Reviewerly/exHarmony huggingface dataset:
THE SOLVING PATH AND EMPIRICAL RESEARCH OF PUPILS' ENGLISH LANGUAGE ATTRITION PROBLEM IN BLENDED LEARNING ENVIRONMENT

THE SOLVING PATH AND EMPIRICAL RESEARCH OF PUPILS' ENGLISH LANGUAGE ATTRITION PROBLEM IN BLENDED LEARNING ENVIRONMENT
MOBILE AND CLOUD TECHNOLOGIES IN THE VIRTUAL LEARNING SYSTEM

G. Madyarova, M. Bolyskhanova, G. Tkach, M. Kuanyshbayev, K. Adamova, T. Aubakirov, Z. ParimbekAl-Farabi Kazakh National University (KAZAKHSTAN)
ERICA: An Empathetic Android Companion for Covid-19 Quarantine

Over the past year, research in various domains, including Natural Language Processing (NLP), has been accelerated to fight against the COVID-19 pandemic, yet such research has just started on dialogue systems. In this paper, we introduce an end-to-end dialogue system which aims to ease the isolation of people under self-quarantine. We conduct a control simulation experiment to assess the effects of the user interface, a web-based virtual agent called Nora vs. the android ERICA via a video call. The experimental results show that the android offers a more valuable user experience by giving the impression of being more empathetic and engaging in the conversation due to its nonverbal information, such as facial expressions and body gestures.
Quality Improvement by enhancing Informal Requirements with Design Thinking Methods

In the current software project, it is still very difficult to extract and define clear requirements in the requirement engineering. Informal requirements documents based on natural language can be interpreted in different meanings depending on the degree of understanding or maturity level of the requirements analyst. Also, Furthermore, as the project progresses, requirements continue to change from the customer. This change in requirements is a catastrophic failure from a management perspective in software projects. In the situation of frequent requirements changes, a current issue of requirements engineering area is how to make clear requirements with unclear and ambigous requirements. To solve this problem, we propose to extract and redefine clear requirements by incorporating Design Thinking methodologies into requirements engineering. We expect to have higher possibilities to improve software quality by redefining requirements that are ambiously and unclearly defined.
Perspectivas do profissional de arquivo sob o olhar das obras audiovisuais

The study aims to investigate the representation of the archival professional and his working environment in works in audiovisual format. It is characterized by a qualitative descriptive study, with content analysis techniques, where after literary review and contextualization of the topics covered, five national works were selected in the series format (a documentary and the rest characterized as works of fiction) launched between 2018 and 2020, and available on streaming platforms. The results present the description and reflection of what is represented on the scene with regard to the universe of archives and their professionals. Among the conclusions, it was noted that no represented character was characterized or identified as an archivist, either in dialogues or images. In general, the works conveyed the idea that the user himself can quickly and accurately locate the information he wants, without the guidance and assistance of a professional.
State-of-the-art bibliometric review of library research 2018-2020 in Scopus database / Muslim Ismail@Ahmad … [et al.]

Three years’ recent library research in eleven academic journals, Library Philosophy and Practice, Serials Librarian, Library Review, Journal of Library Administration, Journal of Academic Librarianship, Library Management, Library Hi Tech, Electronic Library, Library Trends, New Library World, and Reference Librarian were analyzed using bibliometric instrument to describe current research topics in library sciences. This research described state-of-the-art sciences and identified key research themes in library subjects. Total citations retrieved were 1,878 research data ranging from 2018 to 2020. Journals’ ranking in SCImago Journal Ranking and CiteScore were analyzed comparatively and research impact were evaluated by the number of citations received. Co-word analysis was used to extract significant key terms from data collection and citation network analysis identified key papers in respective themes. This research utilized VOSviewer software to visualize library research sciences.
Reinforcement Learning Based Load Balancing for Geographically Distributed Data centres

This paper proposes a method of migrating workload among geo-distributed data centres that are equipped withon-site renewable energy sources (RES), such as solar and windenergy, to decarbonise data centres. It aims to optimise the performance of such a system by introducing a tunable ReinforcementLearning (RL) based load-balancing algorithm that implements aNeural Network to intelligently migrate workload. By migratingworkload within the network of geo-distributed data centres,spatial variations in electricity price and intermittent RES canbe capitalised upon to enhance data centres’ operations. Theproposed algorithm is evaluated by running simulations usingreal-world data traces. It is found that the proposed algorithm isable to reduce costs by 6.1% whilst also increasing the utilisationof RES by 10.7%.
Red Dragon AI at TextGraphs 2021 Shared Task: Multi-Hop Inference Explanation Regeneration by Matching Expert Ratings

