Reviewerly/exHarmony huggingface dataset:
Relationship between Knowledge Flow of Scientific and Technological Innovation and the Collaborative Innovation Ability of Students

Scientific and technological innovation ability of students is an important part of scientific and technological innovation in higher vocational colleges. There are few scientific and technological innovation achievements and low scientific and technological content of technical application achievements in higher vocational colleges at present, which are mainly caused by the single innovation organization form and weak innovation knowledge sharing ability. It is of great significance and value to explore the knowledge flow of scientific and technological innovation in colleges and universities and the collaborative innovation of college students. There is little research on the relationship between knowledge flow of scientific and technological innovation and collaborative innovation of college students in the existing literature, so this article has carried out relevant research. This article constructs the mathematical model of knowledge flow of scientific and technological innovation in colleges and universities, analyzes the stability of the mathematical model of knowledge flow of scientific and technological innovation in colleges and universities, and gives the framework of collaborative innovation ecosystem for college students. This article accurately measures the embedding of scientific and technological innovation resources in colleges and universities, the knowledge flow of scientific and technological innovation and the collaborative innovation performance of college students, and empirically tests the direct influence effect of embedding scientific and technological innovation resource network in colleges and universities on the collaborative innovation performance of college students and the moderating effect of the knowledge flow of scientific and technological innovation in colleges and universities. Finally, the corresponding experimental analysis results are given.
Automation and Novelty –Archaeocomputational Typo-Praxis in the Wake of the Third Science Revolution

In this paper, I will explore some of the implications of machine learning for archaeological method and theory. Against a back-drop of the rise of Big Data and the Third Science Revolution, what lessons can be drawn from the use of new digital technologies and computational approaches as they are applied to archaeological typologies? In this paper, I explore two key aspects of these approaches - automation and epistemic novelty – and attempt to unravel their implications for archaeological practice. Furthermore, the paper will situate these topics within developments of the philosophy of science and technology and suggest an alternative way to think about machine learning that draws on re-thinking what we mean by machines and automation.
Improved Support Vector-Recurrent Neural Network with Optimal Feature Selection-based Spoken Language Identification System

Objective: Spoken language identification being the fore-front of language recognition tasks and most significant medium of communication has to be enhanced in order to improve the accuracy of recently developed spoken language recognition systems.The purpose of this paper is to enhance the Spoken Language Identification (SLID) model using hybrid machine learning with deep learning model for regionally spoken languages of Jammu & Kashmir (JK) and Ladakh.Method: Initially, the speech signals of different languages of JK and Ladakh are manually collected from diverse sources, and it is preprocessed using Spectral Noise Gate (SNG) filtering technique.Once the speech signals are pre-processed, the feature extraction is performed by the cepstral features like Mel-frequency Cepstral Coefficients (MFCCs), Relative Spectral Transform-Perceptual Linear Prediction (RASTA-PLP), and spectral features like spectral roll off, spectral flatness.Findings: From this feature extraction, the length of the feature vector seems to be long, and it is required to reduce the feature length.Hence, optimal feature selection is accomplished using the new meta-heuristic algorithm termed Adaptive Distance-based Tunicate Swarm Algorithm (AD-TSA) by considering the minimum correlation as objective.Finally, the language identification is handled by the hybrid classifier termed Improved Support Vector Machine-Recurrent Neural Network (ISVM-RNN).Novelty: The identification learning algorithm is enhanced by the AD-TSA by considering the minimum correlation as objective among features in order to get minimum number of features that are sufficient for language identification process.The efficiency of the proposed hybrid approach is validated by simulating the experiment on a user-defined language database of JK and Ladakh speech signals in the working platform of Python.
Managing Educational Systems and Sector in the Context of Artificial Intelligence: An Overview

Technology has always played a significant role in the evolution and development of societies everywhere. Artificial intelligence is emerging as the next game changer in the field of technology. It is the simulation of human cognitive processes by computers, specifically computer systems. The use of artificial intelligence might considerably improve the overall functioning of the educational system. The key goals of integrating artificial intelligence in educational management and administration are to improve educational and administrative quality. In the classroom, virtual and augmented reality provides students and teachers with real-time teaching and learning experiences. There is an urgent need to expand educational access, provide technical support and guidance to universities, and include provisions for technology-based online learning management systems that support lifelong learning, as well as online administration and management activities that meet the needs of researchers and academicians. The current paper describes how AI can automatically change existing administrative and management systems at the institutional level, as well as electronically modifies traditional teaching and learning techniques by seamlessly integrating with E-learning technology and online Learning Management Systems.
A Pragmatic Analysis of Flouting Maxims in Classroom Verbal Interaction as Seen in Freedom Writers Movie

