Reviewerly/exHarmony huggingface dataset:
Using WhatsAppbased mobile learning environments during abrupt switches to online learning: A duoethnographic account

Abrupt switches to online learning without face-to-face contact between facilitators and students can cause distress and have a negative impact on student success. As students use instant messaging applications (IMAs) to communicate with one another, we have integrated WhatsApp-based mobile learning environments (MLEs) in two disparate higher education settings to facilitate learning. Christa used an MLE pre-pandemic in a postgraduate distance education context, while Liezel used several MLEs during the pandemic in an undergraduate contact education context. In this duoethnographic1 account, we share our stories about using these MLEs during times of distress. Duoethnography is a collaborative methodology that allowed us to juxtapose our life histories to create multiple understandings of the phenomenon to learn from one another. With currere as theoretical framework, we employed storytelling to compare our life histories, educational contexts and beliefs while we illustrate a sense of personal change. In addition to sharing our insights regarding the affordances and challenges related to WhatsApp-based MLEs, we illustrate how this dialogic methodology facilitated dialogue and reflection – affording two educational researchers in disparate higher education contexts deeper insights regarding their own practices.
-Te iru in L2 Japanese in an L1 Romanian Setting. A Pilot Study

This paper investigates the learning of the Japanese aspect marker -te iru by native speakers of Romanian.The results of a pilot study based on a comprehension task show that intermediate learners of L2 Japanese with L1 Romanian interpret -te iru target-like, with one exception: the habitual interpretation, especially with activities.Non-facilitative transfer effects are found mainly in the activities condition, where no clear distinction is made between the progressive and the habitual values of the -te iru predicates.I argue that the higher percentage of habitual responses given by the L2 learners is indicative of L1 transfer.In spite of the fact that L1 Romanian lacks an overt marker of the progressive, the acquisition of the -te iru marker in L2 Japanese is affected by transfer from the native language.The results also reveal that intermediate learners have acquired the resultative value of -te iru, in support of the view that it is easier to learn a property that is absent in L1.
FORMATION OF ENVIRONMENTAL SAFETY IN PROFESSIONAL TRAINING OF FUTURE TEACHERS IN THE STUDY OF DISCIPLINES THE NATURAL SCIENCE CYCLE

The problem of environmental safety can now be attributed to the most pressing educational problems, since the professional activity of a person is closely related to economic activity. In this regard, there is a lack of attention of specialists to the ecological situation of the environment, its safety. The problems of environmental safety have always existed, however, it is in the modern world that they have become the focus of attention of the world community, because. the existing threat to the security of mankind is associated with its thoughtless attitude to environmental problems, to its own security. The article discusses the topical issues of the formation of environmental safety in the professional training of future teachers in the study of disciplines of the natural science cycle. The authors have identified the key aspects of this problem and proposed effective methods and forms of education that allow future teachers to form a deep understanding of environmental problems and competencies in the field of environmental safety. The article also discusses the possibilities of using the author's program «Fundamentals of Ecological Safety» to solve this problem. The results of the study can be useful for teachers of higher education and secondary schools involved in the professional training of future teachers.
Preliminary investigation of a CFD-assisted virtual reality experience in engineering education

Virtual reality has become a significant asset to diversify tools in the support of engineering education and training. The cognitive and behavioral advantages of virtual reality (VR) can help lecturers reduce entry barriers to concepts that students struggle with. Computational fluid dynamics (CFD) simulations are imperative tools intensively utilized in the design and analysis of chemical engineering problems. Although CFD simulation tools can be directly applied in engineering education, they bring several challenges in the implementation and operation for both students and lecturers. In this study, to tackle these challenges, we developed the “Virtual Garage” as a taskcentered educational VR application with CFD simulations. The Virtual Garage is composed of a holistic immersive experience to educate students through a real-life engineering problem solved with CFD simulation data using a VR headset. The prototype is tested by graduate students (n=24). Participants assessed usability, user experience, task load and cybersickness via standard questionnaires together with self-reported questions and a semi-structured interview. Preliminary results reflect that the Virtual Garage is well-received by participants. We identify features that can further enhance the usability and user experience.
Implementation of Sequential Pattern Neural Classifier in E-Commerce Data Behavioral Characteristic Extraction

