Reviewerly/exHarmony huggingface dataset:
Text Mining

Text mining is such a large topic in data mining that it can be a separate field. It is also so important and has so many applications that a typical data mining book will never miss. So far, all the data we have been using are structured data. By definition, structured data indicate that the data are arranged in a specific format such that they can be easily processed by computer programs. The data we have been using have already been arranged in a table format, a format that is requested by all the data mining methods we have learned. However, text data, what text mining methods work with, is a form of unstructured data and is usually sequential data. Other forms of unstructured data include audio files, images, and so on.
IMPLEMENTASI PERATURAN PERUNDANGAN UU. NO 31 TAHUN 2000 TENTANG DESAIN INDUSTRI BERBASIS INFORMATION TECHNOLOGY

Academic achievement is one of the major subjects in the educational researches.Academic achievement is defined as the outcomes of the education. Preventingstudents from failure is related with identifying the factors affecting the achievement.By defining the important factors affecting the students’ achievement, failure can beunder controlled [Ozguven, 1974]. Education is a complex process and many factorsdirectly or indirectly may affect achievement. Besides, it is difficult to properly definethe major factors influencing students' achievement. Although researchers haveidentified several factors affecting the student achievement, there are still somearguments about them. Some researchers attribute the student’s achievement to theschool; others indicate that the school makes little impact on academic outcome. Otherresearchers say that the effective teacher is the only one who can play the main role interms of student progress. All the factors such as teacher, school context, classroomcontext and the community around the school contribute or impact student’sachievement somehow [Harris, 1999]. In all these thoughts, we can see that there arethree common factors affecting the students’ achievement. Factors related withteachers, students and lastly environment. All these factors are affective on thestudents’ grade more or less. In our research, we handle the students’ perspective andsearch for the factors affecting the students’ achievement i n their demographic itemssuch as age, sex, and their academic background such as high school type, grade,University Entrance score, their families’ social and economic status, income, housing,computer knowledge skills and social behaviors and mannerism. The aim of this studyis to find out what kinds of factors have effects on students’ exam success among thestudents at School of Transportation and Logistics by using the path analysis.
QL= languages

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Physics News

Physik in unserer ZeitVolume 52, Issue 1 p. 11-11 Treffpunkt Forschung Physics News First published: 04 January 2021 https://doi.org/10.1002/piuz.202170109Read 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. Volume52, Issue1January 2021Pages 11-11 RelatedInformation
A Research on Electric Load Forecasting Factors Effecting and Methods Involved

Why load forecasting? And what are the methods are there up to now and methods yet to come in future to do electrical load forecasting. This paper presented a detailed study on electrical load forecasting with traditional; Knowledge based expert systems, artificial intelligent techniques and Hybrid techniques (EMD and ANN) with a brief explanation about the conventional and non-conventional methods of electrical load forecasting. And a very clear individual comparison of both conventional and non-conventional methods.
Extending Features with Plug-ins

A plug-in is a software extension package developed that extends the capabilities of FileMaker by adding new functions and script steps. Plug-ins for FileMaker are available from third-party vendors, which means they involve an added expense and logistical considerations for installing and maintaining them over time. However, a good plug-in can be worth the effort since the features they provide would be difficult or impossible to achieve using only built-in tools. This chapter covers basic plug-in concepts.
Now Inc to purchase Flex Flow

Distributor Now Inc has entered into an agreement to acquire substantially all of the assets of GR Energy Services' Flex Flow business, mainly relating to the rental, sale and service of surface-mounted horizontal pumping systems and horizontal jet pumping systems.
Research collaborations—Foundations of deep learning (NSF)

Federal Grants & ContractsVolume 44, Issue 6 p. 2-2 Grant Alerts Research collaborations—Foundations of deep learning (NSF) First published: 17 February 2020 https://doi.org/10.1002/fgc.30907Read 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. Volume44, Issue620 February 2020Pages 2-2 RelatedInformation
Information Representation

This chapter deals with the information representation in neural networks and the description of the information content of several types of neurons and networks using the concept of sigma-algebra. The main idea is to describe the evolution of the information content through the layers of a network. The network’s input is considered to be a random variable, being characterized by a certain information. Consequently, all network layer activations will be random variables carrying forward some subset of the input information, which are described by some sigma-fields. From this point of view, neural networks can be interpreted as information processors.
Reinforcement Learning

In this chapter, we will introduce the fundamental concepts of reinforcement learning such as Bellman equation, Q-learning, deep Q-learning, etc. We will introduce why reinforcement learning is thought as a method of deep learning. Then, mathematically, we will introduce optimization and data fitting, and understand how these two subjects could be applied to deep learning, especially reinforcement learning.
Chapter 1: What is a signal?

