425 research outputs found
Comparing Probabilistic Models for Melodic Sequences
Modelling the real world complexity of music is a challenge for machine
learning. We address the task of modeling melodic sequences from the same music
genre. We perform a comparative analysis of two probabilistic models; a
Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional
Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns
descriptive music features, such as underlying chords and typical melody
transitions and dynamics. We assess the models for future prediction and
compare their performance to a VMM, which is the current state of the art in
melody generation. We show that both models perform significantly better than
the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally,
we evaluate the short order statistics of the models, using the
Kullback-Leibler divergence between test sequences and model samples, and show
that our proposed methods match the statistics of the music genre significantly
better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer
Science, vol. 6913, pp. 289-304. Springer (2011
Zero-Shot Hashing via Transferring Supervised Knowledge
Hashing has shown its efficiency and effectiveness in facilitating
large-scale multimedia applications. Supervised knowledge e.g. semantic labels
or pair-wise relationship) associated to data is capable of significantly
improving the quality of hash codes and hash functions. However, confronted
with the rapid growth of newly-emerging concepts and multimedia data on the
Web, existing supervised hashing approaches may easily suffer from the scarcity
and validity of supervised information due to the expensive cost of manual
labelling. In this paper, we propose a novel hashing scheme, termed
\emph{zero-shot hashing} (ZSH), which compresses images of "unseen" categories
to binary codes with hash functions learned from limited training data of
"seen" categories. Specifically, we project independent data labels i.e.
0/1-form label vectors) into semantic embedding space, where semantic
relationships among all the labels can be precisely characterized and thus seen
supervised knowledge can be transferred to unseen classes. Moreover, in order
to cope with the semantic shift problem, we rotate the embedded space to more
suitably align the embedded semantics with the low-level visual feature space,
thereby alleviating the influence of semantic gap. In the meantime, to exert
positive effects on learning high-quality hash functions, we further propose to
preserve local structural property and discrete nature in binary codes.
Besides, we develop an efficient alternating algorithm to solve the ZSH model.
Extensive experiments conducted on various real-life datasets show the superior
zero-shot image retrieval performance of ZSH as compared to several
state-of-the-art hashing methods.Comment: 11 page
How to determine local elastic properties of lipid bilayer membranes from atomic-force-microscope measurements: A theoretical analysis
Measurements with an atomic force microscope (AFM) offer a direct way to
probe elastic properties of lipid bilayer membranes locally: provided the
underlying stress-strain relation is known, material parameters such as surface
tension or bending rigidity may be deduced. In a recent experiment a
pore-spanning membrane was poked with an AFM tip, yielding a linear behavior of
the force-indentation curves. A theoretical model for this case is presented
here which describes these curves in the framework of Helfrich theory. The
linear behavior of the measurements is reproduced if one neglects the influence
of adhesion between tip and membrane. Including it via an adhesion balance
changes the situation significantly: force-distance curves cease to be linear,
hysteresis and nonzero detachment forces can show up. The characteristics of
this rich scenario are discussed in detail in this article.Comment: 14 pages, 9 figures, REVTeX4 style. New version corresponds to the
one accepted by PRE. The result section is restructured: a comparison to
experimental findings is included; the discussion on the influence of
adhesion between AFM tip and membrane is extende
Theoretical study of Oldroyd-b visco-elastic fluid flow through curved pipes with slip effects in polymer flow processing
The characteristics of the flow field of both viscous and viscoelastic fluids passing through a curved pipe with a Navier slip boundary condition have been investigated analytically in the present study. The Oldroyd-B constitutive equation is employed to simulate realistic transport of dilute polymeric solutions in curved channels. In order to linearize the momentum and constitutive equations, a perturbation method is used in which the ratio of radius of cross section to the radius of channel curvature is employed as the perturbation parameter. The intensity of secondary and main flows is mainly affected by the hoop stress and it is demonstrated in the present study that both the Weissenberg number (the ratio of elastic force to viscous force) and slip coefficient play major roles in determining the strengths of both flows. It is also shown that as a result of an increment in slip coefficient, the position of maximum velocity markedly migrates away from the pipe center towards the outer side of curvature. Furthermore, results corresponding to Navier slip scenarios exhibit non-uniform distributions in both the main and lateral components of velocity near the wall which can notably vary from the inner side of curvature to the outer side. The present solution is also important in polymeric flow processing systems because of experimental evidence indicating that the no-slip condition can fail for these flows, which is of relevance to chemical engineers
Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals
Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1~4% (3~12 K) over desert and 1~7% (3~20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5~2% (2~6 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 10~17 K under the most severe conditions
Technology-assisted stroke rehabilitation in Mexico: a pilot randomized trial comparing traditional therapy to circuit training in a Robot/technology-assisted therapy gym
Background Stroke rehabilitation in low- and middle-income countries, such as Mexico, is often hampered by lack of clinical resources and funding. To provide a cost-effective solution for comprehensive post-stroke rehabilitation that can alleviate the need for one-on-one physical or occupational therapy, in lower and upper extremities, we proposed and implemented a technology-assisted rehabilitation gymnasium in Chihuahua, Mexico. The Gymnasium for Robotic Rehabilitation (Robot Gym) consisted of low- and high-tech systems for upper and lower limb rehabilitation. Our hypothesis is that the Robot Gym can provide a cost- and labor-efficient alternative for post-stroke rehabilitation, while being more or as effective as traditional physical and occupational therapy approaches. Methods A typical group of stroke patients was randomly allocated to an intervention (n = 10) or a control group (n = 10). The intervention group received rehabilitation using the devices in the Robot Gym, whereas the control group (n = 10) received time-matched standard care. All of the study subjects were subjected to 24 two-hour therapy sessions over a period of 6 to 8 weeks. Several clinical assessments tests for upper and lower extremities were used to evaluate motor function pre- and post-intervention. A cost analysis was done to compare the cost effectiveness for both therapies. Results No significant differences were observed when comparing the results of the pre-intervention Mini-mental, Brunnstrom Test, and Geriatric Depression Scale Test, showing that both groups were functionally similar prior to the intervention. Although, both training groups were functionally equivalent, they had a significant age difference. The results of all of the upper extremity tests showed an improvement in function in both groups with no statistically significant differences between the groups. The Fugl-Meyer and the 10 Meters Walk lower extremity tests showed greater improvement in the intervention group compared to the control group. On the Time Up and Go Test, no statistically significant differences were observed pre- and post-intervention when comparing the control and the intervention groups. For the 6 Minute Walk Test, both groups presented a statistically significant difference pre- and post-intervention, showing progress in their performance. The robot gym therapy was more cost-effective than the traditional one-to-one therapy used during this study in that it enabled therapist to train up to 1.5 to 6 times more patients for the approximately same cost in the long term. Conclusions The results of this study showed that the patients that received therapy using the Robot Gym had enhanced functionality in the upper extremity tests similar to patients in the control group. In the lower extremity tests, the intervention patients showed more improvement than those subjected to traditional therapy. These results support that the Robot Gym can be as effective as traditional therapy for stroke patients, presenting a more cost- and labor-efficient option for countries with scarce clinical resources and funding. Trial registration ISRCTN98578807
Dynamic fluctuations in ascending heart-to-brain communication under mental stress
Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain-heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between electroencephalogram (EEG) oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain-heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain-heart interplay. The observed heart-to-brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the c band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain-heart level. We conclude that directional brain-heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand
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Illustrating the effect of viscoelastic additives on cavitation and turbulence with X-ray imaging
The effect of viscoelastic additives on the topology and dynamics of the two-phase flow arising within an axisymmetric orifice with a flow path constriction along its main axis has been investigated employing high-flux synchrotron radiation. X-ray Phase Contrast Imaging (XPCI) has been conducted to visualise the cavitating flow of different types of diesel fuel within the orifice. An additised blend containing Quaternary Ammonium Salt (QAS) additives with a concentration of 500 ppm has been comparatively examined against a pure (base) diesel compound. A high-flux, 12 keV X-ray beam has been utilised to obtain time resolved radiographs depicting the vapour extent within the orifice from two views (side and top) with reference to its main axis. Different test cases have been examined for both fuel types and for a range of flow conditions characterised by Reynolds number of 35500 and cavitation numbers (CN) lying in the range 3.0–7.7. It has been established that the behaviour of viscoelastic micelles in the regions of shear flow is not consistent depending on the cavitation regimes encountered. Namely, viscoelastic effects enhance vortical (string) cavitation, whereas hinder cloud cavitation. Furthermore, the use of additised fuel has been demonstrated to suppress the level of turbulence within the orifice
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