pinecone/core-2020-05-10-deduplication huggingface dataset:
Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network

Identification and extraction of singing voice from within musical mixtures is a key challenge in source separation and machine audition. Recently, deep neural networks (DNN) have been used to estimate 'ideal' binary masks for carefully controlled cocktail party speech separation problems. However, it is not yet known whether these methods are capable of generalizing to the discrimination of voice and non-voice in the context of musical mixtures. Here, we trained a convolutional DNN (of around a billion parameters) to provide probabilistic estimates of the ideal binary mask for separation of vocal sounds from real-world musical mixtures. We contrast our DNN results with more traditional linear methods. Our approach may be useful for automatic removal of vocal sounds from musical mixtures for 'karaoke' type applications
Blind Separation of Surface Electromyographic Mixtures from Two Finger Extensor Muscles

International audienceBlind source separation (BSS) was performed to reduce the crosstalk in the surface electromyografic signals (SEMG) for the muscle force estimation applications. A convolutive mixture model was employed to separate the SEMG signals from two finger extensor muscles using a frequency-domain approach. It was assumed that the tension of each muscle varies independently and the independence of the SEMG was replaced by minimization of the covar-iance of muscle forces represented by integrated SEMG. This covariance was also used to resolve the permutation ambiguity inherent to the frequency-domain BSS. The forces estimated by the reconstructed sources were compared with the measured forces to calculate the crosstalk reduction efficiency. The proposed algorithm was shown to be more effective in frequency domain than an ICA algorithm for extensor muscles crosstalk reduction
Bernoulli’s principle applied to brain fluids: intracranial pressure does not drive cerebral perfusion or CSF flow

In line with the first law of thermodynamics, Bernoulli's principle states that the total energy in a fluid is the same at all points. We applied Bernoulli's principle to understand the relationship between intracranial pressure (ICP) and intracranial fluids. We analyzed simple fluid physics along a tube to describe the interplay between pressure and velocity. Bernoulli's equation demonstrates that a fluid does not flow along a gradient of pressure or velocity; a fluid flows along a gradient of energy from a high-energy region to a low-energy region. A fluid can even flow against a pressure gradient or a velocity gradient. Pressure and velocity represent part of the total energy. Cerebral blood perfusion is not driven by pressure but by energy: the blood flows from high-energy to lower-energy regions. Hydrocephalus is related to increased cerebrospinal fluid (CSF) resistance (i.e., energy transfer) at various points. Identification of the energy transfer within the CSF circuit is important in understanding and treating CSF-related disorders. Bernoulli's principle is not an abstract concept far from clinical practice. We should be aware that pressure is easy to measure, but it does not induce resumption of fluid flow. Even at the bedside, energy is the key to understanding ICP and fluid dynamics
Characterisation of supra- and infratentorial ICP profiles

In pathophysiology and clinical practice, the intracranial pressure (ICP) profiles in the supratentorial and infratentorial compartments are unclear. We know that the pressure within the skull is unevenly distributed, with demonstrated ICP gradients. We recorded and characterised the supra- and infratentorial ICP patterns to understand what drives the transtentorial ICP gradient.A 70-year-old man was operated on for acute cerebellar infarction. One supratentorial probe and one cerebellar probe were implanted. Both signals were recorded concurrently and analysed off-line. We calculated mean ICP, ICP pulse amplitude, respiratory waves, slow waves and the RAP index of supra- and infratentorial ICP signals. Then, we measured transtentorial difference and performed correlation analysis for every index.Supratentorial ICP mean was 8.5 mmHg lower than infratentorial ICP, but the difference lessens for higher values. Both signals across the tentorium showed close correlation. Supra- and infratentorial pulse amplitude, respiratory waves and slow waves also showed a high degree of correlation. The compensatory reserve (RAP) showed good correlation. In this case report, we demonstrate that the mean value of ICP is higher in the posterior fossa, with a strong correlation across the tentorium. All other ICP-derived parameters display a symmetrical profile
BitWorker, a Decentralized Distributed Computing System based on BitTorrent

In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community
DTN routing optimised by human routines: the HURRy protocol

This paper proposes the HURRy (HUman Routines used for Routing) protocol, which infers and benefits from the social behaviour of nodes in disruptive networking environments. HURRy incorporates the contact duration to the information retrieved from historical encounters among neighbours, so that smarter routing decisions can be made. The specification of HURRy is based on the outcomes of a thorough experiment, which highlighted the importance of distinguishing between short and long contacts and deriving mathematical relations in order to optimally prioritize the available routes to a destination. HURRy introduces a novel and more meaningful rating system to evaluate the quality of each contact and overcome the limitations of other routing approaches in social environments.European Commission, Horizon 2020, Grant Agreement number 645124, UMOBIL
Social tagging for e-learning: an approach based on the triplet of learners, learning objects and tags

