Reviewerly/exHarmony huggingface dataset:
Measuring speed of sound in the violin maker’s workshop through longitudinal standing waves: a simple alternative method

Of great importance to the violin maker and other instrument makers, are the material properties of wood. Speed of sound in transverse and longitudinal directions is commonly measured in the workshop by sending a signal through the material, calculating speed of sound from propagation time and sample length. This method relies on an accurate device, known as a Lucchi Meter, which is usually quite expensive and comes with it’s own set of caveats. An alternative idea is to measure the frequency of some longitudinal standing wave inside the object and calculate speed of sound from frequency and wavelength. This procedure is tested for 6 blanks of spruce tops, maple backs and necks for violins with contact as well as non-contact pick-ups. Results are compared with Lucchi Meter measurements, as well as Young’s Modulus derived from modal analysis of violin blanks. For speed of sound we find generally good agreement between both data sets with absolute values derived by Lucchi Meter method being higher in general. Advantages and disadvantages of both methods are discussed and we conclude that the longitudinal standing wave measurement can effectively replace the much more expensive Lucchi Meter in the workshop in most cases.
Realization of a source-device-independent quantum random number generator secured by nonlocal dispersion cancellation

Quantum random number generators can provide genuine randomness by exploiting the intrinsic probabilistic nature of quantum mechanics, which play important roles in many applications. However, the true randomness acquisition could be subject to attacks from untrusted devices involved or their deviations from the theoretical modelling. Here we propose and experimentally demonstrate a source-device-independent quantum random number generator, which enables one to access true random bits with an untrusted source device. The random bits are generated by measuring the arrival time of either photon of the time-energy entangled photon pairs produced from spontaneous parametric down conversion, where the entanglement is testified through the observation of nonlocal dispersion cancellation. In experiment we extract a generation rate of 1.125 Mbps by modified entropic uncertainty relation. Our approach provides a promising candidate for quantum random number generators with no characterization.
The “Sciencemopoly Game” to improve junior high school students’ learning motivation on the digestive system topic

This study intends to 1) develop teaching media “Sciencemopoly Game” for grade VIII students of SMP Al Qur’an Zaenuddin on the digestive system topic; 2) determine the feasibility of Sciencemopoly Game; 3) know the increase in students’ learning motivation. This research is a research and development (R & D) using the 4D model. Questionnaires with the Likert scale were used as the research instrument, and the collected data were analyzed using the descriptive-statistics method. The results concluded that the Sciencemopoly Game is a suitable teaching media for science learning on the digestive system topic having an average expert validity score of 4,24. After being tested, the score of small-group product trial was 4,08 or in the ’excellent’ category, and the field trial score was 4,39 or in the ’excellent’ category. Further, the Sciencemopoly Game has been proven to increase students’ learning motivation, from 3,76 in.the ‘good’ category to 4,09 in.the ‘excellent’ category. So that, this media can be used in supporting the learning process and forming joy class atmosphere.
Quantum Noise And Measuring Quantum Distance For NISQ Circuits

&lt;p&gt; In this article, we analyzed the performance of several classes of quantum circuits under various errors. We executed NISQ circuits on both noisy simulator and real hardware backend publicly available from IBM Quantum. On simulation, we created noise models with both individual errors and combination of multiple errors to quantify how each type of error impact performance of quantum circuits. We utilized statistical distances such as total variation distance (TVD), Jensen-Shannon divergence (JSD), and Hellinger distance, to measure the deviation of noisy output from ideal output. Finally, we compare the noisy outputs from the simulator and outputs from the real hardware to showcase the gap between simulation and real device experiment. This gap points to the limitation of present noise models failure to exhibit the behavior of real hardware.&lt;/p&gt;
FAMAID: A TOOL FOR AIDING PEOPLE WITH DISABILITY

People with disabilities suffer from discrimination and obstacles that restrict them from participating in society on an equal basis with others every day. They are deprived of their rights to be included in ordinary school systems and even in the work market. In the process of raising awareness, facilitating daily routines, and developing guidance, the idea of assisting such people with handy tools/software arose and was implemented in the FamAid tool. FamAid offers people with hearing disability the opportunity to be engaged in the society through many facilities. In this work, we implemented a web application that serves as a community for people with disability who can use sign language to access the app. The app uses hand gesture recognition technique which is considered an active research field in Human-Computer Interaction technology to perform sign language translation to text. Afterwards, the text will be provided as input to the app where the output will be generated based on the request of the user. This research presents an application which is considered a gift for people with speaking and/or hearing disability as it makes their lives easier.
Learning From Human Correction

