Reviewerly/exHarmony huggingface dataset:
Key competencies and standardization in design education in the UK

The article attempts to consider how key competencies are formed in the process of teaching design disciplines in the UK at each stage of education from kindergarten to higher education, taking into account the requirements of the labor market, as well as how the problems of introducing new competencies and developing basic educational standards for productive development are solved at the state and business level. The article examines step-by-step the processes of competence formation at different stages of training, as well as examines the difficulties and failures faced by design education in the UK and ways to solve the difficulties that can be adopted by Russian design education. Thus, the purpose of the study is to extract useful experience in the formation of key competencies in design education in the UK and bring Russian design education closer to practical, responding to the needs of modern society, since design is policy and strategy for managing industries that uses creativity and innovation as a way of designing the future. It is a methodology used to solve complex problems and find the desired solutions for customers by integrating innovations. Undoubtedly, the author is interested in conducting a comparative analysis of the implementation of design education in the EU countries and in economically developed America, which in the future will be a continuation of research in the field of design education in Russia in order to integrate the positive experience of training future designers abroad into the domestic education system.
PENGEMBANGAN MEDIA BUSY BOOK UNTUK MENINGKATKAN KEMAMPUAN MEMBACA AWAL DAN PERKEMBANGAN KOGNITIF ANAK USIA DINI (Studi Pada Anak Kelompok A PAUD Kota Bengkulu)

The purpose of this study was to produce a product in the form of busy book media as a learning medium to improve early reading skills and cognitive development as well as to determine the increase in early reading and cognitive development of children using developed busy book media compared to the learning media used by teachers. The subjects of this study were PAUD group A children, on a limited scale test the subject was PAUD IT Al Kahfi Bengkulu City, and on a wide scale test the subject was PAUD Islam Intan Insani Kota Bengkulu and PAUD IT IQRA in Bengkulu City. This research method is a research and development method (Research and Development -R &amp; D-). Retrieval of research data using assessment sheets and observation sheets. The data collected in this study are data from media experts, data from material experts, and data from observations. The data analysis technique of the validation instrument used the mean score, the instrument analysis of reading ability and cognitive development used the percentage score and the different aspects of development using busy book media compared to LKA using the t-test. The results of this study indicate that the use of busy book media as a learning medium can improve children's early reading skills and cognitive development.
Corporate Environmental Disclosure Quality and Impression Management Theory in Nigeria

Corporate environmental disclosure acts as a means of providing environmental information to fulfill firms' accountability relationship with stakeholders and to express firm's environmental awareness.However, the level of environmental disclosure by Nigerian firms is still low and the relationship with actual environmental performance is still inclusive.This study examines this phenomenon using the impression management theory.The theory asserts that firms provide environmental information as an attempt to control the impression of the public and the stakeholders.The sample of the study comprises of firms listed on the Nigerian stock exchange as at 31 st December, 2020.GRI disclosure index is used in collecting environmental disclosure data from the annual reports of the sampled firms.The environmental performance (EP) data was collected from the ministry of environment website.The result of this study reveals that EP does not have any influence on companies' disclosure of environmental information.The result of the study provides motivation for the NSE to review all existing CSR reporting framework so as to provide a guidance to firms to prepare a more objective voluntary environmental disclosure.
Prioritization of COVID-19-Related Literature via Unsupervised Keyphrase Extraction and Document Representation Learning

The COVID-19 pandemic triggered a wave of novel scientific literature that is impossible to inspect and study in a reasonable time frame manually. Current machine learning methods offer to project such body of literature into the vector space, where similar documents are located close to each other, offering an insightful exploration of scientific papers and other knowledge sources associated with COVID-19. However, to start searching, such texts need to be appropriately annotated, which is seldom the case due to the lack of human resources. In our system, the current body of COVID-19-related literature is annotated using unsupervised keyphrase extraction, facilitating the initial queries to the latent space containing the learned document embeddings (low-dimensional representations). The solution is accessible through a web server capable of interactive search, term ranking, and exploration of potentially interesting literature. We demonstrate the usefulness of the approach via case studies from the medicinal chemistry domain.
The Use of Popular Cultural Products in Language Learning: A Case Study of Japanese Language Students in Malaysian Public Universities

