Reviewerly/exHarmony huggingface dataset:
Motivation To Self-Improvement Among Physical Education Teachers

The formation of teacher’s motivation to self-improvement during their professional activity is investigated. The aim of the research is to analyse motivation to self-improvement of physical education teachers in the process of professional activity. Physical education teachers for experimental (EG, n=124) and control (CG, n=124) groups were picked randomly from a pedagogical staff of Ukrainian universities. The Motivation Sources Inventory was used to define motivation to self-improvement. Teachers of CG participated in the traditional in-service training course, EG was trained according to the authorial program. We assume that motivation leads and organizes teachers’ activity, provides personal essence and significance of self-improvement, promotes the transformation of externally-formulated aims into inner needs. Basic trends of an effective influence on the intensification of motivation to self-improvement of teachers were: formation of positive guideline for self-improvement in the process of professional activity with the help of specification of requirements to specialists; formation of solid knowledge and skills; actualisation of the need for improvement and professional growth. Intrinsic motivation is important forself-improvement of teachers of physical education in the process of their professional activity. The results of the research show that intrinsic motives dominate among the teachers of CG, which highlights positive attitude to pedagogical activity, and intensify motivation to self-improvement.
Prevent legal, PR damage triggered by public comments

It's been a common occurrence for a very long time — the confrontations that too frequently occur at the end of a hotly contested athletics competition. One or more fans taunt a player, coach, staff member, or administrator, which often incites an emotional response in the heat of the moment. Frustration, disappointment, and anger about the outcome of the competition and the nature of the insult inevitably fuel an acidic and pointed retort.
A Novel Universal Solar Energy Predictor

Solar energy is one of the most economical and clean sustainable energy sources on the planet. However, the solar energy throughput is highly unpredictable due to its dependency on a plethora of conditions including weather, seasons, and other ecological/environmental conditions. Thus, the solar energy prediction is an inevitable necessity to optimize solar energy and also to improve the efficiency of solar energy systems. Conventionally, the optimization of the solar energy is undertaken by subject matter experts using their domain knowledge; although it is impractical for even the experts to tune the solar systems on a continuous basis. We strongly believe that the power of machine learning can be harnessed to better optimize the solar energy production by learning the correlation between various conditions and solar energy production from historical data which is typically readily available. For this use, this paper predicts the daily total energy generation of an installed solar program using the Naive Bayes classifier. In the forecast procedure, one year historical dataset including daily moderate temperatures, daily total sunshine duration, daily total global solar radiation and daily total photovoltaic energy generation parameters are used as the categorical valued features. By way of this Naive Bayes program the sensitivity and the precision measures are improved for the photovoltaic energy prediction and also the consequences of other solar characteristics on the solar energy production have been assessed.
Tensor-Flow Based Approach to Identify Author of the Text

Now-a-days a lot of content is available on internet, and people upload lot of information in form of opinion, review, description, recipe etc. online. In such scenario to trace the authenticity of the data, it is necessary to develop an author identification system. It has become a difficult problem in the scope of unnamed information has increased with fast growing Internet life. It is a process to identify author of unknown text document. In existing system, so many authorship attribution methods were evaluated for natural languages, such as English, Chinese, and Arabic. Most of the experiments are done on the lexical and word based. Classification techniques such as Naive Bayes 1 ,Support Vector Machine, Neural Network, Multilayer Perceptron, Decision Tree 2 ,k-nearest-neighbor are already used, but previous work proved that Support Vector Machine 3 is a good classifier for author identification. In this system we identify author using deep learning. For identification we use features like Bag-of-Words, word tokenization and stemming. We build Deep neural Network and LSTM network using the Tensor-flow library 4 . The average accuracy achieve 68 % using Tensor-flow Deep Neural Network and 38.68 % using Tensor-flow LSTM network. Cite this Article Kajal Patel, Brijesh S. Bhatt. TensorFlow-based Approach to Identify Author of the Text. Current Trends in Information Technology . 2018; 8(3): 23–29p.
Data Interpolations in Deep Generative Models under Non-Simply-Connected Manifold Topology

