Reviewerly/exHarmony huggingface dataset:
Human-computer Interaction in Connection with Conducting Online Classes: The Case of a Technological University in Russia during the COVID-19 Pandemic

Human-computer interaction necessarily takes place in education using information technology. In the situation of the COVID-19 pandemic, with classes to be conducted partly or totally online, the use of computers by both teachers and students is inevitable. The sudden shift from offline to online learning has made both opportunities and challenges of dealing with computer technology more evident. The opportunities of online education are numerous, including remote access and increased flexibility available for the learning process. However, there are certain challenges of human-computer interaction that make the use of these opportunities less efficient, if not impossible. In fact, the real situation of conducting online classes in a given time and place can be rather different from the suggested ideal one – and is to certain extent unpredictable (thus being the situation of uncertainty), dealing with technical, bureaucratic, behavioural and other obstacles. The particular case under analysis is that of Kuban State Technological University in the Russian city of Krasnodar. Based on the observations conducted at the university, including those provided by means of pedagogical experiment, the description of the behaviour demonstrated by the human participants of the online learning process (including students and teachers, as well as administrative and technical staff) towards computer technology is presented in its development since the introduction of the changes caused by the COVID-19 pandemic. Relevant suggestions are proposed in this connection.
High-fidelity storage and on-demand retrieval of quantum states via a microwave waveguide

On-demand quantum memory is an important step towards practical applications in various quantum information tasks such as long-distance entanglement distribution, quantum computation, and quantum networks. In this work, based on stimulated Raman adiabatic passage (STIRAP) protocol, we introduce a controllable delay between the reading pulse and writing pulse so that the quantum state can be stored in the superconducting waveguide and finally retrieved on demand with high fidelity. Through systematic numerical simulations, we find that if the duration of the writing pulse is set to be in a certain range, the readout unit is capable of retrieving the quantum state stored in the waveguide with high fidelity at any moment after a critical time. Moreover, we also investigate the robustness of our protocol, and find that the fidelity is robust against both the average number of thermal photons in the waveguide and the duration of the reading pulse. The numerical results also show that the pulse area in our protocol is only about one third of that in the original STIRAP protocol. Our protocol provides a practical way to combine the advantages of both on-demand quantum memory and the STIRAP protocol.
An Analysis of Strategies for Improving Young University Teachers’ Work Well-being: Based on the Mediating Effect of Psychological Empowerment

Young teachers in universities are the backbone to promote the development of China's education.It is of great significance to explore the formation mechanism of their work well-being.This paper tries to build the model of its internal formation mechanism from the psychological level, and explores the internal forces and external factors that affect the work well-being of young university teachers.In the process of social support and school management activities affecting the work well-being of young university teachers, personality trait plays a moderating effect, and psychological empowerment plays a mediating effect.Then, drawing on the excellent cultivating practices of young teachers in American colleges and universities, this paper establishes a three-level linkage mechanism of work wellbeing promotion strategy from the perspective of psychological empowerment, which needs joint participation of young teachers themselves, universities and society. Keywords：young teachers in universities; mediating effect; psychological empowerment; work well-being
The image of the Great Russian Wall in the works of V. Sorokin

s works often feature images closely related to Chinese culture.One of such images, the Great Russian Wall, acts as a significant element of the meta-plot, which carries an important meaning.This article analyses the image of the Great Russian Wall in V. Sorokin's futurological works "Day of the Oprichnik" and "Kremlin Made of Sugar" primarily through the study of the Great Wall of China and its connotations in Western culture.The article also focuses on the intertextual horizon of Sorokin's image of the Wall: the parallels between the text by Sorokin and the texts by F. Kafka and H. Borges.The article uses comparative and cultural-historical methods to reveal the author's artistic intent.In conclusion, the image of the Great Russian Wall in Sorokin's future world can be perceived as a parody of the Great Wall of China.Sorokin's Wall, on the one hand, symbolizes the closed and stagnant way of life in ancient China with its cruel feudal regime.On the other hand, it exposes the same reality of future Russia.It reflects serious socio-political problems of Russian reality, in particular its "isolation" and "totalitarianism".
Modeling and Planning Process Analysis of Search Task Planning Problems Inside Buildings

In the case of disaster relief, street fighting, etc., the search inside the building is a very important part of the mission scenario. To ensure the safety of personnel, an unmanned system can be used instead of personnel entering the building to search. If the unmanned system can autonomously plan and execute tasks, it will not require personnel to control the unmanned system, thereby preventing personnel from staying in dangerous areas for a long time. The current mission planning process of unmanned systems is usually planned based on known global information, but the internal information and situation of the building are usually not available in advance before the mission starts, and the mission situation is relatively uncertain. Aiming at the uncertainty of the search task inside the building, this paper analyzes the components and key points of the task and designs a method for processing the perception data inside the building and the task planning process for the uncertainty of the task.
Peer Review Declaration

