Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly Supervised Construction of ASR Systems with Massive Video Data

Building Automatic Speech Recognition (ASR) systems from scratch is significantly challenging, mostly due to the time-consuming and financially-expensive process of annotating a large amount of audio data with transcripts. Although several unsupervised pre-training models have been proposed, applying such models directly might still be sub-optimal if more labeled, training data could be obtained without a large cost. In this paper, we present a weakly supervised framework for constructing ASR systems with massive video data. As videos often contain human-speech audios aligned with subtitles, we consider videos as an important knowledge source, and propose an effective approach to extract high-quality audios aligned with transcripts from videos based on Optical Character Recognition (OCR). The underlying ASR model can be fine-tuned to fit any domain-specific target training datasets after weakly supervised pre-training. Extensive experiments show that our framework can easily produce state-of-the-art results on six public datasets for Mandarin speech recognition.
Personalizable Groupware : Accomodating Individual Roles and Group Differences

For groupware to be considered successful, it must be usable and acceptable by most, if not all, members of the group. Yet the differences present between group members—their varying roles, needs, skills—and the differences between groups as a whole are a serious obstacle to achieving uniform acceptance of the groupware product, especially when the product treats all people and groups identically. This paper raises several consequences of not accommodating individual differences, and then offers a possible solution to the problem. First, instances of groupware failure are described: the inability of the group to reach a critical mass; the unequal accessibility of the groupware by participants; the failure to accommodate the different roles participants may play; the failure to balance the work done against the benefits received; and the failure of groupware to evolve with the needs of the group. Second, the notion of personalizable groupware is proposed, defined as a system whose behaviour can be altered to match the particular needs of group participants and of each group as a whole. Finally, the paper presents SHARE, a working example of personalizable groupware. SHARE is a shared screen system that offers its users a flexible choice of floor control models to help them mediate their interactions with the shared application.
Characterization of density oscillations in confined and degenerate Fermi gases

Friedel oscillations appear in density of Fermi gases due to Pauli exclusion principle and translational symmetry breaking nearby a defect or impurity. In confined Fermi gases, this symmetry breaking occurs also near to boundaries. Here, density oscillations of a degenerate and confined Fermi gas are considered and characterized. True nature of density oscillations are represented by analytical formulas for degenerate conditions. Analytical characterization is first done for completely degenerate case, then temperature effects are also incorporated with a finer approximation. Envelope functions defining the upper and lower bounds of these oscillations are determined. It is shown that the errors of obtained expressions are negligible as long as the system is degenerate. Numbers, amplitudes, averages and spatial coordinates of oscillations are also given by analytical expressions. The results may be helpful to efficiently predict and easily calculate the oscillations in density and density-dependent properties of confined electrons at nanoscale.
The GALFA-H i Survey Data Release 2

We present the Galactic Arecibo L-Band Feed Array H i (GALFA-H i) survey data release 2 (DR2). The survey covers the 21 cm hyperfine transition of Galactic H i from −650 to 650 , with 0.184 channel spacing, 4′ angular resolution, and 150 mK rms noise per 1 velocity channel. DR2 covers the entirety of the sky available from the William E. Gordon 305 m antenna at Arecibo, from decl. −1°17′ to decl. + 37°57′ across all R.A. : 4 steradians or 32% of the sky. DR2 differs in a number of ways from data release 1, which was released in 2011. DR2 is built from a largely separate set of observations from DR1, which were taken in a much more consistent mode. This consistency, coupled with more careful attention to systematics and more advanced data reduction algorithms, leads to a much higher-quality DR2 data product. We present three data sets for public use: H i data cubes, far-sidelobe stray-radiation-corrected column density maps, and results of the Rolling Hough Transform linear feature detection algorithm.
An elementary approach to homological algebra, by L. R. Vermani. Pp. 315. £59.99. 2003. ISBN 1 58488 400 2 (Chapman & Hall/CRC).

