Reviewerly/exHarmony huggingface dataset:
Modelling of obstacle avoidance robot using LABVIEW

Robotics is one of emerging technology from past few decades. Now a days most of industries depends on robotic automation. Robotics made human life easier. This paper is overview of such implementation. As we know now a days there are such areas where human cannot work efficiently, with the help of this moving wheeled robot and visual programming platform called as LabView we have proposed kinematic model of moving wheeled robot with consideration of obstacles. This model can work efficiently in any uncertain conditions without human intervention. This model also tracks trajectory and location of robot. Output can be analyzed with the help of graphs on LabView
Research on the Status Quo of Community Sports under the Background of “Construction of Half an Hour Sports Life Circle”

With the increasing pace of life and work pressure, people do not have the time and energy to carry out necessary physical exercise, leading to the body gradually into sub-health, which has a serious impact on residents' life. In order to reduce these effects, in addition to improving the medical level, we should also carry out a wide range of community mass, rich and colorful sports activities, fundamentally improve people's physical quality, the construction of half an hour sports life circle in this background came into being. This paper analyzes a series of concepts of community sports in the half-hour sports life circle, takes the situation of the community residents participating in physical exercise in Shanghai as an example, and puts forward some countermeasures for the development of community sports under this background for reference.
Visual retrieval method of intelligent teaching resource data based on feature index

In order to achieve high-precision and high-efficiency visual retrieval of intelligent teaching resource data, this paper proposes a visual retrieval method of intelligent teaching resource data based on feature index. Firstly, a data mining model of intelligent teaching resources is constructed according to the similarity and feature extraction results of intelligent teaching resources, and then the data mining results are merged and classified. Finally, the feature index is constructed, and the data visual retrieval is realized by combining the similarity calculation results of the initial vector of data retrieval with the data subset. The experimental results show that, compared with the traditional methods, the proposed method can achieve high-precision and high-efficiency visual retrieval of intelligent teaching resource data, and the practical application effect is good.
A model of formative assessment for foreign language teaching in a secondary school

We develop and present a model of formative assessment. The analysis of official educational requirements and existing models is carried out. Further, we compare some of the existing models of formative assessment presented by domestic and foreign authors. Then we develop our own model of formative assessment for foreign language teaching in a secondary school on the base of Spotlight course. The model is developed as a supplementary tool for the assessment model designed by the authors of the course. The main purpose of the model is to involve students in the process of assessment and make them active agents of their own learning. The model consists of the following stages: learning aims delivery and sharing, students’ self and peer assessment, formative feedback, given by a teacher and reflection. Each stage assumes use of certain assess-ment tools. They are: checklists, headings, Forms of comparative assessment, Map of differen-tiated assessment, Achievement Tree and a learning diary.
Sentence Patterns in Descriptive Text of Senior High School English Textbook

This research is aimed at the Sentence Patterns in Descriptive Text of Senior High School English Textbook. Focusing on the problem statements, there are two cases in this research. They are “What types of sentence patterns are found in Descriptive Text of Senior High School English Textbook and what are the found of each elements of the sentence patterns in Descriptive Text of Senior High School English Textbook. This research, applied descriptive qualitative method. The data is collected by documenting. The data is taken from Descriptive Text of Senior High School English Textbook. The procedure of analyzing the data start by analyzing about sentence patterns types based on Brown’s theory. Then find the dominant of the sentence patterns types of Descriptive text of Senior High School English Textbook and the elements of Sentence Pattern in English textbook. Based on the results, the researchers found out 5 patterns which were used in the descriptive text of senior high school English textbook. The sentence pattern which is was frequently used was pattern: S + V + SC and the elements used in the sentence pattern was Phrase namely, Noun Phrase. Finally, the researchers hope that the results can help English learners to improve their understanding on sentence patterns and the elements of the sentence patterns.
Linguistic approach for definition language of SMS

Observed linguistic direction to definition SMS language. Made analysis of existing methods. Marked specifics of SMS and its differs from usual text reports and difficult at using known methods for definition SMS language. Observed special morphological characters for some natural languages. Conclusion: the most effective method base on analysis of suffix, inflections, service verbs, articles, prepositions, pronouns. These text elements need represent as lists with probably for N-grams of text symbols, which have linguistic interpretation and received from purpose-made text corpus.
The concept of power in computer-mediated communication

