Reviewerly/exHarmony huggingface dataset:
Two-Way Analysis Of Variance

Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.
Morten Qvenild – The HyPer(sonal) Piano Project

Towards a (per)sonal topography of grand piano and electronics How can I develop a grand piano with live electronics through iterated development loops in the cognitive technological environment of instrument, music, performance and my poetics? The instrument I am developing, a grand piano with electronic augmentations, is adapted to cater my poetics. This adaptation of the instrument will change the way I compose. The change of composition will change the music. The change of music will change my performances. The change in performative needs will change the instrument, because it needs to do different things. This change in the instrument will show me other poetics and change my ideas. The change of ideas demands another music and another instrument, because the instrument should cater to my poetics. And so it goes… These are the development loops I am talking about. I have made an augmented grand piano using various music technologies. I call the instrument the HyPer(sonal) Piano, a name derived from the suspected interagency between the extended instrument (HyPer), the personal (my poetics) and the sonal result (music and sound). I use old analogue guitar pedals and my own computer programming side by side, processing the original piano sound. I also take out control signals from the piano keys to drive different sound processes. The sound output of the instrument is deciding colors, patterns and density on a 1x3 meter LED light carpet attached to the grand piano. I sing, yet the sound of my voice is heavily processed, a processing decided by what I am playing on the keys. All sound sources and control signal sources are interconnected, allowing for complex and sometimes incomprehensible situations in the instrument´s mechanisms. Credits: First supervisor: Henrik Hellstenius Second Supervisors: Øyvind Brandtsegg and Eivind Buene Cover photo by Jørn Stenersen, www.anamorphiclofi.com All other photo, audio and video recording/editing by Morten Qvenild, unless stated.
LT-AES: Automatic Academic Paper Evaluation Model

With the rapid development of science technology and the enhancement of innovation awareness, more and more papers have been submitted to various conferences and journals.When reviewing a paper, viewers of these conferences or journals ensure that their view of the literature is fast and effective and the results of the review are fair and reasonable.Many scholars have proposed many scoring methods to solve the above problems, but these methods only pay attention to the local features of the literature and do not consider the relationship between different modules in the literature.To this end, this paper proposes an LT-AES model to achieve an automatic evaluation of the paper, and obtain the score value of the academic paper.It was found by the experiment, the LT-AES method proposed in this paper has much higher accuracy than other models, and increasing the accuracy rate of more than 3.6%.
Automatic Caption Generation from Images Based on Facial Emotions

In the current era, the vast number of internet users accesses the social network sites like Facebook, Whatsapp, Twitter, and Instagram for uploading their images. User may upload all kind of images with different emotions. In this research article, we introduce novel facial emotion recognition technique using Convolutional Neural Network (CNN) approach and associated a caption automatically based on the identified emotion. We consider only still images for emotion classification. Using face detection algorithms faces were detected from the facial image which is followed by emotion prediction. We automated this detection process for images having frontal faces. In images having non-frontal faces, we manually plot the eye points for rotating the face in such a way that algorithm can detect faces easily. Inferences obtained as a result of experiments shows that the proposed work is capable of identifying minute differences between different emotions and predict accordingly. Based on the emotions identified corresponding captions are generated with better accuracy.
USING DIGITAL BADGES TO PROMOTE PROFESSIONAL DEVELOPMENT IN HIGHER EDUCATION

Micro-credentials or Digital Badges represent the result of acquiring a new skill or competency in a specific discipline.It is the digital collection of these skills that is recognized beyond the traditional degree that distinguishes the development of key skills that are valued in both industry settings and in higher education.The formal and informal acquisition of this knowledge has become a collection of digital credentials that become part of a learning network or ecosystem.The purpose of this paper is to explore the current ways that digital badging is being used to track the professional development of faculty, students, and staff and to explore other ways to use the badges in the future to promote better communication, learning and growth opportunities for employees.This paper explores the literature around micro-credentials and digital badges and the roles that these credentials play while moving into the future of open education.Also discussed are the challenges of collecting knowledge along with the balancing of the needs of traditional education with the trends of modern society.
Is your library website enough?

