Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of Global and Local Attributional Similarities for Synonym Detection

In this paper, we present a new methodology for synonym detection based on the combination of global and local distributional similarities of pairs of words. The methodology is evaluated on the noun space of the 50 multiple-choice synonym questions taken from the ESL and reaches 91.30% accuracy using a conditional probabilistic model associated with the cosine similarity measure.
ISP-aided Biased Query Search for P2P systems in a Testlab

Summary. More than half of Internet traﬃc today is contributed by peer-to-peer (P2P) systems. P2P systems build their overlay topology largely agnostic of the Internet underlay, which often leads to traﬃc management challenges for Internet Service Providers (ISP) and potentially ineﬃcient neighborhood selection for P2P nodes. To overcome this, we propose to use an oracle hosted by the ISPs, so that ISPs and P2P users can cooperate for improved performance. The oracle can be queried by P2P nodes while choosing neighbors for content search, and it will rank the possible neighbors of the querying node according to a locality indication, like the AS-hop distance. The ISP gains by keeping traﬃc within its Autonomous System (AS, and the P2P node can experience improved performance like lesser delay and better bandwidth. In this paper, we evaluate the beneﬁts of our scheme by performing experiments in a real Testlab consisting of routers, switches and computers running actual instances of P2P applications. We show how we conﬁgure representative AS topologies for P2P networks using VLANs and trunking ports, and present experimental re-sults with content search phase of a P2P network using diﬀerent ﬁle sharing and search query distributions.
Shift-and-invert iteration for purely imaginary eigenvalues with application to the detection of Hopf Bifurcations in large scale problems

The detection of a Hopf bifurcation in a large scale dynamical system that depends on a physical parameter often consists of computing the right-most eigenvalues of a sequence of large sparse eigenvalue problems. This is not only an expensive operation, but the computation of right-most eigenvalues is often not reliable for the commonly used methods for large sparse matrices. In the literature a method has been proposed that computes a value of the parameter that corresponds to a Hopf point without actually computing right-most eigenvalues. This method utilises the Kronecker product and involves the solution of matrices of squared dimension, which is impractical for large scale applications. However, if good starting guesses are available for the parameter and the purely imaginary eigenvalue at the Hopf point, then efficient algorithms are available. In this paper, we propose a method for obtaining such good starting guesses, based on finding purely imaginary eigenvalues of a two-parameter eigenvalue problem (possibly arising after a linearisation process). The problem is formulated as an inexact inverse iteration method that requires the solution of a sequence of Lyapunov equations with low rank right hand sides. It is this last fact that makes the method feasible for large systems. The power of our method is tested on three numerical examples, one of which is a discretised PDE with two space dimensions.
Quality management of research, development and innovation activities in Finnish universities of applied sciences

ABSTRACT This study utilises the quality audit reports of Finnish Universities of Applied Sciences to describe the quality management of their research, development and innovation activities (RDI). The institutions are trying to find ways of enlarging the volume of RDI activities and this is clearly reflected in the ways in which they manage quality. Much of the focus lies on the project proposal preparation phase and strategic direction of resources, while less attention has been paid to monitoring and developing the quality of the output. These emphases are analysed in relation to Harvey & Green’s seminal notions on quality in an attempt to see how useful this theoretical framework is in explaining perceptions on quality in RDI activities. More research should be done on the conceptualisation of quality in especially non-university higher education sector.
Using the Stokes space for equalization of polarization impairments in digital coherent optical receivers

Random polarization rotations caused by residual fiber birefringence is an important physical effect in optical coherent systems employing polarization-division multiplexing. The specificity of the large penalties induced by polarization-related impairments make polarization-dedicated equalization subsystems mandatory for the design of flexible coherent receivers. It has recently been shown that 3-dimensional Stokes space based approaches can improve polarization demultiplexing and polarization dependent losses compensation task in coherent receivers, particularly in terms of convergence speed and transparency to higher-level M-ary signals. This paper reports recent advances on Stokes space based digital signal processing for coherent optical communications. The performance versus computation efforts of different methods used to compute a symmetry plane in the Stokes space, e.g. the geometric approach and Kalman filtering, is assessed for both polarization-dependent losses compensation and PolDemux subsystems. The applicability and robustness of the adaptive Stokes algorithm are tested in a scenario based on an ultra-dense WDM access network. Experimental results demonstrate the suitableness of Stokes PolDemux solution for metro and access networks with flexible transceivers based on higher-level M-ary signals.
On the Development of Speech Resources for the Mixtec Language

