Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Models of Expressive Music Performance: The State of the Art

This contribution gives an overview of the state of the art in the field of computational modeling of expressive music performance. The notion of predictive computational model is briefly discussed, and a number of quantitative models of various aspects of expressive performance are briefly reviewed. Four selected computational models are reviewed in some detail. Their basic principles and assumptions are explained and, wherever possible, empirical evaluations of the models on real performance data are reported. In addition to these models, which focus on general, common principles of performance, currently ongoing research on the formal characterisation of differences in individual performance style are briefly presented.
Graph Based Representations of Density Distribution and Distances for Self-Organizing Maps

The self-organizing map (SOM) is a powerful method for manifold learning because of producing a 2-D spatially ordered quantization of a higher dimensional data space on a rigid lattice and adaptively determining optimal approximation of the (unknown) density distribution of the data. However, a postprocessing visualization scheme is often required to capture the data manifold. A recent visualization scheme CONNvis, which is shown effective for clustering, uses a topology representing graph that shows detailed local data distribution within receptive fields. This brief proposes that this graph representation can be adapted to show local distances. The proposed graphs of local density and local distances provide tools to analyze the correlation between these two information and to merge them in various ways to achieve an advanced visualization. The brief also gives comparisons for several synthetic data sets.
Statistical Wear Leveling for PCM: Protecting Against the Worst Case Without Hurting the Common Case

Phase change memory (PCM) is emerging as a lead alternative to DRAM due to its good combination of speed, density, energy, and reliability. However, PCM can endure far fewer overwrites than DRAM before wearing out. PCM is susceptible to malicious or accidental overwrites which can wear out a frame in a few hundreds of seconds. Previous papers have proposed to randomize periodically the address-to-frame mapping in a memory region. Each randomization involves remapping the region’s memory blocks which incurs significant write overhead. To guarantee reasonable worst-case lifetimes, the papers assume that every write overwrites the same memory block and incur either high write overhead for normal applications (i.e., the common case), or permanent, high hardware overhead (i.e., in all cases). We make the key observation that the overwrite rates of normal applications (i.e., common case) are orders-of-magnitude lower than that of the worst case. However, naively measuring the overwrite rate using brute-force hardware would incur significant complexity and power. Instead, we apply basic statistical sampling to estimate accurately the overwrite rate while requiring a small sampling buffer. Our approach, called statistical wear leveling (SWL), which randomizes address-to-frame mapping on the basis of the estimated overwrite rates instead of write rates. SWL achieves both lower common-case write overhead and lower hardware overhead, and similar, high common-case lifetime as compared to the previous schemes while achieving reasonable worst-case lifetime.
IMPLEMENTATION WITH MULTITHREADING PROCESS USING EMBEDDED SYSTEM 1

In Embedded system based applications, the evolution of multicore architectures offers many performance enhancements like speed, concurrency, real-time implementation support etc. However, design issues like critical section handling, selecting optimal number of threads, racing condition avoidance, concurrent tasks handling etc. needs to be addressed. In this work, these issues are implemented for multicore architecture using openMP tool. Barrier region limitations are removed to exploit concurrency and demonstrated applications include are, (i) array filling multitasking (ii) sorting of number, and (iii) sorting of strings. In all the above examples, the performance of multicore is enhanced compared to single core. Keyword: Multicore, Openmp, Racing, Multithreading, Embedded System.
Cell-specific expression of alpha 1(I) collagen-hGH minigenes in transgenic mice

Sequences within the first intron of the alpha 1(I) collagen gene have been implicated in the regulation of expression of alpha 1(I) collagen- reporter gene constructs in cultured cells. However, the physiological significance of these intronic elements has not been established. We have used in situ hybridization to examine whether a cell-specific pattern of expression of human alpha 1(I) collagen-human growth hormone minigenes exists in transgenic mice. Our results indicate that transgenes which contained 2,300 bp of promoter/5' flanking sequence and an intact first intron were well expressed by fibroblasts in dermis and fascia, whereas transgenes lacking the intronic sequence, +292 to +1440, were not expressed in dermis and poorly expressed in fascia. Analysis of transgene expression in cultured fibroblasts obtained from dermal explants of transgenic animals confirmed the requirement for these intronic sequences in the regulation of the alpha 1(I) collagen gene. In contrast, transgenes with or without the intronic deletion were expressed equally well in tendon and bone, in a manner comparable to the endogenous mouse alpha 1(I) collagen gene, and expression of neither transgene was detected in skeletal muscle or perichondrium. These data support a model in which cis-acting elements in the first intron, and their cognate DNA-binding proteins, mediate transcription of the alpha 1(I) collagen gene in some cells, such as dermal fibroblasts, but not in tendon cells or osteoblasts. Moreover, regions of the gene not included in the sequence, -2300 to +1440, appear to be required for transcription in tissues such as skeletal muscle and perichondrium.
Fast analog design optimization using regression-based modeling and genetic algorithm: A nano-CMOS VCO case study