PreviousNext No AccessUnderstanding Signals: Basic waveform analysis from a geophysical perspectiveChapter 1: What is a signal?https://doi.org/10.1190/1.9781560803584.ch1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Let’s say that you measure something—height, size, strength—and then you measure that same thing again at a different time or in another place. If you record and present those measurements in some way, we can call this a signal. Permalink: https://doi.org/10.1190/1.9781560803584.ch1FiguresReferencesRelatedDetails Understanding Signals: Basic waveform analysis from a geophysical perspectiveISBN (print):978-1-56080-357-7ISBN (online):978-1-56080-358-4Copyright: 2019 Pages: 94 publication data© 2019 All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transcribed in any form or by any means, electronic or mechanical, including photocopying and recording, without prior written permission of the publisher.Publisher:Society of Exploration Geophysicists HistoryPublished in print: 01 Jan 2019 CITATION INFORMATION (2019), "Chapter 1: What is a signal?," Geophysical Monograph Series : 1-2. https://doi.org/10.1190/1.9781560803584.ch1 Plain-Language Summary PDF DownloadLoading ...
Extrapolation of microearthquake populations to predict consequences of low- 3 probability high impact events: the Pohang case study revisited 4 5

The November 2017 magnitude (MW) 5.5 Pohang, Korea, earthquake, induced by an Engineered 24 Geothermal Systems (EGS) project, caused one fatality and ~US$300M of economic 25 consequences. It has been proposed that a significant probability of such losses was predictable 26 beforehand, from the small earthquakes caused by well-stimulation, so the project should have 27 been suspended, implying that its developer was remiss for not doing so. This argument depends 28 on the low (~0.61) estimated b-value of this earthquake population. However, it is shown that 29 many of the magnitude determinations are inaccurate (underestimated) and the true b-value is 30 higher (1.12 for one subset). The probability of any earthquake as large as MW=5.5, predicted 31 beforehand by extrapolation, was thus much lower than has been claimed. This analysis 32 highlights the necessity of taking care over accuracy when reporting datasets like this, especially 33 in situations where such analyses might influence criminal trials of EGS developers.
Storage and query over encrypted sensitive association rules in database

In this modern era of increasing need of data sharing along with data security, processing over encrypted data is highly desirable. Data encryption is the most common technique used for maintaining the data privacy. However, when processing is required to be done on this encrypted data it becomes a critical task. In most of the existing theories data need to be decrypted before it is being processed. Decryption before processing leads to serious threat to data. To avoid this, a new mechanism has been proposed and implemented which provides strong data protection. This mechanism helps to query over encrypted data without decrypting it. Experimental results show that the new technique outperforms the existing one in terms of query performance, computation time and storage memory.
Global Overviews of Granular Test Coverage with Matrix Visualizations

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Strategic Trust

Because of threats to the IoTInternet of Things, agents in the network must decide whether to trust other possibly-malicious agents, i.e., must assess their reliability and dependability. Unfortunately, the dynamic and plug-n-play nature of the IoT makes reputation-based trust systems insufficient. Hence, this chapter develops a framework for predictive or strategic trust in which agents make decisions in view of the incentives of the agents with whom they are communicating.
pyUserCalc: A revised Jupyter notebook calculator for uranium-series disequilibria in basalts

