Miracle-dz/UniFAR-FTUs huggingface dataset:
Lexical Sophistication as a Multidimensional Phenomenon: Relations to Second Language Lexical Proficiency, Development, and Writing Quality

Abstract: This study conceptualizes lexical sophistication as a multidimensional phenomenon by reducing numerous lexical features of lexical sophistication into 12 aggregated components (i.e., dimensions) via a principal component analysis approach. These components were then used to predict second language (L2) writing proficiency levels, holistic lexical proficiency scores, and longitudinal lexical growth. The results from regression analyses indicated that 5 lexical components (i.e., bigram and trigram strength of directional association, content word properties, bigram mutual information, bigram and trigram proportions, and word specificity) explained 16.1% and 31.0% of the variance of L2 writing proficiency and lexical proficiency, respectively. Two additional components (i.e., word acquisition properties and content word frequency) explained an additional 8.5% of the variance of L2 writing proficiency. Six lexical components (i.e., bigram and trigram proportions, word acquisition properties, content word frequency, bigram frequency and range, content word properties, and function word frequency and range) showed significant developmental trends in L2 beginning learners over a year‐long period. These findings provide information about the multidimensional nature of lexical sophistication by expanding its scope beyond frequency and toward other primary dimensions that include various lexical and phrasal features such as concreteness, orthographic density, hypernymy, and n‐gram frequency and association strength. [ABSTRACT FROM AUTHOR]
PRIME: private RSA infrastructure for memory-less encryption

Cold boot attacks exploit the fact that data in RAM gradually fades away over time, rather than being lost immediately when power is cycled off. An attacker can gain access to all memory contents by a restart or short power-down of the system, a so called cold boot. Consequently, sensitive data in RAM like cryptographic keys are exposed to attackers with physical access. Research in recent years found software-based solutions to the cold boot problem in terms of CPU-bound or memory-less encryption. To date, however, the focus has been set on symmetric ciphers, particularly concerning disk encryption systems. Contrary to that, the work in hand aims to close the gap to asymmetric ciphers. With PRIME, we present a cold boot resistant infrastructure for private RSA operations. All private RSA parameters reside symmetrically encrypted in RAM and are decrypted only within CPU registers. The modular exponentiation algorithm for RSA is implemented entirely on the CPU, such that no sensitive state of RSA ever goes to RAM.
The gendered emotional labor of male professional ‘freesurfers’ digital media work

Abstract Male professional ‘freesurfers’ are paid to live an aspirational lifestyle and communicate this through their digital media work. In this article I argue that a ‘stoke imperative’ championed by the surf industry necessitates emotional labour. Stoke is surf vernacular for a clustering of feeling thrilled, joyful, pleased, happy, optimistic, excited and satisfied. The surf industry manufactures and commodifies stoke to profit from it. Emotional labour is often assumed to be what women are ‘naturally’ predisposed to and ‘better at’. It is found that male professional freesurfers are competent at employing strategies for doing emotional labour when doing digital media work, such as micro-celebrity. However, this involves negotiating expectations, traits, and values of masculinity. It is also found that digital media technologies direct a professional sport ‘technosoma’ that networks emotional labour for profit. The article extends a small body of literature on how emotional labour is practised by men in sport.
Dynamic heterogeneities in the out-of-equilibrium dynamics of simple spherical spin models.

The response of spherical two-spin interaction models, the spherical ferromagnet (s-FM) and the spherical Sherrington-Kirkpatrick (s-SK) model, is calculated for the protocol of the so-called nonresonant hole burning (NHB) experiment for temperatures below the respective critical temperatures. It is shown that it is possible to select dynamic features in the out-of-equilibrium dynamics of both models, one of the hallmarks of dynamic heterogeneities. The behavior of the s-SK model and the s-FM model in three dimensions is very similar, showing dynamic heterogeneities in the long-time behavior, i.e., in the aging regime. The appearance of dynamic heterogeneities in the s-SK model explicitly demonstrates that these are not necessarily related to spatial heterogeneities. For the s-FM model, it is shown that the nature of the dynamic heterogeneities changes as a function of dimensionality. With the increasing dimension, the frequency selectivity of the NHB diminishes and the dynamics in the mean-field limit of the s-FM model becomes homogeneous.
Multi-objective test generation for software product lines

