Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvements in the time complexity of two message-optimal election algorithms

Algorithms for election in asynchronous general networks and in synchronous rings are presented. The algorithms are message-optimal, and their time behavior is significantly improved over currently available algorithms. In asynchronous general networks we , present a O([W]+nlogn)-messages, O(n log n ) t ime algorithm, where n is the number of nodes, and IE] is the number of links in the network. For synchronous rings, we propose two algorithms. The first works in O(n) -messages, and O(n2n+lTI 2) time, where IT[ is the cardinality of the set of the node identifiers. The second works in O(n log*n) messages and O(o~-l(log*n)[ T[),time, where oF10 is the functional inverse of log . By contrast, the time behavior of previously known algorithms is exponential in ]T], for fixed n .
Reality Television and the Doing of Hyperauthentic Masculinities

This study examines American masculinity as constructed in 136 reality television programs airing between 1948 and 2016 with an all-male or predominately male cast. We argue that televised reality programs reveal a new form of hegemonic American masculinity, namely, hyperauthentic masculinity. Hyperauthentic masculinity appears to be grounded in essential male traits, but is rather a reflexive process allowing White male viewers to imagine (re)creating a White male utopia in which they have economic and cultural dominance. Unlike previous studies that claim that reality television allows men to escape into a frontier masculinity of the past, we argue these programs encourage White men today to actively do masculinity and, more important, to believe doing hegemonic masculinity is desirable and worth fighting for.
Characterization of MU-MIMO Channels Using the Spectral Divergence Measure

In this work we apply the spectral divergence to characterize the (dis-)similarity of different links in wide-band multi-user multiple-input multiple-output (MU-MIMO) channels. The spectral divergence measures the distance between strictly positive, non-normalized spectral densities, such as the power delay profile. The measurement data has been acquired using Eurecom’s MIMO Openair Sounder (EMOS). The EMOS can perform real-time MIMO channel measurements synchronously over multiple users. For this work we have used a line-of-sight measurement with two transmit antennas and two users with two antennas each. We compare the spectral divergence of different links with respect to the distance of the users. We find that the spectral divergence can be quite low when the users are close together. These findings are important for MU-MIMO precoding and scheduling algorithms. 1
Resettled Burmese Refugee Youths’ Identity Work in an Afterschool STEM Learning Setting

ABSTRACT Youth from nondominant racial and linguistic backgrounds often have limited access to school science learning opportunities. Afterschool settings may provide learning environments in which they improve science knowledge and construct positive science identities. With this premise, our research team designs and provides a community-based afterschool program that engages resettled Burmese refugee youth in Science, Technology, Engineering, and Mathematics (STEM) learning. In this article, the authors seek to understand how refugee youth utilize their funds of knowledge and what identities were foregrounded in the program. The authors adapt a microethnographic perspective in their research and review video recordings of participants’ engagement through multimodal discourse analysis. Their analysis suggests that youth crafted creative ways to participate in the science discourse, such as (1) blending joking and laughter with science discourse to negotiate their identities with each other and with an otherwise intimidating discourse, (2) utilizing place-based ethnic practices and knowledge in participating in science discourses, and (3) coordinating turn taking and responding to others’ ideas that makes the learning environment safe and inviting to all. The authors discuss insights that can potentially advance our understanding of refugee youth identities and transform our ways of supporting their science learning.
ProZed: a multilingual prosody editor for speech synthesis

I present an overview of ProZed an aid for developing prosody rules for speech synthesis using the MOMEL and INTSINT algorithms and interfaced with the MBROLA, MBROLIGN and Praat programs. It allows the interactive editing of a symbolic representation of an utterance in any of the twenty languages and dialects for which an MBIPOLA diphone database is currently available. ProZed defines a number of different levels of representation of varying abstraction. At the lowest level, representations are a specification of the identity of each phonemic segment together with its prosodic characteristics. More abstract representations allow the user to abstract away from speaker-specific characteristics in order to concentrate on the meaningful content of the utterance's prosody. It is evident that no tool is entirely innocent of theoretical bias and the tools described here are no exception to this rule. ProZed is, however, designed to be as theory-independent as possible so that it could be used to describe intonation patterns in a number of different frameworks with the ultimate aim of providing a framework that could be used to evaluate competing models of prosody. The program is currently implemented as a set of Perl scripts.
Bootstrapping a Compiler for an Equation-Based Object-Oriented Language

