Reviewerly/exHarmony huggingface dataset:
The practical activity of development of a system of tasks as an important condition for training a future teacher for a digital school

The problem and the aim of the study. A teacher of a digital school, according to the requirements of the standard of professional activity, must possess such universal qualities related to information and communication technologies, formed communicative competence, the ability to work in a team. The formation of the relevant skills within the framework of university education is complicated by a number of problems of a different nature. The authors suggest organizing a practice of designing a system of specially selected tasks to improve the training of future teachers of a digital school. Research methods. The most important idea is the acquisition of new knowledge by creation and solving tasks. The solution of the system of educational, specially designed tasks supports the implementation of the provisions of the system-activity approach to learning. The pedagogical experiment involved 120 students of specialty 44.03.01 Pedagogical education (two training profiles, bachelor's degree level), Vyatka State University, Kirov, Russia Federation. Statistical verification of the obtained results was made using Fisher's criterion (angular transformation). Results. Students of the experimental group were involved in practical activities to design their own tasks on the example of studying the theory and methods of teaching Informatics (situational-motivational; support; border): self-determination of the plot, the development directions of intensification and extensification. Statistically significant differences were revealed between the experimental and control groups in terms of the level of professional training φcrit &lt; φemp (1.64 &lt; 2.558). In conclusion, the authors generalized the features of the organization of practical activity for the development of a system of own tasks for a digital school: the choice of the first task, the use of information sources of various nature, learning with and without a computer, group discussion of a result, resolving contradictions, "ignorance–knowledge–understanding–skill–proficiency", work in conditions of uncertainty, etc.
The effect of using Different model of images in Augmented Reality on cognitive achievement development of high school students in Jazan in computer curriculum: أثر اختلاف نمط عرض مصورات الواقع المعزز في تنمية التحصيل المعرفي لطلاب الثانوية بمنطقة جازان في مادة الحاسب الآلي

The purpose of the research is to determine the effect of the difference in the mode of presentation of the enhanced reality models in the development of the cognitive achievement of secondary students in Jazan region in computer science, the researcher used quasi-experimental approach in comparing the 2D image models of Augmented reality to the first experimental group, and teaching the pattern of 3D image models of Augmented reality of the second experimental group, to ascertain the hypotheses of the research and to reveal the relationship between the independent variable and the dependent variable, the sample consisted of (60) students: (30) students in the first experimental group, which was studied using the two-dimensional Augmented Reality models, And (30) students in the second experimental group, which was studied using the pattern of Augmented Reality three-dimensional, the results showed that there were statistically significant differences at (α≤05.0) between the mean scores of the students of the first experimental groups studied using the two-dimensional Augmented Reality models, the second experiment, which was studied using the Augmented three-dimensional image models, in the post-application to test cognitive achievement, for the second experimental group studied using the three-dimensional Augmented Reality models, In the light of the results, recommendations and suggestions were made to develop the cognitive achievement of secondary students in computer and various subjects.
Modified Fuzzy Approach to Automatic Classification of Cyber Hate Speech from the Online Social Networks (OSN’s)

The extensive use of online media and sharing of data has given considerable benefits to humankind. Sentimental analysis has become the most dynamic and famous application area in current days, which is mainly used in knowing the public's opinion. Most algorithms of machine learning are used as principle methods for sentimental analysis. Even though several methods are available for classification and reviews, all of them belong to a single class of classification which differs among several different classes. No methods are available for the classifying of multi-class instances. Therefore, fuzzy methods are used for classifying the instances depended on multi-class for achieving a clear-cut view by indicating suitable labels to objects during the classification of text. This paper includes the categorization of cyberhate information. If there is a growth in dislike speeches of the online social network may lead to a worse impact amongst social activities, which causes tensions among communication and regional. So, there is the most demand for cyberhate conversation detection automatically through online social media. Generally, an updated process of fuzzy words is designed that includes two stages of training for the classification of cyberhate conversation into 4 forms, race, disability, sexual orientation, and religion. Depended on the types of classification, experiments have been conducted on these four forms by gathering different conversations through online media. Systems based on rules of fuzzy approach have been used. This fuzzy with rule-based is for the classification of features using Machine Learning techniques such as the words that implants for future bag-of-words and extraction methods. In this, the cyberhate conversations are taken from OSN's depended on the attributes defined in a dataset using rule-based fuzzy.
The Impact of The Green Human Resources on The Efficiency and Effectiveness of Employees on the Industrial Sector in Sudan: أثر توجه إدارة الموارد البشرية الخضراء على كفاءة وفعالية العاملين في القطاع الصناعي في السودان

