Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of Large-Scale Simulated Utterances in Virtual Rooms to Train Deep-Neural Networks for Far-Field Speech Recognition in Google Home

We describe the structure and application of an acoustic room simulator to generate large-scale simulated data for training deep neural networks for far-field speech recognition. The system simulates millions of different room dimensions, a wide distribution of reverberation time and signal-to-noise ratios, and a range of microphone and sound source locations. We start with a relatively clean training set as the source and artificially create simulated data by randomly sampling a noise configuration for every new training example. As a result, the acoustic model is trained using examples that are virtually never repeated. We evaluate performance of this approach based on room simulation using a factored complex Fast Fourier Transform (CFFT) acoustic model introduced in our earlier work, which uses CFFT layers and LSTM AMs for joint multichannel processing and acoustic modeling. Results show that the simulator-driven approach is quite effective in obtaining large improvements not only in simulated test conditions, but also in real / rerecorded conditions. This room simulation system has been employed in training acoustic models including the ones for the recently released Google Home.
Using path integrals to price interest rate derivatives

We present a new approach for the pricing of interest rate derivatives which allows a direct computation of option premiums without deriving a (Black-Scholes type) partial differential equation and without explicitly solving the stochastic process for the underlying variable. The approach is tested by rederiving the prices of a zero bond and a zero bond option for a short rate environment which is governed by Vasicek dynamics. Furthermore, a generalization of the method to general short rate models is outlined. In the case, where analytical solutions are not accessible, numerical implementations of the path integral method in terms of lattice calculations as well as path integral Monte Carlo simulations are possible.
Integrated DC ‑ AC Converter as Power Conditioner for Fuel Cell Based System

This paper presents a new integrated power conditioner topology for power supply systems based on fuel cells. The proposed converter is based in the ZVS active clamp full bridge boost converter but controlled with sinusoidal pulse width modulation technique. The proposed fuel cell power conditioner is intended for stand-alone ac power generation and low voltage fuel cell input. The main characteristic of the proposed topology is the use of fewer components when compared to the conventional two-stage power conditioners approach, so the cost is lower. In addition, the total efficiency is increased by reducing the power processing stages. Therefore, it is expected that the proposed integrated power conditioner topology could be effectively utilized for fuel cells applications. The paper presents a compressive analysis of the main characteristics of the fuel cell which will determine the design parameters for the power conditioner. Also, detailed operations of the integrated topology is introduced. In order to validate the proposed approach a 900 watts prototype was implemented. The paper presents experimental results under several operating conditions.
Multi-Task Minimum Error Rate Training for SMT

Multi-Task Minimum Error Rate Training for SMT We present experiments on multi-task learning for discriminative training in statistical machine translation (SMT), extending standard minimum-error-rate training (MERT) by techniques that take advantage of the similarity of related tasks. We apply our techniques to German-to-English translation of patents from 8 tasks according to the International Patent Classification (IPC) system. Our experiments show statistically significant gains over task-specific training by techniques that model commonalities through shared parameters. However, more finegrained combinations of shared parameters with task-specific ones could not be brought to bear on models with a small number of dense features. The software used in the experiments is released as open-source tool.
Conductance enlargement in picoscale electroburnt graphene nanojunctions

Significance Continuation of Moore’s law to the sub–10-nm scale requires the development of new technologies for creating electrode nanogaps, in architectures which allow a third electrostatic gate. Electroburnt graphene junctions (EGNs) have the potential to fulfill this need, provided their properties at the moment of gap formation can be understood and controlled. In contrast with mechanically controlled break junctions, whose conductance decreases monotonically as the junction approaches rupture, we show that EGNs exhibit a surprising conductance enlargement just before breaking, which signals the formation of a picoscale current path formed from a single sp2 bond. Just as Schottky barriers are a common feature of semiconductor interfaces, conductance enlargement is a common property of EGNs and will be unavoidably encountered by all research groups working on the development of this new technology. Provided the electrical properties of electroburnt graphene junctions can be understood and controlled, they have the potential to underpin the development of a wide range of future sub-10-nm electrical devices. We examine both theoretically and experimentally the electrical conductance of electroburnt graphene junctions at the last stages of nanogap formation. We account for the appearance of a counterintuitive increase in electrical conductance just before the gap forms. This is a manifestation of room-temperature quantum interference and arises from a combination of the semimetallic band structure of graphene and a cross-over from electrodes with multiple-path connectivity to single-path connectivity just before breaking. Therefore, our results suggest that conductance enlargement before junction rupture is a signal of the formation of electroburnt junctions, with a picoscale current path formed from a single sp2 bond.
SRV: Switch-based rules verification in software defined networking

