Reviewerly/exHarmony huggingface dataset:
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism

When deploying infrastructure as a service (IaaS) cloud virtual machines using the existing algorithms, the deployment process cannot be simplified, and the algorithm is difficult to be applied. This leads to the problems of high energy consumption, high number of migrations, and high average service-level agreement (SLA) violation rate. In order to solve the above problems, an adaptive deployment algorithm for IaaS cloud virtual machines based on <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>Q</mi> </math> learning mechanism is proposed in this research. Based on the deployment principle, the deployment characteristics of the IaaS cloud virtual machines are analyzed. The virtual machine scheduling problem is replaced with the Markov process. The multistep <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>Q</mi> </math> learning algorithm is used to schedule the virtual machines based on the <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mi>Q</mi> </math> learning mechanism to complete the adaptive deployment of the IaaS cloud virtual machines. Experimental results show that the proposed algorithm has low energy consumption, small number of migrations, and low average SLA violation rate.
Testing Your Network

Most apps these days will communicate with the Internet at some point. Purely local apps are great, but communicating with a web service can help transform your app to a truly extraordinary app. There is a huge collection of diverse public web services that your app can make use of. And you can also hook into your own private web service to provide an expanded set of features to your users that you just can’t provide if your app is purely local.
English Textbook Evaluation for 7th Grade of Junior High School: Brian Tomlinson’s Perspective

The importance of English in everyday life and the future opportunities, has made English as a central subject in junior and senior high schools. The government develops English competency standards as outlined in the curriculum as a standard for the English learning process. The needs of students as the main reference in making the curriculum so that educational goals can be achieved.Through PP 32/2013, the 2013 curriculum is a curriculum implemented with the aim of building the students as productive, creative and innovative generations and contributing to social life both in Indonesia and the world. The 2013 curriculum is also a curriculum developed in response to increasing the competence of students who are able to compete both in Indonesia and abroad.This monograph presents an evaluation related to the presentation of the 2013 curriculum-based textbook, both visually and in content. The evaluation was carried out based on 14 criteria according to Tomlinson which was carried out on 4 books; 'When English Rings the Bells', 'Let's Speak English', 'Headline English', and 'Interactive English'.
Creativity in special music education

Today, the development of creative and innovative thinking has become an important task of the modern education system. Stimulating creativity is one of the main goals of music education, which involves important changes affecting both the teachers’ mentality and traditional teaching and training methods. In the process of music education, the primary task is to awaken the creative principle of students, to stimulate their interest not only in the result of the creative act, but also in the process of musical activity that reveals the creative nature of the personality, the ways of creating, interpreting, listening and perceiving musical art.
Statistical Methods for Data Compression

Statistical methods are not only applicable in hardcore data science topics. They also have applications in what could be considered more traditional computer science, such as compression algorithms. While there is active research conducted in compression via machine learning, we will explore, derive, and implement a much more medieval, rule-based algorithm.
TOPSIS in Decision-Making Framework Based on Twitter Sentiment Analysis

Twitter is one of social media that categorized in microblogging. Tweets on Twitter which are short sentences containing an opinion or sentiment. This is very beneficial for the organization or company to conduct analysis. The objective for this analysis is market prediction, general elections, measuring reactions to events or news, and measuring subjectivity. This affects the decision making for the company. Therefore, the role of sentiment analysis is very necessary to get the classification of sentiment in the form of positive, negative, and neutral sentiments. This type of sentiment polarity is used as a criteria for preference modeling so that alternative decisions can be calculated for the final value. This study attempts to propose a decision-making framework based on sentiment analysis. In addition, this research is also an improvement from the previous decision-making framework where decision-making is based on sentiment analysis. Improvements were made to the modeling of the criteria which initially used the SAW method to be changed to the TOPSIS method. Furthermore, the final value of the decision alternatives using TOPSIS is compared with using SAW. The comparison parameters used are in the form of final scores and ranking results. The final score of the SAW method is greater than the TOPSIS end score. In addition, there are differences in the ranking results between the TOPSIS and SAW methods.
The Role of Marketing Culture in Enhancing Marketing Performance: A Field Research in Abu- Ghraib Dairy Factory: دور الثقافة التسويقية في تعزيز الأداء التسويقي: بحث ميداني في معمل ألبان أبو غريب