Exploiting the deep generative model's remarkable ability of learning the data-manifold structure, some recent researches proposed a geometric data interpolation method based on the geodesic curves on the learned data-manifold. However, this interpolation method often gives poor results due to a topological difference between the model and the dataset. The model defines a family of simply-connected manifolds, whereas the dataset generally contains disconnected regions or holes that make them non-simply-connected. To compensate this difference, we propose a novel density regularizer that make the interpolation path circumvent the holes denoted by low probability density. We confirm that our method gives consistently better interpolation results from the experiments with real-world image datasets.
A Survey on the CSC-sponsored Visiting Scholars’ English Use Abroad and Its Reflections

This essay aims to make an analysis of the CSC-sponsored visiting scholarsâ€™ English use abroad. The findings from the survey trigger some reflections, and accordingly some strategies are supplied so as to conduce to future English training for visiting scholars.
Discretized Gradient Flow for Manifold Learning in the Space of Embeddings

Gradient descent is a standard technique in machine learning to find minima of penalty functions. Many implementations of gradient descent rely on a discretized version, i.e., moving in the direction of the gradient for a set step size, recomputing the gradient, and continuing. Manifold learning/dimensionality reduction, which seeks a low dimensional manifold that best represents data in a high dimensional Euclidean space, is an inherently infinite dimensional problem. In this context, gradient descent has been applied only after simplifying manifold learning to a finite dimensional problem by e.g. RKHS or parametric methods. In this paper, we present a gradient descent approach to optimize manifold embeddings, where the gradient descent takes place in the infinite dimensional space of smooth embeddings $ϕ$ of a manifold $M$ into $\mathbb{R}^N$. We first argue that the penalty function should be invariant under diffeomorphisms of $M$, as this guarantees that the gradient direction is always pointwise normal to $ϕ(M)$ inside $\mathbb{R}^N$. Thus implementing discretized gradient flow in our framework requires estimating how far we can move in a fixed normal direction before leaving the space of smooth embeddings. We give an explicit lower bound for this distance in terms of the geometry of $ϕ(M)$ induced from its embedding in $\mathbb{R}^N.$
A weak limit theorem for a class of long range type quantum walks in 1d

We derive the weak limit theorem for a class of long range type quantum walks. To do it, we analyze spectral properties of a time evolution operator and prove that modified wave operators exist and are complete.
Paid: Tales of Dongles, Checks, and Other Money Stuff. Bill Maurer and Lana Swartz, eds. Cambridge, MA: MIT Press, 2017. 320 pp.Money at the Margins: Global Perspectives on Technology, Financial Inclusion, and Design. Bill Maurer, Smoki Musaraj, and Ivan Small, eds. New York: Berghahn, 2018. 334 pp.

American EthnologistVolume 46, Issue 1 p. 108-111 Book Review Paid: Tales of Dongles, Checks, and Other Money Stuff. Bill Maurer and Lana Swartz, eds. Cambridge, MA: MIT Press, 2017. 320 pp. Money at the Margins: Global Perspectives on Technology, Financial Inclusion, and Design. Bill Maurer, Smoki Musaraj, and Ivan Small, eds. New York: Berghahn, 2018. 334 pp. DAIVI RODIMA-TAYLOR, Boston UniversitySearch for more papers by this author DAIVI RODIMA-TAYLOR, Boston UniversitySearch for more papers by this author First published: 21 January 2019 https://doi.org/10.1111/amet.12740 Read 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 onEmailFacebookTwitterLinked InRedditWechat Volume46, Issue1February 2019Pages 108-111 RelatedInformation
Guidelines for creating man-machine multimodal interfaces

Understanding details of human multimodal interaction can elucidate many aspects of the type of information processing machines must perform to interact with humans. This article gives an overview of recent findings from Linguistics regarding the organization of conversation in turns, adjacent pairs, (dis)preferred responses, (self)repairs, etc. Besides, we describe how multiple modalities of signs interfere with each other modifying meanings. Then, we propose an abstract algorithm that describes how a machine can implement a double-feedback system that can reproduces a human-like face-to-face interaction by processing various signs, such as verbal, prosodic, facial expressions, gestures, etc. Multimodal face-to-face interactions enrich the exchange of information between agents, mainly because these agents are active all the time by emitting and interpreting signs simultaneously. This article is not about an untested new computational model. Instead, it translates findings from Linguistics as guidelines for designs of multimodal man-machine interfaces. An algorithm is presented. Brought from Linguistics, it is a description pointing out how human face-to-face interactions work. The linguistic findings reported here are the first steps towards the integration of multimodal communication. Some developers involved on interface designs carry on working on isolated models for interpreting text, grammar, gestures and facial expressions, neglecting the interwoven between these signs. In contrast, for linguists working on the state-of-the-art multimodal integration, the interpretation of separated modalities leads to an incomplete interpretation, if not to a miscomprehension of information. The algorithm proposed herein intends to guide man-machine interface designers who want to integrate multimodal components on face-to-face interactions as close as possible to those performed between humans.
Reduced-Reference Image Quality Assessment based on saliency region extraction