Language teaching and learning has become easier with the advent of the internet and the rapid pace of information technology.If in the 1990s, teachers or instructors still used faceto-face medium in language teaching, but little by little, the function of educators is declining in the classroom or lecture room.Some students have already learned this language and can communicate in Japanese by watching anime and reading manga.They have already gained the skills to listen and understand the meaning of some catchy vocabulary and phrases.When they take Japanese language courses at university, learning to recognize writing, pronunciation, grammar, and conversation become more accessible and more exciting.This paper aims to identify Japanese popular culture products that can be used for learning purposes.Two surveys distributed through Google Form were involved in this study, namely 2020 and 2021 and one hard copy survey in 2018.The findings show that in addition to anime and manga, students also use computer games, Seiyu and VTuber as Japanese language learning tools.The students can minimize conventional face-to-face learning hours with the teacher and use their own space and time without reducing learning Japanese.
Deep Learning on EEG Study Concentration in Pendemic

Brainwaves are one of the biometric properties that can be used to identify individuals based on their physical and behavioural characteristics. An electroencephalogram (EEG) can be used to measure and capture brain wave activity. The activities required are in the form of giving complex tasks to get thinking and concentration processes called Cognitive Tests, in the form of a Culture Fair Intelligence Test (CFIT) stimulus and Competency Test (UK). This study aims to obtain a pattern of the relationship between concentration and learning outcomes for late adolescent students during the pandemic. The object of research involved in this research is the 10th grade students of TKJ SMK. Data acquisition was carried out twice on the Beta signal by doing cognitive test questions which were done twice at school and at home. Then the data obtained from the test results will be extracted using Fast Fourier Transform (FFT). Furthermore, after the data extraction results are obtained, the classification process will be carried out using the CNN algorithm. The results of the FFT obtained the average value of the signal peak. The results of the CNN classification show that the pandemic does not affect student concentration. The average signal concentration in schools when testing using CFIT is 0.2445 and at the time of testing using UK Mathematics is 0.1330 with an average CFIT score of 77.05 and for UK average is 53.33 with an accuracy value of 83.33 %. While the average signal concentration at home when testing using CFIT is 0.2252 and at the time of testing using UK Mathematics is 0.1301 with an average CFIT score of 77.13 and for UK average is 57.50 with an accuracy value of 83, 33%.
Physics Teaching in Croatian Elementary and High Schools during the Covid-19 Pandemic

In spring 2020, 916 elementary schools and 443 high schools were closed in Croatia due to the Covid-19 pandemic and remote teaching was introduced. This had an impact on physics teaching as an experimental subject. In addition to positive aspects concealed in new experiences and work perspectives, the sudden transition from conventional face-to-face teaching to a remote format had an undeniable negative impact on physics teaching in elementary and high schools. In order to mitigate the effects and provide a detailed insight into the problems that arose during this transition, we conducted a quantitative study among teachers of physics in elementary and high schools in Croatia, with the aim of identifying logistical and technical problems and challenges in physics teaching during the Covid-19 pandemic. An online questionnaire with five parts (general data, teaching physics during the Covid-19 pandemic, experiments, sociological component, exchange of experience) was completed by 178 Croatian teachers. The results irrefutably point to the flexibility and responsiveness of physics teachers, an increase in the teachers’ workload, a lack of the experimental work that forms an essential part of the subject of physics, and a lack of teacher knowledge (in ICT), skills and equipment for conducting distance teaching. However, it also emerged that online teaching, if carefully designed and individualised, can stimulate additional commitment and interest in the subject among students. The paper presents the research findings in detail, with the aim of helping physics teachers to plan further teaching more effectively as and if the pandemic progresses.
A Semi-supervised Framework for Misinformation Detection

The spread of misinformation in social media outlets has become a prevalent societal problem and is the cause of many kinds of social unrest. Curtailing its prevalence is of great importance and machine learning has shown significant promise. However, there are two main challenges when applying machine learning to this problem. First, while much too prevalent in one respect, misinformation, actually, represents only a minor proportion of all the postings seen on social media. Second, labeling the massive amount of data necessary to train a useful classifier becomes impractical. Considering these challenges, we propose a simple semi-supervised learning framework in order to deal with extreme class imbalances that has the advantage, over other approaches, of using actual rather than simulated data to inflate the minority class. We tested our framework on two sets of Covid-related Twitter data and obtained significant improvement in F1-measure on extremely imbalanced scenarios, as compared to simple classical and deep-learning data generation methods such as SMOTE, ADASYN, or GAN-based data generation.
Feature Selection for Regression Based on Gamma Test Nested Monte Carlo Tree Search

