Reviewerly/exHarmony huggingface dataset:
VTKG: A Vision Transformer Model with Integration of Knowledge Graph for Enhanced Image Captioning

The Transformer model has exhibited impressive results in machine translation tasks. In this research, we utilize the Transformer model to improve the performance of image captioning. In this paper, we tackle the image captioning task from a novel sequence-to-sequence perspective and present VTKG, a VisionTransformer model with integrated Knowledge Graph, a comprehensive Transformer network that substitutes the CNN in the encoder section with a convolution-free Transformer encoder. Subsequently, to enhance the generation of meaningful captions and address the issue of mispredictions, we introduce a novel approach to integrate common-sense knowledge extracted from a knowledge graph. This has significantly improved the overall adaptability of our captioning model. Through the amalgamation of the previously mentioned strategies, we attain exceptional performance on multiple established evaluation metrics, outperforming existing benchmarks. Experimental results demonstrate a 1.32%, 1.7%, 1.25%, 1.14%, 2.8% and 2.5% improvement in Blue-1, Bluu-2, Blue-4, Metor, Rough-L and CIDEr score respectively when compared to state-of-the-art methods.
A Study of Challenges and Recommendations for Teaching: DevOps Education

DevOps has gained significant popularity in the software industry due to its ability to enhance collaboration, improve software delivery, and drive organizational agility. However, providing effective education and training in DevOps poses several Issue. This research paper presents an interview study conducted with a seasoned DevOps professional to explore the challenges faced in DevOps education and provide recommendations for addressing these challenges. The study highlights the evolving nature of the DevOps landscape, the interdisciplinary nature of DevOps, and the need for hands-on learning experiences. Additionally, the study emphasizes the importance of continuous curriculum updates, practical exercises, cross-functional collaboration, industry partnerships, and fostering a continuous learning mindset. The findings from this study contribute to the understanding of the unique challenges and recommendations for improving DevOps education.
BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

The rapid growth and integration of the Internet of Things (IoT) emphasizes the crucial need for effective data governance. This research unveils a novel framework, capitalizing on blockchain and smart contracts, aimed at decentralizing data governance in the IoT sphere. Our approach allows stakeholders to formulate and enforce data governance collaboratively, ensuring a balance between transparency, adaptability, and flexibility. Using the Ethereum platform and Solidity as our smart contract language, we constructed a demonstrative proof-of-concept. Our comparative evaluations highlighted our system's superiority, outpacing previous works with a scalability score of 95%, flexibility at 90%, and an unmatched transparency score of 100%. This framework presents a transformative paradigm for organizations and individuals working with IoT data, offering an efficient, transparent, and robust data governance mechanism.
Unleashing the Power of Deep Attention Networks: A Comprehensive Approach for Enhanced Artificial Intelligence

Deep learning has revolutionized the field of artificial intelligence by achieving state-of-the-art performance on a variety of complex tasks. Attention mechanisms have emerged as a powerful tool to enhance the capabilities of deep neural networks by enabling them to selectively focus on relevant information. In this article, we propose a novel artificial intelligence algorithm called Deep Attention Networks (DANs), which associate multiple attention mechanisms to improve performance on interesting tasks. We evaluate DANs on benchmark datasets in natural language processing, computer vision, and speech recognition and demonstrate superior results compared to existing state-of-the-art approaches. Our approach opens up new possibilities for advancing the field of artificial intelligence and holds promise for various real-world applications. Overall, our results demonstrate the effectiveness and potential of DANs for various AI applications, and highlight the power of combining deep neural networks with attention mechanisms.
RESDEN: A Novel Deep Unified Model for Face Recognition System

The Face Recognition technology plays a significant role in the field of Computer Vision in contemporary times. The research article is centered on a Facial attendance system that utilizes a deep learning technique to recognize face photos. To execute face identification and classification via the use of deep learning processes, many Convolutional Neural Network (CNN) models are taken into account. Previous studies have mostly focused on either the ResNet or DenseNet-based convolutional neural network model. The present research utilizes the merging of ResNet and DenseNet to propose a hybrid model. The proposed work is expected to provide enhanced efficiency and accuracy. In the training and testing stages of the simulation, considerations are made for both binary and category classifications. The current research focuses on the use of the LFW dataset. The pictures undergo an initial step of the noise reduction process. The evaluation of picture quality is conducted by taking into account metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). After the proposed model has undergone training, it generates photographs of superior quality. Finally, the proposed system incorporates the RESDEN framework, which integrates DenseNet with a noise reduction technique, a segmentation mechanism, and a CNN based on ResNet. A comparative analysis has been conducted to evaluate the accuracy of several filtered picture sets across different convolutional neural network (CNN) models. The simulation results indicate that the suggested model exhibited a good level of performance and accuracy.
Application and evaluation of sentence embedding and clustering methods in the context of concept hierarchy construction

