Miracle-dz/UniFAR-FTUs huggingface dataset:
Smooth soft mel-spectrographic masks based on blind sparse source separation

Abstract This paper investigates the use of DUET, a recently proposedblind source separation method, as front-end for missing dataspeech recognition. Based on the attenuation and delay estima-tion in stereo signals soft time-frequency masks are designedto extract a target speaker from a mixture containing multiplespeech sources. A postprocessing step is introduced in order toremove isolated mask points that can cause insertion errors inthe speech decoder. The results for connected digit experimentsin a multi-speaker environment demonstrate that the proposedsoft masks closely match the performance of the oracle maskdesigned with a priori knowledge of the source spectra. Index Terms : speech recognition, missing data, attenuationand delay estimation 1. Introduction The concept of time-frequency (TF) masking has recently at-tracted some interest in the ﬁeld of blind signal separation (BSS)[1, 2]. Demixing via TF-masks has the potential to separatemixtures with more sources than sensors as it does not rely onmatrix inversion. Instead the TF-plane is partitioned into dis-joint regions each assigned to a particular source. The sourcesare then recovered by converting each region back into the timedomain. It seems promising to use BSS systems as front-endsfor automatic speech recognition (ASR). In [3] we have pro-posed such a combination using a BSS technique called DUETand a missing data (MD) speech recognizer. The proposedsystem uses DUET to estimate TF-masks in the sparse Short-Time-Fourier-Transform (STFT) domain before converting thehigh STFT frequency resolution to a perceptual mel-frequencyscale suitable for ASR. In this way we can avoid source re-construction and directly exploit the spectrographic masks forMD-ASR. This paper extends our previous work in two regards.Firstly, we replace binary masks with soft masks which havebeen proven to be beneﬁcial for both speech recognition andspeech enhancement. Several studies [2, 4] have reported thatbinary TF-masking can lead to audible unnatural sound arti-facts that can be avoided to some degree by soft masks. Theadvantages of soft masks in MD-ASR are even more evidentas marginalization approaches based on soft decisions consis-tently outperformed hard masks [5]. Secondly, we show thata simple mask postprocessing can lead to substantial recogni-tion improvements. A two-dimensional (2-D) median ﬁlter wasapplied to reduce the inﬂuence of outliers visible as scattered
Statistical Evidence for Three Classes of Gamma-Ray Bursts

Two different multivariate clustering techniques, the K-means partitioning method and the Dirichlet process of mixture modeling, have been applied to the BATSE gamma-ray burst (GRB) catalog, to obtain the optimum number of coherent groups. In the standard paradigm, GRBs are classified into only two groups, the long and short bursts. However, for both of the clustering techniques, the optimal number of classes was found to be three, a result that is consistent with previous statistical analysis. In this classification, the long bursts are further divided into two groups that are primarily differentiated by their total fluence and duration and hence are called low- and high-fluence GRBs. Analysis of GRBs with known redshifts and spectral parameters suggests that low-fluence GRBs have nearly constant isotropic energy output of 1052 ergs, while for the high-fluence ones the energy output ranges from 1052 to 1054 ergs. It is speculated that the three kinds of GRBs reflect three different origins: mergers of neutron star systems, mergers between white dwarfs and neutron stars, and collapse of massive stars.
Graph Indexing: Tree + Delta >= Graph

Recent scientific and technological advances have witnessed an abundance of structural patterns modeled as graphs. As a result, it is of special interest to process graph containment queries effectively on large graph databases. Given a graph database G, and a query raph q, the graph containment query is to retrieve all graphs in G which contain q as subgraph(s). Due to the vast number of graphs in G and the nature of complexity for subgraph isomorphism testing, it is desirable to make use of high-quality graph indexing mechanisms to reduce the overall query processing cost. In this paper, we propose a new cost-effective graph indexing method based on frequent tree-features of the graph database. We analyze the effectiveness and efficiency of tree as indexing feature from three critical aspects: feature size, feature selection cost, and pruning power. In order to achieve better pruning ability than existing graph-based indexing methods, we select, in addition to frequent tree-features (Tree), a small number of discriminative graphs (Δ) on demand, without a costly graph mining process beforehand. Our study verifies that (Tree+Δ) is a better choice than graph for indexing purpose, denoted (Tree+Δ ≥Graph), to address the graph containment query problem. It has two implications: (1) the index construction by (Tree+Δ) is efficient, and (2) the graph containment query processing by (Tree+Δ) is efficient. Our experimental studies demonstrate that (Tree+Δ) has a compact index structure, achieves an order of magnitude better performance in index construction, and most importantly, outperforms up-to-date graph-based indexing methods: gIndex and C-Tree, in graph containment query processing.
A New and Efficient Algorithm-Based Fault Tolerance Scheme for A Million Way Parallelism

