Miracle-dz/UniFAR-FTUs huggingface dataset:
GPU-Accelerated Atari Emulation for Reinforcement Learning

We designed and implemented a CUDA port of the Atari Learning Environment (ALE), a system for developing and evaluating deep reinforcement algorithms using Atari games. Our CUDA Learning Environment (CuLE) overcomes many limitations of existing CPU-based Atari emulators and scales naturally to multi-GPU systems. It leverages the parallelization capability of GPUs to run thousands of Atari games simultaneously; by rendering frames directly on the GPU, CuLE avoids the bottleneck arising from the limited CPU-GPU communication bandwidth. As a result, CuLE is able to generate between 40M and 190M frames per hour using a single GPU, a finding that could be previously achieved only through a cluster of CPUs. We demonstrate the advantages of CuLE by effectively training agents with traditional deep reinforcement learning algorithms and measuring the utilization and throughput of the GPU. Our analysis further highlights the differences in the data generation pattern for emulators running on CPUs or GPUs. CuLE is available at this https URL .
Unified phase diagram of reversible–irreversible, jamming, and yielding transitions in cyclically sheared soft-sphere packings

Significance The response and self-organization of amorphous matter to externally imposed stresses or deformation is of interest in a variety of contexts. In particular, cyclic-shear deformation has been employed, in computer simulations and experiments, to probe the emergence of irreversibility in colloidal suspensions, yielding and annealing of glasses, jamming, memory formation, etc. We investigate soft-sphere assemblies computationally to obtain a comprehensive understanding of their self-organization and response over a wide range of densities and deformation amplitudes. We find a rich diversity of behaviors and transitions, and obtain a unified phase diagram that exhibits reversible and irreversible regimes and transitions among them that embody yielding, jamming, unjamming, and shear jamming phenomena. Self-organization, and transitions from reversible to irreversible behavior, of interacting particle assemblies driven by externally imposed stresses or deformation is of interest in comprehending diverse phenomena in soft matter. They have been investigated in a wide range of systems, such as colloidal suspensions, glasses, and granular matter. In different density and driving regimes, such behavior is related to yielding of amorphous solids, jamming, memory formation, etc. How these phenomena are related to each other has not, however, been much studied. In order to obtain a unified view of the different regimes of behavior, and transitions between them, we investigate computationally the response of soft-sphere assemblies to athermal cyclic-shear deformation over a wide range of densities and amplitudes of shear deformation. Cyclic-shear deformation induces transitions from reversible to irreversible behavior in both unjammed and jammed soft-sphere packings. Well above the minimum isotropic jamming density (ϕJ), this transition corresponds to yielding. In the vicinity of the jamming point, up to a higher-density limit, we designate ϕJcyc, an unjammed phase emerges between a localized, absorbing phase and a diffusive, irreversible, phase. The emergence of the unjammed phase signals the shifting of the jamming point to higher densities as a result of annealing and opens a window where shear jamming becomes possible for frictionless packings. Below ϕJ, two distinct localized states, termed point- and loop-reversible, are observed. We characterize in detail the different regimes and transitions between them and obtain a unified density-shear amplitude phase diagram.
A State Space Approach to Dynamic Modeling of Mouse-Tracking Data

Mouse-tracking recording techniques are becoming very attractive in experimental psychology. They provide an effective means of enhancing the measurement of some real-time cognitive processes involved in categorization, decision-making, and lexical decision tasks. Mouse-tracking data are commonly analyzed using a two-step procedure which first summarizes individuals' hand trajectories with independent measures, and then applies standard statistical models on them. However, this approach can be problematic in many cases. In particular, it does not provide a direct way to capitalize the richness of hand movement variability within a consistent and unified representation. In this article we present a novel, unified framework for mouse-tracking data. Unlike standard approaches to mouse-tracking, our proposal uses stochastic state-space modeling to represent the observed trajectories in terms of both individual movement dynamics and experimental variables. The model is estimated via a Metropolis-Hastings algorithm coupled with a non-linear recursive filter. The characteristics and potentials of the proposed approach are illustrated using a lexical decision case study. The results highlighted how dynamic modeling of mouse-tracking data can considerably improve the analysis of mouse-tracking tasks and the conclusions researchers can draw from them.
Online Set-Based Dynamic Analysis for Sound Predictive Race Detection

