Reviewerly/exHarmony huggingface dataset:
Analysis of Key Indicators in English Teaching Evaluation Based on Big Data Model

With the advent of the era of big data, the traditional English teaching methods in the past can no longer accurately assess the comprehensive level of English teachers and classrooms because of various factors. In order to reexamine and plan English teaching content, based on the big data model, we will carefully analyze the key indicators in English teaching evaluation using computer technologies such as particle swarm optimization and support vector machine, hoping to dig out the characteristics of English education in a deeper way, so as to make a series of index adjustments to English classroom and improve English teaching level. The results of this study show the following: (1) The average accuracy of the evaluation index of the model designed in this study is as high as 96.56%; after 20 tests, the test time of this model method is the least, and the test time can be as low as 13.32 ms. (2) For eight first-class indexes of A, B, C, D, E, F, G, and H and 29 second-class indexes, the expert scores are all greater than 3.66, and the standard deviation is all less than 1, which accords with the standard of reaching common opinions. The key index test system is reasonable. (3) We find that the weights of A2, D1, H1, and H2 are all higher than 0.5, the weights of A1, B3, C5, E5, F4, and G4 are all higher than 0.3, and the weights of other indexes are all less than 0.3. This shows that each index has a different weight and emphasis on English teaching evaluation. (4) Taking a certain teacher as an example to assess English proficiency can effectively analyze the key indicators of English teachers and enable the teacher to make corresponding improvements and formulate strategies. On the whole, the teacher has strong writing ability and listening ability; the ability of speaking and translating is slightly weak, both of which are about 0.8; for listening analysis, idiom and sentence ability are generally to be enhanced, about 0.8. (5) The comprehensive scoring of English teaching is carried out, large difference in scoring values is avoided, and fairer test results are given. It is found that after big data analysis, the key indicators of English are analyzed accurately, the classroom teaching is diversified, and the students’ final classroom evaluation reflects well, so this method has obvious advantages.
Artificial Intelligence

The data provided by the Internet, plus the cloud-based computing power it allows, have helped develop machine learning (ML) and artificial intelligence (AI). Conversely, AI promises to unlock the value of the data being created. The ideology underlying Internet governance will have an effect on the flow of data and therefore AI. The Silicon Valley Open Internet favours open data, while the DC Commercial Internet allows rightsholders to monetize the data they have, implying returns to integration, while allowing privacy issues to be resolved by contract (privacy policies). The Beijing Paternal Internet provides other means for privately held data to be used in the national interest, while also supporting integration. The position is most complex with the Brussels Bourgeois Internet, where respect for human rights, exemplified by GDPR, makes it harder to accumulate data to train ML algorithms, and so may have a negative effect on the AI industry.
Meta-View of Blockchain Technology Tensions in Organizational Implementation and Use

Blockchain inherits tensions that depend on its infrastructure design as well as distinctive features of, among others, smart contracts and storage mechanisms.Studies propose coping strategies for companies that deal with blockchain-related tensions, but so far suggestions are characterized by context-and casespecificity.This paper proposes a meta-view on tensions arising from the implementation and usage of blockchain in organizational contexts.A structured literature review is conducted to condense existing insights from the literature to a meta-view on blockchain-related tension.A framework provides insights into different types of tensions.The framework has two aims: (1) providing a foundation to jointly build insights and IS theorization on blockchain tensions without being case-and context-sensitive.( 2), it provides food for thought for companies that want to implement or use blockchain, which serves as first step toward developing recommendations that guide companies through identifying and managing tensions arising from blockchain implementation and usage.
The Impact of Culture on Online Toxic Disinhibition: Trolling in India and the USA

The pervasiveness of online trolling has been attributed to the effect of online toxic disinhibition, suggesting that perpetrators behave in less socially desirable ways online than they do offline.It is possible that this disinhibition effect allows for everyone to start on a level playing field online, regardless of race, gender, or nationality, but it is likewise possible that the disinhibition effect is context-dependent and sensitive to socio-cultural variations.We aim to explore if toxic online disinhibition effects depend on national culture and gender by examining the extent of trolling towards tweets by Americans and Indians, from both genders.Content analysis of 3,000 Twitter posts reveals that significantly more trolling comments were posted on tweets by Americans than by Indians, and on tweets by women than men.We conclude that the online disinhibition effect may exacerbate, replicate, or mediate existing socio-cultural differences, but it does not eliminate them.
Calcareous Nannofossils Biostratigraphy of Shiranish Formation (K-306) well, Northern Iraq

