Miracle-dz/UniFAR-FTUs huggingface dataset:
The Universitat d’Alacant Submissions to the English-to-Kazakh News Translation Task at WMT 2019

This paper describes the two submissions of Universitat d’Alacant to the English-to-Kazakh news translation task at WMT 2019. Our submissions take advantage of monolingual data and parallel data from other language pairs by means of iterative backtranslation, pivot backtranslation and transfer learning. They also use linguistic information in two ways: morphological segmentation of Kazakh text, and integration of the output of a rule-based machine translation system. Our systems were ranked second in terms of chrF++ despite being built from an ensemble of only 2 independent training runs.
Using CO line ratios to trace compressed areas in bubble N131

Aims. N131 is a typical infrared dust bubble showing an expanding ring-like shell. We study the CO line ratios that can be used to trace the interaction in the expanding bubble. Methods. We carried out new CO (3–2) observations toward bubble N131 using the 15 m JCMT, and derived line ratios by combining these observations with our previous CO (2–1) and CO (1–0) data from IRAM 30 m observations. To trace the interaction between the molecular gas and the ionized gas in the HII region, we used RADEX to model the dependence of the CO line ratios on kinetic temperature and H2 volume density, and examined the abnormal line ratios based on other simulations. Results. We present CO (3–2), CO (2–1), and CO (1–0) integrated intensity maps convolved to the same angular resolution (22.5″). The three different CO transition maps show a similar morphology. The line ratios of WCO (3–2)/WCO (2–1) mostly range from 0.2 to 1.2 with a median of 0.54 ± 0.12, while the line ratios of WCO (2–1)/WCO (1–0) range from 0.5 to 1.6 with a median of 0.84 ± 0.15. The high CO line ratios WCO (3–2)/WCO (2–1) ≳ 0.8 and WCO (2–1)/WCO (1–0) ≳ 1.2 are beyond the threshold predicted by numerical simulations based on the assumed density-temperature structure for the inner rims of the ring-like shell, where the compressed areas are located in bubble N131. Conclusions. These high CO integrated intensity ratios, such as WCO (3–2)/WCO (2–1) ≳ 0.8 and WCO (2–1)/WCO (1–0) ≳ 1.2, can be used as a tracer of gas-compressed regions with a relatively high temperature and density. This further suggests that the non-Gaussian part of the line-ratio distribution can be used to trace the interaction between the molecular gas and the hot gas in the bubble.
Infrared-excess white dwarfs in the Gaia 100 pc sample

We analyse the 100 pc Gaia white dwarf volume-limited sample by means of VOSA (Virtual Observatory SED Analyser) with the aim of identifying candidates for displaying infrared excesses. Our search focuses on the study of the spectral energy distribution (SED) of 3,733 white dwarfs with reliable infrared photometry and GBP − GRP colours below 0.8 mag, a sample which seems to be nearly representative of the overall white dwarf population. Our search results in 77 selected candidates, 52 of which are new identifications. For each target we apply a two-component SED fitting implemented in VOSA to derive the effective temperatures of both the white dwarf and the object causing the excess. We calculate a fraction of infrared-excess white dwarfs due to the presence of a circumstellar disk of 1.6±0.2%, a value which increases to 2.6±0.3% if we take into account incompleteness issues. Our results are in agreement with the drop in the percentage of infrared excess detections for cool (<8,000 K) and hot (>20,000 K) white dwarfs obtained in previous analyses. The fraction of white dwarfs with brown dwarf companions we derive is ≃0.1–0.2%.
VERISMART: A Highly Precise Safety Verifier for Ethereum Smart Contracts