Software defined networking (SDN) is an innovative networking paradigm that allows network administrators to manage network services through the abstraction of higher-level functionality. This is done by decoupling the system that makes decisions about where traffic is sent (the control plane) from the underlying systems that forward traffic to the selected destination (the data plane). In the control plane, SDN controller translates the rule-based policies from the network applications(OF app) to the switches over the network. The southbound interfaces such as OpenFlow are used to communicate between the SDN Controller and the switches. The northbound interfaces are used to communicate between the SDN Controller and OF apps. According to OpenFlow specification [1] [2], each OF app can enforce their own rule and the controller applies the rules with the highest priority if a packet_in message matches against several rules at the same time, which we call priority-based mechanism. In this paper, we present a security issue of the priority-based mechanism in SDN. In this attack, the malicious rules with lowest priority can manipulate the entire SDN network. This attack can make all the rules with higher priorities fail. A lightweight solution, switch-based rules verification(SRV), is proposed, by leveraging the centralized management in SDN to obtain a global view of the entire network topology and detects the malicious rules. Once a malicious rule is found, SRV will send the warning messages and refuse this rule immediately. We implement the prototype of SRV in Floodlight as a security module and packaged it as a Java library, making it a lightweight and flexible solution with minimal deployment requirements. The preliminary results of our experiments show that the latency remains as low as 640ms even with the presence of 10 thousands rules.
Layout of Bayesian Networks

Bayesian networks are weighted directed acyclic graphs (DAGs). Layout of DAGs has been studied for many years, with variants of the horizontal layering algorithm of Sugiyama et al. (Sugiyama, Tagawa & Toda 1981) the preferred approach for medium size graphs. Following Gansner et al. (Gansner, Koutsofios, North & Vo 1993) we extend the classic horizontal layering algorithm with an additional vertex coordinate assignment phase which is designed to remove overlap between vertices with non-zero width and height. This is required because vertices in the Bayesian network are typically large and may vary greatly in height and width so a major component of good layout is to place vertices closely together without overlap. Our main contribution is to describe and evaluate a variety of novel techniques for vertex coordinate assignment.
Novel, panzootic and hybrid genotypes of amphibian chytridiomycosis associated with the bullfrog trade

Global amphibian declines are linked with the presence of specific, highly virulent genotypes of the emerging fungal disease chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd) known as the global panzootic lineage (Bd‐GPL). The global trade in amphibians for human consumption is suspected to have facilitated emergence of the disease, but evidence to support this is largely lacking. Here, we investigated the role the Lithobates catesbeianus (North American bullfrog) trade in spreading Bd genotypes by comparing strains associated with L. catesbeianus to a global panel using 36 sequenced loci from multiple chromosomal regions. Most bullfrogs were infected with Bd‐GPL genotypes, but we also detected novel, highly divergent Bd genotypes (Bd‐Brazil) from a live bullfrog in a US market and from native Brazilian anurans in the Atlantic Forest where bullfrogs are widely farmed. Sexual reproduction was also detected for the first time in Bd in the form of a hybrid genotype between the Bd‐GPL and Bd‐Brazil lineages in the Atlantic Forest. Despite the demonstration that ribosomal RNA types in Bd fail to undergo concerted evolution (over 20 sequence types may be found in a single strain), the Bd‐GPL and Bd‐Brazil lineages form largely separate clusters of related internal transcribed spacer (ITS) RNA sequences. Using ITS sequences, we then demonstrate the presence of Bd‐Brazil in Japan, primarily on invasive L. catesbeianus. The finding that Bd is capable of sexual reproduction between panzootic and endemic genotypes emphasizes the risk of international wildlife trade as a source of additional Bd epizootics owing to hybridization.
Interference with endogenous ras function inhibits cellular responses to wounding

Wounding of tissue induces cellular responses that ultimately result in wound repair. Studies in tissue culture model systems indicate that these responses include induction of AP-1 regulated genes, cell migration and mitogenesis which are also characteristic of cellular responses to growth factors. Investigations have identified cellular ras proteins as critical components of growth factor-stimulated signal transduction pathways, however their role in the wounding response is less clear. Investigation of the potential involvement of c-Ras in this process utilized quiescent living bovine corneal endothelium cells (BCE) which were microinjected with ras dominant interfering mutant protein (N17) and subsequently stimulated by mechanical wounding. Analysis of these cells demonstrated that microinjection of dominant- interfering ras protein, but not control proteins, inhibited the wounding response as evidenced by diminished Fos expression, lack of cell migration and a block in DNA synthesis.
The Art of Lecturing

