Reviewerly/exHarmony huggingface dataset:
Correction to: Improving the Quality of Training Future Engineering Personnel on the Basis of the Partnership “University-Industrial Enterprise”

In the original version of the chapter, the following belated corrections have been incorporated: The chapter author names tagged in XML is interchanged “FamilyName and GivenName”, which has now been changed to “GivenName and FamilyName”. The chapter has been updated with the change.
CEMI contribution to formation of Runet. Information projects

This review is a continuation of the text «CEMI contribution to formation of Runet. Infrastructure projects» where important infrastructure telecommunications projects by employees of the Central Economics and Mathematics Institute of the USSR Academy of Sciences (since 1992 - RAS) were described. CEMI scientists not only improved the technological infrastructure of the Runet, but also created its software and information tools. The present paper describes their unique developments: «AU!» rubricator, the most important information resource for that time, as well as Socionet information system, which has fully retained its significance to the present day. In addition, the joint work with the ISC RAS on the project «Electronic Library Scientific Heritage of Russia», which used the Institute&amp;apos;s developments, is mentioned.
Designing an Efficient Image Encryption-Then-Compression System by Using Interweaving Permutation and Blockchain-Watermarking

In this paper, we design a novel image encryption-then-compression (ETC) system by using interweaving permutation and blockchain-watermarking. Firstly, the original image is uniformly down-sampled by using interweaving permutation to produce a set of down-sampled images. Secondly, we encrypt each down-sampled image by using a same random permutation matrix individually. Since the encrypted down-sampled images preserve the correlation of the down-sampled ones, they are also highly correlated. Thridly, they are fed into the DPCM encoder to generate binary bitstream. Besides, we also use the encrypted image to generate a blockchain-watermarking to protect the integrity of the image. The experiment results show that the compression performance of the proposed method is significantly better than previous image ETC schemes. More notably, the proposed approach achieves even higher peak signal-to-noise ratio (PSNR) values than JPEG for near-lossless image compression case.
IMPROVING STUDENTS’ ABILITY IN WRITING NARRATIVE TEXT THROUGH DICTOGLOSS TECHNIQUE

This research was aimed at improving students’ ability in writing narrative text through Dictogloss Technique. The design applied in this research was classroom action research that consisted of two cycles. This research was conducted in VIII grade at SMP Muhammadiyah Sukaramai Medan academic year 2018-2019. The instruments applied to collect the data were observation, interview and test. The data were collected in the form of observation sheet, interview guideline, and writing rubric. After the data analysis, based on the quantitative data, the students’ mean score improved. In the pre-test, the students’ mean score was 8.50. In the post-test, the score increased into 15.38. The gain score of the mean scores from the pre-test to the post-test was 6.88. Based on the qualitative data, the students were able to organize their ideas and produce narrative text well. In conclusion, the result of the research showed that the Dictogloss Technique improves students’ ability in writing narrative text.
INFORMATION TECHNOLOGIES AND MATHEMATICAL MODELING IN EDUCATION OF STUDENTS OF NTU «KHPI» IN EMERGENCY CONDITIONS AND SURVIVAL SITUATIONS

The materials of the article consider the possibilities of determining and applying the components of information and computing technologies for various specialties of student education. The work presents examples of the formation of complex knowledge about the principles of construction and operation of the software for determining the possibilities of effective use of modern information and communication technologies in the professional activity of a technologist according to the types of specialization of students starting from the first year of study. When writing the article, many years of experience in teaching the disciplines «General Food Industry Technology» and «Mathematical Modeling and Optimization of Chemical Technology Objects» at the National Technical University «Kharkiv Polytechnic Institute» at the Department of Integrated Technologies, Processes and Devices were used. This experience and good knowledge of the subject determined the high quality of the material for teaching the discipline, and the issues under consideration are overlooked through the prism of one's own creative perception, which makes the material particularly valuable. Developments were carried out using modern, highly effective scientifically based technologies for the use of raw materials, examples and some features of possible learning solutions are presented, which are based on experimental data for the development of process mechanisms and their scientific justification in the form of information technology objects; detailed and analyzed: components of information systems by types of activity;
EXAMPLES OF DETERMINING THE COMPONENTS OF INFORMATION AND COMPUTATION TECHNOLOGIES FOR DIFFERENT INDUSTRIES

