Reviewerly/exHarmony huggingface dataset:
Pemanfaatan Youtube Sebagai Media Pembelajaran Bahasa Jepang di SMAN 10 Malang Pada Masa Pandemi Covid-19

SMAN 10 Malang began implementing learning from home activities since the issuance of a circular from the government regarding the implementation of education policies during the Covid-19 emergency. Japanese language learning which is one of the subjects at SMAN 10 Malang that is studied by students majoring in Language and Mathematics and Natural Sciences, is also carried out online. In meeting these challenges, Youtube media is used for Japanese language learning during home learning activities (BDR). This study aims to describe the use of Youtube in Japanese language class dan to determine how interest and student learning outcomes in Japanese language learning using Youtube media during BDR activities. The method used in this research is descriptive qualitative method with the process of collecting primary data through the results of student response questionnaires, as well as secondary data through the results of evaluation of student learning in Japanese language learning using Youtube media. The results of data analysis showed that students' interest in using Youtube media as a medium for learning Japanese language during BDR activities was in highest criteria. Moreover, the data has shown a satisfactory result in learning Japanese language through Youtube as a learning media.
General Galois processor for transmitters in 5G/6G base stations

This paper proposes a flexible eight-mode high parallel Galois SIMD ASIP(Application Specific Instruction Set Processor). It supports parallel executions of Gold, Scrambling, CRC, CC, Turbo, RM, PSS, SSS encoding LFSR (linear feedback shift registers) algorithms with high performance and flexibility. It can perform also general bit processing and m-sequence. Our design is based on proposed table conversion and a datapath for unified eight-mode encoding. Based on 28 nm digital CMOS technology, the total area is 0.177mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and the clock frequency can be up to 1 GHz. The throughputs of Gold, Scrambling, CRC32, CRC24, CRC16, CRC8, CC, Turbo are 64Gb/s, 64Gb/s, 128Gb/s, 168Gb/s, 256Gb/s, 512Gb/s, 3×80Gb/s, and 72Gb /s, respectively.
CISOs should work closely with their ITAM colleagues

How many CISOs do you know that are proactively working with their IT asset management (ITAM) colleagues? In fact, how many CISOs have even heard of ITAM? While traditionally referred to as the department that ‘counts computers’, ITAM has an important and often overlooked role to play in cyber security. In fact, security will become one of the most important areas for ITAM development by the end of the decade. Let's see why.
Recovering affine curves over finite fields from L-functions

Let $K$ be the function field of a curve over a finite field of odd characteristic. We investigate using $L$-functions of Galois extensions of $K$ to effectively recover $K$. When $K$ is the function field of the projective line with four rational points removed, we show how to use $L$-functions of a ray class field to effectively recover the removed points up to automorphisms of the projective line. When $K$ is the function field of a plane curve, we show how to effectively recover the equation of that curve using $L$-functions of Artin-Schreier extensions of $K$.
Perspectives of Nursing Professionals Regarding The Care of Patients with Covid-19

Introduction: Currently the responsibilities and role of each nursing professional has been put to the test with the need to care for thousands of Covid-19 patients, whose demands for technical, cognitive and personal care have exceeded the capacities of many healthcare professionals. Aims &amp; Objective: To know the perspectives of nursing professionals regarding the care of patients diagnosed with Covid-19. Material &amp; Method: the qualitative method was applied with a phenomenological approach, with the consensual participation of 10 HANM professionals, for convenience. The information was collected through in-depth interviews and analyzed in the atlas ti software. V9, using 6 core categories and 11 subcategories with which the hermeneutical unit was built. Results: Nursing care in the time of Covid-19 has faced uncertainty and fear, not knowing accurately the procedures and treatments due to the lack of information in this regard, despite this they maintain the humanization in the treatment of the patient and the Family members, through emotional intelligence, manage their feelings and fears to provide support to their patients. Conclusions: Despite the limited accessibility to protection barriers and biosafety standards, mechanisms were established to provide comprehensive care, considering the needs of the patient and their families, and accompanying them throughout the disease process. The greatest impact for nursing professionals has been to be in constant contact with death, increasing their fear of catching it and bringing the disease to their family members. Keywords: Covid-19, nursing, care, patients.
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing

