Reviewerly/exHarmony huggingface dataset:
Handling Concept Drift in Data Stream Classification.

Data Streams are having huge volume and it can-not be stored permanently in the memory for processing. In this paper we would be mainly focusing on issues in data stream, the major factors which are affecting the accuracy of classifier like imbalance class and Concept Drift. The drift in Data Stream mining refers to the change in data. Such as Class imbalance problem notifies that the samples are in the classes are not equal. In our research work we are trying to identify the change (Drift) in data, we are trying to detect Imbalance class and noise from changed data. And According to the type of drift we are applying the algorithms and trying to make the stream more balance and noise free to improve classifier’s accuracy.
Bitcoin prices and rupee-dollar exchange rates during COVID-19

Bitcoin is the primary cryptocurrency in the world that can be stored and traded through the internet. Digital contracts and cryptocurrencies created on blockchains have now been used in exchanging instruments on the networks and are available online readily. This paper's main objective is to investigate the causal relationship between bitcoin prices and rupee-US dollar exchange during COVID-19. The study used the Granger causality model to study the price behaviour of bitcoin and the rupee-dollar exchange rate. The study found an unidirectional Granger causality existed, where the rupee-US dollar exchange rate affected the bitcoin price in the Indian market during COVID-19. The bitcoins are widely considered as an investment asset in Indian markets, and the rupee-dollar exchange rate has a significant impact on the bitcoin prices.
3V-JMLE: a three-valued score matrix-based joint parameter estimation algorithm in computerised adaptive testing

During the development of a Computerised Adaptive Testing (CAT) system, certain inadequacies were found in the popular Joint Maximum Likelihood Estimation (JMLE) algorithm utilised to acquire the ideal binary score matrix. When we attempted to acquire a question-response matrix from a traditional online test item pool system, more than 90% response elements were NA in the matrix. An ideal binary score matrix could scarcely be derived from it. Thus, we proposed a revised algorithm named three-valued JMLE (3V-JMLE) in this paper. When the response could not generate an ideal binary score matrix, we can transform the non-ideal binary matrix into a three-valued score matrix, and the parameters can be estimated simply by using 3V-JMLE. Experiment results show that 3V-JMLE has the same estimation accuracy and computational efficiency as JMLE. In addition, 3V-JMLE has an extensive range of applications and high testing efficiency.
The Influence of the Information and Communication Technologies on the Future Electronics Engineers' Professional Mobility

In our modern society it is impossible to become an intelligent, creative and professional mobile specialist without the information and communication technologies. We consider the professional mobility definition as an integrative quality of professional conditions on the basic components of professional culture and professional competences. The most important professional competence is the information and communication one. The uses of engineering projects are the most effective information and communication technologies for the future electronics engineers' professional mobility development. We take the projects as an example of using the problem project approach: 1) the modern electronics problems; 2) the electronics issues; 3) the knowledge of the electronics engineer.
Chapter 27 : Surface Related Multiple Attenuation and Imaging

PreviousNext No AccessIllustrated Seismic Processing Volume 2: PreimagingChapter 27 : Surface Related Multiple Attenuation and Imaginghttps://doi.org/10.1190/1.9781560803690.ch27 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract This chapter is an expansion of the introductory multiple and imaging chapters included in Volume 1. This chapter contains two related processing procedures; related because both use surface-related multiples, multiples that exist because of a free surface, a subsurface-to-air interface. In this chapter first we will explain a technique for attenuating surface-related multiples, and then we will explain how to create subsurface images using these multiples. Permalink: https://doi.org/10.1190/1.9781560803690.ch27FiguresReferencesRelatedDetails Illustrated Seismic Processing Volume 2: PreimagingISBN (print):978-1-56080-368-3ISBN (online):978-1-56080-369-0Copyright: 2020 Pages: 326 publication data© 2020 Copyright © 2020 Society of Exploration Geophysicists. All rights reserved. This book or parts hereof may not be reproduced in any form without written permission from the publisher.Publisher:Society of Exploration Geophysicists HistoryPublished in print: 31 Dec 2020 CITATION INFORMATION (2020), "Chapter 27 : Surface Related Multiple Attenuation and Imaging," Course Notes Series : 191-210. https://doi.org/10.1190/1.9781560803690.ch27 Plain-Language Summary PDF DownloadLoading ...
COVID-19 CORONAVIRUS SCREENING ANALYSIS NEURAL NETWORK TECHNOLOGY

