Reviewerly/exHarmony huggingface dataset:
Semi-Supervised Domain Generalization with Evolving Intermediate Domain

Domain Generalization (DG) aims to generalize a model trained on multiple source domains to an unseen target domain. The source domains always require precise annotations, which can be cumbersome or even infeasible to obtain in practice due to the vast amount of data involved. Web data, however, offers an opportunity to access large amounts of unlabeled data with rich style information, which can be leveraged to improve DG. From this perspective, we introduce a novel paradigm of DG, termed as Semi-Supervised Domain Generalization (SSDG), to explore how the labeled and unlabeled source domains can interact, and establish two settings, including the close-set and open-set SSDG. The close-set SSDG is based on existing public DG datasets, while the open-set SSDG, built on the newly-collected web-crawled datasets, presents a novel yet realistic challenge that pushes the limits of current technologies. A natural approach of SSDG is to transfer knowledge from labeled data to unlabeled data via pseudo labeling, and train the model on both labeled and pseudo-labeled data for generalization. Since there are conflicting goals between domain-oriented pseudo labeling and out-of-domain generalization, we develop a pseudo labeling phase and a generalization phase independently for SSDG. Unfortunately, due to the large domain gap, the pseudo labels provided in the pseudo labeling phase inevitably contain noise, which has negative affect on the subsequent generalization phase. Therefore, to improve the quality of pseudo labels and further enhance generalizability, we propose a cyclic learning framework to encourage a positive feedback between these two phases, utilizing an evolving intermediate domain that bridges the labeled and unlabeled domains in a curriculum learning manner...
CREATIVE TEACHING AND LEARNING DURING THE PANDEMIC TIMES

Creative approaches to education should not be applied only in the fields of art and culture (art subjects), but should permeate the entire process of primary education. Through the methods of qualitative research (observation of lessons, semi-structured interview with teachers and analysis of preparations for lessons) we will investigate which role the creative teaching plays in the times of pandemic and how it differs from other approaches to education of pupils of the Czech primary schools. The change of the form of teaching for pupils during the pandemic times means more responsibility and more individual work at home. Therefore we will deal with the question how can the artistic creativity help us in case of overcoming the barrier of the mingling of two worlds of the offline and on-line teaching. Furthermore, we will detect if teachers use methods of creative teaching. In the on-line environment to pupils is given space for their creativity, fantasy and to use skills which are not directly related to the school subject or to the teaching topic. Digital technologies offer a huge potential for integration of creative teaching in all spheres of education. However, they should not replace the pupils skills of ask questions, experiment and solve problems (NÚV, 2021).
Identification and remediation of students’ disadvantages due to COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has led to a number of problems of which the implications for the future are not minor. The main consequence of the COVID-19 breakout was that almost 100% of the Spanish population had to be confined from March to June. Despite the progressive normalisation of learning, the effects of the pandemic are expected to last for many years. This paper suggests the implications of those side effects that will require not few efforts to become overcome through a descriptive methodology. These effects are not only educational but may also have, according to several studies hereby addressed, an economic effect on the youth. The paper concludes that remedial measures should include additional teaching staff to increase the number of teaching hours in the academic year 2021–2022.&#x0D; &#x0D; Keywords: Pandemic, COVID-19, education, technology, remedial.
The Impact of Project Management on Business Performance of Small and Medium Enterprise in UAE

Today, Small and Medium Enterprises (SMEs) play an essential role in the economy of nations, in terms of employment, development, and growth. SMEs have achieved significant contributions to the economy of United Arab Emirates (UAE) in recent decades. However, SMEs increasingly face a lot of challenges and competition not only from their peers but also from large firms in the international and domestic market. Moreover, the majority of SMEs rely on traditional management styles, while it is still unclear to what extent project management practices enhance SME business performance. Hence, the aim of this study is examining the relationship between project management practices and business performance of SMEs in UAE from the perspective of Balanced Scorecard Theory (BSC). The analysis in this study is based on quantitative methods and survey process for selected firms under SME category in Dubai. The focus is on private limited companies, working in trading, services, and manufacturing. The respondents are the CEOs and general managers. The result indicates a significant relationship does exist between project management and SME business performance. Thus, SMEs should focus on the important aspects of project management from the perspective of BSC business model, such as project time management, project cost management, project quality management, project communications management to foster the performance of SMEs in the market. However, there is yet to be a further researching on other areas in SMEs and extend the study to investigate more variables in future studies.
LibGuides: Information Literacy: Fake News