Locating and fixing bugs is a time-consuming task.Most neural machine translation (NMT) based approaches for automatically bug fixing lack generality and do not make full use of the rich information in the source code.In NMTbased bug fixing, we find some predicted code identical to the input buggy code (called unchanged fix) in NMT-based approaches due to high similarity between buggy and fixed code (e.g., the difference may only appear in one particular line).Obviously, unchanged fix is not the correct fix because it is the same as the buggy code that needs to be fixed.Based on these, we propose an intuitive yet effective general framework (called Fix-Filter-Fix or F 3 ) for bug fixing.F 3 connects models with our filter mechanism to filter out the last model's unchanged fix to the next.We propose an F 3 theory that can quantitatively and accurately calculate the F 3 lifting effect.To evaluate, we implement the Seq2Seq Transformer (ST) and the AST2Seq Transformer (AT) to form some basic F 3 instances, called F 3 ST +AT and F 3 AT +ST .Comparing them with single model approaches and many model connection baselines across four datasets validates the effectiveness and generality of F 3 and corroborates our findings and methodology.
BGP security and the future: A meta-analysis of BGP threats and security to provide a new direction for practical BGP security

The Internet consists of many subnetworks, which are connected to each other. These subnetworks are the autonomous systems (ASes) that make up the Internet: each hosts a part of it. In order to successfully determine routes from one of these ASes to the other, the Border Gateway Protocol (BGP) is used. This protocol has several security flaws however, and exploitation of them has lead to parts of the Internet being temporarily unreachable. In order to combat these flaws, several security solutions have been developed already. However, none of these have been deployed on a wide scale yet. As such, this thesis focuses on the question: why not, and what can be done to protect BGP in the future? This thesis includes an analysis of the BGP threat landscape, to find which threats are most relevant, and to find out whether or not solutions have adapted to the threat landscape. It also includes a comparison of solutions on different practical security aspects. From this comparison, I found that no solution is able to prevent attacks if only one autonomous system deploys it. Due to this, I suggest to shift attention to detective security. This thesis also includes an analysis of some detective security schemes, to see which properties of these schemes can be used for a new scheme. This new scheme is designed to comply with a list of requirements, and it uses properties from three other schemes. Development of this scheme is left as future work. Altogether, this thesis should provide a new direction for the future of BGP security.
Monocular Human Shape and Pose with Dense Mesh-borne Local Image Features

We propose to improve on graph convolution based approaches for human shape and pose estimation from monocular input, using pixel-aligned local image features. Given a single input color image, existing graph convolutional network (GCN) based techniques for human shape and pose estimation use a single convolutional neural network (CNN) generated global image feature appended to all mesh vertices equally to initialize the GCN stage, which transforms a template T-posed mesh into the target pose. In contrast, we propose for the first time the idea of using local image features per vertex. These features are sampled from the CNN image feature maps by utilizing pixel-to-mesh correspondences generated with DensePose. Our quantitative and qualitative results on standard benchmarks show that using local features improves on global ones and leads to competitive performances with respect to the state-of-the-art.
On solving classes of positive-definite quantum linear systems with quadratically improved runtime in the condition number

Quantum algorithms for solving the Quantum Linear System (QLS) problem are among the most investigated quantum algorithms of recent times, with potential applications including the solution of computationally intractable differential equations and speed-ups in machine learning. A fundamental parameter governing the efficiency of QLS solvers is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math>, the condition number of the coefficient matrix <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>A</mml:mi></mml:math>, as it has been known since the inception of the QLS problem that for worst-case instances the runtime scales at least linearly in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> [Harrow, Hassidim and Lloyd, PRL 103, 150502 (2009)]. However, for the case of positive-definite matrices classical algorithms can solve linear systems with a runtime scaling as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msqrt><mml:mi>κ</mml:mi></mml:msqrt></mml:math>, a quadratic improvement compared to the the indefinite case. It is then natural to ask whether QLS solvers may hold an analogous improvement. In this work we answer the question in the negative, showing that solving a QLS entails a runtime linear in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> also when <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>A</mml:mi></mml:math> is positive definite. We then identify broad classes of positive-definite QLS where this lower bound can be circumvented and present two new quantum algorithms featuring a quadratic speed-up in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math>: the first is based on efficiently implementing a matrix-block-encoding of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>A</mml:mi><mml:mrow class="MJX-TeXAtom-ORD"><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>, the second constructs a decomposition of the form <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>A</mml:mi><mml:mo>=</mml:mo><mml:mi>L</mml:mi><mml:msup><mml:mi>L</mml:mi><mml:mo>†</mml:mo></mml:msup></mml:math> to precondition the system. These methods are widely applicable and both allow to efficiently solve BQP-complete problems.
Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

