Reviewerly/exHarmony huggingface dataset:
An integrated fuzzy AHP and fuzzy TOPSIS approach in the hotel industry

In the context of the COVID-19 epidemic, the turnover intention rate is increasing day by day. The objective of this study is to identify the main factors influencing turnover intention in the Vietnam hospitality industry. The study utilizes the fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes Work Itself, Supervision, Coworkers relationships, Salary and Benefit, Career Opportunities, Job Stress, Perceived Risk, and Job Insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance level of dimensions is evaluated by 17 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are Salary and Benefit. Moreover, the results indicate that the least important dimensions are the Co-workers' Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are Work Itself, Job Stress Perceived Risk, and Job Insecurity. Moreover, this study’s results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the Below three-star hotels. The results of the study will help businesses in the fields of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions.
Feynman checkers: towards algorithmic quantum theory

We survey and develop the most elementary model of electron motion introduced by R.Feynman. In this game, a checker moves on a checkerboard by simple rules, and we count the turns. Feynman checkers are also known as a one-dimensional quantum walk or an Ising model at imaginary temperature. We solve mathematically a problem by R.Feynman from 1965, which was to prove that the discrete model (for large time, small average velocity, and small lattice step) is consistent with the continuum one. We study asymptotic properties of the model (for small lattice step and large time) improving the results by J.Narlikar from 1972 and by T.Sunada-T.Tate from 2012. For the first time we observe and prove concentration of measure in the small-lattice-step limit. We perform the second quantization of the model.
Prospects for scientific communications in social sciences and humanities sphere in current conditions

The article discusses the place of social sciences and humanities in the system of scientific knowledge in modern Russia, and shows on the example of historical memory, and how their importance to ensure national security and development of society as a whole, especially emphasizing the predictive function, has increased in the current context. The problem of the transition from old forms of scientific communication to new ones: from printed publications to digital tools of production, storage and distribution of scientific knowledge is considered. Drawing historical parallels, the author explains how important to maintain the position of domestic science and our country in the world to make this transition, and emphasizes the role of the editors and editorial boards in solving this problem.
The Application of Blockchain in Vietnam’s Agriculture Products Supply Chain: A Systematic Literature Review and Directions for Future Research

The objective of the article is to analyze and evaluate the overview of research works related to Blockchain application in the agricultural products supply chain. The article uses qualitative research methods, a systematic literature review from previous national and international studies and directions for future research, as well as the research methods and theories being used in previous publication. On that basis, the article identifies research gaps and proposes further research directions to be carried out in the future. Keywords: Blockchain, supply chain, Agricultural products, Vietnam
Choosing a language strategy for a top-rated Russian academic journal

Increasing citation and improving the impact factor is a challenging task for both authors and scientific journals. It is particularly so for Russian journals indexed in international scientometric databases, including Web of Science and Scopus. This study shows that researchers consider inefficient language strategies to be one of the main reasons for poor international outreach. This article explores the strategies of several Russian journals indexed in Scopus as of March 2022, identifies their advantages and disadvantages as well as the subsequent risks. The study offers recommendations for choosing an optimal language strategy, including the one aimed at increasing citation in international and national databases and promoting rated Russian journals internationally. Based on the analysis of the journals indexed in the Scopus database, six linguistic models have been identified. The study has shown that the bilingual format – publishing in Russian and English – provides the best visibility at the national and international levels.
Customer Satisfaction Act upon the Brand’s Fame: A Case Study of Nestle

Nestle is a globally recognized brand with a large following of dedicated customers because of its variety of products that captivate everyone who consumes it. This study aims to examine the correlation between customer satisfaction on Nestle’s fame and fortune. Nestle may have issues regarding their customer satisfaction which is affecting the company’s development. Therefore, this case study tries to show and analyze how Nestle meets customer satisfaction while improving its products. A survey has been carried out to obtain new, valid, and accurate data. A total of 100 respondents participated in this survey. Besides, secondary data for this study was acquired from a variety of resources such as websites, journals, and articles in order to gain a deeper understanding. The findings indicate that customer satisfaction influences the fame of Nestle. The findings also provide recommendations to enhance the opportunity of improving Nestle’s customer satisfaction and suggestions for future development.
Quantitative measures for classification of human upper body posture in video signal to improve online learning