Objectives: To present a framework for sequential pattern analysis using deep learning with behavioral characteristic extraction.This work intends to address the two major problems of accuracy and false positives predictions due to higher self-similarity in historical clicks.Methods: It implements sequenceaware recommenders for product recommendation using hybrid historical sequential pattern recommendation system (HSPRec) and hybrid sequential pattern based neural (HSPN) algorithm to take advantage of this crucial attribute.Data is gathered from Amazon, Flipkart, and other e-commerce sites.The simulation is carried out in Matlab.Findings: The proposed deep learning model provides 98% accuracy across 46 epochs, which is at least 8% higher, compared to existing works.The false positives in proposed solution are at least 6% lower compared to existing works.Novelty: The accuracy attained in recognizing consumer sequential patterns using HSPN is 95% and 98%, respectively.The computational effectiveness and viability of the neural network algorithm have been shown via our testing of the method.
HiTEK Pre-processing for Speech and Text: NLP

Objective: To develop a system that accepts a sentence consisting of two and/or four languages and convert it to a target language text, termed as Cross Language Speech Identification and Text Translation System.Methods: A combinatorial model consisting of Hidden Markov Model, Artificial Neural Networks, Deep Neural Networks and Gaussian Mixture Model are utilized for direct and indirect speech mapping.Trained dataset consisting of thousand phonemes for each of the Hindi, Telugu, English and Kannada languages, initially for bank, hospital domains, later the grammatical phonemes of each language were added and wave files consisting of cross lingual spoken sentence were created which incurred a six months period to build from scratch, as cross lingual vocal data-set is not available.Hindi language dataset Shabdanjali was also referred.The basic parameters considered for creation of structured dataset are loudness, pause, pitch, tone, noise cancellation, sampling frequency, threshold etc. Findings: Comparative analysis of various techniques, target languages and features are tabulated.Research idea emerged from the comparative analysis of Monolingual Systems where there was a gap for cross lingual speech to text translation.The architecture can be enhanced in future for other regional languages of India.Novelty: A new bench mark for Cross Language dataset was created.This work presents CLSITT tool applicable in transforming public speeches spoken in multiple languages to a selected target language and the tool is helpful for a regional news editor, rural and agricultural activities, medical applications, defence and so on.
Pembuatan Ragum Mini Bagian Rahang Tetap dengan Metode Pengecoran Logam sebagai Cinderamata

Mini vise is a tool to hold a relatively small object. Mini vise also have another function as a souvenirs. This design purpose is to design the mold of mini vise which is simple and effective. Doing the calculation in the procces of making the fix component of the mini vise and doing analysis the effect of mold slope in the procces of casting. The mold material is mildsteel and the case material is aluminium. There are 3 mold for fix component with different inclination angle which are 1̊, 2̊, 3̊. The best cast result is the mold with 3̊ angle. And can be concluded that bigger angle make the take out procces of the result easier.
Gamification in Higher Education: an educational trend with digital needs

The last decade has shown the potential and limitations that Information and Communication Technologies (ICTs) represent in society. During these years it has been possible to appreciate the birth and development of devices whose incorporation into the daily routine has been almost immediate. Some of the most relevant cases are laptops and smartphones, media that have significantly altered the human paradigm. Its presence has meant the origin of new habits and the adaptation of others towards digital terrain, alternating face-to-face and virtual. The impact and repercussions can be observed in numerous areas, however, education is one of the most cohesive with these new ways of living. Gamification is one of the didactic strategies that are most closely linked with ICTs, an interaction that is conceived as natural as it is the translation of a methodology towards tools with resources that can be unlimited and asynchronous. However, as always happens when technology is incorporated into the educational field, these new teaching-learning paths require new ap-proaches and reflections on the needs they demand. It is in the case of Higher Education that its implementation must involve an analysis of the past, present, and future in order to favor the true personal development of those who make up the process: teachers and students.
Komparasi Algoritma Naïve Bayes Dan Support Vector Machine (SVM) Pada Analisis Sentimen Spotify

The Spotify app is a subject of interest to social networking communities with significant disagreements or sentiments. Sentiment Analysis is a solution to automatically categorize opinions or ratings into negative or positive opinions. The techniques used in this research are Support Vector Machines (SVM) and Naïve Baye. The advantages of Naïve Bayes are simple, fast and high accuracy. SVM, on the other hand, can identify different hyperplanes that maximize the margin between two different classes. The classification results of this study have two category labels, namely negative and positive. The resulting accuracy value indicates the best test model for sentiment classification cases. Accuracy is measured by the confusion matrix and the results show that the accuracy value of the SVM algorithm is 84% while the accuracy value of the Naïve Bayes algorithm is higher than SVM which is 86.4%.
Mobile App Prototype for Course Management in Secondary Education