I am not a theologian, but I was once privileged to attend, at a week-end conference, a lecture by a professor of theology. It was twenty-five years ago and it is still vivid to me to-day. The subject was Amos, of whom I previously knew precisely nothing. By the end of the lecture I had not only a dynamic impression of the character and mes sage of the prophet but also a clear and colourful picture of the contemporary economic, political, and social struc ture of the people of Israel.The professor used no notes. He padded round the room, with his hands behind his back, and wearing felt slippers. From time to time he raised one foot to scratch the calf of the other leg. Now and then he looked at one or other of us directly in the eyes, with a kind of challenging glare. At other times he gazed through the window into the extreme distance, as if looking at Palestine, and describing what he saw, taking our gaze with him. I recall that he pronounced Jahweh with the sort of sound one makes in clearing one's throat.
Improved Free-form Modelling of Scattered Data by Dynamic Neural Networks

The aim of this paper is to improve the method of modelling scattered data by free-from surfaces presented in [5]. In that method a neural network was used for ordering the data and forming a quadrilateral control grid from the scattered points, hence the standard free-form methods like Bézier-surface or NURBS could be applied to approximate or interpolate the data. Instead of the original artificial neural network, which has been used for ordering the data, now a recent development, the dynamic version of this neural network is applied. Hence the preprocess of ordering the spatial scattered data is based on the neural network, the improvement of the network yields a much faster and more reliable algorithm.
A Synaptical Story of Persistent Activity with Graded Lifetime in a Neural System

Persistent activity refers to the phenomenon that cortical neurons keep firing even after the stimulus triggering the initial neuronal responses is moved. Persistent activity is widely believed to be the substrate for a neural system retaining a memory trace of the stimulus information. In a conventional view, persistent activity is regarded as an attractor of the network dynamics, but it faces a challenge of how to be closed properly. Here, in contrast to the view of attractor, we consider that the stimulus information is encoded in a marginally unstable state of the network which decays very slowly and exhibits persistent firing for a prolonged duration. We propose a simple yet effective mechanism to achieve this goal, which utilizes the property of short-term plasticity (STP) of neuronal synapses. STP has two forms, short-term depression (STD) and short-term facilitation (STF), which have opposite effects on retaining neuronal responses. We find that by properly combining STF and STD, a neural system can hold persistent activity of graded lifetime, and that persistent activity fades away naturally without relying on an external drive. The implications of these results on neural information representation are discussed.
A stereoscopic video see-through augmented reality system based on real-time vision-based registration

In an augmented reality system, it is required to obtain the position and orientation of the user's viewpoint in order to display the composed image while maintaining a correct registration between the real and virtual worlds. All the procedures must be done in real time. This paper proposes a method for augmented reality with a stereo vision sensor and a video see-through head-mounted display (HMD). It can synchronize the display timing between the virtual and real worlds so that the alignment error is reduced. The method calculates camera parameters from three markers in image sequences captured by a pair of stereo cameras mounted on the HMD. In addition, it estimates the real-world depth from a pair of stereo images in order to generate a composed image maintaining consistent occlusions between real and virtual objects. The depth estimation region is efficiently limited by calculating the position of the virtual object by using the camera parameters. Finally, we have developed a video see-through augmented reality system which mainly consists of a pair of stereo cameras mounted on the HMD and a standard graphics workstation. The feasibility of the system has been successfully demonstrated with experiments.
Simulation of Hypersonic Shock Wave/Boundary Layer Interaction Using High Order WENO Scheme

This paper investigates the accuracy and robustness of high order WENO schemes for predicting hypersonic shock wave/boundary layer interaction. The implicit time marching method with unfactored Gauss-Seidel line relaxation is used with a 5th order WENO flnite difierence scheme for inviscid ∞uxes. The viscous terms are discretized using a 4th order conservative central difierencing. Numerical results agree well with the experiment of a hollow/∞are geometry at Mach number of 12:49 and Reynolds number of 1:09 £ 10 5 =ft.
Towards a new world-ontology

A crucial problem of knowledge representation is that it has to be formal and informal at the same time. Here, ‘formal’ refers to knowledge as a mathematical concept which is thought, and ‘informal’ to knowledge as something which is experienced, i.e. a ‘real’ world phenomenon. This paper is an attempt to reconcile these potentially contradictory conditions. Our aim is to show that a cognitively based formal representation may exist, underlying traditional (formal) ontology, which may uniformly characterize the different domains of human knowledge like logic, language, mathematics, etc. We derive such a representation from the properties of cognition and signification, and elaborate its application in propositional logic and (briefly) in syntax.
Enhancing identification mechanisms in UML class diagrams with meaningful keys

Unlike identification with keys and reference schemes in ER and ORM, UML uses internal, system-generated, identifiers, with a little-known underspecified option for user-defined identifiers. To increase the ontological foundations of UML, we propose two language enhancements for UML, being formally defined simple and compound identifiers and the notion of defined class, which also have a corresponding extension of UML's metamodel.
Non-rigid tracking of musk shrews in video for detection of emetic episodes