The possibilities of using the technology of information computer systems in varieties of examples and tasks of teaching students are considered. The work presents examples of the formation of complex knowledge about the principles of construction and operation of the software for determining the possibilities of effective use of modern information and communication technologies in the professional activity of a technologist according to the types of specialization of students starting from the first year of study. Carried out and analyzed: analysis of the components of information systems by types of activities; examples of business processes of the selected subject area, the definition of business functions and business processes, and problem statement. The requirements for the information system and the definition of functional requirements for the information system have been developed. Criteria for logical and physical modeling of databases are defined; UML modeling of the client part of the information system is developed. The requirements for the functions of the server part and the interface of the client part of the information system were developed, the possibilities of design solutions were described, the interface of the client part of the system was developed, and a database for the selected platform was created; the means of storing procedures, the functions of the server part of the information system (ІС) and the interface of the client part of the ІС, etc. were developed. The mathematical justifications of the applied algorithm are described, and the necessary conclusions are drawn.
Architectural pattern for service collaboration

The aim of this paper is to propose a modeling framework, tailored to build efficient, elastic and autonomous applications from tasks and services. It includes integrated services to develop the software products, reusing on demand in-house services with specific requirements and flexible the representational state transfer (REST) services. The idea is to decouple authorization for reduced service dependency and to provide a possibility for developing the whole application by increasing the existing application flexibility. Based on the fact that there are different web application platforms that serve to offer services to users but they are not integrated; we propose a framework with high flexibility degree, especially integrating the most used services such: e-learning, administrative, and library services, as University services are concern.
COVID-19 Disease Diagnosis Expert System with Certainty Factor Method using iOS-Based App

The drop in COVID-19 patients in Indonesia from January to February 2022 made many companies prepare policies to no longer enforce work from home. At the office, we can interact and meet other people directly and it is possible to be exposed to Covid-19 that could potentially become a new wave of COVID-19. This effect poses a serious risk to all people who come into contact with COVID-19-infected individuals or are close to them. The major course of action that may be performed when someone has COVID-19 is self-isolation and tracking anyone who is around or has a health condition associated to COVID-19. We require an iOS-based COVID-19 diagnosis expert system application to track the health status of everyone around us because we are unable to know the health status of everyone. The application uses artificial intelligence technology in the form of an expert system to check health conditions. The expert system replaces the role of the expert with the certainty factor method. This app should be used every time before entering a potentially crowded place to clarify tracking by using maps feature. In addition to COVID-19, this expert system can also diagnose diseases that have the same symptoms as Typhoid Fever and Pneumonia. The results of the expert system are in the form of diagnosing the user's health condition based on the symptoms given with a confidence level of up to 0.9999952130944 or 99.99952130944% for COVID-19, 0.9676 or 96.76% for Typhoid Fever, and 97% for Pneumonia.
Fault Alarm Communication Scheduling Architecture and Method for Power System

Today, operation and maintenance security has become a key factor for the stable development of enterprises. The flexible alarm information communication scheduling structure and intelligent fault alarm method are of great significance to improve the accuracy of alarm judgment, which can greatly realize the safe production of power enterprises and effectively ensure their steady and healthy development. Therefore, this paper proposes a modular structure. The alarm information communication scheduling architecture of the system uses unsupervised machine learning algorithms to predict fault information, analyze the correlation between faults, and at the same time achieve a high degree of coordination between modules, thereby providing an efficient and stable alarm method.
The effect of Guidance and Counselling on Students’ Discipline in Secondary Schools of Ruhinda North, Mitooma District, Uganda

Stakeholders are concerned about students’ indiscipline in secondary schools of Ruhinda North, Mitooma District, Uganda. The study assessed the effectiveness of guidance and counselling in promotion of discipline of learners in secondary schools of Ruhinda North, Mitooma District, Uganda. The study used descriptive research where both quantitative (questionnaires), and qualitative (interviews) approaches were used during. A total of 234 who were drawn from 600. The study findings revealed that major causes of students’ indiscipline in secondary schools of Ruhinda North , Mitooma District include; incompetent leadership, poor teaching by some teachers, poor feeding practices, and too much freedom in schools. The study findings showed that counsellors collect and keep up to dated students’ records, Counsellors disseminate vital information concerning academics to students, schools have well-furnished offices and rooms to carry out guidance and counselling activities and there is the proper motivation of students from the school administration during guidance and counselling sessions. The results indicated that guidance and counselling is statistically significant related to discipline of students in secondary schools of Ruhinda North, Mitooma District (r=0.159, P = 0.024 &lt; 0.05). It was concluded the major causes of students’ indiscipline in secondary schools in Ruhinda North, Mitooma District were; poor leadership, poor teaching methods, absenteeism of teachers, and poor feeding practices. It was also concluded that there was effective guidance and counselling. Guidance and counselling have a positive influence on students’ discipline. Therefore, effective guidance and counselling promote students’ discipline. It was recommended that Ministry of Education should put more efforts towards ensuring acceptable moral training among students.
Popular Bullying Pattern among Teenage Students: A Study of some School Students in Kathmandu