Fault tolerance overhead of high performance computing (HPC) applications is becoming critical to the efficient utilization of HPC systems at large scale. HPC applications typically tolerate fail-stop failures by checkpointing. Another promising method is in the algorithm level, called algorithmic recovery. These two methods can achieve high efficiency when the system scale is not very large, but will both lose their effectiveness when systems approach the scale of Exaflops, where the number of processors including in system is expected to achieve one million. This paper develops a new and efficient algorithm-based fault tolerance scheme for HPC applications. When failure occurs during the execution, we do not stop to wait for the recovery of corrupted data, but replace them with the corresponding redundant data and continue the execution. A background accelerated recovery method is also proposed to rebuild redundancy to tolerate multiple times of failures during the execution. To demonstrate the feasibility of our new scheme, we have incorporated it to the High Performance Linpack. Theoretical analysis demonstrates that our new fault tolerance scheme can still be effective even when the system scale achieves the Exaflops. Experiment using SiCortex SC5832 verifies the feasibility of the scheme, and indicates that the advantage of our scheme can be observable even in a small scale.
Radioimmunoassayof “ Pregnancy-Specific ’ ‘-3 1-Glycoprotein ( SP 1 )

A radioirnmunoassay for SP1 (“pregnancy-specific” beta1-glycoprotein) is described in which a sensitivity of 0.1 tg/L was achieved by use of an antiserum with Ka 1.7 X lOll L/mol and delayed addition of a 1251-SP1tracer (specific acty, 25 Ci/g) that was stable for use in the assay for at least six to seven weeks. We also report an additional anti-SP serum, from an early bleeding, that displayed “apparent positive cooperativity” in the lgG but not the 1gM fraction.
A robust performance evaluation scheme for rectification algorithms in camera captured document images

Major issues faced by camera captured document analysis is to deal with the page curl and perspective distortions. Perspective distortion occurs when the world plane is not parallel to the imaging plane. This causes parallel lines to become non-parallel and the objects which are far away from the camera to seem smaller. Rectification is an unavoidable process on images with perspective distortion for precise representation. No standard measures for the performance evaluation of rectification algorithms exists with most of the evaluation done to concentrate in visual pleasing impressions. OCR based evaluation methods perform well for evaluation of rectification in text regions, but they fail to measure the performance of rectification algorithm on the non-text regions like mathematical equations, graphics, or tables. Feature based methods, on the other hand require manual assistance. An image based performance evaluation of rectification algorithms using SIFT(Scale Invariant Feature Transform) features was reported earlier. In this paper, a new method for performance evaluation using SURF(Speeded-Up Robust Features) features is proposed, which is more efficient and 12.07 times faster than SIFT based method according to the obtained results.
LASEC: A Localized Approach to Service Composition in Pervasive Computing Environments

Pervasive computing environments (PvCE) are embedded with interconnected smart devices which provide users with services desired. To meet requirements of users, smart devices with different kinds of functions may need to be associated together to provide the service described in the user requirement, which is called service composition. As the service composition environment may be dynamic and large scale, centralized service composition algorithm is usually inefficient due to message cost. On the other hand, a decentralized approach, which employs pre-determined coordinators to search and compose service, may have high cost as well. In this paper, we discuss a localized approach for service composition based on the Ubiquitous Interacting Object (UIO) model we have proposed earlier. UIO is an abstraction of physical devices in PvCE with ability to find and collaborate with other devices through exposing their capabilities as services. In our localized service composition algorithm (LASEC), UIOs collaborate with each other in a bottom-up, localized manner to compose required service without requiring global knowledge. To solve the problem of blind compositions in LASEC, we propose a novel mechanism called Alien-information-based Acknowledging (A-Ack), in which a UIO decides on collaborating with another UIO only after obtaining some additional information from the collaboration candidate. Specifically, this information refers to ability of a given UIO to compose another part of the service. Proposed LASEC is message-efficient and quality-guaranteed. Extensive simulations of LASEC as well as existing decentralized and pull-based centralized algorithms have been conducted. The results show the relatively low communication cost and composition time of LASEC. Moreover, we demonstrate feasibility of our approach with a prototype implementation.
Delineation of hydrochemical facies distribution in a regional groundwater system by means of fuzzy c‐means clustering

