Reviewerly/exHarmony huggingface dataset:
Chaka, P. (2013). An Implimentation of an online based registration system in tertiary institutions in Zimbabwe. International Journal of Engineering Research &amp; Technology (IJERT), 2(10). Curelaru, M.; Curelaru, V.; Cristea, M. (2022). Students’ Perceptions of Online Learning during COVID-19 Pandemic: A Qualitative Approach. Sustainability, 14, 8138. https://doi.org/10.3390/su14138138 Dung, D.T.H. (2020). The Advantages and Disadvantages of Virtual Learning. IOSR Journal of Research Method …

Web-based services offer users convenient access to and the ability to manipulate information that is of concern to such services. Not only does online registration address the manageability issue of a growing student population, but it also ensures greater constancy and reusability of information. These advantages in turn lead to better productivity and hence better quality of the overall registration system. Furthermore, online system can be used not only for registration, but also for making payments, accessing school record, and updating information. Using a descriptive sequential qualitative-quantitative method, this paper investigated the perceptions and experiences of some freshmen concerning online registration system as opposed to traditional paper-based central registration system. Data were collected from 28 participants at a medium size public university in Niger via online questionnaires and online group discussions. The study found that participants are in general very receptive to online registration system and that Computer Skills positively correlated with Perceptions. These results have implications for Niger’s public institutions of higher education wishing to innovate or revolutionize their registration system to better manage the growing number of incoming freshmen each year.
Sensory Vocabulary Distribution in the Local Armenian Texts of the XIX-XXI Centuries

The aim of the research is to determine the nature of distribution of sensory perception vocabulary in local poetic texts about Armenia in the Russian literature of the three periods: the XIX century, the early XX century, the early XXI century. Local texts make it possible not only to describe the history of the country, its cultural, moral and ethical values, but they also create an opportunity to study the peculiarities of their perception by the author of a literary work. The paper investigates the specifics of Armenia’s perception by analysing sensory vocabulary in poems. Scientific novelty of the paper lies in using a quantitative approach involving a number of statistical procedures (coefficient of variation, Busemann coef cient, chi-square criterion, approximation of frequency distributions using an exponential function), which allows the researcher to shed light on the linguistic mechanisms of creating an artistic image of Armenia. As a result of the analysis, patterns and trends reflecting the use of sensory vocabulary in the description of the artistic world of local texts about Armenia have been identified, the ratio of decorative and dynamic descriptions has been determined. It has been found that the dynamics of the description changed to static during the transition from the first to the second period. In the third period, the paradigm of perception modes expanded and the perception types themselves are used with frequencies that correspond to an exponential distribution.
Stitched image based on a real-time video conversion technique

Mosaic video reconstruction is a technique of assembling a video cut into frames to provide a panoramic view of a captured scene. The resulting image of this technique provides a compact representation of the entire video. In this paper we propose a technique for creating image mosaics-based video scene. This technique will be used for real-time compression of videos into mosaic images.
Method of Halved Interaction Elements with Regularity Arrangement that achieves Independent Double Systems for Scalable Fully Coupled Annealing Processing

In recent years, annealing processors have been developed as solutions to large-scale combinatorial optimization problems. In this paper, we propose a new method that has a high affinity with a scalable fully coupled annealing processor and halves the interaction in which there are squares of spins with sequence regularity. In addition, we applied the proposed interaction reduction plan this time to the 384-spin fully-coupled Ising machine using 16 chips conducted in the previous research [1], and succeeded in implementing two independent 384-spin fully-coupled Ising machines with 16 chips. The usefulness of the reduction plan is shown.
Advanced Univariate and Statistical Multivariate Modeling

Chapter 2 explored various recipes for implementing univariate statistical modeling in Python. A few more advanced techniques are explored in this chapter, as well as modeling another type of temporal data—the multivariate time series. Multivariate time series contains additional time-dependent features that impact your target, apart from the date and time. The various statistical methods and recipes for implementing multivariate modeling in Python are explored.
Generative Edge Intelligence for Securing IoT-assisted Smart Grid against Cyber-Threats