Twenty Samples of Shiranish Formation from the well (K-306), Kirkuk area, northern Iraq, are collected and studied on the basis of stratigraphic ranges of the recorded calcareous nannofossils.Eighty-nine species in the studied section reveals five biozones arranged from oldest to youngest as follows: 1.Quadrum trifidum Interval Biozone (CC22) Part 2.Tranolithus phacelosus Interval Biozone (CC23) 3.Rienhardtites lives Interval Biozone (CC24) 4. Arkhangelskilla cymbiformis Interval Biozone (CC25) 5. Nephrolithus frequens Rang Biozone (CC26) PartThese Biozones are correlated with other calcareous nannofossils biozones, from both local and regional sections, leading to conclude the age of Campanian-Maastrichtian.
Machine Learning for Fatigue Estimation and Prediction “An Introduction Study”

Fatigue is considered as reduced workability and motivation that affects physical, emotional, and mental activeness. It is a critical concern that influences the precision and accurate implementation of some tasks or the emotional condition. Early detection of fatigue onset is crucial, such that preventative or corrective controls may be presented to minimize work-related traumas, the inexact performance of a task that require high-level accuracy, as well as to avoid making a wrong decision as a result of tiredness. Our goal is to create a non-invasive, proactive model for real-time fatigue estimation based on typical features as tremor, heart rate, and blood oxygen saturation. We expect to set up a relation among the handshaking, heart rate, and oxygen level on one side and the weariness onset on the other. We will use a compact high-precision accelerometer to capture the low-frequency physiological tremor and an optical sensor to detect the heart rate and blood oxygen saturation. Intelligent learning algorithm will be used to personalize user characteristics, such as baselines of the tremor, heart rate, and oxygen level.
Comparative Study of Individual and Hybrid Renewable Energy Systems (Photovoltaic, Wind Energy and Hybridization). Controlled by Fuzzy Logic Control

The present paper describes and evaluates the performances of individual sources of photovoltaic system (PV), wind energy conversion based on permanent magnet synchronous generator (PMSG), and hybrid system that combines both sources (PV/WEC).This is done to determine which of them would be more efficient to provide reliable power with better performances based on their performances comparison.A fuzzy logic control (FLC) is used to maximize the output power of each of the mentioned systems.For the grid connection, an inverter is used to interconnect the systems controlled by the field oriented control (FOC) technique.The FOC technique aims to efficiently decouple the active and reactive powers and achieve a constant DC output voltage with a better power factor.Modeling using different control strategies has been thoroughly examined and discussed.The effectiveness of the control techniques was tested using MTLAB/Simulink software under varying conditions of sunlight, wind speed and output load adjustment.The simulation results confirmed the hybrid system higher efficiency and ability to supply a reliable power.The FLC controller robustness emphasized the instantaneous variation of weather variations and the feasibility of the decoupled control to guarantee a unity power factor.
63.3 GOOGLE'S EVOLVING APPROACHES TO COUNTERING HATE SPEECH

Participants will understand how a major technology company approaches the problem of hate speech on its multiple platforms such as YouTube.
Dialectica Logical Principles

Gödel' s Dialectica interpretation was designed to obtain a relative consistency proof for Heyting arithmetic, to be used in conjunction with the double negation interpretation to obtain the consistency of Peano arithmetic. In recent years, proof theoretic transformations (so-called proof interpretations) that are based on Gödel's Dialectica interpretation have been used systematically to extract new content from proofs and so the interpretation has found relevant applications in several areas of mathematics and computer science. Following our previous work on 'Gödel fibrations', we present a (hyper)doctrine characterisation of the Dialectica which corresponds exactly to the logical description of the interpretation. To show that we derive the soundness of the interpretation of the implication connective, as expounded on by Spector and Troelstra, in the categorical model. This requires extra logical principles, going beyond intuitionistic logic, namely Markov's Principle (MP) and the Independence of Premise (IP) principle, as well as some choice. We show how these principles are satisfied in the categorical setting, establishing a tight (internal language) correspondence between the logical system and the categorical framework. This tight correspondence should come handy not only when discussing the applications of the Dialectica already known, like its use to extract computational content from (some) classical theorems (proof mining), its use to help to model specific abstract machines, etc. but also to help devise new applications.
Global and national tracks of mobility of graduates of educational institutions in Russia

