Reviewerly/exHarmony huggingface dataset:
A SURVEY ON THE STUDENTS’ READING HABIT IN UNIVERSITY OF PGRI WIRANEGARA

The objective of this research is to know and describes the students’ reading habits of 2016 academic year in PGRI Wiranegara University. The subject of this research is all of the study programs of 2016 academic year, which consists of 138 students. The method used in this research is descriptive quantitative research. This research used the questionnaire as the instrument of data collection using Google form. The questionnaire was distributed starting from May 18th, 2020 until 31st May 2020. The questionnaire involved seven indicators of reading habits. The result of this research showed that the data of attitudes toward reading reveals that most of the students 53,6% liked reading, the frequency of their reading habit was 38,4% of students often read and they spend time one hour to read, but the family's motivation by students was nearly no motivation. It means that the students' reading habit of 2016 academic year was good but no motivation by the family. The suggestion of this research is we get knowledge and help us to do a thesis or test, so the researcher suggestions to promote English reading habits among college students.
The social life of disaster information: cultivating resources for emergent information infrastructures in Nepal

Information infrastructure studies in the fields of human-computer interaction (HCI) and science and technology studies (STS) have sought to understand the ways in which information and communication technology have enabled information sharing and work practice in science and other enterprises, as well as contribute to the design of such systems. While humanitarian information infrastructures may usefully be viewed as emergent, the recurring nature of large-scale international disaster relief activations creates the possibility for, innovations in humanitarian technology to become expected assets during responses to future emergencies. This chapter focuses on the practices of technologists, community organizers, and government officials that cause such infrastructure to emerge. We look at the "creative acts of infrastructuring"] that support the creation, sharing, and use of critical information products in the wake of a major natural disaster. In particular, we draw attention to the resources that enabled them to accomplish their infrastructuring activities. Our study thus seeks to identify the resources that humanitarian technologists drew upon to support their efforts toward the infrastructuring of a particular set of information infrastructures. This focus on the resources that support infrastructuring allows us to chart the relationship between the investments made in building local capacities and networks related to information technology with the events that took place during the response to the 2015 Nepal earthquakes.
PENGEMBANGAN MEDIA PEMBELAJARAN KARTU AJAIB UNTUK MENINGKATKAN KEMAMPUAN MEMBACA DI KELAS 3 MADRASAH IBTIDAIYAH

In general, reading activities are very important, especially for SD / MI students. However, many teachers have not been able to develop students' reading skills. This is due to the lack of learning media for reading. This study aims to develop a magic card learning media that is suitable for improving students' reading skills in grade 3 MI. This type of research is research and development or what we usually call R&D (Research and Development) by following the procedures from Borg and Gall. The development procedure consists of 5 stages used by researchers, namely: (1) Potential and problems, (2) Data collection, (3) Product Design, (4) Product Validation, and (5) Product Revision. The research stages included the media product development stage, the material expert validation stage, the media expert, and the product trial stage. The product trial stage was not carried out due to limited time and places where schools were closed due to the corona outbreak pandemic (covid 19) so that researchers only arrived at the validation stage. The product trial stage required face-to-face because in this study the researcher needed to know how much the students' reading ability increased. The results of this development research indicate that the magic card learning media is suitable for use as a learning medium after passing the validation test of material experts and media experts. The average score obtained as a result of material expert validation is 4.1 and is included in the Good category. The average score obtained as a result of the media expert's validation was 4.25 and was included in the Good category. The two stages of the product validation trial stated that it was feasible to be tested on 3rd-grade students of MI Miftahul Muta'alimin Balad.
Kesulitan Mahasiswa Dalam Menganalisis Wacana Lisan (Spoken Discourse) Pada Kajian Discourse and Conversation

Discourse Analysis examines the nature of language and the use of language in communication and also research and analyzes language use naturally, both spoken and written. The form of discourse is divided into two; namely spoken discourse and written discourse. There are several types of studies in discourse analysis which aim to analyze both spoken and written language and one of them is discourse and conversation. The scope of this research discussed about students’ understanding in analyzing spoken discourse in discourse and conversation. The research method used descriptive qualitative research. The source of data was the sixth semester students at English department IAIN Takengon. The number of sample was 18 students of English department. The techniques of data collection were observation, interview and documentation. Based on the result of research, it can be concluded that the sixth semester students of English department IAIN Takengon still have difficulties in analyzing discourse and conversation. From the result of research, it can be seen that the total sum of error in discourse and conversation about transcription convention was 13 errors, for sequence and structure in conversation was 25 errors, for preference organization was 8 errors, for feedback was 8 errors and 4 errors for repair.
Neuro-Symbolic Constraint Programming for Structured Prediction.