In an era dominated by video conferencing and distance learning, technologies that can increase the quality of education have become exceptionally important. Moreover, these unprecedented times can be used to introduce new and improve the traditional paradigms of classroom teaching. In this regard, it would be highly beneficial to develop methods for efficient estimation and classification of student attention and engagement based on readily available visual information. Today webcams and other different optical sensors have become ubiquitous and are used in online lecturing on regular basis. It was already demonstrated that the visual signal they provide is of sufficient quality for the prediction of student's learning curves. In our previous work, a software application for the recognition of the head, arms, and upper-body orientation and position was developed and initially tested on a limited dataset achieving a mean accuracy of 96.88%. In this research, a catalogue of upper body posture positions characteristic in online lectures is identified and described. A catalogue of quantitative measures for the classification of upper body posture positions, based on the set, are proposed. The measures are divided into spatial, temporal, and functional groups. Subsequent studies should verify the validity of proposed measures.
Multi-sensor configurations in data fusion systems

This paper discusses the problems, related to the classification of sensor configurations in multi-sensor fusion systems from the information theory point of view. The criteria, used at present, are defined by the information interactions between the sources. They are qualitative in nature and allow for subjective interpretation, which significantly complicates the classification process, based on them. The present work proposes new criteria and a new type of classification, defined within the framework of the partial information decomposition - a recent extension of the information theory. The proposed criteria, unlike the existing ones, are quantitative, ensure objectivity in classification and allow for direct comparison and evaluation of different sensor configurations.
Utilizing Language Models to Expand Vision-Based Commonsense Knowledge Graphs

The introduction and ever-growing size of the transformer deep-learning architecture have had a tremendous impact not only in the field of natural language processing but also in other fields. The transformer-based language models have contributed to a renewed interest in commonsense knowledge due to the abilities of deep learning models. Recent literature has focused on analyzing commonsense embedded within the pre-trained parameters of these models and embedding missing commonsense using knowledge graphs and fine-tuning. We base our current work on the empirically proven language understanding of very large transformer-based language models to expand a limited commonsense knowledge graph, initially generated only on visual data. The few-shot-prompted pre-trained language models can learn the context of an initial knowledge graph with less bias than language models fine-tuned on a large initial corpus. It is also shown that these models can offer new concepts that are added to the vision-based knowledge graph. This two-step approach of vision mining and language model prompts results in the auto-generation of a commonsense knowledge graph well equipped with physical commonsense, which is human commonsense gained by interacting with the physical world. To prompt the language models, we adapted the chain-of-thought method of prompting. To the best of our knowledge, it is a novel contribution to the domain of the generation of commonsense knowledge, which can result in a five-fold cost reduction compared to the state-of-the-art. Another contribution is assigning fuzzy linguistic terms to the generated triples. The process is end to end in the context of knowledge graphs. It means the triples are verbalized to natural language, and after being processed, the results are converted back to triples and added to the commonsense knowledge graph.
Analysis and Application of Data Mining Technology for College English Education Integration

With the development and application of information fusion technology, English education can realize intelligent application under multi-information fusion technology. In view of the low degree of educational informationization and single application of intelligent methods in the process of education, this paper puts forward the application of multi-technology in English education, so as to improve the education level and application skills. Firstly, this paper explains the educational application technology, especially the analysis of decision tree and linear regression method in data mining technology, and puts forward the framework and system structure diagram of English education system. In the experiment, the application of different methods is compared, and the results show that the decision number method has higher weight in weight analysis. According to the situation of different course quantity, 50%–80% of the course workload can be completed under multi-information fusion. However, in the amount of homework completion, most of the personnel can complete the homework, which has a good application effect. In different English majors, different research methods have different educational purposes and different teaching effects. Through the system interface and system performance testing, using the data mining method has better UI test results and shorter test time.
Trading app analyzer using implanted sensing technique in IoT via blockchain-based networks