Background: Bullying in itself has several impacts and entire world had been seeking solution for it. Bullying starts from the primary state of growth, which begins from school. Bullying has its various type and impact. Aggression is one of the prominent factor for it. Objectives: 1. To study the nature of bullying in some schools of Kathmandu. 2. To compare bullying pattern among community and private schools. 3. To find out types of bully among the students. 4. To find out aggressive and behavior of students involved in bullying Method: Descriptive with purposive sampling method was used and SPSS was used for data analysis. Discussion: There were 200 respondents where 100 were male and 100 were females. Mean score of male bully (38.08) and female (30.70). There were 83 respondents from community school and 117 from private school. Numbers of boys are higher in bullying, as bullies, victims, and bully-victims. Bullying students have higher aggression. Bullying occurs both in community and private school but it is more in community school and so was aggression. Verbal bullying was higher in teenagers than social and physical bullying. There was significant positive correlation between bully and victim, aggression and bully and bully and behavior. Conclusion: Verbal bullying was higher than that of physical and social pattern of bullying. If gender was taken in count, male bully more than female. Comparing schools, community school has higher bullying than private schools.
Integrated geophysical and geochemical study for investigating the hydrocarbon potentiality of West Dakhla area, Western Desert, Egypt, as an extension of Libyan Kufra basin

The present study represents an integrated study using the potential field maps and well geochemical data of the West Dakhla area in the western central area of the Western Desert area, Egypt. The potential field data are represented by the airborne gravity and total magnetic maps acquired by the Nuclear Material Authority (NMA), Egypt, on behalf of Dana Petroleum Company. The geochemical data consist of geochemical analysis in Ammonite-1 well that were done for source rock evaluation. Different processing techniques on the gravity and magnetic maps are carried out for separating the regional and residual separation and filtering. Modelling and Euler deconvolution tools are utilized for proposing the depth to basement and constructing basement-depth maps to infer the basin configuration of the study area. Before acquiring the present geophysical data, the study area wasn't subjected to any exploration investigations. Therefore, these data and this study are considered as the first efforts carried out and submitted for publication in this area. In addition, a comparison of the present basin is done with matched basins in southern Libya, where this basin is expected to have similar geological features. The study indicates that the studied basin may be a part of a wider basin extending in Egypt and Libya. This basin is expected to have the thickness and features that are favourable for hydrocarbon habitat. The geochemical analysis shows TOC values ranging from poor to very good source rock potentiality.
Comparative Analysis of First and Second Order Methods for Optimization in Neural Networks

Artificial Neural Networks are fine tuned to yield the best performance through an iterative process where the values of their parameters are altered. Optimization is the preferred method to determine the parameters that yield the minima of the loss function, an evaluation metric for ANN’s. However, the process of finding an optimal model which has minimum loss faces several obstacles, the most notable being the efficiency and rate of convergence to the minima of the loss function. Such optimization efficiency is imperative to reduce the use of computational resources and time when training Neural Network models. This paper reviews and compares the intuition and effectiveness of existing optimization algorithms such as Gradient Descent, Gradient Descent with Momentum, RMSProp and Adam that implement first order derivatives, and Newton’s Method that utilizes second order derivatives for convergence. It also explores the possibility to combine and leverage first and second order optimization techniques for improved performance when training Artificial Neural Networks.
Mach-Zehnder Interferometer for Topological Edge States Based on a Designer Domain Wall

We experimentally demonstrate a tunable single-waveguide interferometer based on interfaces between photonic topological insulators. Tunability is achieved by engineering the domain wall without altering the bulk. Topological protection enables compactness and efficiency.
A browser based system for remote evaluation of subjective quality of videos

