Reviewerly/exHarmony huggingface dataset:
NUIG-DSI’s submission to The GEM Benchmark 2021

This paper describes the submission by NUIG-DSI to the GEM benchmark 2021.We participate in the modeling shared task where we submit outputs on four datasets for datato-text generation, namely, DART, WebNLG (en), E2E and CommonGen.We follow an approach similar to the one described in the GEM benchmark paper where we use the pretrained T5-base model for our submission.We train this model on additional monolingual data where we experiment with different masking strategies specifically focused on masking entities, predicates and concepts as well as a random masking strategy for pre-training.In our results we find that random masking performs the best in terms of automatic evaluation metrics, though the results are not statistically significantly different compared to other masking strategies.Tripleset
The Transparency and Management of Derivatives Market in the Era of Digital Transformation in Vietnam

In the globalization and integration era with 4.0 industry, global derivative markets have certain impacts on opportunities and challenges, and roles of speculators who are main players in the derivative market. Derivative instruments will benefit investors in some aspects: risk prevention and help them to finalize profits before unexpected fluctuations, exchange rate gap limitation and avoiding risks from exchange rate movements, or speculators will prefer earning profits in selling or buying within short time. Moreover, transparency on the derivative market need to be enhanced for investor information reliability. In the development trend of digital transformation, digital economy and e-commerce 4.0, internet of things and Digital technology platform has supported much for the development of derivatives market, as well as data privacy solutions for investors. One of our study purposes is aiming to enhance management following digital economy and the connection between e-commerce 4.0 and derivative market in Vietnam. This study uses mainly quantitative analysis combined with qualitative analysis, synthesys, analytical and dialectical materialism method. We run regression with Eviews software to measure the impacts of multi factors on derivative markets.
GPRC Learning Commons: Reading Critically and Evaluating Sources: Grey Literature

Learn how to critically read and evaluate the sources you would like to use in your research.
Smart fuzzy graph

Abstract In recent times, the internet of things has gained more popularity. The internet of things connects people, objects and machines apart from distance through cloud based internet. In this paper, we have introduced the smart fuzzy graph along with some basic properties and related concepts. The aim of this paper is to solve some authentic real life problems using smart fuzzy graph.
Classifying Wu-Qing Couplets and General Couplets with Structural and Semantic Features

The couplet custom is one of China's intangible cultural heritage, and it occupies a pivotal position in Chinese traditional culture. The general couplet requires that the first sentence and the second sentence be opposite and semantically coherent. As a particular type of couplets, Wu-Qing couplets are related on the character level but irrelevant at the sentence level. Such characteristics make the Wu-Qing couplet significantly different in structure and semantics compared to the general couplets. In this paper, Convolutional Neural Network is used to extract structural features. Long Short-Term Memory network and vector operations are used to extract semantic features, and the Attention mechanism is used to strengthen structural and semantic information. Finally, we propose a model with structural and semantic features between general couplets and Wu-Qing couplets. The final F1 score reached 82.6, which was an increase of 5.4 compared to the baseline model.
A learning gap between neuroscience and reinforcement learning.

Historically, artificial intelligence has drawn much inspiration fromneuroscience to fuel advances in the field. However, current progress inreinforcement learning is largely focused on benchmark problems that fail tocapture many of the aspects that are of interest in neuroscience today. Weillustrate this point by extending a T-maze task from neuroscience for use withreinforcement learning algorithms, and show that state-of-the-art algorithmsare not capable of solving this problem. Finally, we point out where insightsfrom neuroscience could help explain some of the issues encountered.
Security Limitations with Cloud Computing: Well-defined Security Measures Using Cloud Computing

Due to the ever-growing threat of security breaches that information technology (IT) organizations continually face, protecting customer information stored in the cloud is critical to ensure data integrity.Research shows that new categories of data breaches frequently emerge; thus, security strategies that build trust in consumers and improve system performance are crucial.The purpose of this qualitative multiple case study was to explore and analyze the strategies used by database administrators (DBAs) to secure data in a private infrastructure as a service (IaaS) cloud environment.The participants comprised of six DBAs from two IT companies in Baltimore, Maryland, with experience and knowledge of security strategies to secure data in private IaaS clouds.The disruptive innovation theory was the foundational framework for this study.Data were collected using semistructured interviews and a review of seven organizational documents.A thematic analysis was used to analyze the data.Two key themes are addressed in this article: importance of well-defined security measures in cloud computing and limitations of existing security controls in cloud computing.The findings of well-defined security strategies may benefit DBAs and IT organizations by providing strategies that may prevent future data breaches.Well-defined security strategies may protect an individual's data which, in turn, may promote individual well-being and build strong communities.
Comparison of SLAM algorithms and neural networks for autonomous navigation in simulated environments

