Reviewerly/exHarmony huggingface dataset:
The Problem of Distance Learning During the Covid-19 Pandemic

The Covid-19 pandemic has an impact on various sectors, including the education sector. Worldwide, no less than 1.38 billion students are affected. In Indonesia, around 68.8 million students are forced to study from home. This fact will certainly cause problems in the implementation of learning. The problems are related to various things, including the readiness of teachers and students to do or participate in distance learning, the readiness of learning facilities and infrastructure, or others. Various complaints lead to the problem. However, until now, accurate information based on in-depth research was not available. On that basis, this research was conducted to know the problems of distance learning in elementary schools in Banjarmasin City. This study used a quantitative descriptive method with a population of elementary school teachers in City Banjarmasin with a sample of 166 respondents, classified based on subject groups, with details of 53 adaptive teachers, 38 normative teachers, and 75 productive teachers spread across Banjar Utara District, West, Central, East, and South. The sampling technique used is proportionate stratified random sampling. The results showed that in general the teachers' perceptions of knowledge and experience related to online distance learning were still low. However, teachers have responded positively to technological developments and are aware of its potential for online-based distance learning. Besides, the ability and experience of teachers to use computers to integrate learning with online learning is in the poor category. The availability of information and communication technology facilities for the implementation of distance learning owned by teachers, students, and parents of students is also in the poor category. The lack of availability of facilities is certainly not very supportive of distance learning activities. These facilities include computers, printers, LCD projectors, cellphones, and internet connection. Based on the findings of this study, it is recommended for teachers and students to improve competency in information and communication technology that supports its integration in learning. Increasing internet access and providing online learning facilities are necessary, both by schools, teachers, and parents of students so that online learning does not experience problems.
Augmented Perception

In their contribution, Yannick Marszalek and Dominik Volz address the purposeful design of immersive virtual environments. In their research at HTWG Konstanz, University of Applied Sciences, they investigate the impact of a virtual environment on the effectiveness of the work performed in it, search for design variables, and observe the well-being of the users in the process. With their findings, Marszalek and Volz provide a first proposal to address the research gap regarding the influence of the environment on work in virtual realities on the basis of design research.
Oceanographic observation and prediction toward SOCIETY5.0

The high-resolution ocean model and high-density ocean observation have been developed to produce ocean big-data around the aquafarm located in the coastal seas toward realizing SOCIETY5.0. The high-resolution (~10 m) ocean simulation has been performed using the operational, meteorological and ocean predictions based on the multiscale resolution and nesting methods. To validate the simulated results, the high-density ocean observation has been conducted using the quad-maran automated vessel (RoboSen). RoboSen can measure more environmental data in the 3D space of the coastal oceans such as water temperature, salinity, and dissolved oxygen concentration than conventional observations with temporally and horizontally low density. Those novel state-of-art simulation and observation are expected to produce the novel datasets utilized for IoT and AI development and to create new values in aquaculture provinces.
Packer Identification Method for Multi-layer Executables with k-Nearest Neighbor of Entropies

The damage cost caused by malware is increasing in the world. Malware coders usually use the method of packing to hinder malware detection and analysis. It is a hard task even for professional malware analysts to unpack a re-packed or a multi-layer packed malwaresBat-Erdene et al. propose a method to identify a packer of multi-layer packing using SAX. Serdar shows that k-nearest neighbor algorithm is the best method to identify the packer of single-packing among the following 4 algorithms: k-Nearest neighbor, Best-first decision Tree, Sequential minimal optimization and Naive Bayes. It can be considered that k-nearest neighbor algorithm is also effective to identify the packer for multi-layer packed malwares.In this paper, we propose a method to identify the packer for multi-layer packed malwares by using k-nearest neighbor algorithm with entropy-analysis for the malwares.
Return probability and self-similarity of the Riesz walk

The quantum walk is a counterpart of the random walk. The 2-state quantum walk in one dimension can be determined by a measure on the unit circle in the complex plane. As for the singular continuous measure, results on the corresponding quantum walk are limited. In this situation, we focus on a quantum walk, called the Riesz walk, given by the Riesz measure which is one of the famous singular continuous measures. The present paper is devoted to the return probability of the Riesz walk. Furthermore, we present some conjectures on the self-similarity of the walk.
Autoregressive Image Generative Models with Normal and t-distributed Noise and the Bayes Codes for Them

