Reviewerly/exHarmony huggingface dataset:
Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance

Recent work on entity coreference resolution (CR) follows current trends in Deep Learning applied to embeddings and relatively simple task-related features.SOTA models do not make use of hierarchical representations of discourse structure.In this work, we leverage automatically constructed discourse parse trees within a neural approach and demonstrate a significant improvement on two benchmark entity coreference-resolution datasets.We explore how the impact varies depending upon the type of mention.
Development of Rubric for enhancing Sensemaking among Team members in PBL in Entrepreneurship Education

Today's entrepreneurship education in Japan is mainly based on knowledge- and skill-oriented programs in the style of Silicon Valley in the United States. However, for university students belonging to Generation Z, the motivation for entrepreneurship tends to be not only wealth, but also altruistic "meaning" such as social contribution and connection with others. Self-awareness of the purpose and implications of entrepreneurship is necessary, but there are very few opportunities for university students to become self-aware in entrepreneurship education. However, Nonaka's SECI model and Weick's concept of Sensemaking are beginning to attract attention, and specific methodologies for self-awareness are desired. The author proposed a methodology to realize self-awareness from the viewpoint of Affective Engineering in a paper published in ISASE2020 on "knowing oneself. In addition, in the paper published in IJAE 2020, I verified the effectiveness of affective sense of value extraction. In this paper, the author discuss the importance of the process of Sensemaking, which has been difficult to supplement in business administration and entrepreneurship research, from the viewpoint of Affective engineering, and propose a rubric as self-assessment tool for PBL participants.
Discourse Markers in Tertiary Level Students’ Essay Writing: Ability and Problems

Writing is a fundamental, yet complicated part of language learning. In writing, Discourse Markers is an indispensable component of writing quality. The aim of the present study was to find out how Discourse Markers (DM) were applied to build coherence in EFL students’ essay writing and the problems encountered. Descriptive design was applied; analyzed 52 target DM and how they were used in 30 academic essay writing. The participants of the study were 30 students majoring in English Education of UIN Raden Fatah Palembang academic year 2019/2020. The results revealed that the participants employ 32 DM in 221 occurrences, in which 102 occurrences were inappropriately used. The problematic matters cover non-equivalent exchange (52 occurrences), and overuse (48 occurrences). Despite their awareness of the importance of DM to assure the coherence of their essays, they need to develop their ability to use DM correctly and efficiently to make their writing connected more logically. Keywords: discourse markers, coherence, essays.
The Groundless Use of Linearity in Daily Thinking and Decision-making

The overuse or groundless use of linearity, that is the fallacy of omnipotent linearity, intertwines our everyday lives and decisions. The misconception of linearity is not an isolated phenomenon, yet we do not handle this question in the proper way. The examples of MPG (Miles per Gallon) and MPH (Miles per Hour) or driving speed have something else in common: there is a widely used indicator conveying a false impression about the nature and physical, economical effects of the described phenomena by creating the illusion of linearity, leading to faulty decisions. In this paper, I show the common cases where we often make linear mistakes, and for which I can give illustrations drawn from scientific publications or everyday examples. Fresh survey research has been done in order to reveal the presence of linearity in the daily decision-making in terms of its groundless use. The article also identifies some common roots to the problem; it also outlines the psychological mechanisms and possible policies to help avoid them.
POPULARIZATION OF SCIENTIFIC CONTENT IN UKRAINE: ON THE EXAMPLE OF “MY SCIENCE”, “ART”, “PUBLIC” (SCIENCE)

The specifics of coverage of popular science materials on the example of such media as "Kunsht", "Moya Nauka" and "Hromadske" (Science) are considered. The content and topics of materials, frequency of publication, genres, specifics of publications, the presence of these media in social networks and the diversity of content are analyzed. The list of topics that most often cover the selected media, the quantity and quality of content published during the calendar month is analyzed. Also the quality of coverage of the topic of coronavirus SARS-CoV-2 and the pandemic of 2020, the development of a vaccine at all stages against the coronavirus SARS-CoV-2, its types and proven effectiveness. The direction of movement of popular science media according to the definition of In Science. The list of Ukrainian popularizers of science is given. The importance of popularization of science and daily development of science was emphasized, so that there is no gap between the knowledge of scientists and the knowledge of ordinary citizens, and the importance of creating new popular science media in Ukraine. And also on the study of the language of modern science, which is English. Because in this language, publications relating to science, technology, and all advanced scientific research are published. Thanks to English-language publications, promoters have the opportunity to learn about the latest discoveries and inventions. And thus, to quickly bring to the public the latest scientific knowledge. The small number of popular science media in Ukraine and the importance of filling this niche are emphasized, as the audience sees the need for it. And also in the importance of promoting popular science content through social networks such as YouTube, Instagram, Facebook, Twitter, Telegram. The key directions of development of Ukrainian scientific popularization and its functions are outlined. The definitions of the terms “popularization of science”, “popular science media” and the functions of popularization of science are given.
Usability of Jawara Sains Mobile Learning Application Using System Usability Scale (SUS)

