Reviewerly/exHarmony huggingface dataset:
Design Radio Network Links to Provide Internet for Pupulation of San Andres de Llamellin-Ancash

In recent years being able to have access to the internet has become a tool not only to be able to communicate in the distance but it is a great tool to be able to feed knowledge, it is because of them that children have a great educational utility and after this pandemic in Peru it was necessary to close schools, to be able to give remote classes or virtual classes. To solve the problem, we propose to be able to design a network of radio links whereby means of a base station of emission and reception, with an antenna of sectorial type and directional antennas to be able to realize a Point – Multipoint link which will be able to manage the quality of signal by means of a routing with functions of control of speeds for each connection of each home. It was the result that the connections of the radio link at an average distance from the coverage that the network had the signal was better and that the connections that were very far or close to the coverage area had complications, but despite this the connections were sufficient to be able to maintain the virtual classes that is what was planned. It is recommended that for a better connection and complete coverage it would be to reinforce the broadcast base with more sectoral antennas in the network. Keywords- Radio link, Point - Multipoint, Router, Download speed, Upload speed.
Integrated Regression Approach for Prediction of Solar Irradiance Based on Multiple Weather Factors

Solar irradiance is the most vital aspect in estimating the solar energy collection at any location. Renewable energy setup at any location is dependent on it and other ambient weather parameters. However, it is hard to predict due to unstable nature and dependence on variations in weather conditions. The correlation of ambient weather factors on the performance of solar irradiance is analysed, by collecting the data using weather API, over the year for a particular location of central India. The training of this non-linear data is carried out with hybrid regression model integrating decision tree regression with Artificial Neural Network (ANN) module. Experimentation is performed using real data of different days from different seasons of the year, also by considering different irradiance conditions. The results demonstrated significant weather factors with moderate positive and negative correlation with solar irradiance, which can be used as a helpful tool to predict it before deployment of solar energy setup.
PEDAGOGICAL REALITY THROUGH INNOVATIONS

Pedagogy as a science of human upbringing needs to be innovated and changed in parallel with changes in science and society, аs at the same time she must be basis for change in both personality and society. The process of upbringing in practice is a reflection of the scientific findings from pedagogy and related sciences. The innovations produced from new knowledge in science have a central force in any science towards advancing the practice, and so in pedagogy. They aim to provide new approaches in the educational process and new quality in practice. Innovation aims to bring dynamics to science and continuous development. The upbringing with the enormous role of positive modifying human behavior and development is essential to the progress of the whole society. Education as a process that takes place from birth to the end of life, have a particular importance in the formal education phase, especially in school. Education within the school period has an pedagogical as well as educational character. Through all its components the upbringing of the intellectual, moral, aesthetic, working and bodily component influences the entire human development. Therefore, every new approach that will be applied in the educational process is important for refreshing the teaching and for enhancing the quality of education in every society. For this reason, it is necessary to look for innovation. Through the globalization of the world, knowledge from other cultures and civilizations is included in the teaching and acquisition of knowledge that enables innovative advancement ways in the educational process. The occurrence of drones related to technological development has enriched visualization opportunities as an important aspect of the educational process. There are also new learning opportunities through unusual themes and imaginations that stimulate thinking and are extremely important for the development of young people. These innovations and many more new approaches that change pedagogical theory and practice have been essential in the educational process of futuristic generations. The paper deals with the topic of innovation in the pedagogical process in primary education in the Republic of North Macedonia. It is a descriptive research wich elaborate the level of application of innovation in the process of education in primary education.
Hybridization of DBN with SVM and its Impact on Performance in Multi-Document Summarization

Data available from web based sources has grown tremendously with growth of the internet. Users interested in information from such sources often use a search engine to obtain the data which they edit for presentation to their audience. This process can be tedious especially when it involves the generation of a summary. One way to ease the process is by automation of the summary generation process. Efforts by researchers towards automatic summarization have yielded several approaches among them machine learning. Thus, recommendations have been made on combining the algorithms with different strengths, also called hybridization, in order to enhance their performance. Therefore, this research sought to establish the impact of hybridization of Deep Belief Network (DBN) with Support Vector Machine (SVM) on precision, recall, accuracy and F-measure when used in the case of query oriented multi-document summarization. The experiments were carried out using data from National Institute of Standards and Technology (NIST), Document Understanding Conference (DUC) 2006. The data was split into training and test data and used appropriately in DBN, SVM, SVM-DBN hybrid and DBN-SVM hybrid. Results indicated that the hybridized algorithm has better precision, accuracy and F-measure as compared to DBN. Pre-classification hybridization of DBN with SVM (SVM-DBN) gives the best results. This research implies that use of DBN and SVM hybrid algorithms would enhance query oriented multi-document summarization.
Japanese Writing Support System with Fast Grammatical Error Correction