The Mixtec language is one of the main native languages in Mexico. In general, due to urbanization, discrimination, and limited attempts to promote the culture, the native languages are disappearing. Most of the information available about the Mixtec language is in written form as in dictionaries which, although including examples about how to pronounce the Mixtec words, are not as reliable as listening to the correct pronunciation from a native speaker. Formal acoustic resources, as speech corpora, are almost non-existent for the Mixtec, and no speech technologies are known to have been developed for it. This paper presents the development of the following resources for the Mixtec language: (1) a speech database of traditional narratives of the Mixtec culture spoken by a native speaker (labelled at the phonetic and orthographic levels by means of spectral analysis) and (2) a native speaker-adaptive automatic speech recognition (ASR) system (trained with the speech database) integrated with a Mixtec-to-Spanish/Spanish-to-Mixtec text translator. The speech database, although small and limited to a single variant, was reliable enough to build the multiuser speech application which presented a mean recognition/translation performance up to 94.36% in experiments with non-native speakers (the target users).
Radiation damage in a micron-sized protein crystal studied via reciprocal space mapping and Bragg coherent diffractive imaging

For laboratory and synchrotron based X-ray sources, radiation damage has posed a significant barrier to obtaining high-resolution structural data from biological macromolecules. The problem is particularly acute for micron-sized crystals where the weaker signal often necessitates the use of higher intensity beams to obtain the relevant data. Here, we employ a combination of techniques, including Bragg coherent diffractive imaging to characterise the radiation induced damage in a micron-sized protein crystal over time. The approach we adopt here could help screen for potential protein crystal candidates for measurement at X-ray free election laser sources.
Multiple isoforms of GAGA factor, a critical component of chromatin structure.

The GAGA transcription factor of Drosophila melanogaster is ubiquitous and plays multiple roles. Characterization of cDNA clones and detection by domain- specific antibodies has revealed that the 70-90 kDa major GAGA species are encoded by two open reading frames producing GAGA factor proteins of 519 amino acids (GAGA-519) and 581 amino acids (GAGA-581), which share a common N-terminal region that is linked to two different glutamine-rich C-termini. Purified recombinant GAGA-519 and GAGA-581 proteins can form homomeric complexes that bind specifically to a single GAGA sequence in vitro. The two GAGA isoforms also function similarly in transient transactivation assays in tissue culture cells and in chromatin remodeling experiments in vitro . Only GAGA-519 protein accumulates during the first 6 h of embryogenesis. Thereafter, both GAGA proteins are present in nearly equal amounts throughout development; in larval salivary gland nuclei they colocalize completely to specific regions along the euchromatic arms of the polytene chromosomes. Coimmunoprecipitation of GAGA-519 and GAGA-581 from crude nuclear extracts and from mixtures of purified recombinant proteins, indicates direct interactions. We suggest that homomeric complexes of GAGA-519 may function during early embryogenesis; both homomeric and heteromeric complexes of GAGA-519 and GAGA-581 may function later.
SHM: Scalable and Backbone Topology-Aware Hybrid Multicast

Application layer multicast (ALM) has been proposed as a promising alternative to the IP multicast due to the difficulties in deploying network layer multicast in an operational network at the Internet scale. However, most of existing application layer multicast approaches build their overlay networks based on simple measurement with the end-to-end delay without considering the physical network topology and IP multicast deploying in local scale on the Internet. Thus, they might suffer some inefficiency such as long join delay, large maintenance overhead, and little flexibility to extend. In this paper we propose a novel hybrid multicast approach named SHM, which combining ALM and IP multicast to achieve ubiquitous multicast delivery. Simulation results show that SHM is able to provide more efficient multicast with less maintenance overhead, higher flexibility and reliability.
Phonetic, idiolectal and acoustic speaker recognition

This paper describes a text-independent speaker recognition system that achieves an equal error rate of less than 1% by combining phonetic, idiolect, and acoustic features. The phonetic system is a novel language-independent speakerrecognition system based on differences among speakers in dynamic realization of phonetic features (i.e., pronunciation), rather than spectral differences in voice quality. The system exploits phonetic information from six languages to perform text-independent speaker recognition. The idiolectal system models speaker idiosyncrasies with word n-gram frequency counts computed from the output of an automatic speech recognition system. The acoustic system is a Gaussian Mixture Model-Universal Background Model that exploits the spectral differences in voice quality. All experiments were performed on the NIST 2001 Speaker Recognition Evaluation Extended Data Task.
Best-First and Depth-First Minimax Search in Practice