Predictive data race detectors find data races that exist in executions other than the observed execution. Smaragdakis et al. introduced the causally-precedes (CP) relation and a polynomial-time analysis for sound (no false races) predictive data race detection. However, their analysis cannot scale beyond analyzing bounded windows of execution traces. This work introduces a novel dynamic analysis called Raptor that computes CP soundly and completely. Raptor is inherently an online analysis that analyzes and finds all CP-races of an execution trace in its entirety. An evaluation of a prototype implementation of Raptor shows that it scales to program executions that the prior CP analysis cannot handle, finding data races that the prior CP analysis cannot find.
Interaction-And-Aggregation Network for Person Re-Identification

Person re-identification (reID) benefits greatly from deep convolutional neural networks (CNNs) which learn robust feature embeddings. However, CNNs are inherently limited in modeling the large variations in person pose and scale due to their fixed geometric structures. In this paper, we propose a novel network structure, Interaction-and-Aggregation (IA), to enhance the feature representation capability of CNNs. Firstly, Spatial IA (SIA) module is introduced. It models the interdependencies between spatial features and then aggregates the correlated features corresponding to the same body parts. Unlike CNNs which extract features from fixed rectangle regions, SIA can adaptively determine the receptive fields according to the input person pose and scale. Secondly, we introduce Channel IA (CIA) module which selectively aggregates channel features to enhance the feature representation, especially for small-scale visual cues. Further, IA network can be constructed by inserting IA blocks into CNNs at any depth. We validate the effectiveness of our model for person reID by demonstrating its superiority over state-of-the-art methods on three benchmark datasets.
New way to access the quark fragmentation functions in electron-positron annihilation

The description of the polarized quark hadronization process is one of the most challenging problems in the physics of strong interactions. The various single hadron and dihadron fragmentation functions, that quantify this process, are determined by analyzing the inclusive production of hadrons in electron-positron semi-inclusive annihilation process (SIA). These, in turn, are used to extract the transverse momentum dependent parton distribution functions from the experiments on semi-inclusive deep inelastic scattering process (SIDIS), elucidating the spin-orbit correlations in nucleon. Here we present a framework for new measurements of polarized quark fragmentation functions in electron-positron annihilation and deep inelastic semi-inclusive processes. These measurements offer a number of exciting opportunities to improve our understanding of the polarized quark hadronization and test the universality of the fragmentation functions. Such measurements can be performed at the upcoming BELLE II, JLab-12 and the future EIC experiments
Inferring Accurate Bus Trajectories from Noisy Estimated Arrival Time Records

Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructure planning and urban anomaly detection. While individual-specific transaction records (such as smart card (tap-in, tap-out) data or taxi trip records) hold a wealth of information, these are often private data available only to the service provider (e.g., taxicab operator). In this work, we explore the utility in harnessing publicly available, albeit noisy, transportation datasets, such as noisy "Estimated Time of Arrival" (ETA) records (commonly available to commuters through transit Apps or electronic signages). We first propose a framework to extract accurate individual bus trajectories from such ETA records, and present results from both a primary city (Singapore) and a secondary city (London) to validate the techniques. Finally, we quantify the upper bound on the spatiotemporal resolution, of the reconstructed trajectory outputs, achieved by our proposed technique.
A qualitative case study of the efficacy of an online English language course at the Syrian Virtual University

The study was undertaken in the online environment of the English language learning course in one of the institutions of higher education that deliver all its courses entirely online: the Syrian Virtual University (SVU). A proliferation in the use of computer conferencing tools (both video and audio) in language learning has taken place. The use of these tools, together with the relatively "traditional" asynchronous text-based ones, allows educators to cater to different learning needs and language skills. Such tools may require the implementation of new teaching approaches according to the nature of the tool and the pedagogical objectives of using the tool. Synchronous tools are a new medium for course delivery. It is not known if these tools can efficiently support English language teaching and learning when used by virtual learners and tutors together with other elements of the online environment. The purpose of the qualitative case study was to explore the nature of an online environment using integrated tools, and how different elements of the online environment such as content free tools and web-based materials are currently used by learners and tutors. Opportunities and constraints of these tools as well as learner and teacher experiences with these tools and materials were included in the study. Factors that hinder/facilitate language learning using these tools was described and analysed. Data analysis involved qualitative content and thematic analysis. The key findings show that the online environment did provide students with the opportunity of experiencing multiple approaches: self study where students worked alone on the interactive materials and received computer feedback, and learning through audio conferencing where they worked with each other and with the teacher to receive human feedback. These two approaches met different language learning needs, i.e., student's needs for independent learning, and their needs for social learning. It also met the needs of students who were less capable of working independently, especially those who did not have the necessary proficiency in English for working alone. These students had the opportunity to have support from the teacher and from other students. The use of multimodality offered many opportunities for language teaching and learning, but at the same time, there were many constraints that need to be addressed in further research.
Controlled Experiments in Software Engineering