When looking at the research and industrial landscape, the tendency to favour SLAM based algorithms is ever present and for a good reason. SLAM algorithms are the most mature algorithms that we have available today. However, competitors to this are starting to arise to fill in the gaps that SLAM has in its capabilities at the moment. One of these competitors is the utilisation of Deep Neural Networks or DNN’s - a term loosely applied to Deep Learning algorithms. The proposed study focussed on establishing the characteristic differences between SLAM based algorithms and CNN based algorithms within simulated environments. The Deep Neural Network being tested was developed by the author of the project and trained using data collected within the chosen simulation’s engine. The simulation engine utilised was Unreal Engine 4 (version 4.24) using the latest version of the AirSim plugin (as of the March 2020 update v1.3.1). The SLAM algorithms being used for the comparison were MATLAB variants of ORB-SLAM and CEKF-SLAM. The findings of the project are largely inconclusive, with the project conclusion defining that additional work needs to be complete in order to provide conclusive evidence for the project. However, the supporting findings of the project validate its position as having useful research findings. A clear consensus has been established on the methods required to operate within these environments and understanding the limitations that apply under these software conditions. This is information that is currently poorly defined in the Literature and as such this project serves as a strong base for future projects to build on. Anecdotally, it has been found that the utilisation of CNNs is far more accessible in simulated environments such as AirSim. However, it is a direct result of immaturity for the software utilised. Additionally, the strong Literature Review provides evidence in the direction of CNN utilisation over SLAM based algorithms however these findings were not validated. The project is aimed to be conducted across the formal 2020 academic year spread across the two courses ENG4111 and ENG4112 as part of the dissertation process for a graduating BENGH Engineer.
LibGuides: HIST2 - Primary Source Research Guide: World War I Resources

This guide provides resources and suggestions for locating both primary source materials and secondary sources that provide context for understanding those primary sources.
LibGuides at Priddy Library: ECED 360: Early Literacy: e-Resoources

Emerging literacy process in children, birth to age five. Examination of strategies, materials, and experiences for literacy development
MODELING THE SYSTEM OF ACCOUNTING FOR STUDENT LEARNING OUTCOMES IN THE FORMATION OF AN INDIVIDUAL PATH OF MULTILEVEL ENGINEERING AND TECHNOLOGICAL EDUCATION

Information about the paper titled "MODELING THE SYSTEM OF ACCOUNTING FOR STUDENT LEARNING OUTCOMES IN THE FORMATION OF AN INDIVIDUAL PATH OF MULTILEVEL ENGINEERING AND TECHNOLOGICAL EDUCATION" at IATED Digital Library
Customers’ Perception Towards Victimization Practices In Banking

The Technological Development In The Banking Sector Began With The Use Of AdvancedLedger Posting Machines (Alpm) In The 1980s And Now-A-Days Banks Are Using Core Banking Solution (Cbs) For Providing Better Services To Their Customers.Information Technology And The Communication Networking Systems Have Revolutionized The Functioning Of Banks And Other Financial Institutions All Over The World.  Though The Technological Developments Have Taken Place, Still People Are Having Very Limited Access With The Technologies In Bank. This Helps The Fraudsters To Cheat The People By Using So Many Tricks. The Trick Has Been Named As Cyber Crime. As There Is No Physical Evidence To These Crimes, Criminals Are Free To Act. In This Background, The Study Has Been Carried Out To Know The Awareness Level Of Customers About Cyber Crimes And Their Satisfaction Level Towards The Protection Made By Their Banks. This Study Consisted Of 540 Sample Respondents And The Information Collected From Them Were Analysed With Help Of Spss 23.0. The Findings Of The Study Have Been Summarised And Concluded With Suitable Suggestions.
Library and Academic Services: Streaming Videos Resources Guide: Streaming Video Collections

This guide contains links to RRC Library's Streaming Video databases as well as curated collections for special topic areas; You will also find here a curated collection of links to popular free external video collections such as TED Talks, YouTube Chan
A Weaker Faithfulness Assumption based on Triple Interactions

One of the core assumptions in causal discovery is the faithfulness assumption---i.e. assuming that independencies found in the data are due to separations in the true causal graph. This assumption can, however, be violated in many ways, including xor connections, deterministic functions or cancelling paths. In this work, we propose a weaker assumption that we call 2-adjacency faithfulness. In contrast to adjacency faithfulness, which assumes that there is no conditional independence between each pair of variables that are connected in the causal graph, we only require no conditional independence between a node and a subset of its Markov blanket that can contain up to two nodes. Equivalently, we adapt orientation faithfulness to this setting. We further propose a sound orientation rule for causal discovery that applies under weaker assumptions. As a proof of concept, we derive a modified Grow and Shrink algorithm that recovers the Markov blanket of a target node and prove its correctness under strictly weaker assumptions than the standard faithfulness assumption.
The Effectiveness of Pictionary Game on Vocabulary Mastery on The Eight Grade Students of SMPU Al-Anwari Banyuwangi