Most practitioners use a variant of the Alpha-Beta algorithm, a simple depth-first pro- cedure, for searching minimax trees. SSS*, with its best-first search strategy, reportedly offers the potential for more efficient search. However, the complex formulation of the al- gorithm and its alleged excessive memory requirements preclude its use in practice. For two decades, the search efficiency of "smart" best-first SSS* has cast doubt on the effectiveness of "dumb" depth-first Alpha-Beta. This paper presents a simple framework for calling Alpha-Beta that allows us to create a variety of algorithms, including SSS* and DUAL*. In effect, we formulate a best-first algorithm using depth-first search. Expressed in this framework SSS* is just a special case of Alpha-Beta, solving all of the perceived drawbacks of the algorithm. In practice, Alpha-Beta variants typically evaluate less nodes than SSS*. A new instance of this framework, MTD(f), out-performs SSS* and NegaScout, the Alpha-Beta variant of choice by practitioners.
Application of the discrete Haar wavelet transform to image fusion for nighttime driving

Infrared images can often provide information missing in visible images in a night driving system, but infrared images lack key features needed to operate a vehicle. Image fusion techniques can be used to combine the relevant information from both the visible and infrared images. The need for high frame rates in an automotive application motivates the investigation into computationally simple methods of combining the visible and infrared images. In this paper we present a computationally simple image fusion technique based on the discrete Haar wavelet transform and apply the technique to combine three images from cameras operating in different wavelength bands.
Behavioral Coding of Therapist Language in Addiction Counseling Using Recurrent Neural Networks

Manual annotation of human behaviors with domain speciﬁc codes is a primary method of research and treatment ﬁdelity evaluation in psychotherapy. However, manual annotation has a prohibitively high cost and does not scale to coding large amounts of psychotherapy session data. In this paper, we present a case study of modeling therapist language in addiction counseling, and propose an automatic coding approach. The task objective is to code therapist utterances with domain spe-ciﬁc codes. We employ Recurrent Neural Networks (RNNs) to predict these behavioral codes based on session transcripts. Experiments show that RNNs outperform the baseline method us-ing Maximum Entropy models. The model with bi-directional Gated Recurrent Units and domain speciﬁc word embeddings achieved the highest overall accuracy. We also brieﬂy discuss about client code prediction and comparison to previous work.
Multichannel recording and stimulation of neuronal cultures grown on microstamped poly-D-lysine

We report progress toward designable, reproducible, patterned in vitro neuronal cultures. Cell adhesive proteins were directly microcontact printed on microelectrode arrays (MEAs) used as substrates for hippocampal neurons grown in a defined culture medium. The patterned neuronal network circuits were maintained up to one month. The recorded activity was comparable to that of cultures grown on unpatterned uniform surfaces. Time-locked evoked responses were recorded across the networks.
Sip Registration Copyright Notice

Status of this Memo This document is an Internet-Draft and is in full conformance with all provisions of Section 10 of RFC2026. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet-Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as " work in progress. " The list of current Internet-Drafts can be accessed at Abstract SIP registration provides personal, pre-call terminal and service mobility. We describe the registration process in detail, considering different options for roaming users.
Double Dose: High Family Conflict Enhances the Effect of Media Violence Exposure on Adolescents’ Aggression

We investigated how exposure to media violence and family conflict affects adolescents’ subsequent aggressive behavior. We expected a double dose effect, meaning that high media violence exposure would lead to higher levels of aggression for adolescents in high conflict families compared to low conflict families. A total of 499 adolescents (aged 10 to 14, 48% girls) participated in a two-wave longitudinal survey (4-month interval). Survey questions assessed their exposure to violence on television and in electronic games, family conflict, and aggressive behavior. Analyses revealed a significant interaction between media violence and family conflict. In families with higher conflict, higher media violence exposure was related to increased subsequent aggression. This study is the first to show a double dose effect of media violence and family conflict on adolescents’ aggression. These findings underscore the important role of the family in shaping the effects of adolescents’ media use on their social development.
Stochastic Games for the Smart Grid Energy Management With Prospect Prosumers