We present VERISMART, a highly precise verifier for ensuring arithmetic safety of Ethereum smart contracts. Writing safe smart contracts without unintended behavior is critically important because smart contracts are immutable and even a single flaw can cause huge financial damage. In particular, ensuring that arithmetic operations are safe is one of the most important and common security concerns of Ethereum smart contracts nowadays. In response, several safety analyzers have been proposed over the past few years, but state-of-the-art is still unsatisfactory; no existing tools achieve high precision and recall at the same time, inherently limited to producing annoying false alarms or missing critical bugs. By contrast, VERISMART aims for an uncompromising analyzer that performs exhaustive verification without compromising precision or scalability, thereby greatly reducing the burden of manually checking undiscovered or incorrectly-reported issues. To achieve this goal, we present a new domain-specific algorithm for verifying smart contracts, which is able to automatically discover and leverage transaction invariants that are essential for precisely analyzing smart contracts. Evaluation with real-world smart contracts shows that VERISMART can detect all arithmetic bugs with a negligible number of false alarms, far outperforming existing analyzers.
Towards Understanding and Improving Code Review Quality

Code review is an essential element of any mature software development project, it is key to ensuring the long-term quality of the code base. Code review aims at evaluating code contributions submitted by developers before they are committed into the project’s version control system. Code review is considered to be one of the most effective QA practices for software projects. In principle, the code review process should improve the quality of committed code changes. However, in practice, the execution of this process can still allow bugs to enter into the codebase unnoticed. Moreover, the notion of the quality of the code review process is not limited to the quality of the source code that passed a review. It goes beyond that, the quality of the code review process can affect how successful a software development project is. For instance, in the world of open source software (OSS), a particular execution code review process may encourage or deter the contributions from “external” developers, the people who are essential to OSS projects. We claim that by analyzing various software artifacts as well as assessing developers’ daily experience, we can create models that represent the established code review processes and highlight potentially weak points in their execution. Having this information, the stakeholders can channel the available resources to address the deficiencies in their code review process. To support such a claim, we perform the following studies. First, we study the tool-based code review processes of two large OSS projects that use traditional model of evaluating code contributions. We analyse the software artifacts extracted from the issue tracking systems to understand what can affect code review response time and eventual outcome. We found that code review is affected not only by technical factors (e.g., patch size, priority, etc.) but also by non-technical ones (e.g., developers’ affiliation, their experience, etc.). Second, we investigate the quality of contributions that passed the code review process and explore the relationships between the reviewers’ code inspections and a set of factors, both personal and social in nature, that might affect the quality of such inspections. By mining the software repository and the issue tracking system of the Mozilla project, as well as applying the SZZ algorithm to detect bug-inducing changes, we were able to find that 54% of the reviewed changes introduced bugs in the code. Our findings also showed that both personal metrics, such as reviewer workload and experience, and participation metrics, such as the number of involved developers, are associated with the quality of the code review process.
Normalizing Flows: Introduction and Ideas

Normalizing Flows are generative models which produce tractable distributions where both sampling and density evaluation can be efficient and exact. The goal of this survey article is to give a coherent and comprehensive review of the literature around the construction and use of Normalizing Flows for distribution learning. We aim to provide context and explanation of the models, review current state-of-the-art literature, and identify open questions and promising future directions.
What Makes a Speaker Recognizable in TV Broadcast? Going Beyond Speaker Identification Error Rate

Speaker identification approaches for TV broadcast are usually evaluated and compared based on global error rates derived from the overall duration of missed detection, false alarm and confusion. Based on the analysis of the output of the systems submitted to the final round of the French evaluation campaign REPERE, this paper highlights the fact that these average met-rics lead to the incorrect intuition that current state-of-the-art algorithms partially recognize all speakers. Setting aside incorrect diarization and adverse acoustic conditions, we show that their performance is in fact essentially bi-modal: in a given show, either all speech turns of a speaker are correctly identified or none of them are. We then proceed with trying to understand and explain this behavior, through perfomance prediction experiments. These experiments show that the most discriminant speaker characteristics are – first – their total speech duration in the current show and – then only – the amount of training data available to build their acoustic model.
vSDNEmul: A Software-Defined Network Emulator Based on Container Virtualization

