Reviewerly/exHarmony huggingface dataset:
Enhanced Bilevel Optimization via Bregman Distance

Bilevel optimization has been recently used in many machine learning problems such as hyperparameter optimization, policy optimization, and meta learning. Although many bilevel optimization methods have been proposed, they still suffer from the high computational complexities and do not consider the more general bilevel problems with nonsmooth regularization. In the paper, thus, we propose a class of enhanced bilevel optimization methods with using Bregman distance to solve bilevel optimization problems, where the outer subproblem is nonconvex and possibly nonsmooth, and the inner subproblem is strongly convex. Specifically, we propose a bilevel optimization method based on Bregman distance (BiO-BreD) to solve deterministic bilevel problems, which achieves a lower computational complexity than the best known results. Meanwhile, we also propose a stochastic bilevel optimization method (SBiO-BreD) to solve stochastic bilevel problems based on stochastic approximated gradients and Bregman distance. Moreover, we further propose an accelerated version of SBiO-BreD method (ASBiO-BreD) using the variance-reduced technique, which can achieve a lower computational complexity than the best known computational complexities with respect to condition number $\kappa$ and target accuracy $\epsilon$ for finding an $\epsilon$-stationary point. We conduct data hyper-cleaning task and hyper-representation learning task to demonstrate that our new algorithms outperform related bilevel optimization approaches.
Cross-speaker Style Transfer with Prosody Bottleneck in Neural Speech Synthesis

Cross-speaker style transfer is crucial to the applications of multi-style and expressive speech synthesis at scale. It does not require the target speakers to be experts in expressing all styles and to collect corresponding recordings for model training. However, the performances of existing style transfer methods are still far behind real application needs. The root causes are mainly twofold. Firstly, the style embedding extracted from single reference speech can hardly provide fine-grained and appropriate prosody information for arbitrary text to synthesize. Secondly, in these models the content/text, prosody, and speaker timbre are usually highly entangled, it's therefore not realistic to expect a satisfied result when freely combining these components, such as to transfer speaking style between speakers. In this paper, we propose a cross-speaker style transfer text-to-speech (TTS) model with explicit prosody bottleneck. The prosody bottleneck builds up the kernels accounting for speaking style robustly, and disentangles the prosody from content and speaker timbre, therefore guarantees high quality cross-speaker style transfer. Evaluation result shows the proposed method even achieves on-par performance with source speaker's speaker-dependent (SD) model in objective measurement of prosody, and significantly outperforms the cycle consistency and GMVAE-based baselines in objective and subjective evaluations.
IMS’ Systems for the IWSLT 2021 Low-Resource Speech Translation Task

This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team.We utilize stateof-the-art models combined with several data augmentation, multi-task and transfer learning approaches for the automatic speech recognition (ASR) and machine translation (MT) steps of our cascaded system.Moreover, we also explore the feasibility of a full end-to-end speech translation (ST) model in the case of very constrained amount of ground truth labeled data.Our best system achieves the best performance among all submitted systems for Congolese Swahili to English and French with BLEU scores 7.7 and 13.7 respectively, and the second best result for Coastal Swahili to English with BLEU score 14.9.
Countability of Inductive Types Formalized in the Object-Logic Level

The set of integer number lists with finite length, and the set of binary trees with integer labels are both countably infinite. Many inductively defined types also have countably many elements. In this paper, we formalize the syntax of first order inductive definitions in Coq and prove them countable, under some side conditions. Instead of writing a proof generator in a meta language, we develop an axiom-free proof in the Coq object logic. In other words, our proof is a dependently typed Coq function from the syntax of the inductive definition to the countability of the type. Based on this proof, we provide a Coq tactic to automatically prove the countability of concrete inductive types. We also developed Coq libraries for countability and for the syntax of inductive definitions, which have value on their own.
The maximum mass of neutron stars may be higher than expected: an inference from binary systems