In this paper, we propose an autoregressive stochastic generative model for images. This model should be one of the most basic models for the new type of lossless image compression which explicitly assume the stochastic generative model. We can easily expand it and theoretically interpret the implicitly assumed stochastic generative models in the various previous predictive coding methods as the expanded versions of our model. Moreover, we can utilize the achievements in the related fields where the linear regression analysis and its expansion are studied to construct the Bayes codes for these generative models. As an example, we expand our generative model from the one with normal noise to the one with the t-distributed noise. Then, we construct the sub-optimal Bayes codes for this generative model by utilizing the variational Bayesian method.
Cyber Crime Awareness and Corresponding Countermeasures

Earlier, the internet came as a primary source for the military. With time the evolution in the digital world leads to the expansion of usage of internet to one and all, hence with no wonders affecting privacy and security. People started misusing the cyber hub for the crimes known as cybercrime. A crime is called a Cybercrime that involves a computer and a network. Today in the 21 century, cyber criminals are dexterous and are collaborating which makes cybercrime a serious issue for the entire world. Such malicious users have committed different types of crime like data diddling, e-mail spoofing, web jacking, virus/warm, cyber defamation, online gambling, cyber pornography, financial crimes etc. It has become a necessity to counter such miscreants and save the people. Various organizations like Government agencies, Police departments, Cybercrime bureau etc. are continuously working to prevent cybercrime.In this paper, we have discussed cybercrime and security’s current scenario in India along with some methods like Elliptical cryptography curve, Router Security, Encryption etc. These algorithms ensure the decrease in the rate of cybercrime and hence increasing cyber security. Nation's economic growth and internal security completely depends on how well its cyberspace is shelled (Kaeo, 2003).
Revisiting the Business English Courses to Meet the Stakeholers’ Demand

In the international business communication, English has become a medium of communication. To respond to such a global challenge, it is vital to equip students with Business English courses to prepare them to be more competitive worldwide. Nevertheless, studying Business English is quite problematic to many non-native learners since they have to focus both on the subject matter and the language. The present study is conducted to investigate the perspectives of the students and alumni on the Business English courses at the Business Administration Department, State Polytechnic of Malang. A survey on the second year students and the alumni was conducted. The questionnaires were distributed to elicit their views on the courses, as well as their recommendations. The existing English syllabuses and materials were collected to be overviewed. The findings indicate most students are in favor of the course. Their motivation and interest in the course are good that they make some attempts to support their Business English skills acquisition. The business English competences, like: business presentation, business meeting, business socializing, negotiation, business correspondence, and knowledge, like global business issues are of their benefits to prepare them to work and develop their career in the future. The alumni claim they apply the Business English knowledge and skills in their workplace. However, the level of the application is different following their job position in the workplace. The students’ proposals for the course are that it should be presented in a more fascinating way and business communication skills are more emphasized. Besides, global business materials and vocabulary in business are to be more inserted. The alumni recommend providing more business communication practices and vocabulary enrichment. Showing the formal and informal English usage is also necessary. Besides, character building related to business needs to be inserted. The Business English syllabuses and materials were in line with the students’ and alumni’s expectation. The content and materials have already covered business knowledge and skills as expected by the stakeholder.
Distributed Computing Column 81

Overview. In this edition of the column, we have an exciting contribution from Shir Cohen, Idit Keidar, and Oded Naor (Technion), who provide an in-depth perspective on communication-efficient Byzantine Agreement. With the huge popularity of blockchains, the classic area of Byzantine Agreement has seen a surge of interest, and, given the large-scale and widely-distributed deployments of such mechanisms, communication efficiency is a chief concern. This column provides a gentle introduction to the area, by rst the early work in the 80s. This provides the necessary context for the recent exciting work on communication reduction, from the King &amp; Saia algorithm to Algorand. One very useful feature in this column's contribution is the fact that it provides a uni ed view of these results, along with the mathematical background to understand and di erentiate the underlying results. Many thanks to Shir, Idit and Oded for their contribution!
PENGARUH PENERAPAN MEDIA BINGO GAMES TERHADAP PEMBELAJARAN AL-QUR’AN HADITS DI KELAS IV MI DARUSSALAM SUMBERMULYO JOMBANG:

This article discusses the effect of the application of Bingo games media on learning Al-Qur'an Hadith, aims to determine 1) the application of bingo games media in learning Al-Qur'an Hadith, 2) the effect of the application of bingo games media on learning Al-Qur ' an Hadith. This study used a quantitative approach with a true experimental design, researchers used the Mann Whitney Test hypothesis test. The results show that: 1) the application of bingo games media is in accordance with what has been prepared in the Learning Implementation Plan (RPP), 2) there is an effect of the application of bingo games media on learning Al-Qur'an Hadith in class IV MI Darussalam Sumbermulyo Jombang with a sign value obtained 0.032.Keywords: Media Bingo Games, Learning Al-Qur'an Hadith
Working with the Ansible Configuration