&lt;p&gt;Increasingly students and researchers are accessing and using information in a wide variety of settings on an array of different devices. Libraries need to adapt and re-purpose their data and information so that it can be used by patrons where, when and how they want to use it. To meet this need the Ryerson Library has initiated several projects to expand access to its resources beyond the traditional confines of the building and the website. &lt;/p&gt;
Memory Allocation of Automated VM on a Server in Cloud

VMMs keep memory utilizing those four previously been coordinated into the mainline portions. This variant offers the shopper solicitation to the server for the memory allocation. In this, we devise a mellow weight structure dependent on the Xen expand intention power to oversee memory inside the server of the VM's. Our purchaser which is going to show does never again meddle with the VM's. We have sorts of planning one is GLOBAL and diverse one is SELF scheduling. This principle thought is to "Procedure MEMORY ALLOCATION". In this we're especially going to utilize the ballon calculation directly here
Desain Banyumas Smart City Berbasis Internet of Things (IoT) Menggunakan Fog Computing Architecture

Internet use in Banyumas Regency is now increasingly diverse according to the demands of the needs. The development of communication technology raises various aspects that also develop. For example, the use of the internet for a traffic light control system so that it can be adjusted according to the settings and can be monitored in real time. In the development of communication technology, the term Internet of Things (IoT) emerged as the concept of extending the benefits of internet communication systems to give impulses to other systems. In other words, IoT is used as a communication for remote control and monitoring by utilizing an internet connection. The Internet of Things in the era is now being developed to create an intelligent system for the purposes of controlling various public needs until the concept of the smart city emerges. Basically, smart cities utilize internet connections for many purposes such as controlling CCTV, traffic lights, controlling arm robots in the industry and storing data in hospitals. If the system is carried out directly from the device to the central server, there will be a very long queue of data while the system created requires speed and accuracy of time so that a system is needed that allows sufficient data control and processing to be carried out on network edge users. Then fog Computing is used with the hope that the smart city system can work with small latency values ​​so that the system is more real-time in sending or receiving data.
Rational Model-Based Training Retain the Health Cadres’ Knowledge, Attitudes, and Practices on Stroke Issue

Stroke is a medical emergency that the patients of it ideally should have received stroke management ≤3 hours since the attack.Emergency situations can occur at anytime, thus the health cadres participation in minimizing pre-hospital delay through FAST method is needed.In order to make the cadres have knowledge, positive attitudes, and good practices about FAST, the rational model-based training was conducted.The aim of this study was to analyze the effectiveness of rational model-based training on the health cadres' changes on knowledge, attitudes, and practices in the stroke symptoms detection using FAST.This study used quasiexperimental research design through pretest-posttest control group design.50 respondents were divided into intervention and control groups.Data analysis used independent sample t-test and mann whitney test.The results show that there were differences in attitude and practices changes between the intervention and the control groups after training, with p values 0.009 and 0.000.There was no any difference in the retention of knowledge, attitudes, and practices in both groups, the p value was 0.849; 0.626;0.456.
Reliability of Fault Tolerance in Cloud using Machine Learning Algorithm

The basic fault tolerance issues seen in cloud computing are identification and recovery. To fight with these issues, so many fault tolerance methods have been designed to decrease the faults. However, due to the reliability and web based service giving behavior, fault tolerance in cloud computing will be a huge challenge. The present model is not just on tolerating faults but also to decrease the possibility of future faults as well[4].The fault tolerance deals with the exact and constant operation of the fault segments. The processing on computing nodes can be done remotely in the real time cloud applications, so there could be more possibilities of errors. Hence there lies an immense necessity for fault tolerance to attain consistency to the real time computing on cloud infrastructure. The “fault tolerance” can be explained through fault processing that have two basic stages. The stages are (i) The effective error processing stage which is used to intended for carrying the “effective error” back to inactive state, i.e., before the error occurred (ii) The latent error processing stage intended for guaranteeing that the fault does not get effective once again.
Supplemental Material for Identifying Robust Correlates of Risk Preference: A Systematic Approach Using Specification Curve Analysis