Today, most processes, methods, and tools in software engineering only rely on experience, lacking empirical evidence for a practical application. For example, an unanswered question for most tools is "Under which circumstances should the tool be used and when not? ". For this reason, research should aim to show which technology is useful for whom for which tasks and in which environment [15]. For finding answers to those questions, controlled experiments can be used. This paper describes controlled experiments in software engineering including necessary steps for performing them and related challenges.
Effect of General Computer Use on Secondary School Students' Performance in Biology

Although knowledge of biology is important for the survival of humans, performance in the subject, both in pre-Kenya Certificate of Secondary Education (pre-KCSE) assessment and national examinations in Vihiga county has always been below average. Several interventions have been put in place to rectify the situation but in vain. However, the effect of the general computer use has not been investigated. This study investigated the effect of the general computer use on secondary school students’ performance in biology. This study used descriptive survey research design. The target population was secondary school biology students of Vihiga county. Data collection was by use of questionnaires, interviews, and document analysis schedule. Sampling was by multistage sampling, purposive sampling, stratified sampling, proportionate sampling and simple random sampling. Sample size was 1003 students. The collected data was analysed using descriptive statistics such as frequencies, percentages and means and inferential statistics such as Pearson’s r, using the Statistical Package for Social Sciences (SPSS). The significance level of the difference between the data was done at the alpha value of 0.05. This study found that there is no relationship between the general computer use and performance in biology. Keywords: Computer, frequency, octile, performance.
Efficient Revocable Certificateless Signature Against Signing Key Exposure

A necessary problem in public key cryptosystem is how to revoke a user when the user's private key is compromised or the permission is prohibited.There have been many effective solutions in both traditional public key cryptosystem(TPKC) and identity based cryptosystem(IBC). But,in certificateless public key cryptosystem the revocation problem still remains to be efficiently solved.As is known,certificateless cryptosystem is a good substitution for TPKC and IBC since it features no certificate and no key escrow with only a little more computation.So,it is very necessary to design efficient revocation solutions in the certificateless setting.This paper gives a revocable certificateless signature scheme in which the system periodically generates new time keys for all non-revoked users via public channels.Compared with the existing Al-Riyami and Paterson revocation mechanism,our scheme is much better in efficiency.Furthermore,the new scheme can resist signing key exposure with very short signing key.In the CDH assumption,our scheme is UF-CMA provably secure.
Facilitating Academic Achievement in High School Interactive Television Programs by Promoting Self-Regulated Learning

The study investigated the effects of self-monitoring on students’ academic achievement and self-regulation in an interactive television (ITV) classroom. High school students taking the Japanese courses via ITV were asked to engage in self-monitoring activities, including goal setting, self-recording, and self-evaluation for 6 weeks using online databases. The study employed a quasi-experimental design with preand posttests. and two groups: control and experimental groups, were formed to examine the effects of self-monitoring. Students’ test grades and the Motivated Strategies for Learning Questionnaires were used to measure academic achievement and self-regulation. Hierarchical regressions were conducted to analyze the data. While no significant difference was found between two groups, the study provided directions for future research.
Advancing Biomedical Named Entity Recognition with Multivariate Feature Selection and Semantically Motivated Features

Automating aspects of biocuration through biomedical information extraction could signi cantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located within natural-language text and their semantic type is determined. This step is critical for later tasks in an information extraction pipeline, including normalization and relationship extraction. BANNER is a benchmark biomedical NER system using linear-chain conditional random elds and the rich feature set approach. A case study with BANNER locating genes and proteins in biomedical literature is described. The rst corpus for disease NER adequate for use as training data is introduced, and employed in a case study of disease NER. The rst corpus locating adverse drug reactions (ADRs) in user posts to a health-related social website is also described, and a system to locate and identify ADRs in social media text is created and evaluated. The rich feature set approach to creating NER feature sets is argued to be subject to diminishing returns, implying that additional improvements may require more sophisticated methods for creating the feature set. This motivates the rst application of multivariate feature selection with lters and false discovery rate analysis to biomedical NER, resulting in a feature set at least 3 orders of magnitude smaller than the set created by the rich feature set approach. Finally, two novel approaches to NER by modeling the semantics of token sequences are introduced. The rst method focuses on the
Real time data transmission over GSM voice channel for secure voice and data applications

