Reviewerly/exHarmony huggingface dataset:
Development of the Interactive Multimedia Software “Inquiry Play-Room” as an Electronic Learning Resource for Rotation and Equilibrium Topic

This study reports the development of the interactive electronic multimedia “Inquiry Play-Room” for use in rotation and equilibrium topics. This was designed following the steps of a guided inquiry laboratory model, containing video problems, feedback, virtual laboratories, student worksheets, animations, practical applications, and quizzes. The tests are offered at two levels, one to grasp the concept and the second to be incorporated into actual life. This difference in learning can spur student confidence that will allow them to concentrate. The teacher can also enhance the content quality and patterns of movement through classes and online learning, as this technology is designed for face-to-face use. This interactive media is developed using the SWiSHMax framework and the ActionScript 2.0 programming language. The architecture of this media production model follows these steps: 1) analysis, 2) design, 3) development, 4) implementation, and 5) evaluation. At a 90.3 percent positive rate, the expert testing results indicate feasibility. The results of 27 students showed that the students responded positively to multimedia design. Therefore, the use of interactive multimedia was shown to be possible. The results of this study open avenues for digital creation in other fields of physics
Development of Drone Mounted BLDC Motor Stator using Multi Stacked Structure of Cartridge

Received:11 november 2020; Accepted: 27 December 2020; Published online: 05 April 2021&#x0D; Abstract: Drones are used in agriculture and external control, utilizing cameras, various sensors, and autonomous flight functions. However, it is difficult to fly for a long time because of flying with heavy equipment. Therefore, it is necessary to increase the flight time through lightening of the drone itself and efficient control of the BLDC motor. That is, it is necessary to improve the motor itself, which accounts for most of the energy consumption in drone flight. Stator fabrication of existing BLDC motors is done by winding copper wires through individual processes on the stator core through an automated process. However, in the case of an ultra-small BLDC motor, the stator core has a small size and is manufactured using a thin-diameter copper conductor, and thus has a lot of problems in the automation process. Therefore, in this paper, the multi-division coupling structure method of individual teeth of the stator was applied through a new type of BLDC motor stator design. That is, the cartridge type BLDC motor stator was applied to improve and reduce the BLDC motor stator method. Through this, the performance limit of the BLDC motor was improved by combining individual teeth with multiple cartridges. The cartridge type BLDC motor is manufactured by stacking several cartridges on each tooth. Therefore, various performances can be produced according to the connection state of the cartridges
A progressive sampling framework for clustering

Clustering algorithms become more and more sophisticated to cope with large data sets of increasing complexity. Sampling selection methods are likely to provide an interesting alternative as they can reduce memory requirements, and reduce execution time. Many sampling algorithms for clustering are efficient but they each have their own limitations with large data sets. In this paper, we introduce a sampling framework for clustering algorithms that inherits from both progressive sampling and stratification concepts. Driven by two parameters, the iterative process consists in managing representatives of independent strata that carry similar statistical information regarding the clustering objective. At each iteration, the candidate representatives of the incoming stratum are examined. The interesting feature of the framework stems from the idea of selecting new representatives of the incoming stratum only if they improve the representation quality of the already selected set of samples. The algorithm stops when new representatives are no longer needed, which is likely to happen without examining the whole data set. The tests conducted on synthetic and real world datasets proved that the progressive sampling framework yielded similar results to the sampling algorithm applied to the whole set in a low computational time. In comparison with progressive sampling techniques, using the proposed framework enables smaller sampling sets to be used without loss of accuracy.
Distance Learning Solutions: Tools Used in Online Lessons

The goals of distance education in higher institutions were clear for many years. Nowadays, owing to the global pandemic situation, higher educational institutions (HEI) have had to transition from conventional teaching modes to online modes. Although many top-ranked universities were prepared for this situation, others suffered, since their distance education department existed only in name; their activities were passive. However, COVID-19 provided an opportunity for them to think deeply about their next steps.&#x0D; In general, distance learning is an effective way of attracting adult learners. Furthermore, these learners desire a higher level of flexibility.&#x0D; This article is based on the theoretical models essential to long-term plausibility and viability in the field of teaching practice. To evaluate the challenges and problems arising during online learning, the author has briefly reviewed all the contributions made to this field in the 21st century.&#x0D; In addition, the paper suggests tools and facilities for teachers and instructors in order to facilitate effective communication between teachers and students, both in and out of the virtual classroom. Researchers, post-graduate students and other readers will be able to use this paper to explore and exploit further modifications of research opportunities in this field.
Non-Functional Requirement Detection Using Machine Learning and Natural Language Processing

