Miracle-dz/UniFAR-FTUs huggingface dataset:
Roving on Phobos: Challenges of the MMX Rover for Space Robotics

This paper presents a small rover for exploration mission dedicated to the moons of Mars, Phobos and Deimos. This project is a collaboration between JAXA for the mother spacecraft, and a cooperative contribution of CNES and DLR to provide a rover payload. This rover will be different in many aspects compared to the existing ones. It will have to drive in a very low gravity with only little power given by the solar arrays. It will also need autonomy in order to achieve a consequent distance during a short mission of 100 days. Apart of the technology demonstration driven mission aspects, the first objective after landing for the rover is to secure the mother spacecraft landing through a characterization of the soil (regolith). Hence, in the nominal rover definition, several payloads are foreseen in order to contribute to the mission of the main spacecraft: to determine the origin of Martian moons.
Generative models for action generation and action understanding

The question of how to build intelligent machines raises the question of how to represent the world to enable intelligent behavior. In nature, this representation relies on the interplay between an organism’s sensory input and motor input. Action-perception loops allow many complex behaviors to arise naturally. In this work, we take these sensorimotor contingencies as an inspiration to build robot systems that can autonomously interact with their environment and with humans. The goal is to pave the way for robot systems that can learn motor control in an unsupervised fashion and relate their own sensorimotor experience to observed human actions. By combining action generation and action understanding we hope to facilitate smooth and intuitive interaction between robots and humans in shared work spaces. To model robot sensorimotor contingencies and human behavior we employ generative models. Since generative models represent a joint distribution over relevant variables, they are flexible enough to cover the range of tasks that we are tackling here. Generative models can represent variables that originate from multiple modalities, model temporal dynamics, incorporate latent variables and represent uncertainty over any variable all of which are features required to model sensorimotor contingencies. By using generative models, we can predict the temporal development of the variables in the future, which is important for intelligent action selection. We present two lines of work. Firstly, we will focus on unsupervised learning of motor control with help of sensorimotor contingencies. Based on Gaussian Process forward models we demonstrate how the robot can execute goal-directed actions with the help of planning techniques or reinforcement learning. Secondly, we present a number of approaches to model human activity, ranging from pure unsupervised motion prediction to including semantic action and affordance labels. Here we employ deep generative models, namely Variational Autoencoders, to model the 3D skeletal pose of humans over time and, if required, include semantic information. These two lines of work are then combined to implement physical human-robot interaction tasks. Our experiments focus on real-time applications, both when it comes to robot experiments and human activity modeling. Since many real-world scenarios do not have access to high-end sensors, we require our models to cope with uncertainty. Additional requirements are data-efficient learning, because of the wear and tear of the robot and human involvement, online employability and operation under safety and compliance constraints. We demonstrate how generative models of sensorimotor contingencies can handle these requirements in our experiments satisfyingly.
The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond

"Applications of multiple imputation have long outgrown the traditional context of dealing with item nonresponse in cross-sectional datasets. Nowadays multiple imputation is also applied to impute missing values in hierarchical datasets, address confidentiality concerns, combine data from different sources, or correct measurement errors in surveys. However, software developments did not keep up with these recent extensions. Most imputation software can only deal with item nonresponse in cross-sectional settings and extensions for hierarchical data - if available at all - are typically limited in scope. Furthermore, to our knowledge no software is currently available for dealing with measurement error using multiple imputation approaches. The R package hmi tries to close some of these gaps. It offers multiple imputation routines in hierarchical settings form any variable types (for example, nominal, ordinal, or continuous variables). It also provides imputation routines for interval data and handles a common measurement error problem in survey data: Biased inferences due to implicit rounding of the reported values. The user-friendly setup which only requires the data and optionally the specification of the analysis model of interest makes the package especially attractive for users less familiar with the peculiarities of multiple imputation. The compatibility with the popular mice package ensures that the rich set of analysis and diagnostic tools and post-imputation commands available in mice can be used easily once the data have been imputed. " (Author's abstract, IAB-Doku) ((en))
Creating a Corpus for Russian Data-to-Text Generation Using Neural Machine Translation and Post-Editing

In this paper, we propose an approach for semi-automatically creating a data-to-text (D2T) corpus for Russian that can be used to learn a D2T natural language generation model. An error analysis of the output of an English-to-Russian neural machine translation system shows that 80% of the automatically translated sentences contain an error and that 53% of all translation errors bear on named entities (NE). We therefore focus on named entities and introduce two post-editing techniques for correcting wrongly translated NEs.
DEEP CONVOLUTIONAL NEURAL NETWORKS FOR MUSIC CLASSIFICATION FROM RAW PCM-ENCODED AUDIO