This research was aimed to get the empirical evidence of the effectiveness of Pictionary Game on students’ vocabulary retention. The method that was used was a quantitative method. The design of this research was quasi-experimental. This research was conducted in SMPU AL-Anwari Banyuwangi. The number of the sample of the research was 50 students of eighth grade. The instrument of this research was tests. The tests were divided into two, there were pre-test and post test The purpose of this research was to measure there is an effectiveness of Pictionary game on the vocabulary mastery of the eighth grade students‟ of SMPU Al-Anwari Banyuwangi in the 2017/2018 academic year. The area of this research was SMPU Al-Anwari Banyuwangi. It was chosen purposively because they have never been taught by using “Pictionary Game” at this school. Another reason was that the permission to conduct this research in this school from the headmaster has already accepted.
Methods of Using Mobile Applications in Practical and Practical Training

This article describes how to use mobile applications in education on the example of C ++. The main task of the program is to calculate the speed of cars based on the exact numbers specified in the standards and automate the solution of practical, logical problems and examples. Automation is done in mobile applications
LibGuides: Teaching Online Certificate: OER

Created for students of the School of Instructor Education, certificate program in online learning.
Human Learners Integrate Visual and Linguistic Information Cross-Situational Verb Learning

Author(s): Zhang, Yayun; Amatuni, Andrei; Cain, Ellis; Wang, Xizi; Crandall, David; Yu, Chen | Abstract: Learning verbs is challenging because it is difficult to infer the precise meaning of a verb when there are a multitude of relations that one can derive from a single event. To study this verb learning challenge, we used children's egocentric view collected from naturalistic toy-play interaction as learning materials and investigated how visual and linguistic information provided in individual naming moments as well as cross-situational information provided from multiple learning moments can help learners resolve this mapping problem using the Human Simulation Paradigm. Our results show that learners benefit from seeing children's egocentric views compared to third-person observations. In addition, linguistic information can help learners identify the correct verb meaning by eliminating possible meanings that do not belong to the linguistic category. Learners are also able to integrate visual and linguistic information both within and across learning situations to reduce the ambiguity in the space of possible verb meanings.
Are Easy Language Best Practices Applied in Educational Texts for Children in French

Prior research identifies children with aphasia, learning difficulties, and cognitive and hearing impairments as part of the primary target groups with legal rights to Easy Language (EL) texts (Hansen-Schirra and Maas 2020). However, little is known about the potential of EL texts for children and adolescents in general, regardless of their reading abilities. Psycholinguistic studies have shown that some practices, such as the use of anaphoric expressions (Joseph et al. 2015) or temporal connectors (Lecorve 2020) could have an effect on children’s reading comprehension. In this context, it would be interesting to have a closer look at EL and educational texts to highlight shared patterns and pin down what their distinctive features are. Our ultimate goal is to empirically test whether EL texts can be successfully used as a tool to enhance Universal Design for Learning (UDL). As a first step towards this goal, we conducted a study aiming to identify common guidelines among different sets of EL principles used in French-speaking countries and investigate whether educational texts for children aged 7-12 comply with them. In the first stage of the study, we analysed and compared five of the most popular sets of EL principles available in French. Guidelines were classified into five groups based on an adapted version of O’Brien (2003) categories for controlled languages, i.e., lexical, syntactic, text structure, pragmatic and typography. During the second stage, we will examine a corpus comprised of children’s journalistic texts (e.g., Le P’tit Libe) and check for compliancy with the common guidelines identified. Determining to what extent children’s educational texts follow EL guidelines will not only inform the next phase of our project for the validation of EL materials, but might also provide some concrete examples on how to implement French EL guidelines, some of which tend to be general and uncorroborated.
Using Games to Understand Intelligence

Author(s): Brandle, Franziska; Allen, Kelsey R; Tenenbaum, Josh; Schulz, Eric | Abstract: Over the last decades, games have become one of the most popular recreational activities, not only among children but also among adults. Consequently, they have also gained popularity as an avenue for studying cognition. Games offer several advantages, such as the possibility to gather big data sets, engage participants to play for a long time, and better resemblance of real world complexities. In this workshop, we will bring together leading researchers from across the cognitive sciences to explore how games can be used to study diverse aspects of intelligent behavior, explore their differences compared to classical lab experiments, and discuss the future of game-based cognitive science research.
Face Recognition Based on Attendance Management System