We propose Nester, a method for injecting neural networks into constrained structured predictors. The job of the neural network(s) is to compute an initial, raw prediction that is compatible with the input data but does not necessarily satisfy the constraints. The structured predictor then builds a structure using a constraint solver that assembles and corrects the raw predictions in accordance with hard and soft constraints. In doing so, Nester takes advantage of the features of its two components: the neural network learns complex representations from low-level data while the constraint programming component reasons about the high-level properties of the prediction task. The entire architecture can be trained in an end-to-end fashion. An empirical evaluation on handwritten equation recognition shows that Nester achieves better performance than both the neural network and the constrained structured predictor on their own, especially when training examples are scarce, while scaling to more complex problems than other neuro-programming approaches. Nester proves especially useful to reduce errors at the semantic level of the problem, which is particularly challenging for neural network architectures.Sub
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise As Much As Possible

We propose Preferential MoE, a novel human-ML mixture-of-experts model that augments human expertise in decision making with a data-based classifier only when necessary for predictive performance. Our model exhibits an interpretable gating function that provides information on when human rules should be followed or avoided. The gating function is maximized for using human-based rules, and classification errors are minimized. We propose solving a coupled multi-objective problem with convex subproblems. We develop approximate algorithms and study their performance and convergence. Finally, we demonstrate the utility of Preferential MoE on two clinical applications for the treatment of Human Immunodeficiency Virus (HIV) and management of Major Depressive Disorder (MDD).
Quality map guided parallel phase unwrapping algorithm for multi-lateral shearing interferometry

Good robustness and fast processing speed are the two main aspects of phase unwrapping algorithm for two-dimensional interferogram. Multi-lateral shearing interferometry requires the use of multidirectional differential wavefronts to reconstruct the wavefront to be measured, which leads to higher requirements on the phase unwrapping speed of the interferogram. The quality map guided algorithm is a reliable algorithm in the phase unwrapping of two-dimensional interferogram. In this paper, the computer unified device architecture (CUDA) programming platform is used to realize the parallel processing of the phase derivative variance map, the maximum phase gradient map, and the pseudo-correlation quality map, in order to improve the speed of phase unwrapping. Parallel calculations are respectively performed on the variance of the wrapped phase gradient in the horizontal and vertical directions in the phase derivative variance map, the wrapped phase gradient in the horizontal and vertical directions of the maximum phase gradient map, and the sine and cosine values of the wrapped phase in the pseudo-correlation quality map. Finally, the CUDA instructions are used to distribute the calculation task and complete the parallel calculation of the quality map. The computer-generated multi-lateral shearing interferograms are used for simulation analysis. The results show that for the same interferogram of 512×512 pixels, the processing speed can be approximately increased by 3 times on the Graphics Processing Unit (GPU) by performing parallel calculation to generate the quality maps. The fastest parallel processing time is 7.34ms for generating the derivative variance map. As the number of pixels increases, GPU processing speed becomes more advantageous, far exceeding that of CPU. Using the self-made quadriwave lateral shearing interferometer, the speed and accuracy of the three quality map guided phase unwrapping algorithms are compared and analyzed. The experimental results show that the derivative variance quality map, which shows the fastest parallel processing speed and the smallest measurement error among the three kinds of quality maps, is more suitable for the parallel phase unwrapping of multi-lateral shearing interferograms.
The Policy Networks of the Korean International Migration Policy: Using Social Network Analysis

This research adds value to the extant international migration policy studies by placing a greater focus on the ‘processes’ of the Korean international migration policy changes. Specifically, this study pays special attention to policy networks in the process of adopting ing the Employment Permit System for Foreigners (EPSF), one of the most important policy changes in Korean international migration policy history. On the basis of the Advocacy Coalition Framework, this research examines the policy network structure that describes the relationships between policy actors at network levels. The results found that the communication network is more hierarchical than the relational network at the global network level, a government-led advocacy coalition was influential in advocating EPSF at the coalition network, and the coordinating role of policy actors such as Office for Government Policy Coordination and New Millennium Democratic Party was significant in the policy process at the egocentric network level.
Readiness and Acceptance of Maternity and Community Undergraduate Nursing Students for Adopting E-Learning during COVID 19 Pandemic