This paper describes a real time prototype implementation of a system, which enables secure voice and data communication over the GSM voice channel. The security of GSM is not guaranteed especially over the core network. The proposed system modulates digital data, which may be encrypted onto speech-like waveforms. The modulated waveform is then transmitted over the GSM voice channel, which can be demodulated and decrypted at the receiver. The real time prototype system has been tested on GSM-to-GSM voice calls, and a proprietary speech codec is used on the real time data channel to produce communication quality speech. A demonstration will be provided at the presentation. (4 pages)
Constraint-minimizing logical topology for wireless sensor networks

Wireless sensor network (WSN) is currently one of the most promising areas in the field of information and communication technologies (ICT). This new technology has unlimited potential for numerous applications in different areas, including environmental research, medical application, military, transportation, entertainment, crisis management, homeland defense, and smart spaces. However, several constraints of the sensor nodes are the main obstacles for designing efficient protocols for WSNs. The major constraints of WSNs include energy consumption severity, low quality of communication, limited computational resource, and scalability. In developing various application protocols for WSNs, such as data collection and dissemination protocols, routing protocols, security or synchronization protocols, various researchers have focused primarily on reducing the aforementioned constraints of WSNs. So far, their approaches tend to focus on developing protocols first, and then to use them on different topologies to implement the protocols. This thesis, however, proposes a novel approach for protocol design paradigm. To contend with the constraints of WSNs, this thesis argues to develop the logical topology before the protocols are designed, because logical topology inherently defines the logical structure and the communication abstraction among the sensor nodes, and thus logical topology governs protocol design. An optimized logical topology facilitates the ability of designers to design efficient protocols, which allow the sensors to communicate with each other with little overheads, lower energy consumption, longer lifetime of sensor nodes, and reduced latency. It is thus more intuitive to approach the constraintsminimizing problem of WSNs from the topological point of view. Moreover, the use of logical topology is inevitable when the sheer number of sensor nodes, their unattended deployment, and hostile environment preclude reliance on physical configuration or physical topology. In such circumstances, designers need to rely only on the logical topologies. Hence, this thesis aims to design an efficient logical topology/structure, with which other application protocols can be designed.
A strategy for supporting students who have fallen behind in the learning of mathematics

Given the diversity of achievement in most classes and the other pressures on teachers, it seems unrealistic to assume that class teachers, as part of their everyday teaching, can provide whatever support is needed by students who have fallen a long way behind. The following is a report of a specific initiative aimed to investigate the potential of an out of class student support intervention, the goal of which is to prepare students for the mathematics lessons they will experience subsequent to the support.
Evaluation of nuchal translucency as a sonographic marker for screening congenital heart defects in high risk cases

Introduction: Congenital heart defects (CHDs) are commonest structural birth defects and leading cause of infant morbidity & mortality. Present study aims to evaluate nuchal translucency (NT) as a sonographic marker for screening CHDs. Methodology: 142 high risk mothers for CHDs, who attended antenatal clinic of hospital between July 2014 to June 2016 underwent NT scan between 10-14 weeks. Results: Heart defects were diagnosed in six newborns (2 hypoplastic left heart syndrome, 1 tricuspid atresia, 2 ventricular septal defect, 1 atrial septal defect). For major cardiac anomalies sensitivity of NT scan was 66.7% & specificity 88.4% at 95th centile cut-off (LR+5.75 & LR-0.376), and at 99th centile cut off sensitivity remained same but it was 99.2% specific (LR +83.3, LR- 0.335). NT scan had poor screening potential for right heart lesions. Conclusion: Increased nuchal translucency thickness was associated with higher risk of major congenital heart defects in chromosomally normal pregnancies.
Performance of Large Scale Data-Oriented Operations under the TEE Constraints

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Performance of Large Scale Data-Oriented Operations under the TEE Constraints Robin Carpentier, Nicolas Anciaux, Iulian Popa, Guillaume Scerri