The main issue related to Software-Defined Network emulators is how to replicate real behavior in experiments. Mininet and others SDN emulators have an architecture that limits both the scope of experiments and the fidelity of networking tests. Consequently, the serialization, contention, and load of background processes may produce delays that compromise the operation of events such as transmitting a packet or completing a computation, possibly invalidating the performance evaluation of a network emulation. To address these problems, this paper presents vSDNEmul, a network emulator based on Docker container virtualization. Different from Mininet, vSDNEmul isolates each node in a container and interconnects the nodes through virtual or tunnel links. By using containers, vSDNEmul allows autonomous and flexible creation of independent network elements, resulting in more realistic emulations. This paper reports performance evaluations comparing vSDNEmul and Mininet. The results obtained with the vSDNEmul emulator are more realistic and present higher accuracy.
Reading the Dictionary

In addition to orthographical aspects of the vocabulary, the German spelling dictionary provides among other, morphological, semantic and stylistic information. The wealth of information sometimes obscures clarity and simplicity. It also strives to be both a specialized orthographical dictionary for certain professions such as proof-readers and publishers as well as a general dictionary for everyone. The defining dictionary includes nearly all orthographical information contained in the spelling dictionary but, in terms of semantics, is much more detailed; indeed in places far too detailed. Its primary disadvantage, however, is that the lexicological ordering of the vocabulary (according to word families, word fields and frames) is lost due to the principle of alphabetical ordering. I therefore propose an alternative dictionary that is also alphabetically arranged, but interspersed with additional information offering lexicographical explanations to the lexicological relations to be found in the vocabulary. If the aim of a dictionary is not only to offer help in individual cases, but also to aid those involved in a more intensive language study, then such a dictionary should provide a more stimulating introduction to the structure of the vocabulary.
APLIKASI BIOMETRIKA PENGENALAN CITRA SIDIK JARI DENGAN METODE MINUTIAE DAN ARTIFICIAL NEURAL NETWORK BACKPROPAGATION

Penelitian biometrika sidik jari dilakakukan karena setiap individu memliki perbedaan sidik jari bahkan pada individu kembar identik. Penelitian ini membangun sebuah aplikasi biometrika pengenalan citra sidik jari dengan metode Minutiae dan Artificial Neural Network Backpropagation untuk pengenalan sidik jari.Citra yang digunakan sebagai objek penelitian adalah citra sidik jari telunjuk dan jari tengah dari kedua tangan dari ATVS- FakeFingerprintDatabase . Aplikasi ini dibangun dalam bahasa pemrograman Matlab dan dirancang dengan Diagram Unified Modeling Language (UML) dan pengembangan sistem yang digunakan adalah prototyping . Hasil yang diperoleh pada penelitian ini adalah nilai Genuine Acceptance Rate (GAR) sebesar 100% untuk citra latih dijadikan citra uji. Untuk citra uji diluar database adalah 67%. Citra uji dari sidik jari yang pengambilan menggunakan flat capacitive sensor by Precise Biometrics model Precise 100 sebesar 55%. Pada pengujian citra uji yang terkena serangan yaitu rotasi 90 o sebesar 40%, Citra uji serangan Noise Gaussian 10 % adalah 40% , BlurGaussian ratio 2.0 sebesar 70%, dan citra uji yang terpotong sebesar 30%.
Contributions of degenerate stable log maps

Let $X$ be a smooth surface and $D$ a (possibly reducible or non-reduced) curve on $X$. An $\mathbb{A}^1$-curve on $(X, D)$ is an irreducible curve $C$ on $X$ such that the normalization of $C\setminus D$ is isomorphic to $\mathbb{A}^1$. We calculate the contributions of the following curves to the genus $0$ log Gromov-Witten invariants of maximal tangency: (a) Under the assumption that $X$ is a projective rational surface, $K_X+D\sim 0$ and $P\in D_\mathrm{sm}$, an $\mathbb{A}^1$-curve $C$ which is smooth at $P=C\cap D$. (b) The sum of two immersed $\mathbb{A}^1$-curves $Z_1, Z_2$ with $(K_X+D). Z_i=0$, intersecting at $P\in D_\mathrm{sm}$ in a general way.
Deep Modulation (Deepmod): A Self-Taught PHY Layer for Resilient Digital Communications