&lt;p&gt;In industry NLP application, our manually labeled data has a certain number of noisy data. We present a simple method to find the noisy data and re-label them manually, meanwhile we collect the correction information. Then we present novel method to incorporate the human correction information into deep learning model. Human know how to correct noisy data. So the correction information can be inject into deep learning model. We do the experiment on our own text classification dataset, which is manually labeled, because we re-label the noisy data in our dataset for our industry application. The experiment result shows that our method improve the classification accuracy from 91.7% to 92.5%. The 91.7% accuracy is trained on the corrected dataset, which improve the baseline from 83.3% to 91.7%.&lt;/p&gt;
The Cyber Centre, Host and Cloud-Based Sensor Technology - An Analysis

&lt;p&gt;The emerging cybersecurity industry in Canada is not seen as anywhere near the scale of its American cyber-industrial complex counterpart, with limited-scale projects occurring to improve security sensor technology for institutions. However, due to international trade increasingly occurring through cyberspace, it is expected that the cyber industry will grow in Canada through both international and domestic partnerships, with Canadian critical infrastructure partners requiring greater security controls in order to ensure the confidentiality, integrity and availability of their data and operations. &lt;/p&gt;
An Interview Study with English Course Teachers On Teaching Writing Skills Through Google Meets During The Covid-19 Pandemic

During the COVID-19 pandemic, this study sought to investigate teachers' ability to integrate writing skills with online learning via Google Meetings. This was qualitative research with semi-structured interviews with a teacher at Zain Academy. Respondents were taken purposefully, namely teachers at Zain Academy who taught writing with Google Meet during the COVID-19 pandemic. This study will explicitly investigate (a) the availability of access to technology at the teacher's home and (b) the difficulties in teaching writing skills online through Google Meeting. The provisional finding of this study was that the availability of access to technology is very limited, and because of the instability of internet access, there are difficulties in maximizing online learning, especially in learning writing skills, because students are unable to open online classes due to frequent power outages or parallel WiFi interference, as well as the capacity and speed of internet access, which are not sufficient. The results of the interview informed the availability of access to technology and the difficulties in teaching writing skills online through Google Meetings during the COVID-19 pandemic. Based on the results of this research, it is hoped that it will provide insight into the impact of forced changes in teaching, which can have implications for teacher competence in terms of digitization, especially in teaching writing skills, which are very important skills for those who want to master written language in English properly and correctly.
DEVELOPMENT OF MOBILE LEARNING BASED ON AN INTEGRATED PREDICTION GUIDE AS A SUPPORT OF PHYSICS LEARNING IN HIGH SCHOOL ON THE TOPIC OF WAVES

This research aimed to develop Android-based Mobile Learning media that is integrated with the Prediction Guide learning model using Smart Apps Creator software as research supporting high school physics learning on wave material. The research method used in this research is Research and Development (R &amp;D) using the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). However, due to the condition of the Covid-19 pandemic, this development research is only carried out until the development stage. The techniques used in analyzing data are descriptive analysis techniques by calculating the percentage of expert validation scores and student response tests. The analysis of this study obtained an average of 83% from media experts, 89% from material experts, and 86% from linguists. Thus, the overall average percentage of expert validation obtained an average percentage value of 86%, with very feasible information, and can be used in school. Meanwhile, the average percentage obtained from the student response test was 74% which describes a good response from the students.
ANALISIS SENTIMEN PADA ULASAN APLIKASI AMAZON SHOPPING DI GOOGLE PLAY STORE MENGGUNAKAN NAIVE BAYES CLASSIFIER

Sentiment analysis or opinion mining is a study that analyzes people's opinions, thoughts and impressions on various topics, subjects, and products or services. The development of social media makes public opinion data available which can be found easily on the internet. The large volume of data causes the need for an automatic system to classify the data based on different aspects because classifying data manually is a time-consuming process. In this study, sentiment analysis will be carried out with a machine learning-based approach using the Naive Bayes algorithm using user review data on the Amazon Shopping application on the Google Play Store. The classification results using the four Naive Bayes algorithms produce an average accuracy of 82.15%, precision of 72.25%, recall of 83.49%, and f1-score of 77.41%. Multinomial NB produces the best accuracy among the four Naive Bayes algorithms used, which is 86.74%. The values of precision, recall, and f1-score are 78.82%, 85.90%, and 82.21%, respectively.
SYSTEMATIC REVIEW : MADU UNTUK ULKUS DIABETIKUM