The application of interactive learning multimedia is one of the factors that impact the learning process for achieving learning outcomes. In developing a mobile application, the main principle is usability. This research goal is to presents a usability evaluation of the Jawara Sains, which is a mobile application to learn science subjects. This research used a System Usability Scale (SUS) questionnaire to measure the level of users’ perceived usability. This score can indicate the usability performance of effectiveness, efficiency, and ease of use. Jawara Sains's SUS score achieved 75.45, which indicates a B grade, acceptable, and categorized in the good range. This score can also indicate whether a user is a promoter or not. The analysis showed that the Jawara Sains is categorized into the passive Net Promoter Score (NPS), which means users will not influence other people. Therefore, recommendations are needed for its usability improvements.
Multiplicative noise and heavy tails in stochastic optimization

Although stochastic optimization is central to modern machine learning, the precise mechanisms underlying its success, and in particular, the precise role of the stochasticity, still remain unclear. Modelling stochastic optimization algorithms as discrete random recurrence relations, we show that multiplicative noise, as it commonly arises due to variance in local rates of convergence, results in heavy-tailed stationary behaviour in the parameters. A detailed analysis is conducted for SGD applied to a simple linear regression problem, followed by theoretical results for a much larger class of models (including non-linear and non-convex) and optimizers (including momentum, Adam, and stochastic Newton), demonstrating that our qualitative results hold much more generally. In each case, we describe dependence on key factors, including step size, batch size, and data variability, all of which exhibit similar qualitative behavior to recent empirical results on state-of-the-art neural network models from computer vision and natural language processing. Furthermore, we empirically demonstrate how multiplicative noise and heavy-tailed structure improve capacity for basin hopping and exploration of non-convex loss surfaces, over commonly-considered stochastic dynamics with only additive noise and light-tailed structure.
Hardware Security in Emerging Technologies: Vulnerabilities, Attacks, and Solutions

This Special Issue of the IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS (JETCAS) is dedicated to demonstrating the latest research progress in the area of hardware security in emerging technologies.
An Efficient Secure Auditing Framework for Big Data Storage in Cloud Computing Environment

Cloud storage enables to use and manage remote data efficiently but increase the risk of tampering data.This proposed paper a public auditing-based framework to develop a novel system for secure data auditing in cloud storage.We build a dynamic index table with no requirement to transfer elements in the update operation for inserting or deleting.If data is not incorporate in the cloud, the auditor from a third party can identify the corrupted block.The authorization is implemented between cloud storage and third-party to prevent dos attack.The proposed model is flexible, efficient, and secure as per detailed analysis and simulation results.
Reception of Kant’s Epistemological Ideas in Fyodor Golubinsky’s Metaphysics

Kant’s views on space and time as well as his doctrine of the categories of understanding attracted the attention of thinkers belonging to the Russian spiritual-academic philosophical tradition of the nineteenth and early twentieth centuries. A prominent representative of these was Fyodor Golubinsky. He was among the first to react to Kant’s “Copernican turn”. He did not merely study the epistemological ideas of Kant but embraced them and modified them in the framework of his own philosophical teaching. To determine why Golubinsky turned to Kant’s ideas, to what extent he shared them and with what he disagreed and why, I propose to reconstruct Kant’s and Golubinsky’s ideas on space and time and to compare their doctrines of the categories of understanding. I come to the conclusion that Golubinsky borrowed some propositions of Kant’s theory of space and time, specifically, the procedure of identifying forms of sensibility — space and time — their a priori character, their being part of sensible intuitions and, finally, their definition as essential properties of sense perception. Golubinsky, unlike Kant, considers space and time to be objective. In his doctrine of the categories of understanding Golubinsky follows Kant in that the foundation of the categories of understanding is the unity of self-consciousness but he attributes the unity of self-consciousness to reason’s idea of the Infinite, whereas Kant sees it in the understanding. With some reservations, it can be said that Golubinsky adopts Kant’s table of categories but changes their order. As for the meaning of the categories, for Golubinsky they are not merely laws of cognising things, but laws of their being. In conclusion, I show that Golubinsky forms his epistemological concept in polemics with Kant, borrowing from him only those propositions which fit his metaphysics or modifying them to that end.
Scheduling Proximity Data Exchange for Contact Tracing