We have analyzed in this work the updated sample of neutron star masses derived from the study of a variety of 96 binary systems containing at least one neutron star using Bayesian methods. After updating the multimodality of the distributions found in previous works, we determined the maximum mass implied by the sample using a robust truncation technique, with the result $m_{max} \sim 2.5-2.6 \, M_{\odot}$. We have checked that this mass is actually consistent by generating synthetic data and employing a Posterior Predictive Check. A comparison with seven published $m_{max}$ values inferred from the remnant of the NS-NS merger GW170817 was performed and the tension between the latter and the obtained $m_{max}$ value quantified. Finally, we performed a Local Outlier Factor test and verified that the result for $m_{max}$ encompasses the highest individual mass determinations with the possible exception of PSR J1748-2021B. The conclusion is that the whole distribution already points toward a high value of $m_{max}$, while several lower values derived from the NS-NS merger event are disfavored and incompatible with the higher binary system masses. A large $m_{max}$ naturally accommodates the lower mass component of the event GW190814 as a neutron star.
Stanford MLab at SemEval-2021 Task 8: 48 Hours Is All You Need

This paper presents our system for the Quantity span identification, Unit of measurement identification and Value modifier classification subtasks of the MeasEval 2021 task.The purpose of the Quantity span identification task was to locate spans of text that contain a count or measurement, consisting of a value, usually followed by a unit and occasionally additional modifiers.The goal of the modifier classification task was to determine whether an associated text fragment served to indicate range, tolerance, mean value, etc. of a quantity.The developed systems used pre-trained BERT models which were fine-tuned for the task at hand.We present our system, investigate how architectural decisions affected model predictions, and conduct an error analysis.Overall, our system placed 12 / 19 in the shared task and in the 2nd place for the Unit subcategory.
THE EFFECT OF AUGMENTED REALITY ASSISTED CHILDREN'S STILL LIFE SKETCH TEACHING

1 National University of Tainan (TAIWAN)2 Southern Taiwan University of Science and Technology (TAIWAN)
The Telegram Chronicles of Online Harm

Harmful language is frequent in social media, in particular in spaces which are considered anonymous and/or allow free participation. In this paper, we analyze the language in a Telegram channel populated by followers of former US President Donald Trump. We seek to identify the ways in which harmful language is used to create a specific narrative in a group of mostly like-minded discussants. Our research has several aims. First, we create an extended taxonomy of potentially harmful language that includes not only hate speech and direct insults (which have been the focus of existing computational methods), but also other forms of harmful speech discussed in the literature. We manually apply this taxonomy to a large portion of the corpus, including the time period leading up to and the aftermath of the January 2021 US Capitol riot. Our data gives empirical evidence for harmful speech, such as in/out-group divisive language and the use of codes within certain communities, that have not often been investigated before. Second, we compare our manual annotations of harmful speech to several automatic methods for classifying hate speech and offensive language, namely list-based and machine-learning-based approaches. We find that the Telegram data sets still pose particular challenges for these automatic methods. Finally, we argue for the value of studying such naturally-occurring, coherent data sets for research on online harm and how to address it in linguistics and philosophy.
SAR Image Despeckling Algorithm Using Non-Local Means with Adaptive Filtering Strength

A new Non-Local Means (NLM) despeckling algorithm (AFS-NLM) with Adaptive Filtering Strength (AFS) is proposed to improve the performance of reducing multiplicative speckle and preserving the edges in SAR images. A modified Kuan filtering coefficient which can better characterize the homogeneous and edge regions of SAR image is formed by using the local mean and variance calculated in the Frost filtered image to improve the estimation of SAR image scene parameters. An improved NLM which adapts to the multiplicative noise characteristics is constructed by the new similarity measurement parameter estimated by the local mean ratio and the new adaptive decay factor estimated by the improved Kuan filtering coefficient. A new weighted filtering model which can automatically adjust the filtering strength is formed. In the new model, the improved NLM filters controlled by the skew smoothing parameters and the skew edge protection parameters are used to replace the local average value of pixels and the gray value of pixels in the classic Kuan filter model as weighting items, and the adaptive adjustment factor constructed by the improved Kuan filter coefficient is used to weight the two items. Experimental results and comparisons with several advanced despeckling algorithms in recent years show that the proposed algorithm has better speckle suppression and edge preservation performance.
Constructing Strings Avoiding Forbidden Substrings

