Reviewerly/exHarmony huggingface dataset:
Virtual trip along the river Tiber

&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Virtual trip along the river Tiber&amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Augusta Marconi&amp;lt;sup&amp;gt;1&amp;lt;/sup&amp;gt;, Giovanna Mauro&amp;lt;sup&amp;gt;1&amp;lt;/sup&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;sup&amp;gt;1) &amp;lt;/sup&amp;gt;&amp;amp;#8220;James Joyce&amp;amp;#8221; Public High School, Ariccia (Rome) , Italy.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Teachers : A. Marconi, G. Mauro&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Classes: second year, language sections C and D&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;School: Public High school &amp;amp;#8220;James Joyce&amp;amp;#8221; &amp;amp;#8211; Ariccia&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Principal: R. Scialis&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The knowledge of geography gives students the essential elements to get to know and understand the world in all its spacial variability. This accomplishes a strategic function which is all the more relevant nowadays due to the complex processes of change and globalization.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The use of &amp;amp;#8220;Google Earth&amp;amp;#8221; allows a simple but innovative approach, helping the students to acquire an accurate evaluation of the distances between places and to experiment with different ways of perceiving the territory. The work is proposed within the teaching of geography in English, in the second year classes (sections C and D), who are doing the Cambridge Language Course, IGCSE.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The project is constructed in two parts. The first will be held in the technology lab, observing the course of the river Tiber from its source to its mouth, using the application &amp;amp;#8220;Google Earth&amp;amp;#8221;. The second part will take place in the field, with the aim of recognizing the morphology of the territory generated by the action of the river. The activity lends itself to connections with aspects and phenomena leading to other disciplines.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;One aim of the experience is to strengthen the use of specific language, in Italian as in a foreign language, English. A second aim is to develop the ability to analyse and interpret the territory, using both satellite images and &amp;amp;#8220;hand-on&amp;amp;#8221; experience in the field.&amp;lt;/p&amp;gt;
Privilege Analysis

One of the top things an attacker does is use a compromised account to move laterally through the network. The more privileges the account has, the more damage an attacker can do. For this reason, you need to limit accounts to only the privileges required to function, and nothing else.
Image Resurrection on the Basis of Array Methodologies

Picture compass stow away profitable data. The prerequisite for picture recovery is high in setting of the rapidly creating extents of picture information. Picture mining deals with the extraction of picture structures from an enormous social occasion of pictures in database. Obviously, picture mining is uncommon in association with low-level PC vision and picture dealing with systems in light of the manner in which that the point of convergence of picture mining is in extraction of models from gigantic party of pictures as exhibited by client request, however the purpose of union of PC vision and picture taking care of procedures is in recognition and moreover isolating explicit highlights from a particular picture. In picture mining, the objective is the divulgence of picture structures that are huge in a given social affair of pictures as shown by client request. In this paper the social affair strategies are examined and isolated. Additionally, we propose a philosophy HDK that utilizations more than one social affair framework to propel the execution of picture recuperation. This framework makes utilization of dynamic and isolate and vanquish K-Means gathering system with equivalency and extraordinary affiliation contemplations to update the execution of the KMeans for utilizing as a bit of high dimensional datasets. It likewise showed the part like hiding, surface and shape for cautious and staggering recovery structure.
Image Captioning

When you are vacationing, you capture several pictures of beautiful landscapes and places, and then you put some captions on these photos and publish them on your social network. Just imagine that you would have a mobile app doing photo captioning for you; would this not be a wonderful thing to achieve? In this chapter, you will learn how to create and train a neural network to create captions for your photos.
VR Unmatched - Leveraging Non-experts as Co-Urban Designers

The recent development in Virtual Reality (VR) allows for novel engagement in participatory urban design. Despite that any design approach cannot include and address all items that are relevant or needed during a design process, social VR design instruments offer additionality via their real-time generation and visualisation possibilities that are unmatched in conventional realms. The research employs an anthropogenic approach to design research to engage end-users in the design process. An Immersive Virtual Environment (IVE) instrument 'SketchPad' allows laypersons to design successfully urban forms. SketchPad engaged laypersons in a meaningful design discussion and generations of urban spaces. The research discusses the findings of the experiments. The paper concludes with a reflection of how non-experts as co-designers can use IVE instruments to drive change of their neighbourhood proactively and to positively impact on the liveability of their neighbourhood.
Preface