This paper investigates the nested Monte Carlo tree search (NMCTS) for feature selection on regression tasks. NMCTS starts out with an empty subset and uses search results of lower nesting level simulation. Level 0 is based on random moves until the path reaches the leaf node. In order to accomplish feature selection on the regression task, the Gamma test is introduced to play the role of the reward function at the end of the simulation. The concept Vratio of the Gamma test is also combined with the original UCT-tuned1 and the design of stopping conditions in the selection and simulation phases. The proposed GNMCTS method was tested on seven numeric datasets and compared with six other feature selection methods. It shows better performance than the vanilla MCTS framework and maintains the relevant information in the original feature space. The experimental results demonstrate that GNMCTS is a robust and effective tool for feature selection. It can accomplish the task well in a reasonable computation budget.
Morphological Practical Teaching Platform Improves the Outcome of Anatomy Laboratory Teaching

To investigate if the new morphological practice teaching platform could improve the outcome of anatomy laboratory teaching. Students were randomly divided into two groups taught with two different teaching methods. The two teaching methods used in this study were the traditional teaching model and the innovative teaching model. The teaching outcome including learning satisfaction between the two groups were studied. Both the teaching results and the teaching satisfaction of students in the integrated innovation teaching group were significantly higher than those in the control group. (P < 0.05) This suggests that the new morphological practical teaching platform improves the outcome of anatomy laboratory teaching.
Leveraging Digital Library Infrastructure to Build a Language Archive

Building a digital language archive requires a number of steps to ensure collecting, describing, preserving, and providing access to language data in effective and efficient ways. The Computational Resource for South Asian Languages (CoRSAL) group has partnered with the University of North Texas (UNT) Digital Library to build a series of interconnected digital collections that leverage existing UNT technical and metadata infrastructure to provide access to data from and for various language communities. This article introduces the reader to the background of this project and discusses some of the important for representing language materials areas where UNT metadata has needed flexibility to better fit the needs of intended audiences. These areas include a workflow for standardized language representation (the Language field), defining roles for persons related to the item (Creator and Contributor fields), and representing interconnections between related items (the Relation field). Although further work is needed to improve language data representation in the CoRSAL digital language archive, we believe the model adopted by our team and lessons learned could benefit others in the language archiving community.
The Role Of Institutional Conditions In The Impact Of Economic Growth On Poverty

Purpose: According to the New Institutional View, the main reason for the great difference between countries in terms of growth, development and economic welfare is their institutional structures and foundations. Creating a stable structure in human relationships, institutions reduce insecurity, transaction costs and increase people's motivation. In this regard, the present study examined the role of institutional conditions in the impact of economic growth on poverty in middle and high per capita income countries from 2004 to 2017.
Detection and Identification of Pancreatic Cancer Using Probabilistic Neural Network

The fact that pancreatic cancer has a low life expectancy, that is only 9% of people survive five years, makes a diagnosis catastrophic. The majority of patients are diagnosed late in life, where care choices are minimal. Early diagnosis of pancreatic cancer will greatly increase a person’s chances of survival. Accurate PC staging will help doctors have the right treatment plan for PC patients at different stages, as well as the diagnostic measures needed for a quicker cancer recovery. In this proposed project, ultrasound images will be analyzed. The noise in the image is minimised using the Median Filter. In the next step, Gray Level Co-occurrence Matrix (GLCM) and Discrete Wavelet Transform (DWT)are used to extract related features. Following this extraction step, the refined characteristics are fed into a Probabilistic Neural Network (PNN) neural network classifier, which determines whether or not cancer is present. Metrics such as sensitivity, precision, and specificity are used in experimental computation.
A novel and robust method of indexing the uncoded stripes for multi‐line based structured light application

Finding the correspondence between the captured and projected uncoded stripe pattern, which is called the indexing problem, has proved to be difficult to overcome reliably. Due to the interference of the non-ideal phenomena, the extracted stripe might be lost, increased or shifted undetectably. This letter proposes a graph-matching based method to address this problem. The captured stripes are categorized into two parts according to whether they should be offset after projection. For the non-offset stripes, they can be accurately indexed by the predetermined projection pattern. Based on the structural similarity that exists on the two kinds of stripes, we establish two graphs and match them to index the offset stripes fast and effectively. Thus, the iterative process in the previous study is avoided and the troublesome issues are solved. The proposed method is applied to the virtual touchpad scheme to make an arbitrary surface touch-sensitiveness. Experimental results show that the ameliorated virtual touchpad scheme yields an average touch detection accuracy of 96.07%, and the indexing accuracy evaluated by randomly selected patterns is 100%.
Features of the design of social posters of the XXI century and their role in the formation of ecological culture