The purpose of this LibGuide is to provide students with resources on information literacy. This page explores the definition of fake news and how to recognize fake news.
Research Committee Update: The curmudgeon's column: High-tech low tech

When I posted to LinkedIn some time back to generate publicity for my Geophysical Society of Houston technical lunch talk on beam tomography, one of the interesting comments from a colleague at a large service company was that beam technology is “a technology with many benefits that unfortunately is commonly regarded as old school/low tech.” I loved receiving the comment because it gives me an opportunity to talk about one of my favorite business concepts that I always look to apply: high-tech low tech. “High tech” is a term for new technology that incorporates advanced features. “Low tech” is old-school technology. I'll start with an example: the story of the Nest thermostat.
ONLINE ENGAGEMENT AS A DECISION CRITERION IN DIGITAL COURSE DESIGN

In education, few would argue against the importance for academic institutions, teachers and instructional designers to capture, develop, maximise and maintain the level, intensity and persistence of the students’ engagement in their learning experience. This is hardly surprising as researchers have found student engagement to be positively associated with academic performance and persistence, as well as other positive academic, social and emotional outcomes such as attendance, social awareness and emotional self-regulation.More recently, researchers have turned their attention to the factors that promote learner engagement in an online context, thanks largely to the widespread adoption of massive open online courses (MOOC), the democratisation of online and blended learning in traditional academic institutions, and the more recent legitimisation of online learning as a viable alternative to the face-to-face mode of delivery in times of crises such as the COVID-19 pandemic.This paper proposes an antecedent-consequent framework for employing online engagement as a decision criterion in digital course design. Its application is illustrated via a marketing course with two different course designs (the antecedents). Using data from Canvas, a learning management system (LMS), and an online engagement framework developed by Tan & Koh (2018), nine online access metrics are computed to measure different aspects of online learning engagement for each of the two course designs. Subsequently, based on the online engagement behaviour desired (the decision criterion), the appropriate digital course design is identified and can then be implemented to enhance learning outcomes (the consequents).The rationale underlying the antecedent-consequent framework focused on online engagement to aid digital course design is that online engagement is important as it is associated with positive outcomes. Also, online engagement is itself affected by course design, among other factors. Hence, by mapping the associations between various course designs and the resulting online engagement metrics computed with LMS data and learning analytics, an appropriate course design can be identified leading to the desired online engagement behaviour, which will in turn, lead to positive outcomes.The proposed framework assumes the availability of alternative course designs and their resultant online engagement behaviours as measured with LMS data. Despite this limitation, it is hoped that this study can help instructors and course designers develop courses that can better enhance learning outcomes and learner experience.
Motion-aware Contrastive Video Representation Learning via Foreground-background Merging

In light of the success of contrastive learning in the image domain, current self-supervised video representation learning methods usually employ contrastive loss to facilitate video representation learning. When naively pulling two augmented views of a video closer, the model however tends to learn the common static background as a shortcut but fails to capture the motion information, a phenomenon dubbed as background bias. Such bias makes the model suffer from weak generalization ability, leading to worse performance on downstream tasks such as action recognition. To alleviate such bias, we propose \textbf{F}oreground-b\textbf{a}ckground \textbf{Me}rging (FAME) to deliberately compose the moving foreground region of the selected video onto the static background of others. Specifically, without any off-the-shelf detector, we extract the moving foreground out of background regions via the frame difference and color statistics, and shuffle the background regions among the videos. By leveraging the semantic consistency between the original clips and the fused ones, the model focuses more on the motion patterns and is debiased from the background shortcut. Extensive experiments demonstrate that FAME can effectively resist background cheating and thus achieve the state-of-the-art performance on downstream tasks across UCF101, HMDB51, and Diving48 datasets. The code and configurations are released at https://github.com/Mark12Ding/FAME.
Safe Autonomous Racing via Approximate Reachability on Ego-vision

