Reviewerly/exHarmony huggingface dataset:
Appendix A: Conversation analysis transcription conventions

With recent advances in natural language understanding techniques and farfield microphone arrays, natural language interfaces, such as voice assistants and chatbots, are emerging as a popular new way to interact with computers. They have made their way out of the industry research labs and into the pockets, desktops, cars and living rooms of the general public. But although such interfaces recognize bits of natural language, and even voice input, they generally lack conversational competence, or the ability to engage in natural conversation. Today's platforms provide sophisticated tools for analyzing language and retrieving knowledge, but they fail to provide adequate support for modeling interaction. The user experience (UX) designer or software developer must figure out how a human conversation is organized, usually relying on commonsense rather than on formal knowledge. Fortunately, practitioners can rely on conversation science. This book adapts formal knowledge from the field of Conversation Analysis (CA) to the design of natural language interfaces. It outlines the Natural Conversation Framework (NCF), developed at IBM Research, a systematic framework for designing interfaces that work like natural conversation. The NCF consists of four main components: 1) an interaction model of "expandable sequences," 2) a corresponding content format, 3) a pattern language with 100 generic UX patterns and 4) a navigation method of six basic user actions. The authors introduce UX designers to a new way of thinking about user experience design in the context of conversational interfaces, including a new vocabulary, new principles and new interaction patterns. User experience designers and graduate students in the HCI field as well as developers and conversation analysis students should find this book of interest.
Penalaan Mandiri Full State Feedback dengan LQR dan JST Pada Kendali Quadrotor

Quadrotor is one type of unmanned aerial vehicle that has the ability to vertical takeoff and landing. In this research, a system designed to stabilize quadrotor during flight condition by maintaining at angle of roll, pitch, yaw, and x, y, and z axis position using LQR full state feedback with artificial neural network (ANN).The LQR full state feedback method uses 12 states with each K constant being tuned with ANN. This research implements ANN method to change feedback constant at angle of roll, pitch, and yaw and x, y, and z axis. The artificial neural network method uses 12 input layers, 12 hidden layers, and 1 output layer.Testing with ANN improved the rise time to ± 2.18 seconds at the roll angle, ± 1.23 seconds at the pitch angle, and ± 0.31 seconds at the yaw angle. Improved settling time value up to ± 2.41 seconds at roll angle, ± 1.23 seconds at pitch angle, and ± 1.07 seconds at yaw angle. Improved steady state eror value of ± 0.61% at roll angle, ± 4.88% at pitch angle, and ± 0.82% at the yaw angle.
Appendix B: Dialog design pseudocode

With recent advances in natural language understanding techniques and farfield microphone arrays, natural language interfaces, such as voice assistants and chatbots, are emerging as a popular new way to interact with computers. They have made their way out of the industry research labs and into the pockets, desktops, cars and living rooms of the general public. But although such interfaces recognize bits of natural language, and even voice input, they generally lack conversational competence, or the ability to engage in natural conversation. Today's platforms provide sophisticated tools for analyzing language and retrieving knowledge, but they fail to provide adequate support for modeling interaction. The user experience (UX) designer or software developer must figure out how a human conversation is organized, usually relying on commonsense rather than on formal knowledge. Fortunately, practitioners can rely on conversation science. This book adapts formal knowledge from the field of Conversation Analysis (CA) to the design of natural language interfaces. It outlines the Natural Conversation Framework (NCF), developed at IBM Research, a systematic framework for designing interfaces that work like natural conversation. The NCF consists of four main components: 1) an interaction model of "expandable sequences," 2) a corresponding content format, 3) a pattern language with 100 generic UX patterns and 4) a navigation method of six basic user actions. The authors introduce UX designers to a new way of thinking about user experience design in the context of conversational interfaces, including a new vocabulary, new principles and new interaction patterns. User experience designers and graduate students in the HCI field as well as developers and conversation analysis students should find this book of interest.
JavaScript Functions and Context

The previous chapter introduced the concept of objects and used the array object to illustrate how objects can be used to help you develop your application.
Novel Use of an Artificial Neural Network to Computationally Model Cognitive Processes in Science Learning

The purpose of this paper is to outline the creation of a computational model making use of an underlying processing element in the form of an artificial neural network (ANN). Within the study, the ANN models multiple conservation tasks as inputs from video game play during a high school science content learning game. This model is based upon the identification of cognitive attributes and integration of two advanced psychological and educational measurement theories. Using the approached of cognitive diagnostics, and item response theory (IRT) data examined for computational suitability. Once initial task response patterns are identified via IRT; the patterns are parametrized and presented to an artificial neural network (ANN) as probabilities. Using the ANN derived Student Task and Cognition Model (STAC-M); the study authors simulated a cognitive training intervention using 100,000 students in science classrooms. Results of the simulation suggest that it is possible to increase levels of student success using a targeted cognitive attribute approach and that computational modeling provides a means to develop future science education research and is a means to test current educational theory.
LibGuides: CSUL 2019: Welcome