A key aspect of software quality is when the software has been operated functionally and meets user needs. A primary concern with non-functional requirements is that they always being neglected because their information is hidden in the documents. NFR is a tacit knowledge about the system and as a human, a user usually hardly know how to describe NFR. Hence, affect the NFR to be absent during the elicitation process. The software engineer has to act proactively to demand the software quality criteria from the user so the objective of requirements can be achieved. In order to overcome these problems, we use machine learning to detect the indicator term of NFR in textual requirements so we can remind the software engineer to elicit the missing NFR.We developed a prototype tool to support our approach to classify the textual requirements and using supervised machine learning algorithms. Survey wasdone toevaluate theeffectiveness of the prototype tool in detecting the NFR.
A Study on Determinants of Customer Satisfaction in E-enabled Bus Booking Platforms

E-enabled ventures (especially the online bus booking services) have witnessed impressive growth in India during last decade. Especially after COVID-19, customer shift towards online services is expected to augment. This paper is an attempt to develop a scale for determinants of customer satisfaction amongst the existing users of online bus booking (e-enabled platform). Using e-SERVQUAL model by Parasuraman et al. (2005), a draft instrument was designed. Since online bus services also includes physical experience of services offered, Tangibility factor was added in the construct. The questionnaire was tested on a sample of existing users of online bus booking services (n=105). &#x0D; After checking for the adequate reliability score, Exploratory factor Analysis (EFA) was performed. It resulted into extraction of four factors such as Contact, Fulfilment, Privacy and Responsiveness, accounting for 50.5% of total variance explained. Validating this scale on a larger sample for generalisation of the results would be the future agenda of research. Development of India specific scale for e-enabled business models in public transports can be considered as one of the major contribution of this study.
The Chinese Remainder Theorem for Compact, Task-Precise, Efficient and Secure Word Embeddings

The growing availability of powerful mobile devices and other edge devices, together with increasing regulatory and security concerns about the exchange of personal information across networks of these devices has challenged the Computational Linguistics community to develop methods that are at once fast, space-efficient, accurate and amenable to secure encoding schemes such as homomorphic encryption.Inspired by recent work that restricts floating point precision to speed up neural network training in hardware-based SIMD, we have developed a method for compressing word vector embeddings into integers using the Chinese Reminder Theorem that speeds up addition by up to 48.27% and at the same time compresses GloVe word embedding libraries by up to 25.86%.We explore the practicality of this simple approach by investigating the trade-off between precision and performance in two NLP tasks: compositional semantic relatedness and opinion target sentiment classification.We find that in both tasks, lowering floating point number precision results in negligible changes to performance.
USE OF MOBILE APPLICATIONS IN THE LEARNING PROCESS

Nowadays the interest in integrating mobile applications into the learning process is increasing rapidly, so we need such teaching methods that will facilitate and accelerate the transmission of knowledge to students, intensify the process of learning, teach them techniques for independent work with material, increase productivity of learning and teacher's work. Such teaching methods can be implemented through the use of mobile information technology in education. Mobile technology can make the learning process more interesting, meeting today's requirements, providing the right information at the right time.&#x0D; The article considers the concept of "mobile learning", analyzes the features and directions of its use in modern education. It is noted that the use of mobile electronic devices and applications in higher mathematics allows you to check quickly the solution, to draw the chart in a few minutes as well as to apply them to distance learning, which greatly facilitates and accelerates knowledge, increases students' productivity and independent work. It is also noted that despite the widespread use and availability of mobile phones among students, mobile learning is not widespread in native universities. The didactic principles to which mobile applications should correspond are defined, and also the attention to the basic advantages and disadvantages of the use of mobile applications in learning process of higher mathematics is paid.
Blockchain enabled technology platform for enhancing supply chain financing for SME’s