What does it mean to bootstrap a compiler, and why do it? This paper reports on the first bootstrapping of a full-scale EOO (Equation-based Object-Oriented) modeling language such as Modelica. Bootstrapping means that the compiler of a language can compile itself. However, the usual application area for the Modelica is modeling and simulation of complex physical systems. Fortunately it turns out that with some minor extensions, the Modelica language is well suited for the modeling of language semantics. We use the name MetaModelica for this slightly extended Modelica. This is a prerequisite for bootstrapping which requires that the language can be used to model and/or implement itself. The OpenModelica Compiler (OMC) has been written in this MetaModelica language. It originally supported only the standard Modelica language but has been gradually extended to also cover the MetaModelica language extensions. After substantial work, OMC is able to quickly compile itself and produces an executable with good performance. The benefits include a more extensible and maintainable compiler by introducing improved language constructs and a more powerful runtime that makes it easy to add functionality such as parser generators, debuggers, and profiling tools. Future work includes extracting and restructuring parts of OMC, making the compiler smaller and more modular and extensible. This will also make it easier to interface with OMC, making it possible to create more powerful and user-friendly OpenModelica-based tools. The compiler and its bootstrapping is a major effort -- it is currently about 330 000 lines of code, and the MetaModelica extensions are used routinely by approximately ten developers on a daily basis.
The long-term impact of stroke on cognition: Prevalence, predictors and assessment

Stroke is indiscriminate and has the potential to erase a lifetime of experiences or abilities in an instant. Given that stroke sequelae can have long-lasting consequences, with many stroke survivors experiencing ongoing adverse effects several years later, there is mounting evidence supporting stroke not only as an acute but also as a chronic medical condition. Cognitive impairment is a frequently reported symptom post stroke, occurring in more than two thirds of stroke patients. Unlike physical impairments which can often recover following stroke, cognitive impairment becomes increasingly worse over time resulting in poor prognosis. Moreover, symptoms commonly associated with cognitive impairment are often overlooked, leading to increased rates of admission to private hospitals and higher rates of mortality. This is further complicated by the fact that assessment of post stroke cognitive function is not routinely carried out therefore prevalence of cognitive deficits may be underestimated. Existing data on long-term outcomes specific to stroke are scarce in NZ, particularly in terms of cognition. The purpose of this thesis was to determine prevalence, profiles, predictors, and trajectory of cognitive impairment in a cohort of four-year stroke survivors in NZ. Additionally, this thesis also sought to determine the accuracy of a screening tool to detect post stroke cognitive impairment. This population-based follow-up study adopts a quantitative approach and includes a sample drawn from the fourth Auckland Regional Stroke Outcomes Study (ARCOSIV). Two and hundred and fifty-seven people with stroke, completed cognitive assessments at baseline or within two weeks of stroke, and/or 1 month, 6, 12 and 48 months after stroke onset. At four years post-stroke, the greatest proportion (84%) of stroke survivors exhibited below average cognitive functioning as assessed by the Montreal Cognitive Assessment Scale (MoCA) (M = 20.7, ± 4.70). Specific domains of cognition most affected by chronic stroke included attention, memory, information processing speed and executive functioning. While there was some recovery of cognitive function within the first 12 months, cognition steadily declined from this time-point to four-years. Regression analysis revealed baseline predictors including; older age (>75 years), male gender, not working, greater cognitive impairment at baseline and stroke-related vascular risk factors (i.e. hypertension, diabetes mellitus and arrhythmia) were associated with declining cognition over the four-year period. Vascular territory and stroke subtype as
Prediction of Off-Target Drug Effects Through Data Fusion

We present a probabilistic data fusion framework that combines multiple computational approaches for drawing relationships between drugs and targets. The approach has special relevance to identifying surprising unintended biological targets of drugs. Comparisons between molecules are made based on 2D topological structural considerations, based on 3D surface characteristics, and based on English descriptions of clinical effects. Similarity computations within each modality were transformed into probability scores. Given a new molecule along with a set of molecules sharing some biological effect, a single score based on comparison to the known set is produced, reflecting either 2D similarity, 3D similarity, clinical effects similarity or their combination. The methods were validated within acurated structural pharmacology database (SPDB) and further tested by blind application to data derived from the ChEMBL database. For prediction of off-target effects, 3D-similarity performed best as a single modality, but combining all methods produced performance gains. Striking examples of structurally surprising off-target predictions are presented.
Computer Simulation and Recognition of Foundation Loading Based on Differential Evolution Algorithm and Finite Element Method

Research of foundation bearing capacity possesses significant value of theory and construction. As the calculation assumed conditions of ultimate bearing capacity of classic foundation are so many and the soil parameters are indeterminate, we exploit a foundation loading simulation program based on difference evolution(DE) algorithm and finite element method(FEM) in this paper, which we can simulate foundation loading test and identify actual soil parameters. Based on the discussion of algorithm and calculation course, we carried out research and demonstration of simple examples, the outcome of ultimate bearing capacity and analytical results comparatively accord. We identified the elastic modulus of stuff within two soil layers by using DE algorithm and got good recognition accuracy and favorable convergence performance. The work in this paper is with active meaning for the further research of complex foundation bearing capacity and mechanics behavior analysis.
Integration of reactive navigation with a flexible parallel hardware architecture

