Deciphering the performance hints hidden in J. S. Bach’s quaver beams

Bach often beamed his quavers beyond the beat-unit indicated by the time-signature, as if to indicate the way he perceived, phrased or articulated a musical line. In my previous study in 2011 I demonstrated the significance for both performers and editors of critical editions of quaver beaming against a broader background of Bach’s notational practice. In this article, I go one step further and demonstrate that Bach’s quaver beams reflect how Bach responded to his pieces in composition and performance, which sheds light on how he engaged with and perceived his music from motivic to structural levels. This enquiry has never before been pursued thoroughly and it promises to uncover the ideas that guided his notational practice as well as his spontaneous responses to the challenges he faced while writing out his music on paper

Using the hidden Markov model to capture quality of care in Lombardy geriatric wards

Quality of care is an important aspect of healthcare monitoring, which is used to ensure that the healthcare system is delivering care of the highest standard. With populations growing older there is an increased urgency in making sure that the healthcare delivered is of the highest standard. Healthcare providers are under increased pressure to ensure that this is the case with public and government demand expecting a healthcare system of the highest quality. Modelling quality of care is difficult to measure due to the many ways of defining it. This paper introduces a potential model which could be used to take quality of care into account when modelling length of stay. The Coxian phase-type distribution is used to model length of stay and the associated quality of care incorporated into the Coxian using a Hidden Markov model. Covariates are also introduced to determine their impact on the hidden level to find out what potentially can affect quality of care. This model is applied to geriatic patient data from the Lombardy region of Italy. The results obtained highlighted that bed numbers and the type of hospital (public or private) can have an effect on the quality of care delivered.

Hidden Markov Models With Set-Valued Parameters

Hidden Markov models (HMMs) are widely used probabilistic models of sequential data. As with other probabilistic models, they require the specification of local conditional probability distributions, whose assessment can be too difficult and error-prone, especially when data are scarce or costly to acquire. The imprecise HMM (iHMM) generalizes HMMs by allowing the quantification to be done by sets of, instead of single, probability distributions. iHMMs have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. In this paper, we consider iHMMs under the strong independence interpretation, for which we develop efficient inference algorithms to address standard HMM usage such as the computation of likelihoods and most probable explanations, as well as performing filtering and predictive inference. Experiments with real data show that iHMMs produce more reliable inferences without compromising the computational efficiency.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Diabetes Distress: Understanding the Hidden Struggles of Living with Diabetes and Exploring Intervention Strategies

Diabetes Distress is a rational emotional response to the threat of a life-changing illness. Distinct from depression, it is rooted in the demands of diabetes management and is a product of psychological adjustment. Diabetes distress has been found to be significantly associated with HbA1c and self-care, which demonstrates its clinical use in treatment outcomes. Interpersonal factors such as perceived support and protectiveness of partners significantly contribute to elevated distress, suggesting that these are valued areas of focus for interventions. Pioneering large-scale research, DAWN2, gives voices to the families of those with diabetes and reaffirms the need to consider psychosocial factors in routine diabetes care. Structured diabetes education programmes are the most widely used in helping individuals cope with diabetes, but they fail to consider the psychological or interpersonal aspects of diabetes management. Psycho-educational approaches are found to be effective in reducing diabetes distress while also improving HbA1c. Certain limitations in the current literature are discussed, along with future directions. Of utmost importance is the need for health practitioners, irrespective of background, to demonstrate an understanding of diabetes distress and actively engage in discussion with individuals struggling to cope with diabetes; to normalize this and integrate it into routine diabetes practice.

Land deed between Samuel Howell and Calvin Spencer

This document is a land deed between Samuel Howell and Calvin Spencer, sealed and delivered in the presence of Nicholas Powers and Holden Wade.

Poéticas do testemunho em Maurice Blanchot e Samuel Beckett : o dom da literatura

Tese de doutoramento, Estudos da Literatura e da Cultura (Estudos Comparatistas), Universidade de Lisboa, Faculdade de Letras, 2014

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.