In this paper, classification of a large hydrochemical data set (more than 600 water samples and 11 hydrochemical variables) from southeastern California by fuzzy c‐means (FCM) and hierarchical cluster analysis (HCA) clustering techniques is performed and its application to hydrochemical facies delineation is discussed. Results from both FCM and HCA clustering produced cluster centers (prototypes) that can be used to identify the physical and chemical processes creating the variations in the water chemistries. There are several advantages to FCM, and it is concluded that FCM, as an exploratory data analysis technique, is potentially useful in establishing hydrochemical facies distribution and may provide a better tool than HCA for clustering large data sets when overlapping or continuous clusters exist.
An Analysis on the Influence of Network Topologies on Local and Global Dynamics of Metapopulation Systems

Metapopulations are models of ecological systems, describing the interactions and the behavior of populations that live in fragmented habitats. In this paper, we present a model of metapopulations based on the multivolume simulation algorithm tau-DPP, a stochastic class of membrane systems, that we utilize to investigate the influence that different habitat topologies can have on the local and global dynamics of metapopulations. In particular, we focus our analysis on the migration rate of individuals among adjacent patches, and on their capability of colonizing the empty patches in the habitat. We compare the simulation results obtained for each habitat topology, and conclude the paper with some proposals for other research issues concerning metapopulations.
Reducing the sparsity of contextual information for recommender systems

Our work focuses on the improvement of the accuracy of context-aware recommender systems. Contextual information showed to be promising factor in recommender systems. However, pure context-based recommender systems can not outperform other approaches mainly due to high sparsity of contextual information. We propose an idea to improve accuracy of context based recommender systems by context inference. Context inference is based on effect discovered by analyses of the context as a factor influencing user needs. Analyses of the news readers reveals existence of behavioural correlation which is the main pillar of proposed context inference. Method for context inference is based on collaborative filtering and clustering of web usage (as a non-discretizing alternative to association rules mining).
On algebraic singularities, finite graphs and D-brane gauge theories : a string theoretic perspective -- with a digression on string field theory

In this writing we shall address certain beautiful inter-relations between the construction of 4-dimensional supersymmetric gauge theories and resolution of algebraic singularities, from the perspective of String Theory. We review in some detail the requisite background in both the mathematics, such as orbifolds, symplectic quotients and quiver representations, as well as the physics, such as gauged linear sigma models, geometrical engineering, Hanany-Witten setups and D-brane probes. We investigate aspects of world-volume gauge dynamics using D-brane resolutions of various Calabi-Yau singularities, notably Gorenstein quotients and toric singularities. Attention will be paid to the general methodology of constructing gauge theories for these singular backgrounds, with and without the presence of the NS-NS B-field, as well as the T-duals to brane setups and branes wrapping cycles in the mirror geometry. Applications of such diverse and elegant mathematics as crepant resolution of algebraic singularities, representation of finite groups and finite graphs, modular invariants of affine Lie algebras, etc. will naturally arise. Various viewpoints and generalisations of McKay's Correspondence will also be considered. The present work is a transcription of excerpts from the first three volumes of the author's PhD thesis which was written under the direction of Prof. A. Hanany - to whom he is much indebted - at the Centre for Theoretical Physics of MIT, and which, at the suggestion of friends, he posts to the ArXiv pro hac vice; it is his sincerest wish that the ensuing pages might be of some small use to the beginning student.
Simplified Voronoi diagrams

We are interested in Voronoi diagrams as a tool in robot path planning, where the search for a path in anr-dimensional space may be simplified to a search on an (r−1)-dimensional Voronoi diagram. We define a Voronoi diagramV based on a measure of distance which is not a true metric. This formulation has lower algebraic complexity than the usual definition, which is a considerable advantage in motion-planning problems with many degrees of freedom. In its simplest form, the measure of distance between a point and a polytope is the maximum of the distances of the point from the half-spaces which pass through faces of the polytope. More generally, the measure is defined in configuration spaces which represent rotation. The Voronoi diagram defined using this distance measure is no longer a strong deformation retract of free space, but it has the following useful property: any path through free space which starts and ends on the diagram can be continuously deformed so that it lies entirely on the diagram. Thus it is still complete for motion planning, but it has lower algebraic complexity than a diagram based on the Euclidean metric.
CD2v Interacts with Adaptor Protein AP-1 during African Swine Fever Infection