The emerging of the Web 2.0 has allowed users more interactivity with Web applications. Social tagging has been recognized as an important solution to the description of resources available on the Web. In the context of elearning it may be used as an auxiliary mechanism to the composition of learning object metadata. This paper presents an approach based on the triplet of learners, learning objects and tags for providing the social tagging for e-learning. We performed an experiment with 336 technician students that marked 218 electronic learning objects for about 4,985 times. Although our results have shown that social tagging is a promising practice for e-learning some challenges on how to implement it has to be overcome.International Workshop on Learning Technology for Education in Cloud - LTEC (4. 2015 Maribor
Mini-Orb : A personal indoor climate preference feedback interface

The control of environmental factors in open-office environments, such as lighting and temperature is becoming increasingly automated. This development means that office inhabitants are losing the ability to manually adjust environmental conditions according to their needs. In this paper we describe the design, use and evaluation of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to maintain awareness of environmental factors, report on their own subjectively perceived office comfort levels and see how these compare to group average preferences. The system is complemented by a mobile application, which enables users to see and set the same sensor values and preferences, but using a screen-based interface. We give an account of the system’s design and outline the results of an in-situ trial and user study. Our results show that devices that combine ambient and tangible interaction approaches are well suited to the task of recording indoor climate preferences and afford a rich set of possible interactions that can complement those enabled by more conventional screen-based interfaces
Some remarks on proof-theoretic semantics

This is a tripartite work. The first part is a brief discussion of what it is to be a logical constant, rejecting a view that allows a particular self-referential “constant” • to be such a thing in favour of a view that leads to strong normalisation results. The second part is a commentary on the flattened version of Modus Ponens, and its relationship with rules of type theory. The third part is a commentary on work (joint with Nissim Francez) on “general elimination rules” and harmony, with a retraction of one of the main ideas of that work, i.e. the use of “flattened” general elimination rules for situations with discharge of assumptions. We begin with some general background on general elimination rules.Publisher PDFPeer reviewe
It’s not the way you look, it’s how you move:validating a general scheme for robot affective behaviour

In the emerging world of human-robot interaction, people and robots will work together to achieve joint objectives. This paper discusses the design and validation of a general scheme for creating emotionally expressive behaviours for robots, in order that people might better interpret how a robot collaborator is succeeding or failing in its work. It exemplifies a unified approach to creating robot behaviours for two very different robot forms, based on combinations of four groups of design parameters (approach/avoidance, energy, intensity and fre- quency). 59 people rated video clips of robots performing expressive behaviours both for emotional expressivity on Valence-Arousal-Dominance dimensions, and their judgement of the successfulness of the robots’ work. Results are discussed in terms of the utility of expressive behaviour for facilitating human understanding of robot intentions and the design of cues for basic emotional states
Proxemic Flow: Dynamic Peripheral Floor Visualizations for Revealing and Mediating Large Surface Interactions

Interactive large surfaces have recently become commonplace for interactions in public settings. The fact that people can engage with them and the spectrum of possible interactions, however, often remain invisible and can be confusing or ambiguous to passersby. In this paper, we explore the design of dynamic peripheral floor visualizations for revealing and mediating large surface interactions. Extending earlier work on interactive illuminated floors, we introduce a novel approach for leveraging floor displays in a secondary, assisting role to aid users in interacting with the primary display. We illustrate a series of visualizations with the illuminated floor of the Proxemic Flow system. In particular, we contribute a design space for peripheral floor visualizations that (a) provides peripheral information about tracking fidelity with personal halos, (b) makes interaction zones and borders explicit for easy opt-in and opt-out, and (c) gives cues inviting for spatial movement or possible next interaction steps through wave, trail, and footstep animations. We demonstrate our proposed techniques in the context of a large surface application and discuss important design considerations for assistive floor visualizations
Materializing aaseline views for deviation detection exploratory OLAP

