Miracle-dz/UniFAR-FTUs huggingface dataset:
Communication delay analysis based on network calculus

Network calculus is a promising theory for analyzing and modeling networks based on min-plus algebra. Using network calculus theory, we propose formulas of arrival curve and service curve for end-to-end communication, build the corresponding time model, and derive the communication delay formulas for two scenarios of the model respectively. Then we take fat tree topology, which is widely used in Infiniband interconnection, as an example to analyze the delay of one-to-all broadcast. This paper, as a groundwork, provides a new approach for the network researchers to delve communication delay in future researches.
Population Response to Natural Images in the Primary Visual Cortex Encodes Local Stimulus Attributes and Perceptual Processing

The primary visual cortex (V1) is extensively studied with a large repertoire of stimuli, yet little is known about its encoding of natural images. Using voltage-sensitive dye imaging in behaving monkeys, we measured neural population response evoked in V1 by natural images presented during a face/scramble discrimination task. The population response showed two distinct phases of activity: an early phase that was spread over most of the imaged area, and a late phase that was spatially confined. To study the detailed relation between the stimulus and the population response, we used a simple encoding model to compute a continuous map of the expected neural response based on local attributes of the stimulus (luminance and contrast), followed by an analytical retinotopic transformation. Then, we computed the spatial correlation between the maps of the expected and observed response. We found that the early response was highly correlated with the local luminance of the stimulus and was sufficient to effectively discriminate between stimuli at the single trial level. The late response, on the other hand, showed a much lower correlation to the local luminance, was confined to central parts of the face images, and was highly correlated with the animal's perceptual report. Our study reveals a continuous spatial encoding of low- and high-level features of natural images in V1. The low level is directly linked to the stimulus basic local attributes and the high level is correlated with the perceptual outcome of the stimulus processing.
Muscle Network of Excellence Multimedia Understanding through Semantics, Computation and Learning Work-package 5 N -multimodal Processing and Interaction Deliverable Dn5.3: Algorithms and Software Tools for Cross-modal Multimedia Analysis with Documentation Muscle –network of Excellence Project Co-f

Dissemination Level PU Public X PP Restricted to other program participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services) Keyword List: Cross-modal multimedia analysis and integration, audiovisual speech recognition, cross-modal interaction in human-computer interfaces, automatic video analysis and modalities integration, multimodal saliency detection, multimedia content. Figure 1: Screen shot demonstrating speaker clustering into 2 classes corresponding to an actor and an actress from a dialogue scene extracted from the movie ANALYZE THAT. The accuracy of segmentation into three classes is 70%. Overview Speaker clustering is performed using the Expectation Maximization variant proposed in [1]. Four features are extracted from audio namely, the short-term normalized log energy, the short-term normalized zero crossing rate, the normalized pitch frequency, and the normalized energy below 150 Hz. First, 5 clusters are created without any supervision. The cluster having center placed at the smaller energy is identified as being composed by silent/noisy frames and next the four clusters are grouped in two Gaussian Mixture Models using the short-term normalized pitch frequency and the normalized energy below 150 Hz with respect to maximum likelihood principle in order to distinguish between the actor (in blue) and the actress in (red). Although the actor indicator functions derived by the method are not error-free, they were used to compute the cross-correlation function for each pair and the magnitude of the corresponding cross-power spectral density, which were fed next as input to several neural networks including voted perceptrons, radial basis function networks, and support vector machines for dialogue detection [2]. Although the dialogue classifiers were previously trained with error-free ground truth indicator functions provided by annotators for the entire MUSCLE movie dataset 1 , they have correctly detected the dialogue events. The software package is provided as a zip folder that contains the following subfolders and files: DemoExe Data-a sample audio file (in wav format) to test the tool with ground truth (in a Matlab .mat file) Icons-images and graphics used in the GUI PRVerveridis, Results – empty folders needed during operation SpeClusterTool.mcr – method specific components needed to produce the Matlab demo SpeClustTool.exe – main executable file SpeClustTool. * SpeClustTool_mcc_component_data. c-source files needed to produce the Matlab demo. Libraries – generic code in order to produce a run-time Matlab demo readme.txt – instructions Example Usage Run SpeClustTool.exe and use the …
Biological and Chemical Study of Astragalus gombiformis

Extracts of aerial parts and roots of wild Astragalus gombiformis Pomel were tested for their antibacterial, antioxidant, and insecticidal activities and contents of phenolic compounds. Antibacterial activity was tested by the paper disk agar diffusion method and determination of the minimal inhibitor concentration. Among the tested extracts, three extracts (methanol, chloroform, and ethyl acetate) from aerial parts and two extracts (water, methanol) from roots exhibited diameters of inhibition zone equal or above 12 mm (at 150 μg/ disk) and minimal inhibitor concentrations ranging between 233 and 1250 μg/ml. Spectrophotometric and HPLC analyses showed that contents of both total polyphenols and flavonoids, as well as antioxidant activity were higher in the methanolic extract of aerial parts as compared to roots. No insecticidal activity of the extracts of the aerial parts was found against Culex pipiens.
Dynamic techniques for the optimization of data race detection.

