Reviewerly/exHarmony huggingface dataset:
Nonlinear educational process

The article describes the features of organizing a competently oriented educational process of the university, showing its strengths and weaknesses. The features of nonlinear management of educational organizations and nonlinear construction of the educational process are described. Higher education development in Russia is proposed. The importance of the personality of students, the importance of the formation of professionally significant personality traits is indicated. The data of the survey (attitude of students to the existing educational process) of graduate students and their analysis are presented. New directions and conditions for the organization of a nonlinear educational process at the university are considered - blended learning using the traditional form of work (face to face), electronic and distance technologies, electronic information educational environment, modular structuring of educational material, etc.
Federated Optimization Based on Compression and Event-triggered Communication

Federated learning is deemed as a promising solution to large-scale machine learning problem, which enables multiple edge users cooperatively to train a global parameter model and guarantees users a basic privacy level. However, despite the increasing interest, communication expenditure usually turns out to be a major bottleneck for scaling up distributed algorithms with possibly irresponsible or limited data rate network environments. In fact, users or clients synchronize models periodically regardless of whether current models change significantly from last one, it is a waste of communication resources. Considering how much message to transmit each communication round and when to communicate, in this paper, we propose FedCET, which is a compression and event-triggered algorithm for federated learning. We present convergence analysis of algorithm and rigorous proof for smooth nonconvex, strong convex or PL condition and general convex objective functions, respectively, testifying that such communication method is efficient without affecting the convergence property of the algorithm. Further, we evaluate the proposed FedCET on several dataset to demonstrate the effectiveness compared with other methods.
Intelligent IoT System Requirements to Support Self-Management for People with Learning Disabilities – A Study with Care Providers

Internet of Things (IoT) technology and Smart Home (SH) solutions are a growing area of research and development, particularly within health and social care where they have potential to offer information and support for self-management and independent living. However, successful design and deployment of these technologies are predicated on a clear understanding of user aspirations, needs, and requirements. This paper presents findings from seven one-to-one interviews with care staff who contributed their experiences representing a diverse range of job roles and categories of service-users supported. Our participants were from a regional supported-living provider with facilities for people with learning disabilities. The interviews provided insight into care service provision and service-users' needs, as well as helping to identify areas of the current service that can be supported by IoT based intelligent systems. The feedback that staff provided was based on their knowledge and understanding of the needs of specific service user groups and included information regarding the appropriateness and applicability of the technologies, as well as the appeal, acceptability and usability of these solutions.
Infrared Divergences of S-Matrix

We first review the S-matrix in quantum field theories with emphasis on asymptotic states. We then review the soft photon theorems up to the subleading order. In the last section, we review the infrared divergences of the conventional S-matrix in QED.
Using Dynamic Analysis to Automatically Detect Anti-Adblocker on the Web

With the continuous development of Internet technology, there are more and more advertisements on the website and some of them can track and monitor users. To avoid the leakage of privacy information, many people are using adblockers to remove advertisements on web pages. This behavior of filtering advertisements seriously threatens the benefits of online publishers, and they have begun to detect and counterattack users who use adblockers. Previous work focused on detecting and filtering anti-adblockers to fight against the counterattacks of online publishers. So far, one of the most effective ways to prevent anti-adblockers is to create a blacklist. However, the generation and maintenance of blacklists involve considerable manual work, which is inefficient and difficult to maintain. This paper proposes a machine learning anti-adblocker detection system called ABDetector, which is the first system that can automatically generate blacklists of anti-adblockers. This system greatly reduces the manual workload. Since the difference of code with and without anti-adblocking detection behavior mainly lies in that they call different APIs, thus, we for the first time tried to build a classifier of anti-adblockers using JavaScript APIs as features and use dynamic analysis method to extract features. Unlike static analysis method, the dynamic analysis method can effectively avoid code obfuscation. The accuracy of ABDetector on the test set is 81.46%.
Design Handbook for Central Bank Digital Currencies

Central banks around the world are evaluating the option of issuing a centrally banked digital currency (CBDC). There are a number of policy objectives attributed to offering a CBDC. Curiously, some of the stated objectives are contradictory. This confusion is a consequence of a very broad design landscape, which runs contrary to the conventional wisdom that suggests CBDCs can be broken into 2 or 4 main categories. In this paper, we systematically iterate through 8 key design decisions, most of which have 3 or more possible designs. Our design landscape is based on dozens of whitepapers and technical reports issued by central banks, international financial institutions, and technology firms. By laying out a comprehensive set of options, we offer central banks a finer grained approach to tailoring a design that meets their specific objectives—objectives that will change from country to country.
Digital Image Watermarking Method Using The Gyrator And Dyadicwavelet Transforms