Attendance is very important task for an organization like school, colleges, companies etc. Taking of attendance manually is very time consuming. It takes up to 5 to 20 minutes and it depends upon the number of students in a class. Now a day’s technology become more advance, so we have to use biometric system for attendance because it takes very less time as compared to taking attendance manually. In this project we are going to make an attendance system using face recognition. There are many algorithms by which we can make an attendance system using face recognition. In this project we use Viola-Jones Algorithm and Local Binary Pattern Histogram (LBPH) Algorithm. Viola-Jones algorithm is used for face detection and Local Binary Pattern Histogram is used for samples training and face recognition
La evaluación de los aprendizajes en las prácticas didácticas de la formación docente en matemática

This work collectivizes the purpose, the objectives and the theoreticalmethodological strategy of an ongoing research within the framework of the realization of a PhD thesis in Educational Science, at the Facultad de Filosofia y Letras of the Universidad de Buenos Aires. In this study, a qualitative investigation is proposed, through a case study from a clinical approach, with the purpose of studying the assessment modalities of Didactics III teachers in mathematics teacher training and their link with the modalities adopted by their students in their associated pre-professional training practices.This research aims to produce and contribute knowledge, from the singular and contextualized, around the assessment of learning in the classroom in the preprofessional practices of teacher training in mathematics.
PERANCANGAN APLIKASI SISTEM PENYEWAAN LAPANGAN BASKET DENGAN ALGORITMA FIRST COME FIRST SERVED DI KOTA BATAM BERBASIS WEB

ABSTRACT The era of globalization now demands to use systems to be effective and efficient in a business, because technological developments are growing rapidly. This makes competition tough in all fields, especially in the business sector. There are various models of ordering in business like ordering a basketball court. To order a basketball court, there must be a compromise from the owner of the field. In general, this basketball court ordering system is usually done directly to the owner or through social media by chatting with the owner. There are still shortcomings in this process, including the time.The conclusion of this research is to create a web-based application specifically for ordering basketball courts to solve the problems in ordering basketball courts. Based on the conclusions of this study, it is recommended: (1) A web-based basketball court ordering system which can help consumers who want to play basketball. (2) With this system, consumers do not have to go directly to the place. (3) Can provide information on the playing schedule easily.
Ethnocultural competencies of a teacher in the context of education digitalization

The topicality of this research problem is based on the necessity to create a digital educational environment and expand prospects of online education that is realized in correspondence with the project “Modern digital educational environment”, approved by the Government of the Russian Federation within the framework of implementing the state-run program “Education development” in 2013-2020. In the context of education digitalization, the requirements for teachers’ ethnocultural competencies also change and acquire new content. Consequently, the aim of the research is to elaborate and analyze the content of ethnocultural competencies in the context of education digitalization as well as to reveal and experimentally verify the effectiveness of practical experience of an educational institution in forming future teachers’ ethnocultural competencies. This article discusses the experience of the Faculty of Psychology and Pedagogy of Mari State University in this direction. Research methods: theoretical methods, аs far as empirical methods are concerned, a questionnaire and a pedagogical experiment were used. The 50 participants of this experiment are fourth- and fifth-year students pursuing a bachelor’s degree in Psychology and Pedagogy. Results and recommendations. These research results conclude that it is necessary to implement system-based and civilizational approaches when forming ethnocultural competencies of future teachers in the context of education digitalization. In this case, it will be possible to form a person adequate to the digital economy and able to use digital technologies in their ethnically oriented work. These research results can be applied to design curriculums and academic course syllabuses of higher education as well as to carry out comparative studies for improvement of education quality of future teachers.
Breast Cancer Detection Using Various Classification Algorithms

Machine learning algorithms are playing an important role, nowadays, to extract the features of any application. Here used these mechanisms to detect breast cancer by considering the standard dataset. Various classification techniques are considered to find the performance of the detected results. Initially removed the noise over a data set that is missed data and then extracted the features and next applied the classifiers such as SVM, KNN, Random Forest, decision tree, etc. The classifier efficiency was evaluated by considering the characteristics like true positive, false positive, ROC curve, etc. The main strength of this work is experimental results which are shown by considering the standard dataset from Kaggle.
pRSL: Interpretable Multi-label Stacking by Learning Probabilistic Rules

A key task in multi-label classification is modeling the structure between the involved classes. Modeling this structure by probabilistic and interpretable means enables application in a broad variety of tasks such as zero-shot learning or learning from incomplete data. In this paper, we present the probabilistic rule stacking learner (pRSL) which uses probabilistic propositional logic rules and belief propagation to combine the predictions of several underlying classifiers. We derive algorithms for exact and approximate inference and learning and show that pRSL reaches state-of-the-art performance on various benchmark datasets. In the process, we introduce a novel multicategorical generalization of the noisy-or gate. Additionally, we report simulation results on the quality of loopy belief propagation algorithms for approximate inference in bipartite noisy-or networks.