The data is generated using analytical model for analysis
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search

Neural architecture search (NAS) automates the design of deep neural networks. One of the main challenges in searching complex and non-continuous architectures is to compare the similarity of networks that the conventional Euclidean metric may fail to capture. Optimal transport (OT) is resilient to such complex structure by considering the minimal cost for transporting a network into another. However, the OT is generally not negative definite which may limit its ability to build the positive-definite kernels required in many kernel-dependent frameworks. Building upon tree-Wasserstein (TW), which is a negative definite variant of OT, we develop a novel discrepancy for neural architectures, and demonstrate it within a Gaussian process surrogate model for the sequential NAS settings. Furthermore, we derive a novel parallel NAS, using quality k-determinantal point process on the GP posterior, to select diverse and high-performing architectures from a discrete set of candidates. Empirically, we demonstrate that our TW-based approaches outperform other baselines in both sequential and parallel NAS.
Effect of Smooth Transition and Hybrid Reality on Virtual Realism: A Case of Virtual Art Gallery

Virtual reality (VR) is finding applications in a wide range of industries; however, a significant number of users find VR experience considerably different from the real-world experience.To match the real-world experience, the VR experience should look real, should be immersive, and be in line with the users' anticipation.Achieving realism in the virtual representation of objects, however, presents several technical challenges.This study presents a new approach, "Smooth Transition and Hybrid Reality (STHR)," to easily enhance VR realism.In this approach, the participants are exposed to a mix of real-world objects (RWO) and virtual objects (VO), and a smooth transitioning from the real world to the VR space is obtained by making the real-space highly relevant to the VR space and viceversa.To test the effectiveness of STHR, different experiments on spatial awareness were conducted, and finally, a virtual art gallery was created for the public.A total of 21 participants were included in the study and were randomized into experiment and control groups.The results indicated that the interaction with an RWO in the initial phase of VR significantly increases the task completion time and the attention (both, p<0.05).It was found that almost 50% of the participants relied on prior knowledge of the real space even when different visual information is delivered through VR.STHR based virtual art gallery (VAG) was created for the public, and the experience of random visitors was noted.In VAG, haptic feedback was provided by using an RWO (3D printed artwork), and the smooth transition from RW to VR was maintained.The average time spent in the VAG more than 5 minutes, and the feedback of visitors was highly positive.
Research on the Application of Artificial Intelligence in Music Listening Learning -- Taking Intelligent Hearing Training as an Example

Abstract The integration of AI and intelligent big data can simulate the process of human thinking and reasoning, and realize efficient neural network evolution and algorithm iteration. Its utilization in the field of music education can extend and expand the process of music teaching, and gradually become a powerful teaching assistant and tool. Based on this, this paper first analyses the integration and utilization status of AI and music listening teaching, then studies the utilization of AI in music listening learning, and finally gives the utilization strategy and optimization strategy of AI in music listening learning.
Research on the Construction of Multimedia Assisted Classroom Education Mode of British and American Literature Course

Abstract At present, there are still many problems and deficiencies in the teaching of British and American literature, especially the examination oriented education mode is difficult to ameliorate the comprehensive quality of students, which limits the amelioration of the teaching quality and level of British &amp; American literature. Based on this, this paper first analyzes the connotation and principle of multimedia assisted classroom education mode, then studies the multimedia assisted classroom education mode of British &amp; American literature course, and finally gives the construction strategy of multimedia assisted classroom education mode of British &amp; American literature course.
Formation and development of digital skills in university education

The aim is to develop a concept for implementing a systematic approach to the practice of forming and developing digital skills in higher education institutions. In this research, the methods of analysis and synthesis have been applied to integrate various approaches to the formation of digital skills into university education. Research results. Within the framework of a systematic approach to the formation and development of digital skills, consistent linking of the following approaches is suggested: standard-oriented, expert-oriented, student-oriented, problem-oriented. Integration of these approaches will ensure synergy in a changing technological environment. The main principles of a systematic approach are defined as processability, flexibility, and adaptability, problem orientation, timeliness, creativity. The scientific value of the research lies in the integration of various approaches that are practically used in university education to develop the concept of digital skills management.
Quantum metrology with coherent superposition of two different coded channels*