Low-cost, reliable and quick screening diagnosis of coronavirus can be implemented on the basis of intelligent technologies for analyzing a set of signs and symptoms with solving the problem of pattern recognition in the basis of artificial neural networks. The high degree of coronavirus infection diagnostic procedure uncertainty, the vector dimension of input factor-symptoms, fuzzy conditioning and poor formalizability of the subject condition connection with these symptoms require appropriate analytical tools. An analysis of the problem and possible solutions allows justifying the feasibilit y of implementing screening diagnostics as a solution to the problem of nonlinear optimization in a multidimensional space of high-dimensional factors and states. Artificial neural networks with compulsory training on a representative sample were chosen as a tool for implementing the project. The proposed technology brings diagnostics of coronavirus infection closer to full automation, robotization and intellectualization of complex monitoring (diagnostic) systems as the most promising technology for pattern recognition in systems with a high degree of entropy and allows you to solve the problem at the lowest cost and required performance indicators.
Operation Support System for Electric Wheelchair Using the Remaining Functions of a Thumb for Muscular Dystrophy Patients

For patients with muscular dystrophy, a motor dysfunction, who have difficulty operating an electric wheelchair with joysticks, a simplified one-input device is used. However, avoiding obstacles can be time-consuming. In this study, we analyzed the motor functions of the thumb of a patient with severe muscular dystrophy and identified the operations that did not cause physical fatigue. Then, we developed an operation support system to continuously operate. Finally, we conducted experiments comparing the proposed system with the conventional system and verified the effectiveness of the proposed system based on the steering accuracy of the electric wheelchair and the task completion time.
Supplemental Material: A 3 b.y. record of a biotic influence on terrestrial weathering

Major-element geochemical data and mass balance calculations used in this study.&lt;br&gt;
The RFP Process at the University of Memphis: A Work in Progress

SUMMARY. McDonald reported on the process the Memphis area library consortium is following in order to develop an RFP (Request for Proposal) to choose a new integrated library system. The consortium is required by state law to write an RFP for major purchases. The workshop focused on the basic organization needed to achieve their goals and concluded with a question and discussion period. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com &gt; Website: &lt; https://www.HaworthPress.com &gt;]
Research and Application of English Corpus Digitization Using Intelligent Numerical Method and Big Data Technology

Corpus Linguistics is based on the material provided by the corpus for language research. Based on the development of corpus, the article explains the definition and connotation of corpus linguistics, introduces the theoretical basis and historical background of corpus linguistics, and discusses the application of corpus linguistics in foreign language teaching.
The Tries of Stefan Altakov

The article analyzes the artworks by Stefan Altakov, created in the last few years and presented in the virtual exhibition “Tries“ on the website of the project “Art Initiatives 2020”, the project is implemented under the Scientific Research Fund for Sofia University. A few sentences from the text of this article were published at the opening of the respective virtual exhibition.
RETRO +: SQL to SPARQL improvement of the RETRO framework

Semantic web has recently gained a great attention due to its potential for providing a common framework that allows data sharing and reprocessed, relational databases are still the most used. To deal with the variety of modern database formats and query languages, we propose an approach to translate SQL queries into equivalent SPARQL queries for querying resource description framework (RDF) data. The main purpose is to give an extension of the Retro framework by adding a set of algorithms to improve its function. The algorithms in question deal with the conversion of the relevant SQL queries INSERT, UPDATE, DELETE and improve the SELECT query by adding the aggregate function, GROUP BY and ORDER BY in equivalent SPARQL queries and validate all translated queries on allegrograph.
Chapter 8: Fuzzy Clustering Algorithms

Hard (or crisp) clustering algorithms require that each data point of the data set belong to one and only one cluster. Fuzzy clustering extends this notion to associate each data point in the data set with every cluster using a membership function. Since the concept of fuzzy sets (Zadeh, 1965) was introduced, fuzzy clustering has been widely discussed, studied, and applied in various areas. Early work on applying fuzzy set theory in cluster analysis was proposed by Bellman et al. (1966) and Ruspini (1969).
What Is Python?