Diabetes Mellitus is a chronic disease caused by abnormalities in insulin secretion, insulin absorption or both. Characteristics of people who suffer from diabetes mellitus is an increase in blood sugar (hyperglycemia). Damage to the peripheral nervous system will reduce the response to the patient's pain or also called numbness of the peripheral tissues. Lack of sensitivity will cause the patient to be unaware of the wound. In addition to using anti-diabetic drugs and wound care, honey can also be an alternative in wound care and accelerate the healing of ulcers decubitus. Methods: This study is a literature review using research data taken from Google Scholar. The journal criteria taken are from 2017 to 2022 with the keywords honey and pressure ulcers. From the journals reviewed, it was found that honey can accelerate the healing of diabetic wounds. Healing diabetic ulcers with honey can be compared with other methods. The use of honey is cheaper than other wound healing methods. Honey as a wound dressing in diabetic wounds can improve healing at a lower cost
Parental Attention and Learning Motivation of Elementary School Students: Correlation Studies

Lack of parental attention affects student learning motivation. This study aims to determine: 1) the level of attention of students' parents, 2) the level of student learning motivation, and 3) the relationship between parents' attention and students' learning motivation. The research was conducted in MI throughout the Gatak District, Sukoharjo, from January to May 2021. The data collection technique used a questionnaire of 39 grade V students. The sampling technique used cluster sampling. The results of the study showed: 1) Parents' attention was in the medium category of 18 students or 46.16%, 2) Students' learning motivation is in the medium category of 24 students or 61.54%, 3) Based on the calculation of the hypothesis test at a significance level of 5%, the results obtained are rcount (0.626) &gt; rtable (0.316). So it can be concluded that there is a relationship between parental attention and student learning motivation. With a coefficient of determination of 0.392, the amount of contribution made by parental attention to learning motivation is 39.2% influenced by parental attention, while 60.8% is influenced by other factors not examined. The relationship between these two variables is at a strong relationship level, between 0.61-0.80
Internet-mediated Language and style in Chimamanda Ngozi Adichie’s Americanah

The astounding development in Information Communication Technology (ICT) has transformed all fields of human endeavours and provided various media that writers employ in their literary texts. As rich as internet-mediated language and style are in the study of Adichie’s Americanah, there are paucity of scholarly studies that discussd their linguistic features and relevance. Therefore, the objective of this study is to investigate the aspects of internet-mediated language and style used in Chimamanda Ngozi Adichie’s Americanah. This study adopted Computer-mediated Communication (CMC) and this theory is dichotomised into synchronous and asynchronous modes. Synchronous modes comprise telephone conversations and instant messaging whereas asynchronous modes include e-mails, blogs and text messages. Methodologically, this study selected Adichie’s Americanah as a primary source using judgemental sampling. The documentary sources were obtained via journal articles, textbooks, dictionaries, dissertations and theses that boosted this study’s review. As for data presentation and analysis, the author read Americanah; selected Internet-mediated (IM) features; classified them into blogs, e-mails, text messages and telephone conversations and analysed them. One of the findings is that IM style saves time and enhances quick narration than letters. Secondly, the domestication of IM jargons in Americanah also indicates that the language of ICT is relevant in literature. Lastly, IMC is a recent style that Adichie employs in Americanah. This study will have tremendous impacts on English, Linguistics, Mass Communication, ICT and Literature students, researchers, scholars and lecturers.
Are Classifiers Trained on Synthetic Data Reliable? An XAI Study

&lt;p&gt;Machine learning (ML) solutions are being applied in many areas of our daily lives, but they often require high-quality, balanced datasets in order to perform well.&lt;/p&gt; &lt;p&gt;However, datasets for real-world problems are often imbalanced, requiring the use of special-purpose ML algorithms or synthetic data to address the class imbalance.&lt;/p&gt; &lt;p&gt;Traditional techniques such as Synthetic Minority Oversampling Technique (SMOTE) and generative models such as Variational Auto Encoders (VAE) and Generative Adversarial Networks (GAN) are commonly used to generate minority class samples. &lt;/p&gt; &lt;p&gt;Evaluating the quality of synthetic samples can be challenging, and researchers often rely on improved classifier performance as justification for their use. &lt;/p&gt; &lt;p&gt;However, simply performing well on a test set is not sufficient to ensure the trustworthiness of a model, and further analysis of model predictions is necessary. &lt;/p&gt; &lt;p&gt;To address this, we trained multiple classifiers on synthetic data generated by various methods and analyzed their predictions using SHAP, an explainable AI technique. &lt;/p&gt; &lt;p&gt;Our in-depth analysis showed that these classifiers used different features for making predictions and placed different levels of importance on commonly used features. Therefore, we conclude that classification models trained on synthetic data must be carefully analyzed by human experts before being deployed in the real world.&lt;/p&gt;
Correction to: Regression-Based 3D Hand Pose Estimation for Human-Robot Interaction