We propose a new digital watermarking method combining the gyrator transform and the dyadic wavelet transform (DYWT). The gyrator transform produces a rotation dependent on the angle in the twisted phase plane, while DYWT has the properties of redundancy and shift invariance. Combining these two transforms, we develop a new digital watermarking method that enables multi-resolution analyses of images twisted in the spatial frequency plane. Using experiments, we confirm the image quality of the watermarked images and their resistance to various attacks, including clipping, JPEG compression, and geometric manipulation. The results are shown, and the effectiveness of this new method is examined.
An Educated Peer Discovery Expanding Blockchain Framework

Abstract The key benefit of blockchain Bitcoin-style networks is their immutability and autonomous power. Bitcoin is suffering from scalability problems in spite of its performance. Unless it is rendered more scalable, the promise of blockchain technology cannot be achieved completely. We broaden an earlier study on a fundamental balance between the blockchain system’s efficiency and forking rate. We also suggest a system to improve blockchain device efficiency by reducing block spread time. Informed neighbor selection is adopted by the proposed system. Miners detach from neighbors with restricted bandwidth and choose higher bandwidth nodes. To test the efficiency of the proposed system, we construct a Blockchain Interactions Emulator. In standard operations proposed system increases the performance by 20% by ∼40%.
Filament plots for data visualization

The efficiency of modern computer graphics allows us to explore collections of space curves simultaneously with “drag-to-rotate” interfaces. This inspires us to replace “scatterplots of points” with “scatterplots of curves” to simultaneously visualize relationships across an entire dataset. Since spaces of curves are infinite dimensional, scatterplots of curves avoid the “lossy” nature of scatterplots of points. In particular, if two points are close in a scatterplot of points derived from high-dimensional data, it does not generally follow that the two associated data points are close in the data space. Andrews plots provide scatterplots of curves that perfectly preserve Euclidean distances, but simultaneous visualization of these graphs over an entire dataset produces “visual clutter” because graphs of functions generally overlap in 2D. We mitigate this “visual clutter” issue by constructing computationally inexpensive 3D extensions of Andrews plots. First, we construct optimally smooth 3D Andrews plots by considering linear isometries from Euclidean data spaces to spaces of planar parametric curves. We rigorously parametrize the linear isometries that produce (on average) optimally smooth curves over a given dataset. This parameterization of optimal isometries reveals many degrees of freedom, and (using recent results on generalized Gauss sums) we identify a particular member of this set which admits an asymptotic “tour” property that avoids certain local degeneracies as well. Finally, we construct unit-length 3D curves (filaments) from Bishop frames induced by 3D Andrews plots. We conclude with examples of filament plots for several standard datasets,1 illustrating how filament plots avoid “visual clutter”.
Fault Analysis in the Field of Fused Deposition Modelling (FDM) 3D Printing Using Artificial Intelligence

It is used for 3-dimensional (3D) production, which is called additive manufacturing, which emerged In the 1980s, with the inadequacy of traditional methods. Today, with the development of this technology, all kinds of geometry are produced rapidly. However, with 3D printing technology development, the problems are known as complexity have increased significantly. This situation made the fault analysis during the study a matter to be focused. User intervention is generally required in case of faulty in the parameters during printing using 3D printing technologies. The user must first observe whether there is any faulty and decide what to do. The study focused on automatic diagnostics to help the user diagnose the potential faulty and solve the problem. The data from the sensors belonging to the electronic card designed in the study were taken. The analog values were then read and analyzed, and the faulty conditions were checked according to the analysis. In the field of 3D printing technologies, a new approach has been presented by analyzing the data obtained in faulty analysis with the artificial intelligence method.
Using Artificial Bat Swarm Algorithm In Scheduling Problem

Software Project scheduling problem  is considered one of the basic and important processes in the software industry at the present time as software manufacturers strive to meet customer needs in terms of time and money factor and the ability to find good solutions where we can achieve 60% of project success if planned and make good use of human resources. And other resources The project manager is responsible for planning the resources and identifying the critical points facing the project in addition to defining the tasks assigned to the employees to implement them according to their skills, experience and the extent of relevance of each task to another. In this paper, project scheduling is presented using the intelligent bat swarm algorithm.
Implementation of Software Product Line with .NET