There are several problems in applying grammatical error correction (GEC) to a writing support system. One of them is the handling of sentences in the middle of the input. Till date, the performance of GEC for incomplete sentences is not well-known. Hence, we analyze the performance of GEC model for incomplete sentences. Another problem is the correction speed. When the speed is slow, the usability of the system is limited, and the user experience is degraded. Therefore, in this study, we also focus on the non-autoregressive (NAR) model, which is a widely studied fast decoding method. We perform GEC in Japanese with traditional autoregressive and recent NAR models and analyze their accuracy and speed. Furthermore, in this study, we construct a writing support system with a grammatical error correction function. Specifically, the trained NAR model is embedded in the back-end system. We confirm the system’s effectiveness by both objective and subjective evaluations.
Тraditions and innovations in continuing education of a rural school teasher: summer pedagogical school

The article continues to acquaint with the results of a historical and pedagogical study of the theory and practice of professional and personal formation and development of a rural teacher in Russia, carried out in the discourse of his lifelong education (journal «Pedagogy of rural school», № 1, 2021). At the stage of the development of rural schools and rural teachers (XIX – early XX centuries), the prerequisites for the continuous education of a rural teacher are found in such forms of advanced training as teachers' congresses and courses for folk (zemstvo, rural) teachers. The illustration of the possibility of reviving traditions and harmonizing the ideas of educators with the development trends of modern rural school and its teacher is the Summer Pedagogical School for leaders and teachers of rural educational organizations of the Republic of Karelia. The reliance on traditions in improving the qualifications of rural teachers is manifested in the concept, content, structure and forms of implementation of the program of additional pedagogical education, carried out in this format. The article substantiates the viability and prospects of the following ideas of teachers' congresses and courses: 1. The actual content of the additional education of a rural teacher, adequate to modern trends in the development of education and at the same time verified (coordinated) with the specifics of rural school, professional activity and lifestyle of a teacher in the in the village. 2. The interdependence and interconnection of theory and practice, the practical orientation of additional pedagogical education and its focus on the translation of learning outcomes into the life of rural school, into the professional activities of a rural teacher. 3. Democratic creative atmosphere, «friendly interface» of the Summer Pedagogical School of rural teachers. 4. Integration of resources of subjects of joint educational activities – organizers and participants of the Summer Pedagogical School. The innovativeness of the summer pedagogical school manifested in the compatibility of team and personalized training, in a modular approach to the construction and implementation of the educational program, in the priority of active, interactive technologies, in the use of information technologies and etc.
Recognizing a participant behavior in a multi-party conversation

In this paper, we discuss a task to recognize a participant’s behavior in a multi-party conversation. We focus on a detection task of a participant that returns to a discussion that is already over; we call the participant “BDH (Beat a Dead Horse) participant.” The target corpus contains 17 conversations about a topic with three participants, and one of three participants is the BDH participant. To detect the BDH participant, we apply machine learning methods. We compare three machine learning methods; naive bayes, decision tree, and support vector machines. In addition, we introduce a selection model based on the task setting. The experimental result shows the effectiveness of SVMs with our selection model.
ORGANIZATION OF THE MATHEMATICAL CYCLE DISCIPLINES PROPAEDEUTIC STUDY OF NATURAL SCIENTIFIC AND ENGINEERING DIRECTIONS

Currently, the main trends in the reform of higher education naturally lead to a significant reduction of the part of classroom studies in the educational process, which is extremely negative for the study of the mathematical cycle disciplines due to their abstraction and often cumbersome presentation of the material. Thus, there is a need to increase the effectiveness of contact work and to strengthen the role of students’ independent work. One of the factors contributing to an increase in the effectiveness of contact work is independent propaedeutic consideration of the material under study. The approach to organizing extracurricular independent work in the propaedeutic study of the mathematical cycle disciplines by students of natural sciences and engineering should include the following steps: recalling the facts previously studied, presenting the natural science (engineering) applications in their historical retrospective and presenting the main ideas of this section. The latter is supposed to be performed the most clearly, with the maximum use of interdiscipline relations. To increase the effectiveness of propaedeutic independent work, it is advisable to use appropriate methodological support. As the latter (depending on the section under study), you can use interactive study guide integrated with applications written in various high-level languages, presentations, educational films and study guide in written form. Thus, the preliminary acquaintance with the new mathematical section should be during extracurricular independent work with the widespread use of interactive teaching technologies.
PREPARING FUTURE TEACHERS FOR EDUCATIONAL WORK WITH YOUNGER STUDENTS