Python is a modern programming language that supports object-oriented, functional, and imperative programming styles. It is ideal for the beginner because of its readability and ease of use. The upside to all of this is that you can write programs in less lines of code than an equivalent C/C++ or Java program.
Authorship in the Age of Machine Learning and Artificial Intelligence

Abstract A new generation of machine learning (ML) and artificial intelligence (AI) creative tools are now at the disposal of musicians, professionals and amateurs alike. These new technical intermediaries allow the production of unprecedented forms of compositions, from generating new works by mimicking a style or by mixing a curated ensemble of musical works to letting an algorithm complete one’s own creation in unexpected directions or by letting an artist interact with the parameters of a neural network to explore fresh musical avenues. Unsurprisingly, this new spectrum of algorithmic compositions question both the nature and the degree of involvement of the creator in the musical work. As a consequence, the issue of authorship and, in particular, the assessment of the specific contribution of a (human) creator through the algorithmic pipeline may require special scrutiny when AI and ML tools are used to produce musical works.
Analysis on Regional Social Organization Standardization Based on Big Data

Since the issuance of the Plan for Furthering the Standardization Reforms in March 2015, in the more than five years of cultivating and developing social organization standards, government departments and social organizations across the country have actively promoted social organization standardization work, and social organization standards have developed rapidly in China. In order to better study the standardization work of various local organizations, this paper selected Beijing for research based on big data analysis methods. In the process of actively implementing the standardization reform policy, cultivating and developing social organization standards, Beijing's social organization standardization work has achieved remarkable results, but there are also some problems. Based on the data disclosed by the National Social Organization Standard Information Platform, this paper sorts out and summarizes the situation of Beijing's social organizations carrying out social organization standardization work, analyzes existing problems and makes suggestions.
Key Event Planning Issues

Nonprofit Communications ReportVolume 17, Issue 11 p. 8-8 Articles Key Event Planning Issues First published: 10 October 2019 https://doi.org/10.1002/npcr.31332Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume17, Issue11November 2019Pages 8-8 RelatedInformation
A Descriptive Quantitative Study of Students’ Anxiety in Reading and Writing in Learning English at the Eighth Grade of Mts Hadharatul Islamiyah Sipispis

This study was about students’ anxiety in reading and writing in learning English at the eighth grade of Mts Hadharatul Islamiyah Sipispis. In this research, the researcher used quantitative descriptive method. This study is aimed to find out the students’ anxiety level in reading and writing in learning English. The data was collected by using questionnaire with two aspects includes reading and writing. In this study, the researcher found that the students’ anxiety in reading are categorized in low anxiety level there are 6 students (22%), students who categorized in medium anxiety there are 10 students (37%), and the high anxiety level are 11 students (41%). While in writing anxiety in this study shows that the students categorized in low anxiety level are 4 students (15%), in medium anxiety category are 13% students (48%), and the high anxiety category are 10 students (37%). It can be concluded the students’ anxiety level in reading English at the eighth grade of MTs Hadharatul Islamiyah Sipispis is categorized in the high anxiety level. Whereas students’ level anxiety in writing in categorized medium anxiety level.
Research and Application of Artificial Intelligence in Path Planning of 7-DOF Smart Mobile Robot

Objective To model, teach and simulate a 7-DOF Sawyer robot by using the robot toolbox of MATLAB, and to plan and simulate the trajectory of the robot between two points in space. Methods based on the structure of the robot, the improved D-H method was used to build the robot model. Using the functions provided by the MATLAB robot toolbox to model, display and teach the robot; According to the known initial and end angles of the joints and the iterative steps, the motion trajectory of the robot is planned by the quintic polynomial. The robot toolbox provides the function to realize the trajectory planning of the robot, the curve of the Angle, angular velocity and angular acceleration of each joint, and finally the initial position and end position of the robot are constructed by using the fkine function. Conclusion Through simulation, it can be seen that in the process of the robot moving from the initial position A1 to the final position A2, the position of each joint Angle changes steadily, the velocity and acceleration curves are continuously smooth, and the movement process is stable.
Tunisia – Corruption Report

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 12 p. 22827A-22827A Policy and Practice Tunisia – Corruption Report First published: 05 February 2020 https://doi.org/10.1111/j.1467-6346.2020.09298.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue12February 2020Pages 22827A-22827A RelatedInformation
Estimation of Fiber Orientation Distribution in the Carbon Fiber Reinforced Polyamide 6 by the X-Ray Diffraction Image