In this paper, a novel saliency theory based RR-IQA metric is introduced. As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. In order to extract the salient regions, we use blob decomposition (BD) tool as a texture component descriptor. A new method for blob decomposition is proposed, which extracts blobs not only in different scales but also in different orientations. Different blob components consist of location of blobs, blob shape and color attributes are used to describe texture of the image accordance to the human visual system conception. A region Covariance matrix is calculated from extracted blob components which can be easily interpreted in terms of its eigenvalues. Therefore, the reference image is described as a squared covariance matrix and a good data reduction is achieved. The same process is used for describing the received image in the destination. Finally, the image quality is estimated by using the eigenvalues of two covariance matrices. The performance of the proposed metric is evaluated on different databases. Experimental results indicate that the proposed method performs in accordance with the human visual perception and uses few reference data (maximum 90 values).
Generating a Highlight Moments Summary Video of Apolitical Event using Ontological Analysis on Social Media Speech Sentiment

Numerous viewers choose to watch political or presidential debates highlights via TV or internet, rather than seeing the whole debate nowadays, which requires a lot of time.However, the task of making a debate summary, which can be considered neutral and does not give out a negative nor a positive image of the speaker, has never been an easy one, due to personal or political beliefs bias of the video maker.This study came up with a solution that generates highlights of a political event, based on twitter social network flow.Twitter streaming API is used to detect an event's tweets stream using specific hashtags, and detect on a timescale the extreme changes of volume of tweets, which will determine the highlight moments of our video summary at first, then a process is set up based on a group of ontologies that analyze each tweet of these moments to calculate the percentage of each sentiment's positivity, then classify those moments by category (positive, negative or neutral).
From the EIC: Special Section on Test

The two articles in this special section were presented at the 2017 International Test Conference (ITC’17).
Mixed reality laboratory, University of Nottingham

opinion Share on Mixed reality laboratory, University of Nottingham Authors: Steve Benford View Profile , Jocelyn Spence View Profile , Pat Brundell View Profile , Teresa Castle-Green View Profile , Lewis Hyland View Profile , Murray Goulden View Profile Authors Info & Claims InteractionsVolume 26Issue 2March - April 2019 pp 18–21https://doi.org/10.1145/3308643Published:22 February 2019Publication History 0citation605DownloadsMetricsTotal Citations0Total Downloads605Last 12 Months144Last 6 weeks18 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Consistency Maintenance of Collaborative Shared Documents in Unstable Network Environment

Aim to the instability of the mobile internet, the paper proposes an algorithm to achieve the consistency maintenance of the shared documents during the collaborative editing process in the broken network environment. Unlike with the previous studies, we divide network statuses into three types: break-before, break-after and connect-after, in order to record the document and net states, the paper puts forward two new definitions about cursor and network statuses. In the break-before phase, the algorithm updates all the collaborative sites’ cursors regularly to record the latest consistency point. In the break-after phase, the algorithm packs the operations according to cursor and network attributes. While in the connect-after process, the algorithm adapts the address space transformation strategy to resend and execute lost operations as well as constructing necessary performing condition for ABST or other algorithms that support asynchronous cooperation. In this paper, a case analysis is given to describe the execution process of strategy, and correctness proof is also given to validate the whole strategy.
“Latino Flavors”

Shifting from the previous chapter’s analysis of the contested construction of a Latinx ethnoracial category, Chapter 3 demonstrates how emblems of Latinx identity are made recognizable in everyday life. In particular, it focuses on the ways in which qualities attributed to objects, practices, and bodies are mapped onto one another in the contemporary fashioning of a Latinx US ethnoracial category. By analyzing interrelations among forms of emblematicity associated with a range of cultural concepts, from hairstyles, clothing, and language, to food, dance, and music, the chapter tracks the complex semiotic operations that connect the creation <italic>Latinx things</italic> to the embodiment of <italic>Latinx people</italic>. These processes allow actors within New Northwest High School to experience and enact Latinx identities. The chapter concludes by pointing to the close relationship between conceptions of Latinx identity and “Spanishness” as a cultural and linguistic quality, laying the groundwork for the second half of the book.
Implementation of search robot's function to collect information in scientometric systems

