Reviewerly/exHarmony huggingface dataset:
On Optimizing Interventions in Shared Autonomy

Shared autonomy refers to approaches for enabling an autonomous agent to collaborate with a human with the aim of improving human performance. However, besides improving performance, it may often also be beneficial that the agent concurrently accounts for preserving the user's experience or satisfaction of collaboration. In order to address this additional goal, we examine approaches for improving the user experience by constraining the number of interventions by the autonomous agent. We propose two model-free reinforcement learning methods that can account for both hard and soft constraints on the number of interventions. We show that not only does our method outperform the existing baseline, but also eliminates the need to manually tune a black-box hyperparameter for controlling the level of assistance. We also provide an in-depth analysis of intervention scenarios in order to further illuminate system understanding.
Mesoscopic and macroscopic quantum correlations in photonic, atomic and optomechanical systems

This paper reviews the progress that has been made in our knowledge of quantum correlations at the mesoscopic and macroscopic level. We begin by summarizing the Einstein-Podolsky-Rosen (EPR) argument and the Bell correlations that cannot be explained by local hidden variable theories. It was originally an open question as to whether (and how) such quantum correlations could occur on a macroscopic scale, since this would seem to counter the correspondence principle. The purpose of this review is to examine how this question has been answered over the decades since the original papers of EPR and Bell. We first review work relating to higher spin measurements which revealed that macroscopic quantum states could exhibit Bell correlations. This covers higher dimensional, multi-particle and continuous-variable EPR and Bell states where measurements on a single system give a spectrum of outcomes, and also multipartite states where measurements are made at multiple separated sites. It appeared that the macroscopic quantum observations were for an increasingly limited span of measurement settings and required a fine resolution of outcomes. Motivated by this, we next review correlations for macroscopic superposition states, and examine predictions for the violation of Leggett-Garg inequalities for dynamical quantum systems. These results reveal Bell correlations for coarse-grained measurements which need only distinguish between macroscopically distinct states, thus bringing into question the validity of certain forms of macroscopic realism. Finally, we review progress for massive systems, including Bose-Einstein condensates and optomechanical oscillators, where EPR-type correlations have been observed between massive systems. Experiments are summarized, which support the predictions of quantum mechanics in mesoscopic regimes.
Romantic-Computing

In this paper we compare various text generation models' ability to write poetry in the style of early English Romanticism. These models include: Character-Level Recurrent Neural Networks with Long Short-Term Memory, Hugging Face's GPT-2, OpenAI's GPT-3, and EleutherAI's GPT-NEO. Quality was measured based syllable count and coherence with the automatic evaluation metric GRUEN. Character-Level Recurrent Neural Networks performed far worse compared to transformer models. And, as parameter-size increased, the quality of transformer models' poems improved. These models are typically not compared in a creative context, and we are happy to contribute.
Adversarial Attack via Dual-Stage Network Erosion

Deep neural networks are vulnerable to adversarial examples, which can fool deep models by adding subtle perturbations. Although existing attacks have achieved promising results, it still leaves a long way to go for generating transferable adversarial examples under the black-box setting. To this end, this paper proposes to improve the transferability of adversarial examples, and applies dual-stage feature-level perturbations to an existing model to implicitly create a set of diverse models. Then these models are fused by the longitudinal ensemble during the iterations. The proposed method is termed Dual-Stage Network Erosion (DSNE). We conduct comprehensive experiments both on non-residual and residual networks, and obtain more transferable adversarial examples with the computational cost similar to the state-of-the-art method. In particular, for the residual networks, the transferability of the adversarial examples can be significantly improved by biasing the residual block information to the skip connections. Our work provides new insights into the architectural vulnerability of neural networks and presents new challenges to the robustness of neural networks.
Wavelet Transparency

Order-independent transparency schemes rely on low-order approximations of transmittance as a function of depth. We introduce a new wavelet representation of this function and an algorithm for building and evaluating it efficiently on a GPU. We then extend the order-independent Phenomenological Transparency algorithm to our representation and introduce a new phenomenological approximation of chromatic aberration under refraction. This generates comparable image quality to reference A-buffering for challenging cases such as smoke coverage, more realistic refraction, and comparable or better performance and bandwidth to the state-of-the-art Moment transparency with a simpler implementation.
SurfGen: Adversarial 3D Shape Synthesis with Explicit Surface Discriminators