In this paper, the problem of the smart grid energy management under stochastic dynamics is investigated. In the considered model, at the demand side, it is assumed that customers can act as prosumers who own renewable energy sources and can both produce and consume energy. Due to the coupling between the prosumers’ decisions and the stochastic nature of renewable energy, the interaction among prosumers is formulated as a stochastic game, in which each prosumer seeks to maximize its payoff, in terms of revenues, by controlling its energy consumption and demand. In particular, the subjective behavior of prosumers is explicitly reflected into their payoff functions using the prospect theory, a powerful framework that allows modeling real-life human choices, rather than objective, user-agnostic decisions, as normative models do. For this prospect-based stochastic game, it is shown that there always exists a stationary Nash equilibrium where the prosumers’ trading policies in the equilibrium are independent of the time and their histories of the play. Moreover, to obtain one of such equilibrium policies, a novel distributed algorithm with no information sharing among prosumers is proposed and shown to converge to an $\epsilon$-Nash equilibrium in which each prosumer is able to achieve its optimal payoff in an equilibrium up to a small additive error $\epsilon$. On the other hand, at the supply side, the interaction between the utility company and the prosumers is formulated as an online optimization problem in which the utility company's goal is to learn its optimal energy allocation rules. For this case, it is shown that such an optimization problem admits a no-regret algorithm meaning that regardless of the actual outcome of the game among the prosumers, the utility company can follow a strategy that mitigates its allocation costs as if it knew the entire demand market a priori. Simulation results justify the convergence of the proposed algorithms and present new insights toward more efficient energy management in the smart grids.
Eliciting and prioritizing quality requirements supported by ontologies: a case study using the ElicitO framework and tool

As software complexity grows and clients demand higher quality software, quality requirements can no longer be considered to be of secondary importance. Thus, eliciting, specifying, prioritizing and validating quality requirements is a prerequisite to the development of effective and efficient information systems. Despite the critical importance of quality requirements, there is a considerable gap in the breadth and depth of quality requirements engineering (RE) support in most RE approaches. In practice, it is often the case to have quality requirements considered as an afterthought in the systems development process. While there is a wealth of modelling techniques and tools for functional requirements, there is very limited support for quality requirements in RE. Support for quality requirements is usually ad‐hoc, without clear guidelines on how to capture, specify and manage quality requirements and also without proper usage of standardized terminologies based on established quality models such as the ISO/IEC 9126 quality model. In this paper, we discuss a quality‐driven RE framework and tool that applies knowledge management techniques and quality ontologies to support RE activities. The ontology implements the quality characteristics and metrics prescribed by the ISO/9126 quality model, providing a common vocabulary to address quality concerns/aspects across RE activities. We empirically validate how the framework and tool can be used to effectively support the requirements elicitation and prioritization activities through a case study addressing the development of an intranet portal project at the University of Manchester.
Mapping Tasks to Processors at Run-time

We consider the dynamic task allocation problem in multicomputer system with multiprogramming. Programs are given as task interaction graphs that have to be mapped onto the processors at run-time. We propose a fast two-phase heuristic algorithm where phase 1 performs a hierarchic clustering of the tasks which is used by the second phase to map clusters of suitable size onto free partitions of the processor graph.
Mortality and Life-Cycle Models

I compare two different ways of integrating mortality into life-cycle models: the standard additive model with time preferences, on the one hand, and a formulation that rules out the existence of time preference, but allows for risk aversion with respect to the length of life, on the other hand. These models are of similar complexity, but rather different in their fundamental assumptions. I show, however, that the latter formulation can reproduce all the predictions of the additive models with non-negative rates of time preference, as far as life-cycle behaviors under a single exogenous non-degenerate mortality pattern are considered. It leads, nonetheless, to radically different predictions for the effects of mortality changes.
Nondeterministic Extensions of the Strong Exponential Time Hypothesis and Consequences for Non-reducibility

We introduce the Nondeterministic Strong Exponential Time Hypothesis (NSETH) as a natural extension of the Strong Exponential Time Hypothesis (SETH). We show that both refuting and proving NSETH would have interesting consequences. In particular we show that disproving NSETH would give new nontrivial circuit lower bounds. On the other hand, NSETH implies non-reducibility results, i.e. the absence of (deterministic) fine-grained reductions from SAT to a number of problems. As a consequence we conclude that unless this hypothesis fails, problems such as 3-SUM, APSP and model checking of a large class of first-order graph properties cannot be shown to be SETH-hard using deterministic or zero-error probabilistic reductions.
Automated Unit Testing Tool for .Net Framework

Developers use unit testing to improve the quality of software systems. Current development tools for unit testing help with automating test execution, with reporting results, and with generating test stubs. However, they offer no aid for designing tests aimed specifically at exercising the effects of changes to a program. This paper describes a unit testing tool that makes writing unit tests Easier and more efficient by introducing an open source unit testing tool for the . NET Framework. Unit testing is tightly associated with test-driven development (TDD), refactoring, and other practices from agile software development approaches such as Extreme Programming or Scrum [19, 20]. The tool provides developers with the Standard unit testing features such as test, fixture, setup, teardown, ignores, expected exception, etc. The tool has an easy graphical user interface to facilitate to the user the testing process. The tool also has a lot of advanced features like the Recipes which make the user able to combine several test assemblies into one test suite plus the Search capabilities across tests, output, and statistics and also generates Statistics per test to create performance base line and grouping tests by categories for execution and works with any . Net language.