In modern conditions related to a growing role of universal human values in society, activation of the culture-creating function of school, the role and importance of the teacher-educator, guiding the spiritual and moral formation of the child's personality, is increasing. In the study, based on the analysis of psychological and pedagogical literature, diagnostics and a modeling method, the authors determined indicators of teacher's readiness for educational work, revealed pedagogical conditions and mechanisms to build teacher's readiness for educational work at university.
Personas creation using Google Analytics

This case study investigates how a marketing persona may be created with the use of data gathered by cookies and with the use of Google Analytics. The data gathered originates from the largest IT e-learning platform VITA. The basis of our research was measurement in the Google Analytics tool and the WooCommerce plug-in within the WordPress content management system. Our case study shows how a marketing persona may be created and recommends that once such a persona is created it needs to be validated repeatedly with data on real customers before it may be used for marketing purposes.
Perfectly Regular and Perfectly Edge-Regular Intuitionistic Fuzzy Graphs

A Perfectly regular intuitionistic fuzzy graph is an intuitionistic fuzzy graph that is both regular and totally regular. In this paper we introduce and classify these types of intuitionistic fuzzy graphs and study several of their properties, including how two classes of intuitionistic fuzzy graphs structurally relate to one another and several of their spectral properties such as isospectral intuitionistic fuzzy graphs and when the energy of intuitionistic fuzzy graph is proportional to the energy of their underlying crisp graphs. These properties are studied in particular due to having at least one constant function and .
Stored Procedures, Views, and Functions

In this chapter, you are going to look into ways to leverage the built-in programmable features of SQL Server that allow for maximum performance and efficiency.
KnHiGAN: Knowledge-enhanced Hierarchical Generative Adversarial Network for Fine-grained Text-to-Image Synthesis

To generate fine-grained images with greater authenticity, in this paper, we propose a Knowledge-enhanced Hierarchical Generative Adversarial Network (KnHiGAN) for text-to-image synthesis. KnHiGAN sets up a Knowledge Enhancement Module to expand conditions for the limited text descriptions by combining with the knowledge graph, as a result, it can provide richer fine-grained details to the generative network. Moreover, a Hierarchical Generative Adversarial Network is designed to generate the foreground and background separately, and the two are integrated together to composite the final result. Experiments on CUB-200 and Oxford-102 datasets show that our KnHiGAN can not only generate the fine-grained images which are more like those that exist in the real world, but also can maintain a high degree of consistency with the original text input.
FAKTOR-FAKTOR YANG MEMPENGARUHI KASUS DBD DI SULAWESI SELATAN DENGAN MENGGUNAKAN REGRESI POISSON INVERSE GAUSSIAN

Poisson regression is used to model enumeration data such as data on the number of DHF cases. This model has the assumption that is fulfilled is the average and the variance must have the same value or it is called the equidispersion. But this assumption is not fulfilled because the data on the number of dengue cases experienced violations of this assumption. The violation is that the average value is smaller than the variance value or it is called overdispersion. This results in incorrect conclusions because the prediction standard error is underestimated. The way to prevent this is by combining the Poisson distribution and discrete or continuous distribution, this combination is called Mixed Poisson Distribution. Researchers use one of the Mixed Poisson methods, namely Inverse Gaussian Poisson Regression (PIG) because the method is used when the data is overdispersed and the parameters are known or close form on the likelihood function. Based on the results of the study, it is known that the height of the area is a factor that significantly influences DHF cases in South Sulawesi and the model form is as follows: π=exp(5,902-0,0004189 X_2)Keyword: DHF Cases; Poisson Regression; Overdispersion; Poisson Inverse Gaussian Regression;
The peculiarities of using emoji pictograms in online communities with different frequency of use of obscene lexicon