Creating explanations for answers to science questions is a challenging task that requires multi-hop inference over a large set of fact sentences. This year, to refocus the Textgraphs Shared Task on the problem of gathering relevant statements (rather than solely finding a single 'correct path'), the WorldTree dataset was augmented with expert ratings of 'relevance' of statements to each overall explanation. Our system, which achieved second place on the Shared Task leaderboard, combines initial statement retrieval; language models trained to predict the relevance scores; and ensembling of a number of the resulting rankings. Our code implementation is made available at https://github.com/mdda/worldtree_corpus/tree/textgraphs_2021
Performance Improvement of Classification Model with Imbalanced Dataset Classification models based on machine learning for the application of real life carry out classification tasks using real life dataset. Classification models have class imbalance pro

Classification models based on machine learning for the application of real life carry out classification tasks using real life dataset. Classification models have class imbalance problems when the dataset is imbalanced in nature. Classification models show biases for performing the classification towards the majority class due to class imbalance issues. The purpose of the study is to examine and control the class imbalance problem using the cluster centroid undersampling technique with the motive of improving the performance of machine learning classification. In order to accomplish the goal, this study performs experimental analysis for examining and controlling the class imbalance problem before and after applying the cluster centroid undersampling technique on imbalanced dataset. The experimental study is performed by using five different imbalanced datasets, cluster centroid undersampling technique and decision tree classification model. The results of this study are promising that supports this study and confirm that the class imbalance problem can be handled using undersampling techniques very effectively with performance improvement of a classifier from 11% to 67%. This study highlights the influences of class imbalance problems on machine learning classification models and experimental results with analysis provide an appropriate conclusion with an improvement in the performance of machine learning based classification models.
"LEARNING BY DOING" TRAINING - IMPLEMENTATION OF PROJECT SOLUTIONS IN THE EDUCATIONAL PROCESS OF BULGARIAN UNIVERSITIES

"LEARNING BY DOING" TRAINING - IMPLEMENTATION OF PROJECT SOLUTIONS IN THE EDUCATIONAL PROCESS OF BULGARIAN UNIVERSITIES
Application for Online College Voting System Using Android Device

Online voting system is used to vote online by the authenticated voters in order avoid any type of dummy voting. Proposed system allows user to vote online after signing in on the app. Authentication is provided by email ID as username and general registered number (GR No.) as password. OTP is sent to registered mobile no and then only user can vote. By using this application we can elect the college committee without any manual efforts. This system is more secure than the current manual system. Keywords: One Time Password (OTP), android devices, online college voting system, technology, mobile Cite this Article: Ojas Uday Deo, Omkar Vaiti, Shubham Kale, Rina Bora. Application for Online College Voting System Using Android Device. Recent Trends in Programming Languages. 2020; 7(2): 1–5p.
Strategic Implementation of Cloud Containers with Scheduling in the Locality Aware Decision Support System

Cloud stage is a sort of Internet-based measure that gives shared PCs change resources and data to PCs and various devices on interest. The fundamental general guideline is to balance the complex weight of containerized cloud organizations alongside numerous other significant highlights including application execution are disregarded. The current framework intends to improve today’s cloud administration by thinking about application execution for cutting edge compartment schedulers. More explicitly in this work gather and also separate another world view that think about both weight equity and application execution. In Contrast to past tests, the model tends to the issue between trouble equity and application execution as an improvement issue and afterward utilizes an adaptable procedure to address it adequately. The most testing part is that some sub problems are amazingly unpredictable. To actualize a framework model of the proposed planning technique for containerized cloud administrations. The proposed framework, with the limit layer which isn't actually a typical arrangement of Linux record structures, will give the centralized cloud performance evaluation of the system through strategic implementation of cloud container with scheduling in the locality aware decision support system.
ASSESSING THE BEHAVIOURAL COMPONENT OF COMPETENCES, PERSONAL QUALITIES AND PROFESSIONAL ABILITIES BY MEANS OF AN ELECTRONIC PORTFOLIO

T. Shaposhnikova, A. Gerashchenko , T. Tedoradze, M. Romanova, K. PopkoKuban State Technological University (RUSSIAN FEDERATION)
Analysis on the Influencing Factors of “Innovation and Entrepreneurship Education” Incorporating into the Construction of Higher Vocational Public English Teaching

As an important goal of talent cultivation, innovation and entrepreneurship can not only strengthen the effectiveness of higher vocational education, but also enable students to find a more suitable learning method while stimulating the sense of innovation, so as to achieve the goal of smooth employment in a subtle way. As an important basic course, public English is not only an important content to strengthen students’ language application ability, but also to a certain extent help students have a higher English literacy, making them a high-quality talent that the country needs. Starting from different educational perspectives, this article explores the main ways to carry out high-quality public English classes, hoping to strengthen the teaching effect and respect the law of student personality development while effectively enhancing students’ innovation and entrepreneurship capabilities.
PENGEMBANGAN BAHAN AJAR ECO GARBAGE ENZYME SEBAGAI MEDIA PEMBELAJARAN DI MASA PANDEMI COVID-19