African swine fever virus (ASFV) CD2v protein is believed to be involved in virulence enhancement, viral hemadsorption, and pathogenesis, although the molecular mechanisms of the function of this viral protein are still not fully understood. Here we describe that CD2v localized around viral factories during ASFV infection, suggesting a role in the generation and/or dynamics of these viral structures and hence in disturbing cellular traffic. We show that CD2v targeted the regulatory trans-Golgi network (TGN) protein complex AP-1, a key element in cellular traffic. This interaction was disrupted by brefeldin A even though the location of CD2v around the viral factory remained unchanged. CD2v-AP-1 binding was independent of CD2v glycosylation and occurred on the carboxy-terminal part of CD2v, where a canonical di-Leu motif previously reported to mediate AP-1 binding in eukaryotic cells, was identified. This motif was shown to be functionally interchangeable with the di-Leu motif present in HIV-Nef protein in an AP-1 binding assay. However, we demonstrated that it was not involved either in CD2v cellular distribution or in CD2v-AP-1 binding. Taken together, these findings shed light on CD2v function during ASFV infection by identifying AP-1 as a cellular factor targeted by CD2v and hence elucidate the cellular pathways used by the virus to enhance infectivity.
Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on “abstract metrics” that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging “big data” domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.
Research on passenger flow counting based on embedded system

Passenger flow counting is an important issue for management and decision in many public areas such as shopping centers, airports, gyms and galleries. This paper presents some algorithms of Head-counting and Head-tracking for embedded systems in vertically-installed cameras. The system is able to count the number of passengers who enter or leave the detection area. The results are reliable, accurate and stable.
Institutional Microaggressions at a Hispanic Serving Institution: A Diné (Navajo) Woman Utilizing Tribal Critical Race Theory through Student Activism

ABSTRACT From private to public, from small to large, campus protests and demonstrations have risen across the country to address institutional racism regarding a range of issues including offensive Halloween costumes, university/college seals, lack of faculty color, and racist vandalism. One such example occurred at Southwest University where Native American students were protesting the university seal, which represents settler colonialism and genocide. In this article, we provide a case study of Joy, a Diné (Navajo) young woman, and describe her student activism in regards to the seal and how she utilizes it to connect to her culture, language, and identity. We utilize critical race theory (CRT) and tribal critical race theory (TribalCrit) to analyze the institutional microaggressions that Joy experienced on campus. Our main conclusions explain how student activism enables students to address systemic racism and provides a vehicle to create better conditions on university campuses.
Block diagonalization precoding game in a multiuser multicell system

This paper characterizes the multicell precoding game where block-diagonalization (BD)-based precoding is utilized on a per-cell basis for downlink transmissions. Sharing the same frequency band, the base-station (BS) at each cell wishes to maximize the sum-rate for its connected mobile-stations (MS) with BD precoding. In this context, the paper considers a strategic non-cooperative game (SNG), where each BS greedily determines its precoding strategy in a distributed manner, based on the knowledge of the inter-cell interference (ICI) at its connected MSs. Via the game-theory framework, the existence and uniqueness of a Nash Equilibrium (NE) of this multicell game are subsequently studied. It is shown that there always exists at least one pure NE in the game, whereas the uniqueness of the NE is guaranteed under a certain condition on the ICI. The paper also characterizes the multicell precoding game where BD-Dirty Paper Coding (BD-DPC) is utilized at each BS on a per-cell basis. Simulation results then confirm our analysis on the NE's uniqueness in the BD and BD-DPC multicell precoding games.
Soot and SO[subscript 2] contribution to the supersites in the MILAGRO campaign from elevated flares in the Tula Refinery

This work presents a simulation of the plume trajectory emitted by flaring activities of the Miguel Hidalgo Refinery in Mexico. The flame of a representative sour gas flare is modeled with a CFD combustion code in order to estimate emission rates of combustion by-products of interest for air quality: acetylene, ethylene, nitrogen oxides, carbon monoxide, soot and sulfur dioxide. The emission rates of NO2 and SO2 were compared with measurements obtained at Tula as part of MILAGRO field campaign. The rates of soot, VOCs and CO emissions were compared with estimates obtained by Instituto Mexicano del Petr óleo (IMP). The emission rates of these species were further included in WRF-Chem model to simulate the chemical transport of the plume from 22 to 27 March of 2006. The model presents reliable performance of the resolved meteorology, with respect to the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), mean bias (BIAS), vector RMSE and Index of Agreement (IOA). WRF-Chem outputs of SO 2and soot were compared with surface measurements obtained at the three supersites of MILAGRO campaign. The results suggest a contribution of Tula flaring activities to the total SO 2 levels of 18 % to 27 % at the urban supersite (T0), and of 10 % to 18 % at the suburban supersite (T1). For soot, the model predicts low contribution at the three supersites, with less than 0.1 % at three supersites. According to the model, the greatest contribution of both pollutants to the three supersites occurred on 23 March, which coincides with the third cold surge event reported during the campaign.