Introduction. Involvement in global information flows, holding major international events in Russia, focusing on interaction with foreign universities and partners creates conditions for the formation of modern youth's focus on the global track of mobility – admission to educational organizations of foreign countries. At the same time, role and quality of education in Russia in the global market are increasing through the development of Russian education, internationalization and networking of universities. Such tendencies to increase mobility in education naturally require a study of the prevalence of the ideas of mobility in general and in certain areas among schoolchildren and university students. The aim of the study is to reveal the prevalence of the ideas of mobility (potential mobility), both within Russia and abroad, among graduates of educational institutions (at different levels). Materials and research methods. The study involved 1136 graduates of educational institutions in Ekaterinburg, of which 30% are graduates of secondary schools, lyceums and gymnasiums, 60% are graduates of bachelor's degrees from 4 universities, and 10% are graduates of master's degree from 3 universities. Research results. A study conducted in 2020–2021 indicated the following trends: the higher the level of education, the higher the value of the educational environment in the country of residence, the more broadly represented the national track of mobility (schoolchildren – 46%, bachelors – 51%, masters – 54%). Among the global market of educational services for all graduates of educational institutions in Russia, priority is given to Europe. Among bachelors, there are more of those who are confident that they can find the desired job in Russia (21%) than in another country. Master students are more confident in the possibilities of working in their specialty in Russia (36%). The older the graduate becomes, the more rational motives prevail in the track of mobility. Conclusion. The study of potential mobility allows us to conclude that the predominance of the national track of mobility is directly proportional to growing up, the older the respondent, the more rationally he approaches the choice of a further place of study and residence, taking into account the possibilities, both intellectual and financial. Thus, it becomes obvious why sufficiently high figures of potential mobility do not become as high indicators of real educational and labor emigrations.
Sarcastic Sentiment Detection and Polarity Classification of Tweets Using Supervised Learning

Nowadays, due to the rapid growth in web technologies and internet usage, there is an enormous amount of data available in WWW and also growing progressively. The data includes online learning, exchanging ideas and opinions, etc. People are using social networking websites such as Twitter, Facebook, Instagram, Google+ as a common platform for all these. These platforms nowadays have become very popular as they permit people to share and exchange their views about any topics/events and have considered by the researchers for sentiment analysis, opinion mining, text summarization, question answering, etc. In this paper, we proposed the approach to classify the tweets into sarcastic and non-sarcastic sentences. Initially, Twitter data is preprocessed and feature extraction is done that considers n-grams, POS tags, term position and frequencies. Further, the approach use machine learning and deep learning algorithms for identifying sarcasm in tweets. Further, the classification algorithms such as Naive Bayes, Decision Tree, Random Forest and CNNs used to classify the polarities of non-sarcastic sentences. The experimental results are promising with good classification accuracy.
DETECTION AND CLASSIFICATION OF HATE SPEECH

The challenges that are to be faced while handling with hate speech is not a new thing. From thepast few years due to the boosted usage of internet, hateful activities across social media is increasing rapidly. Improved technology has made it possible to create a platform where people can feel free to share their opinions and experiences.it wouldn't be a problem if this is just the case. but we can also see hateful comments running throughout the social media targeting a person or a community. Hate speech is the statement that targets a person or community of people discriminating based on caste, creed, nationality etc. Our project aims at resolving the above problem by using Machine Learning techniques to automatically detect hate speech and classify them into various classes such as extremely positive, positive neutral etc. We have used classifier that works based on the lexicons and finally compare it with other classifiers that doesn't use lexicons. Aimed beneficiaries of this model are the people who are being targeted on social media. Based on the results they can calculate intensity of the comments.
Noise Reduction in Electrical Signal Using OMP Algorithm Based on DCT and DSC Dictionaries

The noise is the most common issue present in all signals. Depending on the process or application, the reduction of the noise is mandatory mainly in areas such as signal classification, pattern recognition, and training process, among others. In recent years, diverse methodologies for noise reduction have been proposed, but they have left some issues with no solution. Such are the noise reduction in signals immersed in white noise without changes in their amplitude or phase or the high performance of recovering components of the desire signals distributed among the frequency spectrum. Also, filtering techniques without significant changes in signal phase and amplitude are necessary. This article proposes a methodology for noise reduction based on the orthogonal matching pursuit algorithm with dictionaries constructed from kernel functions of the discrete cosine transform and discrete sine transform. The methodology is proved in synthetic signals and real electrical signals, reaching noise reduction of white noise (~34 dB in electrical signals) and recovering without distortion.
Design-build of photovoltaic panel data logger pressure