Background: Electronic learning (E-learning) is the most suitable solution for academic universities to continue the education process during the coronavirus disease 2019 (COVID-19 pandemic). Aim: This study aimed to assess the readiness and acceptance of maternity and community undergraduate nursing students for adopting E-learning during COVID-19 pandemic. Setting: This study was conducted at the Faculty of Nursing, Mansoura University. Egypt. Subjects: A nonprobability purposive sample of 401 regular maternity and community undergraduate nursing students was enrolled in this study. Data collection tool: An online questionnaire was used to assess the general characteristics, readiness, and acceptance for adopting E-learning of the nursing students. Results: More than half (52.6%) of the students under the study were ready for adopting E- learning. Additionally, less than half (48.4%) of the students accepted E-learning. Conclusion: Around half of the studied students were ready and accept to adopt E-learning during COVID-19 pandemic. Recommendations: Organizational investment for technological software, hardware, or license is essential to increase the acceptance and readiness rate of students at universities for adopting E-learning. Moreover, the development of training workshops to increase students’ skills in using technology for education is important.
Voice Assistants and Chatbots Hands on Essentials of UI and Feature Design Development and Testing

Intelligent virtual assistants are software applications that is designed with the motive to search and present the information that user demands after retrieving it from the internet. The core of the intelligent agents is Artificial Intelligence (AI). It has multiple methods of interaction like Text, which includes Chatbots, then Voice, which includes Amazon Alexa on Amazon Echo device, Siri on an iPhone, Google Assistant on Android and by taking or uploading images, for example, Samsung Bixby on Samsung Galaxy S8. Chatbots are software applications that simulates a chat (conversation) with users in the natural language using natural language processing (NLP) with the help of a messaging application, websites or mobile applications. From the technological perspective, NLP has been leveraged by Chatbot to represent simple question and answering system. The backend of the chatbot working performs two tasks: first, User Request Analysis and second, Returning the Response. There are basically three types of chatbots: Rule-Based Chatbots - People interact with bots only by clicking the buttons or by using predefined options; these are good for leads. Intellectually Independent Chatbots - This bot learns from user inputs and requests by using the concepts of Machine Learning. AI - Powered Chatbots - It combines the best from rule-based and intellectually independent bots and it uses free language but also uses predefined flow to solve user problems.
Application of the C4.5 Algorithm Determination of Depreciation Classification Volume of Fertilizer on Storage Warehouse

The problems faced by the fertilizer warehouse PT. Iskandar Muda currently shrinking the volume of fertilizer for storage in warehouses, which is often reduced, is not yet known by the management. In reducing the volume of this fertilizer, the author wants to apply the C4.5 Algorithm to help in making decisions. From all the existing data will be classified and predicted, from the classification results will present the rules. So that it can be easily understood in natural language. Based on the application of the C4.5 Algorithm in the classification technique of fertilizer volume shrinkage on storage in the warehouse at the Pupuk Iskandar Muda warehouse, the results of this study show that 1) the C4.5 algorithm with the decision tree method can provide executive information and the system is used to describe processes related to depreciation classification. 2) The C4.5 algorithm is considered as an algorithm that is very helpful in classifying data because the characteristics of the classified data can be obtained clearly, both in the form of a decision tree structure and rules or rule-if-then. 3) Form a decision tree in providing recommendations for decision making.
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands.

The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power of natural language processing to the command line. Participants were tasked with building models that can transform descriptions of command line tasks in English to their Bash syntax. This is a report on the competition with details of the task, metrics, data, attempted solutions, and lessons learned.
Design and Implementation of Music Teaching Management System Based on Modern Information Technology

Information management of music teaching refers to the full penetration of information technology in music teaching management activities, so as to achieve a high degree of integration and sharing of music information. The application of modern educational technology, as an effective method to solve the problems of traditional music teaching and improve college music teaching, has brought many influences to college music teaching. The informatization construction of teaching management is the foundation and key link to realize the modernization of university education. In the actual construction process, how to integrate the brand-new development concept and make the university music education build a by going up one flight of stairs is the primary problem facing universities at present. This paper analyzes the application of modern educational technology in music teaching, and puts forward the design and implementation scheme of university education and teaching management system under the modern information technology environment. Teachers should pay attention to the training of students' music skills, and at the same time, strengthen the training of students' ability to adapt to changes and analyze and deal with problems, and set scientific and reasonable goals according to students' actual situation.
Analisis Sentimen Kepuasan Pelanggan Terhadap Produk dan Pelayanan PT Pertamina Pada Twitter Menggunakan Algoritma Naïve Bayes