Cryptographic algorithm is the most commonly used method of information security protection for many devices. The secret key of cryptographic algorithm is usually stored in these devices' registers. In this paper, we propose an electromagnetic information leakage model to investigate the relationship between the electromagnetic leakage signal and the secret key. The registers are considered as electric dipole models to illustrate the source of the electromagnetic leakage. The equivalent circuit of the magnetic field probe is developed to bridge the output voltage and the electromagnetic leakage signal. Combining them, the electromagnetic information leakage model's function relationship can be established. Besides, an electromagnetic leakage model based on multiple linear regression is proposed to recover the secret key and the model's effectiveness is evaluated by guess entropy. Near field tests are conducted in an unshielded ordinary indoor environment to investigate the electromagnetic side-channel information leakage. The experiment result shows the correctness of the proposed electromagnetic leakage model and it can be used to recover the secret key of the cryptographic algorithm.
Toppling on Permutations with an Extra Chip

The study of toppling on permutations with an extra labeled chip was initiated by the first author with D. Hathcock and P. Tetali (arXiv:2010.11236), where the extra chip was added in the middle. We extend this to all possible locations $p$ as well as values $r$ of the extra chip and give a complete characterization of permutations which topple to the identity. Further, we classify all permutations which are outcomes of the toppling process in this generality, which we call resultant permutations. Resultant permutations turn out to be certain decomposable permutations. The number of configurations toppling to a given resultant permutation is shown to depend purely on the number of left-to-right maxima (or records) of the permutation to the left of $p$ and the number of right-to-left minima to the right of $p$. The number of permutations toppling to a given resultant permutation (identity or otherwise) is shown to be the binomial transform of a poly-Bernoulli number of type B.
Meta Distant Transfer Learning for Pre-trained Language Models

With the wide availability of Pre-trained Language Models (PLMs), multi-task fine-tuning across domains has been extensively applied.For tasks related to distant domains with different class label sets, PLMs may memorize nontransferable knowledge for the target domain and suffer from negative transfer.Inspired by meta-learning, we propose the Meta Distant Transfer Learning (Meta-DTL) framework to learn the cross-task knowledge for PLM-based methods.Meta-DTL first employs task representation learning to mine implicit relations among multiple tasks and classes.Based on the results, it trains a PLM-based meta-learner to capture the transferable knowledge across tasks.The weighted maximum entropy regularizers are proposed to make meta-learner more task-agnostic and unbiased.Finally, the meta-learner can be fine-tuned to fit each task with better parameter initialization.We evaluate Meta-DTL using both BERT and ALBERT on seven public datasets.Experiment results confirm the superiority of Meta-DTL as it consistently outperforms strong baselines.We find that Meta-DTL is highly effective when very few data is available for the target task.
Ulixes: Facial Recognition Privacy with Adversarial Machine Learning

Abstract Facial recognition tools are becoming exceptionally accurate in identifying people from images. However, this comes at the cost of privacy for users of online services with photo management (e.g. social media platforms). Particularly troubling is the ability to leverage unsupervised learning to recognize faces even when the user has not labeled their images. In this paper we propose Ulixes, a strategy to generate visually non-invasive facial noise masks that yield adversarial examples, preventing the formation of identifiable user clusters in the embedding space of facial encoders. This is applicable even when a user is unmasked and labeled images are available online. We demonstrate the effectiveness of Ulixes by showing that various classification and clustering methods cannot reliably label the adversarial examples we generate. We also study the effects of Ulixes in various black-box settings and compare it to the current state of the art in adversarial machine learning. Finally, we challenge the effectiveness of Ulixes against adversarially trained models and show that it is robust to countermeasures.
Immersive experience design path of memorial architectural space based on augmented reality technology

Memorial architecture is undoubtedly one of the oldest architectural types of human beings. During its long development, it has undergone great changes from form to function to emotional expression. Situational experience tour is a brand-new tourism mode, which is supported by computer digital technologies such as augmented reality technology, realistic modeling technology and tracking registration technology, and combines digital movies with real scenes through technical means. Immersive experience design of memorial architectural space from the perspective of immersive augmented reality technology is a new attempt of immersive experience design of memorial architectural space based on information age. Taking memorial architectural space as the breakthrough point, this paper analyzes and expounds the connotation of augmented reality technology. Immersive visual experience, as a design factor to be considered in memorial architectural space, plays an important role in promoting visual communication and space display.
Lackadaisical Quantum Walk in the Hypercube to Search for Multiple Marked Vertices