Abstract All papers have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: Google Form • Number of submissions received: 140 articles • Number of submissions sent for review: 121 manuscripts • Number of submissions accepted: 59 papers • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 42.14% • Average number of reviews per paper: 2 reviews • Total number of reviewers involved: 25 experts • Any additional info on review process: Each paper took 2-4 weeks for revisions after review. • Contact person for queries: Name: Komariah, PhD. Affiliation: Sebelas Maret University, Indonesia Email: komariah@staff.uns.ac.id
Improved filtering H∞ finite frequency of Takagi-Sugeno fuzzy systems

The work treats the filter H∞ finite frequency (FF) in Takagi-Sugeno (T-S) two dimensional (2-D) systems described by Fornasini-Marchesini local state-space (FM LSS)models. The goal of this work is to find an FF H∞ T-S fuzzy filter model design in such a way that the error system is stable and has a reduced FF H∞ performance over FF area swith noise is established as aprerequisite. Via the use of the generalized Kalman Yakubovich Popov (gKYP) lemma, Lyapunov functions approach, Finsler’s lemma, and parameterize slack matrices, new design conditions guaranteeing the FF H∞ T-S fuzzy filter method of FM LSS models are developed by solving linear matrix inequalities (LMIs). At last, the simulation results are provided to show the effectiveness and the validity of the proposed FF T-S fuzzy of FM LSS models strategy by a practical application has been made.
Deep neural network ensembles for detecting self-admitted technical debt

Effectively identifying self-admitted technical debt (SATD) from project source code comments helps developers quickly find and repay these debts, thereby reducing its negative impact. Previous studies used techniques based on patterns, text mining, natural language processing, and neural networks to detect SATD. Compared with these above, Convolutional Neural Networks (CNN) have the strong feature extraction ability. Deep network ensembles are demonstrated great potential for the task of sentences classification. In order to boost the performance of CNN-based SATD detecting, we propose a deep neural network ensemble contribute to ensemble learning in a simple yet effective way. Specifically, CNN, CNN-LSTM (convolutional neural network and long short-term memory), and DPCNN (Deep Pyramid Convolutional Neural Networks) are used as individual classifiers to diversify the deep network ensembles. In order to improve the explainability, we introduce attention to measure the contribution of feature words to SATD classification. 62,285 source code comments from 10 projects were used in our experiments. The results show that our approach can effectively reduce misjudgment and detect more SATD, especially for cross-project, so as to greatly improve the detection accuracy.
Study of the level of need development for self-education in future FSIN students

The concept of lifelong education in modern Russia is focused on significant expansion of the entire educational space, where the issues of self-education and self-development of the individual are paramount. The problem of developing the skills of student’s self-education in departmental organizations of higher education for the formation of a stable highly professional staff of the penal system is especially urgent, since self-education allows them to ensure the conscious development of professionally important personality traits. The aim of the study was to study the level of need for self-education among future employees in a departmental university. The tasks of the experimental work is diagnostics of the process of self-education of students and the study of ways and means of organizing the process of self-education in a departmental university. The study was based on the Federal State Educational Institution of Higher Education “Vologda Institute of Law and Economics of the Federal Penitentiary Service of Russia”. The study involved 10, 3-year students of the Faculty of Psychology; was used the questionnaire “The need for self-education” (by S. V. Yudakova), consisting of three parts: 1) it allows you to identify the ability of students to develop; 2) is aimed at identifying factors that stimulate and hinder the self-education of the subjects; 3) allows to identify the degree of proficiency in the skills of independent work by future specialists. The results of the survey revealed the following: 20 % of students scored more than 55 points and have a high desire and motivation for self-education. Most of the subjects – 50 % – scored from 36 to 54 points and showed an average level of desire for self-education. Three respondents – 30 % of students have a low level of development of the need for self-education. Thus, the results obtained made it possible to reveal that future employees of the penitentiary system have, predominantly, an average and low level of development of the need for self-education. Consequently, it is expedient to work on organizing the process of developing the need for self-development and self-education skills of students in a departmental educational organization of higher education.
A Thousand Cuts: Cumulative Lead Exposure Reduces Academic Achievement

We study how ambient lead exposure impacts learning in elementary school by leveraging a natural experiment where a large national automotive racing organization switched from leaded to unleaded fuel. We ﬁnd increased levels and duration of exposure to lead negatively aﬀect academic performance, shift the entire academic performance distribution, and negatively impact both younger and older children. The average treated student in our setting has an expected income reduction of $5,200 in present value terms. Avoiding said treatment has an eﬀect size similar to improving teacher value added by one-fourth of a standard deviation, reducing class size by 5 students, or increasing school spending per pupil by $750. The marginal impacts of lead are larger in impoverished, non-white counties, and among students with greater duration of exposure, even after controlling for the total quantity of exposure.
National Security vs Privacy in India