In recent years, convolutional neural networks (CNNs) have achieved state of the art performance on a variety of large scale image classification tasks. Despite these successes, their use in music classification has remained relatively unexplored. In this work, we present a CNN model that automatically learns relevant features in a supervised fashion. Our model achieves 92.29% classification accuracy on a dataset of 3,529 clips distributed across six musical genres. We also show that the pretrained convolutional layers of our model can accelerate and improve learning on the GTZAN dataset. Moreover, whereas previous work in feature learning for music information retrieval has relied on intermediate representations of audio, such as discrete Fourier transforms and spectrograms, our system learns features and classifies audio directly from PCM-encoded audio samples.
Identifying Temporal Trends Based on Perplexity and Clustering: Are We Looking at Language Change?

In this work we propose a data-driven methodology for identifying temporal trends in a corpus of medieval charters. We have used perplexities derived from RNNs as a distance measure between documents and then, performed clustering on those distances. We argue that perplexities calculated by such language models are representative of temporal trends. The clusters produced using the K-Means algorithm give an insight of the differences in language in different time periods at least partly due to language change. We suggest that the temporal distribution of the individual clusters might provide a more nuanced picture of temporal trends compared to discrete bins, thus providing better results when used in a classification task.
E-CRM applications of soccer teams as a strategic tool : a content analysis of English Premier League and Turkish Super League

Electronic customer relationship management (e-CRM) is a strategic initiative of sport marketing and allows building long-term relationships. This paper discusses the results of content analysis of the websites of the most popular soccer teams in Premier League and Super League (English and Turkish, respectively), carried out to identify the features of electronic customer relationship management on websites. A content analysis of websites was performed, utilizing categories representing a range of e-CRM. Differences between Turkey and England and among soccer clubs based on e-CRM features are identified. The results show that many of soccer teams employ the features of e-CRM strategy. The results of the study indicate that there are slightly differences among teams of Turkish Super League and English Premier League.
Guiding Instability A craft-based approach for modular 3D clay printed masonry screen units

As the field of 3D printing technologies expand, complex materials that require a deeper engagement, due to their more unstable properties, are of increasing interest. Cementitious composites, clays and other ceramic materials are of particular relevance: their potential for fast large-scale fabrication and local availability position these technologies at the forefront of expansion for 3D printing. Despite the extensive benefits inherent to clays, their irregularities and the largely unpredictable deviations that occur when printing from a digital model, currently limit design and architectural-scale applications. However, these deformations could conversely be harnessed as design generators, opening up avenues for both aesthetic and functional exploration. The paper presents an investigation into the inherent material instabilities of the clay 3D printing process for the development of an architectural masonry facade system. Through an iterative process based in craft, a new capacity for material expression and authenticity beyond previous manufacturing capabilities can become actualized.
Advanced D-Partitioning Stability Analysis of Digital Control Systems with Multivariable Parameters

This paper contributes in further advancement of the method of D-Partitioning stability analysis applied to digital control system with multivariable parameters. It also explores the effects of simultaneous system uncertainties by determining graphically regions of stability in the space of the system’s parameters. The Euler's approximation is taken into account and the Bilinear Tustin Transform method is employed as one of the most precise facilities for systems discretization. The interaction between the variable parameters will bring a new light in the graphical solution of the problem of control system stability, where the analysis of control systems with two and three simultaneously variable parameters is taken into consideration. The proposed research is a continuation and further development of the already published author’s work on the advancement of the method of the D-Partitioning stability analysis of digital control systems with variable parameters. The suggested implementation for system’s stability analysis is fundamental for the further advancement of control theory in this area.
Dendritic solidification of binary alloys

The purpose of this seminar is to discuss the thermodynamic and kinetic background for simulation of dendritic growth in binary alloys. The equilibrium and non-equilibrium effects on phase diagram are considered. Theory of homogeneous nucleation is presented. Interface balances are considered by taking into account the curvature effect. Simulation of dendritic growth of Al-7Si alloy is presented, based on quadtree-adaptive cellular automaton algorithm and explicit finite volume method.
Phylogenetic relationships of the Genus Tamarix L . ( Tamaricaceae ) from Iran based on nuclear and plastid DNA sequences

Tamarix L. with almost 54 species is the largest genus of the Tamaricaceae. This study was carried out on the species of Tamarix that growing in Iran. Plastid trnS-trnG sequences were obtained for 16 samples recognized by recent taxonomic treatments from Iran. In addition, we used 13 previously trnS-trnG sequences from GenBank to test the monophyly of Tamarix in Iran. Phylogenetic analysis were conducted using Bayesian inference. In this study we use DNA sequence data to identify species of Tamarix that growing in Iran, and to determine if the molecular data are congruent with the morphological distinctions that currently segregate taxa. We also test congruence of morphologically based sectional classifications and our molecular gene trees. The results indicate that Tamarix species from Iran constituted a monophyletic group. Data analysis indicates the three taxonomic sections based on morphology (Baum 1978) are not supported by the molecular analyses and to determine the evolution of Tamarix use of morphological characteristics coupled with molecular data will be most effective.
Confinated horizontal vortex generator Generador de un vórtice horizontal confinado