The study aims at identifying the orientation of the green human resources administration and its impact of the employee’s efficiency and effectiveness on the industrial sector in Sudan. To realize the objectives of the study, The analytical descriptive method was followed and the questionnaire was used as the main tool for collecting data from a non-probability sample comprised of total 330 employees. The response percentage to questionnaire was estimated 88%. The data was statistically analyzed and processed by AMOSV25 and the reliability of the model was tested by Alpha Corpnakh Test. The study concluded with some results such as there is a partial positive relationship found between the orientations of the green human resources administration and the efficiency and effectiveness of employees. The conclusions were discussed in comparison with the literature reviews and presented a number of proposals for future studies.
Rekonstruksi Lintasan Objek Bergerak Pada Citra Digital Video Dengan Metode Belief Propagation

The control device in an auto-navigation car is a computer assisted by two cameras on the front of the car to determine the three-dimensional coordinates of all pixels of the digital image captured by the camera from frame to frame. So that the computer will be able to determine where the streets are flat or potholes. The purpose of this research is to create a program code that is able to determine the disparity from one frame to the next. With the help of recordings from two cameras, the disparity of any object captured on the two cameras will be calculated for each pixel. This data is used to compare the accuracy of the methods developed in this study. We use a program code developed to calculate the disparity of each frame in the video. The model developed in this study still needs to be studied in order to find a better method.
Reasons for Flouting Maxim in Talk Show

This study is entitled Reasons for Flouting Maxim in Talk Show. The aim is to analyze the types of flouting maxim used by the participants in the talk show through their utterances based on theory of Conversational Maxim proposed by Grice and supporting theory Context of Situation by Halliday &amp; Hasan to see how the maxim is flouted. The data was taken from one of the famous American talk shows which contains various topics of talk and the implementation of the conversational maxim, it is The Ellen Show. The data was collected by using observation method. Descriptive qualitative method was used as a method and technique of analyzing data. The data was presented in a form of words and sentences. The results show that all types of maxim are flouted in the talk show. The most flouted maxim found in conversation is maxim of quantity because the participants deliver more information than it is required even though that experience is based on their experiences.
MG-BERT: Multi-Graph Augmented BERT for Masked Language Modeling

Pre-trained models like Bidirectional Encoder Representations from Transformers (BERT), have recently made a big leap forward in Natural Language Processing (NLP) tasks.However, there are still some shortcomings in the Masked Language Modeling (MLM) task performed by these models.In this paper, we first introduce a multi-graph including different types of relations between words.Then, we propose Multi-Graph augmented BERT (MG-BERT) model that is based on BERT.MG-BERT embeds tokens while taking advantage of a static multi-graph containing global word co-occurrences in the text corpus beside global real-world facts about words in knowledge graphs.The proposed model also employs a dynamic sentence graph to capture local context effectively.Experimental results demonstrate that our model can considerably enhance the performance in the MLM task.
Local Information as an Essential Factor for Quantum Entanglement

Quantum entanglement is not only a fundamental concept in quantum mechanics but also a special resource for many important quantum information processing tasks. An intuitive way to understand quantum entanglement is to analyze its geometric parameters which include local parameters and correlation parameters. The correlation parameters have been extensively studied while the role of local parameters have not been drawn attention. In this paper, we investigate the question how local parameters of a two-qubit system affect quantum entanglement in both quantitative and qualitative perspective. Firstly, we find that the concurrence, a measure of quantum entanglement, of a general two-qubit state is bounded by the norms of local vectors and correlations matrix. Then, we derive a sufficient condition for a two-qubit being separable in perspective of local parameters. Finally, we find that different local parameters could make a state with fixed correlation matrix separable, entangled or even more qualitatively entangled than the one with vanished local parameters.
An Approach based on Machine Learning Algorithms for the Recommendation of Scientific Cultural Heritage Objects