After the development and inception of cryptocurrencies, Blockchain has found much usefulness in many domains. The Blockchain technology offers several advantages like decentralization, traceability, anonymity, cryptography, collective maintenance and immutability. The possible disruption and prospective capabilities of the Blockchain technology has been extensively utilized in the Finance domain. There has been extensive exploration on the integration and application of Blockchain technology in the domain of supply chain and supply chain finance as well. But, a detail framework of application is seldom mentioned. In this research, we have studied and analyzed the possible synchronization between Blockchain technology and supply chain finance. This study also presents a conceptual framework based on Blockchain technology to enhance the efficiency of supply chain financing for small and medium scale enterprises. Finally, this study proposes three supply chain finance models and their operation processes on a Blockchain Platform.&#x0D;
The System of Monitoring the Success of Training in the Formation of Technical Competencies of Students of Technical Specialties

In connection with modern requirements for education in the undergraduate system, there is a need to ensure the adequacy of the requirements of life and the content of education, including educational technology. This is especially important now in the context of the need to form competencies aimed at bridging the gap between learning outcomes and modern practice requirements. In this regard, training technologies are required that are focused on the participation of individuals in the educational process and contribute to the integration of future specialists in society. In this study, our efforts were aimed at creating and implementing in the educational process of the technical university conditions for mutual adaptation of the student and the learning environment – the infosphere. Filling the learning environ- ment with specific subject content is one of the most important tasks of educators. In this paper we analyze the quality aspects of educational process and methodological system, forming technical com- petences. We present the developed system of a midterm control as a part of pedagogical control. Our research shows that the midterm control is an effective tool for raising the quality of education especially in conditions when the amount of student’s independent work is increasing. Key words: infosphere, technical competencies, bachelor, midterm control, university education.
Small Network for Lightweight Task in Computer Vision: A Pruning Method Based on Feature Representation

Many current convolutional neural networks are hard to meet the practical application requirement because of the enormous network parameters. For accelerating the inference speed of networks, more and more attention has been paid to network compression. Network pruning is one of the most efficient and simplest ways to compress and speed up the networks. In this paper, a pruning algorithm for the lightweight task is proposed, and a pruning strategy based on feature representation is investigated. Different from other pruning approaches, the proposed strategy is guided by the practical task and eliminates the irrelevant filters in the network. After pruning, the network is compacted to a smaller size and is easy to recover accuracy with fine-tuning. The performance of the proposed pruning algorithm is validated on the acknowledged image datasets, and the experimental results prove that the proposed algorithm is more suitable to prune the irrelevant filters for the fine-tuning dataset.
Acquiring a Formality-Informed Lexical Resource for Style Analysis

To track different levels of formality in written discourse, we introduce a novel type of lexicon for the German language, with entries ordered by their degree of (in)formality.We start with a set of words extracted from traditional lexicographic resources, extend it by sentence-based similarity computations, and let crowdworkers assess the enlarged set of lexical items on a continuous informal-formal scale as a gold standard for evaluation.We submit this lexicon to an intrinsic evaluation related to the best regression models and their effect on predicting formality scores and complement our investigation by an extrinsic evaluation of formality on a German-language email corpus.
Design Rules Application in Manufacturing Industries: A State of the Art Survey and Proposal of a Context-Aware Approach

Abstract [Context] In manufacturing industries, the design of a product needs to comply with many design rules. These rules are essentials as they help industrial designers to create high quality design in an efficient way. [Problem] However, the management of an ever-increasing number of design rules becomes a real problem, especially for new designers. Even if there exists some knowledge management tools for design rules, their capabilities are still limited and many companies continue to store their design rules in unstructured documents. Nowadays, design rule application is still a difficult task that needs a circular validation process between many expert services in a manufacturing company. [Proposition] In this paper, we will analyze the main existing approaches for design rules application from which we will demonstrate the need of a new approach to improve the current state-of-the-art practices. To minimize rule application impact on the design process, we propose to develop a Context-Aware Design Assistant that will perform design rule recommendation on the fly while designing using computer-aided technologies. Our Design Assistant relies on the modelling of the design rules and the design context in a single knowledge graph that can fuel a recommendation engine. [Future Work] In future work, we will describe the technical structure of the Context-Aware Design Assistant and develop it. The potential outcome of this research are: a better workflow integration of design rules application, a proactive verification of design solutions, a continuous learning of design rules, the detection and automation of design routines.
DRUG AND SUBSTANCE ABUSE PROBLEM BY THE ZIMBABWEAN YOUTH: A PSYCHOLOGICAL PERSPECTIVE

