Reviewerly/exHarmony huggingface dataset:
Improvement of Skills through the Technology Integrated Learning in English Language

Now we are thrown into an era of technology, we can't think of a step without technology.For English language learning it is not an exceptional issue.Technology is not a supplementary thing in this modern era rather it is essential and ubiquitous in the English language teaching-learning process.Due to COVID-19 Pandemic teaching-learning situation has taken a different track i.e. it shifts from the traditional path of teaching to technology-integrated teaching.This digital realm of English language learning for the amelioration of skills paved the way to amalgamate with the international arena.Technology-mediated learning can only be flourished and encouraged by the active participation of the teachers as well as the administrators and other authorities.The teacher should not be stuff of content knowledge rather a teacher should have Technological, Pedagogical and Content knowledge.For teaching the English language and inculcate skills technology has a great role, especially since this situation has made it mandatory to use technology conveniently.In the teaching-learning process, there are mainly four skills -reading, writing, speaking, and listening.Listening and reading are known as 'receptive skills' as it focuses on the product of reception by our five senses.The other two skills speaking and writing are known as productive skills.The four types of skills can be acquired the various tools.The present study highlights the various educational technologies to enhance the skills regarding reading, writing, speaking and listening in English Language learning.
Team Member Selection in Global Software Development—A Blockchain-Oriented Approach

Global Software Development (GSD) is gaining importance and touching large user base with accessibility to multiskilled human resources, 24 hours working cycles because of geographically located teams, and promoting raid software development. The main challenge in GSD is to select team members in a transparent and fair manner. A well thought-out decision in this regard enhances team spirit and reduces technical and strategic issues, including understanding of different factors and involving task dependencies. This chapter proposes a novel blockchain-oriented approach for transparent team member selection, ensuring privacy, verifiability, completeness, and uniqueness in the entire selection process. Results of experimentation conclude that the proposed method is transparent and effective in selecting team members without ambiguity.
A recommendation algorithm based on local principle component analysis in mobile wireless sensor networks

Modern technological advances have created low-cost, low-power, multi-functional micro sensing devices, which can form a network of thousands of sensors distributed in a wide area After data collection, processing and analysis, sensor networks can obtain information at any time and anywhere, so as to become a part of intelligent environment In a wide range of applications, sensor networks have innovated the sensing function This is because of its reliability, accuracy, flexibility, cost performance, and ease of use The data detected and collected by intelligent sensors may involve machine failures, earthquakes, floods, and signs of terrorist attacks The functions of sensor networks are: collecting information, processing information, monitoring the environment, which can be used for military or civil. Sensor network is a comprehensive technology based on wireless communication, digital electronics, MEMS and so on According to the high dimensionality and sparsity of rating matrix in traditional collaborative filtering recommendation system, a new recommendation model based on Local Principle Component Analysis is proposed in mobile wireless sensor networks to make dimension reduction for different subject genre respectively, and remainsthe real interested users in one specific subject of the web pages.
Toward Distributed Ledger Support for 5G Network Services

The fifth generation (5G) wireless networks technologies support diverse vertical applications by connecting heterogeneous devices and machines, promising drastic improvements in terms of low latency, increased network capacity and enhanced system throughput. Despite all these advantages that 5G will bring about, there are still major challenges to be addressed, including decentralization, transparency, risks of data interoperability, network privacy and security vulnerabilities. On paper, Distributed Ledger Technologies provide a framework to effectively handle most challenges in 5G networks. The talk outlines recent developments in blockchain-based 5G services, focusing on the potential of blockchain for key 5G technologies, including edge computing, Network Function Virtualization, Network Slicing, and M2M communications and for 5G services, including from spectrum management, virtualization, and resource management. Then, it considers the properties that DLT can support in terms of trust, privacy and security, identifying and possible 0research challenges with open issues.
Research on the Application of Computer Big Data Multimodal Teaching Mode in College

Many applications of computer-assisted English learning in colleges and universities lack the evaluation and feedback of multimodal learning. The article describes a multimodal teaching system of spoken English in colleges and universities using speech recognition technology. In addition to the usual pronunciation scoring, we also provide error detection based on phoneme association and phoneme recognition. Combines improvement suggestions from the Correction Knowledge Base and Prosody Correction Speech. The system can help learners in a timely manner. The experimental results show that the system can correct most of the unintentional mistakes of learners with a certain base.
Smart Microgrid-Based Energy Management Using Blockchain