The critical dependence of industrial smart grid systems on cutting-edge Internet of Things (IoT) technologies has made these systems more susceptible to a diverse array of assaults. This consequently puts at risk the integrity of energy data as well as the safety of energy management activities that depend on those data. This study offers a generative federated learning framework for semi-supervised threat detection in an IoT-assisted smart grid system. We refer to this framework as FSEI-Net. A unique semi-supervised edge intelligence network (SEI-Net) is presented in the FSEI-Net to enable semi-supervised training using labeled and unlabeled data in the edge tier. The design of SEI-Net is based on with bidirectional generative convolutional network that can intelligently capture the patterns of threat data from partially labeled smart grid data. We present federated training to enable remote edge servers to work together on training a semi-supervised detector without disclosing their own private local data. This is accomplished through cooperative training. To facilitate communication between cloud and edge layers that is both secure and respectful of users' privacy, a reputation-based block chain is introduced in the FSEI-Net. The outcomes from the practical applications demonstrate that the effectiveness of the proposed FSEI-Net over the most recent cutting-edge detection approaches are valid
Application of Optimization Techniques in Cloud Resource Management

For over one-decade computing with communication that uses technology innovation has played a prominent role. The computing paradigm includes utility-based computing. The utility-based computing paradigm includes grid computing and cloud computing, which follow the features of daily life by computing, for example, electricity, water, and gas supplies. The computing paradigms have wide applications including in education, health, and agricultural settings. Resource management covers the storage, computing, and network resource management requirement for resource availability at the user’s end globally. The optimization provides optimal assignment of tasks on a virtual machine (VM). This chapter provides a detailed study of how an optimization framework helps in cloud resource management. Cloud resource management focuses on the management of infrastructure, platform, and application delivery models in a scalable cloud scenario. Apart from scalability, the service level agreement (SLA) will be the major concern of cloud service providers and cloud computing consumer satisfaction. This chapter focuses on a systematic review of the existing optimization techniques and an evaluation of the≥1 optimization methodology, which is known as pigeon-inspired optimization (PIO). The PIO approach provides an optimal performance that uses the global optimal fitness function as an optimization criterion. The chapter sections cover a comprehensive review of the optimization techniques and applications of optimization-based methodologies in cloud resource management and the application of optimization techniques in real-life applications. The chapter also covers a presented framework for real-time problem-solving in the interdisciplinary domain for the optimal assignment of cloud resources at the infrastructure and platform levels.
Route Book As a Tool for the Formation of Regulatory Universal Educational Activities of Younger Schoolchildren

The article discusses the problem of the formation of universal regulatory actions that ensure the development of such a personality trait as independence. The period of primary school age is the most sensitive and, accordingly, optimal for their formation. As one of the pedagogical tools for organizing educational activities that contribute to the successful development of universal regulatory actions among younger schoolchildren, the authors proposed the use of a route book, which allows students to more clearly formulate their educational goals and objectives; correct actions in the process of mastering the subject content; think systematically. The data of preliminary and ascertaining monitoring are given to assess the level of development of universal regulatory educational actions among schoolchildren of the second grade; the method of using the route book is described; Based on the analysis of the achievements of second-graders, conclusions are drawn about its effectiveness.
VisionX—A Virtual Assistant for the Visually Impaired Using Deep Learning Models

We are living in world where there are many difficulties faced by various people. But, visual impairment is one of the biggest challenges faced by people. We can see visually impaired people using sticks or any other means for doing their tasks, but they can’t find or identify any object by themselves. In today’s world, there are many advancements in technology like artificial intelligence, machine learning where we can train machines for identifying different objects and different text present in a scene. The objective of this work is to develop a system using Esp32 Camera module to help the visually impaired to identify objects. The proposed system takes images from Esp32 and identifies different objects and text present in the scene and gives the output in the form of speech. The system has a voice assistant with commands for performing object detection, text detection and camera usage. This research helps visually impaired people in various aspects like object detection and text detection using voice commands and they can listen to the description of different objects detected by the system. The results show training accuracy of 97% and test accuracy of 88% using deep learning CNN models.
Collapse Detection Using Fusion of Sensor

As the number of elderly and patients in the world has increased, these people are common in the scenarios of falling inside or outside house. Therefore, it is more important to pay attention to the protection of these people. Therefore, detecting fall people is crucial. Throughout the collection of the data in the website, the fall and non-fall in outside and inside home automatically detect the falling people. From single heart rate sensor, we can detect the fall with low accuracy and good time management. For better results, combining both heart rate sensor and accelerometer with the gyroscope sensor is preferred over a single component even in accuracy and time management. In this paper, fall detection by the fusion of heartbeat sensor and accelerometer with gyroscope sensor is discussed.
Upshot and Disparity of AI Allied Approaches Over Customary Techniques of Assessment on Chess—An Observation