The final publication is available at link.springer.comAlert-raising and deviation detection in OLAP and explora-tory search concerns calling the user’s attention to variations and non-uniform data distributions, or directing the user to the most interesting exploration of the data. In this paper, we are interested in the ability of a data warehouse to monitor continuously new data, and to update accordingly a particular type of materialized views recording statistics, called baselines. It should be possible to detect deviations at various levels of aggregation, and baselines should be fully integrated into the database. We propose Multi-level Baseline Materialized Views (BMV), including the mechanisms to build, refresh and detect deviations. We also propose an incremental approach and formula for refreshing baselines efficiently. An experimental setup proves the concept and shows its efficiency.Peer ReviewedPostprint (author's final draft
Binary Shapelet Transform for Multiclass Time Series Classification

Shapelets have recently been proposed as a new primitive for time series classification. Shapelets are subseries of series that best split the data into its classes. In the original research, shapelets were found recursively within a decision tree through enumeration of the search space. Subsequent research indicated that using shapelets as the basis for transforming datasets leads to more accurate classifiers. Both these approaches evaluate how well a shapelet splits all the classes. However, often a shapelet is most useful in distinguishing between members of the class of the series it was drawn from against all others. To assess this conjecture, we evaluate a one vs all encoding scheme. This technique simplifies the quality assessment calculations, speeds up the execution through facilitating more frequent early abandon and increases accuracy for multi-class problems. We also propose an alternative shapelet evaluation scheme which we demonstrate significantly speeds up the full search
HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values

We propose an efficient algorithm, called HI-Tree, for mining high influence patterns for an incremental dataset. In traditional pattern mining, one would find the complete set of patterns and then apply a post-pruning step to it. The size of the complete mining results is typically prohibitively large, despite the fact that only a small percentage of high utility patterns are interesting. Thus it is inefficient to wait for the mining algorithm to complete and then apply feature selection to post-process the large number of resulting patterns. Instead of generating the complete set of frequent patterns we are able to directly mine patterns with high utility values in an incremental manner. In this paper we propose a novel utility measure called an influence factor using the concepts of external utility and internal utility of an item. The influence factor for an item takes into consideration its connectivity with its neighborhood as well as its importance within a transaction. The measure is especially useful in problem domains utilizing network or interaction characteristics amongst items such as in a social network or web click-stream data. We compared our technique against state of the art incremental mining techniques and show that our technique has better rule generation and runtime performance
Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the
main causes of premature death. These facts reveal the centrality of one`s daily
habits, and how important it is the early diagnosis of these kind of illnesses, not
only to the patients themselves, but also to the society in general. Therefore, this
work will focus on the development of a diagnosis support system to these kind
of maladies, built under a formal framework based on Logic Programming, in
terms of its knowledge representation and reasoning procedures, complemented
with an approach to computing grounded on Artificial Neural Networks.FCT -Fundação para a Ciência e a Tecnologi
An economic insight into additive manufacturing system implementation

With an ever growing diffusion of Additive Manufacturing (AM) system in industrial and commercial level, as well as the direct and indirect dynamics which are being introduced resulting from its inclusion as a possible production technology on companies’ portfolio, the need to reconfigure production system and adapt the production strategy becomes even more relevant than before. There are several studies which have emphasized on the importance of a paradigm shift in order to exploit advantages of AM, not only considering changes within design and functionality of the product, but also concerning AM’s impact on the entire value chain (re)configuration. Thus, it is of crucial importance to take into consideration that for this shift to be feasible and manageable, there is a need to include both technical and managerial aspects of manufacturing. This work proposes an economic insight in order to provide a guideline for the proper evaluation of AM system implementation. © IFIP International Federation for Information Processing 2015
Elastic Recoil Detection Analysis

International audienceAmong the family of Ion Beam Analysis techniques for material characterization, Elastic Recoil Detection Analysis (ERDA) exploits the spectroscopy of recoil nuclei moving under the impact of the ions of the beam. This technique is well suited to light elements profiling, especially for hydrogen measurements which can be performed with usual helium-4 beams available in most facilities. This chapter presents an overview of ERDA main features and focuses on a selection of recent papers dealing with hydrogen measurements in materials for miscellaneous applications, divided into four sections: metals, ceramics, minerals, and thin films
Multiwavelength Studies of Young OB Associations