We investigate the advantage of coherent superposition of two different coded channels in quantum metrology. In a continuous variable system, we show that the Heisenberg limit 1/ N can be beaten by the coherent superposition without the help of indefinite causal order. And in parameter estimation, we demonstrate that the strategy with the coherent superposition can perform better than the strategy with quantum switch which can generate indefinite causal order. We analytically obtain the general form of estimation precision in terms of the quantum Fisher information and further prove that the nonlinear Hamiltonian can improve the estimation precision and make the measurement uncertainty scale as 1/ N m for m ≥ 2. Our results can help to construct a high-precision measurement equipment, which can be applied to the detection of coupling strength and the test of time dilation and the modification of the canonical commutation relation.
DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering.

We introduce DoubleField, a novel representation combining the merits of both surface field and radiance field for high-fidelity human rendering. Within DoubleField, the surface field and radiance field are associated together by a shared feature embedding and a surface-guided sampling strategy. In this way, DoubleField has a continuous but disentangled learning space for geometry and appearance modeling, which supports fast training, inference, and finetuning. To achieve high-fidelity free-viewpoint rendering, DoubleField is further augmented to leverage ultra-high-resolution inputs, where a view-to-view transformer and a transfer learning scheme are introduced for more efficient learning and finetuning from sparse-view inputs at original resolutions. The efficacy of DoubleField is validated by the quantitative evaluations on several datasets and the qualitative results in a real-world sparse multi-view system, showing its superior capability for photo-realistic free-viewpoint human rendering. For code and demo video, please refer to our project page: this http URL.
Application of Mobile App in English Teaching in an Intelligent Environment

With the rapid development of social economy and technology, the application of technology in the field of education has also been further developed. The past paper information carriers can no longer fully meet the development needs of the modern society. In this context, this thesis explores a learning model that combines mobile learning based on mobile apps with English teaching. The school’s hardware facilities have been continuously updated with the development of social information technology, and intelligent voice systems have been continuously introduced into classrooms. This article focuses on exploring the application of mobile app in English teaching in a smart environment, using the implementation of the mobile learning English model, and dividing two identical classes into an experimental class and control class through questionnaires and comparisons. The experimental design finally concluded that the use of mobile app to assist English teaching in all aspects of the relative improvement of the English performance of the class, the teaching effect is obvious, effectively improves students' interest in learning English and, at the same time, realizes students’ mobile learning, changes the scope of teaching activities from classroom changes to a wider range, and plays a role in consolidating and supplementing classroom English.
Safe Reinforcement Learning Using Advantage-Based Intervention

Many sequential decision problems involve finding a policy that maximizes total reward while obeying safety constraints. Although much recent research has focused on the development of safe reinforcement learning (RL) algorithms that produce a safe policy after training, ensuring safety during training as well remains an open problem. A fundamental challenge is performing exploration while still satisfying constraints in an unknown Markov decision process (MDP). In this work, we address this problem for the chance-constrained setting. We propose a new algorithm, SAILR, that uses an intervention mechanism based on advantage functions to keep the agent safe throughout training and optimizes the agent's policy using off-the-shelf RL algorithms designed for unconstrained MDPs. Our method comes with strong guarantees on safety during both training and deployment (i.e., after training and without the intervention mechanism) and policy performance compared to the optimal safety-constrained policy. In our experiments, we show that SAILR violates constraints far less during training than standard safe RL and constrained MDP approaches and converges to a well-performing policy that can be deployed safely without intervention. Our code is available at https://github.com/nolanwagener/safe_rl.
Alumni Social Networking Site

A social networking site is an online platform that allows users to create a public profile and interact with other users. In this constantly updating world, there’s a need of a network that helps the institution to keep track of their alumnae and vice versa. And also, there might be a need of a friendly guidance to the students regarding their career. The main objective of this project is to build an alumni website and social networking site that establishes a link between the present students and the alumnae of the institute. This helps the institution keep a record of their old students. Also, it does not have much staff involvement and thus, will cleanly act as a bridge between the alumnae and the present students. This website provides a user-friendly interface that facilitates the user to understand the working of the site easily. The user will be able to register or sign up and log in to their timelines and interact with other users. The user can share ideas, digital photos and videos, posts, personally chat, and inform others about online or real-world activities and events.