Chess is considered to be one of the toughest brain puzzle because of its complex strategies, huge set of combinations, numerous tactics, multifaceted evaluation methods, and substantial memory. In the field of computer science, chess is the longest studied logical game, which opened the door to many aspects of computation, evaluation methods, and many more. In this study, two chess engines with their variants are compared which are built with traditional and modern approaches of evaluation techniques, involving various set of algorithms thereby resulting in performance variances. The parameters which are considered for the comparative study are searching depth, time complexity, accuracy, and overall performance of the chess engines under various platforms of execution such as speed and memory capacity of the computer. Overall, in the current work, observations have been made on the effect of introduction of modern evaluation methods versus traditional evaluation methods through computer chess engines as a case study.
MOTIVATIONAL CHALLENGES OF ATTRACTING YOUNG PEOPLE TO THE IT-SPHERE IN RUSSIA

The article summarizes the results of a study conducted to assess the expectations of graduates of IT-areas of higher educational institutions. The difficulties of staffing the process of formation of the digital economy as a chosen priority in the development of the Russian Federation are highlighted. A list of factors that are decisive when choosing a future job by potential applicants has been formed.
Walking as a way to fight fatigue: A philosophical aspect

Introduction. The article deals with the problem of walking in the digital age context. It is one of the forms of social activity that lets us keep our mind and body on toes – walking, and it is not high on the public agenda anymore. Theoretical analysis. The analysis of the works of P. Handke, B. Vigarello etc. helps to suggest that every day individual completes a series of tasks being distracted by social media and doing some other minor things. A device cannot be considered either a good or a bad thing; it depends on the function that an owner attaches to the smartphone. Although it rather makes an individual stop from feeling lonely. M. Kundera or L. Tolstoy assumed that solitude is an essential part of life in which they would reflect upon their behaviour and, therefore, find repose. The distance between A and B becomes much shorter: a private car reaches B in a few moments, a personal computer and a smartphone help reply in a second. We do everything to succeed in productivity and, perhaps, damage our health. Conclusion. Thus, it shortens time and distance but limits our possibilities and depletes our chances of earning new experience and ability to enjoy the moments. It seems that only having understood the restrictions of movement, we will realize the value of unhasting stroll.
Flashcard-Based Augmented Reality To Increase Students' Scientific Literacy

Augmented Reality (AR) is a type of learning media that combines virtual and real worlds in real-time. It can make it easier for students to visualize the phenomena. This research aimed to measure flashcard-based AR’s effectiveness based on scientific literature. This research used a quasi-experimental method using a post-test-only control group design, and the participants were 60 college students at Universitas PGRI Adi Buana Surabaya. Data in the research were collected through tests to determine students’ scientific literacy skills, including aspects of knowledge and competence in analyzing scientific phenomena, connecting physics concepts to existing phenomena, and interpreting data or scientific evidence and questionnaires. The data were analyzed by calculating the average test score according to scientific literature and the percentage of user satisfaction. Based on the research, using flashcard-based augmented reality could increase the students’ scientific literacy.&#x0D; Keywords: augmented reality; learning media; scientific literacy
Adopting electronic healthcare services during COVID-19 and the nations responding: evidence from Jordan

This research aims to examine the national responding of healthcare services and the existing initiatives among adoption of electronic service during the COVID-19 in Jordan. The study model is extending to the theory of acceptance technology and use, which includes effort expectancy, performance expectancy, and facilitating position factors. A quantitative approach survey questionnaire was conducted towards employees working in private hospitals in Jordan. A total of 315 valid and completed responses were retrieved. The sample was randomly selected to ensure fair representation of the population society. The conceptual model of this research was empirically examined using hierarchical regression. The results showed that all independent predictors conceptualised in the model were significant predictors with 80% of the variance in the adoption of electronic healthcare. The study provides some new findings that would help in understanding the role of technology over the emerging situations and crisis particularly in the COVID-19 pandemic.
Unexpected optimal measurement protocols in Bell's inequality violation experiments