There has been a recent increase of interest in the phenomenon of power amongst linguists and also philosophers. The presented article attempts to consider power and ways in which it is exercised through language of computer-mediated communication (further CMC). This unique environment is determined by the specific conditions of an Internet chat room, such as anonymity and no audio-visual cues. In the theoretical part, Watts’s and Diamond’s investigations of power in various open and closed groups in oral communication are discussed and the notion of status is presented. The author divides the chat group corpus into individual sub-groups and tries to draw a graphical presentation, a sociogram, to show their complexity and distribution of power. However, the question remains how tight the sub-groups in CMC are or how interrelated they are with one another. In this respect, it is noteworthy to observe how a selected chat participant develops her status in various sub-groups and to analyze the means by which this possible status is achieved. The corpus was collected by the author herself. The main hypothesis is that the status of power changes quickly throughout chatting and it depends to a great extent on other cues such as address, non-verbal action displays, punctuation marks and so on. In other words, there are very few means by which to exercise power and hold it in this continuously changing and anonymous environment.
SWOT Analysis of BYOD (Bring Your Own Device)

Bring your own device (BYOD) grants delegates to use their own gadgets, application, and framework for business or work reason, with an idea of extending productivity, reduces the IT costs, and adjusting undertaking system. A SWOT assessment of BYOD is furthermore a result to provide a succinct audit of favorable circumstances with downsides of BYOD technology. Furthermore, an examination of a modification concept is given which explains a comprehensive diagram of various needs of IT industry and their unmistakable security level over their data and structure for executing BYOD. At the present time, we are focusing on conduction of SWOT examination of BYOD.
GroupRank: Ranking Online Social Groups Based on User Membership Records

Social networks are valuable sources for marketers. Marketers can publish campaigns to reach target audiences according to their interest. Although Telegram was primarily designed as an instant messenger, it is used as a social network in Iran due to censorship of Facebook, Twitter, etc. Telegram neither provides a marketing platform nor the possibility to search among groups. It is difficult for marketers to find target audience groups in Telegram, hence we developed a system to fill the gap. Marketers use our system to find target audience groups by keyword search. Our system has to search and rank groups as relevant as possible to the search query. This paper proposes a method called GroupRank to improve the ranking of group searching. GroupRank elicits associative connections among groups based on membership records they have in common. After detailed analysis, five-group quality factors have been introduced and used in the ranking. Our proposed method combines TF-IDF scoring with group quality scores and associative connections among groups. Experimental results show improvement in many different queries.
Effects of Using the WARMA Tool for Learning Quechua in Bilingual Educational Institutions in Huamanga City

The limitations of educational services in regular basic education are a frequent problem that affects the quality of teaching, and in the cities of the Peruvian highlands, due to the scarcity of learning materials or instruments adapted to Andean mother tongues, among them the Quechua language, this contributes to the weakening of the cultural identity of the indigenous populations of the department of Ayacucho, located in Peru. This paper presents the results of a study about the use and effects of the mobile application "Warma" (Warma, means "child" in the Quechua language of Ayacucho), as a tool for learning language and mathematics in Quechua-speaking educational institutions in communities near the city of Huamanga (Ayacucho, Peru). This study corresponds to the continuation of a previous experience, which took place during the year 2019, and in which children from educational institutions of Quechua-speaking indigenous communities located in the city of Ayacucho participated. The results show that the use of the mobile application is superior to traditional teaching methodology in the process of learning language and mathematics, indicating that the use of mobile applications has a favorable effect on the teaching of indigenous languages, such as Quechua, in both rural and urban educational institutions.
Development of Socio-cultural Competence in Future Primary School Teachers Devorova

This article deals with the development of socio-cultural competence in future primary school teachers on the basis of an axiological approach. There are some skills about how to use it efficiently.
European expansion of DenseBreast-info.org educational resource

Poster: ECR 2020 / C-04048 / European expansion of DenseBreast-info.org educational resource  by: Vourtsis1, W. A. Berg2, J. Pushkin3, C. Cruwys 4; 1Athens/GR, 2Pittsburgh, PA/US, 3Deer Park NY/US, 4Haute Vienne/FR
Topic Sentiment Trend Detection and Prediction for Social Media