Successful classroom verbal interactions will occur when both the teacher and the students intend to be cooperative conversational agents contributing to the conversation's aims. In Pragmatics, this underlying principle is called Grice’s conversational maxims. However, in the classroom, both sides often intentionally flout these conversational maxims. Thus, this research aimed to conduct a pragmatic analysis to investigate the types of Grice’s conversational maxims violated by the main character of Freedom Writers movie along with the categories of teacher’s verbal interactions found in that movie under Flanders Interaction Analysis Categories System (FIACS). Using the document analysis method, the researcher used the movie transcript as the primary document to be analyzed. The findings showed that the four maxims were violated intentionally for several reasons, including warning the students of the consequences of their actions, encouraging them, avoiding certain topics of discussion, and emphasizing important messages without blatantly stating them to the whole class, and avoiding hurting the students’ feelings. Meanwhile, under Flanders Interaction Analysis Categories (FIAC), direct and indirect talks could be found in the movie. The result of this study can provide educators and pre-service teachers a glimpse of the importance of promoting appropriate classroom verbal interactions by analyzing the quality of classroom verbal interaction in terms of Grice’s Conversational Maxims and Flanders’ Interaction Analysis.
Travel Direction Recommendation Model Based on Photos of User Social Network Profile

Travelling is one of the most enjoyable activities for people of all ages. It is constantly looking for innovative solutions on how to tailor travel recommendations to the needs of its customers. The purpose of our proposed recommendation model is to suggest travelling countries based on photos from the user’s social network account and metadata associated with the photos. Such recommendation models are highly dependent on the data used in the model preparation steps and on the technologies and methods implemented in the model. The newly collected data from the Instagram users’ accounts were used in the model preparation. The recommendation system is based on the combination of four methods: object detection, similarity measures, classification, and data clustering. The novelty of the proposed recommendation model is that it adopts different data (Instagram photos) for travel direction recommendation, defines a new combined method, integrates results of similarity measurement and SOM application results into one final recommendation, and estimates the parameter impact for different components of recommendation model. A proposed evaluation measure has been used to conclude the results of the recommendation model and as a result the names of the travelling countries have been recommended. The results of the proposed recommendation model are promising, and the validation results demonstrate that on average 63% of the users who visited countries match the recommendations provided for the trip directions, while the accuracy of recommendations, matching user visited countries, but not presented in the photos for recommendation estimation, on average was 96%. The accuracy performance is very positive, while the recommendation system is fully automated and machine learning based. With time, the accuracy of the model may even increase by adopting the photo metadata (location).
Improving the Face Recognition Performance Using Gabor and VGGFace2 Features Concatenation

This paper presents a new method for face recognition that is based on concatenation of Gabor and VGGFace2 features. The proposed method is composed of three stages: a feature extraction, concatenation and a recognition stage. The feature extraction stage is implemented using the pre-trained model VGGFace2 and PCA is used to reduce the Gabor features, while the recognition stage is implemented using full connected neural networks. The proposed method was evaluated on the IJB-A dataset and Labeled Faces in the Wild (LFW) dataset. The results show that it is able to achieve recognition accuracy more than 99%.
Significance of Block Chain Technology and Industry 5.0 in Indian Banking Sector

Since the time when liberalization was introduced, many changes have taken place in banking world. Although in India block chain technology is still at its initial stage, many of the banks are using this technology to make their tasks easier. However, block chain technology will offer remarkable progress in the area of banking as with the help of it; banks are able to provide quick, accurate, and quality service to their customers. With the inception of blockchain technology, the banking sector has transformed, as many of its processes have become transparent, safe, and efficient as well. Under blockchain technology, banking systems are basically based on one point data base, which has dispersed ledger for reducing cyber crimes. The present chapter tries to depict the same with the help of a descriptive analysis of increase in incentives, and also the inconvenience faced by banks in recent times after the introduction of block chain technology.
Blockchain-Based E-Certificate Verification and Validation Automation Architecture to Avoid Counterfeiting of Digital Assets in Order to Accelerate Digital Transformation

