Reviewerly/exHarmony huggingface dataset:
The main directions of introducing bachelors-future teachers to research activities

The article actualizes the problem of introducing bachelors-future teachers to research activities. Today, in connection with the reform of the higher education system, increased attention is paid to the competence of future teachers. Society requires a competent, creative, initiative, independent specialist, competitive in the labor market, able to develop ideas and find non-standard solutions to professional problems. For the most successful implementation of the goals of professional training of future specialists in a pedagogical university, research activities should become an integral part of it. Thus, the provisions of the Bologna Declaration speak about the fundamental nature of education, the focus on training specialists who are able to engage in science. Socio-economic progress is impossible without science. The authors, having analyzed the scientific and methodological literature on the problem of introducing bachelors-future teachers to research activities, identified the most effective areas that improve the quality of this process. Among them, the authors include: the use of the research principle in the process of training future teachers; the implementation of the project-research model of “learning through action”; the construction of training based on a competence-based approach; their involvement in the research space of the university. The article describes the main types of research activities in which future teachers can be involved in order to form research skills. These are: a pedagogical workshop; an experimental platform; participation in scientific, practical, theoretical and pedagogical conferences, seminars; compilation of a reference book, dictionary, thematic collections (together with teachers); writing articles in collections, magazines, newspapers; preparation of reports, speeches; development of abstracts on topical topics; conducting diagnostic studies; studying at the master’s degree, and then postgraduate studies, job application ( long-term plan).
Identifying Malicious Accounts in Social Media Based on Online Promotions

There is a developing number of individuals who hold accounts via web-based networking media stages however conceal their character for pernicious purposes. Tragically, almost no research has been done to date to distinguish counterfeit characters made by people, particularly so via web-based networking media stages. Online social media step by step incorporate monetary capacities by permitting the utilization of genuine and virtual money, filling in as new stages to have an assortment of organizations, for example, online limited time occasions, where clients can become virtual assesses as a compensation for going to such occasions. Both NSOs and business stakeholders are essentially concerned when Attackers actualize an assortment of records to gather virtual money from these occasions, making these occasions insufficient and the outcome in critical budgetary misfortune. It turns out to be critical to proactively identify these malignant records before on the web and special exercises in this manner they decline their need to be remunerated. In this paper, we have present a new framework, called ProGuard, for accomplish this by deliberately coordinating highlights that describe accounts from three viewpoints, including their overall conduct, their top-up designs and the utilization of their cash. We directed various experiments dependent on information gathered by Ten cent QQ, a world chief OSN with coordinated budgetary administration exercises. Exploratory outcomes have indicated that our framework is equipped for accomplishing a high recognition pace of 96.67% at a low false positive pace of 0.3%.
Pengaruh Reward dan Gaya Mengajar Terhadap Prestasi Belajar IPS di SD Negeri 2 Wonco

This study aims to determine (i) the effect of rewards on social studies learning achievement; (ii) the effect of teaching style on social studies learning achievement; and (iii) the effect of reward and teaching style simultaneously on social studies learning achievement at SD Negeri 2 Wonco. Methods This research uses the type of ex post facto research. Data collection techniques through questionnaires. The population is all students of SD Negeri 2 Wonco, totaling 136 people for the 2020/2021 academic year. The sampling technique used purposive sampling so that a sample of 45 was determined. The data analysis technique uses prerequisite analysis and inferential analysis. The results of the study show that rewards have a significant effect on social studies learning achievement, this indicates that if the reward is good, the learning achievement of students increases; teaching style has a significant influence on social studies learning achievement, this shows that if the contribution of teaching style is in a good category, the learning achievement of students increases; reward and teaching style simultaneously have a significant effect on social studies learning achievement, this shows that the contribution between reward and teaching style affects the improvement of students' learning achievement.
RRTs Postprocessing for Uncertain Environments

Path planning is one of the central tasks to be solved in mobile robotics. Rapidly Exploring Random Tree is one of possible alternatives addressing path planning. While it does not deliver optimal solution it provides a good performance that is crucial for most cases in mobile robotic systems. Unfortunately the algorithm may produce unnecessary or even dangerous waypoints that might lead to collisions with obstacles or other robotic systems. A significant part of the possible collisions are caused by uncertainty of robot positioning or obstacle sensing. In this paper we propose a set of plan post processing steps to estimate and decrease the possibility of collisions during plan execution.
Seal Extraction and Incomplete Restoration in Complex Document Image