Meeting information, agenda and meeting materials for the Council of State University Libraries.
EA-Based Refactoring of Mapped Logic Circuits

The increasing complexity of the designs and problematic scalability of original representations led to a shift in internal representations used in logic synthesis and optimization. Heterogeneous representations were replaced with homogeneous intermediate representations. And-inverter graph (AIG) has been identified as the most promising structure for scalable logic optimization and many efficient algorithms were implemented on top of it. However, the inability of AIG to efficiently represent XOR gates together with heuristic nature of logic optimization algorithms leads to some inefficiency causing that the logic can be further minimized even after it has been mapped. This paper presents an optimization technique based on refactoring targeting mapped combinational circuits. It iteratively selects large cones of logic, optimizes them and returns them back to the original structure provided that there is an improvement in some metric. Performance of the method is evaluated on a set of complex academic and industrial benchmarks. We show that a 9.2% reduction in area can be achieved in average compared to the highly optimized results obtained using the academic state-of-the-art synthesis tool. In average, more than 14% reduction was observed for arithmetic circuits.
Sistem Pakar Diagnosis Penyakit Pada Tanaman Jeruk Manis dengan Metode Dempster Shafer

&lt;p&gt;&lt;em&gt;Orange plants are plants that are cultivated by farmers. This study aims to assist farmers in diagnosing the disease of sweet orange plants using the Dempster Shafer method. Calculating the trust value of the selected symptoms by comparing each weight value of the 2 initial symptoms selected then compared with the weight values of other symptoms so that new symptoms that lead to a disease are produced accompanied by the value of their beliefs&lt;/em&gt;&lt;em&gt;.&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;pre&gt;Keywords:&lt;em&gt;Expert System, Dempster Shafer, Orange plant disease&lt;/em&gt;&lt;/pre&gt;
Review of application-driven quantum and statistical physics, vol. 1: foundations

"Review of application-driven quantum and statistical physics, vol. 1: foundations." Contemporary Physics, 60(1), p. 87
METHODICAL DISCOURSE OF CONDUCTOR-CHOIR TRAINING TEACHER OF MUSICAL ART

The methodical aspects of preparing the future teacher of musical art during obtaining of higher education are studied. It is emphasized on the necessity to enrich the cognitive thesaurus of students, to develop a valuable perception of vocal and choral works, analytical thinking, possession of methods of learning vocal and choral works. The preparation of a teacher for work with choir collective or vocal band is opened. The students' work on the analysis of vocal and choral works, selection of educational repertoire for schoolchildren of different age groups and enrichment of auditory experience has fundamental importance. At this stage, it is necessary to create students' capability to make analysis (musical-theoretical, vocal-choral, performing) and interpretation of choral works, to compose it annotations, to collect and train exercises for developing the vocal-acoustic skills. The approximate vocal and choral analysis of the M. Lysenko Choir "Son" is presented; its general genre features are opened as a musical work intended for choral performance. Based on theoretical knowledge gained during the professional training, acquired methodical skills and independently working out specific choral works, the teacher of musical art can achieve the desired results in musical development of schoolchildren by vocal and choral singing.
Quantum Photonic Neural Networks

We propose an architecture for next generation quantum photonic processors, which maps the features of neural networks into the quantum optical domain. Through numerical simulation we demonstrate a range of new quantum information processing tasks. © 2019 The Author(s)
Ave Verum Pentium: singing, recording, archiving and analysing within the digital domain

This chapter considers the role of technology in recording, processing, and archiving the singing voice. It challenges the predominant theory that the recording chain is deterministic and free of context and suggests that those who use technology in the recording process often have different needs in technological solutions to problems as well as the scientific understanding required for effective practice. This chapter defines sound, how it is captured and the tools used, the differences between analog and digital methods of recording, as well as frequencies, compression, and file size. It attempts to offer readers from different backgrounds a somewhat broader understanding about the recorded voice and reveal and challenge proximate worlds and practices. It emphasizes that outside the highly specialized worlds of research and scholarship in electronics, engineering, and physics, successful recordings are possible when using a systematic approach.
Developing Vocabulary Material using Longtion Autorun Application for Hearing Impaired-Eleventh Grade Learners at SLB Negeri Cerme