The study aims to study the role of marketing culture in enhancing marketing performance by examining the relationship and impact models between them, as the study problem was embodied by questions, including: What is the role of marketing culture in enhancing marketing performance and what is the truth about the relationship between them in the researched organization ?, So the study sample was represented by an Intentional sample, consisting of (32) employees, which included all the personnel working in the marketing department, customer service, and managers at the upper and middle administrative levels. The questionnaire was adopted as a main measurement tool for the study in addition to personal interviews to collect data. The study also relied on the descriptive and analytical approach to present and analyze the data. Several statistical methods have been employed to analyze these data, the most prominent of which are (Pearson Correlation Coefficient, Simple Regression Analysis Method, F- Test and t). Among the most important conclusions reached by the study: The overall marketing culture of the researched organization has influenced the activities and indicators that enhance its marketing performance. As for the most important recommendations presented by the study: The need for the researched organization to benefit from the support of the administration and workers to enhance the marketing culture in the organization by setting the reference framework for the work within the organization and the principles and foundations that guide and govern the work of all individuals working in the organization and focus on the dimensions of the marketing culture to support and enhance the marketing performance.
Assessment of Automatic Hair Colorization and Relighting Using Chromaticity Distribution Matching

This paper presents a new approach to human hair colorization and relighting. Human hair colorization, concerning given model hair image without changing neither hairstyle nor hair texture, is challenging. The fundamental problem making this task complicated is the difference in the hair texture and the illumination between a user and model images. Natural human hair consists of a mix of hair swatches. Each swatch has its chromaticity distribution, which, generally, is non-Gaussian. The proposed method treats these swatches as color clusters in the hair image. In this case, matching the user and the model hair swatches or color clusters solves the problem. After this matching, the color transfer between the relevant model and user swatches is applied. Besides, the model’s hair should be compressed to a reasonable size to provide simultaneous representation for numerous hair colors. The model’s hair colors are taken from the images of hair color packs that usually are available in decorative cosmetic stores. These images, however, are taken in standard illumination conditions, so appropriate relighting should be applied to provide a photorealistic user’s appearance. Experimental results with 530 different color models and more than 20,000 users show that the proposed technique achieves high photorealistic perception and a reasonable compression ratio. On average, a high pick signal to noise ratio (39 dB) indicates just a noticeable difference between original and reproduced model hair color.
Individual Privacy Accounting via a Rényi Filter

We consider a sequential setting in which a single dataset of individuals is used to perform adaptively-chosen analyses, while ensuring that the differential privacy loss of each participant does not exceed a pre-specified privacy budget. The standard approach to this problem relies on bounding a worst-case estimate of the privacy loss over all individuals and all possible values of their data, for every single analysis. Yet, in many scenarios this approach is overly conservative, especially for typical data points which incur little privacy loss by participation in most of the analyses. In this work, we give a method for tighter privacy loss accounting based on the value of a personalized privacy loss estimate for each individual in each analysis. To implement the accounting method we design a filter for Renyi differential privacy. A filter is a tool that ensures that the privacy parameter of a composed sequence of algorithms with adaptively-chosen privacy parameters does not exceed a pre-specified budget. Our filter is simpler and tighter than the known filter for $(\epsilon,\delta)$-differential privacy by Rogers et al. We apply our results to the analysis of noisy gradient descent and show that personalized accounting can be practical, easy to implement, and can only make the privacy-utility tradeoff tighter.
Teaching Songwriting with MIDI Projects

The projects in this chapter introduce MIDI recording, sequencing, and editing techniques for composition and songwriting. The projects include strategies for enabling students to quickly generate a large amount of original musical material quickly. Beginner songwriters and composers find empty DAW sessions to be daunting, so it is essential to build their confidence. Therefore, the chapter gives techniques for quickly generating melodic and drum sequences, duplicating them, and creating variations on them. This approach also has the benefit of mirroring “real-world” professional production practice. The projects cover drum programming and arranging, as well as writing chord sequences, basslines, and short melodies. A pragmatic instrument taxonomy of “drums” and “not-drums” is used, and the typical instrumental layers in contemporary electronic music genres are explained. Also presented is a practical approach to relevant music theory concepts. Finally, three popular genres—future bass, house music, and trap—are used to introduce musical form.
Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework

Answering questions asked from instructional corpora such as E-manuals, recipe books, etc., has been far less studied than open-domain factoid context-based question answering. This can be primarily attributed to the absence of standard benchmark datasets. In this paper, we meticulously create a large amount of data connected with E-manuals and develop a suitable algorithm to exploit it. We collect E-Manual Corpus, a huge corpus of 307,957 E-manuals, and pretrain RoBERTa on this large corpus. We create various benchmark QA datasets which include question answer pairs curated by experts based upon two E-manuals, real user questions from Community Question Answering Forum pertaining to E-manuals etc. We introduce EMQAP (E-Manual Question Answering Pipeline) that answers questions pertaining to electronics devices. Built upon the pretrained RoBERTa, it harbors a supervised multi-task learning framework which efficiently performs the dual tasks of identifying the section in the E-manual where the answer can be found and the exact answer span within that section. For E-Manual annotated question-answer pairs, we show an improvement of about 40% in ROUGE-L F1 scores over most competitive baseline. We perform a detailed ablation study and establish the versatility of EMQAP across different circumstances. The code and datasets are shared at https://github.com/abhi1nandy2/EMNLP-2021-Findings, and the corresponding project website is https://sites.google.com/view/emanualqa/home.
Developing a monograph book for teaching English skills to young learners in wetlands areas

To enable Universitas Lambung Mangkurat (ULM) to become the Asia-Pacific centre for wetlands development in 2027, one of the efforts ULM makes is to raise awareness about the importance of optimising human resources in wetlands through research and development in the educational and cultural fields. English is considered a foreign language in Indonesia, allowing students to use the language outside of academic settings. English becomes a required subject in junior and senior high school; however, the government requires that English be taught in primary schools as a local topic. English, on the other hand, remains a mandatory subject in a large number of Indonesian primary schools, particularly in Banjarmasin. The issue arises in primary school English instruction because there is no clear guidance for teachers on how to teach English in an appropriate and engaging manner for the students. Due to the absence of a monograph book on teaching methods, teachers in some primary schools in Banjarmasin, particularly those located in wetland areas, have limited access to teaching English to young learners (EYL). In light of the university's policy and the critical nature of achieving teaching and learning objectives, as well as the absence of a suitable reference book for teaching EYL, this study aims to develop an appropriate monograph book on teaching techniques for students of young ages. The research and development design is chosen because it aims to create a product and meets the needs of the reference book's development. The results are expected to improve students' academic performance and to assist EYL teachers in wetland areas in conducting effective and meaningful teaching.
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning

Recent prompt-based approaches allow pretrained language models to achieve strong performances on few-shot finetuning by reformulating downstream tasks as a language modeling problem. In this work, we demonstrate that, despite its advantages on low data regimes, finetuned prompt-based models for sentence pair classification tasks still suffer from a common pitfall of adopting inference heuristics based on lexical overlap, e.g., models incorrectly assuming a sentence pair is of the same meaning because they consist of the same set of words. Interestingly, we find that this particular inference heuristic is significantly less present in the zero-shot evaluation of the prompt-based model, indicating how finetuning can be destructive to useful knowledge learned during the pretraining. We then show that adding a regularization that preserves pretraining weights is effective in mitigating this destructive tendency of few-shot finetuning. Our evaluation on three datasets demonstrates promising improvements on the three corresponding challenge datasets used to diagnose the inference heuristics.
Relationship between Participation Motivation and Psychological Well-being of Marine Leisure Sports Participants

This study aims to find out the psychological wellbeing relationship and motivation of participants in marine sports.The subjects to the study were the population of participants who regularly participate in marine leisure sports.For sampling, a random sampling method was used.The survey was answered using the self-evaluation method through a questionnaire.Data processing was obtained by statistical processing of 341 questionnaires out of all the sincere data among the questionnaires.Through data processing, we got the following results.First, the internal motivation of marine leisure sports participants was positively correlated with all factors of psychological well-being.Second, all factors of participation motivation of marine leisure sports participants were found to have positive effects on selfacceptance and positive interpersonal relationships.Research has also shown that voluntary and continuous participation in sports activities will increase levels of psychological well-being.In particular, the study showed that the motivation for participants in marine sports is an important factor that has a beneficial influence on psychological happiness.This suggests that participation motivation of marine sports participants can positively contribute to the improvement of quality of life by contributing to positive emotional purification.
Technology’s Impacts in the Students of Higher Education in the Covid-19 Pandemic Period