Handheld devices equipped with sophisticated sensors enabling data collection as well as remote monitoring would lay the groundwork for one low-cost data trading approach. This data, for example, could be linked to contaminants and greenhouse emissions and then used to assess the limitations of current regulatory requirements. On a larger scale, the current IoT data trade method relies on a centralised third-party organisation to regulate among data producers and users, which is ineffective and unsafe. These decentralised solutions based on block chain technology, on the other hand, allow data exchange while guaranteeing integrity, confidentiality, and anonymity. However, leading to a lack of understanding of process efficiency between retailers and buyers, there is a significant gap in assessing data trading procedures in IoT. We propose a paradigm for IoT-based data trade known as the Internet of Things and the blockchain network, that is intended to allow significant environmental monitoring and is influenced through the knowledge gap. We can examine the efficacy of transmission of three fundamental IoT trade protocol connections with respect to delay and power usage. These protocols model and analysis serve as a baseline for IoT data exchange solution.
Leveraging small scale quantum computers with unitarily downfolded Hamiltonians

In this work, we propose a quantum unitary downfolding formalism based on the driven similarity renormalization group (QDSRG) that may be combined with quantum algorithms for both noisy and fault-tolerant hardware. The QDSRG is a classical polynomially-scaling downfolding method that avoids the evaluation of costly three- and higher-body reduced density matrices while retaining the accuracy of classical multireference many-body theories. We calibrate and test the QDSRG on several challenging chemical problems and propose a strategy for avoiding classical exponential-scaling steps in the QDSRG scheme. We report QDSRG computations of two chemical systems using the variational quantum eigensolver on IBM quantum devices: i) the dissociation curve of H$_2$ using a quintuple-$\zeta$ basis and ii) the bicyclobutane isomerization reaction to $trans$-butadiene, demonstrating the reduction of problems that require several hundred qubits to a single qubit. Our work shows that the QDSRG is a viable approach to leverage near-term quantum devices for the accurate estimation of molecular properties.
Tradisi Sodoran Tengger sebagai Alat Diplomasi Budaya Indonesia melalui Pembelajaran BIPA

Culture in BIPA learning as a tool of cultural diplomacy has become an interesting theme for researchers. The cultural aspect of BIPA is also related to the cultural closeness of BIPA students to the place where they study (the area/city where BIPA is studied in Indonesia). This study aimed to identify and describe the use of the Sodoran Tengger tradition in BIPA learning of B2 level activities to increase Indonesian knowledge competence. This research is a qualitative type with a descriptive method. The use of descriptive analysis methods is carried out to describe the facts, which are then studied with the relevant theory. The results of this study are the use of the Tengger Sodoran dance as BIPA teaching material and the use of traditional sodoran fairy tales as BIPA teaching materials. Utilizing Sodoran Tengger's local tradition material on aspects of the meaning of dance moves and fairy tales is an innovative and interesting choice for BIPA class teachers. The existing aspects can be explored and collaborated into various fun learning activities. Besides improving linguistic competence, it is also a means of introducing local Tengger culture (Javanese culture) to BIPA students.
Evaluasi Pemanfaatan Aplikasi Game dalam Ujian Bahasa Indonesia (Studi Kasus di SMAN 1 Polanharjo Klaten)

This study aims to evaluate the implementation of the exam by utilizing game applications in Indonesian subjects at SMA Negeri 1 Polanharjo. This study involved a teacher and four students, consisting of two students in class X and two in class XI. This research uses a qualitative approach with a case study strategy; research data is obtained by observation and interviews; data validity is done by triangulation of data and sources. The results of the research: (1) the implementation of the Indonesian language exam at SMA Negeri 1 Polanharjo has used the Scorative game application as a learning evaluation tool; (2) the advantages of using Scorative games in exams, namely making students more enthusiastic in carrying out exams and making the exam atmosphere more fun; (3) deficiencies in the use of Scorative games, namely that they cannot be used for large-scale examinations due to limited facilities and infrastructure as well as the competence of human resources in the use of technology; and (4) obstacles that arise in the implementation of game-based exams, namely the readiness factor for the quality and quantity of devices, networks, and the level of students' understanding of the use of applications.
Pengaruh Model Discovery Learning Berbantuan “Kuba-Kusa” Terhadap Hasil Belajar Matematika Siswa Kelas V