Racing demands each vehicle to drive at its physical limits, when any safety infraction could lead to catastrophic failure. In this work, we study the problem of safe reinforcement learning (RL) for autonomous racing, using the vehicle's ego-camera view and speed as input. Given the nature of the task, autonomous agents need to be able to 1) identify and avoid unsafe scenarios under the complex vehicle dynamics, and 2) make sub-second decision in a fast-changing environment. To satisfy these criteria, we propose to incorporate Hamilton-Jacobi (HJ) reachability theory, a safety verification method for general non-linear systems, into the constrained Markov decision process (CMDP) framework. HJ reachability not only provides a control-theoretic approach to learn about safety, but also enables low-latency safety verification. Though HJ reachability is traditionally not scalable to high-dimensional systems, we demonstrate that with neural approximation, the HJ safety value can be learned directly on vision context -- the highest-dimensional problem studied via the method, to-date. We evaluate our method on several benchmark tasks, including Safety Gym and Learn-to-Race (L2R), a recently-released high-fidelity autonomous racing environment. Our approach has significantly fewer constraint violations in comparison to other constrained RL baselines in Safety Gym, and achieves the new state-of-the-art results on the L2R benchmark task. We provide additional visualization of agent behavior at the following anonymized paper website: https://sites.google.com/view/safeautonomousracing/home
Mood Analysis of Bengali Songs Using Deep Neural Networks

Nath, Devjyoti Phani, ShantaIn the current state of the situations around the world, song and music are the true helpers to calm the depressed minds. People try to listen to the songs which sync with their emotions, and therefore, this has led to emotion labeling as an emerging trend for the digital song libraries or song repositories. Several studies on emotion or mood analysis of songs have been carried out for the highly resourced languages such as English and Japanese; it is relatively less observed for low-resourced languages like Bengali, which is a morphologically rich language. In this paper, we have proposed emotion classification for Bengali songs based on simple features and the classical machine learning as well as deep learning algorithms, from textual lyrics. We have also proposed annotated dataset lyrics with positive and negative polarities. Our proposed models achieve more than 81% accuracy on the Bengali song lyrics based on the above-said features.
Psychological aspects of acquisition of writing skills in English language

Affective factors play an integral role in English language learning. If we want to be successful in teaching language writing, we need to look into these socio-psychological factors of students. There is a correlation between self-efficacy and writing anxiety that directly influences students’ writing performance. Students’ self-confidence in writing can minimize the anxiety. Pedagogically, methods are chosen specially by teachers, because of acquisition and learning of writing skills of students.
REFORMS IN THE EDUCATION OF STUDENTS AND FUTURE TEACHERS AIMED AT STRENGTHENING THE CONTENT OF THE CURRICULUM TOWARDS INFORMATION TECHNOLOGY

Information about the paper titled "REFORMS IN THE EDUCATION OF STUDENTS AND FUTURE TEACHERS AIMED AT STRENGTHENING THE CONTENT OF THE CURRICULUM TOWARDS INFORMATION TECHNOLOGY" at IATED Digital Library
Pengembangan Gerakan Madrasah Membaca (GMM) dengan Program Literasi Perpustakaan (PLP)

The objectives of this service are 1) increasing knowledge and understanding of the madrasah reading movement based on library management, 2) increasing madrasa library management services, 3) increasing the ability of library management resources, 4) increasing madrasah services in implementing the madrasa reading movement. The method of implementing this trial uses a participation rular appraisal approach, which is a method of involving various elements that are considered to contribute in submitting ideas, ideas for the smooth running of a service program. The results of the service implementation consist of four solution programs that have been implemented, namely 1) problem mapping with the discovery of what potential can be realized together through a group discussion forum agenda, 2) assistance for reading/literacy movement programs for madrasas in collaboration with the University of Muhammadiyah Magelang (UNIMMA) library and Regional Library (Perpusda) Magelang Regency, 3) strengthening library resource services in collaboration with the University of Muhammadiyah Magelang library, 4) performance program follow-up plans, namely the madrasa reading movement which began with the madrasa library organizational structure, book donation movement by student guardians, committee management madrasas and PRM and PCM, improving library infrastructure (rooms, shelves, book layouts, and preparing library corners in the corner of the classroom), mosaic competitions, speed reading, coloring, story-telling, and assistance in making proposals for collaboration.
INFORMAL LANGUAGE LEARNING THROUGH INTERACTIVE SOCIAL MEDIA TOOLS: CURRENT TRENDS AND PRACTICES

Informal learning is recognised as a more entertaining and less forced process compared to formal learning, which makes the former a useful pedagogical complement to the latter. The aim of the present paper is to identify current trends and formulate best practices regarding the design of learning materials for English as a foreign or second language as found on the Instagram social network. The research involves the analysis of selected Instagram profiles that are positioned as providing informal assistance for English learning, with the focus on the content of regular posts as well as topical highlights selected for permanent access by the account owner. A particular issue of interest includes the representation of different types of linguistic, sociolinguistic and pragmatic knowledge as well as individual aspects of communicative competence in the posts and stories. Attention is also paid to the evaluation of the strength and weaknesses of posts with different formats and topical orientation, based on user feedback in the commentary section
Self-dual twisted generalized Reed-Solomon codes