The scarcity of fossil fuel sources and the growing energy demand has resulted in more intensively searching for alternative energy. One alternative energy source that is suitable for the equatorial region is solar energy. One of the technologies for utilizing solar energy that has begun to be widely used in Indonesia is the photovoltaic (PV) system. The output of PV is highly dependent on environmental conditions, especially the intensity of the sun and temperature. In addition to these two factors, shading (shadows) and soiling (dust) also affects the PV output. So, this must be observed at all times by monitoring the voltage and current as the PV output. This study aims to design a PV panel instrumentation structure based on a data logger. PV output data in the form of voltage and current and environmental conditions such as ambient temperature and solar intensity were recorded in real-time. The measurement results from the data logger will be compared with manual measurements. PV output data, output voltage and current, as well as sunlight intensity were compared with measurements using an avometer. Temperature data will be compared with thermocouple measurements. PV in this study will be connected to a 1kOhm load resistor. The results of the data logger and manual measurements indicated an insignificant difference. The manual measurement was conducted every hour, from 09.00 – 16.00. The maximum differences for voltage, PV output current, pyranometer voltage, and ambient temperature are 0.89 V, 0.0007 A, 0.00014 V, and 0.25oC, respectively.
MFSL-Net: A Modality Fusion and Shape Learning based Cascaded Network for Prostate Tumor Segmentation

Contouring prostate tumor in magnetic resonance images is a prerequisite for diagnosis. Automatically segmenting blurred lesion regions is challenging and requires fully leveraging multi-parameter MR images. This paper proposes MFSL-Net, an end-to-end network that cascades two novel sub-networks: 1) a modality fusion network that selectively fuses information of two MRI modalities by expanding a dual-stream CNN with spatial and channel attention modules; 2) a shape learning network that integrates shape learning and context learning to recognize the shape and edge information while preserving high-resolution semantic information. We justify MFSL-Net’s design by ablation experiments and compare its performance with the state-of-the-art approaches. Experimental results show a 3.6% improvement in Dice Similarity Coefficient, which confirms the effectiveness of MFSL-Net.
The Rural School and the Rural Teacher: Productive Russian and International Practices

The comparative analysis of Russian and foreign theory and practice aims at identifying productive practices of modern rural schools, professional training and development of rural teachers. Since the sociocultural, deficiency and ambivalent approaches are determined as basic for this study, their verification allows for a constructive balance in the development of rural schools and teachers as well as for positive changes in the sociocultural educational situation in rural settlements. The comparative analysis is based on theoretical and empirical studies from different countries of the world. The authors draw on the data and analytics of large-scale international studies, results of foreign and Russian researches, international documents of educational management, statistics and media information. They also rely on their long-term experience of teaching and organizing continuous professional training for rural teachers. A rural school teacher's activity is considered as professional, determined by the specificity of the sociocultural educational situation with its differentiation, inconsistency and instability, as well by the characteristics of modern rural schools, including their social mission, multifunctionality, openness, instability/variability of its position, the latter brought about by the increasing paucity of rural school students. These factors directly determine the specificity of teaching in rural areas: educators have to teach multiple subjects and fulfill multiple functions; they are involved in local community life and often have to changes the type of their professional activity. The chain of interrelated problems in the professional activity of rural teachers is considered within the framework of their integral, professionally-oriented development. The productive Russian and foreign practices of mixed-age teaching in rural schools are underpinned by the idea of relations in mixed-age child and child-adult communities as a system-forming factor in the modern information society. The authors determine and give grounds for the following priorities in modernization of the rural school and rural teacher training: formation and development of rural schools as sociocultural educational centers of settlements; establishment of federal and regional network educational centers to promote and support mixed-age child-adult educational communities that would function as a tool for solving vital problems of local communities and rural development; mixed-age education as a productive educational technology in small rural school; personalized training for rural teachers. The study can be useful for teachers, school administrators, researchers of lifelong education for rural teachers, and pedagogical students.
Scientific Study of Serverless Architecture, Implementation and Pros and Cons

This paper will explain the concept and need for the serverless architecture. In this concept the need for separate infrastructure to install application is not there. In order to exchange data, client and servers are needed where client will raise query to the server and the centralised server which has the information will respond with the results to the client. Here, the server is a centralised storage unit in which all the details are stored and that can be accessed remotely. In a server less architecture this server can be implemented without having the need for infrastructure which is known as serverless architecture. The paper will explain the process of implementation of the serverless architecture, its advantages, disadvantages, challenges and characteristics.