The Scientific Cultural Heritage (SCH) of the Drâa-Tafilalet region in south-eastern Morocco is a rich source of data testifying to the ingenuity of an older generation that has shaped the past of the region.These data must be preserved for future generations, particularly with new technologies and the semantic web.Recommendation systems (RS) are intended to assist prospective users in recommending the most suitable services based on their profile and expectations.The collaborative filtering (CF), content filtering (CB) or hybrid filtering (CF) RS has shown promising results in order to explore the problems experienced especially in CH.However, there are some limitations to be resolved, mostly due to the ability of these methods to build a stable and complete framework, which can provide a complete image of the user profile and suggest the most appropriate offers.This paper presents a hybrid recommender system for SCH data; a field little explored despite its historical importance and the value it generates.The results presented in this paper belong to the data collected from the region of Drâa-Tafilalet in southern Morocco.
The Types of Communication Accommodation Strategies in English as Foreign Language (EFL) Classrooms

English is one of international language which is taught widely in various countries in the world. Entering millennial and industrial 4.0 era, English has important role as the function of English is as a tool or media to communicate with other countries and it is also as language of science, technology, social-economy, culture, and art. Communication Accommodation Theory which consists of communication accommodation strategies are very important to accommodate the students in teaching learning activity. This research aimed at analyses types of communication accommodation strategies are used by teacher when teaching Basic English and the motive of implementing communication accommodation strategies by the teacher Classroom Interactions. Subjects of this research were two the English teachers. This research was designed in qualitative research. The data were collected through voice recorder, interview and documentation. The data were analyzed qualitatively. The results of this study revealed that there were four strategies used in teaching learning process by the teacher such as approximation, interpretability, discourse management and emotional expression. Moreover, the teachers had some main motive to apply these strategies such as to make the students understand, give clear explanation to students and get the students’ attention.
Fine-tuning Transformers for Identifying Self-Reporting Potential Cases and Symptoms of COVID-19 in Tweets

We describe our straight-forward approach for Tasks 5 and 6 of 2021 Social Media Mining for Health Applications (SMM4H) shared tasks.Our system is based on fine-tuning Distill-BERT on each task, as well as first fine-tuning the model on the other task.We explore how much fine-tuning is necessary for accurately classifying tweets as containing self-reported COVID-19 symptoms (Task 5) or whether a tweet related to COVID-19 is self-reporting, non-personal reporting, or a literature/news mention of the virus (Task 6).
AStudy on GBW-KNN Using Statistical Testing

In the 4th industrial revolution, big data and artificial intelligence are becoming more and more important. This is because the value can be for by applying artificial intelligence techniques to data generated and accumulated in real-time. Various industries utilize them to provide a variety of services and products to customers and enhance their competitiveness. The KNN algorithm is one of such analysis methods, which predicts the class of an unlabeled instance by using the classes of nearby neighbors. It is used a lot because it is simpler and easier to understand than other methods. In this study, we proposed a GBW-KNN algorithm that finds KNN after assigning weights to each individual based on the KNN graph. In addition, a statistical test was conducted to see if there was a significant difference in the performance difference between the KNN and GBW-KNN methods. As a result of the experiment, it was confirmed that the performance of GBW-KNN was excellent overall, and the difference in performance between the two methods was significant.
O is for open (as well as optimal, operable, optimistic, organic)

Much as we might like to think of the academy as an enlightened domain of pure knowledge creation, it is inextricably linked to financial and corporate influences. The business of academic publishing is a complex ecosystem of actors, processes, expectations, and perversions. Many of us have encountered—indeed, have reinforced—such entanglements. Very often our academic success depends on learning the rules of engagement and then following them. We research, we write, we publish; we review, we critique, we edit. We make our textual submissions and pay our subscription fees, whether directly to a journal or indirectly through our participation in the institutions, organizations, and libraries to which we are connected. But this system, when we start to unpack it, can present some pretty nefarious effects. Research papers published in for-profit journals are not easily and freely accessible to those outside of institutional life. Yet these papers are generally produced by people with access to public funding, either from research councils or educational institutions. By paying for journal articles that sit behind paywalls, we are effectively transferring tax revenue into the pockets of private corporations. Of course, for those who can’t or don’t want to pay, there are semi- and non-legal options, but even ‘free’ access to PDFs comes with costs (often folded back into commercial publishers’ fee structures).
A Study Concerning The Human Observer Role in Photo-Interpretation and Remote Sensing.(Dept.C)