vectors in A are those with the smallest (non-zero) squared length, iV(A), and the volume of A, vol (A), is the volume of the hyper-parallelipiped spanned by e\, . , e„. Centring non-overlapping spheres at the points in A gives a sphere packing whose density turns out to be proportional to the square root of the (modified) Hermite constant y* (A) = N (A)" / vol (A). Extreme lattices are those giving local maxima, necessarily rational, of y*; among these is the extreme lattice (or lattices) with the global maximum value of y*. Martinet organises his account of extreme lattices by isolating two key properties perfection and eutaxy which the set of minimal vectors, M, of an extreme lattice necessarily possesses; these follow from equating an appropriate derivative of y* to 0. In linear algebra parlance, perfection means that every linear functional on the set of non-symmetric matrices is a linear combination of maps of the form A -» A(x) JC for x in M; eutaxy means that the trace functional is a linear combination of such maps with positive coefficients. Up to equivalence, there are only finitely many perfect (respectively, eutactic) lattices. Martinet gives the classification details for n < 7 (respectively n < 5) first by using bare hands and then via the Voronoi algorithm: the number of perfect lattices for 1 < n < 1 is 1,1,1,2, 3,7, 33. En route he introduces the key families of lattices that have been constructed using algebraic techniques of gradually increasing sophistication: these include root lattices, those associated with the names of Coxeter, Todd, Barnes, Craig and Leech, Conway and Sloane's laminated lattices, Venkov's strongly perfect lattices and lattices that arise as modules over carefully chosen subrings of appropriate algebras with involution. Between them, these families definitely contain the critical lattices for n < 8 and are thought to contain the critical lattices for 9 < n < 24, but the subject is full of quirks. Not only are some of the algebraic details esoteric but the capriciousness of the results obtained is bizarre: for example all perfect lattices for n < 6 belong to the families above, for n = 7 only 9 out of 33 do and, for n = 8 where there are at least 10916 perfect lattices, classification becomes intractable. Furthermore, while laminated lattices look critical for 1 < n < 10 and for 14 < n < 26, they definitely are not for 11 < n < 13 !
Indirect Representation and the Lando Principles. An Analysis of Some Problem Areas From the Perspective of English Law

The unpublished second report of the Lando Commission on The Principles of European Contract Law ('the Principles' or 'PECL') contains an important recent attempt to harmonise the laws of agency of European jurisdictions. Chapter 3 of the Principles deals with 'Authority of Agents'. Following the civil law model, Article 3:102 PECL distinguishes between direct and indirect representation. Direct representation exists where an agent acts 'in the name of' a principal (Art. 3:102(1) PECL). If the agent acts within the scope of his authority (real or apparent), his acts bind the principal and third party directly; the agent drops out. Indirect representation covers two types of case in which a principal enlists the assistance of an intermediary to act for him in transactions with third parties (Art. 3:102(2) PECL). The first can be termed 'undisclosed agency'. In these cases, the principal confers authority on the intermediary to create privity between him (the principal) and third parties. As it happens, however, the third party neither knows nor has reason to know that the intermediary acts as an agent. The second category of indirect representation can for convenience be termed 'commission agency'. In this case, by contrast, the principal does not confer authority on the intermediary to create privity of contract between him (the principal) and third parties. The intermediary is to act 'in his own name': he is to contract with third parties in a personal capacity. In both cases of indirect representation, intermediary and third party are bound to each other; principal and third party are not (Art. 3:301 PECL). Even so, in two situations the principal is entitled to exercise against the third party the rights that are acquired on his behalf by the intermediary: if the intermediary goes bankrupt or is guilty of a fundamental non-performance of his duties to the principal (Art. 3:302 PECL). The third party is entitled, in similar circumstances, to exercise against the principal the rights that the third party has against the intermediary (Art. 3:303 PECL).
The Impact of Adverse Weather and Climate on the Width of European Beech (Fagus sylvatica L.) Tree Rings in Southeastern Europe

European beech (Fagus sylvatica L.) is the most important deciduous tree species in Europe. According to different climate scenarios, there is a relatively high probability of a massive decline in and loss of beech forests in southern Europe and in the southern part of central Europe. Thus, the authors of this study explored the dynamics of tree diameter increments and the influence of extremely dry years on the width of tree rings. This study used dendroecological methods to analyze the growth and diameter increments of European beech trees at locations in Serbia and the Republic of Srpska. The sampling was conducted along the vertical distribution of beech forests, at five sites at the lower limit of the distribution, at five optimal sites of the distribution, and at five sites at the upper limit of the distribution. Long-term analyses indicate that dry conditions during a growing season can reduce tree-ring width, but a reduction in tree growth can be expected as a result of more than one season of unfavorable conditions. Low temperatures in autumn and winter and prolonged winters can strongly affect upcoming vegetation and reduce tree development even under normal thermal conditions during a growing season.
Perimenopause: the complex endocrinology of the menopausal transition.