Privacy and national security have assumed a limelight position in contemporary times. While privacy is one of the fundamental human rights that serve as a pivot in the preservation of human dignity, national security is the defense and protection of the citizenry of a country. But the growing contest of strength between citizen privacy and national security has once again renewed the concerns of where a fine line of balance should be drawn between them. The advancement in the technological world has made it viable for the Government to gather data and store hundreds of data points on every individual and this has put the individual’s privacy lower and threaten. This article analyses the concept of an individual’s privacy in India and the appraise link with national security. This article also discusses the various facets of privacy and national security, and it also takes the views of the citizens of the country with regards to the altercation between national security and privacy.
Comparison Experimental Analysis of Different Cryptocurrencies

Cryptocurrencies have proliferated in recent years, and all of them have more or less optimized the shortcomings of bitcoin. This paper selected four representative cryptocurrencies including LiteCoin, ETH, Zcash, and Ripple, and made a comprehensive comparison of their advantages and disadvantages, attacks and defenses and other aspects, based on reading a significant volume of relevant papers. The comprehensive comparison can more easily highlight the advantages of cryptocurrencies on the market so far, and more importantly, more vulnerabilities will be discovered and more defense methods will be interpreted, which must have certain guiding significance for the future vulnerability repair and defense against attacks of cryptocurrencies to a large extent. This will greatly improve the security of future cryptocurrencies. By analyzing their generation mode, their working mechanism, their security capabilities and their algorithms, the strengths and weaknesses of the four popular cryptocurrencies mentioned above can be summed up very clearly. On the basis of these pros and cons, it will be very easy to delineate where each cryptocurrency is suitable. In addition, potential vulnerabilities could be found by studying the consensus algorithm of each cryptocurrency. What we did was looking for possible attacks based on those vulnerabilities, and trying to find the appropriate defense methods. We have done a very thorough study of the work mentioned above, and have finally achieved a very detailed comparison of the differences between several cryptocurrencies. Finally, we came to the conclusion that each cryptocurrency has different styles in terms of advantages and features, and is relatively easy to spot in terms of weaknesses, making it vulnerable to some large-scale attacks. By comparing these cryptocurrencies in all aspects, a more secure and more powerful cryptocurrency may be created soon.
Formation of Educational Ecosystem as a Key Priority of the Russian Education Development Strategy

The article analyzes the educational ecosystem in the context of the strategic development of education.The purpose of the article is to study the experience of implementing the ecosystem approach while organizing the educational process in accordance with the challenges of the emerging information society.The article presents the basic features of the educational ecosystem and briefly describes the major changes in educational activities: the integrative nature of the content of teaching methods and tools; adaptability, co-evolution of the environment and its subjects; the theory of connectivism dwelling upon learning in the digital age.Referring to the research by V.L. Kvint and O.E.Permyakov, the authors conclude that the ecosystem approach is an essential factor for the strategic development of education.In their research, N.V. Dyorina, L.I. Savva, N.I.Rabina identified the peculiarities of forming the university innovative ecosystems.Particular attention is paid to the ideas of S. Panda on methods for studying the digital footprint of students and the use of cluster analysis of the obtained data for taking the managerial decisions.A paradigm approach, the theory of strategizing and learning models in the context of digital transformation were used during the analysis of the ecosystem approach to the educational system.The analysis of various research positions led to the conclusion that the transformation of the educational environment of a university into an eco-educational one is a comprehensive problem; its solution is in the development of an appropriate theory of education and of a corresponding eco-educational model.The article has considerable practical value because it contains recommendations and suggests approaches that can be taken into account when modernizing educational activities in higher education institutions: a step-by-step transition to the implementation of changes is necessary through the strategic planning of the development of structures and processes in the educational ecosystem of the university with the help of digital innovative technologies used for education and educational management.
IMPROVING STUDENTS’ READING COMPREHENSION THROUGH TOP-DOWN STRATEGY

The objective of this research was to find out the improvement of the students’ reading comprehension by using Top-Down strategy in learning reading comprehension at SMA Negeri 1 Wajo. This research employed Pre-experimental method. The population of this research was eight classes of the Tenth grade students at SMA Negeri 1 Wajo in academic year 2019/2020 with the total population were 242 students. The researcher took random sampling and chosen X MIA 1. The data of the research were collected by using the instrument, namely reading test. The result of data analysis showed that there was significant difference between the students’ score after they were taught by top-down strategy and before they were taught by using top-down strategy. It was proved by the mean score of post-test was higher than the mean score of pre-test (67.2042.56). Furthermore, the result of the p- value (0.00) was lower than α (0.000.05) which meant that H1 was accepted.
Multi-objective Optimization and Multi-attribute Decision Making Method of UAV Swarm Based on Elastic Network