Earth and Space Science Open Archive This work has been accepted for publication in Earth and Space Science. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v2]pyUserCalc: A revised Jupyter notebook calculator for uranium-series disequilibria in basaltsAuthorsLynne JElkinsiDMarcSpiegelmanSee all authors Lynne J ElkinsiDCorresponding Author• Submitting AuthorUniversity of Nebraska-LincolniDhttps://orcid.org/0000-0002-0903-7091view email addressThe email was not providedcopy email addressMarc SpiegelmanColumbia Universityview email addressThe email was not providedcopy email address
Applied Cognition

The chapter focuses on the applications of cognition in the real world encompassing both <italic>applied</italic> as well as <italic>applicable</italic> works, that is, the work that could be potentially applied someday to solve real world problems. Applied cognitive psychology emphasizes the applications of cognitive psychology in everyday life. Cognitive processes such as attention, perception, memory, cognitive styles, reasoning, and decision making are deployed in many settings. The research related to applied cognition in social systems has focussed on the complexities of humans working in various domains such as social functioning, education (especially neo-literacy), organizational behaviour, health, consumer behaviour and marketing, clinical setting, life span development, and environment. Cognitive theory is also being applied to the development of technologies which augment various cognitive processes such as memory, problem solving and attention. Finally, the major problems faced by researchers in this field are indicated.
Accessibility of ecological information: The traditional and digital resources at F. I. Tyutchev Regional Scientific Universal Library

Traditional and digital resources acquired by the Library to support educational and research activities are reviewed. The Library’s in-house digital resources are presented. The need for integrated approach to combine traditional and digital resources in library services is substantiated.
Essential Math

This chapter introduces mathematics essential to understand the basics of neural networks. We emphasize you to not skip this chapter if your mathematical concepts are rusty. You may use this chapter as reference when studying later chapters.
Selecting Amongst Multinomial Models: An Apologia for Normalized Maximum Likelihood

The modeling of multinomial data has seen tremendous progress since Riefer and Batchelder’s (1988) seminal paper. One recurring challenge, however, concerns theavailability of relative performance measures that strike an ideal balance between goodness of fit and functional flexibility. One approach to the problem of model selection is Normalized Maximum Likelihood (NML), a solution derived from the Minimum Description Length principle. In the present work we provide an R implementation of a Gibbs sampler that can be used to compute NML for models of joint multinomial data. We discuss the application of NML in different examples, compare NML with Bayes Factors, and show how it constitutes an important addition to researchers’ toolboxes.
PERBANDINGAN GAYA SELINGKUNGDALAM JURNAL ILMIAH ARTIKULASI, BAHTERA, LITERA, SALINGKA, DAN RETORIKA

Abstract: Scientific journals onsite style artikulasi and litera.Scientific articles for the journal is designed for scientific writings published in scientific journals. Before starting to write the article, usually the author already has plans to the journal where the article was about to shipped. Each Publisher should ideally have a Publisher's style/style onsite or house style. This is important because they are written and how writing style, adapted to the style of the journal where the intended recipients. This onsite writing rules may differ between the container issue with one another, both within one agency or institution.
GEO 2021 Learning Conference

Nonprofit Business AdvisorVolume 2021, Issue 378 p. 4-4 Conferences & Events GEO 2021 Learning Conference First published: 11 February 2021 https://doi.org/10.1002/nba.30950Read 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 onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume2021, Issue378March 2021Pages 4-4 RelatedInformation
Language Identification

We introduce the language identification problem—a vital component in a multilingual text analysis pipeline. We discuss the document and word level formulations of the language identification task, briefly discuss supervised solutions, and then present low-supervision methods based on polyglot training that are highly applicable in low-resource settings. We then discuss code mixing, a linguistic phenomenon common in bilingual and multilingual speakers. We extend our language identification methods to model code mixing and measure the extent of English-Hindi code mixing in various social media data sets.
Introducing ExecuteSQL