Traditional physical (PHY) layer protocols contain chains of signal processing blocks that have been mathematically optimized to transmit information bits efficiently over noisy channels. Unfortunately, this same optimality encourages ubiquity in wireless communication technology and enhances the potential for catastrophic cyber or physical attacks due to prolific knowledge of underlying physical layers. Additionally, optimal signal processing for one channel medium may not work for another without significant changes in the software protocol. Any truly resilient communications protocol must be capable of immediate redeployment to meet quality of service (QoS) demands in a wide variety of possible channel media. Contrary to many traditional approaches which use immutable man-made signal processing blocks, this work proposes generating real-time blocks {\it ad hoc} through a machine learning framework, so-called deepmod, that is only relevant to the particular channel medium being used. With this approach, traditional signal processing blocks are replaced with machine learning graphs which are trained, used, and discarded as needed. Our experiments show that deepmod, using the same machine intelligence, converges to viable communication links over vastly different channels including: radio frequency (RF), powerline communications (PLC), and acoustic channels.
The effect of a wall on the interaction of two spheres in shear flow: Batchelor-Green theory revisited

The seminal Batchelor-Green's (BG) theory on the hydrodynamic interaction of two spherical particles of radii a suspended in a viscous shear flow neglects the effect of the boundaries. In the present paper we study how a plane wall modifies this interaction. Using an integral equation for the surface traction we derive the expression for the particles' relative velocity as a sum of the BG's velocity and the term due to the presence of a wall at finite distance, z_0. Our calculation is not the perturbation theory of the BG solution, so the contribution due to the wall is not necessarily small. The distance at which the wall significantly alters the particles interaction scales as z_0^{3/5}. The phase portrait of the particles' relative motion is different from the BG theory, where there are two singly-connected regions of open and closed trajectories both of infinite volume. For finite z_0, there is a new domain of closed (dancing) and open (swapping) trajectories. The width of this region behaves as 1/z_0. Along the swapping trajectories, that have been previously observed numerically, the incoming particle is turning back after the encounter with the reference particle, rather than passing it by, as in the BG theory. The region of dancing trajectories has infinite volume. We found a one-parameter family of equilibrium states, overlooked previously, whereas the pair of spheres flows as a whole without changing its configuration. These states are marginally stable and their perturbation yields a two-parameter family of the dancing trajectories, where the particle is orbiting around a fixed point in a frame co-moving with the reference particle. We suggest that the phase portrait obtained at z_0>>a is topologically stable and can be extended down to rather small z_0 of several particle diameters. We confirm this by direct numerical simulations of the Navier-Stokes equations with z_0=5a.
Development of image motion compensation system for 1.3m telescope at Vainu Bappu Observatory

We developed a tip-tilt system to compensate the turbulence induced image motion for the 1.3 m telescope at Vainu Bappu Observatory, at Kavalur. The instrument is designed to operate at the visible wavelength band (480 − 700 nm) with a field of view of 1′ × 1′. The tilt corrected images have demonstrated up to ≈ 57% improvement in image resolution and a corresponding peak intensity increase by a factor of ≈ 2.8. A closed-loop correction bandwidth of ≈ 26 Hz has been achieved with on-sky tests and the root mean square motion of the star image has been reduced by a factor of ∼ 14. These results are consistent with theoretical and numerical predictions of wave-front aberrations caused by atmospheric turbulence and image quality improvement expected from a real-time control system. In this paper, we present details of the instrument design, laboratory calibration studies and quantify its performance on the telescope.
A Magic Treemap Cube for Visualizing Olympic Games Data