Extend methods and materials 1.1 Wording of the propensity measuresThe self-reported propensity measures were collected in the German Socio-Economic Panel (SOEP; see https://paneldata.org/soep-is/inst/soep-is-2014-f/Q70 for the item measuring general risk preference, and https://paneldata.org/soep-is/inst/soep-is-2014-f/Q71 for the various items measuring domain-specific risk preference).Below we provide our own English translation of these items, as the translation in the official documentation does not entirely match the original German wording.All responses were provided on an 11-point scale ranging from 0 = "not at all willing to take risks" to 10 = "very willing to take risks". General risk preference:"How do you evaluate yourself?Are you generally a person who is willing to take risks or do you try to avoid risks?"Domain-specific risk preference:"One can behave differently in different domains.How would you evaluate your willingness to take risks concerning the following areas?How about..."• when driving?• concerning financial investments?
Effective Way to Analyze and Rupture the Assessment using ESB Algorithm

Study of perception or opinion mining is statistical analysis of the views of the people.In past years, it is one of the most effective fields of research in the language processing and text mining.Our views and interpretations of reality, and the decisions that we make, are largely dependent on how others see and judge the world.A general method for categorizing sentiment polarity is suggested, with detailed descriptions of the process.Data are collected from the students entry such as Feedback mechanism and it is substituted in our research algorithm. Experiments are performed with promising results for both assessment-level categorisation and analysis-level categorization. Finally, we also give insight into our future work on an examination of sentiments.
Electronic Music

With the end of World War II came the rebirth of European radio. Government stations in both France and Germany established experimental studios for research, from which arose a new kind of music, “electronic music.” The station in France, Office de Radiodiffusion Télevision Française (ORTF), was directed by the engineer/composer Pierre Schaeffer and his partner, Pierre Henry, who called their musical creations <underline>musique concrète</underline>. In Germany the Westdeutscher Rundfunk (WDR) studio produced music through the process of “synthesis.” This chapter will explain the difference between the two approaches used to create electronic music with examples from the percussion solo and ensemble repertoire. Early experiments using wire recorders, test records, and tape recorders by composers Halim El-Dabh, John Cage, and Edgard Varèse precede the major electronic works of Karlheinz Stockhausen, Mario Davidovsky, and the American composer Stephen Everett, whose use of computers in “real time” brings the reader into the next century.
The First International Workshop on Knowledge Graph Technology and Applications Chairs' Welcome

research-article Share on The First International Workshop on Knowledge Graph Technology and Applications Chairs' WelcomeWWW '19: Companion Proceedings of The 2019 World Wide Web ConferenceMay 2019 Pages 672–673https://doi.org/10.1145/3308560.3317700Published:13 May 2019Publication History 0citation56DownloadsMetricsTotal Citations0Total Downloads56Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Education and Employment are at two Poles- A Research using Fuzzy Cognitive Linguistic Multimaps

The status of white collar jobs are gradually declining in India and the people are getting accustomed to just in jobs for their livelihood sustainability. The question of existence of such unfilled gaps between education and employment is still unanswered and now it has become a predicament. It is indeed a crucial period for the higher educational institutions of the nation to balance both enrollment and placement of the students amidst the prevailing competitions in the educational market. In the present days, educational sectors are becoming corporatized by institutionalizing the principles of corporate into the dictionary of academics with the argument of fostering quality in education. The management of the institutions also substantiates such kind of transition in this era of technology. Should the institutions become manufacturing companies of quality employees to make them fit into the job market, which demands excess of skills and competencies to go for a long run? The reasons for education and employment being at two poles have to be studied to develop a deeper comprehension on the grounds of such emerging crisis. This study will be fruitful to the educationalists, academic experts and educational reformers to frame certain remedial measures for rectification. To carry out this research work systematically the concept of Fuzzy Cognitive Linguistic Multimaps, which is an extension of fuzzy cognitive trimaps, is used to draw feasible concluding remarks and inferences devoid of ambiguity and uncertainty.
Influenza Prediction