Enero-junio 2017 ISSN: 0122-3461 (impreso) 2145-9371 (on line) * Ingeniero Mecánico, Facultad de Ingeniería, Escuela de Ingeniería Mecánica, Grupo de Investigación en Dinámica de Fluidos. Luis.diaz@co­ rreounivalle.edu. co ** Ingeniero Agrícola, Facultad de Ingeniería, Escuela de Ingeniería de Recursos Naturales y del Medio Ambiente, Grupo de Investigación en Di­ námica de Fluidos. gerardo.a. torres@correounivalle.edu. co *** Profesor Asociado, Doctor en Mecánica Teórica, Facultad de Inge­ niería, Escuela de Ingeniería de Recursos Naturales y del Medio Ambien­ te. efraín. del@correounivalle.edu. co. Correspondencia: Efraín del Risco Moreno, Universidad del Valle, Sede Cali calle 13 no 100­00. Teléfono: 3212153 Ext. 119. Luis Fernando Díaz González* Gerardo Andrés Torres Casierra** Efraín del Risco Moreno*** Universidad del Valle (Colombia) ARTÍCULO DE INVESTIGACIÓN / RESEARCH ARTICLE http://dx.doi. org/10.14482/inde.35. 1.8942
FOR STATISTICALLY DOWNSCALING DAILY GCM PRECIPITATION OUTPUTS TO SIMULATE REGIONAL STREAMFLOW 1

This study applied three statistical downscaling methods: (1) bias correction and spatial disaggregation at daily time scale (BCSD_daily); (2) a modified version of BCSD which reverses the order of spatial disaggregation and bias correction (SDBC), and (3) the bias correction and stochastic analog method (BCSA) to downscale general circulation model daily precipitation outputs to the subbasin scale for west-central Florida. Each downscaled climate input dataset was then used in an integrated hydrologic model to examine differences in ability to simulate retrospective streamflow characteristics. Results showed the BCSD_daily method consistently underestimated mean streamflow because the highly spatially correlated small precipitation events produced by this method resulted in overestimation of evapotranspiration. Highly spatially correlated large precipitation events produced by the SDBC method resulted in overestimation of the standard deviation of wet season daily streamflow and the magnitude/frequency of high streamflow events. BCSA showed better performance than the other methods in reproducing spatiotemporal statistics of daily precipitation and streamflow. This study demonstrated differences in statistical downscaling techniques propagate into significant differences in streamflow predictions, and underscores the need to carefully select a downscaling method that reproduces precipitation characteristics important for the hydrologic system under consideration. (KEY TERMS: statistical downscaling; general circulation model (GCM); bias correction; spatiotemporal variability in daily precipitation; hydrologic implications; integrated hydrologic model (IHM). ) Hwang, Syewoon and Wendy D. Graham, 2014. Assessment of Alternative Methods for Statistically Downscaling Daily GCM Precipitation Outputs to Simulate Regional Streamflow. Journal of the American Water Resources Association (JAWRA) 1-23. DOI: 10.1111/jawr.12154
Virtual Muscle Force: Communicating Kinesthetic Forces Through Pseudo-Haptic Feedback and Muscle Input

Natural haptic feedback in virtual reality (VR) is complex andchallenging, due to the intricacy of necessary stimuli and re-spective hardware. Pseudo-haptic feedback aims at providinghaptic feedback without providing actual haptic stimuli butby using other sensory channels (e.g. visual cues) for feed-back. We combine such an approach with the additional inputmodality of muscle activity that is mapped to a virtual force toinfluence the interaction flow. In comparison to existing approaches as well as to no kines-thetic feedback at all the presented solution significantly in-creased immersion, enjoyment as well as the perceived qualityof kinesthetic feedback.
An Unconditionally Stable FDTD Method Using Tetrahedral Cells

The concept of the finite difference time domain method is applied to tetrahedral cells in order to permit its use with structures of complex shapes. Unconditional stability is achieved through the Newmark time discretization of wave equation and the conjugate gradient method with incomplete Cholesky preconditioning provides a fast solver for the system of linear equations to be evaluated every time step. Numerical experiments have shown that there exists an optimum time step value which conducts to an accurate solution with the minimum of two iterations per time step. Keywords– FDTD, FETD, tetrahedral mesh, conjugate gradient
MHD turbulence: a biased review