Bell's inequality violation experiments are becoming increasingly popular in the practical teaching of undergraduate and master's degree students. Bell's parameter S is obtained from 16 polarization correlation measurements performed on entangled photons pairs. We first report here a detailed analysis of the uncertainty u(S) of Bell's parameter taking into account coincidence count statistics and errors in polarizers' orientation. We show using both computational modeling and experimental measurement that the actual sequence of the polarizer settings has an unexpected and strong influence on the error budget. This result may also be relevant to measurements in other settings in which errors in parameters may have non-random effects in the measurement.
Automated video game parameter tuning with XVGDL+

Usually, human participation is required in order to provide feedback during the game tuning or balancing process. Moreover, this is commonly an iterative process in which play-testing is required as well as human interaction for gathering all important information to improve and tune the game components&amp;rsquo; specification. In this paper, a mechanism is proposed to accelerate this process and reduce significantly the costs of it, contributing with a solution to perform the game parameter tuning and game balancing using search algorithms and artificial intelligence (AI) techniques. The process is executed in a fully automated way, and just requires a game specification written in a particular video game description language. Automated play-testing, and game&amp;rsquo;s feedback information analysis, are related to perform game parameters&amp;rsquo; tuning and balancing, leading to offer a solution for the problem of optimizing a video game specification. Recently, XVGDL, a new language for specifying video games which is based on the eXtensible Markup Language (XML), has been presented. This paper uses XVGDL + , an extension of this lan- guage that incorporates new components to specify, within the video game specification, desirable goals or requirements to be evaluated after each game execution. A prototypical implementation of a Game Engine (termed XGE + ) was also presented. This game engine not only enables the execution of an XVGDL + game specification but also provides feedback information once the game has finished. The paper demonstrates that the combination of XVGDL + with XGE + &amp;nbsp; offers a powerful mechanism for helping solving game AI research problems, in this case, the game tuning of video game parameters, with respect to initial optimization goals. These goals, as one of the particularities of the proposal presented here, are included within the game specification, minimizing the input of the process. As a practical proof of it, two experiments have been conducted to optimize a game specification written in XVGDL via a hill climbing local search method, in a fully automated way.
Mechanical properties prediction of tire cord steel via multi-stage neural network with time-series data

ABSTRACTCord steel is a kind of high-quality wire, whose mechanical properties will affect the safety and service life of tire. Therefore, the prediction model of mechanical properties during production process is very important to ensure the quality stability. In the paper, the Multi-Stage Neural Network with Time-Series data (MSNNTS) is proposed to mine the rich information of high-resolution time-series data and represent multistage process to achieve accurate mechanical properties prediction. According to the results, the best mean relative error, for tensile strength prediction, is about 1.25% and the hit rate with 3% error limit is about 98% on the testing set. It also obtains good results in predicting reduction of area. The results show that the method is of great significance to improve the quality stability and uniformity of cord steel.KEYWORDS: Time-series dataneural networkdeep learningdata miningmechanical propertiescord steelsteel rollingmultistage process Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research is supported by the National Key Technology R&D Program of the 12th Five-year Plan of China [grant number 2015BAF30B01]. This research is supported by the Fundamental Research Funds for the Central Universities [grant number FRF-AT-20-04].
The Prince Nikolay Konstantinovich Romanov’s personal library: The provenance and existence in Turkestan in the late 19th – early 20th century

The authors revive the history of the Prince Nikolay Romanov’s personal library, its presence in Turkestan, and characterize its features. They define the role of the owner as an educator, researcher, and bibliophile. The article is based on the periodicals, academic papers, memoirs, letters and archival materials of that period. The main methods applied were historical bibliological analysis, and visual observation of library and archival collections. The archival documents being introduced into scientific discourse enable to investigate into the matters related to selection principle, ex libris and inscripts. The Grand Duke Romanov’s book collection can be partially reconstructed with the collections of A. Navoi National Library of the Republic of Uzbekistan and Uzbekistan Academy of Sciences Fundamental Library. The study expands the knowledge of the Prince’s personal library, of his scientific interest and reading preferences. The findings will be interesting to the researchers of the Russian emigration, book and library historians. The authors conclude that Grand Duke Nikolay Romanov was a philanthropist, researcher, and bibliophile. His personal book collection is of great value for study and preservation of Russian cultural heritage in the Republic of Uzbekistan.