This paper proposes a method to quickly locate and extract the seal from the complex background. First, this paper uses the color model and two-dimensional projection method to quickly distinguish the local block(s) with red seals from other red interference information. This step not only reduces the complexity of stamp extraction work, but also increases the accuracy of positioning. Then use the specific shape feature of the seal to locate the seal image. Then, the difference in color is used to separate the seal from the background covered by the seal. Finally, use methods such as filling to repair the incomplete seal. Experimental results show that the proposed method can better locate, extract and repair the seal in most cases, and complete the entire task faster than most of the compared techniques.
Priority Based Job Scheduling Strategy in Cloud Computing

Cloud computing is one in every of the booming technologies within the gift day. range of users availing cloud services is increasing day by day, that successively needs higher performance of the cloud. Cloud information Center is one in every of the key elements of cloud computing. one in every of the key challenges of cloud information center is handling and mating ample requests from the users. Distributing the load fairly across all the on the market machines is termed load reconciliation and therefore the main aim of load balancing is to assist in achieving high resource utilization and user satisfaction. Therefore, the load reconciliation algorithms used should be terribly economical and may reach the goals of the user. during this paper AN formula is planned that balances the load supported the priority of the virtual machines and state of the virtual machines employed in the cloud. Allocating the resources on virtual machines supported priority achieves the higher response time and process time. Load reconciliation ensures all instances in a very node within the networks do the equal quantity of work any instant of your time. Priority based mostly resource provision to enhance the employment of resources and reducing latency of cloud services.
Impact of higher music education on coping with stress during COVID-19

The article is dedicated to the study if students with special musical education have any benefits of stress coping over students of other specialties during the pandemic. The main purpose is to study the attitude of student musicians to overcome stressful situations caused by COVID-19 in the learning process. Research objectives include: current state of music education in the context of forced quarantine distance learning; the impact of forced quarantine distance learning on stress among students of music and non-music specialties; the analysis of stress coping skills and the impact of music education on them; recommendations for improving the psychological and pedagogical interaction of the participants in the educational process. The study involved 160 respondents, 80 of them are music students and 80 students of other specialties that do not belong to the study of musical art. To collect information and data, the study participants were asked to fill out a Google form. The results of the study show that online learning is very time-consuming and that losing a satisfactory work-life balance is stressful. But students became more organized in managing their activities. Internet platforms have proven useful for sharing materials, communicating, sharing information and content, and keeping track of all work done. Thus, there is a tendency towards easier tolerance of stress by musicians, although our study showed that with a slight margin of 80.6%, people without musical education consider themselves happier by 82%. This is also confirmed by the fact that non-musicians are more optimistic about their future according to the results obtained on the Beck's Hopelessness Scale, where 2 units are for musicians and 1 for non-musicians. These results indicate that hopelessness has not been identified and students are optimistic about their future. In the context of stress coping recommendations for students are provided. In conclusion, based on the information gained and own experience there is a variety of ways to obtain benefits from both online and offline learning forms for both musicians and non-musicians.
Medical data encryption in private cloud based on MAR

It’s easy to exchange files, folders, and emails in a private network with the aid of a private cloud (PriCld). However, the most common attack with this sort of system is the guessing of the password. The unencrypted connection makes it potential for a man-in-the-middle attack (MaMiAtk) to occur at times. Scanners used to discover vulnerabilities in the system and exploiting them are also a major issue. Therefore, a system that can withstand assaults such as MaMiAtk, Denial of Service Attack (DoS attack), and password guessing is required. In the presented study, a log-based analysis approach has been recommended to guard the system against assaults such as DoS attack, password guessing, and automated scanners. We also use encrypted channels to prevent attacks such as MaMiAtk.
Formulating Neural Sentence Ordering as the Asymmetric Traveling Salesman Problem

The task of Sentence Ordering refers to rearranging a set of given sentences in a coherent ordering. Prior work (Prabhumoye et al., 2020) models this as an optimal graph traversal (with sentences as nodes, and edges as local constraints) using topological sorting. However, such an approach has major limitations – it cannot handle the presence of cycles in the resulting graphs and considers only the binary presence/absence of edges rather than a more granular score. In this work, we propose an alternate formulation of this task as a classic combinatorial optimization problem popular as the Traveling Salesman Problem (or TSP in short). Compared to the previous approach of using topological sorting, our proposed technique gracefully handles the presence of cycles and is more expressive since it takes into account real-valued constraint/edge scores rather than just the presence/absence of edges. Our experiments demonstrate improved handling of such cyclic cases in resulting graphs. Additionally, we highlight how model accuracy can be sensitive to the ordering of input sentences when using such graphs-based formulations. Finally, we note that our approach requires only lightweight fine-tuning of a classification layer built on pretrained BERT sentence encoder to identify local relationships.
Personal Development As A Key Competence In Formation Of Professional Skill Teacher