Animal study plays a key role in understanding the mechanisms of emesis induced by many diseases and drug treatments. The traditional measurement of emesis usually requires manual observation which is labor intensive, difficult to standardize across coders, and often lacks spatial and temporal precision. This paper proposes a vision-based system for non-rigid tracking of musk shrews in videos and automatic characterization of eme-sis response when a chemotherapy agent is applied. Firstly, we learn a 80-dimensional non-rigid shape model (defined by 40 two-dimensional landmarks) to characterize the non-rigid shape variation of a musk shrews. After the body contour of the musk shrew is initialized in the first frame, we propose an algorithm for non-rigid tracking of the 40 landmarks in a video sequence. In each frame the contour of the musk shrew is estimated using background subtraction and a major challenge is to solve for the correspondence between the body contour and the shape model. Once the tracking is done, we used the shape changes to characterize the retch response during the emetic episodes. Finally, an emetic episode is detected when there're consecutive retches.
Regulation of Ca2+ Signaling in Pulmonary Hypertension

Understanding the cellular and molecular mechanisms involved in the development and progression of pulmonary hypertension (PH) remains imperative if we are to successfully improve the quality of life and life span of patients with the disease. A whole plethora of mechanisms are associated with the development and progression of PH. Such complexity makes it difficult to isolate one particular pathway to target clinically. Changes in intracellular free calcium concentration, the most common intracellular second messenger, can have significant impact in defining the pathogenic mechanisms leading to its development and persistence. Signaling pathways leading to the elevation of [Ca2+]cyt contribute to pulmonary vasoconstriction, excessive proliferation of smooth muscle cells and ultimately pulmonary vascular remodeling. This current review serves to summarize the some of the most recent advances in the regulation of calcium during pulmonary hypertension.
Web Browsing For Visually Impaired People Through Handheld Devices

Information Systems can help the peoples by providing many varieties of information’s to peoples. We can access the information’s anywhere by using the World Wide Web. But the information’s can’t be viewed by the blind peoples. Due to their inability in accessing information from written text documents, blind people face tremendous difficulties in accessing information through web.In this paper, we propose an automatic summarization system to ease web browsing for visually impaired people on handheld devices. In particular, we propose a new architecture for summarizing Semantic Textual Units [2] based on efficient algorithms for linguistic treatment [3][6] which allow real time processing and deeper linguistic analysis of web pages, thus allowing quality content visualization. Moreover, we present a text-to-speech interface to ease the understanding of web pages content. To our knowledge, this is the first attempt to use both statistical and linguistic techniques for text summarization for browsing on mobile devices.
An information-theoretic primer on complexity, self-organization, and emergence

Complex Systems Science aims to understand concepts like complexity, self-organization, emergence and adaptation, among others. The inherent fuzziness in complex systems definitions is complicated by the unclear relation among these central processes: does self-organisation emerge or does it set the preconditions for emergence? Does complexity arise by adaptation or is complexity necessary for adaptation to arise? The inevitable consequence of the current impasse is miscommunication among scientists within and across disciplines. We propose a set of concepts, together with their possible information-theoretic interpretations, which can be used to facilitate the Complex Systems Science discourse. Our hope is that the suggested information-theoretic baseline may promote consistent communications among practitioners, and provide new insights into the field. Published 2008 Wiley Periodicals, Inc. Complexity, 2009 This article was submitted as an invited paper resulting from the “Understanding Complex Systems” conference held at the University of Illinois at Urbana-Champaign, May 2007.
High-Intensity Interval Training in Stroke Rehabilitation

Abstract After stroke, people with weakness enter a vicious cycle of limited activity and deconditioning that limits functional recovery and exacerbates cardiovascular risk factors. Conventional aerobic exercise improves aerobic capacity, function, and overall cardiometabolic health after stroke. Recently, a new exercise strategy has shown greater effectiveness than conventional aerobic exercise for improving aerobic capacity and other outcomes among healthy adults and people with heart disease. This strategy, called high-intensity interval training (HIT), uses bursts of concentrated effort alternated with recovery periods to maximize exercise intensity. Three poststroke HIT studies have shown preliminary effectiveness for improving functional recovery. However, these studies were varied in approach and the safety of poststroke HIT has received little attention. The objectives of this narrative review are to (1) propose a framework for categorizing HIT protocols; (2) summarize the safety and effectiveness evidence of HIT among healthy adults and people with heart disease and stroke; (3) discuss theoretical mechanisms, protocol selection, and safety considerations for poststroke HIT; and (4) provide directions for future research.