BglII were chosen and used to analyse 31 T. brucei isolates. Similarity levels calculated with the Pearson correlation coefficient ranged from 15 to 98%, and clusters were determined using the unweighted pair-group method using arithmetic averages (UPGMA). At the intraspecific level, AFLP fingerprints were grouped by numerical analysis in 2 main clusters, allowing a clear separation of T. b. gambiense (cluster I) from T. b. brucei and T. b. rhodesiense isolates (cluster II). Interspecies evaluation of this customized approach produced heterogeneous AFLP patterns, with unique genetic markers, except for T. evansi and T. equiperdum, which showed identical patterns and clustered together

Conditions for Posterior Contraction in the Sparse Normal Means Problem

The first Bayesian results for the sparse normal means problem were proven for spike-and-slab priors. However, these priors are less convenient from a computational point of view. In the meanwhile, a large number of continuous shrinkage priors has been proposed. Many of these shrinkage priors can be written as a scale mixture of normals, which makes them particularly easy to implement. We propose general conditions on the prior on the local variance in scale mixtures of normals, such that posterior contraction at the minimax rate is assured. The conditions require tails at least as heavy as Laplace, but not too heavy, and a large amount of mass around zero relative to the tails, more so as the sparsity increases. These conditions give some general guidelines for choosing a shrinkage prior for estimation under a nearly black sparsity assumption. We verify these conditions for the class of priors considered by Ghosh and Chakrabarti (2015), which includes the horseshoe and the normal-exponential gamma priors, and for the horseshoe+, the inverse-Gaussian prior, the normal-gamma prior, and the spike-and-slab Lasso, and thus extend the number of shrinkage priors which are known to lead to posterior contraction at the minimax estimation rate