The study presented in this research shows the important roll of the human being in Photo-interpretation and remote sensing.  Consequently, this paper deals with the observers functions of measuring, recognition, and Photo-interpretation in conjection with the human being characteristics.  These characteristics are classified into three scops:  a- self-confidence concerning the perception of the own l,  b- the internal world-mind, and c- the external world-mind.  The study confirms the importance of human observer's function.
Power-based Side Channel Analysis and Fault Injection: Hacking Techniques and Combined Countermeasure

Over the last years, physical attacks have been massively researched due to their capability to extract secret information from cryptographic engine.These hacking techniques are based on exploiting information from physical implementations instead of cryptographic algorithm flaws.Faultinjection attacks (FA) and Side-channel analysis (SCA) are the most popular techniques of implementation attacks.Aiming to secure cryptographic devices against such attacks, many studies have proposed a variety of developed and sophisticated countermeasures.Hence, the majority of these secured approaches are used for precise and single attack and it is difficult to thwart hybrid attack, such as combined power and fault attacks.In this work, the Advanced Encryption Standard is used as a case study in order to analyse the most well-known physical-based Hacking techniques: Differential Fault Analysis (DFA) and Correlation Power Analysis (CPA).Consequently, with the knowledge of such contemporary hacking technique, we proposed a low overhead countermeasure for the AES implementation that combines the concept of correlated power noise generating with a combined-approach based fault detection scheme.
LongSumm 2021: Session based automatic summarization model for scientific document

Most summarization task focuses on generating relatively short summaries. Such a length constraint might not be appropriate when summarizing scientific work. The LongSumm task needs participants generate long summary for scientific document. This task usual can be solved by language model. But an important problem is that model like BERT is limit to memory, and can not deal with a long input like a document. Also generate a long output is hard. In this paper, we propose a session based automatic summarization model(SBAS) which using a session and ensemble mechanism to generate long summary. And our model achieves the best performance in the LongSumm task.
Haze Removal System using Dark Channel Prior

Mostly in winter season, the Northern area of India is mostly affected due to heavy haze. The road traffic and air traffic is affected due to poor visibility. According to the survey of Ministry of Road Transport and Highways of India, the number of accident due to poor visibility increasing every year. Hence there is need of robust algorithm to enhance the visibility of the camera feed. In the proposed approach, image dehazing algorithm has been present using dark channel prior. The proposed algorithm is developed for outdoor images. The proposed system processed the image through dark channel prior, estimation of atmospheric light, estimation of transmission and scene radiance. The proposed system achieved the promising results on O-Haze dataset.
Computer Networks Optimization using Load Balancing Algorithms on the Citrix ADC Virtual Server

In the digital era and the outbreak of the COVID-19 pandemic, all activities are online. If the number of users accessing the server exceeds IT infrastructure, server down occurs. A load balancer device is required to share the traffic request load. This study compares four algorithms on Citrix ADC VPX load balancer: round-robin, least connection, least response time and least packet using GNS3. The results of testing response time and throughput parameters show that the least connection algorithm is superior. There were a 33% reduction in response time and a 53% increase in throughput. In the service hits parameter, the round-robin algorithm has the evenest traffic distribution. While least packet superior in CPU utilization with 76% reduction. So algorithm with the best response time and throughput is the least connection. The algorithm with the best service hits is round-robin. Large scale implementation is recommended using the least connection algorithm regarding response time and throughput. When emphasizing evenest distribution, use a round-robin algorithm.
APPLYING VLOG IN TEACHING VOCABULARY

The aim of this study is to find out whether or not the use of vlog will enhance the vocabulary of the students. This study used pre-experimental studies consisting of pre-test, treatment, and post-test. The participants in the study were 25 students of the second grade students of Universitas Muhammadiyah Bulukumba. Based on the findings of the study, there is a substantial difference between the mean pre-test score and the mean post-test score, from a very bad classification to a decent classification. In addition, the t-test value of this analysis (16,12) is greater than the t-table value (3,745) with a degree of significance of 0,05. It means that it supports the alternative hypothesis.