In this article we give an overview of a dynamic data race detector in a Java virtual machine (JVM). We define what exactly is a data race in the context of Java and show how these data races can be detected. Next we show that by by using accordion clocks and the TRaDe heuristic we can perform live data race detection.
TR A 2 / 0 6 A Bayesian Interpretation of Interpolated Kneser

Interpolated Kneser-Ney is one of the best smoothing method s for n-gram language models. Previous explanations for its superiority have been based on intu itive and empirical justifications of specific properties of the method. We propose a novel interpretation of i terpolated Kneser-Ney as approximate inference in a hierarchical Bayesian model consisting of Pitman-Yor processes. As opposed to past explanations, our interpretation can recover exactly the formulation of interpolated Kneser-Ney, and performs better than interpolated Kneser-Ney when a better inf rence procedure is used.
Cognitive aging: effects of education and task demands

The aim of this study was to investigate whether the age-extrinsic factors ‘education’ and ‘sex’ modify the well-documented effects of age on information processing speed. The interacting effects of age (three age groups), educational attainment (low, intermediate or high), and sex were tested on the information processing speed of 1469 healthy individuals ranging in age from 24 to 67 years. Performance on the Letter Digit Substitution Task (LDST), Stroop Color-Word Test (SCWT) and Memory Scanning Task (MST) was negatively affected by higher age, lower educational level and male sex. A high educational level reduced age differences on the LDST. Furthermore, women demonstrate larger age differences than men on the LDST and the MST. However, there were no interactions on SCWT performance. The overall findings suggest that the effects of education and sex on age-related differences in information processing are substantial in the pre-senescence.
Effect of human attributes and type of robots on psychological evaluation of humanoids

In this study, we investigate the effect of the attributes of humans, such as sex and age, on their psychological evaluation of humanoids. We used 11 humanoids in order to investigate the basic tendency of humans to evaluate humanoids. In addition, we included wheeled-walking robots, biped-walking robots, and androids in order to consider the influence of the type of humanoid. We collected data from 2,624 Japanese individuals, ranging from teenagers to people in their 70s, in three major cities in order to obtain maximally representative data. For our psychological scale, we used a humanoid-oriented scale that was developed on the basis of parameters for the evaluation of humanoids according to the perspectives of ordinary people. These parameters are familiarity, utility, and humanness. The results show that middle-aged and older females tend to rate the familiarity and humanness of all humanoids higher, adolescents tend to rate the familiarity and utility of wheeled-walking humanoids higher and the utility of androids lower, and middle-aged people tend to rate the utility of all humanoids higher. We discuss the improved design of humanoids considering both human characteristics and types of humanoids.
Fiscal Trends in Real Economic Aggregates

Using cointegration analysis, the authors examine long-term interactions between fiscal variables and the consumption-output and leisure-labor ratios. The motivation is to test if fiscal trends are an independent source of stochastic trends underlying the long-run behavior of real economic aggregates. The authors' results support the presence of fiscal trends and can be interpreted quite well in terms of the equilibrium approach to fiscal policy. They suggest that neoclassical growth models that embed fiscal trends and distinguish between components of government purchases are more consistent with the data than simple real-business-cycle models. Copyright 1995 by Ohio State University Press.
AGILITY OF THE FIRM : CUSTOMERS ’ PERSPECTIVE Research-in-Progress

Agility is emerging as an important determinant of success and achieving sustained competitive advantage in hyper-competition. Whilst the digital natives are on the rise, ubiquitous technologies, networks and associated systems are increasingly weaving themselves into the very fabric of everyday life of both individuals and corporations. With a global shift towards “everywhere retailing”, ubiquitous contemporary information systems such as mobile CRM systems (C-CRMS) are evolving. Unlike in traditional CRMS, customers are becoming an important user group in this new paradigm. Draws on agility literature, this study examine how customers’ use of C-CRMS influence firm’s customer sensing capability, firm’s customer responding capability, and how customer-perceived firm’s responsiveness influence customers use of C-CRMS. Following the notions of agility we theorized firm’s customer agility from customers’ standpoint where we use customers’ use of CCRMS and customer-perceived firm’s responsiveness for sensing and responding components of agility respectively. This research-in-progress paper investigates how C-CRMS facilitates firm’s customer agility, and reports the approach pursued in adopting sense and response measures of customer agility taking the customers perspective derived through extant literature.
Structure and Anonymity of the Bitcoin Transaction Graph

