Reviewerly/exHarmony huggingface dataset:
University traditions in the context of the introduction of educational innovations: the research case of the University of Tyumen

The institution of higher education in Russia is currently involved in the process of cardinal modernization, which affects and reforms its forms and content that have been developing for a considerable time. During this process, the aim and values of education are also transforming: the idea of commitment and of integral personal development are substituted for the concept of service, profit and competitiveness. The novelty of this work is in the study of innovations in the system of higher education through analysis of university as an establishment with historically developed traditions. In this article, for the first time, the ratio of existing traditions and innovations that are being currently introduced is analyzed on the example of a specific university. The purpose of this paper is to examine the traditions of a single university involved in the process of innovative development and to identify how they compare to introduced innovations, as well as in what way the role of university traditions changes in this context. During the research, the authors’ typology of research approaches based on the ideas of M. Rokeach, C. Kluckhohn, and F. Strodtbeck, methodological works of S. H. Schwartz and R. Inglehart was used. The article presents the results of an interuniversity study of the value orientations of the university students and teaching staff, as well as of the transformations of its traditions in connection with the modernization of education in general and the introduction of innovations in particular. In this sense, the case of University of Tyumen is of interest — it is the university that entered the project 5-100 in 2015 and commenced the process of active modernization and the introduction of innovations in its educational process. The article presents the results of in-depth expert interviews with the management and teaching staff of the University of Tyumen (n = 60), as well as the analysis of mass survey data of the students (n = 743). The study revealed the following points: the university focuses on innovative development in its priorities; a demand for a new type of the university and corresponding personality is formed gradually. In the context of the development of the University of Tyumen, it is not only the traditions that change but rather their role. The university is not generally aimed at reproduction of traditions preferring innovative educational processes.
Contributors to this Issue

Other| December 01 2021 Contributors to this Issue Nineteenth-Century Literature (2021) 76 (3): 401–402. https://doi.org/10.1525/ncl.2021.76.3.401 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Contributors to this Issue. Nineteenth-Century Literature 1 December 2021; 76 (3): 401–402. doi: https://doi.org/10.1525/ncl.2021.76.3.401 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentNineteenth-Century Literature Search This content is only available via PDF. © 2022 by The Regents of the University of California2022 Article PDF first page preview Close Modal You do not currently have access to this content.
Blockchain Technology

Travel and technology tend to possess seamless amalgamation. Advancements in technologies are significantly changing the way people travel, with exciting and promising experiences. Incorporation of smart devices and solutions in businesses enables easier ways to analyze, collect, as well as share the real-time data with vendors. One such concept includes blockchain technology, inclusion of which brings about an extreme change in the way the data are being accessed and stored. This technology enables the businesses to fortify operations, transactions, as well as processes, thereby bolstering productivity and growth and discovering newer profit models. This chapter discusses the different competitive advantages offered by the tourism businesses on inclusion of blockchain technology in their strategic-decisions and emphasizes how the blockchain concepts help in simplifying the tourism and hospitality businesses, amidst different challenges being faced by these industries.
Traceable PRFs: Full Collusion Resistance and Active Security

The main goal of traceable cryptography is to protect against unauthorized redistribution of cryptographic functionalities. Such schemes provide a way to embed identities (i.e., a “mark”) within cryptographic objects (e.g., decryption keys in an encryption scheme, signing keys in a signature scheme). In turn, the tracing guarantee ensures that any “pirate device” that successfully replicates the underlying functionality can be successfully traced to the set of identities used to build the device. In this work, we study traceable pseudorandom functions (PRFs). As PRFs are the workhorses of symmetric cryptography, traceable PRFs are useful for augmenting symmetric cryptographic primitives with strong traceable security guarantees. However, existing constructions of traceable PRFs either rely on strong notions like indistinguishability obfuscation or satisfy weak security guarantees like single-key security (i.e., tracing only works against adversaries that possess a single marked key). In this work, we show how to use fingerprinting codes to upgrade a single-key traceable PRF into a fully collusion resistant traceable PRF, where security holds regardless of how many keys the adversary possesses. We additionally introduce a stronger notion of security where tracing security holds even against active adversaries that have oracle access to the tracing algorithm. In conjunction with known constructions of single-key traceable PRFs, we obtain the first fully collusion resistant traceable PRF from standard lattice assumptions. Our traceable PRFs directly imply new lattice-based secret-key traitor tracing schemes that are CCA-secure and where tracing security holds against active adversaries that have access to the tracing oracle.
Protecting Your Privacy While Sharing Public Scholarship