Social media often plays a crucial role in disseminating information to warn the public about health concerns. Opioid addiction has become of the significant outbreaks in the United States. Studying opioid issues in social media has the potential to reveal patterns of opioid abuse and understand people's opinions on this issue. On the other hand, social media forums like Twitter allow for open discussions among the public and popular information exchanges. The question arises if the trends of such concerns like opioid abuse can be automatically detected and predicted for a better understanding of people's attitude changes in a specific direction.In this thesis, we developed a novel framework for topic sentiment trend detection and prediction in social media. The proposed framework was designed to cope with the following tasks: topic trend detection, sentiment analysis, and topic prediction. The VADER-based time series sentiment analysis and the KATE-based topic modeling methods were applied to analyze the social media data from the public, social media news, and newspapers. We have further extended the framework for the successful prediction of topic trends for given the current issues. For the topic trend prediction model, the deep neural network model called Long Short Term Memory (LSTM) was used along with topic embedding techniques. The two-step communication model was used to evaluate how different types of media are active in the emergence and escalation dissemination and how effective it is in the pacification and prevention of concerns related to epidemics, like opioids. The proposed framework was also applied to the Twitter data as well as New York Times articles on opioids over ten years, from 2010 to 2019. The results of this study have shown some exciting findings from topic sentiment detection and high accuracies from the topic trend prediction.
Energy-Efficient, Flexible and Fast Architectures for Deep Convolutional Neural Network Acceleration

RESUME: Les methodes basees sur l'apprentissage profond, et en particulier les reseaux de neurones convolutifs (CNN), ont revolutionne le domaine de la vision par ordinateur. Alors que jusqu'en 2012, les methodes de traitement d'image traditionnelles les plus precises pouvaient atteindre 26% d'erreurs dans la reconnaissance d'images sur l'etalon normalise et bien connu ImageNet, une methode basee sur un CNN a considerablement reduit l'erreur a 16%. En faisant evoluer la structure des CNN, les methodes actuelles basees sur des CNN atteignent desormais couramment des taux d'erreur inferieurs a 3%, depassant souvent la precision humaine. Les CNN se composent de nombreuses couches convolutives, chacune effectuant des operations de convolution complexes de haute dimension. Pour obtenir une precision elevee en reconnaissance d’images, les CNN modernes empilent de nombreuses couches convolutives, ce qui augmente considerablement la diversite des motifs de calcul entre les couches. Ce haut niveau de complexite dans les CNN implique un nombre massif de parametres et de calculs.----------ABSTRACT: Deep learning-based methods, and specifically Convolutional Neural Networks (CNNs), have revolutionized the field of computer vision. While until 2012, the most accurate traditional image processing methods could reach 26% errors in recognizing images on the standardized and well-known ImageNet benchmark, a CNN-based method dramatically reduced the error to 16%. By evolving CNNs structures, current CNN-based methods now routinely achieve error rates below 3%, often outperforming human level accuracy. CNNs consist of many convolutional layers each performing high dimensional complex convolution operations. To achieve high image recognition accuracy, modern CNNs stack many convolutional layers which dramatically increases computation pattern diversity across layers. This high level of complexity in CNNs implies massive numbers of parameters and computations. Since mobile processors are not designed to perform massive computations, deploying CNNs on portable and mobile devices is challenging.
Logic and Interactive Rationality (LIRA) 2019 Slides

Slides from a presentation to the Logic and Interactive Rationality (LIRA) at the Institute of Logic, Language and Computation at the University of Amsterdam, 5 March 2020.
Professional Development of the Performance of Faculty Members in the Field of Dealing with Entrepreneurship Distance Learning Platforms in Light of the Corona Pandemic (Covid-19) Suggested Framework

The study aimed to identify the status of professional development for the performance of faculty members in the field of dealing with remote education platforms in light of the Corona pandemic (Covid-19) at the College of Education, Imam Abdul Rahman bin Faisal University. To achieve the aim of the study, the descriptive method was used in its survey form. The questionnaire was used as a study tool and it was applied to a sample selected from the study population from the faculty of the College of Education, Imam Abdul Rahman bin Faisal University, whose number is (138) members, and the study sample amounted to (121) faculty members with a rate (87%) of Total community. The study resulted in several results, the most important of which are: The state of professional development of members ’performance in dealing with Distance learning platforms was high. It was also found that there are no statistically significant differences at (α ≤ 0.05) in the reality of developing the performance of faculty members to deal with Distance learning platforms during the Corona pandemic in relation to the variable (academic rank, and the number of courses before and during the Corona pandemic). A proposed framework was presented to develop performance in light of the results of the study.
Yeni Medyada Ürün Yerleştirmenin Ebeveynlerin Satın Alma Eğilimine Etkisi: Çocuk Videolarıyla İlgili Kırıkkale İlinde Bir Araştırma