The traditional energy resources are not able to suffice present requirements. Renewable energy resources, efficient management of the energy, saving distribution cost of energy, and cheaper availability of energy to end-users are some of the crucial issues in energy supply and management today. The distributed- network concept of Blockchain technology is having capability to modernize the energy generation and distribution sector. The energy industry is consistently catalyzed by innovations including rooftop solar, electric vehicles, communication among energy devices, smart metering, and energy cryptocurrency. Distributed ledger technology of Blockchain has more possibilities to expand the efficiencies for utility providers by finding the owners of grid materials. Blockchain offers exclusive solutions for renewable energy supply in addition to origin tracking. Blockchain technology is getting popular in many use cases around the world, which includes new representations with blockchain for energy marketplaces, real-time data management, renewable energy certificates, and moving carbon credits. Combined efforts from technology developers in energy supply fields, academicians, financial institutions, and government sectors to coordinate Blockchain with the energy sector is one of the smartest and spectacular technology innovations in recent times. The blockchain energy schemes are designing peer-to-peer energy markets. A peer-to-peer energy market is a distributed network of people who sell and buy surplus energy from other contributors. These energy markets help the common people by reducing control from traditional wholesale entities. This energy management is usually done with the help of Microgrids, also known as Smartgrids. End users can access prepaid energy, which can be done by easy mobile transactions. Many companies have connected communities to each other for creating Microgrids and visualize a bright future with entirely distributed peer-to-peer grids. The main advantages of Blockchain in the energy segment are cost reduction, environmental sustainability, more security, and transparency for stakeholders with the benefit of not compromising privacy. This work discusses the concept of Blockchain technology in brief, features of the Microgrid or Smartgrid, some useful use cases of energy Blockchain and benefits of application of Blockchain technology to Smartgrid operations in the following sections.
Let’s Get Rolling! Exact Optimal Solitaire Yahtzee

SummaryYahtzee is a popular dice game that involves a combination of chance and decision making. We implemented a brute-force algorithm to understand optimal play for a solitaire version of Yahtzee using Mathematica. The novelty in our approach is that we were able to compute probabilities and expectations of the optimal player’s score exactly as rational numbers. Previous work involved only numerical approximations. We give an overview of our approach and analyze some of the data generated by our implementation. The figures provided in the article should give an insight as to how a game under optimal play would typically unfold.
Research on the Symbiosis Mode of Large-scale Sports Events Based on Computer Internet Technology and Intelligent Information Systems

This article is based on computer Internet technology and uses symbiosis theory to analyze how to better reciprocate symbiosis and interdependence between sports events and cities. At the same time, the article analyzes the requirements of designing a general community sports management framework based on .NET component technology from the perspective of large-scale urban sports events, thereby optimizing the design and design of a general sports event management information system, and analyzes the benefits of the system framework in practical applications. The research results show that a general sports event management information system is implemented based on the .NET component design, and the positive design value is exerted. Compared with the traditional sports event management information system, the general sports event management information system designed by the framework technology has an application benefit of 18.0%.
5 • La parola-segnale come criterio di scelta fra diverse proposte testuali

Starting from the recognition of signal-words in the transmitted text, the author supports suggestions for constitutio already advanced by other scholars, but unsuccessfully because lacking a plausible genetic explanation of the corruption.
Effective and Secure Two-Factor Multi-Server Authentication Scheme without Password

Increasing number of online services have brought great convenience to users, and remote user authentication schemes have been widely used to verify the legitimacy of the authorized users. However, most of the existing authentication schemes are based on password, in which users need to remember the complex passwords and change them frequently. In addition, the great majority of authentication schemes have security defects. Through the analysis of the scheme proposed by Haq et al., we find that it is difficult to resist the key compromise impersonation attack. Therefore, an improved two-factor multiserver authentication scheme without password is proposed. The perfect combination of the user’s biological characteristics and the PUF’s physical characteristics enhances the practicality and efficiency of the solution. Security analysis of the proposed scheme shows that it can resist various known security attacks.
Towards an Evaluation Metric for Carbon-Emitting Energy Provenance of Bitcoin Transactions