The configuration file for Ansible controls how the system configuration utility, Ansible, will operate on the managed devices. This may include the way in which rights are escalated and the user account to use in making the connection to the managed device. Do these need to be the same on every project that you work with? Should individual administrators or developers have control over their own configuration? These are good questions, and questions we will try to answer here. Let’s look at both the contents of the configuration, what can go into an Ansible configuration file, and the hierarchy of configurations that can be made and their search order.
TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation

Automatic augmentation methods have recently become a crucial pillar for strong model performance in vision tasks. While existing automatic augmentation methods need to trade off simplicity, cost and performance, we present a most simple baseline, TrivialAugment, that outperforms previous methods for almost free. TrivialAugment is parameter-free and only applies a single augmentation to each image. Thus, TrivialAugment's effectiveness is very unexpected to us and we performed very thorough experiments to study its performance. First, we compare TrivialAugment to previous state-of-the-art methods in a variety of image classification scenarios. Then, we perform multiple ablation studies with different augmentation spaces, augmentation methods and setups to understand the crucial requirements for its performance. Additionally, we provide a simple interface to facilitate the widespread adoption of automatic augmentation methods, as well as our full code base for reproducibility. Since our work reveals a stagnation in many parts of automatic augmentation research, we end with a short proposal of best practices for sustained future progress in automatic augmentation methods.
Audit of NZ COVID Tracer QR poster display and use in Dunedin

Aims To assess how well the NZ COVID Tracer QR (Quick Response) code poster is displayed by Dunedin businesses and other venues in which groups of people gather indoors, and to calculate the proportions of visitors to those venues who scan the QR code poster. Methods We randomly selected 10 cafes, 10 restaurants, 10 bars, five churches, and five supermarkets and visited them at their busiest times. We evaluated the display of QR code posters using a six-item assessment tool that was based on guidance provided to businesses and services by the Ministry of Health, and we counted the number of people who entered each venue during a one-hour period and the number who scanned the QR code poster. Results All six criteria for displaying QR code posters were met at half of the hospitality venues, four of five churches, and all supermarkets. Scanning proportions were low at all venues (median 10.2%), and at 12 (30%) no visitors scanned; eight of these venues were bars. Conclusion This audit provides a snapshot of the display and scanning of QR code posters in a city with no managed isolation and quarantine facilities and where no COVID-19 cases have been detected for 10 months.
APPLICATION OF QUANTITATIVE ANALYSIS OF GEAR FAULT IN μ-SVD NOISE REDUCTION ALGORITHM DIAGNOSIS

In order to extract the fault features of mechanical equipment submerged by strong background noise, a general subspace denoising algorithm based on Singular value decomposition (SVD) is used to process the signal, that is, μ-SVD denoising algorithm. This algorithm overcomes the disadvantage of traditional wavelet threshold denoising algorithm, which only deals with the wavelet coefficients point by point and ignores the whole structure of the wavelet coefficients. The traditional SVD denoising algorithm is a special case when Lagrange multiplier μ = 0 in μ-SVD denoising algorithm. μ-SVD denoising algorithm includes filter factor, which can suppress the contribution of singular value dominated by noise contribution to the signal after denoising. The parameter selection method of μ-SVD denoising algorithm is discussed, and the influence of denoising order and Lagrange multiplier on denoising effect is emphatically studied. The test results of gear fault simulation signal and gear fault vibration signal at the early stage show that μ-SVD denoising algorithm is better than traditional SVD denoising algorithm in denoising effect. It can extract gear fault features better under strong background noise.
Periodicity for the fourier quantum walk on regular graphs

Quantum walks determined by the coin operator on graphs have been intensively studied. The typical examples of coin operator are the Grover and Fourier matrices. The periodicity of the Grover walk ...
The Impact of Technology on Access to Law and the Concomitant Repercussions: Past, Present, and the Future (From the 1980s to Present Time)