AuRA (autonomous robot architecture), a hybrid, schema-based software architecture encompassing aspects of both deliberative and reactive control is described. A flexible, real-time, message-passing hardware platform for the development of AuRA and other software architectures is also presented. To demonstrate their flexibility and portability, they were integrated within a very short period to be used in a mobile robot competition. The experience confirmed the advantages of onboard computational capability in mobile systems. <<ETX>>
MuPADLibrary for Symbolic Computation with PolynomialMatrices Petr Augusta 2005

This diploma thesis comes with a freely available library for symbolic computation with polynomials and polynomial matrices, named Polmat. The Polmat library is developed for MuPAD, which is an easily accessible efficient computer algebra system and programming language. MuPAD does not contain functions used for design and analysis of control systems, therefore, an endeavour to make them arose. Solvers for linear equations with polynomials and polynomial matrices, spectral factorization of polynomials and polynomial matrices and others have been implemented. This document contains introduction into polynomial matrix computation and basic usage of computer algebra systems, syntax of implemented functions and procedures, description of usedmethods, demonstrative examples and results of computational testing.
A Dynamic Data Structure for Parsing of Discontinuous Constituents

Research has shown that natural language parsing allowing discontinuous constituents is linguistically well-motivated but computationally expensive. In particualr, the time needed to store and query existing subparses can become prohibitive as the length of the string increases. This reports presents a chart data structure that efficiently supports both of these intermediate operations. Our design limits the number of gaps allowed in any single constituent and models chart queries as instances of the range query problem. We present the range tree, an existing dynamic data structure for range queries, and modify it to better support parsing with discontinuity. We show how our chart data structure can be applied to synchronous and monolingual parsing, and compare it with previous solutions for the monolingual case. Implementations of the modified range tree and of discontinuous parse charts are available in the GenPar toolkit at http://nlp.cs. nyu.edu/GenPar/.
The link between perceived high-performance work practices, employee attitudes and service quality

PurposeThe purpose of this paper is to focus on the Greek banking sector and examine the indirect effects of high-performance work systems (HPWS) on service quality. Specifically, this study examines the effects of employees’ perceptions of HPWS on their trust toward their managers, as well as on service quality, through the mediating role of employee outcomes (measured by job satisfaction and affective commitment). In addition, trust is also tested for its role as a potential mediator and moderator in the relationship between HPWS and employee outcomes.Design/methodology/approachPartial least squares structural equation modeling was used on a sample of 350 front-line employees working in the Greek banking sector.FindingsThe findings showed that employee outcomes mediated the relationship between HPWS and service quality. On the other hand, although trust mediated the relationship between HPWS and employee outcomes, no support was found for its moderating effect. Finally, although not included in the initial analysis, trust was found to play a mediating and moderating role in the relationship between HPWS and service quality.Practical implicationsThis study highlights the vital role that a “trusting” work environment has to play on employee attitudes and outcomes. As this study shows, the positive employee behaviors along with their willingness to accept and support organizational goals influence their level of productivity.Originality/valueThis study sheds lights on the mediating and moderating role of trust in the relationship between HPWS, employee outcomes, and service quality. Finally, implications are drawn for organizations, managers, and practitioners.
Automatic Extraction of Subcategorization Frames from Spoken Corpora

We built a system for automatically extracting subcategorization frames (SCFs) from corpora of spoken language. The acquisition system, based on the design proposed by Briscoe & Carroll (1997) consists of a statistical parser, a SCF extractor, an English lemmatizer, and a SCF evaluator. These four components are applied in sequence to retrieve SCFs associated with each verb predicate in the corpus. An initial experiment, based on a sample of 14 verb types and 330 verb tokens, tests the hypothesis that this will work acceptably for spoken language. The current prototype system achieves accuracy (type precision and recall and token recall) comparable to previous systems that work with written corpora.
Microscopic quantum superpotential in N=1 gauge theories