The article considers the poster design as a means of broadcasting and its role in the formation of ecological culture. The impact of the development of technological progress on the birth of completely new forms of the poster, which are not limited to one paper medium. The value of a social poster is in its content aspect, conceptual solution, well-chosen palette, composition. The language of graphic design changes along with the situation in society, becomes extremely figurative, exaggerated, metaphorical, symbolism takes the place of verbatim. The main task of the design of a social poster focused on nature conservation is to contribute to the formation of an ecological culture, starting with personal motivation for self-preservation and preservation of the environment, where the knowledge and skills of both each person individually and entire human communities. The purpose of the social poster is to orient the viewer to the commitment to the highest social values - such as humanism, love for people, for life, and nature. The poster is an iconic carrier of information, simple and understandable, which does not require intellectual efforts from the viewer and educates him both morally and aesthetically, influences a person’s emotions, his attitude to the environment.
PROFESSIONAL DEVELOPMENT OF STUDENTS BASED ON COMPETENCE-MODULAR LEARNING TECHNOLOGY

An innovative approach to the organization of students' independent education is described. The invariant structure of self-educational competence formation activity is considered. The notion of self-educational competences of four levels of complexity is introduced. With the help of the proposed methodological aids a student can independently organize his/her studies at a convenient time for him/her, as well as carry out self-control and determine the level of his/her knowledge. The proposed technology has been tested in two universities: Samara State University of Railway Transport and Samara State Technical University. The pedagogical experiment was carried out in the first and second year of fulltime and correspondence courses of mathematics.
Students’ Perception on Learning Vocabulary through WhatsApp Group Media During Covid-19 Pandemic

Social networking apps have emerged as potentially useful new tools for improving second language vocabulary acquisition. The current research compares the growth of academic vocabulary knowledge in English. The purpose of this study is to compare the perspectives or views of the Department of English Education at Singaperbangsa Karawang University (UNSIKA). Online learning conducted during the Covid-19 Pandemic students using WhatsApp group media to traditional vocabulary instruction methods. The qualitative research method used in this study is a descriptive design with an explanation of the form of narrative related to the views of students in online learning during the pandemic. Data was collected through interviews specially semi structure interview based on interview guideline and data analysis by involving three students in the online learning process. The findings provide information about the learning process as well as the advantages and disadvantages of WhatsApp media. The interview results show that students in general have a positive attitude toward learning vocabulary through WhatsApp group media. However, technological limitations, unfamiliar presentation, and learning activities may prevent students from participating in a WhatsApp media lesson.&#x0D;
Developing a tool to measure interest in audiences of a virtual planetarium show

Informal learning environments often have a clear ambition to spark interest [1].People also need multiple exposures to content [2,3] to learn.The Dome+ model, with its principles of interest, identity, and agency, was developed to guide the construction of the Big Astronomy Project consisting of a planetarium show plus additional resources, to support audiences in extending engagement beyond the physical space of the planetarium.A main design principle was sparking interest through the immersive environment of the show.The Big Astronomy Project released a show as a virtual YouTube 360 • stream due to the COVID-19 pandemic.Here we test the utility of the four-phase interest model [4] to characterize interest surrounding the virtual show for use in our larger dataset.The four-phase model suggests people progress from earlier phases of situational interest induced by the environment to later phases of individual interest marked by self-driven engagement.We use this model to characterize the role the show plays in audience interest and look for the role of interest in a virtual environment.We used focus groups with audience members on our premiere day of the planetarium show consisting of eight individuals, and included follow-up interviews with five of those individuals to understand how they continued their engagement with the Big Astronomy Project.Everyone indicated that they chose to watch the show because of an established interest in astronomy.Since self-induced engagement is an aspect of individual interest, we placed all participants in phases 3 to 4. Our data lacked people who fell into the situational interest phases.We suggest that virtual shows will attract individuals who have an individual interest.We plan to use this research as a tool for the analysis of the larger dataset that includes a more diverse set of individuals.