Women in Higher EducationVolume 31, Issue 3 p. 8-14 In Her Own Words Protecting Your Privacy While Sharing Public Scholarship Teresa Valerio Parrot, Teresa Valerio ParrotSearch for more papers by this author Teresa Valerio Parrot, Teresa Valerio ParrotSearch for more papers by this author First published: 28 February 2022 https://doi.org/10.1002/whe.21110Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume31, Issue3March 2022Pages 8-14 RelatedInformation
Storytelling Tools

In this chapter, we will look at the technical effort required to make stories using visualization software. Some of the popular visualization tools will be discussed at a high level to give an overview of the visualization process. The general steps of the visualization process will also be briefly discussed.
An Approach Towards Architecture-Independent Output for Generative Networks: Texturing Aerial Town Maps for Roleplaying Games

Siracusa, Gianfranco Seychell, Dylan Bugeja, MarkGenerative Adversarial Networks (GANs) have benefited of significant attention from the research community in recent years. The advancements in the field have led to high-quality results being achieved, but the computational requirements for matching these results have increased, making high-end methods unattainable by researchers with more limited equipment working on domains where pre-trained models for transfer learning are not available. A new system is presented for combining the output of small-sized, easily trained conditional generative adversarial networks to synthesise output at much higher resolution, even with small datasets, by applying a blending technique that uses redundant colour information to mend seams between network output that is spatially adjacent in the final image. The system was found to be capable of generating structurally consistent output, although it exhibits some defects where there are large areas of the same feature. The system creates output with average user opinion score of 3.5 on a scale from 1 to 5, which was generally judged to be an improvement over plain procedural output by users. The algorithm parameters allow the user to balance between performance, blending efficiency and sharpness of detail.
Siamese Networks for Image Comparison and Discrepancy Localization

With the prevalence of online learning and exams, a side camera view overlooking a student's computer screen and work area is recommended to compare the expected view on exam screen to that of student's screen and identify cheating. This work proposes a novel architecture of Siamese convolutional neural networks to automate the proctoring process by simultaneously detecting disallowed activities on computer screen and localizing the region in cases where such activities are carried out in a portion of screen only. While the proposed Siamese detector compares the base image to test image to detect features in the entire image to ascertain discrepancy, the Siamese localizer splits the image area in sections to perform regional feature comparisons to yield discrepant regions. Both components run in a single-shot mode and avoid multi-shot regressions. On a public web screenshot database, the proposed Siamese detector and localizer both achieve impressive results with detector achieving 96.4% accuracy on 20-way full-screen discrepancy detection task and localizer achieving 94.4% accuracy along with mean overall IoU of 0.72 over discrepant segments.
Machine English Translation Scoring System Based on Deep Neural Network in the Internet of Things Environment

In machine translation, the evaluation method of the translation system is a very critical link, and it is also critical to the research of machine translation. The evaluation method helps to evaluate the characteristics of the translation system, and find the existing problems, so as to guide the development trend of the system. The correct evaluation method is the main cornerstone of the software system development process, and it is also the main force that promotes the development of machine translation systems. If there is no correct and effective evaluation method, it can be said that there will be no development of machine translation system. In this paper, we will study the deep neural network machine English translation scoring system under the Internet of Things environment, and understand the relevant theories of the machine translation scoring system based on the literature, and then design the machine English translation scoring system based on the deep neural network, and tested the designed system. The result of the test is that the score of the system in this paper is not related to the manual score, and the error range is within 10%.
Teaching “Gen Z”. A Study of the Media Competencies of International Baccalaureate Teachers in Loja-Ecuador

The objective of this research is to identify and categorize, through a case study, the level and quality of media competencies of secondary school teachers, who are currently teaching the famous “Generation Z”. In order to obtain data, an ad hoc questionnaire was administered via online to 49 teachers of the International Baccalaureate (IB) in Loja (Ecuador). The research was conducted in second and third quarter of 2018. Results indicate that level of media competence of teachers, ranges between remarkable and average, which is evidenced in the irregular conformation of the skills they deploy. With respect to knowledge, use and consumption of media and technological applications, giving more importance, as constantly manifested in research on this topic, to the dimension of technology, over others such as aesthetics and production and dissemination, in which, to the detriment, the role of their students is increasingly emphasized. Although it has been declared in documents of official entities in the country, the recognition of media education as a transversal issue in teacher training and fundamentally in its application in the classroom, still leaves a significant gap to be worked on.
Advanced Scene Sensing for Virtual Teleconference