In the originally published version of chapter 24, the acknowledgements section was erroneously omitted. The acknowledgements section and grant number have been added.
Automated Measures of Sentiment via Transformer- and Lexicon-Based Sentiment Analysis (TLSA)

&lt;p&gt;The last decade witnessed the proliferation of automated content analysis in communication research. However, existing computational tools have been taken up unevenly, with powerful deep learning algorithms such as transformers rarely applied as compared to lexicon-based dictionaries. To enable communication scholars to adopt modern computational methods for valid and reliable sentiment analysis, we propose a free and open web service named transformer- and lexicon-based sentiment analysis (TLSA). TLSA integrates different sentiment analysis tools including transformer-based deep learning models and sentiment dictionaries. TLSA enables users with limited computational resources to use these tools and validate their results at once. Two cases showed that transformer-based models provided more accurate measurement of sentiments in tweets, compared to lexicon-based methods. The performance of different tools varied to a large extent based on the dataset, suggesting the importance to validate different sentiment tools in a specific study. TLSA is expected to empower communication scholars to reap the benefit of state-of-the-art computational methods for valid measurement and insight discovery. &lt;/p&gt;
Copy-cat Bot for Narendra Modi which generates plausible new speeches in Modhi’s style using machine learning approaches

Many consequences in the human past can be traced back to that one well-written, well-presentedspeech. Speeches grasp the power to move nations or touch hearts as long as they are well-thought-out.This is why gaining the expertise of speech giving and speech writing is something we should all intent togain. A copy-cat bot is a model that can learn the writing and talking style of a certain person and replicateit. The main objective of this research study is to apply simple Recurrent Neural Network (RNN), LongShort-Term Memory (LSTM) Recurrent Neural Networks and Gated Recurrent Unit (GRU) in developinga speech generation system that deep learns one text and then generates new text. This research looks intothe generation of English transcripts of Narendra Modi’s speeches. The generated text using LSTM andGRU models has great potential. The output resulted by RNN is less realistic and pragmatic, but itsvariants LSTM and GRU performed better. Though the grammatical correctness and the sentencetransitions were absent in generated text of LSTM and GRU, but their output is somewhat logical ascompared to RNN. LSTM and GRU performed better as it generated more realistic text and training lossis small, perplexity is small and mean probability is high compared to RNN.&#x0D;
Digital &amp; media literacy as a condition for the formation of the digital generation

The article shows that the formation of the digital generation today takes place in difficult crisis conditions. It causes the need to rethink and apply new methodological tools, didactic approaches that will meet the requirements of modernity and the needs of the individual. It was analyzed by the "theory of generations" and it was determined that the vast majority of students today are the digital generation. It is substantiated that for the digital generation, standard teaching methods lose their effectiveness. In this context, it is shown that the orientation of the goals and content of school education to the development of "4K digital skills" in students: critical thinking, creativity, communication skills, cooperation becomes especially relevant. It was clarified that working with information occupies a prominent place in the problem of developing "4K digital skills" among students. "4K digital skills" are characterized. It was concluded that the development of the considered digital skills among schoolchildren is successfully implemented within the course "Digital and media literacy".
СПЕЦИФИЧНОСТ ВАСПИТНО-ОБРАЗОВНИХ МЕТОДА У РАДУ СА ДЕЦОМ ПРЕДШКОЛСКОГ УЗРАСТА

The problems of methods of education (teaching) are dealt with successfully and continously by the didactics. Within this pedagogical discipline, the teaching methods are systematically studied, defined, classified, and from the various aspects evaluated. Thereby, on one side their universal importance is being considered, while on the other side, their contribution to the teaching in schools is being studied. The aim of this paper is to try to point out ,taking both sides into consideration, the need of being familiar with the particularities of educational methods applied in work with children of pre-school age. It is difficult (even impossible) to differentiate the two sides as they both consider the learning process and a child, both in school and pre- school institutions (e.g. kindergardens). There are fewer sources dealing with this subject than of those ones dealing with the methods applied to school teaching but thus, the challenge is greater! The basic aim is that the activities of the educator that lead to the passive response of children should turn into their greater inclusion ( active response). The aim is thus to find out specific properties of each pre-school child and its motivation, directing the way that suits him/ her the best as they are the unique ones. The child wants and expects to be free and have its needs respected according to its abilities. The methods of work at this age must be accepted, not forced upon when there is a successful cooperation between caring educators and a curious child interested in improving and making a progress in learning about its entire environment. Key words: method, methods of work with pre-school children
Provably Solving the Subset Sum Problem by lp-norm SVP Oracle

Abstract The authors have requested that this preprint be removed from Research Square.