The Bitcoin network of decentralized payment transactions has attracted a lot of attention from both Internet users and researchers in recent years. Bitcoin utilizes a peer-to-peer network to issue anonymous payment transactions between different users. In the currently used Bitcoin clients, the full transaction history is available at each node of the network to prevent double spending without the need for a central authority, forming a valuable source for empirical research on network structure, network dynamics, and the implied anonymity challenges, as well as guidance on the future evolution of complex payment systems. We found dynamical effects of which some increase anonymity while others decrease it. Most importantly, several parameters of the Bitcoin transaction graph seem to have become stationary over the last 12–18 months. We discuss the implications.
On detecting the large separation in the autocorrelation of stellar oscillation times series

Context. The observations carried out by the space missions CoRoT and Kepler provide a large set of asteroseismic data. Their analysis requires an efficient procedure first to determine if a star reliably shows solar-like oscillations, second to measure the so-called large separation, third to estimate the asteroseismic information that can be retrieved from the Fourier spectrum. Aims. In this paper we develop a procedure based on the autocorrelation of the seismic Fourier spectrum that is capable of providing measurements of the large and small frequency separations. The performance of the autocorrelation method needs to be assessed and quantified. We therefore searched for criteria able to predict the output that one can expect from the analysis by autocorrelation of a seismic time series. Methods. First, the autocorrelation is properly scaled to take into account the contribution of white noise. Then we use the null hypothesis H0 test to assess the reliability of the autocorrelation analysis. Calculations based on solar and CoRoT time series are performed to quantify the performance as a function of the amplitude of the autocorrelation signal. Results. We obtain an empirical relation for the performance of the autocorrelation method. We show that the precision of the method increases with the observation length, and with the mean seismic amplitude-to-background ratio of the pressure modes to the power 1.5 ± 0.05. We propose an automated determination of the large separation, whose reliability is quantified by the H0 test. We apply this method to analyze red giants observed by CoRoT. We estimate the expected performance for photometric time series of the Kepler mission. We demonstrate that the method makes it possible to distinguish � = 0 from � = 1 modes. Conclusions. The envelope autocorrelation function (EACF) has proven to be very powerful for the determination of the large separation in noisy asteroseismic data, since it enables us to quantify the precision of the performance of different measurements: mean large separation, variation of the large separation with frequency, small separation and degree identification.
2015 Ieee International Conference on Big Data (big Data) Exos: Expansion on Session for Enhancing Effectiveness of Query Auto-completion

—Query auto-completion (QAC) is an important feature of a search system that helps users reach their target queries faster. Personalization is a powerful technique that improves the relevance of QAC to the current query. This paper proposes a novel framework, EXOS, to augment the native query by important tokens in the user's search contexts to provide personalized auto-completions dynamically. EXOS is composed of three major steps: expansion, selection and boosting. Each token from the user's search contexts is evaluated and stored by EXOS. The tokens with the highest importance are chosen by the expansion step to augment the native query from the user. These augmented queries are used to retrieve QAC results. The selection and boosting models then extract qualified results, merge and re-rank these results based on their query importance to provide the user with a personalized QAC. We designed two large-scale experiments with over six million queries to evaluate the effectiveness of EXOS. Compared with an advanced MostPopularCompletion system, EXOS has 126% gain on Mean Reciprocal Rank (MRR) and 270% gain on Success Rate at Top-1 in a prefix-based experiment. EXOS shows 10.5% gain on first-token MRR and about 9% gain on Token Saved Rate in a token-based experiment. The results of our experiments show that EXOS significantly enhances the relevance of QAC by predicting the user's target query with using fewer keystrokes. I. INTRODUCTION Query auto-completion (QAC) is an important and integral feature of most modern search systems [1], [2]. One of the main functions provided by QAC is to predict the target query for a user when a search system receives the first few characters typed by her. This helps a user quickly populate and formulate her search queries via suggesting popular and well-known queries from the search system. Such QAC systems help reduce query ambiguity, and help users converge to their target queries faster. The underlying mechanism of most QAC systems calculates the most popular queries given the prefix of a query typed by a user in the search box [3]. The prefix here can be either incomplete or complete token(s). For example, if a user attempts to search for the target nike shoes in a search engine, an incomplete token can be ni and a complete token can be nike. As the user increases the length of her prefix, the
A Python Engine for Teaching Artificial Intelligence in Games

Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments, and our experiences using it in a class on Game Artificial Intelligence.
Tumor mRNA expression profiles predict responses to chemotherapy.