In discontinuous carbon fiber reinforced thermoplastics molded by kneading resin and carbon fiber, controlling fiber length, dispersion and orientation state is an issue because those dominant mechanical properties of them. Therefore, the methods to measure fiber orientation distribution in the composites are indispensable. X-ray structure analysis is an effective means for the measurement. Because it allows us to acquire data in a short time without destruction of specimens. We established the method for estimating the fiber orientation distribution from the X-ray diffraction image of carbon fiber reinforced PA6 (CFR-PA6). The X-ray diffraction image shows overlapped signals correspond structures form carbon fibers and PA6, respectively. We assumed that the intensity distribution of each signal can be express Gaussian function in diffraction and azimuthal angle direction. To extract signal of carbon fibers from the image, the waveform separation in diffraction angle direction was carried out. Subsequently, the extracted intensity distribution was converted to fiber length distribution by the waveform separation in azimuthal angle direction. This method was applied to CFR-PA6s with known and simple orientation distributions such as pseudo-isotropic and the estimated results almost correspond to the expected values.
Pendeteksian Citra Pengunjung Menggunakan Single Shot Detector untuk Analisis dan Prediksi Seasonality

This study discusses the analysis of retail store with time series method to obtain information about sales trend and seasonality by looking at visitor data and total transaction data at a time period. Data in the form of the number of customers who visit are obtained through CCTV video camera recordings placed at retail store X and the total transaction occurred at retail store X. The visitor counting uses the deep learning method with SSD (Single Shot Detector) object detection framework and MobileNet architecture. The library used to count the number of customers visiting the store is OpenCV, Pandas, Numpy, Dlib, and Imutils. The number of customers visiting the store will then be compared to the number of transactions that occur at the same time so that a conversion rate can be obtained. From here, we can see sales trend that occur at any time. Time series analysis is also carried out to determine and analyze the pattern of data obtained based on certain time to predict the things that need to be done in the future. Through this research, information has been successfully obtained related to seasonality patterns, value and interpretation of retail conversion rates, models for predicting the number of visitors and transactions, and answering the hypothesis with the Wilcoxon test method obtained a p-value of 0,014 which states that the data pattern of the number of consumers is not the same as the transaction data pattern.
Setting Up an Online Survey Instrument for Effective Quantitative Cross-Tabulation Analysis

The building of an online survey instrument involves sophisticated understandings of the research context, research design, research questions, and other elements. A lesser observed need is to consider what types of data analytics will be applied to the findings. With beginning-to-end online survey research suites, it becomes all the more necessary to think through the process from beginning to end in order to create an instrument that achieves all the necessary aims of the research. After all, improper online survey instrument designs will result in makework when it comes time to analyze data and will foreclose on particular data analytics opportunities. (Such instruments also will not have second or third uses after the first one-off.) This chapter explores how to build an effective online survey instrument to enable a quantitative cross tabulation analysis with the built-in analysis Qualtrics.
Automatic reasoning

In this chapter, we will see how to use the HermiT and Pellet reasoners in Python, in order to check the consistency of an ontology and to perform automatic deductions and classification, on the basis of the logical constructors.
Analysis of the Relationship between Wearing a Mask and Facial Expression Recognition

Wearing a mask is mandatory because it is believed to prevent the spread of COVID-19 infection. However, wearing a mask makes it difficult to read facial expressions, which may lead to miscommunication. The purpose of this study is to clarify whether facial expressions and emotions are correctly conveyed to the other person when masks are worn and when they are not. We used a morphing application to create 12 facial images with 100% of the six basic emotions (happiness, surprise, fear, anger, sadness, and disgust) and 50% of the emotions expressed in daily life. In addition, mask images were combined with the mug shots to create a total of 24 patterns of photo samples. A questionnaire survey was conducted on 172 respondents (26 males and 146 females) to evaluate their emotions. The questionnaire consisted of selecting one of the six basic emotions for each evaluation sample. In the "Happiness 100%" category, 100% of the respondents selected "Happiness" for both the masked and unmasked samples, and in the "Surprise 100%" category, 98% of the respondents selected "Surprise" for both the masked and unmasked samples. The increase in the percentage of correct responses without the mask was seen in "50% surprise" (+39%), "50% sadness" (+36%), and "50% happiness" (+30%), indicating that the facial expression intensity was affected by the mask.