We consider the problem of constructing strings over an alphabet Σ that start with a given prefix u, end with a given suffix v, and avoid occurrences of a given set of forbidden substrings. In the decision version of the problem, given a set Sk of forbidden substrings, each of length k, over Σ, we are asked to decide whether there exists a string x over Σ such that u is a prefix of x, v is a suffix of x, and no s ϵ Sk occurs in x. Our first result is an O(|u| + |v| + k|Sk|)-time algorithm to decide this problem. In the more general optimization version of the problem, given a set S of forbidden arbitrary-length substrings over Σ, we are asked to construct a shortest string x over S such that u is a prefix of x, v is a suffix of x, and no s ϵ S occurs in x. Our second result is an O(|u| + |v| + ||S|| · |Σ|)-time algorithm to solve this problem, where ||S|| denotes the total length of the elements of S. Interestingly, our results can be directly applied to solve the reachability and shortest path problems in complete de Bruijn graphs in the presence of forbidden edges or of forbidden paths. Our algorithms are motivated by data privacy, and in particular, by the data sanitization process. In the context of strings, sanitization consists in hiding forbidden substrings from a given string by introducing the least amount of spurious information. We consider the following problem. Given a string w of length n over Σ, an integer k, and a set Sk of forbidden substrings, each of length k, over Σ, construct a shortest string y over Σ such that no s ϵ Sk occurs in y and the sequence of all other length-k fragments occurring in w is a subsequence of the sequence of the length-k fragments occurring in y. Our third result is an O(nk|Sk| · |Σ|)-time algorithm to solve this problem.
Products of Integers with Few Nonzero Digits

Abstract Let s ( n ) be the number of nonzero bits in the binary digital expansion of the integer n . We study, for fixed k, ℓ, m , the Diophantine system s ( ab )= k, s ( a )= ℓ, and s ( b )= m in odd integer variables a, b .When k =2 or k = 3, we establish a bound on ab in terms of ℓ and m . While such a bound does not exist in the case of k =4, we give an upper bound for min{ a, b } in terms of ℓ and m .
Analisis Kinerja Website Dinas Komunikasi dan Informatika Menggunakan Metode Pieces

The Diskominfo website is a means of communication to convey various information to the wider community. The existence of a website helps at the same time cover up the government's limitations in the dissemination of various information so that the public does not experience information gaps. This website is analyzed using the Pieces method such as performance, information, economic, control, efficiency, and service by testing using the GT Matrik Tools and Google Transparency Report, while the test results obtained after the analysis are obtained that the average page speed grade is 27%. or in grade F. This means that the quality of the Diskominfo website based on the index generated by Google is still very low, the same thing is also produced by YSlow Grade from Yahoo where the average YSlow Grade is 66% or grade D. The low quality of the web will certainly affect website performance. While testing based on the results of control measurements, the Diskominfo website is safe for public visits. The Diskominfo website has good efficiency, because the existing system can be used properly and can also produce the expected output. In the analysis measurement results, the menu structure that is built can be seen from its initial purpose, which is to provide services to the community, however, this service is still not optimal because the content of the service is not well filled. D. Rendahnya kualitas web tersebut tentu akan mempengaruhi kinerja website. Sedangkan pengujian Berdasarkan hasil pengukuran control, website Diskominfo aman untuk dikunjungi oleh masyarakat. Website Diskominfo telah memiliki efisiensi yang baik, karena sistem yang ada telah dapat digunakan dengan baik dan juga dapat menghasilkan output yang diharapkan. Pada hasil pengukuran analisis bahwa struktur menu yang dibangun dapat dilihat tujuan awalnya yaitu dapat memberikan pelayanan kepada masyarakat, Akan tetapi pelayanan ini masih belum maksimal dikarenakan konten pelayanan belum banyak terisi dengan baik.
Online English Learning during Covid-19 Pandemic

Abstract Purpose: This article aims to describe English learning in the Covid-19 Pandemic Era. This article also explains the importance of the Internet in the learning process and the importance of parents in the development of students in the Covid-19 Pandemic Era. Research methodology: This study used a descriptive method. Results: This study suggests that parents should motivate their children in this situation because the learning process is carried out at home, and only parents can directly monitor the learning process. Limitations: This study has limitations. It is the information of parents who guide their students in the learning process, especially English Subject in the Covid-19 pandemic. Contribution: The study is beneficial for teachers and parents to conduct a better learning strategy during Covid -19 pandemic.
A Temporal Memory-based Continuous Authentication System