Drug abuse has become a problem among youths in Zimbabwe, so dire is the situation that more than half of the youths’ population, approximately 57% in Zimbabwe are involved in drug abuse. The statistics on youth drug abuse in Zimbabwe increase yearly despite measures implemented by various stakeholders to fight the pandemic. The study seeks to understand the problem of drug abuse within the Zimbabwean context from a psychological perspective. The current study takes a desk research approach to understand the problem of drug abuse by the youth in Zimbabwe. The study unearths the most affected age group by drug abuse, the causes of drug abuse, the types of drug abuse and the effects of drug abuse to that age group. The study reviewed relevant literature, using key terms in the study, which are youth, drug abuse and problem. Literature was systematically categorised into categories of causes of drug abuse, types of drug abuse and the effects of drug abuse among the youth. Findings from the study are that, the youth are the most affected age group by drug abuse in Zimbabwe and the problem stems from lack of self-control and negative self-concept on the youth drug abusers. The study also established that cannabis is the most abused drug in Zimbabwe and that the problem of drug abuse has negative effects to the drug abuser, family, community and nation at large. The current study recommends for future studies to establish intervention programs in Zimbabwe that aim to enhance self-control and self-concept in youth drug abusers.
POSITIVE POLITENESS IN “OPRAH’S 2020 VISION TOUR” HOW REASONS AND FACTORS INFLUENCED THE CHOOSING OF STRATEGY

Politeness can be said to be very sensitive interpersonal act carried out by someone in the form of a threat of the acting politely or not. Positive politeness influence greatly influence the attitudes and behaviors carried out by someone. Attitudes and behaviors in positive politeness are reflection of a person’s character to be good or not to others. The aimed of this research is to give an example in order to prioritize using positive politeness when speaking in any situation, including talk shows. The data were taken from the utterances in every conversation that Oprah Winfrey said with her guests. Conversation data is transcribed into written data. And analyzed qualitatively based on conversations between Oprah Winfrey and her guests Michelle Obama in Oprah’s 2020 Vision Tour Talk Show. The positive politeness strategy aims to minimize the distance between Oprah Winfrey and her guests which is expected to create a sense of comfort when talking on the talk show. There are 8 strategies found in this data that categorized as positive politeness, they are: Exaggerate (interest, approval, sympathy with hearer), intensify interest to the hearer, seek agreement (to find and try to approval by the opponent said), avoid disagreement, presuppose/rise/assert common ground, joke (make a joke), be optimistic, include both the speaker and the hearer in the activity, and give (or ask for) reason. This research also founds that payoff and circumstances become factor on why the speaker use certain positive politeness strategy. Circumstances which are found in this research are relative power and social distance.
Evaluation of Students Performance using Fuzzy Set Theory in Online Learning of Islamic Finance Course

&lt;p class="0abstract"&gt;&lt;strong&gt;Abstract—&lt;/strong&gt;The objective of this study is to evaluate student performance using fuzzy set theory in Islamic Finance online course. This study focuses on selecting best individual among 30 students that registered for Islamic Bank Management course. The variables that involved in this study are online quiz marks, online assignment marks and online self-learning time. The outcome of the fuzzy set analysis was compared with final examination data. The methodology of this study involving converting real data to fuzzy set, intersection calculation, decision analysis using maximizing approach. Result of fuzzy set shows the best individual score is 0.9. This student selected as best candidate for student performance in online learning with considering three variables namely online quizzes, online assignment and online self-learning hour. The comparison with final examination marks shows a good agreement with fuzzy set theory that concluded best individual from fuzzy set theory exhibits highest performance during final examination. The main finding of this study can help educators to predict the best performer in online learning class. In the same time, finding of this study can act as guideline to advise students in achieving their desired grade for online learning course.&lt;/p&gt;
Paraphrasing Chinese Idioms: Paraphrase Acquisition, Rewording and Scoring

Paraphrasing is a process to restate the meaning of a text or a passage using different words in the same language to give a clearer understanding of the original sentence to the readers. Paraphrasing is important in many natural language processing tasks such as plagiarism detection, information retrieval, and machine translation. In this article, we describe our work in paraphrasing Chinese idioms by using the definitions from dictionaries. The definitions of the idioms will be reworded and then scored to find the best paraphrase candidates to be used for the given context. With the proposed approach to paraphrase Chinse idioms in sentences, the BLEU was 75.69%, compared to the baseline approach that was 66.34%.