In the special education, especially hearing impaired learner, the students also learn English, but the learners have the difficulty in learning English vocabulary. There are several reasons for the learners who have the difficulties in learning English vocabulary. One of the reason is because they have physical and mental weakness. Learners of SLB Negeri Cerme also have the difficulties of learning English vocabulary. To help the learners in learning better vocabulary, the researcher will use longtion autorun application to show the picture, text and translation. Longtion autorun application as the base material of learning vocabulary will help learners achieve better vocabularies, which will make the learners more interested and understand the material easily by using some pictures and exercises. The research and development design uses ADDIE instructional design model, to develop vocabulary material using Longtion autorun application for hearing impaired-eleventh grade learners at SLB Negeri Cerme. The research was conducted in SLB Negeri Cerme, involving three hearing impaired learners of eleventh grade. In this research and development, the steps are: need analysis, design, development, implementation, evaluation. The need analysis gave some explanations; First, analysis of interviews with English teacher about the learning need, second, analysis of interviews with learners about their target need and learning need, third, curriculum document analysis. Researcher created a design instruction called material prototype as a framework that was used in developing syllabus and application. Researcher developed a material according to the result of need analysis and design. The activities of the learning are in three phases (pre, whilst, and post) Strategy. From the result of English teacher assessment, the score was 87,5. While the result of learner’s questionnaire about the product, the total score was 88,3. It belongs to the good category based on scoring. This second draft of material was considered as the final draft. The overall conclusion appears that the learners interested when they learnt English using Longtion autorun application because the materials were easy to understand, interesting, and suitable for eleventh grade hearing impaired learners. The researcher gives some recommendation, the next researcher could conduct the similar project to do the same research with different level and focus in order to enrich the variety of the research. For the teacher, this product could be used as a combination when they teach English to introduce the simple English vocabulary to the learners.
ASSOCIATION PARAMETERS IN SUPPORTING MAJORS AND GPA CORRELATION

Abstract —According to the Educational Psychologist of Integrity Development Flexibility (IDF) that 87% of Indonesian students who were wrong in choosing majors in higher education have caused a number of things such as triggering number of unemployment, not getting the highest GPA, being unable to attend and not optimistic lectures, not interested in study program subjects and the worst impact is drop out. The selection of appropriate majors in higher education is very important, and to assist prospective students in choosing majors needs an online system, so that everyone can access it to assist in the major selections. This system uses association techniques in data mining. The use of the support and confidence parameters is to process the knowledge base in the form of alumni database. The variables used are the names of universities, the categories of colleges, provinces, majors in schools, programs in higher education and GPA. As the initial stage for the knowledge base, the data will be inputted that consisting of 93 universities from 19 provinces throughout Indonesia. Currently the database training is 10,254 records and will produce new information and knowledge about the correlation between majors and GPA.
Dual-Pump Design Enables Novel Photon-Pair Characterization and Engineering

We experimentally demonstrate a dual-pump spontaneous four-wave mixing photon-pair source for which we quantify the noise to determine the generation probability and collection efficiency directly, and that generates photons in pure quantum states. © 2019 The Author(s)
Free Speech in the USA

Edited 13.7.2020. One of our younger readers has been doing some research on free speech and asked if we could add a link here to the information she ...
CURRENT STATE OF USE OF INFORMATION AND DISTANCE LEARNING TECHNOLOGIES IN THE DEVELOPMENT OF SKILLS IN THE ELECTRONIC INFORMATION ENVIRONMENT OF TODAY'S ECONOMISTS

The article addresses the issues the content of advanced training of economists in the electronic information environment and improvement of quality requirements based on modern approaches, periodically during professional activities and issues of improving the methodology of lifelong learning.In addition, forms of distance learning, distance learning methods and the importance of these methods.
Decentralized Isolated Educational Content Aggregation System

In this age of digital transformation, where every industry equips itself to carry out its operations online, it is often the case, especially in developing nations, that many primary and secondary educational institutions lack the means to realize a quality implementation of such transformation.In this paper, we discuss an educational technology platform that enables academic institutions to share, organize and maintain their educational content along with hosting functions including (but not limited to) parent-teacher communication, event notifications and test taking.The platform is presented as an Android app and uses the Google Firebase for data storage allowing seamless scalability and cost-efficiency.
Corpus extraction tool LIST 1.0

The LIST corpus extraction tool is a Java program for extracting lists from text corpora on the levels of characters, word parts, words, and word sets. It supports VERT and TEI P5 XML formats and outputs .CSV files that can be imported into Microsoft Excel or similar statistical processing software.
Implementasi Sistem Payment Toll Dengan Barcode Reader Berbasis Mikrokontroler