At present, the World Wide Web is developing rapidly, and every day the problem of automated collection and analysis of information placed on various web resources is becoming increasingly urgent.If in the 90s of the last century, the World Wide Web was a huge amount of poorly structured information, to search in which it was difficult for a person.It was then that the first developments in the field of automated agents began to appear, facilitating the task of finding the necessary information on the web.The main part of such systems is a search robot -a software package that navigates through web resources and collects information for a database.In the Kazan (Volga Region) Federal University, a monthly rating of academic staff is compiled based on data placed in the personal offices of employees in the Electronic University system.Now there is a need to move away from manually filling the Hirsch index in a personal account with KFU staff to avoid incorrect data filing and validation of the entered information by the Prospective Development Center.What was required was the creation of a search robot to automatically collect the Hirsch indices of KFU employees from the Scopus system.This article discusses the search robot: What is it?How does he work?How to write your program to collect information?All these issues were addressed in this article.The possible types of search robots and the whole process of their work were considered.The Scopus scientometric system and scientometric indicator -Hirsch index, its purpose, and calculation were considered.For implementation, the Python programming language was used and the tools for implementing HTTP requests and processing HTML pages were considered.
Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game

In this paper, we present the strategy of Agent Madoff, which is a heuristic-based negotiation agent that won 2nd place at the Automated Negotiating Agents Competition (ANAC 2017). Agent Madoff is implemented to play the game Diplomacy, which is a strategic board game that mimics the situation during World War I. Each player represents a major European power which has to negotiate with other forces and win possession of a majority supply centers on the map. We propose a design architecture which consists of 3 components: heuristic module, acceptance strategy and bidding strategy. The heuristic module, responsible for evaluating which regions on the graph are more worthy, considers the type of region and the number of supply centers adjacent to the region and return a utility value for each region on the map. The acceptance strategy is done on a case-by-case basis according to the type of the order by calculating the acceptance probability using a composite function. The bidding strategy adopts a defensive approach aimed to neutralize attacks and resolve conflict moves with other players to minimize our loss on supply centers.
Animasi Interaktif Pengenalan Huruf Hijaiyah Berbasis Android

The development of animation that occurred in this era is very rapid. Animation is now an alternative in conveying the intent and purpose of information in digital media that is often used on computers and smartphones. As Muslims it is important to learn the Hijaiyah letter in the form of Arabic, because it is the beginning of the beginning of learning in Arabic sentences, and also in the fluent reading of the Qur'an along with its punctuation marks. Android smartphone users at this time are very diverse, including parents, young people, and children, but seeing in terms of function and benefits, smartphones can be interactive digital media that is useful and useful in knowing new knowledge and adding insight. In this case the author designs interactive animations to recognize letters and numbers hijaiyah and is equipped with games that are expected so that children do not get bored quickly, exercise memory, and are easy to understand. The method used in the development of this software uses the waterfall model. The concept of the animation system is made into a practical application and as an intermediary medium can be run on their gadgets
Engaging in Logical Code Reasoning with an Activity-Based Online Tool

Using freely available online automated reasoning tools, we will demonstrate a sequence of engaging reasoning activities that are suitable to introduce beginning programmers and software engineering students to reason logically and symbolically about code. The automated tools have an underlying verification engine that makes it possible for the tool to offer activities and directed logical feedback not possible with typical development environments. The tools have been used in undergraduate classrooms for multiple years by well over a thousand students. The imperative language used by the tool is integrated with the underlying verification engine, and because it closely resembles many commercial languages, it presents little barrier to student usage. A comprehensive activity-based "Reason with Components" tool takes 5-10 minutes of instructor introduction and allows student exploration of contracts, objects, loops, recursion, and reusable concepts. Multiple versions of "Begin to Reason" tools are designed to help students learn the basics of code tracing in intro CS courses "on their own". Students and instructors can create new activities and can fine-tune the existing activities to their specific needs.