In this paper, by using some properties for linear algebra methods, the parity-check matrices for twisted generalized Reed-Solomon codes with any given hook $h$ and twist $t$ are presented, and then a sufficient and necessary condition for the twisted generalized Reed-Solomon code with $h\ge t$ to be self-dual is given. Furthermore, several classes of self-dual codes with small Singleton defect are constructed based on twisted generalized Reed-Solomon codes, especially some of these self-dual codes are MDS or NMDS.
Maximizing the Skills of Bringing Student Events Through the Use of Youtube

The background of the research is the importance for the students to have master of ceremony skill. Therefore, appropriate alternative learning concept needs to be formulated to help the students to optimize the skill to be a master of ceremony. This study aims to describe Youtube as an alternative learning. This research uses a qualitative approach with descriptive methods. Data collection techniques using literature study and observation. The instruments used were data cards and observation guidelines that had been validated by experts. The study was conducted in 2019 with informants of Indonesian Language Education Study Program students at the University of PGRI Semarang who took the Speaking Course. Data validity uses the triangulation of data sources. The data collected was analyzed using stages: classification, analysis, and drawing conclusions. The results showed that Youtube can be used as a source of learning, learning media, and a means of disciplining learning products. With the right form of utilization, Youtube can minimize various obstacles, including limited time for practice, students' oral language skills, and knowledge possessed by students.
Learning Continuous Environment Fields via Implicit Functions

We propose a novel scene representation that encodes reaching distance -- the distance between any position in the scene to a goal along a feasible trajectory. We demonstrate that this environment field representation can directly guide the dynamic behaviors of agents in 2D mazes or 3D indoor scenes. Our environment field is a continuous representation and learned via a neural implicit function using discretely sampled training data. We showcase its application for agent navigation in 2D mazes, and human trajectory prediction in 3D indoor environments. To produce physically plausible and natural trajectories for humans, we additionally learn a generative model that predicts regions where humans commonly appear, and enforce the environment field to be defined within such regions. Extensive experiments demonstrate that the proposed method can generate both feasible and plausible trajectories efficiently and accurately.
Penerapan Data Mining Klasifikasi Pada Calon Pelanggan Baru Indihome dengan C.45

Indihome customers are people who are buyers of products that have been made and marketed by a company, where this person not only buys the product once but repeatedly. Meanwhile, Prospective Indihome customers are those who have not become your customers (buyers/service users) but are considered to have the opportunity to become customers in the near future or in the future. An algorithm is needed to classify indihome's new prospective customers so that there is no loss between the two parties. The C4.5 algorithm was chosen because it is able to classify new prospective customers of Indihome by using the rapid miner application and the calculation using Microsoft Excel. From the calculations using the two applications, the results obtained include: If Income 2000000 then the result is Eligible (Eligible = 54 and Not Eligible = 0)
Desafíos de la práctica docente en tiempos de pandemia

In recent times, teaching practices needs to be rethink in order&nbsp;to continue with the main purpose: to educate. This leads us&nbsp;to think about what the qualities of a teacher are or should&nbsp;be and reflect on their ability to adapt to the new reality.&nbsp;However, the responsibility should not fall only on them, but&nbsp;on an entire system that should ensure accessibility to the&nbsp;new form of teaching-learning due to the Covid19 pandemic.&nbsp;In this exceptional situation that we are experiencing,&nbsp;we need to stop and reflect on the current challenges that&nbsp;teachers present and the ability to break down the barriers of&nbsp;traditional education.
Labor Education in Primary and Secondary Schools in the New Era Based on Modern Information Technology

With the rapid development of information technology represented by artificial intelligence (AI), there has been a great impact on educational methods, educational behaviors, and educational models. It can even be said that there is a fundamental change. Especially under the influence of the pandemic, educational behaviors have undergone radical changes. The education management information system in primary and secondary schools strengthens the service of labor education for primary and secondary school students, with a data analysis system for labor education. A survey on labor education in 103 primary and secondary schools in the region has been carried out. Information technology can well improve the form of labor education in primary and secondary schools and promote the development of labor education. Big data can be used to objectively analyze the problems of labor education in primary and secondary schools, thus proposing a new era of labor education data analysis system and management for primary and secondary schools.