Concept hierarchies, as part of knowledge representation methods, play an important role in supporting the exchange and sharing of information. We developed and automated a concept hierarchies construction process which includes several artificial intelligence techniques. When automating their construction from an existing, more or less structured, body of knowledge, the evaluation of the resulting concept hierarchy is an important step. We propose an approach for concept hierarchy construction (CHC) from short sentences, that makes use of methods like Sentence Embedding, Clustering, and Automatic Labeling to create a hierarchical representation consisting of three layers. Our major focus in this paper is not on the algorithms used but on their evaluation using manual clustering by experts and fuzzy sets.
Transition from classical to entrepreneurial university: alternative vision (on the example of Derzhavin Tambov State University)

Universities have always had a special place in society both as education and research centers. However, in the last decade there has been a worldwide trend of universities moving from a research type to an entrepreneurial one. This shift reflects the new challenges and opportunities for educational organizations in the modern world. Considered theoretical and methodological basis of an entrepreneurial university determines its specifics and its difference from a research or classical one, we analyze of the current state of the Derzhavin Tambov State University based on the strategic academic leadership program “Priority-2030”. G.N. Konstantinov and S.R. Filonovich proposed the matrix of entrepreneurial activity of the university – overcoming the limitations in knowledge generation, teaching and putting knowledge into practice and overcoming resource constraints: overcoming the shortage of human resources, overcoming the shortage of financial resources, overcoming the shortage of information resources. Based on the research mentioned above we formulate the tasks to accelerate the transformation of the Derzhavin Tambov State University into an entrepreneurial type organization: attracting leading scientists to the university in accordance with the needs of the university and the region, more targeted support for interdisciplinary research and networking, creating an accelerator for innovative projects, developing the concept of advanced training of scientific and pedagogical workers, diversifying educational programs, developing the innovative and entrepreneurial environment of the university, etc.
Model for formation of professionally important qualities among cadets in the system of additional education of Moscow school

The purpose of the study is theoretical substantiation and empirical verification of the effectiveness of the process of formation of professionally important qualities among cadets in the system of additional education within the framework of the project “Cadet class in Moscow school”. The task of the study necessitated the development of a model for the formation of professionally important qualities of cadets in the additional education of the Moscow school, to determine the indicators and levels that evaluate the effectiveness of their formation. The study used activity-based, personality-oriented, culturological methodological approaches, united by the general methodological principle of consistency. A model for the formation of professionally important qualities of cadets has been developed, which allows for theoretical and applied research. The pedagogical conditions for the formation of professionally important qualities of cadets that contribute to improving the effectiveness of the system of additional education of the Moscow school are determined. The expected social consequences of the practical use of the research results will be the high readiness of cadets to study at military universities. The originality of the research remains relevant and valuable not only due to the short duration of the project, which led to the fact that such a phenomenon as the formation of professionally important qualities of cadets of the project “Cadet class in Moscow school” has not found proper consideration in psychological and pedagogical research, but also in the fact that the above process is different complexity, has different dynamics of formation, features of its manifestation in students.
Dynamic Matching Algorithm of Human Resource Allocation Based on Big Data Mining

In order to ensure the dynamic matching effect of human resources allocation and improve the accuracy and efficiency of dynamic matching of human resources allocation, a dynamic matching algorithm of human resources allocation based on big data mining is studied. Analyze the meaning and function of big data mining, and explain the common analysis principles of big data mining. The information entropy is selected as the basis for measuring human resource allocation, the human resource allocation is extracted, and the similarity of human resource allocation is calculated using the Huasdorff similarity method based on time interpolation. According to the Apriori algorithm and FP-Growth classification algorithm, the human resource allocation is classified and mined, and the K-Means clustering algorithm is used to realize the dynamic matching of human resource allocation. The experimental results show that the proposed algorithm has better dynamic matching effect of human resources allocation, and can effectively improve the accuracy and efficiency of dynamic matching of human resources allocation.
Vigilant Salp Swarm Algorithm for Feature Selection

Feature selection (FS) averts the consideration of unwanted features which may tend the classification algorithm to classify wrongly. Choosing an optimal feature subset from the given set of features is challenging due to the complex associations present within the features. In non-convex conditions, the gradient-based algorithms suffer due to local optima or saddle points with respect to initial conditions where swarm intelligence algorithms pose a higher chance to converge over the global optima. The Salp Swarm Algorithm (SSA) proposed by Mirjalili et al. is based on the chaining behaviour of sea salps but the algorithm lacks diversity in the exploration stage. Rectifying the exploratory behaviour and testing the algorithm against the FS problem is the motivation behind this work. Three variants of the algorithm are proposed, of which the Vigilant Salp Swarm Algorithm (VSSA) inherits the vigilant mechanism in Grey Wolf Optimizer (GWO), the second variant and the third variant replace a simple crossover operator and shuffle crossover operator instead of the follower's position update mechanism used in the VSSA to form Vanilla Crossover VSSA (VCVSSA) and Shuffle Crossover VSSA (SCVSSA).
Investigating the efficacy of gamification in reducing language anxiety in adults: a case study