Recent advances in deep generative models have led to immense progress in 3D shape synthesis. While existing models are able to synthesize shapes represented as voxels, point-clouds, or implicit functions, these methods only indirectly enforce the plausibility of the final 3D shape surface. Here we present a 3D shape synthesis framework (SurfGen) that directly applies adversarial training to the object surface. Our approach uses a differentiable spherical projection layer to capture and represent the explicit zero isosurface of an implicit 3D generator as functions defined on the unit sphere. By processing the spherical representation of 3D object surfaces with a spherical CNN in an adversarial setting, our generator can better learn the statistics of natural shape surfaces. We evaluate our model on large-scale shape datasets, and demonstrate that the end-to-end trained model is capable of generating high fidelity 3D shapes with diverse topology.
The Pomeron -- A Bootstrap Story

In a contribution to the volume {\it A Passion for Physics}, a collection of essays in honor of Geoffrey Chew's sixtieth birthday, I wrote, together with A. Capella, Uday Sukhatme, and Tran Thanh Van {\it The Pomeron Story.} This is a follow-up to that contribution. This sequel also serves as an opportunity to acknowledge my gratitude to Geoff as a PhD student under his tutelage.
Leaky Frontends: Security Vulnerabilities in Processor Frontends

This paper evaluates new security threats due to the processor frontend in modern Intel processors. The root causes of the security threats are the multiple paths in the processor frontend that the micro-operations can take: through the Micro-Instruction Translation Engine (MITE), through the Decode Stream Buffer (DSB), also called the Micro-operation Cache, or through the Loop Stream Detector (LSD). Each path has its own unique timing and power signatures, which lead to the side- and covert-channel attacks presented in this work. Especially, the switching between the different paths leads to observable timing or power differences which, as this work demonstrates, could be exploited by attackers. Because of the different paths, the switching, and way the components are shared in the frontend between hardware threads, two separate threads are able to be mutually influenced and timing or power can reveal activity on the other thread. The security threats are not limited to multi-threading, and this work further demonstrates new ways for leaking execution information about SGX enclaves or a new in-domain Spectre variant in single-thread setting. Finally, this work demonstrates a new method for fingerprinting the microcode patches of the processor by analyzing the behavior of different paths in the frontend. The findings of this work highlight the security threats associated with the processor frontend and the need for deployment of defenses for the modern processor frontend.
Rancang Bangun Sistem Informasi Berbasis Website Lembaga Pelatihan Kewirausahaan (LPK) Ayostart dengan Metode Extreme Programming (XP)

The Ayostart Entrepreneurship Training Institute is a training institution in Madiun City which was established with the aim of being a forum for every business actor to set up a business with optimal preparation so that it can increase the business to be more developed. The availability of trading land for UMKM actors from the Mayor of Madiun City, Mr. Maidi, made the agency conduct several business trainings to improve the economy of the people of Madiun City. All business processes that occur at LPK Ayostart are carried out offline at the Ayostart Office. This is deemed inefficient, so that the improvement of business processes that can be carried out to support the activities that occur at the Ayostart Entrepreneurship Training Institute (LPK) is to create a website-based entrepreneurship training information system so that the training can be accessed online and business actors who do not reside in Indonesia. Madiun can participate in activities that occur at the Ayostart Entrepreneurship Training Institute wherever they are. Making this website using the extreme programming method. Extreme Programming (XP) can be seen as a software development method that tries to increase the efficiency and flexibility of software development projects by combining simple ideas without compromising the quality of the software to be built.&#x0D; &#x0D; Keywords—: Entrepreneurship Training Institute, UMKM, Training, Website, Extreme Programming.
Rancang Bangun Aplikasi Pemesanan Dan Penjualan Berbasis E – Commerce Pada Produk UMKM Desa Kiringan Kabupaten Magetan (Studi Kasus: Ds. Kiringan Kec. Takeran Kab. Magetan)

The advancement of information technology is currently growing rapidly,especially the development of the internet has become a necessity to findinformation. The use of the internet allows everyone to easily carry out the processof buying and selling online known as "e-commerce". In UMKM of Kiringan Villagethere are chicken egg breeders numbering 28 breeders. One of the producers in thisstudy provided two types of chicken eggs, namely red chicken eggs and kampungchickens with a production of 2,450 eggs per day. The problem is that chicken eggssold have never been marketed online, so consumers do not know much about theexistence of chicken eggs in Kiringan Village. With this problem, the owner of achicken egg UMKM needs a marketing information system in the form of a website.In this study poured the idea to design an information system in the form of awebsite using the waterfall method to expand market share in order to increaseincome in chicken egg UMKM, The delivery process also uses a special containerof anti-breakible eggs that are good so that on the go when shipping no eggs arebroken, and also support the marketing of Chicken Egg UMKM in MagetanRegency. Effectiveness is supported by internet technology to market productsthroughout the magetan region, in order to improve the economy of UMKM owners.Keywords: Website-based applications, Waterfall, UMKM, Sales, E-commerce
Analisis dan Perancangan E-Commerce Mitra Dolanan Store Guna Meningkatkan Layanan Penjualan dengan Metode Extreme Programming