Abstract The fields of magnetohydrodynamics (MHD) and plasma physics might appear esoteric at first glance, but dig a little deeper, and one realizes that many of the most fundamental challenges facing mankind are underpinned by these processes. Examples range from the design of controlled thermonuclear fusion reactors as an ecologically-friendly approach to renewable energy, to tornado and vortex generation from a climate science perspective, and all the way to understanding the origin of the chemical elements within the hearts of dying stars. The breadth of these applications, the algorithm development required to model such processes, and the associated Big Data analysis tools, are inexorably linked and contribute to the philosophy of this year’s MHD and Plasma Physics Workshop. Our goal in organizing the 3 rd in this series of Workshops has been to provide opportunities for these apparently disparate communities to both highlight their recent developments and discuss the future of algorithm co-design optimized for accuracy, scalability, and efficiency. This year, we have all worked and lived with the daily threat of Covid19; the need for social distancing and relative isolation has impacted upon the familiar and fundamental nature of conferences. Regardless, such interactions are the lifeblood of our respective communities, and so we made the decision to proceed with the Workshop, bring participants together from around the world through a digital platform.
Anatomical Sciences Education Vol. 13, Issue 2, 2020 Cover Image

Anatomical Sciences EducationVolume 13, Issue 2 p. C1-C1 Cover ImageFree Access Anatomical Sciences Education Vol. 13, Issue 2, 2020 Cover Image First published: 02 March 2020 https://doi.org/10.1002/ase.1951AboutPDF 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume13, Issue2March/April 2020Pages C1-C1 RelatedInformation
Advanced Plotting Techniques

Advanced plotting techniques continues with more on the plot functions introduced in Chapter 3. Different two-dimensional plot types, such as logarithmic scale plots, pie charts, and histograms are introduced, as is customizing plots using cell arrays and string functions. Three-dimensional plot functions as well as some functions that create the coordinates for specified objects are demonstrated. Core graphics objects and their use by higher-level plotting functions are demonstrated. Applications that involve reading data from files and then plotting use both cell arrays and string functions.
Unsupervised Learning

Unsupervised learning is a machine learning task that finds hidden patterns and structure in the dataset without the aid of labeled responses. Unsupervised learning is ideal when you only have access to input data and training data is unavailable or hard to obtain. Common methods include clustering, topic modeling, anomaly detection, and principal component analysis.
Tagungen: Vakuum in Forschung und Praxis 4/2019

Vakuum in Forschung und PraxisVolume 31, Issue 4 p. 44-45 Magazin Tagungen: Vakuum in Forschung und Praxis 4/2019 First published: 13 August 2019 https://doi.org/10.1002/vipr.201970407AboutPDF 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. Volume31, Issue4Special Issue: VakuummesstechnikAugust/September 2019Pages 44-45 RelatedInformation
SportsStore: Administration

In this chapter, I add the administration features to the SportsStore application, providing the tools required to manage orders and products. I use GraphQL in this chapter rather than expanding the RESTful web service I used for the customer-facing part of SportsStore. GraphQL is an alternative to conventional web services that puts the client in control of the data it receives, although it requires more initial setup and can be more complex to use.
Efficient Quantum Simulation of Dynamic Correlations on Superconducting Quantum Computers

We present experimental results for the quantum simulation of spin-spin time-correlations, obtained on IBM superconducting quantum processors. We discuss the prospective scalability of this approach to larger magnetic complexes, inaccessible to simulation with classical computers.
IoT based Eye Movement Guided Wheelchair driving control using AD8232 ECG Sensor

Each and every muscular movement in the body is induced by electrical signals. These electrical signals are in mV and they are very sensitive to noise factors like electrical gadgets placed nearby, different movements, earthing, etc. If such signals are traced carefully, they can be used to accomplish multiple tasks. Such signals are called Myographs. This paper proposes a new method for eye-movement tracking, using Arduino Nano along with AD8232, i.e. the ECG Sensor. Most of the devices for Eye Tracking need to be placed right on the eye which sometimes use Infrared Radiations which may be harmful to eyes. This proposed method captures the gaze direction by muscular contraction, also called Myography. This is done by placing the electrode pads on the forehead and the ECG line graphs demonstrate the direction of gaze which can be understood using the convolution method. After the movement direction is decided based on convolution method, the values are sent and received from the IoT cloud. Thus, the wheelchair movement can be controlled by online and offline modes, making it more opportune to the patient. The goal of the system is to avail low-cost solutions to the needer.
Layouts