In the last decade, mobile applications have shown an expansion to a great diversity of uses that can be made, which has influenced at different levels (economic, cultural, political), as in the area of learning where it has played a very important role in learning, since now with the development of technologies, children and adolescents are very interested in these new technologies and it is easier for them to use them, which also supports them in learning a great diversity of subjects of their own interest. That is why in this work a prototype of a mobile application for the management of mobile education using the Scrum methodology at the Norbert Wiener University of Lima-Peru, knowing that there are learning problems in students in the classroom, for this, want to provide a mobile application that supports the student to improve their learning. As a result, obtained from the study, was a prototype of a mobile application to improve learning in the Monte Carmelo private school in Lima-Peru, where a virtual model of the mobile application is shown, register the user, login where you can view their classes and share their class assignments, facilitating the user to enter their class and study material, this was achieved using balsamiq, the Scrum methodology with its four phases. The results of the survey conducted to the experts show that in most of the questions they gave a high scale, with the highest average of 4.91 with a standard deviation of 0.302 and only one low scale obtained of 1.45 on average with a standard deviation of 0.52.
Text Mining dan Klasifikasi Sentimen Berbasis Naïve Bayes Pada Opini Masyarakat terhadap Makanan Tradisional

Indonesia has several famous traditional foods and is available in some cities. In addition, several international foods also are interesting to Indonesian. This article analyzes the netizen sentiment for these food categories where the data source is Twitter. The foods are rendang, sate, gudeg, pizza, hamburger, and spaghetti. The text mining approach is adopted to process data. The research steps are data crawling, cleaning, filtering, translating, and splitting. Furthermore, the classifier model based on the Naïve Bayes algorithm is developed. The analysis result shows that the gudeg food reaches a high percentage of positive sentiment with 57,9. Then, the high rate of negative sentiment is achieved by the rendang food with 21,9 %. Moreover, hamburger food obtains a high percentage of neutral sentiment. Meanwhile, the evaluation of classifier model performance shows that the model with the hamburger dataset achieves a high score for accuracy, precision, and recall parameters with 0.72, 0.72, and 0.68 sequentially.
Effects of WhatsApp Based Lessons on Undergraduates’ Writing Accuracy

Despite the building up of research on the adoption of social media tools in teaching and learning of English especially writing, the differential effects of WhatsApp blended lessons on undergraduates writing accuracy remain unclear. Thus, this study fills in the lacuna by examining how WhatsApp affects undergraduates’ overall writing accuracy. Using a quasi-experimental design, the findings of this mixed method study demonstrate the potentials of WhatsApp in improving students’ writing accuracy. The results were primarily attributed to the ability of WhatsApp to promote interactive and collaborative learning environment which is helpful in learning writing. Nonetheless, some challenges were reported, such as overcorrections and bombardment of text messages. Implications for writing pedagogy and future studies have been discussed.
The Use of Augmented Reality Flashcard in Enriching Students’ vocabulary

The objective of the research is to find out whether or not the Augmented Reality Flashcard can enrich the young learners’ vocabulary. This study is a pre-experimental study with a population of RA. Perwanida 1 Lipu for the 2020/2021 academic year, with a total population of 64 young learners. The sample of this study was group 1 from class B RA Perwanida 1 Lipu, consists of 22 young learners. The instrument used in this study was a vocabulary test. The researcher was giving a pre-test and post-test in the form of an objective test, namely multiple choice. This research used descriptive statistics to analyze the data. Descriptive statistics used in this research include summation, average, standard deviation, and frequency table. The results of this study indicate that the use of Augmented Reality teaching media has a positive impact on enriching students' vocabulary. It was proven from the increase in student scores from the pre-test to the post- test with the average value during the pre-test was 3.02 and the average value after the post-test was 6.02. So, it can be concluded that Augmented Reality flashcard media has an effect in increasing the students' vocabulary.
Data Hiding In Audio File

In the prevalence of digital communication, data transmission through computer networks has become commonplace.However, the security of these transmissions is often overlooked, which can result in private messages being exposed.To address this issue, data hiding has been introduced as a method to embed messages a header, like the top of an audio file, before, before transmission, with the recipient extracting the message upon receipt.However, there are still challenges regarding size and quality of the message of the resulting stego data.This paper focuses on addressing these challenges by considering factors such as well as processes for lowering, smoothing, and embedding.The audio signal is discretized and interpolated to provide space for hiding the message.To mitigate the potential drop in quality of the stego audio, There are steps for smoothing and decreasing.According to experimental findings, this strategy can enhance stego quality while preserving the designated payload capacity, with a minimum increase in PSNR value of 10 dB depending on the payload size and techniques.
The Implementation of English Teaching Learning Process For Young Learnes In TK Harapan, Semampir Distric, Surabaya, Academic Year 2021/2022