Adding self-loops at each vertex of a graph improves the performance of quantum walks algorithms over loopless algorithms. Many works approach quantum walks to search for a single marked vertex. In this article, we experimentally address several problems related to quantum walk in the hypercube with self-loops to search for multiple marked vertices. We first investigate the quantum walk in the loopless hypercube. We saw that neighbor vertices are also amplified and that approximately 1/2 of the system energy is concentrated in them. We show that the optimal value of l for a single marked vertex is not optimal for multiple marked vertices. We define a new value of \(l = (n/N)\cdot k\) to search multiple marked vertices. Next, we use this new value of l found to analyze the search for multiple marked vertices non-adjacent and show that the probability of success is close to 1. We also use the new value of l found to analyze the search for several marked vertices that are adjacent and show that the probability of success is directly proportional to the density of marked vertices in the neighborhood. We also show that, in the case where neighbors are marked, if there is at least one non-adjacent marked vertex, the probability of success increases to close to 1. The results found show that the self-loop value for the quantum walk in the hypercube to search for several marked vertices is \(l = (n / N) \cdot k \).
Tiny Drone Tracking Framework Using Multiple Trackers and Kalman-based Predictor

Unmanned aerial vehicles like drones are one of the key development technologies with many beneficial applications. As they have made great progress, security and privacy issues are also growing. Drone tacking with a moving camera is one of the important methods to solve these issues. There are various challenges of drone tracking. First, drones move quickly and are usually tiny. Second, images captured by a moving camera have illumination changes. Moreover, the tracking should be performed in real-time for surveillance applications. For fast and accurate drone tracking, this paper proposes a tracking framework utilizing two trackers, a predictor, and a refinement process. One tracker finds a moving target based on motion flow and the other tracker locates the region of interest (ROI) employing histogram features. The predictor estimates the trajectory of the target by using a Kalman filter. The predictor contributes to keeping track of the target even if the trackers fail. Lastly, the refinement process decides the location of the target taking advantage of ROIs from the trackers and the predictor. In experiments on our dataset containing tiny flying drones, the proposed method achieved an average success rate of 1.134 times higher than conventional tracking methods and it performed at an average run-time of 21.08 frames per second.
Entangling operations in nonlinear two-atom Tavis-Cummings models

We derive an analytical approximate solution of the time-dependent state vector in terms of material Bell states and coherent states of the field for a generalized two-atom Tavis-Cummings model with nonlinear intensity-dependent matter-field interaction. Using this solution, we obtain simple expressions for the atomic concurrence and purity in order to study the entanglement in the system at specific interaction times. We show how to implement entangling atomic operations through measurement of the field. We illustrate how these operations can lead to a complete Bell measurement. Furthermore, when considering two orthogonal states of the field as levels of a third qubit, it is possible to implement a unitary three-qubit gate capable of generating authentic tripartite entangled states such as the Greenberger-Horne-Zeilinger state and the $W$ state. As an example of the generic model, we present an ion-trap setting employing the quantized mode of the center-of-mass motion instead of the photonic field, showing that the implementation of realistic entangling operations from intrinsic nonlinear matter-field interactions is indeed possible.
What does parity mean? A detailed comparison of ASR and human transcription errors

Automatic speech recognition (ASR) has seen dramatic improvements as a result of advances in deep learning. This has led several recent studies to conclude that ASR is approaching parity with human performance, at least in certain speech contexts. These studies use average word error rate (WER) as their primary evaluation metric, dividing the total insertions + substitutions + deletions by the reference length (WER = (I + D+S)/Nr), to compare ASR systems to human transcribers. Averaging combined error types obscures important differences between human and ASR error patterns which impact human comprehension of the output. Human transcribers tend to delete pragmatic and discourse markers (such as fillers and backchannels) and disfluencies, whereas ASR tends to make more substitution errors on words. In conversational settings listeners are able to recover from missing discourse markers, function words, or backchannels, but word substitutions are harder to recover from because they interrupt the information flow. WER is a reasonable first pass metric of ASR performance, but when it comes to communicative parity, it averages out important ways in which it differs from human transcription.
Inter-Level Feature Balanced Fusion Network for Street Scene Segmentation

Semantic segmentation, as a pixel-level recognition task, has been widely used in a variety of practical scenes. Most of the existing methods try to improve the performance of the network by fusing the information of high and low layers. This kind of simple concatenation or element-wise addition will lead to the problem of unbalanced fusion and low utilization of inter-level features. To solve this problem, we propose the Inter-Level Feature Balanced Fusion Network (IFBFNet) to guide the inter-level feature fusion towards a more balanced and effective direction. Our overall network architecture is based on the encoder-decoder architecture. In the encoder, we use a relatively deep convolution network to extract rich semantic information. In the decoder, skip-connections are added to connect and fuse low-level spatial features to restore a clearer boundary expression gradually. We add an inter-level feature balanced fusion module to each skip connection. Additionally, to better capture the boundary information, we added a shallower spatial information stream to supplement more spatial information details. Experiments have proved the effectiveness of our module. Our IFBFNet achieved a competitive performance on the Cityscapes dataset with only finely annotated data used for training and has been greatly improved on the baseline network.