Layouts are the main mechanism to organize UI components on the screen. For example, you might want to create a form with text fields and combo boxes aligned vertically. Or maybe you want a search bar with a text field and a button aligned horizontally. Vaadin includes layouts for these scenarios and more. This chapter teaches you how to use all the layout components included in Vaadin.
Foreword

International Statistical ReviewVolume 88, Issue S1 p. S1-S1 Editorial Foreword Scott H. Holan, Scott H. Holan University of Missouri/US Census Bureau, USASearch for more papers by this authorNalini Ravishanker, Nalini Ravishanker University of Connecticut, USASearch for more papers by this author Scott H. Holan, Scott H. Holan University of Missouri/US Census Bureau, USASearch for more papers by this authorNalini Ravishanker, Nalini Ravishanker University of Connecticut, USASearch for more papers by this author First published: 23 November 2020 https://doi.org/10.1111/insr.12433Read 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. Volume88, IssueS1Special Issue: “Data Science versus Classical Inference: Prediction, Estimation, and Attribution”, honouring Prof. Brad Efron's International Prize in Statistics in 2019December 2020Pages S1-S1 RelatedInformation
Extensible Contemporary Communication

The crypto analysis approach to the partition table is defined not only by the understanding of infor-mation retrieval systems, but also by the intuitive need for the Ethernet. In fact, few cyberinformati-cians would disagree with the evaluation of hash.
Reinforced Social Ant with Discrete Swarm Optimizer for Sensitive Item and Rule Hiding

In data mining Privacy Preserving Data mining (PPDM) of the important research areas concentrated in recent years which ensures ensuring sensitive information and rule not being revealed. Several methods and techniques were proposed to hide sensitive information and rule in databases. In the past, perturbation-based PPDM was developed to preserve privacy before use and secure mining of association rules were performed in horizontally distributed databases. This paper presents an integrated model for solving the multi-objective factors, data and rule hiding through reinforcement and discrete optimization for data publishing. This is denoted as an integrated Reinforced Social Ant and Discrete Swarm Optimization (RSA-DSO) model. In RSA-DSO model, both Reinforced Social Ant and Discrete Swarm Optimization perform with the same particles. To start with, sensitive data item hiding is performed through Reinforced Social Ant model. Followed by this performance, sensitive rules are identified and further hidden for data publishing using Discrete Swarm Optimization model. In order to evaluate the RSA-DSO model, it was tested on benchmark dataset. The results show that RSA-DSO model is more efficient in improving the privacy preservation accuracy with minimal time for optimal hiding and also optimizing the generation of sensitive rules.
Convolutional Neural Networks in Image Retrieval System

Image is an important medium for monitoring the treatment responses of patient’s diseases by the physicians. There could be a tough task to organize and retrieve images in structured manner with respect to incredible increase of images in Hospitals. Text based image retrieval may prone to human error and may have large deviation across different images. Content-Based Medical Image Retrieval(CBMIR) system plays a major role to retrieve the required images from the huge database.Recent advances in Deep Learning (DL) have made greater achievements for solving complex problems in computer vision ,graphics and image processing. The deep architecture of Convolutional Neural Networks (CNN) can combine the low-level features into high-level features which could learn the semantic representation from images. Deep learning can help to extract, select and classify image features, measure the predictive target and gives prediction models to assist physician efficiently. The motivation of this paper is to provide the analysis of medical image retrieval system using CNN algorithm.
C itizen Identity Management using Blockchain Architecture

The main objective of this paper is to put forward a system for managing the identity of the citizens of a country by leveraging the power of blockchain technology. The paper illustrates how a decentralized system can help make the entire process of identity management transparent and tamper-proof at the same time. While most of the existing blockchain based solutions rely on blocks themselves, the system proposed here emphasizes on the usage of transactions. Decentralization is achieved with this system in the sense that total control over the network does not reside with a single authority, but rather is distributed among multiple authorized government entities.
Kurze Einführung in Python

No AccessNumerisches PythonJun 2019Kurze Einführung in PythonBernd KleinBernd KleinSearch for more papers by this authorhttps://doi.org/10.3139/9783446453630.003SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2019Pages: 9-40Print ISBN: 978-3-446-45076-9eISBN: 978-3-446-45363-0 Copyright & Permissions© 2019 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Study of Implementation of State Requirements to College Students’ Professional Training in Choreography