Purpose – Product placement is one of the methods used to deliver marketing messages to the consumer. New media tools, especially social networks, which are developing and becoming widespread today, have resulted in product placement in these areas as well. The aim of this study is to investigate the effect of product placement on videos for children in social networks on parents' tendency to purchase products in videos. Design/methodology/approach – Studies on product placement in new media are generally related to internet-based games. Within the scope of the aim of the study, primary data were collected from 200 parents with children aged between 1-8 years in Kirikkale province by convenience sampling method and analyzed. Findings – As a result of the analysis, it has been found that; the attitudes towards brands in the videos, the request of the child to purchase the products in the videos, the awareness of advertising and the recall of the products / brands in the videos, has a positive effect on the tendency to purchase products in videos. Discussion – The findings of the study support the idea that placing products for children on social media can be an important method for influencing parents' purchasing tendencies. At this point, it can be said that creating a positive attitude towards brands in children's videos will be beneficial for businesses.
Application of the quantum approximate optimization algorithm to combinatorial optimization problems

This licentiate thesis is an extended introduction to the accompanying papers, which encompass a study of the quantum approximate optimization algorithm (QAOA). It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems and is a promising algorithm to run on near term quantum devices. In this thesis, we will introduce the workings of the QAOA, together with some applications of it on combinatorial optimization problems.
Reasons for Integrated Library Systems (ILS) switching in Nigerian University Libraries

This study sought to determine the reasons for switching ILS among Nigerian university libraries. A qualitative research approach using multiple case study design was used to gain a better understanding of the problem; purposive sampling technique was used to select the participants. Interview was the instrument used for data collection, and the researcher conducted five interviews with five (5) participants from university libraries across the geo-political zones of Nigeria. Data were collected from June 2016 through July 2016. The analysis of data was done using themes derived from the objectives of the study. Findings revealed that delay in getting vendors support to fix ILS problems, some ILS have limited storage space to accommodate large data, crashing and data loss, and political considerations, were some of the reasons given by Nigerian  University Libraries for switching ILS. The study, therefore, recommended among others that Nigerian university libraries should conduct adequate and thorough feasibility study based on the peculiar needs of their libraries before selecting the appropriate library software, libraries should adoptand deploy open source ILS which are more cost effective and easier to maintain rather than buying proprietary ILS which were developed based on US and UK standards and which might not fit their needs. The study concluded that the switching over from one ILS to another by NUL studied is too frequent. The frequency of change is associated with lack of proper feasibility study and knowledge involved in determining the implications of frequent switching on the libraries.Keywords: Reasons, Integrated Library Systems (ILS), Switching, Nigerian University Libraries
Working in Groups Through Trainings as a Factor in the Socialization of the Younger Generation

In the education system, the role of the teacher is great in the free, creative, independent thinking of students in the educational process and training activities. It is expedient to use two principles in the structure of education - independent work and its organization - the principle of systematic and consistent work of independent work. The historical experience of the institute in each period of social development shows that the task of education cannot be accomplished without a certain system.
Algoritma Fungsi Perlatihan pada Machine Learning berbasis ANN untuk Peramalan Fenomena Bencana

Research has been carried out with several training functions using standard backpropagation methods, One-Step Secant (OSS), and Bayesian regulation. The purpose of this study was to (i) analyze the Performance accuracy (Performance) of the standard backpropagation method and (ii) optimize the training function with the One-Step Secant (OSS) and Bayesian regulation methods to obtain comparison results of the three methods in the search for the best results implementation of disaster phenomenon forecasting data. The research method is based on quantitative methods with times-series data on disaster phenomena in Indonesia over the last ten years (2011-2020) which were analyzed using two network architecture models, namely 4-8-1 and 4-10-1. The results showed that the 4-8-1 architectural model with the Bayesian regulation training function method was able to optimize quite well through accelerating training time and resulted in a low MSE measurement, although not the lowest with an epoch value of 197 iterations and a Performance of 0.0148480766. The lowest epoch value is generated by the OSS method, but it Performs poorly. The best Performance is produced by the standard backpropagation method with the traingd training function, but the training process for achieving convergence is also too long. In general, it can be concluded that the 4-8-1 architectural model with Bayesian regulation can be used to predict (predict) the phenomenon of natural disasters in Indonesia because the training time to achieve convergence is not too long and Performs exceptionally well.&#x0D;