The development of prognostic and diagnostic markers suchastumorstagingandmorerecentlymolecularfactorshavegreatlycontributed to identifying lung cancer patients that can beneﬁtfrom adjuvant or neoadjuvant chemotherapy. However, the pre-dictingefﬁcienciesvaryconsiderably,andmanytherapiesfailwhilesurviving patients often experience severe toxicities. Moreover,patients displaying similar clinical characteristics often responddifferently to therapy, and this is likely a result of heterogeneity ofthe tumors’ genetic and epigenetic characteristics. The advent ofthe human genome sequencing project and the concurrent devel-opment of many genomic-based technologies, including expres-sion microarrays, have allowed scientists to explore the possibilityof using expression proﬁles to predict tumor drug sensitivity orresistance before treatment, and thereby select the best possibletherapies while decreasing the risk of toxicities for the patients.To this end, various gene signatures and sequence alterationintargetgeneshavebeenobtainedforpredictionofdrugresponsein patients. Examples include signatures for taxane/doxorubicinsensitivity in breast cancer,
A P 1 - P 1 Finite Element Method for a Phase Relaxation Model II: Adaptively Refined Meshes

We examine the effect of adaptively generated refined meshes on the P1 - P1 finite element method with semi-explicit time stepping of part I, which applies to a phase relaxation model with small parameter $\ep>0$. A typical mesh is highly graded in the so-called refined region, which exhibits a local meshsize proportional to the time step $\tau$, and is coarse in the remaining parabolic region where the meshsize is of order $\sqrt\tau$. Three admissibility tests guarantee mesh quality and, upon failure, lead to remeshing and so to incompatible consecutive meshes. The most severe test checks whether the transition region, where phase changes take place, belongs to the refined region. The other two tests monitor equidistribution of pointwise interpolation errors. The resulting adaptive scheme is shown to be stable in various Sobolev norms and to converge with a rate of order $\Or(\tau/\sqrt\ep)$ in the natural energy spaces. Several numerical experiments illustrate the scheme's efficiency and enhanced performance as compared with those of part I.
Isolation of male germ stem cell-like cells from testicular tissue of non-obstructive azoospermic patients and differentiation into haploid male germ cells in vitro.

BACKGROUND The purpose of this study was to establish the culture conditions required to isolate, identify and expand male germ stem cell-like cells (GSC-LC) from the testicular tissue of patients with non-obstructive azoospermia (NOA). METHODS AND RESULTS Testicular tissues obtained from patients (two with maturation arrest (MA, n = 2) and Sertoli cell-only syndrome (SCOS, n = 11) were dissociated and plated into gelatin-coated dishes. After 2-4 weeks, cultures from both MA patients (100%) and four SCOS patients (36.3%) exhibited multicellular colonies, which proliferated successfully until passage 10. GSC-LC in the colonies displayed alkaline phosphatase activity, as well as Oct-4 and integrin b1 expression after every passage. After the fifth passage, GSC-LC were differentiated by encapsulation in calcium alginate and further cultivation. At 2 and 6 weeks, cells expressed c-Kit, Scp3, testis-specific histone protein 2B (TH2B), and transition protein (TP)-1. Fluorescence in situ hybridization additionally disclosed a few tetraploid and haploid cells at 6 weeks. Human oocytes were activated in the absence of artificial activation and cleaved after the injection of presumptive spermatids. CONCLUSIONS Our novel culture system may be useful for diagnosing the existence of germ cells and facilitating the treatment of NOA patients.
Modern Texture Mapping in Computer Graphics

Textures have a variety of applications in computer graphics. While the original idea of texture mapping was just to cover the surface of an object with an image to avoid having to model every detail geometrically, in time a lot of other uses have been proposed. In this paper, the most important applications of texture mapping (except the original approach) will be explained.
FEAST As A Subspace Iteration Eigensolver Accelerated By Approximate Spectral Projection

The calculation of a segment of eigenvalues and their corresponding eigenvectors of a Hermitian matrix or matrix pencil has many applications. A new density-matrix-based algorithm has been proposed recently and a software package FEAST has been developed. The density-matrix approach allows FEAST's implementation to exploit a key strength of modern computer architectures, namely, multiple levels of parallelism. Consequently, the software package has been well received, especially in the electronic structure community. Nevertheless, theoretical analysis of FEAST has lagged. For instance, the FEAST algorithm has not been proven to converge. This paper offers a detailed numerical analysis of FEAST. In particular, we show that the FEAST algorithm can be understood as an accelerated subspace iteration algorithm in conjunction with the Rayleigh-Ritz procedure. The novelty of FEAST lies in its accelerator which is a rational matrix function that approximates the spectral projector onto the eigenspace in question. Analysis of the numerical nature of this approximate spectral projector and the resulting subspaces generated in the FEAST algorithm establishes the algorithm's convergence. This paper shows that FEAST is resilient against rounding errors and establishes properties that can be leveraged to enhance the algorithm's robustness. Finally, we propose an extension of FEAST to handle non-Hermitian problems and suggest some future research directions.