This review of scaling theories of magnetohydrodynamic (MHD) turbulence aims to put the developments of the last few years in the context of the canonical time line (from Kolmogorov to Iroshnikov–Kraichnan to Goldreich–Sridhar to Boldyrev). It is argued that Beresnyak's (valid) objection that Boldyrev's alignment theory, at least in its original form, violates the Reduced-MHD rescaling symmetry can be reconciled with alignment if the latter is understood as an intermittency effect. Boldyrev's scalings, a version of which is recovered in this interpretation, and the concept of dynamic alignment (equivalently, local 3D anisotropy) are thus an example of a physical theory of intermittency in a turbulent system. The emergence of aligned structures naturally brings into play reconnection physics and thus the theory of MHD turbulence becomes intertwined with the physics of tearing, current-sheet disruption and plasmoid formation. Recent work on these subjects by Loureiro, Mallet et al. is reviewed and it is argued that we may, as a result, finally have a reasonably complete picture of the MHD turbulent cascade (forced, balanced, and in the presence of a strong mean field) all the way to the dissipation scale. This picture appears to reconcile Beresnyak's advocacy of the Kolmogorov scaling of the dissipation cutoff (as $\mathrm {Re}^{3/4}$) with Boldyrev's aligned cascade. It turns out also that these ideas open the door to some progress in understanding MHD turbulence without a mean field – MHD dynamo – whose saturated state is argued to be controlled by reconnection and to contain, at small scales, a tearing-mediated cascade similar to its strong-mean-field counterpart (this is a new result). On the margins of this core narrative, standard weak-MHD-turbulence theory is argued to require some adjustment – and a new scheme for such an adjustment is proposed – to take account of the determining part that a spontaneously emergent 2D condensate plays in mediating the Alfvén-wave cascade from a weakly interacting state to a strongly turbulent (critically balanced) one. This completes the picture of the MHD cascade at large scales. A number of outstanding issues are surveyed: imbalanced turbulence (for which a new, tentative theory is proposed), residual energy, MHD turbulence at subviscous scales, and decaying MHD turbulence (where there has been dramatic progress recently, and reconnection again turned out to feature prominently). Finally, it is argued that the natural direction of research is now away from the fluid MHD theory and into kinetic territory – and then, possibly, back again. The review lays no claim to objectivity or completeness, focusing on topics and views that the author finds most appealing at the present moment.
Title Distinct Features of Auditory Steady-State Responses asCompared to Transient Event-Related Potentials

Transient event-related potentials (ERPs) and steady-state responses (SSRs) have been popularly employed to investigate the function of the human brain, but their relationship still remains a matter of debate. Some researchers believed that SSRs could be explained by the linear summation of successive transient ERPs (superposition hypothesis), while others believed that SSRs were the result of the entrainment of a neural rhythm driven by the periodic repetition of a sensory stimulus (oscillatory entrainment hypothesis). In the present study, taking auditory modality as an example, we aimed to clarify the distinct features of SSRs, evoked by the 40-Hz and 60-Hz periodic auditory stimulation, as compared to transient ERPs, evoked by a single click. We observed that (1) SSRs were mainly generated by phase synchronization, while late latency responses (LLRs) in transient ERPs were mainly generated by power enhancement; (2) scalp topographies of LLRs in transient ERPs were markedly different from those of SSRs; (3) the powers of both 40-Hz and 60-Hz SSRs were significantly correlated, while they were not significantly correlated with the N1 power in transient ERPs; (4) whereas SSRs were dominantly modulated by stimulus intensity, middle latency responses (MLRs) were not significantly modulated by both stimulus intensity and subjective loudness judgment, and LLRs were significantly modulated by subjective loudness judgment even within the same stimulus intensity. All these findings indicated that high-frequency SSRs were different from both MLRs and LLRs in transient ERPs, thus supporting the possibility of oscillatory entrainment hypothesis to the generation of SSRs. Therefore, SSRs could be used to explore distinct neural responses as compared to transient ERPs, and help us reveal novel and reliable neural mechanisms of the human brain. Citation: Zhang L, Peng W, Zhang Z, Hu L (2013) Distinct Features of Auditory Steady-State Responses as Compared to Transient Event-Related Potentials. PLoS ONE 8(7): e69164. doi:10.1371/journal.pone. 0069164 Editor: André Mouraux, Université catholique de Louvain, Belgium Received November 22, 2012; Accepted June 12, 2013; Published July 9, 2013 Copyright: 2013 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: LH was supported by the National Natural Science Foundation of China (31200856), Natural Science Foundation Project of CQ CSTC, and Special Financial Grant from the China Postdoctoral Science Foundation (2012T50755). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: huli@swu.edu. cn