Software Products Lines (SPLs) are families of products sharing common assets representing code or functionalities of a software product. These assets are represented as features, usually organized into Feature Models (FMs) from which the user can configure software products. Generally, few features are sufficient to allow configuring millions of software products. As a result, selecting the products matching given testing objectives is a difficult problem. The testing process usually involves multiple and potentially conflicting testing objectives to fulfill, e.g. maximizing the number of optional features to test while at the same time both minimizing the number of products and minimizing the cost of testing them. However, most approaches for generating products usually target a single objective, like testing the maximum amount of feature interactions. While focusing on one objective may be sufficient in certain cases, this practice does not reflect real-life testing situations. The present paper proposes a genetic algorithm to handle multiple conflicting objectives in test generation for SPLs. Experiments conducted on FMs of different sizes demonstrate the effectiveness, feasibility and practicality of the introduced approach.
Inferring likely data invariants of distributed systems

Distributed systems are difficult to debug and understand. One key reasons for this is distributed state, which is not easily accessible and must be pieced together from the state at the individual nodes. Developers have few tools to help them extract and reason about distributed state. By contrast, the state of a sequential program is well defined (e.g., stack and heap), easy to inspect (e.g., with breakpoints) and can be checked for correctness (e.g., by asserting invariants). In this poster and demo1 we describe a systems analysis tool called DInv2. DInv use a combination of static and dynamic analyses to identify and record at runtime the sets of concrete values for node variables that make up distributed state in a distributed system. It then determines consistent snapshots of distributed state in the system and uses the Daikon tool [2] to infer likely data relations, or invariants, over the tracked variables. The inferred data invariants relate variables at different nodes in the system and can be used in a variety of ways. For example, they can improve developer understanding of their systems and can be used by test-case generation techniques to more effectively drive the system towards invalid states (i.e., states that violate a mined invariant). They can be also used for debugging: a mined invariant that violates the system’s specifications can be tracked back to observed concrete values, which may help in reproducing an execution that led to an incorrect state of the system. For example, consider a two phase commit protocol in which the coordinator first queries other nodes for their vote and if all nodes, including the coordinator, voted “Commit” then the coordinator broadcasts a “TX Commit”, otherwise it broadcasts a “TX Abort”. At the end of this protocol all nodes should either commit or abort. To check if the algorithm is correct, developers can examine the DInv-inferred distributed state invariants for a set of executions. In this case a developer can check whether DInv mines the invariant coordinator.commit = replicai.commit for each replica i in the system (i.e., commit state at all nodes should be identical). The DInv tool is implemented in Go3 and works on systems written in Go. We have applied DInv to a Go implementation of the Raft consensus algorithm [4] by HashiCorp4. With minimal instrumentation of the source code we are able to detect basic invariants about the system regarding whether or not multiple leaders are active at the same time and the number of active nodes in the system.
Free Deconvolution for MIMO Capacity Estimation

In many channel measurement applications, one needs to estimate some characteristics of the channels based on a limited set of measurements. This is mainly due to the highly time varying characteristics of the channel. In this contribution, it will be shown how free probability can be used for channel capacity estimation in MIMO systems. Free probability has already been shown to be an invaluable tool for describing the asymptotic behaviour of many systems when the dimensions of the system get large (i.e. the number of antennas). In particular, introducing the notion of free deconvolution, we provide hereafter an asymptotically (in the number of antennas) unbiased capacity estimator (w.r.t. the number of observations) for MIMO channels impaired with noise. Another unbiased estimator (for any number of observations) is also constructed by slightly modifying the free probability based estimator. The framework is then extended to MIMO channels with phase off-set and frequency drift for which no estimator has been provided so far.
The Differential Representation of Latina and Black Female Victims in Front-Page News Stories: A Qualitative Document Analysis

Critical race feminists posit that perceptions of White and minority females differ, which suggests that media representations will vary among female crime victims. To explore this proposition, we examined front-page crime stories from four different U.S. newspapers using Altheide’s approach to qualitative document analysis. We found that stories about White female victims received more repeated coverage and were more likely to contain sympathetic narratives than stories about Latina/Black female victims. In contrast, Latina/Black female victims were more likely to be portrayed as risk-takers and “bad” women, and their victimization was normalized through descriptions of their unsafe environments.
Study and validation of human gait in a virtual environment for a biped robot

The new technology advances have allowed us the design and construction of sophisticated artificial legs, which give a very close to normal human gait to patients that have received these devices. But the task is very difficult, and it requires a lot of research with interdisciplinary-science teams. One of the tools which lets to get excellent artificial legs is the study and design of biped robots, since they can test the algorithms of control balance and equilibrium together with the desired joint positions in human gait with the consequently learning of the requirements to get the best possible construction of artificial legs, so that patients can feel these prosthesis as they do with natural legs. This study presents the second part of a new methodology to get an optimum design of prothesis legs. It has been built a Three Dimentional (3D) Environment for physical simulation, together with a calculated torque control for a biped robot to simulate human gait, starting from desired joint positions, acquired previously and modified by the balance requirements, this way, it is possible to get movements from the robot very near to the real ones, and so, to obtain a proposal prosthesis that minimizes the traumatism in the patients.
Optimization of the dorsal skinfold window chamber model and multi-parametric characterization of tumor-associated vasculature