Nowadays, to pass through the toll road, mostly riders often complain that the queue is quite long and quite long. Implementing Tool for Toll Payment Systems Using a Microcontroller-based Bar Code Reader is designed to facilitate transaction processing and make the time spent in the process of using the toll road more efficient. This paper describes the process of making automatic vehicle detection devices so that drivers do not need to stop to process the toll road usage. This tool is designed using a barcode reader as input data, Ethernet shield as an internet network (local), Arduino Uno as a process controller in sending data from barcode reader into SPT application, servo motor / as a driver to automatically open the gate and Android as notification/notification for toll road users. From the results of testing all input and output functions can be performed. In testing using a toy car unit, the reading distance of the barcode with the barcode reader is ± 7cm. In this case, the system can run well and has a pretty good performance because the barcode reader can read a maximum of ± 15cm.
ENHANCEMENT OF ELECTRICAL ENERGY EFFICIENCY BY “INTERNET OF THINGS” 

ABTRACTThis paper goals at studying the place and possible contribution of "Internet of Things" (IoT) in the context of the EU's ambitious climate and energy targets for 2020.Using qualitative procedure, we are mainly concentrating on Demand Side Management (DSM) as an effective method in balancing the load of Electrical Distribution Networks.The role of IoT in DSM is to enable and enhance electrical energy peak demand reduction and its maximum uniform time--distribution achieved through society's eco education.Using computational tools such as Data Mining and Recommender System we can achieve results at the level of electrical energy distribution network reflected in peak reduction and its uniform time distribution.
Automated essay scoring using machine learning

Through this project, we aim to build a linear regression model for automated essay grading. Essays form a huge part of certain college applications and are a part of major competitive exams such as GRE, GMAT etcetera. Manually grading the essays can be extremely time consuming and pressurizing for the instructor. To make these tasks simple, we can train an essay grading program to do the grading automatically. The aim of the grader would be to predict the score of the essay with as much accuracy as possible. The machine assigns scores and should be near the human grader’s score. A dataset of around 2000 essays was used. The essays were graded on the basis of parameters like word count, coherence, number of long words, correct grammar, etc. Feature selection is used to arrive at the most accurate score prediction.
College Students Understanding on Spectroscopy Topic Using STAD Cooperative Learning Combined with Moodle

Abstract : Spectroscopy is an abstract and difficult topic in chemistry. Students should be able to explain this concept. The purpose of this pre-experimental research was to explore the understanding of students about spectroscopy using STAD cooperative learning combined with Moodle. A sample of this study were 34 fifth-semester college students majoring at Chemistry studying at the University X. The results showed the students’ understanding on tools instrumentation and their functions on Raman spectroscopy, photometric titration method, the function of the components in IR spectrophotometer, compounds based on transition-absorbing electrons, and the basic principle of atomic spectroscopy material were low. Key Words : students’ understanding of spectroscopy concept, STAD cooperative learning, moodle Abstrak : Spektroskopi merupakan salah satu materi yang bersifat abstrak dan sulit. Mahasiswa harus mampu menjelaskan konsep tersebut dengan baik. Penelitian pra-eksperimental ini bertujuan untuk menggali pemahaman materi spektroskopi mahasiswa pada pembelajaran kooperatif STAD yang dipadu dengan Moodle. Sampel penelitian adalah mahasiswa program Pendidikan Kimia Universitas X semester 5 yang berjumlah 34 mahasiswa. Hasil penelitian menunjukkan bahwa pemahaman mahasiswa pada alat-alat instrumentasi pada spektroskopi Raman beserta fungsinya, metode titrasi fotometrik, fungsi komponen-komponen dalam spektrofotometer IR, macam-macam senyawa penyerap berdasarkan transisi elektronnya, dan prinsip dasar materi spektroskopi atom tergolong rendah. Kata kunci : pemahaman mahasiswa pada materi spektroskopi, pembelajaran kooperatif STAD, moodle
Differential Evolution Based Model Selection Approach for Machine Learning

As the application of big data becomes more and more popular, machine learning algorithms are changing with each passing day, and the models produced by machine learning are increasingly diversified.The focus of big data applications has gradually shifted to the prediction and inference of models.How to choose the most suitable model for enterprise application scenarios among many machine learning models has become a topic of research that has attracted much attention.Ensemble methods have been proposed to discover best model by multiple training phase.Studies of finding best combination within multiple modes are still few.Configuring different machine learning models with appropriate parameters and looking for parameters is an NP-hard problem, which requires an optimization algorithm.This study proposes to apply differential evolution algorithm to integrate multiple trained machine learning models into an appropriate model.In this paper, the regression model is taken as an example and the differential evolution algorithm is compared with the particles swarm optimization algorithm.The results show that the differential evolution algorithm has better performance.
Variational Quantum Unsampling on a Programmable Nanophotonic Processor

We introduce the Variational Quantum Unsampling (VQU) protocol, a nonlinear quantum neural network approach for verification and inference of near-term quantum circuits outputs. We experimentally demonstrate this protocol on a quantum photonic processor. © 2019 The Author(s)