That technology increasingly impacts everything that is linked to law—from access to law, legal education, the services provided by the legal industry, and, increasingly, even adjudication (in-court or via alternative dispute resolution)—is a fact. The role that technology plays in these contexts varies, yet one may safely presume that the influence will intensify. In order to reflect on the future, this article canvasses and tries to draw some conclusions based on the comparison of accessibility to foreign and local law in the hard copy versus the digital and Internet-based, as well as the recently unfolding era of algorithms. The examples range from the curious encounter of Central and Eastern European socialist enterprises and law students with punitive damages and strict tortious liability known in the USA through the most recent launching of the first transnational letter of credit transaction exploiting blockchain technology. The advancements generated by technology advancements in these three stages are then reflected upon primarily from the perspectives of (i) researchers and lecturers of law as well as legal education; (ii) company boards and managements (especially foreign market-oriented business firms) formulating their business policies; and (iii) regulators as well as law and policy-makers. The article concludes with thoughts on the broader implications of enhanced access to law. In particular, it posits that technology has made the shift from ‘mechanical’ to ‘analytic access to law’ possible. Yet it also raises the more fundamental question of whether the advancements denote, and the selected examples properly illustrate, that a more fundamental shift is unfolding: a shift from governance by law to governance by technology?
Guides: Teaching with E-resources: Getting Links From OneSearch

This guide is meant to help faculty with using electronic library resources and integrating them into their course shells (in Blackboard). It covers how to find persistent links, proxy links, and copyright information related teaching.
Annealed Stein Variational Gradient Descent

Particle based optimization algorithms have recently been developed as sampling methods that iteratively update a set of particles to approximate a target distribution. In particular Stein variational gradient descent has gained attention in the approximate inference literature for its flexibility and accuracy. We empirically explore the ability of this method to sample from multi-modal distributions and focus on two important issues: (i) the inability of the particles to escape from local modes and (ii) the inefficacy in reproducing the density of the different regions. We propose an annealing schedule to solve these issues and show, through various experiments, how this simple solution leads to significant improvements in mode coverage, without invalidating any theoretical properties of the original algorithm.
Mask DNA led to homicide charges against West Allis man in fatal shooting

Prosecutors say on Sept. 27, 2019, Keith Wolf was watching TV with his wife and 7-year-old daughter when they heard something downstairs.
Localization does not occur for the Fourier walk on the multi-dimensional lattice

The existence of localization for the Grover walk on the multi-dimensional lattice is known. This paper gives some conditions for the existence of localization for the space-homogeneous quantum walks. We also prove that localization does not occur for the Fourier walk on the multi-dimensional lattice.
Pandemic emergency, crisis of knowledge and required public functions: Fundamental rights conditioned by science during the covid-19 crisis

The Covid-19 pandemic emergency has complicated the relationship between law and science, between technology and administration The urgency of man-aging the pandemic emergency, in a situation of scientific uncertainty, has shown that the State has to address several difficulties when obliged to take decisions of significant public interest having a strong impact on the fundamental rights and freedoms of citizens, even if, paradoxically, they are adopted to guarantee and protect them The Covid-19 pandemic is an example of coex-istence and close interrelation between emergency law, precautionary risk man-agement, and urgent decision-making It has highlighted the existence of a cir-cular process as the emergency arose from the occurrence of unexpected harmful events, resulting from unknown natural phenomena that caught human beings helpless and unprepared It also revealed the inadequacy of ordinary emergency management tools Scientific uncertainty has strongly influenced the modus operandi of national governments, which did not immediately adopt a uniform and concerted emergency government policy, despite the global nature of the phenomenon Rather, they devised epidemiological risk containment strategies based on hypotheses (or rather conjectures) formulated ex tunc by groups of trusted experts, specifically appointed The pandemic emergency, therefore, seems to have produced a negative spiral from the crisis of the “statute of science” to a crisis in the legal system It has been demonstrated that crises of knowledge, of institutions, of fundamental freedoms and legal protection are interconnected We should therefore question the role of political decisions and administrative discretion, when the “violence” of public decision-making is exacerbated – or perhaps overshadowed-–by presupposed scientific evaluations © 2020, University of Urbino All rights reserved
Unsupervised anomaly detection in digital pathology using GANs

Machine learning (ML) algorithms are optimized for the distribution represented by the training data. For outlier data, they often deliver predictions with equal confidence, even though these should not be trusted. In order to deploy ML-based digital pathology solutions in clinical practice, effective methods for detecting anomalous data are crucial to avoid incorrect decisions in the outlier scenario. We propose a new unsupervised learning approach for anomaly detection in histopathology data based on generative adversarial networks (GANs). Compared to the existing GAN-based methods that have been used in medical imaging, the proposed approach improves significantly on performance for pathology data. Our results indicate that histopathology imagery is substantially more complex than the data targeted by the previous methods. This complexity requires not only a more advanced GAN architecture but also an appropriate anomaly metric to capture the quality of the reconstructed images.
Library: Library Resources for Graduate Students: Publishing, Sharing & Open Access

This guide presents library resources, services, and programs that may be of interest to graduate students