The subject of this research is the use of pictograms for expressing emotions and feelings in network communication. The object is the comments in several communities in the popular among youth social network VKontakte. The goal of this article lies in the comparison of preferred emoji used by the users to express their emotions and feelings, who are part of the communities with different frequency of use of obscene lexicon. The hypothesis is advanced that the groups with different frequency of use of obscene lexicon differ in their emotional tonality and the emoji pictograms used for expressing emotions and feelings. The research is based on the method of survey in form of the questionnaire about the peculiarities of Internet preferences and most attractive communities in social network for the respondents; as well as the method of content analysis. The questionnaire survey involved 854 persons; the data on the frequency of use of emoji was collected on the example of 14 communities in VKontakte social network. It is determined that in communities with lesser use of obscene lexicon, the rating of emoji denoting positive (hedonic and affinity) emotions is higher. In communities with more obscene lexicon, the users equally use pictograms that express negative and positive emotion; most frequent negative emotions such denote anger and frustration, or melancholy, sadness. The acquired results can be applied in development of the methods for monitoring the moods of the users of network communication.
A Lightweight Model for Falling Detection

In human activities life, accidental falls are a frequent occurrence. It can happen in children, the elderly, and even adults. Early detection of human falls is the most effective way to avoid the high risk of loss of self-control, death, or injury in humans. This means also reducing the national health system’s cost. Therefore research and development of fall detection and rescue systems are needed. Currently, the fall detection system is mainly based on wearable sensors, ambient, and vision sensors. Each method has certain advantages and limitations. The previous works usually focused on size while the speed was not often considered. Therefore, studies that aim to propose a lightweight model for Fall Detection with less complexity of memory and processing time but having reasonable accuracy are still potential. A 3-dimensional lightweight model has been proposed based on MobileNet architecture for falling detection in this paper.
Mimicry Attacks Against Behavioural-Based User Authentication for Human-Robot Interaction

Robots are often used in highly sensitive, safety-critical, or high-value applications (e.g. medical, nuclear, space, offshore, manufacturing). Where AI is not able or trusted to perform the necessary tasks, humans operators are required to train or directly control these systems. However, robots are not usually built with security as a key concern, and malicious actors need to be identified before they can cause damage or disruption through the robot’s operation. Of particular interest is ensuring whether operators of robots are who they claim to be, i.e., there is a need for identification and authentication. Traditionally, authentication is carried out through passwords or demonstrating possession of a token such as a smart card, but these are one-shot approaches and confidence in authentication wanes as time elapses. Thus, repeated authentication may be needed to provide ongoing confidence, though, in practice, such repeated actions may be highly disruptive. In this paper, we evaluate how ongoing user behaviour monitoring can be used as the basis for unobtrusive continuous user authentication, which is a form of biometric behaviour modelling. To gather data, we use a simulation in which a group of users hand-guide a robotic manipulator to perform a task (analogous to teaching by demonstration or teleoperation), with some users posing as malicious agents. We then tested our continuous authentication technique against a popular behavioural biometric attack called a ‘mimicry attack.’
Analyzing the state of regional higher education systems

Introduction. Higher education systems at the present stage of development are facing new serious challenges. On the one hand, universities function as independent units, on the other, they are part of the regional system, they attract and share the attention of the stakeholders interested in the system (applicants, students, research and teaching staff, business structures, etc.). The purpose of the study is to assess the competitiveness of regional higher education systems through the formed system of indicators, as well as to draw conclusions about the degree of uniformity in the development of these networks. Methods. To assess the state of the higher education system in Russia, the author uses an indicative method of analysis, which makes it possible to determine the degree of compliance of the indicator values achieved by now with the criteria that meet the set requirements for the development of society. Scientific novelty of the research. The novelty of the research consists in forming a set of indicators, which makes it possible to draw conclusions about the competitiveness of regional systems and the degree of their development uniformity, as well as the number of universities in the regional system and their influence on the entire system, according to their uniform development relative to each other. Results. Following the results of diagnosing the regional higher education systems, the author identifies the regions-leaders and the regions-outsiders. The diagnostic results are compared with the data of international rankings. Conclusions. The conclusion states that the region with fewer but equally developing universities (for example, the Belgorod region or the Republic of Tatarstan) have higher indicators of competitiveness. On the contrary, regional higher education systems, represented by a large number of universities, but with unevenly developing performance indicators, are characterized as less competitive, i.e. the performance indicators of the leading university are leveled within the system as a whole.