The mature electronic design automation (EDA) tools and well-defined abstraction-levels for digital circuits have almost automated the digital design process. However, analog circuit design and optimization is still not automated. Custom design of analog circuits and slow analog in SPICE has always needed maximum efforts, skills, design cycle time. This paper presents a novel design flow for constrained optimization of nano-CMOS analog circuits. The proposed analog design flow combines polynomial-regression based models and genetic algorithm for fast optimization. For evaluating the effectiveness of the proposed design flow, power minimization in a 50nm CMOS based current-starved voltage-controlled oscillator (VCO) is carried out, while treating oscillation frequency as a performance constraint. Accurate polynomial-regression based models are developed for power and frequency of the VCO. The goodness-of-fit of the models is evaluated using SSE, RMSE and R2. Using these models, we form a constrained optimization problem which is solved using genetic algorithm. The flow achieved 21.67% power savings, with a constraint of frequency ≥ 100 MHz. To the best of the authors' knowledge, this is the first study which approaches a VCO design problem as a mathematical constrained optimization involving the usage of regression based modeling and genetic algorithm.
The effects of year repetition (redoublement) on the progress of pupils in the first three years of French schooling.

In the French educational system, difficulties which occur in the first years of primary school are perceived to be rarely overcome and to have a negative effect on the child’s future achievement at school. It is therefore important to attempt to identify precursors of failure in the first years of elementary education, both individual ones and contextual ones at the school level. The present study uses a panel of pupils followed for the first two years of compulsory schooling.
Contact force estimation from flexible tactile sensor values considering hysteresis by Gaussian process

Flexible tactile sensors are important elements for facilitating the physical interaction between robots and uncertain environments. For instance, tactile information is used by the robot to grasp objects and interact with humans. A model-based approach is one technique for building a relationship between tactile sensor values and task-relevant information such as force, slip, and temperature. However, it is difficult to create models of flexible tactile sensors for converting sensor signals beforehand due to a nonlinear relation between a contact and the deformations of the flexible form caused by its hysteresis [1]. In contrast, machine learning techniques can be adopted to represent these relationships. For example, Tada et al. [2] proposed a model to acquire the relationship between tactile sensor values and slip vibration using a neural network. The purpose of this study was to develop computational models for learning the association between the force applied to a tactile sensor and the sensor value by compensating for the hysteresis in the sensor. We used the tactile sensor of an iCub fingertip in order to apply our models to cognitive studies. This paper first presents our proposed models that consider a Markov property of taxel (tactile sensor elements) values, and then reports experimental results.
A Necessary and Sufficient Condition for Equality in the Matrix Fisher-Information-Inequality

A necessary and suucient condition for equality in the matrix form of the Fisher-Information inequality is derived. In this technical report we consider the matrix form of the Fisher Information Inequality (FII), which was introduced in 5]. In particular, we provide a necessary and suucient condition for equality in the matrix-FII. We rst introduce a special form of Fisher Information (FI), called the FI with respect to a translation parameter, which does not involve explicitly a parameter. Let f(x) be the density of
Discovery of Deuterated Water in a Young Protoplanetary Disk

We report the first detection of the ground transition of deuterated water at 464 GHz in the young protoplanetary disk surrounding the solar-type protostar DM Tau. The line is observed in absorption against the continuum from the cold dust in the disk midplane, with a line-to-continuum ratio close to unity. The observation implies that deuterated gaseous water is present, with a relatively large abundance (~3 × 10-9), in the outer disk above the midplane, where the density is ~106 cm-3, within a factor of 10, and the temperature is lower than about 25 K. In these conditions, the H2O condensation timescale is much smaller than the DM Tau disk age, and, therefore, water should be fully frozen onto the grain mantles. We suggest that UV photons and/or X-rays sublimate part of the mantles, reinjecting the ices into the gas phase. Even though there is currently no measurement of H2O, we provide arguments that the HDO/H2O ratio should be about 0.01 or larger, which would be hundreds of times larger than the values measured in solar system objects. This suggests the need for strong caution in comparing and linking the HDO/H2O in solar system and star-forming environments.
The 1-d stochastic wave equation driven by a fractional Brownian motion

In this paper, we develop a Young integration theory in dimension 2 which will allow us to solve a non-linear one dimensional wave equation driven by an arbitrary signal whose rectangular increments satisfy some H\"{o}lder regularity conditions, for some H\"older exponent greater than 1/2. This result will be applied to the infinite dimensional fractional Brownian motion.
Liquid Water Content and Droplet Sizing Shadowgraph Measuring System for Wind Turbine Icing Detection

