Reviewerly/exHarmony huggingface dataset:
The role of social media in the social, cultural and security change of Arab society from the viewpoint of journalists in (Jordan, the Emirates): DOI: 10.46988/IJMMC.02.02.2020.006

The research aims to identify the role of social media in the social, cultural and security change of the Arab community from the viewpoint of journalists in (Jordan and the Emirates) and the media. the results of the study showed that the role of social media in the social, cultural and security change was medium, as the results showed that there were no statistically significant differences in the estimates of the sample members of the study according to the variables in each field of study and in the tool as a whole, and showed the study of the existence of 6 future roles agreed upon by the members of the sample. The study included an introduction and the importance of research, procedural terms and terminology, previous studies, the problem of the research, its goals, its temporal and spatial limits, methods and procedures, society and sample, the study tool, the test of the tool's sincerity, and discussion of results, in addition to the recommendations proposed by the researcher in the light of the study results. This study was conducted in the second half of 2019.
LibGuides: Research Data Management: Data, Archiving and Preservation

A guide to managing outputs of research projects and handling issues such as copyright and data protection laws
A Practical Guide to Multi-Objective Reinforcement Learning and Planning.

Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcement learning and decision-theoretic planning either assumes only a single objective, or that multiple objectives can be adequately handled via a simple linear combination. Such approaches may oversimplify the underlying problem and hence produce suboptimal results. This paper serves as a guide to the application of multi-objective methods to difficult problems, and is aimed at researchers who are already familiar with single-objective reinforcement learning and planning methods who wish to adopt a multi-objective perspective on their research, as well as practitioners who encounter multi-objective decision problems in practice. It identifies the factors that may influence the nature of the desired solution, and illustrates by example how these influence the design of multi-objective decision-making systems for complex problems.
Intermediaries’ Liability in Light of the Recent EU Copyright Reform

The field of copyright law is dynamic and shaped by technological advances. The disruptive digitization of the last three decades has enabled on the one hand more creativity and on the other hand facilitated copyright infringement. Technology itself has become a tool of copyright management and legislators have increasingly entrusted platforms with a critical role in copyright enforcement. The article is set against this backdrop and seeks to explore in particular the recent reform of the European Union’s copyright law that only endorses the two highlighted trends. The article’s focus is on the much-contested Article 17 of the new Directive on Copyright in the Digital Single Market and provides a careful analysis of the legal provision, its standing against other legal acts and existing case-law. The article ultimately provides an appraisal of the likely effects of Article 17 underscoring some of the perils of algorithmic enforcement for creativity online.
Do Word Embeddings Really Understand Loughran-McDonald's Polarities?

In this paper we perform a rigorous mathematical analysis of the word2vec model, especially when it is equipped with the Skip-gram learning scheme. Our goal is to explain how embeddings, that are now widely used in NLP (Natural Language Processing), are influenced by the distribution of terms in the documents of the considered corpus. We use a mathematical formulation to shed light on how the decision to use such a model makes implicit assumptions on the structure of the language. We show how Markovian assumptions, that we discuss, lead to a very clear theoretical understanding of the formation of embeddings, and in particular the way it captures what we call frequentist synonyms. These assumptions allow to produce generative models and to conduct an explicit analysis of the loss function commonly used by these NLP techniques. Moreover, we produce synthetic corpora with different levels of structure and show empirically how the word2vec algorithm succeed, or not, to learn them. It leads us to empirically assess the capability of such models to capture structures on a corpus of around 42 millions of financial News covering 12 years. That for, we rely on the Loughran-McDonald Sentiment Word Lists largely used on financial texts and we show that embeddings are exposed to mixing terms with opposite polarity, because of the way they can treat antonyms as frequentist synonyms. Beside we study the non-stationarity of such a financial corpus, that has surprisingly not be documented in the literature. We do it via time series of cosine similarity between groups of polarized words or company names, and show that embedding are indeed capturing a mix of English semantics and joined distribution of words that is difficult to disentangle.
The relationship of cognitive functions in the development of creative thinking The relationship between cognitive functions in the development of creative thinking

In the article, the need for the development of cognitive abilities is discussed in accordance with modern needs in order to form creative personality. The authors consider such cognitive functions as perception, sensation, attention, memory, imagination, speech, which play an important role in the formation of creative thinking. Today, a decrease in cognitive functions in humans is a barrier to the development of creative thinking. The purpose of this article is to analyze the causes of cognitive decline, to order recommendations for addressing these causes and the development of cognitive abilities. The relationship between thinking and cognitive functions has been explained, reflecting the activity of the brain as a unified holistic structure. The sides of cognitive functions such as implicitness, relevance, selectivity and dependency have been highlighted. The idea of teaching pupils and students in educational institutions not only to the subject, but to the ability to listen, remember, concentrate and solve problems is put forward.
Review of First Breaks Automatic Picking Algorithms Through Several Advanced Modern Software