With the emerging use of technology, verifying a user’s identity continuously throughout a device’s usage has become increasingly important. This paper proposes an authentication system that unobtrusively verifies a user’s identity continuously, based on his/her hand movement patterns captured using accelerometer, while a user performs free-text typing. Our model validates a user’s identity with a verification decision in every ≈ 20ms interval. The authentication model utilizes a short temporal memory of size M of a user’s hand movement patterns. Experiments on different values of M suggests that the model shows an improved and consistent performance by increasing the size of the temporal memory of a user’s hand movement patterns to M ≈ 300ms.The authentication system requires only a user’s hand movement signals in order to authenticate a user on a device. Experiments on the hand movement patterns of 27 volunteer participants, captured using motion sensors of a Sony Smartwatch while they performed free-text typing on a desktop/laptop device, show that our model could achieve an average authentication accuracy of 99.8% with an average False Accept Rate (FAR) of 0.0003 and an average False Reject Rate (FRR) of 0.0034.
Analysis and optimization of quantum adaptive measurement protocols with the framework of preparation games

A preparation game is a task whereby a player sequentially sends a number of quantum states to a referee, who probes each of them and announces the measurement result. Many experimental tasks in quantum information, such as entanglement quantification or magic state detection, can be cast as preparation games. In this paper, we introduce general methods to design n-round preparation games, with tight bounds on the performance achievable by players with arbitrarily constrained preparation devices. We illustrate our results by devising new adaptive measurement protocols for entanglement detection and quantification. Surprisingly, we find that the standard procedure in entanglement detection, namely, estimating n times the average value of a given entanglement witness, is in general suboptimal for detecting the entanglement of a specific quantum state. On the contrary, there exist n-round experimental scenarios where detecting the entanglement of a known state optimally requires adaptive measurement schemes.
USING 3D PRINTING AND AUGMENTED REALITY FOR TEACHING AND LEARNING IN MECHANICAL ENGINEERING HIGHER EDUCATION

USING 3D PRINTING AND AUGMENTED REALITY FOR TEACHING AND LEARNING IN MECHANICAL ENGINEERING HIGHER EDUCATION
Penggunaan Video Pembelajaran bagi Anak Usia Dini dalam Pembelajaran Daring

Online learning is the choice of educational services for early childhood during the pandemic. The purpose of PKM is to design, create and implement learning videos in online learning. The implementation method is carried out in three initial, core, and final stages. The results showed that the child has a high interest in learning activities and has a curious attitude towards the material presented. Parents' responses to the use of learning videos showed that out of 20 parents there were 90% agreeing with the use of learning videos and 10% disagreed. Parental feedback on the content in the learning video showed that 60% were very satisfied, 40% expressed satisfaction and 0% were dissatisfied. The conclusion states that online learning with learning videos shows the increasing ability of students as well as the satisfaction of parents to the implementation and presentation of content in each video.
Information Retrieval with Root- and Rule-Based Terms

Root- and rule-based terms are structured representations of natural language phrases that can be automatically generated using a combination of statistical and symbolic methods. These terms are able to represent and normalize syntactic information about natural language phrases, making them richer than basic n-grams while greatly reducing the vocabulary size. In this paper, we discuss the use of root- and rule-based terms for information retrieval. We represent documents and queries as collections of root- and rule-based terms and show that this improves conventional information retrieval methods such as Latent Semantic Indexing and Latent Direchlet Allocation. Root- and rule-based terms improve on state of the art evaluation scores for the TREC 2016 clinical decision support track.
Document Parsing Tool for Language Translation and Web Crawling using Django REST Framework

Abstract There are 7.5 billion inhabitants and over 7,117 languages existing around the world, but only 20% of the people speak English. To understand the wisdom and knowledge of other cultures language translation becomes a basic need. In this paper, a computer-assisted document parsing tool is investigated. The proposed approach uses a language translator that performs translation from images eliminating the need of a human translator for images avoiding the scope for misinterpretation and misunderstanding among people of different ethnic groups. The proposed tool is also capable of performing web crawling using Django Representational State Transfer framework. Further, the proposed approach employs Python packages such as pytesseract, textblob and beautifulsoup to perform Optical Character Recognition, Translation and Extraction of Hypertext Markup Language data respectively. Experimental results of translation on four different categories of images such as Maps, Comics, Newspapers and Magazines, Scientific Publications demonstrate an accuracy of 97.2%, 93.3%, 95.82% and 98.27% respectively. By considering websites like E-commerce, Magazines, Blogs, Social Media, News and Educational sites average precision of 5.4, recall of 7.45 and F-score of 6.24 is achieved. The results reveal that the proposed system can be used as an improvement over a human translator and a data entry operator.
Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.