Treemap, a common information visualization approach for dividing a display area into nested rectangles, has a good performance on visualizing hierarchical data. And it enables user to compare nodes in the same level and to learn certain relationship between adjacent levels. However, treemap layout is limited to visualize multi-dimensional hierarchical data in which the hierarchy is unfixed and complex, especially when the hierarchy is an arbitrary graph. Considering this problem, we present a novel extension called magic treemap cube, which improves the layout and has a good performance on visualizing unfixed (cross-level) and complex data, inverting hierarchy without reorganizing the structure, and enabling users to easily compare among treemaps. The magic treemap cube is a three-dimensional regular hexahedron whose six faces are covered by six different treemaps. Each dimension of the magic treemap cube is a hierarchy structure specified by users according to a hierarchical division of visualization information. With the treemap algorithm, tagcloud and mapping rules, the treemaps are automatically controlled by permutations of three dimensions of the cube. Users could observe the six correlative treemaps respectively by rotating the magic treemap cube in three dimensional Cartesian coordinate. And this magic treemap cube can be unfolded into a tiled treemap in 2D Cartesian coordinate for users-friendly comparison of each treemap. Meanwhile, a merging operation to the tiled treemap is proposed to not only compare two treemaps through the adjacency relations among faces but also provide more information. For demonstrating the above characteristics, an application (called OlympicVis) has been implemented to visualize the Beijing 2008 Olympic Games information, which involves multi-dimensional hierarchy and interconnected data. The OlympicVis can display Cube View, Schedule View, Medal View, Date Filter and Time Line.
Resource Allocation for Non-Orthogonal Multiple Access (NOMA) Enabled LPWA Networks

In this paper, we investigate the resource allocation for uplink non-orthogonal multiple access (NOMA) enabled low-power wide-area (LPWA) networks to support the massive connectivity of users/nodes. Here, LPWA nodes communicate with a central gateway through resource blocks like channels, transmission times, bandwidths, etc. The nodes sharing the same resource blocks suffer from intra-cluster interference and possibly inter-cluster interference, which makes current LPWA networks unable to support the massive connectivity. Using the minimum transmission rate metric to highlight the interference reduction that results from the addition of NOMA, and while assuring user throughput fairness, we decompose the minimum rate maximization optimization problem into three sub- problems. First, a low-complexity sub-optimal nodes clustering scheme is proposed assigning nodes to channels based on their normalized channel gains. Then, two types of transmission time allocation algorithms are proposed that either assure fair or unfair transmission time allocation between LPWA nodes sharing the same channel. For a given channel and transmission time allocation, we further propose an optimal power allocation scheme. Simulation evaluations demonstrate approximately 100dB improvement of the selected metric for a single network with 4000 active nodes.
Supplementary Material for VSO : Visual Semantic Odometry

1. Detailed derivations for both the semantic observation likelihood model (Sec. 1) and our EM-based optimization (Sec. 2). 2. Implementation details for integrating the semantic framework into existing VO systems, as well as details on weighting the residual terms based on the uncertainty of the 3D scene points (Sec. 3). 3. Additional results of our method to provide a better intuition on the effectiveness of the different components (Sec. 4).
Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in O(√n) iterations

We analyze the classical EM algorithm for parameter estimation in the symmetric two-component Gaussian mixtures in $d$ dimensions. We show that, even in the absence of any separation between components, provided that the sample size satisfies $n=\Omega(d \log^3 d)$, the randomly initialized EM algorithm converges to an estimate in at most $O(\sqrt{n})$ iterations with high probability, which is at most $O((\frac{d \log^3 n}{n})^{1/4})$ in Euclidean distance from the true parameter and within logarithmic factors of the minimax rate of $(\frac{d}{n})^{1/4}$. Both the nonparametric statistical rate and the sublinear convergence rate are direct consequences of the zero Fisher information in the worst case. Refined pointwise guarantees beyond worst-case analysis and convergence to the MLE are also shown under mild conditions. This improves the previous result of Balakrishnan et al \cite{BWY17} which requires strong conditions on both the separation of the components and the quality of the initialization, and that of Daskalakis et al \cite{DTZ17} which requires sample splitting and restarting the EM iteration.