In the contemporary world, software product line use has become so rampant and of great significance. This is because for every software developed, there is a new product line that emerges with it. Whereas a few literature pieces have already covered the generic development of Software Product Line (SPL) and its instantiation, there is very little focus directed towards its implementation in a business context by using the .NET framework, thus forming the basis of this research study. The present article will give insight into the performance of a software product line .NET. Concerning this statement, the paper will attempt to address some .NET basic concepts, distinguishing features, factors to consider in implementing the .NET framework, the benefits of implementing .NET frameworks .NET. The paper will also understand some of the approaches used to implement .NET in a software product line. The report will conclude by giving a recommendation for further research.
Digital Signature Scheme with Hidden Group Possessing Two-Dimensional Cyclicity

A method is proposed for constructing digital signature schemes based on the hidden discrete logarithm problem, which meet ageneral criterion of post-quantum resistance. The method provides a relatively small size of the public key and signature. Based on the method, a practical digital signature scheme has been developed, in which the exponentiation operation in a hidden group with two-dimensional cyclicity is the basic cryptographic primitive. The algebraic support of a cryptoscheme is a four-dimensional finite non-commutative algebra with associative multiplication operation. By specifying algebra using abasis vector multiplication table with half of empty cells, the performance of signature generation and authentication procedures is improved. A public key is a triple of four-dimensional vectors calculated as images of elements of a hidden group which are mapped using two types of masking operations: 1) mutually commutative with the exponentiation operation and 2) not having this property.
Beyond sentiment: an algorithmic strategy for identifying evaluations within large text corpora

In this paper, we propose a new strategy for classifying evaluations in large text corpora, using supervised machine learning (SML). Departing from a conceptual and methodological critique of the use of sentiment measures to recognize object-specific evaluations, we argue that a key challenge consists in determining whether a semantic relationship exists between evaluative expressions and evaluated objects. Regarding sentiment terms as merely potentially evaluative expressions, we thus use a SML classifier to decide whether recognized terms have an evaluative function in relation to the evaluated object. We train and test our classifier on a corpus of 10,004 segments of election coverage from 16 major U.S. news outlets and Tweets by 10 prominent U.S. politicians and journalists. Specifically, we focus on evaluations of political predictions about the outcomes and implications of the 2016 and 2020 U.S. presidential elections. We show that our classifier consistently outperforms both off-the-shelf sentiment tools and a pre-trained transformer-based sentiment classifier. Critically, our classifier correctly discards numerous non-evaluative uses of common sentiment terms, whose inclusion in conventional analyses generates large amounts of false positives. We discuss contributions of our approach to the measurement of object-specific evaluations and highlight challenges for future research.
Hypertextuality representation in a novel of J. Barnes: a history of the world in 10½ chapters

Background: The 21st century is marked by a drastic development of computer technology, which caused the growing interest in the hypertext. Despite the fact that it is mainly associated with the informational technology, the hypertext has also been a center of cross-disciplinary researches, as well as in the field of text linguistics.&#x0D; Purpose: Hence, the present article deals with the hypertextuality phenomenon in the emotive prose.&#x0D; Design and methods: By implementing the methods of comparative, structural, contextual, and intertextual analysis, the compositional and linguistic means of its representation are investigated on the basis of the novel by J. Barnes A History of the World in 10 ½ Chapters.&#x0D; Results: Julian Barnes is one of the most popular contemporary British writers. He is considered a postmodernism icon, whereas an American writer and critic J. C. Oates calls him a “pre-postmodernist”. He is an author to more than 20 novels. A History of the World in 10 ½ Chapters (1989) is a novel where the author experimented with a form. The book consists of ten novellas and Parenthesis. As far as the novel is considered an icon of postmodernistic literature, the revelation of a hypertext system there makes it possible to claim hypertextuality a distinctive marker of a postmodernistic perception of the world.
Quantum cryptography integration

Nowadays, the internet and the web are more popular with electronic commerce services. Networkexchange security is extremely essential for e-commerce service and the key to the success of e-commerce isconstantly (e-commerce). In this article, we address some problems connected to the safety of conventional andnew e-commerce models, including P2P authentication, authorization, non-repudiation and integrity. Inexamining the key characteristics of P2P e-commerce, we summaries several trust model design concepts in P2Pe-commerce. We provide a comprehensive review of network security problems relating to e-commerce and ecommerceapplications and suggest an appropriate research framework for e-commerce safety. We think thatP2P e-commerce would be greatly successful compared to other security techniques in the future e-commercemarketplaces, as long as security concerns are properly handled.
Proposal of an Improved Contactless Measurement Method Using an Advanced Light Emitting Diode Displacement Sensor for Vibration Stress of Piping Systems