The security and confidentiality of data are very important for institutions. Meanwhile, data fabrication or falsification of official documents is still common. Validation of the authenticity of documents such as certificates becomes a challenge for various parties, especially those who have to make decisions based on the validity of the document. Scanning-based signatures on printed and digital documents are still relatively easy to counterfeit and yet still difficult to distinguish from the original. The traditional approach is no longer reliable. Solutions to these problems require the existence of data security techniques, seamless online verification of the authenticity of printed documents, and e-certificates quickly. The objective of the study is to model the e-certificate verification process via blockchain and proof-of-stake consensus methods and use MD5 encryption. The data or identity listed on the e-certificate is secured with an embedded digital signature in the form of a QR code and can be checked for the truth online. A combination of technologies capable of suppressing or removing counterfeiting of digital assets will accelerate digital transformation across spectrums of modern life. The resulting architectural model can be used as a starting point for implementing a blockchain-based e-certificate verification and validation automation system.
An Analysis of Barriers and Facilitators for the Development of Digital Competencies of Engineering Students

OECD has established that adults should have the necessary skills and competencies to solve problems and perform complex tasks in “technology-rich environments”. This would mean considering not only basic competencies, but also higher-order skills needed to use information, evaluate information critically, and use it to solve problems. A key concept in the present proposal is related to Digital Competence (hereafter DC). Ferrari et al. Define DC as the: “the set of knowledge, skills, attitudes, abilities, strategies and awareness that is required when using ICT and digital media to perform tasks; solve problems; communicate; manage information; behave in an ethical and responsible way; collaborate; create and share content and knowledge for work, leisure, participation, learning, socializing, empowerment and consumerism” [4]. The general objective of this research was to analyze the characteristics of the DCs of students pursuing engineering and related careers in a private institution of VET, recognizing barriers and facilitators that intervene in the development of DCs. The results obtained are an approximation to DC and the perceptions of Chilean students from a VET institution of it. They allow the authors also, to identify various aspects of the online learning experience in the context of the global pandemic and new needs to be corrected by teachers and university authorities in the design and implementation of OL in VET context.
3D CNN hand pose estimation with end-to-end hierarchical model and physical constraints from depth images

Previous studies are mainly focused on the works that depth image is treated as flat image, and then depth data tends to be mapped as gray values during the convolution processing and features extraction. To address this issue, an approach of 3D CNN hand pose estimation with end-to-end hierarchical model and physical constraints is proposed. After reconstruction of 3D space structure of hand from depth image, 3D model is converted into voxel grid for further hand pose estimation by 3D CNN. The 3D CNN method makes improvements by embedding end-to-end hierarchical model and constraints algorithm into the networks, resulting to train at fast convergence rate and avoid unrealistic hand pose. According to the experimental results, it reaches 87.98% of mean accuracy and 8.82 mm of mean absolute error (MAE) for all 21 joints within 24 ms at the inference time, which consistently outperforms several well-known gesture recognition algorithms.
Exploring Engineering Students’ Perceptions About the Use of ICTs and Educational Technologies in VET

At the institutional level, Chilean universities and Vocational Education and Training (VET) institutions have made significant investments in information and communication technologies (ICTs), such as virtual platforms, learning technologies, and streamlining bureaucratic processes related to university management among others. Before the COVID-19 pandemic, there was already a significant use of ICT resources, especially in many post-graduate programs, which were offered in online or blended learning modalities. The main goals of the study were to explore students’ perceptions from a Chilean vocational school (post-secondary education) and university of applied sciences, with campuses (more than 27) in all regions of Chile about the use of ICTs and educational technologies, and to know about the participants’ attitudes towards the educational use of ICTs and other educational software. Based on scientific literature and their previous experience in research projects about the use of ICTs and the development of a didactical strategy to incorporate educational technologies in the learning process of engineering students, the authors developed a categories system with indicators for the instrument design. The instrument consists of a questionnaire with closed (25 items) and open-ended questions (3) organized into eight main categories with their respective items.
AN EMPIRICAL ANALYSIS OF SPECULATIVE BEHAVIOR AND THE SPILLOVER EFFECT IN CRYPTOCURRENCY MARKETS