This paper shows that the liquid water content (LWC) and the median volume diameter (MVD) can be derived from the images of water droplets using a shadowgraph imaging system with incoherent LED illumination. Icing on structures, such as a wind turbine, is the result of a combination of LWC and MVD, and other parameters, such as temperature, humidity, and wind speed. Today, LWC and MVD are not commonly measured for wind turbines. Systems for measuring these properties are often expensive or impractical in terms of location or remote reading. The aim of this paper is to gain knowledge about how to design a single instrument based on imaging that has the ability to measure these properties with enough precision and accuracy to detect icing conditions for wind turbines. A method to calculate both the LWC and the MVD from the same images is described in this paper. The size of one droplet is determined by measuring the shadow created by the droplet in background illumination. The concentration is calculated by counting the measured droplets and estimating the volumes in which these droplets can be observed. In this paper, the observation volume is shown to be dependent on the particle size and the signal-to-noise ratio for each measured particle. An expected coefficient of variation of the LWC depending on the droplet size is shown to be 2.4% for droplets 10 μm in diameter and 1.6% for 25-μm droplets. This is based on an error estimation of the laboratory measurements calibrated using a micrometer dot scale.
Ouroboros: Using potential field in unexplored regions to close loops

An autonomous robot requires a map of the environment for many tasks. Yet, in many cases, this map is unavailable and the robot must build one in real-time, in the so-called integrated exploration task. Several integrated exploration approaches adopt some sort of loop-closing strategy combined with an online simultaneous localization and mapping (SLAM) technique. This is important because the robot can reduce the uncertainty about its pose by revisiting known areas. One solution for environment exploration is to use the vector field computed from the numeric solution of a Boundary Value Problem (BVP). This approach is called BVP Path Planner and generates smooth and free of local minima potential fields. However, this planner cannot actively close loops and does not scale well in large scenarios. In this paper we present a technique which performs active loop closure using the BVP Path Planner. Our proposal takes advantage of the potential of unexplored regions, and induces the robot to close loops by placing dynamic barriers at the visited space. The update of the potential field is boosted using a local window charged by a Voronoi diagram of the environment containing global information. We show through experimental results the effectiveness of the technique with a thorough discussion of its characteristics.
Scalable Latent Tree Model and its Application to Health Analytics

We present an integrated approach to structure and parameter estimation in latent tree graphical models, where some nodes are hidden. Our overall approach follows a “divide-and-conquer” strategy that learns models over small groups of variables and iteratively merges into a global solution. The structure learning involves combinatorial operations such as minimum spanning tree construction and local recursive grouping; the parameter learning is based on the method of moments and on tensor decompositions. Our method is guaranteed to correctly recover the unknown tree structure and the model parameters with low sample complexity for the class of linear multivariate latent tree models which includes discrete and Gaussian distributions, and Gaussian mixtures. Our bulk asynchronous parallel algorithm is implemented in parallel using the OpenMP framework and scales logarithmically with the number of variables and linearly with dimensionality of each variable. Our experiments conﬁrm a high degree of efﬁciency and accuracy on large datasets of electronic health records. The proposed algorithm also generates intuitive and clinically meaningful disease hierarchies.
A SYSTEMIC MODEL OF ATM SAFETY: THE INTEGRATED RISK PICTURE

There are many new concepts being developed for future ATM, e.g. conflict detection and resolution systems, new traffic management and airport throughput systems, etc. Each can have its own safety assessment and assurance programme. But the future vision of e.g. 2020, may involve a number of such new tools or systems or concepts. This raises a number of questions: • What is the safety assessment of the overall system? • How might these new elements interact? • Are there negative interactions that can be avoided, or even positive interactions, as yet unplanned into the system design concept, which could yield extra safety? • Where are the strong and weak safety areas in the overall system? • Is the resultant system risk sensitive to the sequence and timing of implementation? These are not easy questions, but deserve an answer. Therefore an Integrated Risk Picture (IRP) is being developed within EUROCONTROL which has as its scope gate-to-gate operations. This development is closely co-ordinated with the FAA within the scope of the FAA/EUROCONTROL Action Plan 15 on Safety. What is being achieved in this paper is the description of the baseline risk picture for 2005 and the risk picture for 2012 (predictive mode for the Single European Sky implementation). Lessons learnt related to practical techniques for risk analysis are provided as well.
Event-Driven Simulation for IEEE 802.11e Optimization

This work provides the specification of a PHY and MAC layers simulator that allows to evaluate the IEEE 802.11e service quality. A detailed state transition diagram is presented along with a description of the related attributes and methods, an identification of the associated events and input variables, and a description of functions for events. For validation purposes, results of the goodput as a function of the signal to interference noise ratio were obtained with an error margin lower than 10%. Higher values are found for the goodput for background and video services, mainly because the frames transmitted in these services are longer than the voice application ones. However, the number of supported users is higher for voice. This simulator will allow for tuning-up several parameters like the ones related to how to use BlockACK, normal ACK, and NO ACK policies.
Oscillatory response function: Towards a parametric model of rhythmic brain activity