PT Pertamina is one company that still uses Twitter. With the existence of Twitter, PT Pertamina can find out by looking at the public's complaints about PT Pertamina's products and services. The number of public comments on Twitter regarding PT Pertamina makes it difficult for PT Pertamina to segment in the form of positive comments, negative comments, and neutral comments. Not only that, PT Pertamina itself also finds it difficult to distinguish between comments related to SPBU (SPBU category) and comments related to SPBE (SPBE category) because on the twitter all comments are combined into one (not categorized by SPBU and SPBE). So that to be able to help obtain this information, segmentation and categorization are needed which should make it easier for PT Pertamina to pay more attention to PT Pertamina itself. The process that can be used to deal with these problems is by using Text Mining to find words that can represent the content that is was in the comments regarding PT Pertamina on Twitter, then classified using the Naive Bayes algorithm. Output of the sentiment analysis system is in the form of positive segmentation, negative segmentation and neutral segmentation. Then there is product categorization based on gas station services and services. So that the results of the segmentation and categories can be a reference for PT Pertamina to improve and improve the quality of products and services to the community. The test results using a k-fold value of 2 to 10 and tested 10 times for each k value resulted in the accuracy of the naive Bayes algorithm around 99.393% From 627 twitter data collected in the system, it can be seen that public sentiment tends to be positive in the gas station category, around 40.07%. Also, public sentiment tends to be neutral in the SPBE category at around 37.50%.
Tools for the design of quantum repeater networks

The Internet, a global network of communicating computers, has profoundly changed our lives, both in the way we work and relax. Quantum computers are a fundamentally new type of computer which brings certain computational tasks within reach, for example chemistry simulations for a reduction in global energy consumption. The Quantum Internet, the vision of a global network of quantumcomputers, combines these two,with applications such as secure quantumcomputing in the cloud. A barrier to the realisation of a Quantum Internet is the loss of transmitted quantum information, usually encoded in particles of light. This fundamental limit can be overcome by splitting up the distance into segments and positioning so-called quantum repeaters in between. In principle, chains of quantum repeaters can extend the transmission range of quantuminformation to an arbitrarily long distance. In this thesis, we consider the type of quantum repeater closest to experimental realisation, which is based on quantum memories for storing quantum information and probabilistically succeeding operations on them. Researchers have proposed a multitude of such quantum repeater schemes on the drawing board. We develop tools to analyse how these quantum repeater schemes will perform when implemented on real hardware suffering from time-dependent noise, in particular imperfect quantum memories for storing quantum information. Such time-dependent noise is often hard to capture, due to its complex interplay with the random time that these quantum repeater schemes need to finish. Our tools thus help to bridge the gap between theoretical proposals for quantum repeaters and the hardware components that are currently experimentally available. On the one hand, they enable optimisation over the design of quantum repeaters, while on the other hand they provide us with an indication of the hardware components whose improvement will pay off most to bring quantum repeaters to realisation.
ЗНАЧЕНИЕ БИЗНЕС-ИНФОРМАТИКИ В СОВРЕМЕННОЙ ЭКОНОМИКЕ

This article examines the development and directions of Business Informatics as a modern science, the need to use information technology. The analysis of specialties related to information and communication technologies is carried out, the types of activities of are studied, the profession of business informatics is assessed on the labor market in Russia.
A frequency-shifting technique for pixel-wise absolute phase retrieval

A more general technique termed frequency-shifting (FS) is proposed, based on which the behavior of periodicity is eliminated and absolute phase can be retrieved pixel-wisely without any phase unwrapping.
Linear Regression Optimization using Gradient Descent Algorithm to Predict Smartphone Feasibility

With the development of technology today, even in the future, smartphone sales are increasingly growing and more and more competitive in the world of technology, where there are more and more interesting features with specifications that exist in smartphones such as Ram, Rom, Storage and Processor which can affect the benchmark score, the higher the benchmark, the better the smartphone. So that consumers are faced with difficulties in choosing the smartphone they want. For this reason, we currently aim to build a system that will find out a prediction of the feasibility of a smartphone by applying the Linear Regression method with a gradient descent algorithm which will help provide solutions to consumers regarding the performance and smartphone benchmark expectations they need.