The aim of this study was to describe the implementation of English learning in TK Harapan. This study applied the qualitative approach in form of a descriptive research. The data source was teacher, documents (weekly plan program, daily lesson plan, instruments for assessment, the students’ works, photos and videos. The data collection was conducted by interview, documentation, and observation. The data validity was conducted by applying the source and technique triangulations. The technique of data analysis was conducted by data reduction, data display, and verification. The result showed media used was flashcard, LCD, projector, and English textbook for Kindergarten.The methods of English teaching learning process applied were TPR (Total Physical Response), song, and game. The learning implementation was applied through composing the daily lesson plan which including five procedures namely before coming into class, opening activity, apperception activity, opening activity, main activity, and closing activity. The assessment was conducted by observation, check-list, and portfolio. The English learning for young learners was focussed on listening and speaking skills. Based on the data in this study, it could be assumed that the English teaching learning process in TK Harapan had worked well and it was able to develop the English ability of young learners.
An Implicit Multidimensional Parity based Data Coding and Decoding Algorithms with FPGA Implementation in Communication Systems

The usability and use of devices in wireless communication is increasing gradually.The mobility and security of the system and the data integrity in the communication process are the requirements of the communication technology for the system.This is the main reason for the development of low voltage generators.Wireless communication medium consists of multiple signals, low voltage communication that can affect any system.Therefore, in wireless systems operating with low-power signals, it is best to use good data encoding and decoding strategies to send data over the medium.The data decoder can recognize changes in the data transmitted in the communication method and correct the data.This encoding-decoding process is calledDetection and Correction of error (EDAC) coding.One of such techniques, most often used in communication, is based on the concept of parity encoding and decoding.In the presented study, a multidimensional parity check based coding-decoding algorithm is proposed based on its results and simulation.With the help of proposed work, the associated process can be effectively used to detect and correct 3-bit errors in data transmission.
Analisa Tingkat Kepuasan Masyarakat Terhadap Kualitas Pelayanan CCTV Lalu Lintas Menggunakan Metode Naïve Bayes

This study aims to determine the level of public satisfaction with the quality of traffic CCTV services at the Palembang City Police Station based on the results of a questionnaire containing Tangibles, Reliability, Responsiveness, Assurance, Emphaty. This research is a quantitative research. The subject of this study was the community of Palembang city which amounted to 300 people Data collection uses questionnaire questionnaires, while data analysis is processed and calculated in mining applications, namely rapidminers using the Naïve Bayes method. The results showed that out of 300 respondents, 73 were very satisfied, 139 satisfied, 34 neutral, 29 dissatisfied, and 25 very dissatisfied. While the most respondents based on gender attributes are men with a total of 166, age attributes are 20-30 with a total of 86, education attributes are high school with a total of 150, job attributes are private employees with a total of 140, vehicle attributes are motorcycles with a total of 150. And from the category is Satisfied with the number of 139.
Advanced Features of the Developed Digital Library to Supplement Conventional Information Access: A Perceptive View

Beginning with removing time and space constraints imposed by traditional physical libraries, digital libraries promise significant societal benefits, especially for e-learning in the digital or mobile age.Since libraries are one of the service sectors most affected by information technology, library and information professionals must acquire this knowledge and skills.This article summarizes recent developments in digital libraries, including their characteristics, strengths, and weaknesses, which come from our perception.The views in this work reflect the influence of information technology on traditional information search.
Prospective mixed-methods study evaluating the potential of a voicebot (CovBot) to relieve German health authorities during the COVID-19 infodemic

Background During the COVID-19 pandemic, telephone hotlines of local health authorities in Germany were overloaded due to information requests by the public. Objective Evaluating the use of a COVID-19-specific voicebot (CovBot) in local health authorities in Germany during the COVID-19 pandemic. This study investigates the performance of the CovBot by assessing a perceptible relief of staff in the hotline service. Methods This prospective mixed-methods study enrolled local health authorities in Germany from 01 February 2021 to 11 February 2022 to deploy the CovBot, which was mainly designed to answer frequently asked questions. To capture the user perspective and acceptance, we performed semistructured interviews and online surveys with their staff, conducted an online survey among callers, and analyzed the performance metrics of the CovBot. Results The CovBot was implemented in 20 local health authorities serving 6.1 million German citizens and processed almost 1.2 million calls during the study period. The overall assessment was that the CovBot contributed to a perceived relief of the hotline service. In a survey among callers, 79% indicated that a voicebot could not replace a human. The analyzed anonymous metadata revealed that 15% of calls hung up immediately, 32% after hearing an FAQ answer, and 51% of calls were forwarded to the local health authority offices. Conclusions A voicebot primarily answering FAQs can provide additional support to relieve the hotline service of local health authorities in Germany during the COVID-19 pandemic. For complex concerns, a forwarding option to a human proved to be an essential functionality.