We consider the = 1 super Yang-Mills theory with gauge group U(N), adjoint chiral multiplet X and tree-level superpotential Tr W(X). We compute the quantum effective superpotential Wmic as a function of arbitrary off-shell boundary conditions at infinity for the scalar field X. This effective superpotential has a remarkable property: its critical points are in one-to-one correspondence with the full set of quantum vacua of the theory, providing in particular a unified picture of solutions with different ranks for the low energy gauge group. In this sense, Wmic is a good microscopic effective quantum superpotential for the theory. This property is not shared by other quantum effective superpotentials commonly used in the literature, like in the strong coupling approach or the glueball superpotentials. The result of this paper is a first step in extending Nekrasov's microscopic derivation of the Seiberg-Witten solution of = 2 super Yang-Mills theories to the realm of = 1 gauge theories.
The Measurement of Data Locations in the Cloud

If a company uses cloud computing services to process their employees or their customers personal data, they need to ensure that the cloud provider complies with the relevant privacy statues. One of the things that need to be ensured is that all personal data are processed only in lawful locations. Data sources that can be used to automatically determine the current location of data processing could help cloud users to ful fill their duty and to strengthen the confidence in a privacy friendly processing of their personal data. For that, data location metrics need to be defined, appropriate data sources need to be determined and the measured data need to be combined reasonable. This paper describes the procedure and system architecture of such data location metrics.
Co-axial fed double L-slot microstrip patch antenna array for WiMAX and WLAN application

In this paper, a co-axial fed double L-shaped slotted micro-strip patch antenna array is proposed for multi-band operation satisfying WLAN (Wireless Local Area Network) and WiMAX (Worldwide interoperability for Microwave Access) application. A single micro-strip rectangular patch antenna is designed with center frequency at 3.6 GHz for WiMAX application and it also reduces the resonance frequency using double L-slot on the patch from 3.6 GHz to 2.6 GHz, which is also suitable for WLAN (IEEE 802.11b standard frequencies from 2.23 GHz to 5.35 GHz) applications. A measured 7 dB gain is achieved with array (1×2) antenna. The bandwidth is increased up to 60% at upper band of operating frequencies than the single patch antenna. The simulation results such as radiation pattern, VSWR, gain, and return loss are simulated using Ansoft HFSS. Measured and simulated results of return loss for both single patch and array antenna are analyzed and presented.
Hybrid Mechanism : Structural Model and Empirical Analysis ∗

We study a hybrid mechanism that combines auction and lottery to allocate indivisible goods. One advantage of hybrid mechanism is to balance e ciency, revenue, and equality. In this model, players self-select into a multi-unit auction with unknown number of bidders. We characterize one symmetric Bayesian Nash equilibrium where auction participants use a monotone bid function. Based on this equilibrium, we identify structural primitives of the model from observables, from which we are able to quantify various performance measures. We then apply the model to analyze the hybrid mechanism adopted in Guangzhou to allocate new vehicle licenses. With this application in mind, we develop a by-period estimation method to balance modelt and interpretability of estimation results. Our analysis shows that Guangzhou's practice increases equality by 10-fold at a cost of $1.45 million revenue every month.
A Sampling Oscilloscope Based System with Active RF/IF Load-pull for Multi-Tone Non-linear Device Characterization

This paper presents a fully automated measurement system based around a Tektronix sampling oscilloscope. The system is capable of measuring calibrated time domain voltage and current waveforms at the device plane. A novel active load-pull loop is incorporated which has proved very useful for increasing the speed of multi-tone device characterization, moreover the architecture opens up the possibility of multi-tone load pull measurements, novel concepts are discussed which explain how the system can be used to perform non-linear device characterization in real time, the system also incorporates an intermediate frequency (IF) test set to measure the complete waveforms, which could be useful in characterization of memory effects. Triggering issues of sampling oscilloscopes are discussed in some detail along with a novel sampling approach which allows for more efficient measurement of multi-tone waveforms. Some interesting applications of the system are also introduced.
Closed-loop dialog model of face-to-face communication with a photo-real virtual human

We describe an advanced Human Computer Interaction (HCI) model that employs photo-realistic virtual humans to provide digital media users with information, learning services and entertainment in a highly personalized and adaptive manner. The system can be used as a computer interface or as a tool to deliver content to end-users. We model the interaction process between the user and the system as part of a closed loop dialog taking place between the participants. This dialog, exploits the most important characteristics of a face-to-face communication process, including the use of non-verbal gestures and meta communication signals to control the flow of information. Our solution is based on a Virtual Human Interface (VHI) technology that was specifically designed to be able to create emotional engagement between the virtual agent and the user, thus increasing the efficiency of learning and/or absorbing any information broadcasted through this device. The paper reviews the basic building blocks and technologies needed to create such a system and discusses its advantages over other existing methods.
Text Data Mining: Theory and Methods

This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of some of the interesting challenges that remain to be solved within the area. Finally, the articles serves as a very rudimentary tutorial on some of techniques while also providing the reader with a list of references for additional study.