The Structured Query Language (SQL) is a standardized programming language used to manage relational databases and perform numerous operational functions to the data they store. It was created in the 1970s and became the standard programming language for relational databases. The American National Standards Institute (ANSI) and the International Organization for Standardization (ISO) adopted an official SQL standard in 1986 and 1987, respectively. Since then, many updates to the standard have been released jointly by both organizations. Numerous companies now develop proprietary and open source SQL-compliant database systems. While FileMaker is not built on the standard, it has some support for performing SQL queries internally and externally. In version 9.0 (2007), FileMaker introduced the ability to create live connections to external ODBC data sources (Chapter 7). Version 12.0 (2012) introduced the ExecuteSQL function which can perform queries against FileMaker tables from any calculation within a FileMaker database. A SQL Query is a text-based statement used to instruct a database to perform an action. The most frequently used type of query and the only one supported by the ExecuteSQL function in FileMaker is the SELECT query, which contains data retrieval instructions for a desired result set. Experienced SQL programmers will appreciate the direct back-end access of this feature but may find the limitation constraining. Others may find the divergence from FileMaker’s interface context–centric data access confusing. But the ability to perform a search, sort, and summarize data directly within a calculation formula in a completely context-independent manner is something many will appreciate. It isn’t necessary to learn SQL or to use this command to create databases since it doesn’t replace native FileMaker features. However, it is worth learning for situations where it complements those features more efficiently. This chapter explores the ExecuteSQL function.
Factors Influencing Research Productivity of Private Higher Education Institutions Lecturers in Kopertis Region XII Maluku and North Maluku

A researcher is said to be productive after publishing their findings. The analysis of the Science and Technology Index portal, called SINTA, shows the productivity of researchers of private higher education institutions lecturers in Kopertis Region XII Maluku and North Maluku is still very low. The ranking of private higher education institutions in Kopertis Region XII compared with other universities in Indonesia further strengthens the opinion. This research aimed to determine the factors influencing the research productivity of private higher education institutions lecturers in Kopertis Region XII. The method used was an online survey on 155 samples of lecturers in Maluku and North Maluku. The data obtained were analyzed statistically descriptive. The results showed that individual and institutional factors influence research productivity. Individually, the most prominent driving factor is the perception of the function and benefits of research for human life, while the smallest one is the desires to be famous and financial benefits. The most significant inhibiting factor is the limited cost of research and publication, while the lowest is the motivation to research and publish. Institutionally, library facilities are deemed inadequate, thus contributing less to the increase of research productivity.
Privacy preservation using hybrid cloud environment and Map-Reduce for data deduplication

Cloud is an umbrella wherein the internet based development and services are scrutinised and then explored. Cloud can be entitled as an enigma, wherein the novel opportunities are pioneered to manifest a large scale and flexible computing framework. The actors of a cyber supply chain can be commenced through the important functionalities such as, the utility model of consumption with elasticity, the abstraction of the framework and so on. Hybrid clouds vary greatly in sophistication facilitating portability of workloads across the entire inter-cloud, without compromising user's availability, security, or performance requirements. This paper comprehensively helps to enhance a privacy design model with cloud computing adaptation hitting the fast lane. In the first phase, the system assimilates and devises the formation of hybrid cloud architecture. In the second phase, the system implements various security tactics that are advanced encryption standard (AES) Technique, byte replacement shuffling (BRS) algorithm in consonance with sensitivity level, assigned to the file to preserve privacy. The third phase delineates the optimisation of response time (to upload and download a file) and workflow using Map-Reduce for data deduplication for a cavernous privacy and security solution.
Emerging bimodal biometrics authentication for non-venue-based assessments in open distance e-learning (OdeL) environments

Authentication plays a significant role in security during the non-venue-based examination, as it verifies the identity of online students. Existing authentication techniques have not yet provided an optimal cheating-free, non-venue-based assessment. This research proposes an emerging biometrics technology model of facial recognition and keystroke dynamics (FRAKD) to minimise the problems of malpractice during examinations significantly. Detailed experiments conducted on the Moodle learning management system (LMS), using a client-server platform of 100 diverse students who were captured as a positive data set, produced an average recognition rate (RR) of 85%, while for 20 imposter students, an average rejection rate of 90% was realised. When benchmarked with related solutions, this result shows that using the FRAKD biometrics model in non-venue-based assessment demonstrates reliable security and minimises impersonation more than state-of-the-art practices such as portfolio-based distance assessment without supervision. This improved solution will obviously have great value for ODeL institutions and examination bodies.