Abstract This paper proposes an improved contactless measurement method for vibration stress of piping systems, by which the measurement time is shorter and the measuring works are more simple. The proposed method includes two processes, in which the bending mode shape of piping vibration is identified by a transmission-type light emitting diode (LED) displacement sensor and the vibration stress is calculated based on beam theory using the approximated curve of the bending mode shape. The proposed method uses one advanced LED displacement sensor to measure the vibration stress in contrast to multiple conventional LED sensors, which must be used in the previous method developed by the authors. Therefore, the measuring system could be reduced in size and a light-weight and portable measurement instrument was developed. The measurement accuracy and reliability of the new method were validated by the vibration experiment using a mockup piping system.
Towards a Generic Framework for Intercultural User Interface Design to Evoke Positive Cross-Cultural UX

So far, there are more plausible than reliable intercultural user interface design recommendations. Furthermore, there is a lack of plausible and model-based explanations of which sustainable and use-case-crossing products might apply. The goal of the considerations presented in this paper is to find a way to use results from empirical studies to be able to generate sustainable rules for UI design for cultural contexts in general to generate cross-cultural user experience. This is done through an explanatory approach by extending the existing IUID approach in a way that elementary explanatory design guidelines for intercultural UI design based on human factors should emerge. Based on a hybrid approach covering cultural contexts in human–computer interaction (HCI) design using a model of culturally influenced HCI, the IUID method-mix is extended by the concepts of user needs, interaction principles and task complexity to obtain a generic framework for intercultural user interface design (IUID) as condition of possibility for positive cross-cultural user experience.
A Text Analysis of the 2020 U.S. Presidential Election Campaign Speeches

Campaign speeches provide significant insight into how candidates communicate their message and highlight their priorities to various audiences. This study explores the campaign speeches of Donald Trump, Joseph Biden, Michael Pence, and Kamala Harris during the 2020 US presidential election using Natural Language Processing (NLP) techniques and a novel data pipeline of unstructured automated video captions. The intent of this effort is to evaluate the stylistic elements of the candidate speeches through elements such as formality, repetitiveness, topic variance, sentiment, and vocabulary choice/range to establish how candidates differ in their approaches and what effectively resonates with the voters. The NLP methods used include unsupervised similarity and clustering algorithms. Through this work, the results uncovered large stylistic differences amongst the candidates overall; however, more notably also indicate stark differences between the top and bottom of the Republican ticket compared to the Democratic ticket. The findings support the idea that the candidate pairs were selected strategically to cover the largest bloc of voters possible as part of the election process.
Organization of project-heuristic activity of future mathematics teachers in creating multimedia teaching tools

Now we can see a widespread introduction of modern digital technologies into the educational process in mathematics. These technologies can make learning more visual and accessible, implement an individual approach in teaching and manage the educationalcognitive heuristic activity of schoolchildren. The organization of project-heuristic activities in a higher pedagogical school can help prepare a future teacher for the development of computer-related tools. We refer to the means of digitalization of modern education as heuristic-didactic constructions in the form of computer programs for “non-rigid” control of educational activities of students in mathematical disciplines. The article describes the procedure for constructing such constructions in the form of accentuated, branched, chained programs and programs with delayed correction. The organization of project-heuristic activities of students — future mathematics teachers is aimed at teaching the creation of heuristic training and corrective simulators for schoolchildren based on the above programs. When designing multimedia heuristic simulators, students include a variety of heuristic tasks, systems of heuristically oriented tasks and other means of managing the educational and cognitive heuristic activity of students in their content. Teaching future mathematics teachers to build such simulators and manage them when working with schoolchildren is an important competence that should be formed in students in the context of digitalization of education.
Modular Adders Based on Reversible Circuits

Reversible logic is a computing model which has gained remarkable heed in recent years due to its properties that lead to ultra power and reliable circuits. Reversible circuits are key, for quantum computing. In this work we propose the usage of modular adders, in particular modular 2n-1 adders, with the use of reversible logic. Analysis comparison with normal adders and modular adders with reversible gates.