Over the last year the need for video conferences has risen significantly due to the ongoing global pandemic. The goal of this project is to improve user experience from having access to only voice and plain 2D image by adding a third spatial dimension, creating a more immersive setting. Azure Kinect Development Kit utilizes multiple cameras, namely the RGB camera and depth camera. Depth camera is based on ToF principle, which uses near-IR to cast modulated illumination onto the scene. The setup uses multiple Azure Kinect devices in sync and offset in space to obtain non-static 3D capture of a person. Unity engine with Azure Kinect SDK is used to process the data gathered by all devices. Firstly, a depth spatial map is created by combining overlaid outputs from each device. Secondly, RGB pixels are mapped onto depth spatial points to provide a final texture to the 3D model. Taking into account the need to export a continuous capture of raw data to a server, body tracking and image processing algorithms are used. Finally, the processed data can be exported and utilized in AR, VR or any other 3D capable interface. This 3D projection aims to enhance sensory experience by utilising non-verbal communication along with classical speech in video conferences.
U-Net first-arrival picking optimization method based on traces connectivity

PreviousNext No AccessSEG 2021 Workshop: 4th International Workshop on Mathematical Geophysics: Traditional & Learning, Virtual, 17–19 December 2021U-Net first-arrival picking optimization method based on traces connectivityAuthors: Jinlong ChengShulin PanJinlong ChengSouthwest Petroleum UniversitySearch for more papers by this author and Shulin PanSouthwest Petroleum UniversitySearch for more papers by this authorhttps://doi.org/10.1190/iwmg2021-31.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract The first-arrival automatic picking method based on deep learning has the problems of insufficient picking accuracy when processing seismic data with low signal-to-noise ratio, and still needs a lot of manual interaction. In order to solve this problem, based on the classic four-layer U-Net network, this paper proposes a new optimization method for picking up results based on seismic trace connectivity. Firstly, manually select some seismic data and make training labels. Next, four-layer U-Net network is used for training, and network parameters suitable for automatic pickup are obtained. Then, input the seismic data to be picked into the trained network and the segmented data is automatically obtained. Finally, the data after segmentation is processed by using the traces connectivity method, and the boundary of the processed data is automatically picked up to obtain the final first-arrival picking result. After the above steps, the accuracy of the first-arrival result of picking is greatly improved. Keywords: optimization, noise, amplitude, processing, samplingPermalink: https://doi.org/10.1190/iwmg2021-31.1FiguresReferencesRelatedDetails SEG 2021 Workshop: 4th International Workshop on Mathematical Geophysics: Traditional & Learning, Virtual, 17–19 December 2021ISSN (online):2159-6832Copyright: 2022 Pages: 193 publication data© 2022 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 24 Feb 2022 CITATION INFORMATION Jinlong Cheng and Shulin Pan, (2022), "U-Net first-arrival picking optimization method based on traces connectivity," SEG Global Meeting Abstracts : 119-121. https://doi.org/10.1190/iwmg2021-31.1 Plain-Language Summary KeywordsoptimizationnoiseamplitudeprocessingsamplingPDF DownloadLoading ...
VIA: A Virtual Informative Assistant for Smart Tourism

Tourism can be approached from the technological virtual continuum, calling it smart tourism which is related to cultural computing. To achieve that, we implemented an application for mobile devices to enrich the visit of locals and foreigners to the San Antonio neighbourhood in the city of Santiago de Cali, Colombia using concepts such as augmented reality, natural language processing and techniques such as speech-to-text, text-to-speech, skeletal animation and blend shapes. The main objective is to guide and inform about the neighbourhood in order to provide awareness of it as a heritage site. We developed the application following a software development cycle which included analysis, design, prototyping, implementation, and validation. Particularly, in validation, we performed unitary tests, functional tests and user tests. The resulting application was well received among participants in the test.
CluniacChain

Blockchain technology generally is associated with financial applications where it serves the role of maintaining records. However, such a tamper-resistant distributed ledger can be used for fashioning applications in the healthcare domain. Harnessing the potential of blockchain as a data store for health records would ensure that they would be secure as multiple copies of them are preserved in a decentralized manner to ensure data redundancy and security. With this technology in effect, the medical sector could leverage blockchain tech to allow any authorized hospitals to securely communicate, share information/records independent from a central figure. Information shared would only contain relevant data related to the query between stakeholders with appropriate permission attached to their roles. This chapter delineates the architecture of such a system explaining its benefits and limitations as a medical data-storage architecture.
MBCED: Multi-task learning event detection method based on pre-training