The relevance of this research is associated with higher education institutions’ transitioning to new educational standards, FGOS 3++, based on professional standards’ requirements to the level of professional learning, since it requires comprehending the role of the state in regulating the content of higher education. The paper focuses on the issues of implementing federal educational standards’ requirements to choreography education. Research methods used to study this problem were as follows: analysis of academic papers and FGOS 3++ requirements to graduates’ skills and surveying students of higher education institutions on the prospects of their future employment. Students were offered a questionnaire and asked to rank the types of professional activity they found promising, considered to be fulfillment opportunities and planned to build their professional career in, on a scale of 1 to 10. The methodology analysis of literature and learning regulation documentation revealed problematic issues connected with graduates’ qualification, content of education and technologies at higher education institutions providing vocational training in choreography art. Students’ survey identified the most attractive types of professional activity that it would make sense to include in curricula, at least at the level of optional courses or electives. Creating conditions for graduates’ professional fulfillment in various activities will not only expand their vocational training but also create conditions for shaping the individual paths of students’ learning. Conclusions and recommendations concerning shaping of educational programs of vocational training in choreography possess practical significance.
Fast causal division for supporting robust causal discovery

Discovering the causal relationship from the observational data is a key problem in many scientific research fields. However, it is not easy to detect the causal relationship by using general causal discovery methods among large scale data, due to the curse of the dimension. Although some causal dividing frameworks are proposed to alleviate these problems, they are, in fact, also faced with high dimensional problems. In this work, we propose a split-and-merge method for causal discovery. The original dataset is firstly divided into two smaller subsets by using low-order CI tests, and then the subsets are further divided into a set of smaller subsets. For each subset, we employ the existing causal learning method to discovery the corresponding structures, by combined all these structures, we finally obtain the complete causal structure. Various experiments are conducted to verify that compared with other methods, it returns more reliable results and has strong applicability.
Severity of defect: an optimised prediction

To assure the quality of software an important activity is performed namely software defect prediction (SDP). Historical databases are used to detect software defects using different machine learning techniques. Conversely, there are disadvantages like testing becomes expensive, poor quality and so the product is unreliable for use. This paper classifies the severity of defects by using a method based on optimised neural network (NN). In full search space, a solution is found by many meta-heuristic optimisations and global search ability has been used. Hence, high-quality solutions are finding within a reasonable period of time. SDP performance is improved by the combination of meta-heuristic optimisation methods. For class imbalance problem, meta-heuristic optimisation methods such as genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) are applied. The above method is based on SFLA and the experimental outputs show that it can do better than Leven berg Marquardt based NN system (LM-NN).
Security firms breached

Security vendors FireEye and Sophos have themselves both suffered breaches. And in the case of FireEye, the attackers made off with some of the company's most valuable intellectual property.
Performance Evaluation of Stochastic Quantization Methods for Compressing the Deep Neural Network Model

Discretizing the Deep Neural Network (DNN) is enforced by a rounding function of weights and activations, which can severely degrade the performance of DNN. This paper categorizes the available quantization methods to be uniform or non-uniform according to the distribution of its quantized interval, and proposes a noble stochastic rounding method to reduce the accuracy loss of the quantized DNN model. Two stochastic rounding methods of linear or nonlinear probability distribution are quantitatively evaluated and analyzed to give an important insight to employ them for designing the compressed DNN model, by comparing them with the previous deterministic nearest rounding. Experimental results show that the stochastic rounding methods are not always superior to the deterministic one and the optimal performance is obtained via a hybrid rounding scheme when applying the stochastic rounding to the input adjacent to the intermediate value between the neighboring quantized values and still using the deterministic one near to the quantized value.
An HTML and CSS Primer

Developers come to the world of web app development via many paths and are not always grounded in the basic technologies that web apps rely on. In this chapter, I provide a brief primer for HTML and introduce the Bootstrap CSS library, which I use to style the examples in this book. In Chapters 5 and 6 , I introduce the basics of JavaScript and TypeScript and give you the information you need to understand the examples in the rest of the book. If you are an experienced developer, you can skip these primer chapters and jump right to Chapter 7 , where I use Angular to create a more complex and realistic application.