For risk management and stable pricing in the cryptocurrency market, it is necessary to determine the interdependence of speculative behaviour and crypto assets. The correlation and high volatility caused by the interdependence of financial assets in the cryptocurrency market can lead to spreading risks. The study aims to measure the speculative behaviour and spillover effect in the prices of financial assets in the cryptocurrency market. The study used the SADF test, the generalized Dickey-Fuller test (GSADF), and the frequency domain causality test of Breitung and Candelon (2006) to determine the speculative behaviour and spillover effect in the prices of financial assets in the cryptocurrency market. Empirical evidence of speculative bubble formation between January 1, 2018, and December 2021 for the cryptocurrency assets covered in the study (ADA, BNB, BTC, DOGE, ETH, XLM, and XRP) is presented. Moreover, the frequency domain causality results obtained in the study show a contagion and spillover effect between crypto assets. The results provide essential information on the development of speculative behaviour and spread risk in the formation of financial asset prices in the cryptocurrency market.
THE USE OF DIGITAL TECHNOLOGIES IN THE IMPLEMENTATION OF DISTANCE LEARNING AT THE UNIVERSITY

The article discusses the features of distance learning at the university. The positive influence of digital technologies on the process of modernization of domestic education, on the personification of learning, on the nature of interaction between participants in the educational process is determined. The results of the survey are presented, the purpose of which was to study the effectiveness of the use of digital technologies in the educational process in the implementation of distance learning, as well as to find out the opinion of students about the features of the educational process during the implementation of distance learning. Most students note that they have adapted well to the conditions of distance learning at the university and are satisfied with the organization of the educational process. In the educational process, the following digital technologies are used to conduct classes: the BigBlueButton webinar system, the Zoom service, Jamboard, YouTube, Slido, Microsoft Teams, Google Classroom, programs for creating presentations. In the course of the study, positive and negative characteristics of distance learning were identified, data were obtained confirming the influence of distance learning on the well-being of respondents and the relationships of the team. The article notes that distance learning stimulates the development and transformation of the educational process, encourages finding and using new learning tools and technologies.
IMAGINATION AS "INTERNAL VISION SCREEN" IN THE CREATIVE PROCESS OF THE WORK OF THE ACTOR ON THE ROLE

The relevance of this study is due to the fact that the concept of imagination, which is much talked about in psychology, remains incomplete outside of theatrical discourse, actor's and director's understanding of this category. Imagination is not a spontaneous, automatically developing process, but an in-depth process based primarily on the intellectual capabilities of the actor through the manifestation of his analytical abilities, which are directly related to the degree of development of his imagination, which determines the professional quality of the actor. The algorithm of the work of the imagination, its phased development is investigated. Examples are given from the pedagogical experience of the author of the article on activating the imagination of students - trainings and tasks that develop figurative thinking and, as a result, acting skills. An integral part of learning is tasks for the memory of physical actions, where the subject is imaginary, and actions with it are real. The problems of interaction between the actor and the spectator in the performances of the puppet theater are touched upon: the role of imagination control in theatrical activity. Lack of imagination or thoughtless departure from it leads to a negative result: instead of "co-creation", immersion in the picture created by the actor, repulsive feelings awaken in the viewer. Imagination has a special role in theater as a "three-dimensional art".
Evaluation Method of Physical Education Teaching Quality in Higher Vocational Colleges Using Mobile Teaching Terminal

At present, there is a problem of single subject and mode in the evaluation of physical education teaching quality in higher vocational colleges, which affects the accuracy of the evaluation results. In order to improve the accuracy of teaching quality evaluation results, this paper proposes an evaluation method of physical education teaching quality in Higer Vocational Colleges by using mobile teaching terminal. Analyze the application strategy of mobile teaching terminal in physical education teaching; Collect physical education teaching data based on mobile teaching terminal; Design the teaching quality evaluation index system; Determine the index weight and build the quality evaluation model; The comprehensive evaluation of physical education teaching quality in higher vocational colleges is realized through the qualitative index fuzzy quantitative method. The test results show that the higher vocational physical education teaching quality evaluation method using mobile teaching terminal proposed in this paper has high detection rate and accuracy, so the evaluation results are more effective.