Event detection is the first step in event extraction. Its goal is to filter out event sentences containing event information from candidate texts and determine their types. In order to solve the problem of sparse corpus and inaccurate judgment of the trigger word type caused by the polysemy of the trigger word in the existing event detection methods, this paper proposes a multi-task learning event detection method based on pre-training - MBCED, which performs event detection and word sense disambiguation tasks at the same time, transfers the knowledge learned in the word sense disambiguation task to the event detection task, which not only supplements the corpus, but also alleviates the inaccuracy of trigger word classification to a certain extent . Experiments on the ACE2005 dataset prove that the MBCED method has better event detection performance compared with existing methods.
Handling Realistic Noise in Multi-Agent Systems with Self-Supervised Learning and Curiosity

Abstract 1 Most reinforcement learning benchmarks – especially in multi-agent tasks – do not go beyond observations with simple noise; nonetheless, real scenarios induce more elaborate vision pipeline failures: false sightings, misclassifications or occlusion. In this work, we propose a lightweight, 2D environment for robot soccer and autonomous driving that can emulate the above discrepancies. Besides establishing a benchmark for accessible multi-agent reinforcement learning research, our work addresses the challenges the simulator imposes. For handling realistic noise, we use self-supervised learning to enhance scene reconstruction and extend curiosity-driven learning to model longer horizons. Our extensive experiments show that the proposed methods achieve state-of-the-art performance, compared against actor-critic methods, ICM, and PPO.
SoliNomic: A Self-modifying Smart Contract Game Exploring Reflexivity in Law

Ellul, Joshua Pace, Gordon J.Smart Contracts built on Blockchain systems have brought about the ability to deploy code that is tamperproof, verifiable and guaranteed to do exactly what it is written to do over a network of decentralised systems. This enables for decentralised (and centralised) organisations to define rules for particular operations, or even for the entire organisations’ decision-making processes. The rules, decision making processes and ability to alter both the rules and processes are encoded within smart contracts. Nomic was a game of self-modifying rules originally meant to explore self-reference and amendment from a regulatory perspective. In this paper we explore the encoding of such a rule system formally as self-modifying yet otherwise tamper-proof code in smart contracts.
Author Reply

We read with great interest the commentary by Nguyen et al. regarding our group's recent publication study titled ‘Implications of a Novel Biopsy Downloading System on Prostate Cancer Detection Rate, Surveillance and Focal Therapy – A Prospective Study’. Very interesting points were raised, and we thank them for the thought-provoking insights.
A Brokering Model for the Cloud Market

The cloud broker is an IT role and a business model that acts as an intermediary agent between cloud providers and end users. The exponentially increasing adoption of the IaaS market has contributed significantly to the so far growth of the Cloud Broker market. The unprecedented scenario of COVID-19 pandemic has upgraded the role and the contribution of broker to the cloud market, since cloud adoption has been further accelerated by the COVID-19 crisis. Cloud broker guarantees the availability of a given amount of resources for use at a specific time, offering pricing policies that benefit consumers and boost broker’s profitability. Into that context a cloud brokering model, is introduced and described, together with a profit maximization economic model, suggesting and evaluating different pricing policies that ensure the viability of the business and boost profitability. The pricing policy that is able to lead to the maximum profit potential is also highlighted.
Protecting Data in Snowflake

Not so long ago, protecting your data from accidental deletion or modification, hardware or software failure, or recovering the database after it was polluted by loading corrupt data into it was not a trivial affair.
Best Before: An Expiry Date Checker Website to Track the Expiry of Perishable Items

An item’s expiration date is the time during which the item remains stable, which implies that its purity, strength and quality remain the same when it is kept in accordance to the appropriate storage conditions. Products expire or become unsafe for consumption if they are not stored in ideal conditions. Thus, expiry dates are printed on the products’ label. When the product has passed its expiry date, it may give out poisonous substances, which on consumption can lead to several side effects. In this research, we have proposed a web application built using MongoDB, Express.js, ReactJS and Node.js that will keep a track of the expiry date of the products and notify the user about the items that have already expired. The notification will be sent to the user as an SMS using the Twilio API. The aim of this study is to reduce the wastage of various items like food, drugs, etc., and to avoid unwanted side effects.