The dorsal skinfold window chamber (DSWC) model is a unique tool that enables analysis of various aspects of tumor biology and therapeutic response. Although the protocol for the murine DSWC model is standardized, certain tumors fail to grow or require a particular environment to promote growth. Given such limitations, we optimized the DSWC model for a slow-growing tumor that regresses spontaneously in the standard protocol. We further characterized the vascular network in the tumor model compared with that of non-tumor-bearing mice and observed significant differences in multiple parameters related to vascular structure and function.
Error Modeling in Dependable Component-Based Systems

Component-based development (CBD) of software, with its successes in enterprise computing, has the promise of being a good development model due to its cost effectiveness and potential for achieving high quality of components by virtue of reuse. However, for systems with dependability concerns, such as real-time systems, a major challenge in using CBD consists of predicting dependability attributes, or providing dependability assertions, based on the individual component properties and architectural aspects. In this paper, we propose a framework which aims to address this challenge. Specifically, we present a revised error classification together with error propagation aspects, and briefly sketch how to compose error models within the context of component-based systems (CBS). The ultimate goal is to perform the analysis on a given CBS, in order to find bottlenecks in achieving dependability requirements and to provide guidelines to the designer on the usage of appropriate error detection and fault tolerance mechanisms.
Toward an Implementation of the "Form Template Method" Refactoring

This paper presents an implementation of the "form template method" refactoring. This transformation has not been automated yet, but has many similarities with other transformations such as clone detection and removal or method extraction. Forming a template method is a difficult process because it has to deal with code statements directly. Few abstractions and algorithms have been investigated yet, compared to transformations dealing with higher level aspects such as the classes, methods, fields and their relations. We present a new algorithm that performs this transformation in a semi-automated way on Java programs. We state the difficulties inherent to this transformation and propose solutions to handle them.
Development and evaluation of participant-centred biofeedback artworks

This exegesis details the development of four interactive artworks that enable audiences to observe and reflect on aspects of their own psychophysiology, using the technologies of biofeedback interaction as a way of situating the participant’s subjectivity and bodily experiences within each other as reciprocal phenomena. The central theme addressed through these works concerns the representation and experience of subjectivity as a physiologically embodied phenomenon. Although contemporary theories of psychophysiology and phenomenology have overturned the idea of mind-body separation, many forms of cultural practice continue to represent subjectivity as a fundamentally disembodied phenomenon. In addition, bodily experience in contemporary culture is framed almost entirely in terms of narrowly defined and commodity driven notions of sexuality and desirability, or even pathology. Such representations and experiences perpetuate feelings of mistrust and hostility towards the body, in ways that inhibit our ability to fully engage with the world as fully humans. This problematic use and representation of the body in contemporary culture has attracted the attention of many artists and theorists over the past fifty years, generating a diverse body of works celebrating and sometimes questioning the embodied subject as a medium for enquiry and aesthetic enrichment. The artworks documented in this exegesis extend this process of reexamination through the use of interactive bio-sensing technologies and audience participation. Interactive practices reframe subjectivity as a fundamentally active process, shifting our sense of involvement in the issues at hand from one of detached onlookers to active participants. Each of the works creates a space where participants and observers alike can become present to aspects of body-mind process. Audience responses to these works have been studied as a way of evaluating the extent to which these interests have been realised through interaction and this exegesis contributes to an emerging but growing body of research into the use of audience experience as a tool for designing and evaluating interactive artworks.
Data-flow-based Testing of Object-Oriented Libraries

Data-ﬂow-based testing is a well-established approach to program testing. Much object-oriented code is written as libraries; hence data-ﬂow-based testing of object-oriented libraries is of great importance. However, ﬁnding def-use relationships in libraries written in object-oriented languages (e.g., Java and C++) is diﬃcult because of unknown aliasing between parameters, unknown concrete types of the parameters, dynamic dispatch and exceptions. We present the ﬁrst algorithm for ﬁnding def-use relationships in object-oriented libraries that overcomes the above diﬃculties. We also show how the information computed by our algorithm can be used in generating relevant test cases. Our algorithm is ﬂow-and context-sensitive and based on our earlier points-to analysis [CRL99]
Cost-effective functional testing of reactive software