The evaluation of the quality of videos is posing a significant problem in research on video processing, including compression.Different algorithms and their modifications aim to improve the quality of the video, while keeping the necessary bitrate as low as possible, and every time, the performance of the method must be evaluated.The bitrate can be measured readily, while for quality there are different metrics and, therefore -different results.The ultimate verdict always has to be the subjective opinion about the quality that is expressed by the viewers.For now, the only reliable way to measure the quality of the video is to perform a subjective test with a group of viewers.Subjective tests are difficult to perform -not only one has to gather all viewers in one place, but also the evaluation schemes may be difficult to follow.In the paper we present an implementation of a system that greatly simplifies the process of performing the subjective quality assessment of videos.We discuss strengths and weaknesses of the system when compared to the commonly used procedures.Finally, we also provide the results of a quality assessment for the HEVC video encoder.Presented data proves that the idea of remote quality evaluation together with the usage of the two-level grade is a valid one and provides reliable results.
FeatSet+: Visual Features Extracted from Public Image Datasets

Real-world applications generate large amounts of images every day. With the generalized use of social media, users frequently share images acquired by smartphones. Also, hospitals, clinics, exhibits, factories, and other facilities generate images with potential use for many applications. Processing the generated images usually requires feature extraction, which can be time-consuming and laborious. In this paper, we present FeatSet+, a compilation of color, texture and shape visual features extracted from 17 open image datasets reported in the literature. FeatSet+ provides a collection of 11 distinct visual features, extracted by well-known Feature Extraction Methods (FEMs) such as LBP, Haralick, and Color Layout. We organized the available features in a standard collection, including the metadata and labels, when available. Eleven of the datasets also contain classes, which aid the evaluation of supervised methods such as classifiers and clustering tasks. FeatSet+ is available for download in a public repository as sql scripts and csv files. Additionally, FeatSet+ provides a description of the domain of each dataset, including the reference to the original work and link. We show the potential applicability of FeatSet+ in four computational tasks: multi-attribute analysis and retrieval, visual analysis using Multidimensional Scaling (MDS) and Principal Components Analysis (PCA), global feature classification, and dimensionality reduction. FeatSet+ can be employed to evaluate supervised and non-supervised learning tasks, also widely supporting Content-Based Image Retrieval (CBIR) applications and complex data indexing using Metric Access Methods (MAMs).
Data-Driven Forecasting of Nonlinear System with Herding via Multi-Dimensional Taylor Network

This work focuses on developing a forecasting model for the nonlinear system with herding. Firstly, for clear presentation of the mechanism of herding behavior, a concept called intermittent positive feedback is defined. The mathematical expression of intermittent positive feedback is formulated in terms of dead-zone functions with the beginning and ending thresholds in the positive and negative directions. Then a dynamic surrogate based on the intermittent positive feedback multi-dimensional Taylor network is established, and a method for identifying its parameters is proposed. Multi-dimensional Taylor network module simulates the long-term trends of time series. Subsequently, an optimization model based on the alternating iteration of the parameters is developed to enhance the forecast accuracy of the intermittent positive feedback part. Simulation results demonstrate that the forecasting effect of the proposed modeling method is superior to that of conventional non-mechanism data-based surrogates for herding behavior.
Dynamic Analysis of Musical Triangle

The paper deals with dynamic analysis of a two types of musical triangles, one made from stainless steel and other from alloy. The experimental method applied in this study consisted in exciting the structure with the impact hammer and recording the acoustic signals with the help of the microphone located near the sample, the acquired signals being subsequently processed in the program developed in Matlab. The time and frequency analysis showed for each drag, the frequency spectrum, the dominant frequency and the damping. Then, finite element analysis and damping simulation of the musical triangles was done with Simcenter 3D software, based on real properties of materials and experimental signals. The results between the experimental and the numerical analysis showed a good correlation between the two methods. Thus, it was observed that at the frequency of 878 Hz, the triangle vibrates in a torsional mode, followed by longitudinal vibrations (at the frequency of 1053 Hz), and at the dominant frequency, of 1877 Hz, the triangle vibrates in a transverse mode, in the plane or. The higher modes corresponding to the frequencies 3089 Hz and 3454 Hz are torsion modes.
Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data.

The mixture cure model allows failure probability to be estimated separately from failure timing in settings wherein failure never occurs in a subset of the population. In this paper, we draw on insights from representation learning and causal inference to develop a neural network based mixture cure model that is free of distributional assumptions, yielding improved prediction of failure timing, yet still effectively disentangles information about failure timing from information about failure probability. Our approach also mitigates effects of selection biases in the observation of failure and censoring times on estimation of the failure density and censoring density, respectively. Results suggest this approach could be applied to distinguish factors predicting failure occurrence versus timing and mitigate biases in real-world observational datasets.