Rhythmic brain activity, measured by magnetoencephalography (MEG), is modulated during stimulation and task performance. Here, we introduce an oscillatory response function (ORF) to predict the dynamic suppression–rebound modulation of brain rhythms during a stimulus sequence. We derived a class of parametric models for the ORF in a generalized convolution framework. The model parameters were estimated from MEG data acquired from 10 subjects during bilateral tactile stimulation of fingers (stimulus rates of 4 Hz and 10 Hz in blocks of 0.5, 1, 2, and 4 s). The envelopes of the 17–23 Hz rhythmic activity, computed for sensors above the rolandic region, correlated 25%–43% better with the envelopes predicted by the models than by the stimulus time course (boxcar). A linear model with separate convolution kernels for onset and offset responses gave the best prediction. We studied the generalizability of this model with data from 5 different subjects during a separate bilateral tactile sequence by first identifying neural sources of the 17–23 Hz activity using cortically constrained minimum norm estimates. Both the model and the boxcar predicted strongest modulation in the primary motor cortex. For short‐duration stimulus blocks, the model predicted the envelope of the cortical currents 20% better than the boxcar did. These results suggest that ORFs could concisely describe brain rhythms during different stimuli, tasks, and pathologies. Hum Brain Mapp, 2010. © 2009 Wiley‐Liss, Inc.
Sober-Drive: A smartphone-assisted drowsy driving detection system

Drowsy driving, a combination of sleepiness and driving, has become a worldwide problem that often leads to tragic accidents and outcomes. Existing research findings have shown that the percentage of closure of eyelid (a.k.a PERCLOS) is an effective indicator to evaluate the driver's drowsiness. We present the Sober-Drive system, which leverages PERCLOS for on-vehicle drowsy driving detection using smart phones. Specifically, Sober-Drive is built upon a number of indicators that are discrete-approximated from PERCLOS, blink time and blink rate, and it exploits the Neural Network to classify the eye “open/close” states. We developed a Sober-Drive prototype on Android smart phones, and we conducted extensive real-world experiments to evaluate its performance, the results of which show that Sober-Drive has a high detection rate of more than 90% for drowsy driving behaviors.
Multimodal interface within a simulator of service robotic applications

The use of a multimodal interfaces for human-robot communication is an open issue, with a true market in service robotic applications. This paper describes a service robotic simulator which uses a multimodal interface (audio-video, speech-prosodic communication based) that demonstrates the usefulness of integrating many "modes" of interaction. A typical service robotic architecture is multi-layered: cognitive, deliberative, reactive layers are the most referred terms in literature. The design of each level requires an accurate testing methodology; the system development is thus accelerated and simplified using a simulator. The paradigm we take into account consists of robots and human operators continuously linked to a supervising centre. The operator's natural mode of communication is dialogue-based: so far the system we propose uses a prosody-based visuo-dialogical interface with the robot by means of keywords and prosody extracted from spoken commands. The simulator is based on this paradigm and allows to interact by means of conversational and visual interfaces. The former is composed by: speech recognition, prosody detection, keyword extraction, text to speech conversion; the latter by a visual interface and VRML 3D visualization.
Distances Realized by Sets Covering the Plane*

A proof is given of the (known) result that, if real n-dimensional Euclidean space R” is covered by any n + 1 sets, then at least one of these sets is such that each distance d (0 < d < a)) is realized as the distance between two points of the set. In particular, this result holds if the plane is covered by three sets; but it does not necessarily hold if the plane is covered by six sets. I f each set in a covering of the plane fails to realize the same distance d, say d = 1, and if the sets are either closed or simultaneously divisible into regions (in a sense to be made precise), then at least six sets are needed and seven suffice, and the number of closed sets needed is at least as great as the number simultaneously divisible into regions.
Cost reduction of reliable networks using load balanced routing

The routing based on load balancing and shortest path routing (LB-SPR) was recently introduced, and it was shown to have advantages over the standard shortest path routing (SPR) algorithms: it can support higher guaranteed traffic loads, and it simplifies the resource reservation processes. In this paper, the cost of setting up the reliable network which is resilient to node or link failures is analyzed. In such a network, enough capacity has to be provisioned on all the links for routing the traffic even in the case of a failure. The cost of setting up the reliable network using the shortest path routing (SPR) is compared to the cost of setting up the reliable network using the load balanced shortest path routing (LB-SPR). It is shown that LB-SPR can significantly decrease the network cost.