The article deals with pedagogical skills, professional competence of the teacher - the components of its professionalism is essential to the effective solution of professional tasks. The professional competence of the teacher - the components of its professionalism, is a condition for effective professional applications. The substantiation of self-development, as a key competence in the development of professional skills and competence. This is due to the ongoing transformation in the education system, the changed requirements for the personality and activities of the teacher. The results of empirical research presented 80 preschool teachers about the level of formation of their important components of pedagogical skills: natural prerequisites due to the selection and successful implementation of professional activity; pedagogical abilities as a socio-psychological basis for improving pedagogical activity; professionally important qualities of the individual teacher. According to the survey of all the studied parameters revealed the prevalence of high and medium levels, with somewhat higher values at high level. The low level was observed in a small amount of teachers in 1 component (6.3%), but component 3 - he has already identified 20% of the subjects that may be caused by low self-esteem, critical attitude towards themselves, an objective reality, which hinders the implementation of high-quality professional activities. However, the study of ideas about the characteristics of pedagogical activity showed that they are at the ascertaining and fragmentary level for all respondents. The revealed contradiction in the ideas about the components of professional skill shows the directions of professional self-development of teachers.
REPLICATION IMAGE DETECTION USING CONVOLUTIONAL NEURAL NETWORK

The ease of access to image data has led to overuse of repeated images at various instances which leads to increases duplication and redundancy in many industries. Advanced editing techniques which are available very easily, encourages original copyrights images to be misused. This results in lack of originality in data generated at every level. Common solutions include allowing manual selections of duplicate images or compares images pixel by pixel. The conventional method is to use 3 branch Siamese Convolution model to detect duplication of medical images. We propose to develop a model to detect duplication in everyday images by training a Siamese Convolutional Neural Network and try to achieve greater accuracy than previously developed solutions. Using Grad-Cam network inspection we propose to inspect the decisions taken by the CNN upon detecting duplication in images.
LibGuides: ASL for Beginners: ASL Dictionaries

A resource tool for those interested in learning ASL who have no experience with the language.
Hybrid Measurement of the similarity value based on a Genetic Algorithm to improve prediction in a collaborative filtering recommendation system

Recently, a recommendation system (RS) has been widely used in several disciplines, like education, economics, scientific researches and other related fields. Based on the user interface, preferences and constraints the personalized RS has been rated as the most effective method. Collaborative filtering (CF) is one of the primary applications that researchers use for the prediction of the accuracy rating and recommendation of objects. In this filtering method nearest neighbour is identified to a recommendation system. The existing similarity measures use only the co-rated items ratings while calculating the similarities between a pair of users or items. For example, the two standard methods used to measure similarities are cosine similarity (CS) and pearson correlation similarity (PCS). In the present study, we have proposed a model to improve the prediction accuracy of RS using the merge output of CS with PCS based on a Genetic Algorithm (GA). The results show superior features of GA and its ability to achieve more correct predictions as compared to both CS and PCS when used alone.
A Scrutiny on opportunities and challenges of block chain

A block chain can be defined as a distributed technology that is associated with bitcoins and they can form a chain of blocks. Here each block contains information and data which are packed together and they are also verified. Blocks are validated and they are added to the chain in previous blocks. This technology is having numerous benefits like decentralization , anonymity , audibility and it has been used in many areas like financial services , risk management , Internet of things , cryptocurrency etc. This paper deals with both technological and application perspectives of block chain. Introduction to block chain consensus algorithms, technical challenges and some recent solutions to tackle these challenges area also discussed here.
Removing personal information from structured documents: a graphic and text based solution.