We present an approach to evaluating the carbon-emitting energy provenance of Bitcoin transactions and transaction outputs. Our approach incorporates published global energy production data and existing state-of-the-art estimates of Bitcoin energy consumption into a scoring algorithm for individual mined blocks. We then present two proposals for deriving scores for transactions based on the coinbase origins of the Bitcoin currency values of the transactions' inputs. The first proposal is comparatively simple, and weights coinbase origin contributions to a transaction based on recency in transaction hops from its origin block. The second proposal adjusts the weights of coinbase contributions at each intermediary transaction based on the input and output values of those transactions. Using these methods we are able to associate individual transactions and unspent transaction outputs with specific quantities of atmospheric carbon. Finally, we offer an outline of an incentivization strategy in the form of a blockchain-based carbon-offsetting oracle that would track the creation and exchange of offsets based on the metrics proposed.
Real Time Approach for Face Mask Detection using CNN

With the horizon still brim-full, effective solutions to contain the COVID-19 pandemic require close attention to reduce severely impacted communal health and worldwide economy. Many approaches are advised by WHO to manage the infection rate and avoid depleting the limited medical resources in the absence of effective antivirals and inadequate medical resources. Wearing a mask is one of the non- pharmaceutical interventions that can be utilised to reduce the principal source of SARS-CoV2 droplets ejected by an infected person. Regardless of debates about medical resources and mask varieties, all countries require public use of nose and mouth coverings. This strategy intends to develop a highly precise and real-time technique that can efficiently detect non- mask faces in public, hence mandating mask usage. For mask detection, the proposed strategy uses a convolutional neural network-based approach.
Enhancement of TextRank Algorithm using Coreference Resolution

TextRank Algorithm is an unsupervised graph-based algorithm by Mihalcea with two primary applications, namely in text summarization and keyword extraction of a text document.This study will focus on the enhancement of the TextRank algorithm on the keyword extraction side.This paper introduces an enhanced version of the algorithm wherein the whole text document is preprocessed with a method known as Coreference Resolution, wherein this method normalizes every referenced entity in a text into a single entity.The application of this method to a document text with a longer sequence, outperforms the Precision, Recall, F1-Measure, and the Mean Average Precision metrics of the original algorithm.
Epistemics of the Body

This presentation is about the relationship between the factors of space, story and body in non-fictional VR projects with the user as a first-person protagonist. What used to be called immersive journalism, i.e., the attempt to offer the user physical experiences of factual journalism, has now become much more film-oriented in the last years. Most projects, therefore, tell stories that have a relation to reality and allow the protagonists to enter real-life narratives. The paper starts by focusing on the state of the art of research from the direction of media and information science. Mel Slater has been investigating VR projects with others since 2005, naming factors such as place illusion or plausibility illusion; in later writings, he expanded this to include the body-oriented sense of embodiment (SoE) (Slater et al. 2009, 2010a, 2010b, 2012). These methodological explanations are supplemented by the immersion effect of the story itself. Domenic Arsénault pointed out there are three levels of narrative immersion in VR (Arsénault 2005). From this, an integrative matrix is developed. In the following, four current examples are presented that were used for the research project. The results of a small, non-representative study with 24 participants are presented afterwards. The findings include, among other things, that both the space and the story in first-person VR are related to the user's body, while the installation of a working plausibility illusion is rather insignificant. The user reads, experiences and understands the projects with the senses, perceptions and cognition of the whole body, as it seems, which makes it possible to speak of an epistemic of the body.
Solving Linear Systems of Equations on a Trapped Ion Quantum Computer

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Implementing symmetric entangling gates using quantum optimal control on nuclear-spin qudits in <sup>87</sup>Sr atoms

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De Bruijn Shapes: Theory and Instances

Working with ever-increasing datasets can be time-consuming and resource-intensive. De Bruijn sequences, which allow you to visit all conceivable combinations of data exactly once, may be an attractive choice for trying to process the related items inside those datasets in the best feasible way. These sequences are unidimensional, but the same approach can be extended to include more dimensions, such as de Bruijn tori for bidimensional patterns or de Bruijn 3D-hypertori for tridimensional patterns, which can be further developed to infinite dimensions. The objectives of this study are to expose the main features of all those de Bruijn shapes, along with some relevant particular instances, which may be useful in pattern location in one, two and three dimensions. De Bruijn sequences have been extended to higher dimensions, generating de Bruijn hypertori, and presenting a generic template for the most common condition to achieve such shapes.
Online Coreference Resolution for Dialogue Processing: Improving Mention-Linking on Real-Time Conversations