The purpose of this study was to determine whether the discovery learning model assisted by the "Cuban-Kusa" teaching aid had an effect on mathematics learning outcomes, especially on the volume of cubes and blocks for fifth-grade students at SDN 1 Duren. The sample of this research is the fifth-grade students at SDN 1 Duren as many as 14 students and the fifth-grade students at SDN 1 Dermosari as many as 13 students. The research method uses quantitative research, and the type of research is a non-equivalent pretest and posttest control group design. Mathematics learning outcomes are measured by a test instrument in the form of 20 multiple-choice questions. Based on the research results from hypothesis testing using an independent sample t-test, the results obtained are sig. (2-tailed) namely (0.003 &lt; 0.05), so the results show that Ha is accepted and H0 is rejected. It can be concluded that the mathematics learning outcomes of students at SDN 1 Duren are influenced by the discovery learning model assisted by the "Cuban-Kusa" teaching aids. It can be seen from the average posttest results of 80.00 in the experimental class and the average results of 66.92 in the control class.
An integrated fuzzy-VIKOR-DEMATEL-TOPSIS technique for assessing QoS factors of SOA

Quality of service (QoS) is a very important concept in service-oriented architecture (SOA). While there is a growing body of study on QoS-based service selection based on SOA, there is little research on analyzing QoS factors from the viewpoints of IT workers and researchers. As a result, the purpose of the current study aims to offer an integrated fuzzy VIKOR-TOPSIS-DEMATEL approach framework for evaluating QoS factors of online services from the viewpoint of experts in a fuzzy environment. A numerical assessment of the QoS factors for a case firm in Ghana indicated that the suggested technique is appropriate for the problem. Furthermore, the technique outcomes divided QoS factors into cause-effect variables, ranked QoS factors, and lastly, suggested conflicting QoS factors. The results from the Fuzzy DEMATEL aspect of the proposed approach found integrity, availability, accessibility, compliance, documentation, latency, and adaptability as causal variables. While response time, cost/price, reliability, performance, security, reputation, throughput, best practices, success ability, encryption, portability, storage, and consistency are regarded as influential variables. The Fuzzy TOPSIS aspect of the technique found adaptability, documentation, consistency, transaction, and accessibility are the most ranked QoS factors of online services. The fuzzy VIKOR side of the proposed method discovers integrity, cost, and latency as incommensurable QoS factors. Finally, a sensitivity analysis was carried out, and the results show the model is robust. This study confirms the position of existing knowledge on sensitivity analysis in the QoS literature. In the issue of QoS factor evaluation, this work effectively blended three MCDM techniques. The study's shortcoming stems from its reliance on data from QoS specialists from only one developing nation (i.e. Ghana).
Discrete Hyperparameter Optimization Model Based on Skewed Distribution

As for the machine learning algorithm, one of the main factors restricting its further large-scale application is the value of hyperparameter. Therefore, researchers have done a lot of original numerical optimization algorithms to ensure the validity of hyperparameter selection. Based on previous studies, this study innovatively puts forward a model generated using skewed distribution (gamma distribution) as hyperparameter fitting and combines the Bayesian estimation method and Gauss hypergeometric function to propose a mathematically optimal solution for discrete hyperparameter selection. The results show that under strict mathematical conditions, the value of discrete hyperparameters can be given a reasonable expected value. This heuristic parameter adjustment method based on prior conditions can improve the accuracy of some traditional models in experiments and then improve the application value of models. At the same time, through the empirical study of relevant datasets, the effectiveness of the parameter adjustment strategy proposed in this study is further proved.
Correction to: Hybrid Adaptive Moth-Flame Optimizer and Opposition-Based Learning for Training Multilayer Perceptrons

In the original version of chapter “Hybrid Adaptive Moth-Flame Optimizer and Opposition-Based Learning for Training Multilayer Perceptrons” Author provided new figures are updated for Figs. 1 to 6. The correction chapter and the book has been updated with the change.
Opinion Paper: Methodology and Significance

The functional features of the opinion paper structure are revealed, its specificity is characterized. The necessity of a clear focus of the author's point of view on the analyzed problem from the standpoint of its balanced review to stimulate scientific discussion is emphasized. An opinion paper helps to demonstrate the opinion of its author regarding the contribution of the presented problem to general knowledge on the topic. Also, it serves as a basis for revising an existing theory or concept or introduces the reader to a new problem. Extreme clarity and brevity of presentation, transparent argumentation are essential tools for building a successful opinion paper. Preliminary familiarity with the conventions of its construction is a decisive step in achieving the effectiveness of the content and ensuring its contribution to the exchange of scientific knowledge.