I. Introduction II. Defining the Perimenopause III. Classic Studies of the Perimenopause A. Historical studies B. Early reports of women’s experiences in the perimenopause C. Early prospective menstrual cycle interval and basal temperature documentation IV. Prospective Epidemiological Studies of the Perimenopause A. Manitoba Project on Women and Their Health in the Middle Years B. Massachusetts Women’s Health Study C. Kuopio Osteoporosis Risk Factor and Prevention (OSTPRE) Study V. Systematic Studies of the Endocrinology of the Perimenopause A. Cross-sectional (single-cycle) hormonal studies in the perimenopause B. Prospective ovarian hormonal levels in the perimenopause VI. Histological Studies of Ovarian Changes Across the Lifespan VII. Physiological Studies of Changing Ovarian Hormones in Women in Their Forties and Fifties A. Folliculogenesis and ovarian hyperstimulation for in vitro fertilization (IVF) B. Inhibin physiology in women over forty VIII. Hypotheses to Explain Perimenopausal Endocrinology A.
ALGORITHM DESIGN FOR APPROXIMATION FOR BOTH HARDWARE AND SOFTWARE LEVEL

This paper presents a generalized recursive formula to obtain orthogonal approximation of DCT where roughly DCT of length might be produced from some DCTs of length at the cost of additions for input preprocessing. Many of the existing computations for approximation within the DCT target just the DCT of small transform measures and most of them are non-orthogonal. Approximation of discrete cosine transform (DCT) is helpful for reducing its computational complexity without major effect on its coding performance. We perform recursive sparse matrix decomposition and use the symmetries of DCT basis vectors for deriving the suggested approximation formula. Suggested formula is extremely scalable for hardware furthermore to software implementation of DCT of greater measures, plus it will make technique existing approximation of 8-point DCT to obtain approximate DCT connected getting an electrical two length, . We show the suggested approximation of DCT provides comparable or better image and video compression performance compared to existing approximation techniques. It's proven that suggested formula involves lower arithmetic complexity in comparison while using the other existing approximation computations. We've presented an entirely scalable reconfigurable parallel architecture for the computation of approximate DCT while using suggested formula. One distinctively interesting feature within the suggested design is it might be configured for the computation in the 32-point DCT or parallel computation of two 16-point DCTs or four 8-point DCTs obtaining a marginal control overhead. The suggested architecture can be found to provide several positive aspects in relation to hardware complexity, regularity and modularity. Experimental results acquired from FPGA implementation show the benefit of the suggested method.
Thrombomodulin

The active role played by the endothelial cell in the maintenance of the hemostatic balance has come into focus only in recent years. A major component on the endothelial surface in this regard is the thrombin receptor, thrombomodulin (TM). This receptor serves to convert thrombin from a procoagulant protein into the activator for protein C. Once converted to activated protein C (APC), this protein serves as a major anticoagulant in blood through its ability to inactivate the activated cofactors of the coagulation cascade, Factors Va and VIII a . 3 Recent studies indicate that the protein C anticoagulant pathway may also be involved in other host defense systems. A complete description of the protein C anticoagulant pathway is beyond the scope of this report and can be found in several recent reviews. Only those features of protein C structure and function required for an understanding of TM function will be discussed in this presentation.
Global adaptive stabilization for high‐order uncertain time‐varying nonlinear systems with time‐delays

This paper focuses on the adaptive stabilization problem for a class of high‐order nonlinear systems with time‐varying uncertainties and unknown time‐delays. Time‐varying uncertain parameters are compensated by combining a function gain with traditional adaptive technique, and unknown multiple time‐delays are manipulated by the delicate choice of an appropriate Lyapunov function. With the help of homogeneous domination idea and recursive design, a continuous adaptive state‐feedback controller is designed to guarantee that resulting closed‐loop systems are globally uniformly stable and original system states converge to zero. The effectiveness of the proposed control scheme is illustrated by the stabilization of delayed neural network systems. Copyright © 2016 John Wiley & Sons, Ltd.
Jacobian-based control of soft robots for manipulation using implicit surface models

Soft robot hands offer numerous advantages over rigid ones for manipulation, including robustness and safety. Yet, compared to rigid robots, soft robots are characterized by continuous mechanics, and finite-element approximations with many degrees of freedom present a significant obstacle for modern control approaches. The central question my thesis explores is whether we can capture the benefits of soft robot hands with relatively simple dynamical models. Specifically, we demonstrate a very simple model of a 2D soft manipulator that uses pulleys and cables to model deformable surfaces. This model captures much of the qualitative behavior of soft membranes, while also proving amenable to modern control techniques. We validate this model physically using a hardware set-up. We then demonstrate a simple quasi-static Jacobian controller which solves a second-order cone program to achieve the task of in-hand object repositioning. Thesis Supervisor: Russ Tedrake Title: Professor
InstaHide: Instance-hiding Schemes for Private Distributed Learning