Summary Nowadays, the question of a quick solution for the a priori statics calculation issue remains acute. In this regard, the search for a solution to reduce the first breaks picking time is a crucial task. The perfect option for processing is a fully automatic picking procedure with virtually zero involvement of the processing operator. Thus, the task of this report is to determine the optimal tool for automatically first breaks picking. As a result of testing several modern software algorithms, the Flatirons Refraction Statics software package (Threshold Auto Picker, mostly the Delay Time Stack Prediction) and the NN_TRAINING and NN_FIRST_BREAK_PICK neural network modules in the Omega Schlumberger 2019.1 software package have chosen as the preferred options for automatic first breaks picking. They are also can be used together in different combinations.
EFEKTIVITAS PENGGUNAAN MEDIA PEMBELAJARAN VISUAL DALAM MENINGKATKAN KOSAKATA BAHASA INGGRIS SISWA SD

The purpose of related service is carried out to provide good learning services to students so that they are more enthusiastic in learning English and do not feel bored quickly. So it is hoped that in the future students can learn and play English in a fun way and have an impact on the progress of their skills in learning English. The method of implementing the related service is carried out by means of practicing the use of visual learning media. The result of practicum is that 75% of students cancapture the essence of learning. This results in an increase in students' vocabulary
Book Review: Cryptocurrencies and Blockchains

Book review of Cryptocurrencies and BlockchainsQuinn DuPont, Cryptocurrencies and Blockchains. Polity Press: Cambridge, 2019; 224 pp,; ISBN 9781509520237, £15.99 (pbk)
Data Generation in Low Sample Size Setting Using Manifold Sampling and a Geometry-Aware VAE

While much efforts have been focused on improving Variational Autoencoders through richer posterior and prior distributions, little interest was shown in amending the way we generate the data. In this paper, we develop two non \emph{prior-dependent} generation procedures based on the geometry of the latent space seen as a Riemannian manifold. The first one consists in sampling along geodesic paths which is a natural way to explore the latent space while the second one consists in sampling from the inverse of the metric volume element which is easier to use in practice. Both methods are then compared to \emph{prior-based} methods on various data sets and appear well suited for a limited data regime. Finally, the latter method is used to perform data augmentation in a small sample size setting and is validated across various standard and \emph{real-life} data sets. In particular, this scheme allows to greatly improve classification results on the OASIS database where balanced accuracy jumps from 80.7% for a classifier trained with the raw data to 89.1% when trained only with the synthetic data generated by our method. Such results were also observed on 4 standard data sets.
Developing and Testing a Tool to Classify Sentiment Analysis

The era has faced with explosive growth in data generation. Data generation has undergone a renaissance change. This availability of data has led a paradigm shift in the Ecommerce sector; data is no longer a by-product of business activities, but are the asset to a company it helps in providing insights which are required in satisfying customers’ needs. This paper provides an overview of Sentiment Analysis of product reviews based on different algorithms and its efficiency in determining positive from negative reviews based on N-gram, Bigram with the application of Count-Vectorizer and TFIDF Matrix. Different classification models have been employed to check the prediction accuracy of the unlabeled text. Based on the above classification and tool has been developed which predicts the incoming reviews and classify its sentiment polarity.
Kubernetes and the Edge

Cloud Computing infrastructures have highlighted the importance of container orchestration software to manage the life cycle of distributed applications. With the advent of Edge Computing era, DevOps expect to find features that made the success of containerized applicationsin the cloud, also at the edge. However, orchestration systems have not been designed to deal withresources geo-distribution aspects such as latency, intermittent networks, locality-awareness, etc. In other words, it is unclear whether they could be directly used on top of such massively distributed infrastructures or whether they must be revised. In this paper, we provide reflections regarding Kubernetes, the well-known container orchestration platform. More precisely, we provide two contributions. First, we discuss results we obtained during an experimental campaign we made to analyze the impact of WAN links on the vanilla Kubernetes. Second, we analyze ongoing initiatives that propose to revise part of the Kubernetes design to better address geo-distribution aspects.
The legacy of Tohoku-oki

Natural HazardsTen years ago, the magnitude 9 Tohoku-oki earthquake rocked Japan and caused massive damage. The earthquake also generated a destructive tsunami, the impacts of which are still being managed today. Kodaira et al. review what was learned from the tremendous number of observations from the great earthquake that unexpectedly ruptured into a shallow part of the megathrust fault. Postseismic deformation is ongoing, as is the risk of another very large normal fault earthquake seaward of the Japan Trench.Science , this issue p. [eabe1169][1] [1]: /lookup/doi/10.1126/science.abe1169
Intersection Regularization for Extracting Semantic Attributes.