Mitra Dolanan Store is a company engaged in the retail of children's toys. However, the shop is still not supported with good facilities. As in the case of data processing goods and customers still use a system that is less efficient. Likewise in the marketing system in this store, they still do offline marketing by making banners and posters that are installed in front of the store. In this study, the method used in system design is the Extreme Programming method. The Extreme Programming method has the first stage of planning (Planning), then the second is designing (Design), then the third is coding (Coding), and finally the fourth is testing (Testing). These problems must be supported by implementing a system with structured and computerized functions in sales and purchases which is expected to assist shop owners in increasing their business activities. So we need an E-Commerce on a website-based Dolanan Store Partner. Through this web application, it can help Dolanan Store Partners eliminate competition between sellers and can be a special attraction for customers while helping to increase sales profits.
Saúde mental em psicólogos que atuam em hospitais durante a pandemia de Covid-19

Of a qualitative and quantitative nature, this study sought to understand and analyze the repercussions of the COVID-19 pandemic on the mental health of psychologists (as) in hospitals, through the correlation between two instruments: Hamilton’s Anxiety Assessment Scale (HAM-A) and a questionnaire made up solely and exclusively for this research, applied through an online form, the data analysis process took place through the statistical program SPSS (Statistical Package for the Social Science) and the combination of qualitative and quantitative data collected. This study had the voluntary participation of five hospital psychologists working in the front line of the COVID-19 confrontation identified by the codenames: Agnes, Eleanor, Sophia, Amália and Bianca. The results obtained point to a scarce literature regarding mental health research of hospital psychologists, besides the mental health of these professionals was also negatively affected, leading professionals to adopt different adaptation and coping strategies.
Information System Data Population in Gunung Panjang Samarinda Seberang

The development of technology today is getting faster. With the sophistication of today's technology, we can facilitate the work to be done. We can find the information we need and we can expand the communication network using advanced technology. Currently, population data collection in the government system can be said to be ineffective. Population data collection with a manual system can cause inefficient processing of population data and administrative services will take a longer time. This study uses two methods of data collection, namely: interviews (interviews) and observation. The system development used in this research is the Waterfall model, which starts with the analysis, design, coding, testing, and maintenance stages. The Gunung Panjang Village Population Data Information System was created using several programming languages, Hypert Text Markup Language (HTML), Hypertext Preprocessor (PHP), and Cascading Style Sheet (CSS). and MySQL. It can be concluded that the results of this study are an Information System for Population Data Collection in Gunung Panjang Village which can be used for processing population data and as a means of delivering information on Gunung Panjang Village through the website.
A High-dimensional Anomaly Detection Algorithm Based on IForest with Autoencoder

The existing anomaly detection algorithms based on isolated forest are limited by the height of isolated tree. High-dimensional problem domains pose significant challenges for anomaly detection. The presence of irrelevant features can conceal the presence of anomalies. This problem known as curse of dimensionality, is an obstacle for many anomaly detection techniques. Building a robust anomaly detection model for high- dimensional data requires the combination of an unsupervised feature extractor and an anomaly detector. A high-dimensional anomaly detection algorithm is proposed based on isolated forest with deep autoencoder (AE-IForest). Firstly, AE-IForest maps the high-dimensional and nonlinear original data to the low- dimensional space by a deep self-coding network. In the low-dimensional space, the isolated forest algorithm is used to sort the data isolation score, and the reconstruction error of the samples is fused to detect the abnormal data. Finally, the experimental results on six data sets show that the anomaly detection effect of AE-IForest algorithm is better than three classical algorithms LOF, IForest and SVDD. AE-IForest is an efficient anomaly detection model for high-dimensional data.
Rhodes: A Next-Generation OS based on Resource Governance Model

&lt;p&gt;The kernel is the core part of an operating system. At present, four types of kernels are widely available: monolithic kernels, microkernels, hybrid kernels, and exokernels. These kernel architectures are either too tightly-coupled, like monolithic kernels, put too many modules into the kernel, or too free, like exokernels, allow users to freely develop core features such as IPC, Virtual Memory, etc, or have no rules, like hybrid kernels, kernel modules organization is uncontrolled. In recent years, to solve these problems, resource management concept frequently appears in industry and academia. Although resource management concept makes resources in OSes orderly, no existing OSes or software systems can modify and extend management rules conveniently and dynamically.&lt;/p&gt; &lt;p&gt;This paper proposes a resource governance model that places resources such as applications and hardware into the model. Through unified rule governance, the organization of resources is more orderly and scalable. At the same time, by separating rules from resources, rules in the model are also scalable and flexible. Based on the model, we built Rhodes OS that allows users to modify and extend resource management rules by governance center which separates rules from resources. In addition, Rhodes also fits all kinds of OSes that are optimized for specific scenarios such as mobile, big data, IoT and AI. We implemented Rhodes on x86-64 and evaluated it. Our evaluation results show that applications performance in Rhodes is equivalent to Linux in native mode. So we believe that OSes will enter resource governance age from resource management age in the near future.&lt;/p&gt;
Design and Build an Internet of Things (IoT) Automatic TV Broadcasting Antenna System