As the situation of unmanned combat changes rapidly, it is necessary to carry out dynamic task planning. How to conduct dynamic task scheduling for distributed intelligent unmanned combat systems has become a hot and difficult problem. In order to solve this problem, this paper proposes a method of fusing multi-attribute decisions under the framework of multi-objective optimization by using the characteristics of elastic networks, which can generate scheduling policies quickly when the execution sequence of input tasks is finite. Secondly, a multi-attribute decision-making method combining filter and Pearce correlation coefficient is set up to select the optimal compromise scheme on the Pareto surface. Finally, an experimental case of UAV group rescue is designed to obtain the Pareto front of the problem, and the optimal compromise scheme is selected on the Pareto surface to verify the effectiveness of the proposed method.
Feasibility of bootstrap aggregating to enhance extreme learning machine for reference evapotranspiration estimation

Estimation of evapotranspiration (ET) is a challenging, yet important task as the ET value can be used to predict many other natural phenomena. In this work, the reference evapotranspiration (ET 0 ) was estimated using the extreme learning machine (ELM) at two meteorological stations located in the northern region of the Straits of Malacca. Optimum designs of the ELM were first determined and it was found that the different number of hidden neurons and activation functions were favourable to various input combinations. In order to enhance the performance of the ELM, the bootstrap aggregating algorithm was integrated to resample the original dataset. However, the performance of bagged-ELM was found to be poorer than the base ELM. This could be attributed to the high stability of the base ELM model whereby the training size already overwhelmed the dimensionality of the problem itself. The bootstrap aggregation data fusion technique produced a “backfire” effect that degraded the accuracy and generalisability of the base ELM model.
Pemodelan dan Pemetaan Jumlah Penderita Kusta di Jawa Barat dengan Regresi Binomial Negatif dan Flexibly Shaped Spatial Scan Statistic

Abstract. Flexibly Shaped Spatial Scan Statistics is a statistical scan method used to detect hotspots in a location in the form of points or aggregates. This method will be more flexible to the shape of the resulting hotspot. The hotspot detection process with this method requires forecast data for each region. The forecast data was obtained with the best modeling between poisson regression and negative binomial regression. In the Poisson regression method there are assumptions that must be met, namely the mean and variance of the response variables must be the same. In fact, in the count data this assumption is often not fulfilled because of overdispersion problems. The negative binomial distribution is an unusual statistical model, this distribution can adjust for the overdispersion problem in the poisson distribution. Therefore, the overdispersion problem in poisson regression modeling can be overcome by negative binomial regression. This study uses secondary data on the number of leprosy sufferers in West Java in 2019. Leprosy is a disease caused by the bacterium Mycobacterium leprae. According to the 2019 Health Service Report, West Java is the second province with the highest number of new cases of leprosy in Indonesia. The results of this study indicate that there were 2 leprosy hotspots in West Java in 2019.&#x0D; Abstrak. Flexibly Shaped Spatial Scan Statistic merupakan salah satu metode scan statistic yang digunakan untuk mendeteksi wilayah kantong (hotspot) di sebuah lokasi yang berupa titik atau agregat. Metode ini akan lebih fleksibel terhadap bentuk hotspot yang dihasilkan. Proses pendeteksian hotspot dengan metode ini membutuhkan data ramalan untuk setiap wilayah. Data ramalan tersebut diperoleh dengan pemodelan terbaik diantara regresi poisson dan regresi binomial negatif. Dalam metode regresi poisson terdapat asumsi yang harus dipenuhi yaitu nilai mean dan variance variabel respon harus sama. Kenyataanya pada data count asumsi ini sering tidak terpenuhi karena terjadi masalah overdispersi. Distribusi binomial negatif merupakan model statistik yang tidak biasa, distribusi ini dapat menyesuaikan adanya masalah overdispersi pada distribusi poisson.Oleh karena itu, masalah overdispersi dalam pemodelan regresi poisson dapat diatasi dengan regresi binomial negatif. Pada penelitian ini digunakan data sekunder Jumlah Penderita Kusta di Jawa Barat Tahun 2019. Kusta merupakan penyakit yang disebabkan oleh bakteri Mycobacterium leprae. Menurut Laporan Dinas Kesehatan tahun 2019, Jawa Barat merupakan provinsi kedua dengan jumlah kasus baru kusta terbanyak di Indonesia. Hasil pada penelitian ini menunjukkan adanya 2 hotspot kusta di Jawa Barat pada tahun 2019.