The point of the undertaking is to foresee the spread of a plague by breaking down the conditions in the territories where individuals are influenced. The momentum focal point of the task is one specific pestilence ailment, Influenza, which is an irresistible illness brought about by introduction to the flu infection. The expectation will be finished by breaking down the spread dependent on the development of the infection through the populace. To achieve such a forecast, an administered learning model was utilized on the informational collection assembled. The calculation utilized is Random Forest Algorithm (RFA), which is basic and is typically utilized for arrangement and relapse.
Discussion on the reform of incorporating socioscientific issues into science education in China based on NVivo : Discourse analysis of middle school textbooks

This study mainly adopts text analysis, supplemented by literature retrieval and comparative research. A text analysis model of science textbooks was designed based on Fairclough’s text discourse analysis framework, including three analysis indicators: knowledge expression, teaching-learning process, and social practice and application. Then, the qualitative analysis software NVivo is selected to conduct qualitative analysis on the text analysis data, the frequency analysis in the four textbook samples. The e-books of 4 samples were reviewed by NVivo coding function; The case node, automatic coding and manual coding function are used to combine the data of four samples; the text search function is used to scan specific chapters of 4 samples to compare the frequency of various discourses, etc. The first purpose of this study is to help the teacher better understand students’ learning methods in science, the value of science teaching and learning to make reasonable changes in science classrooms under the new requirements of incorporating Socioscientific issues (SSI) methods into science teaching. The second purpose is to provide a reference for compiling science textbooks in line with scientific development rules, conducive to cultivating students’ Scientific Literacy and expected to present more local cultural characteristics by comparing Chinese textbooks and two westerns.
Mathematical Part

As will become clear from the first chapters of the book, the theories of Physics which study motion have a common base and structure and they are not independent and unrelated considerations, which at some limit simply produce the same numerical results. The differentiation between the theories of motion is due either to the mathematical quantities they use or in the way they describe motion or, both.
Critique on Cache Transition Techniques for Semantic Graph Parsing for optimizing Search Process using Text Mining

This paper elaborates the transition system that gives the standard transition-based dependency parsing techniques for generating the graph. It is essential to know the standard transition techniques for all graphical problems. Cache transition technique plays a vital role in optimizing the search process in various text mining applications. This paper provides an overview on cache transition technique for parsing semantic graphs for several Natural Language Processing (NLP) applications. According to this paper, the cache is having the fixed size m, by tree decomposition theory according to which there is a relationship between the parameter m and class of graphs produced by the theory.
Dynamic Load Aware Scheduler of Map Reduce Tasks for Cloud Environments

Most of the current day applications are data and compute intensive which led to invention of technologies like Hadoop. Hadoop uses Map Reduce framework for parallel processing of big data applications using the computing resources of multiple nodes. Hadoop is designed for cluster environments and has few limitations when executed in cloud environments. Hadoop on cloud has become a common choice due to its easy establishment of infrastructure and pay as you use model. Hadoop performance on cloud infrastructures is affected by the virtualization overhead of cloud environment. The execution times of Hadoop on cloud can be improved if the virtual resources are effectively used to schedule the tasks by studying the resource usage characteristics of the tasks and resource availability of the nodes. The proposed work is to build a dynamic scheduler for Hadoop framework which can make scheduling decision dynamically based on job resource usage and node load. The results of the proposed work indicate an improvement of up to 23% in execution time of the Hadoop Map Reduce applications.
A New Direct Node Data Splitting Technique in Decision Tree Induction

Learning knowledge from the example data and then applying that knowledge on new applications is the goal of machine learning. Split attribute technique is inseparable and an important means of decision tree construction technique. It is a well known fact and universally accepted truth that a difficult and larger data mining model tends to create less significant generalized performance results. Researchers are being continuously trying to find new and the best split attribute techniques during decision tree induction. In this paper a new direct split attribute technique for decision tree induction is proposed based on the mathematical A implies B tautology principle. The experimental results show that this rule is worthy and useful in many real world applications, particularly in medical field. The resulted association relationships are perfectly matching with the expected results.
Circuits with dependent sources

The chapter begins with a discussion of dependent sources, including an introduction, the different types, equivalent conversion, and circuits with dependent sources. It goes on to discuss their analysis using Kirchoff&apos;s Voltage Law, Kirchoff&apos;s Current Law, node voltage, mesh current, superposition theorem, and Thevenin&apos;s theorem.