Nowadays, television is used for educational purposes. It is easily accessible through air-to-air broadcasts and can be connected via satellite. What is witnessed on a television screen is all image and sound elements. Many people feel uncomfortable watching television shows because when the television is used, the broadcasts that appear are not all images and sounds that can be seen and heard properly. Most antennas used by every household are patented in a certain position. Based on the existing description, the problem that would be solved is how to design an IoT-based TV broadcasting antenna system to make it easier to watch television with clear broadcasts and good sound without changing the antenna's position manually. With the design method, the tool to be made consists of a flowchart and a circuit design, namely, building a system with inputs, processes, and outputs. The automatic TV broadcasting antenna system based on the internet of things (IoT) is a system that points the antenna in the best position for each selected broadcast that can be controlled via Android using the Blynk IoT Application. After that, the test was carried out by taking data at two locations for the IoT antenna. The assessment results showed that each location was different, and the position of the antenna direction would also be different, so the location of the antenna must be changed by changing the angle contained in the Arduino IDE software.
On the randomness of time ordered quantum measurements

Abstract A new method for efficient, high-quality randomness extraction is presented. The method relies on quantum processes such as the emission of single photons and their subsequent detection, where each detection event has an associated detection time. We show that, by utilising the number of possibilities to arrange a timed quantum measurement sequence, the efficiency can be increased many-fold compared to current methods. The method delivers fundamentally uniform randomness and therefore does not need any post processing or de-biasing.
Interactive Dashboard with Visual Sensing and Fast Reactivity

These days, technology is growing rapidly, and the market has been introduced with lots of fascinating ways to interact with computers. The advancement of deep learning models and hardware technology also enables more applications with fancy features to be built. The importance of hand gesture recognition has increased due to the prevalence of touchless applications. However, developing an efficient recognition system needs to overcome the challenges of hand segmentation, local hand shape representation, global body configuration representation, and a gesture sequence model. This paper proposed an interactive dashboard that could react to hand gestures. This is also an initiative of the Tunku Abdul Rahman University College (TAR UC) Smart Campus project. Deep learning models were investigated in this research and the optimal model was selected for the dashboard. In addition, 20BN Jester Dataset was used for the dashboard development. To set up a more user-friendly dashboard, the data communication stream between the captured input stream and commands among the devices were studied. As to achieve higher responsiveness from the dashboard, evaluation on data communication protocols which were used to pass the input data were included in the study.
GENERAL ASPECTS OF STUDYING HYPERTEXTS AS AN OBJECT OF LEXICO-SEMANTIC ANALYSIS

The article is devoted to the problems of hypertext research as an object of lexical-semantic analysis. The article defines the concept, essence and features of hypertexts. Special attention is paid to lexical and semantic characteristics of hypertexts, as well as defining features of historical realities in hypertexts on the material of the electronic encyclopedia Wikipedia. It was established that in some cases it is inappropriate to use a literal translation of historical realities in hypertexts, as this affects the logical structure of the sentence and the adequacy of the translation as a whole. Keywords: hypertexts; link; electronic hypertexts; translation; lexical and semantic characteristics.
Threat modeling framework for mobile communication systems

Due to the complex nature of mobile communication systems, most of the security efforts in its domain are isolated and scattered across underlying technologies. This has resulted in an obscure view of the overall security. In this work, we attempt to fix this problem by proposing a domain-specific threat modeling framework. By gleaning from a diverse and large body of security literature, we systematically organize the attacks on mobile communications into various tactics and techniques. Our framework is designed to model adversarial behavior in terms of its attack phases and to be used as a common taxonomy matrix. We also provide concrete examples of using the framework for modeling the attacks individually and comparing them with similar ones.
On-site and Online Academic Performance During the Pandemic

This article analyzes the on-site and online academic performance obtained in a written communication course at a Peruvian university in the context of the COVID-19 pandemic. The methodology applied corresponds to Grounded Theory in data collected and codified through two procedures: the reconstruction of pedagogical strategies and the interpretation of quantitative data corresponding to learning outcomes. Despite the adverse context, it is concluded that the effective use of pedagogical approaches overcomes situational constraints. Moreover, it achieves similar learning outcomes in both face-to-face and online modalities.