This study aims to develop teaching materials for eco garbage enzymes as learning media. The product produced was teaching materials for making eco garbage enzymes of liquid organic fertilizer. The research model employed was the 4D model, which comprises four stages, but only the development stage used in this study. The instruments used in this study were validation sheets and questionnaires to measure the validity and practicality of the developed eco garbage enzyme products.Two experts validated the product then analyzed it on the Gregory test. The value obtained was 1, which means the product was valid and feasible to use. Based on product used observation, the practicality value showed 4,6 means the product had used as a whole. According to learning outcomes, the product effectivity was 78.25 % in the high to very high categories (completeness equal to 75%). In addition, the positive response from students was 94.09%, this indicates that the teaching materials are effective to use as learning media
Pengaruh Teknologi Informasi Dalam Pembelajaran Jarak Jauh Masa Pandemi Covid19 di STIE Nias Selatan

A decent house is a house that meets the building safety requirements and the minimum adequacy of the building area and the health of the occupants. Decision support system or Decision Support System (DSS) is a system that can help in making decisions in an organization or company by applying methods that are appropriate to the field of decision taken, conventional decision making without the help of SPK will result in an assessment that is not objective and not right. The AHP (Analytical Hierarchy Process) method of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is one of the multi-criteria decision making methods by applying weighting values ​​to each criterion. The choice of the TOPSIS method compared to other SPK methods is that this method uses the principle that the chosen alternative must have the shortest distance from the positive ideal solution and the farthest distance from the negative ideal solution. The system that was made allowed the South Nias Regency Settlers Office to determine aspects of the assessment based on criteria according to the needs of the Office so that it was more flexible. The decision support system using the AHP TOPSIS method is expected to help in the selection of decent home subsidies.
REMOTE LEARNING EXPERIENCES WITH INTRODUCTORY MOBILE APPLICATION DEVELOPMENT COURSE

After years of providing an introductory mobile app development course for our undergraduate bachelor students in electrical engineering, during the Covid-19 outbreak and lockdown, we had to offer the same course as a remote e-learning course. It was our intention to cover all the topics of the standard course and to, somehow, carry out both the lectures and practical computer labs. While the lectures could be mostly performed as one-way, less-interactive remote learning, for computer labs we had to choose a solution allowing two-way interaction as well as mechanisms for students to present their current work.This paper describes the approach used for performing our course in remote learning mode. Synchronous lectures, as well as asynchronous recordings of those lectures, are shown as an example. Details and a list of useful tools used for remote two-way computer lab teaching are also given. Some remarks relating to (also online/remote learning) student exams are included, together with our subjective view related to the achieved students' results. In our opinion, it can be concluded that remote learning can be used for those kinds of courses, but, as it is presented in the paper, there were some time-related issues that resulted in some minor decrease of course scope, meaning that all the topics planned were not completely covered.
Using Project Based Learning (PBL) Program Integrated with Information Technology (IT) in Developing Secondary School Students' Reading Skills.

Learning Program integrated with Information Technology in developing reading skills of first year secondary school students. The Participants were sixty students. They were randomly assigned to a treatment group and a control group (30 students each). The instruments of the study included a checklist of Reading sub- skills and a test on Reading skills. The treatment group was taught using Project Based Learning Program integrated with Information Technology  while the control group was taught following the plan of the Ministry of Education in Egypt. The participants were pre - and – post tested. The program was administered in the first term of the academic year 2020/2021. Results revealed that Project Based Learning Program integrated with Information Technology had positive results. Recommendations and suggestions for further research were presented.
AI CAMPUS – CO-CREATING INSTRUCTIONAL DESIGN STANDARDS FOR AN OPEN AI LEARNING ECOSYSTEM

Appears in: EDULEARN21 Proceedings Publication year: 2021Page: 8373 (abstract only)ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.1693Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference
Language Grounding with 3D Objects