This paper suggests a direction of coreference resolution for online decoding on actively generated input such as dialogue, where the model accepts an utterance and its past context, then finds mentions in the current utterance as well as their referents, upon each dialogue turn.A baseline and four incrementalupdated models adapted from the mentionlinking paradigm are proposed for this new setting, which address different aspects including the singletons, speaker-grounded encoding and cross-turn mention contextualization.Our approach is assessed on three datasets: Friends, OntoNotes, and BOLT.Results show that each aspect brings out steady improvement, and our best models outperform the baseline by over 10%, presenting an effective system for this setting.Further analysis highlights the task characteristics, such as the significance of addressing the mention recall.
Interaction design of financial insurance products under the Era of AIoT

Abstract This study aims to explore how the insurance business can combine artificial intelligence (AI), huge data technology and good design under the ecological background of AIoT to improve the efficiency of double-entry in the insurance business and improve the user experience. It is accomplished through observation, user interview and other methods to explore user needs and distress points, comprehensive use of image and video analysis, face recognition, behaviour detection and other AI technologies. aiCore intelligent dual-recording system is proposed, which integrated mobile terminal dual-recording application and backstage quality control system. The proposed system realised the design optimisation of the whole process of intelligent dual-recording scenario combining the three functions ‘front-end intelligent dual-recording, in-process real-time quality control and post-AI quality control.’ Using in-process detection, post-review and manual final audit, the aiCore intelligent dual-recording system has significantly improved the efficiency of dual-recording, quality inspection pass rate and user experience satisfaction.
Scientific Expertise of the Psychological and Pedagogical Definition

The methodology of scientific examination of psychological and pedagogical definitions presented in the article is justified by the need to clarify the content of the basic set of definitions that form the core of methodological, research and innovative work in the field of education.First of all, this applies to those definitions that contain a contradictory interpretation of the psychological and pedagogical concepts.The tools under discussion are (the semantic model of the phenomenon, maps of expert assessment of the model and the results of the revision of concepts) and expert-analytical procedures for various stages of such examination (grouping of existing interpretations of the same phenomenon, wording of interpretations, revision of interpretations).The developed methodology ensures the possibility of a consistent revision of the definition of concepts, progressing from the description of the phenomenon to its normative explanation.The proposed tools and procedures are illustrated by the example of scientific expertise of the psychological and pedagogical phenomenon of "didactic difficulty".
Trajectory Anomaly Detection based on Similarity Analysis

Automatic trajectory processing has multiple applications, mainly due to the wide availability of the data. Trajectory data have a significant practical value, making possible the modeling of various problems such as surveillance and tracking devices, detecting anomaly trajectories, identifying illegal and adverse activity. In this study, we show a comparative analysis of the performance of two descriptors to detect anomaly trajectories. We define Wavelet and Fourier transforms as trajectory descriptors to generate characteristics and subsequently detect anomalies. The experiments emphasize performance in the description in the coefficient feature space. For that, we used unsupervised learning, specifically clustering techniques, to generate subsets and identify which are irregular. The implications of the study demonstrate that it is possible to use descriptors in trajectories for automatic anomaly detection and the use of unsupervised learning methods that automatically segment the required information. The performance and comparative analysis of our study are demonstrated through experiments and case studies considering synthetic and real data sets that leave evidence of our contribution.
Studies in the Experience of Philosophical and Anthropological Analysis of Digital Education in the Realm of Digital Technologies

The article deals with the problem of the influence of the digitalization of education on human consciousness and the development trends of modern society. The main approaches of modern philosophy to the formation processes of the world educational space are under research. The authors set themselves the goal of identifying the most important consequences of these processes for human consciousness and the evolution of society. The article discusses the impact of digital education on the structure and functions of traditional educational institutions and the modern human consciousness; attention is paid to the consequences of the digitalization of education for such a historically established social group as the professional intelligentsia (clerisy). The analysis of the problem concludes that a fundamentally new model of the transmission of social experience and scientific knowledge is emerging in the modern world educational space. Traditional educational institutions like schools and universities are giving way to a whole system of network structures. This process is accompanied by the deinstitutionalization of education, the departure of education from some of its historical functions, such as the reproduction of the traditional worldview, the decline in the social status of a university diploma, and the transformation of the clerisy.