Creating test cases to cover all functional requirements of real-world systems is hard, even for domain experts. Any method to generate functional test cases must have three attributes: (a) an easy-to-use formal notation to specify requirements, from a practitioner's point of view, (b) a scalable test-generation algorithm, and (c) coverage criteria that map to requirements. In this paper we present a method that has all these attributes. First, it includes Expressive Decision Table (EDT), a requirement specification notation designed to reduce translation efforts. Second, it implements a novel scalable row-guided random algorithm with fuzzing (RGRaF)(pronounced R-graph) to generate test cases. Finally, it implements two new coverage criteria targeted at requirements and requirement interactions. To evaluate our method, we conducted experiments on three real-world applications. In these experiments, RGRaF achieved better coverage than pure random test case generation. When compared with manual approach, our test cases subsumed all manual test cases and achieved up to 60% effort savings. More importantly, our test cases, when run on code, uncovered a bug in a post-production sub-system and captured three missing requirements in another.
Curved Gaussian Models with Application to the Modelingof Foreign Exchange

Gaussian distributions lie at the heart of popular tools for capturing structure in high dimensional data. Standard techniques employ as models arbitrary linear transformations of spherical Gaussians. In this paper, we present a simple extension to a class of non{ linear, volume preserving transformations which provides an eecient local description of curvature. The resulting generalized Gaussian models give a simple statistical tool for measuring deviations from multivariate Gaussian distributions. Remarkably, there is a computationally eecient, analytic solution for tting the parameters of the non{linear models. The power of this approach is demonstrated in a curvature analysis of the Asian foreign exchange market. 1.1 Introduction In many strategies for risk management and asset allocation amongst multiple investments, the expected values and covariance structure of the returns are the fundamental statistical quantities of interest (eg Burmeister et al 1994]). These quantities emerge exactly as a result of tting Gaussian probability distributions to the data { making critical the task of understanding and broadening the nature of Gaussian ts. Principal component analysis (PCA) is one of the main tools used in tting Gaussian distributions. The idea underlying PCA is that high dimensional data often have lower dimensional structure, and that this structure can be described in a computationally eecient manner by nding the eigenvectors associated with the largest eigenvalues of the covariance matrix of the data. PCA is a well established multivariate modeling and signal processing tool, favored for its simplicity and ease of interpretation. Recently, for example, researchers in computational nance investigated the use of PCA for isolating the driving factors in the market (eg Utans et al 1997]). From a statistical perspective, PCA can be seen as having two linked aspects {
On Co-Scheduling of Update and Control Transactions in Real-Time Sensing and Control Systems: Algorithms, Analysis, and Performance

Maintaining sensor data validity while exercising timely control is crucial in real-time sensing and control systems. The goal of scheduling algorithms deployed in such systems is to maintain the validity of real-time sensor data so as to maximize the schedulability of update transactions with minimum update workload so that control actions occur on time. In this paper, we first propose a dynamic scheduling algorithm, called Deferrable Scheduling with Least Actual Laxity First (DS-LALF). DS-LALF is designed by extending the deferrable scheduling algorithm, DS-FP which is designed for fixed priority systems. We develop a schedulability test algorithm for DS-LALF based on pattern analysis and a pattern search algorithm to find the shortest and earliest pattern in the schedule. Then, based on DS-LALF, a co-scheduling algorithm called Co-LALF-to schedule update transactions and control transactions in a real-time sensing and control system together-is developed 1) to meet the deadlines of all the control transactions and 2) to maximize the quality of data (QoD) utilized by the control transactions. Co-LALFschedules the jobs in the ascending order of their actual laxities and defers the release times of update jobs as long as the corresponding sensor data are maintained within the required quality. Experimental results show that DS-LALF incurs lower update workload compared with DS-FP and ML, and its schedulability is close to DS-FP but is much better than ML and DS-EDF. The experimental results also show that Co-LALF is effective in improving the overall performance by ensuring better QoD for the real-time data while meeting the deadline constraints of all the control transactions.
Dielectric loaded exponentially tapered slot antenna for 60GHz wireless networks

This paper deals with the dielectric loaded Exponentially Tapered Slot (ETS) antenna needed for ultra-high-speed, ultra high-capacity wireless communication systems which work at 60 GHz for wireless communication networks applications and illustrates its specifications and requirements. The antenna in such systems requires high gain, high-efficient and high performance design specifications. The ETS antenna and the loaded dielectric are integrated by using the same single substrate resulting in easy fabrication and low cost. The ETS antenna with rectangular and elliptical shaped loaded dielectrics were designed and fabricated. These antennas have high gain and narrow beamwidths both in the E-plane and in the H-plane. The designed antenna is simulated using 3D electromagnetic software CST Microwave Studio and made comparison with Ansys HFSS to validate the design procedure. The results from the simulations and those from the measurements are in good agreement.