Seemingly simple natural language requests to a robot are generally underspecified, for example "Can you bring me the wireless mouse?" Flat images of candidate mice may not provide the discriminative information needed for "wireless." The world, and objects in it, are not flat images but complex 3D shapes. If a human requests an object based on any of its basic properties, such as color, shape, or texture, robots should perform the necessary exploration to accomplish the task. In particular, while substantial effort and progress has been made on understanding explicitly visual attributes like color and category, comparatively little progress has been made on understanding language about shapes and contours. In this work, we introduce a novel reasoning task that targets both visual and non-visual language about 3D objects. Our new benchmark, ShapeNet Annotated with Referring Expressions (SNARE) requires a model to choose which of two objects is being referenced by a natural language description. We introduce several CLIP-based models for distinguishing objects and demonstrate that while recent advances in jointly modeling vision and language are useful for robotic language understanding, it is still the case that these image-based models are weaker at understanding the 3D nature of objects -- properties which play a key role in manipulation. We find that adding view estimation to language grounding models improves accuracy on both SNARE and when identifying objects referred to in language on a robot platform, but note that a large gap remains between these models and human performance.
Modeling Text using the Continuous Space Topic Model with Pre-Trained Word Embeddings

In this study, we propose a model that extends the continuous space topic model (CSTM), which flexibly controls word probability in a document, using pre-trained word embeddings.To develop the proposed model, we pre-train word embeddings, which capture the semantics of words and plug them into the CSTM.Intrinsic experimental results show that the proposed model exhibits a superior performance over the CSTM in terms of perplexity and convergence speed.Furthermore, extrinsic experimental results show that the proposed model is useful for a document classification task when compared with the baseline model.We qualitatively show that the latent coordinates obtained by training the proposed model are better than those of the baseline model.
Blockchain based Land Registry and Land Transformation system using Ethereum Blockchain

Land Registry is a simple Dapp based on the ethereum blockchain. It can be used as an alternative to the existing approach. Here the land owner registers the land details along with the land value by providing necessary proofs. Only a registrar or government authority who is registered as the superadmin can do the registration process. Lands coming under a particular area (eg. a village) can register to the system only through the superadmin assigned to that area. The smart contract has been written in such a way that the owner has to transfer his full asset to the buyer and no partial transaction of the asset is allowed. Even though the registration process requires a government authority, the entire process is transparent and the transaction happens between the two clients without any intermediaries.
Multi-Label Image Classification with Contrastive Learning

Recently, as an effective way of learning latent representations, contrastive learning has been increasingly popular and successful in various domains. The success of constrastive learning in single-label classifications motivates us to leverage this learning framework to enhance distinctiveness for better performance in multi-label image classification. In this paper, we show that a direct application of contrastive learning can hardly improve in multi-label cases. Accordingly, we propose a novel framework for multi-label classification with contrastive learning in a fully supervised setting, which learns multiple representations of an image under the context of different labels. This facilities a simple yet intuitive adaption of contrastive learning into our model to boost its performance in multi-label image classification. Extensive experiments on two benchmark datasets show that the proposed framework achieves state-of-the-art performance in the comparison with the advanced methods in multi-label classification.
EMBEDDING SUSTAINABILITY AND AGILE MANAGEMENT IN AN ONLINE PROJECT-BASED LEARNING SEMESTER

Appears in: EDULEARN21 Proceedings Publication year: 2021Pages: 195-203ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.0073Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference
중국 초·중등학교 인공지능 교육정책 분석

This study aimed to analyze artificial intelligence (AI) education policies of elementary and secondary schools in China and find implications for Korea. This study adopted the four dimensions of policy theory by Cooper for the analysis and the results are as follows. China is emphasizing the implementation of AI education in elementary and secondary schools by setting long-term policies. Also, with the impact of AI education policies, the revision of the curriculum for AI education in secondary schools, publishing AI textbooks, close cooperation with various stakeholders were found as features. Despite the performance of AI education in primary and secondary schools in China, there existed challenges such as the absence of a comprehensive AI education curriculum and textbooks, lack of AI competency of teachers, leakage of personal information, and invasion of privacy. Based on the results, the implications for Korea are as follows: establishing long-term policies, cooperative relationships with various organizations, and preparing comprehensive curricula.
The Effect of Problem-Posing Learning Method on Students Achievement in Reading Invitation Letter

The aims of this research is to know if there is a significant effect of problem-posing learning method on students’ achievement in reading invitation text of the twelfth grade students of SMA Negeri 1 Sipirok. The population is the twelfth grade students of SMA Negeri 1 Sipirok, which is consist of 190 students. Then, the sample is taken from the population by cluster random sampling technique and the total sample is 79 students. The writer uses experimental method. After calculating the data, it is found that the mean score of students reading invitation letter before taught by Problem Posing learning method is 68; it is categorized “enough”. While the mean score of students reading invitation letter after taught by Problem Posing learning method is 79, it is categorized “good”. After finding the score of ttest and ttable, both of the scores are compared. It is found that ttest is higher than ttable (ttest &gt; ttable = 15.71 &gt; 2.04). It means there is significant effect of Problem Posing learning method on reading invitation letter of the Twelfth grade students of SMA Negeri 1 Sipirok. So, the hypothesis in this research can be accepted