Mixup. See Section 2. Mixup can improve both generalization and adversarial robustness (Verma et al., 2019). It has also been adapted to various learning tasks, including semi-supervised data augmentation (Berthelot et al., 2019), unsupervised image synthesis (Beckham et al., 2019), and adversarial defense at the inference stage (Pang et al., 2019). Recently, (Fu et al., 2019) combined Mixup with model aggregation to defend against inversion attack, and (Liu et al., 2019) proposed a novel method using Mixup for on-cloud privacy-preserving inference. Differential privacy. Differential privacy for deep learning involves controlling privacy leakage by adding noise to the learning pipeline. If the noise is drawn from certain distributions, say Gaussian or Laplace, it is possible to provide guarantees of privacy (Dwork et al., 2006; Dwork & Roth, 2014). Applying differential privacy techniques to distributed deep learning is non-trivial. Shokri and Shmatikov (Shokri & Shmatikov, 2015) proposed a distributed learning scheme by directly adding noise to the shared gradients. However, the amount of privacy guaranteed drops with the number of training epochs and the size of shared parameters. DPSGD (Abadi et al., 2016) was proposed to dynamically keep track of privacy spending based on the composition theorem (Dwork, 2009). However, it still leads to an accuracy drop of about 20% on CIFAR-10 dataset. Also, to control privacy leakage, DPSGD has to start with a model pre-trained using nonprivate labeled data, and then carefully fine-tunes a few layers using private data. Privacy using cryptographic protocols. In distributed learning setting with multiple data participants, it is possible for the participants to jointly train a model over their private inputs by employing techniques like homomorphic encryption (Gentry, 2009; Graepel et al., 2012; Li et al., 2017) or secure multi-party computation (MPC) (Yao, 1982; Beimel, 2011; Mohassel & Zhang, 2017; Dolev et al., 2019). Recent work proposed to use cryptographic methods to secure federated learning by designing a secure gradients aggregation protocol (Bonawitz et al., 2016) or encrypting gradients (Aono et al., 2017). These approaches slow down the computation by orders of magnitude, and may also require special security environment setups.
Vision-Based Range Regulation of a Leader-Follower Formation

This brief describes a single-vehicle tracking algorithm relying on active contours for target extraction and an extended Kalman filter for relative position estimation. The primary difficulty lies in the estimation and regulation of range using monocular vision. The work represents a first step towards treating the problem of the control of several unmanned vehicles flying in formation using only local visual information. In particular, allowing only onboard passive sensing of the external environment, we seek to study the achievable closed-loop performance under this model.
Multiplierless Algorithm for Multivariate Gaussian Random Number Generation in FPGAs

The multivariate Gaussian distribution is used to model random processes with distinct pair-wise correlations, such as stock prices that tend to rise and fall together. Multivariate Gaussian vectors with length n are usually produced by first generating a vector of n independent Gaussian samples, then multiplying with a correlation inducing matrix requiring O(n2) multiplications. This paper presents a method of generating vectors directly from the uniform distribution, removing the need for an expensive scalar Gaussian generator, and eliminating the need for any multipliers. The method relies only on small read-only memories and adders, and so can be implemented using only logic resources (lookup-tables and registers), saving multipliers, and block-memory resources for the numerical simulation that the multivariate generator is driving. The new method provides a ten times increase in performance (vectors/second) over the fastest existing field-programmable gate array generation method, and also provides a five times improvement in performance per resource over the most efficient existing method. Using this method, a single 400-MHz Virtex-5 FPGA can generate vectors ten times faster than an optimized implementation on a 1.2-GHz graphics processing unit, and a hundred times faster than vectorized software on a general purpose quad core 2.2-GHz processor.
On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms

The interplay between mutation and selection plays a fundamental role in the behavior of evolutionary algorithms (EAs). However, this interplay is still not completely understood. This paper presents a rigorous runtime analysis of a non-elitist population-based EA that uses the linear ranking selection mechanism. The analysis focuses on how the balance between parameter η, controlling the selection pressure in linear ranking, and parameter χ controlling the bit-wise mutation rate, impacts the runtime of the algorithm. The results point out situations where a correct balance between selection pressure and mutation rate is essential for finding the optimal solution in polynomial time. In particular, it is shown that there exist fitness functions which can only be solved in polynomial time if the ratio between parameters η and χ is within a narrow critical interval, and where a small change in this ratio can increase the runtime exponentially. Furthermore, it is shown quantitatively how the appropriate parameter choice depends on the characteristics of the fitness function. In addition to the original results on the runtime of EAs, this paper also introduces a very useful analytical tool, i.e., multi-type branching processes, to the runtime analysis of non-elitist population-based EAs.
Error-based or target-based? A unified framework for learning in recurrent spiking networks

∆t is the discrete time-integration step, while τs and τm are respectively the spike-filtering time constant and the temporal membrane constant. Each neuron is a leaky integrator with a recurrent filtered input obtained via a synaptic matrix w ∈ RN×N and an external signal I i . wres = −20 accounts for the reset of the membrane potential after the emission of a spike. v = 0 and vrest = −4 are the the threshold and the rest membrane potential.