In this period of Covid-19 pandemic, in which there were sudden changes in education, with the transition from traditional education to e-learning, it is essential to analyze the impacts related to access and use of technology in the context of e-learning, in the perception of higher education students. In this context, all students were forced to use the technology, so it is relevant to investigate the interrelationships between satisfaction with distance learning and all the components associated with the use and acceptance of technology as a support to their learning. Data were collected through a questionnaire, which includes a set of 26 items that aim to assess students' perceptions about distance learning using six different subscales: Familiarity, Barriers, Anxiety, Usefulness, Ease of use, and Satisfaction concerning the e-learning. A Structural Equation Model (SEM) analysis was performed using Partial Least Squares (PLS), to test the validity of the constructs and the model hypotheses. The results revealed a statistically significant relationship between Satisfaction concerning the distance learning and the constructs Barriers, Ease of use and Usefulness. Based on the model used, other significant interrelationships were registered, such as familiarity with technology positively affects the ease of use of technological resources and barriers, while anxiety negatively affects the ease of use of these resources and the usefulness for students. A multigroup analysis revealed, among other results, that in the students with a moderate to high autonomy, the familiarity with technology positively affects satisfaction with e-learning comparatively to the students with low autonomy.
RECURSIVE FORMULAS GENERATING POWER MOMENTS OF TERNARY KLOOSTERMAN SUMS WITH TRACE NONZERO SQUARE ARGUMENTS: O (2 n + 1, 3 r ) CASE

In this paper, we construct four infinite families of ternary linear codes associated with double cosets in O(2n + 1, q) with respect to certain maximal parabolic subgroup of the special orthogonal group SO(2n + 1, q) . Here q is a power of three. Then we obtain two infinite families of recursive formulas, the one generating the power moments of Kloosterman with trace nonzero square arguments and the other generating the even power moments of those. Both of these families are expressed in terms of the frequencies of weights in the codes associated with those double cosets in O(2n + 1, q) and in the codes associated with similar double cosets in the symplectic group Sp(2n, q) . This is done via Pless power moment identity and by utilizing the explicit expressions of exponential over those double cosets related to the evaluations of Gauss sums for the orthogonal group O(2n + 1, q) .
An Axis Orbit Reconstruction Method for Rotating Machinery Based on Machine Vision

In this paper, a three-dimensional axis orbit reconstruction method based on machine vision is proposed for rotating machinery. Firstly, the center of rotor is marked and its motion is videotaped. Secondly, the local phase of captured image sequences is extracted, which is linear with the axis orbit displacement. Combined with the binocular stereo vision, three-dimensional axis orbit is reconstructed. According to the linear relation between phase and displacement, the actual axis orbit can be obtained. Finally, the experiment is performed on a permanent magnet synchronous motor, and the experimental results verify the effectiveness of the proposed method.
Ableton Live and Push

Ableton Live and the Push controller support a wide range of expressive, creative, and educational possibilities. This chapter covers how Live and Push differ from other digital audio workstations (DAWs) and MIDI interfaces. The DAW functions like a score and a suite of instruments, as well as a recording device—a tool for creating music from scratch, rather than simply documenting it. Ableton Live was originally designed for onstage performance, and its compositional workflow has an appealing improvisational aspect. However, rather than performing entire songs as DJs do, Live users play back clips and patterns of any arbitrary length. The Push’s tactile clip-launching interface is a genuinely new visualization and organization scheme, with potentially profound significance for users’ musical imaginations. Since Ableton Live is not the best DAW for every case, the chapter also compares it to three prominent alternatives: Avid’s Pro Tools, Apple’s Logic Pro, and Image-Line’s FL Studio.
The Right to Contest AI

Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability.In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for its establishment. This Article argues that despite considerable differences between the United States and other countries,establishing the right to contest AI decisions here would be in keeping with a long tradition of due process theory.This Article then fills a gap in the literature, establishing a theoretical scaffolding for discussing what a right to contest should look like in practice. This Article establishes four contestation archetypes that should serve as the bases of discussions of contestation both for the right to contest AI and in other policy contexts. The contestation archetypes vary along two axes: from contestation rules to standards and from emphasizing procedure to establishing substantive rights. This Article then discusses four processes that illustrate these archetypes in practice, including the first in depth consideration of the GDPR’s right to contestation for a U.S. audience. Finally, this Article integrates findings from these investigations to develop normative and practical guidance for establishing a right to contest AI.