We consider the problem of supervised classification, such that the features that the network extracts match an unseen set of semantic attributes, without any additional supervision. For example, when learning to classify images of birds into species, we would like to observe the emergence of features that zoologists use to classify birds. We propose training a neural network with discrete top-level activations, which is followed by a multi-layered perceptron (MLP) and a parallel decision tree. We present a theoretical analysis as well as a practical method for learning in the intersection of two hypothesis classes. Since real-world features are often sparse, a randomized sparsity regularization is also applied. Our results on multiple benchmarks show an improved ability to extract a set of features that are highly correlated with the set of unseen attributes.
A Study on the Cultural Contents of Elementary English Textbooks Based on 2015 Revised National Curriculum - Focusing on 5th and 6th Grade Textbooks

The learning of culture is an integral part of language learning and education. Culture, empathy for other people, and global awareness are important elements in the teaching of foreign languages at the elementary school level. 2015 revised English national curriculum are based on four key competencies: English communicative competence, self-managing competence, knowledge information competence, and consideration and tolerance of the others. This paper is related to the community competence and the elementary English textbook based on the 2015 revised national curriculum are considered the necessity of English cultural instruction in English language classroom. The purpose of this study is to analyse comparatively the contents of the culture, teaching technics of the culture, and the integration of language and cultural contents in 2 types of English textbooks for 5th and 6th graders based on 2015 revised national curriculum. Also this paper suggests a few suggestions for choosing and developing useful cultural elements and strategies for elementary school English language teaching. (Gongju National University of Education)
Colour Feature Analysis for Gender Prediction using Image Processing and Soft Computing Techniques

Soft computing techniques in clustering or classification area have made an amount of progress in last decade or two. Use of camera for image capturing and using it for analysis of any given task with the help of soft computational approach itself gained attraction of most of the researchers. Classification being one of the prime areas of application mostly utilized in majority of industrial, monitoring, security applications. This research work focusing on usage of human hand dorsal portion for gender predication or classification with the help colour feature of an image. An image feature colour of a hand dorsal part can be analyzed in better way for classification or clustering of an image in to two gender class as male or female. The analysis using colour feature is carried out on colour image with the help of Convolutional Neural Network and with the help of image parameters such as pixel values, pixel averaging, channel based specific analyzer etc. Further the results obtained in colour analysis are been merged with a study of texture analysis on same dorsal portion of hand has been judged to obtain desired clustering.
Multiple Simple Sentences or a Single Complex Sentence

When writing a composition, when do you use a sequence of simple sentences, and when do you use a single complex sentence instead? Grammarians have yet to clarify the norms for determining which option to choose. In this presentation, we argue that when it comes to the interchangeability of a complex sentence with a sequence of simple sentences, there is asymmetry between statements of cause/reason and those featuring a contrastive conjunction. We also argue that in the case of lengthy complex sentences, Japanese, unlike Chinese, actively uses non-restrictive noun phrase modifiers to avoid a linear sequence of adverbial (dependent) clauses.
Designing self-monitoring data for chronic care.

When a self-monitoring tool is developed and implemented in chronic care nurses' work, it changes the way nurses accomplish their work, creating new requirements. This article is based on a design ethnographic study that helps us understand the implications of these changes.
Global Public Sentiment About “Use Of Drones” To Fight Covid-19 Pandemic

Covid-19, a global pandemic has affected every sector of life and poses a whole lot of challenges to the entire world. It has forced the governments, organizations and societies to ensure social distancing while carrying out day to day tasks. Drones can play a very important role for surveillance and medical help aroused speedily. Technically, drone is small aerial device loaded features and functions like high definition cameras, sensors to detect the environment around, metallic arms to hold some gadget or deliver groceries or medicines, speakers to make the announcement and many more such features. Big data including articles, blogs and reviews have played a major role in increased awareness and usage of drones during the pandemic. The study provides positive, negative and neutral sentiments related to use of drones during COVID 19. The study will help manufacture of drones, to understand the need and preference of the consumers using online platform.
ASurvey on Reversible Data Hiding Techniques