Preserving privacy in imageIn the last years data analytics is increasingly applied to scanned documents stored in the format of images. However,this kind of documents presents a large number of sensitive or potentially sensitive information, defined as “PII” (Personally Identifiable Information) in compliance with the GDPR, the General Data Protection Regulation. The project presented in this Master Thesis has been performed in collaboration with Reale Mutua Assicurazioni and aims to develop a complete anonymization tool for scanned document, in particular structured documents, such as Invoices. In order to deal with text contained in images OCR, Optical Character Recognition, has been exploited and its output has been elaborated and analyzed by a NER, Named Entity Recognition, module to recognize several classes information. The NER module is based both on fuzzy regular expressions for pattern - based attributes, and on specific recognition techniques based on the semantic content of words for free - structured attributes. Words detected as sensitive information by NER module are obscured and replaced by their general category by the Anonymization module. However, in this type of documents the graphical structure plays a fundamental role in deciphering the semantic content by grouping together related information, effectively replacing the role played by traditional grammar and syntax in natural language processing. For instance, contact information is interpreted differently if associated to a person or to a company. In addition, the presence of keywords can improve the accuracy of the NER especially in the case of OCR errors or ambiguities. For this reason, a module to perform document segmentation has been developed, based on a Deep Neural Network. It has been trained over a synthetic dataset of structured documents generated by custom document Generation. The combination of the anonymization tool and the document segmentation tool allows to perform a more selective anonymization, only on PII sections such as customer information and preserving information related to companies. The tool was tested on both real and synthetic documents. analytics: removing personal information from images
HOW THE PSYCHOLOGICAL SAFETY OF EMPLOYEES INFLUENCES JOB PERFORMANCE IN THE INSURANCE INDUSTRY? THE MEDIATION ROLE OF ORGANIZATIONAL COMMUNICATION AND ORGANIZATIONAL LEARNING

Due to the nature of the insurance industry, it is necessary to explore factors that can influence job performance. To understand how psychological safety can enhance the performance of employees in the insurance industry, the present study examines the role of organizational communication and organizational learning. This study used a structural equation model of a questionnaire for analysis. The results show that job performance is directly affected by psychological safety and organizational learning. Organizational communication, however, only affects job performance indirectly through organizational learning. The results of the mediation analysis show that, in addition to the effect of psychological safety through organizational learning, psychological safety also promotes the learning behavior of employees through organizational communication, enhancing job performance.
La capture d’écran face aux fils de discussion étendus sur Facebook

EnglishThis article discusses the methodological implications of using screenshot in research on native digital corpus. It addresses some problems related to the choice of screenshot in works on native discursive productions online, while very few researchers are interested in extended discussion threads that really highlight the interactive and participatory characters of Web 2.0. The proposals make it possible to consider an analysis of native written digital conversations based on the description, structural organization and functioning of the various forms of native online conversation, from research protocols designed specifically to report on them. The researchers in language sciences are therefore invited to pay more attention to native written digital conversations characterized by forms of discourse and conversation that fall within a new linguistic order : the technolinguistic order. francaisCet article revient sur les implications methodologiques de l’utilisation de la capture d’ecran dans les recherches sur les corpus numeriques natifs. Il aborde certains problemes en rapport avec le choix de la capture d’ecran dans les travaux sur les productions discursives natives en ligne, alors que tres peu de chercheur.euse.s s’interessent aux fils de discussion etendus qui mettent veritablement en evidence les caracteres interactif et participatif du web 2.0. Les propositions faites permettent d’envisager une analyse des conversations numeriques ecrites natives articulee autour de la description, de l’organisation structurale et du fonctionnement des diverses formes de conversation natives en ligne, a partir de protocoles de recherche concus specifiquement pour en rendre compte. Les chercheur.euse.s en sciences du langage sont donc invite.e.s a s’interesser davantage aux conversations numeriques ecrites natives caracterisees par des formes d’exercice du discours et de la conversation qui relevent d’un ordre linguistique nouveau : l’ordre technolinguistique. portuguesEste artigo discute as implicacoes metodologicas da utilizacao da captura de tela na investigacao de corpora digitais nativos. Discute algumas questoes relacionadas com a escolha da captura de tela em trabalhos sobre producoes discursivas nativas on-line, uma vez que pouquissimos pesquisadores/as estao interessados/as em fios de conversa ampliados que realcem verdadeiramente as caracteristicas interativas e participativas da web 2.0. As propostas apresentadas permitem-nos prever uma analise das conversas escritas digitais nativas articuladas em torno da descricao, organizacao estrutural e funcionamento das varias formas de conversas nativas on-line, com base em protocolos de investigacao especificamente concebidos para delas dar conta. Os pesquisadores/as em ciencias da linguagem sao, portanto, convidados/as a concentrarem-se em conversas digitais escritas nativas caracterizadas por formas de discurso e conversacao que fazem parte de uma nova ordem linguistica: a ordem tecnolinguistica.