We discuss how contemporary multiwavelength observations of young
OB-dominated clusters address long-standing astrophysical questions: Do
clusters form rapidly or slowly with an age spread? When do clusters expand and
disperse to constitute the field star population? Do rich clusters form by
amalgamation of smaller subclusters? What is the pattern and duration of
cluster formation in massive star forming regions (MSFRs)? Past observational
difficulties in obtaining good stellar censuses of MSFRs have been alleviated
in recent studies that combine X-ray and infrared surveys to obtain rich,
though still incomplete, censuses of young stars in MSFRs. We describe here one
of these efforts, the MYStIX project, that produced a catalog of 31,784
probable members of 20 MSFRs. We find that age spread within clusters are real
in the sense that the stars in the core formed after the cluster halo. Cluster
expansion is seen in the ensemble of (sub)clusters, and older dispersing
populations are found across MSFRs. Direct evidence for subcluster merging is
still unconvincing. Long-lived, asynchronous star formation is pervasive across
MSFRs.Comment: 22 pages, 9 figures. To appear in "The Origin of Stellar Clusters",
  edited by Steven Stahler, Springer, 2017, in pres
Boundary Controlled Iterated Function Systems

International audienceBoundary Controlled Iterated Function Systems is a new layer of control over traditional (linear) IFS, allowing creation of a wide variety of shapes. In this work, we demonstrate how subdivision schemes may be generated by means of Boundary Controlled Iterated Function Systems, as well as how we may go beyond the traditional subdivision schemes to create free-form fractal shapes. BC-IFS is a powerful tool allowing creation of an object with a prescribed topology (e.g. surface patch) independent of its geometrical texture. We also show how to impose constraints on the IFS transformations to guarantee the production of smooth shapes. Objects modeled through Computer Aided Geometric Design (CAGD) systems are often inspired by standard machining processes. However, other types of objects, such as objects with a porous structure or with a rough surface, may be interesting to create: porous structures can be used for their lighter weight while maintaining satisfactory mechanical properties, rough surfaces can be used for acoustic absorption. Fractal geometry is a relatively new branch of mathematics that studies complex objects of non-integer dimensions. Because of their specific physica
On a new conformal functional for simplicial surfaces

We introduce a smooth quadratic conformal functional and its weighted version
$$W_2=\sum_e \beta^2(e)\quad W_{2,w}=\sum_e (n_i+n_j)\beta^2(e),$$ where
$\beta(e)$ is the extrinsic intersection angle of the circumcircles of the
triangles of the mesh sharing the edge $e=(ij)$ and $n_i$ is the valence of
vertex $i$. Besides minimizing the squared local conformal discrete Willmore
energy $W$ this functional also minimizes local differences of the angles
$\beta$. We investigate the minimizers of this functionals for simplicial
spheres and simplicial surfaces of nontrivial topology. Several remarkable
facts are observed. In particular for most of randomly generated simplicial
polyhedra the minimizers of $W_2$ and $W_{2,w}$ are inscribed polyhedra. We
demonstrate also some applications in geometry processing, for example, a
conformal deformation of surfaces to the round sphere. A partial theoretical
explanation through quadratic optimization theory of some observed phenomena is
presented.Comment: 14 pages, 8 figures, to appear in the proceedings of "Curves and
  Surfaces, 8th International Conference", June 201
TopCom: Index for Shortest Distance Query in Directed Graph

Finding shortest distance between two vertices in a graph is an important problem due to its numerous applications in diverse domains, including geo-spatial databases, social network analysis, and information retrieval. Classical algorithms (such as, Dijkstra) solve this problem in polynomial time, but these algorithms cannot provide real-time response for a large number of bursty queries on a large graph. So, indexing based solutions that pre-process the graph for efficiently answering (exactly or approximately) a large number of distance queries in real-time are becoming increasingly popular. Existing solutions have varying performance in terms of index size, index building time, query time, and accuracy. In this work, we propose TopCom, a novel indexing-based solution for exactly answering distance queries in a directed acyclic graph (DAG). Our experiments with two of the existing state-of-the-art methods (IS-Label and TreeMap) show the superiority of TopCom over these two methods considering scalability and query time
An Evaluation of Diversification Techniques

Diversification is a method of improving user satisfaction by increasing the variety of information shown to user. Due to the lack of a precise definition of information variety, many diversification techniques have been proposed. These techniques, however, have been rarely compared and analyzed under the same setting, rendering a ‘right’ choice for a particular application very difficult. Addressing this problem, this paper presents a benchmark that offers a comprehensive empirical study on the performance comparison of diversification. Specifically, we integrate several state-of-the-art diversification algorithms in a comparable manner, and measure distinct characteristics of these algorithms with various settings. We then provide in-depth analysis of the benchmark results, obtained by using both real data and synthetic data. We believe that the findings from the benchmark will serve as a practical guideline for potential applications.Full Tex