There is a perpetual requirement for secure data communication in order to transmit a message over a shaky network prone to various attacks. Steganography, which provides a means of cover writing, is effective in hiding sensitive data by embedding them in host images which can be reversibly extracted. Steganography schemes also based on Discrete Wavelet Transformation (DWT), Discrete Cosine Transformation (DCT) and Singular Value Decomposition (SVD) are applicable on spatial domain exclusively. Public key cryptography in Reversible Data Hiding (RDH) imparts double layer security to sensitive images. An overview of various such reversible data hiding techniques are discussed in this paper which throws light on the recent research works in this domain. The application areas of RDH are put forward. The paper concludes by summarizing the studies on different proposed methods. The paper ends with delivering a direction to the future work which gives scope of improvement to existing methodologies.
LibGuides: Criminal Justice Resources: Library Databases

This guide provides resources for information pertaining criminal justice or government. These resources are located on the CCC A-Z Databases List.
Economic growth in Africa: Does gender education still matter?

This study examines the relevance of gender education to economic growth in Africa. This is investigated across different levels of education attainments and human capital stocks for females and males. Using the datasets of Barro and Lee (2013) and Lee and Lee (2016) which cover the period from 1960 to 2010 and static panel estimation methods (pooled, fixed effects and random effects) as well as dynamic GMM methods (one step and two step difference and system GMM) for analysis, it is found that education attainments and human capital stocks (for females and males) are indispensable to economic growth in Africa. Specifically, we find that male education attainment and human capital stock contribute more to economic growth than female education attainment and human capital stock. Based on these findings, it is imperative for governments in Africa to provide a quality education for both genders which would be based not only on theoretical learning but also on practical learning and skill development that would increase the stocks of human capital embodied in both genders. This would enable them to contribute more to economic growth of the continent.
Neural Network Algorithm-based Fall Detection Modelling

Falling is a well-known as a threat among elderly people which may lead to injuries or even death. High recognition of developed fall detection model is very significance for the elderly to detect the falls. Related algorithm for the fall detection has been discussed in depth by researcher during the past decade. However, the improvement of model accuracy is still needed. This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. Two participants involved in obtaining the acceleration and angular velocity. The training is divided into 4 different type of input source. The selection of the model was based on the comparison of optimization epochs, magnitude of validate error or mean square error (MSE), magnitude of correlation performance, the progress of convergence graph in term of MSE performance, accuracy of regression and non-zero value in autocorrelation graph. The simulated result shows that the training model of Type 2 is the best model with a training result of 6.1551mse, 40 epochs, time 0.06s, and 0.92742 accuracy. The result indicates that LM function produce the better solution when compared to another optimization function. In fact, the model accuracy demonstrated that the proposed method was reliable and efficient.
The Construction and Effect Improvement of English Teaching Atmosphere from the Perspective of Classroom Ecology

The ecological classroom has an effective promotion effect on cultivating students 'interest in learning, and is conducive to the formation of students' good learning habits. While the college English ecological classroom plays the above role, it also needs to pay attention to the creation of classroom atmosphere. This article mainly studies and discusses college English courses under the ecological perspective, focusing on the teaching status, classroom atmosphere creation and the effect achieved.
Conclusion: The Promise of a Delighted Environmental Ethic

This book is primarily an interpretation of Walden. Focusing on Walden as I have, however, ignores some of the most interesting scholarship on Thoreau of the past few decades. Sharon Cameron and William Howarth have both argued for the centrality of Thoreau’s Journal in any assessment of his life and work as a whole.1 For both, the Journal is Thoreau’s great work, both by external literary criteria and in his own view. This argument rests on the way in which the ongoingness of the Journal suits Thoreau’s sense that thinking itself is ongoing, that it can never rest, that it always happens in place, as I suggested in the Introduction.
What Is 'Dehumanizing' Speech?

Advocates of speech bans commonly claim that it is legitimate to suppress speakers who dehumanize others. That claim means by definition that the censors' own political philosophies contain no dehumanizing elements. In this article, however, it is argued that there is no such thing as a non-dehumanizing politics, even if some political models are admittedly better than others.
Library Guides: Voyant Tools: An introduction: Interpreting the Voyant Analysis Page

Voyant Tools (http://voyant-tools.org) is a web-based platform for analyzing texts using a bunch of different visualization methods. This guide will walk you through several different ways to analyze texts using this web-based-resource.