The aim of this research is to analyze the level of language anxiety among adult students and evaluate the effectiveness of incorporating gamification elements into the language learning process. The primary objective is to address the pressing need to reduce language anxiety and enhance the overall educational experience for adults studying a foreign language. We employ a multi-phase research approach involving a small group of five participants with diverse educational and cultural backgrounds. These phases yield valuable insights into the nature of language anxiety and the impact of gamification integration on students' attitudes and success. The research findings confirm the prevalence of language anxiety among adult students and underscore the potential of gamification as a successful strategy for reducing it. The introduction of gamification elements fosters a positive educational environment, promoting engagement, the development of camaraderie, and resilience among participants. As a result, students exhibit higher motivation, reduced fear of making mistakes, and a more positive attitude toward the language learning process. Further research can delve deeper into the analysis of specific gamification methods and their long-term consequences, as well as explore the applicability of this approach in various language learning contexts. From a practical perspective, this work has the potential to revolutionize language education by breaking down language anxiety barriers and promoting a more engaging and effective learning experience. Ultimately, the primary contribution of this research lies in demonstrating that gamification can not only reduce language anxiety but also change students' attitudes toward errors and challenges, enriching their language learning journey and providing benefits to both educators and adult students.
Value-motivational component of educator’s digital competence

Currently, there is an active development of digital technologies that affect all spheres of human life. In addition to the need to train personnel for the digital economy, we are faced with the consequences of the covid-19 coronavirus pandemic. All this has become a reason to believe that one of the most important directions of the development of education in Russia is digitalization. In connection with this trend, new requirements are being put forward for educators of all areas, there is a need for the formation of digital competence. Digital competence goes beyond the simple possession of technical skills and includes a deep understanding and effective use of digital tools in teaching practice. It also implies the ability to adapt to an ever-changing digital environment, critically analyze information, solve problems using digital resources, and communicate effectively in virtual and interactive environments. This study is an attempt to systematize and analyze the role and content of the value-motivational component of educator’s digital competence. We conducted an analysis of current scientific research, identified the key criteria for the presence of this component and emphasized its essential importance in the process of formation and development of digital competence. The conclusions and recommendations obtained may be in demand when developing educational programs, trainings and other educational resources aimed at preparing educators for the successful integration of digital technologies into the educational process.
The role of mother tongue in enhancing maritime environment education awareness in Indonesia

In this research, the term “maritime” describes issues related to the relationships and activities between humans and the sea. A country with a major maritime region, like Indonesia, can also be referred to as maritime. This serves as an idea of a starting point for a nation seeking for ways to improve its marine education. However, students find it difficult to understand the material due to the use of foreign language that they don’t understand. In order to increase student knowledge and interest, the researcher offers the use of mother tongue. For this study, researcher conduct qualitative research. 25 students from University Maritim Raja Ali Haji (UMRAH) participate in responding the questionnaire. The data indicates that people strongly agree using their mother language is a good way to raise awareness in the maritime environment. Because, it can facilitate their understanding of the subject during the learning process. Besides, students’ motivation in studying maritime education is also greatly influenced by their mother tongue. When teachers utilize their mother tongue fluently and avoid complicating things, students have an easier time processing the material and their enthusiasm in studying about maritime will also rise.
REALIZATION OF INDIVIDUAL EDUCATIONAL TRAJECTORY AS A FACTOR OF PROFESSIONAL SELF-DETERMINATION OF STUDENTS IN THE SYSTEM OF ADDITIONAL EDUCATION

Successful professional self-determination of students is of high importance, because it allows young people to reveal the scope of their professional interests, needs and values, which in the future gives more opportunities for self-realization and achieving greater satisfaction with their lives. Organizations of additional education have a great potential for designing and implementing individual educational trajectories of students in order to ensure their successful professional self-determination and further choice of ways to obtain professional education. The article reveals some aspects of modeling the technology of implementing individual educational trajectories on the basis of an interactive scientific and technical center focused on improving the efficiency of the process of professional self-determination of high school students and students. In relation to the system of additional education, an individual educational trajectory is an individual learning path that is developed for each student taking into account his needs, abilities, interests and goals. The construction and implementation of an individual educational trajectory is the main way to individualize the educational process, which allows you to receive an education directed on achieving the goals of professional development and comprehensive self-realization of the individual. The model of technology for constructing and implementing an individual educational trajectory in an interactive scientific and technical center developed within the framework of the study is a block-modular system consisting of four blocks: diagnostic, strategic, technological and procedural. The results of a survey conducted among high school students enrolled in the programs of the interactive science and technology center suggest that this technology has a positive impact on the professional self-determination of students.
EDUCATION OF DUTY BY V.A. SUKHOMLINSKY: APPEAL TO THE ESSENCE OF THE CONCEPT

The problem of forming spiritual and moral values, which has become relevant in the last decade, required an appeal to rich experience of domestic pedagogy. In this article, the author explores concept “duty” in the prose of Vasiliy A. Sukhomlinsky. The concept itself was subjected to conceptual analysis, since it has a rather complex and ambiguous semantics. A mandatory moral and ethical component of duty as an inner feeling of a person was established. Contextual analysis was applied to the text of “Education of Duty” in order to clarify the author’s modality. The noun “duty” and its derivatives were analyzed within the context of one predicative structure for each case of use, only free lexical compatibility was taken into account, nouns, adjectives and verbs were included in the context structure. The processing of the results made it possible to establish the comparative frequency of the noun, to highlight the main accompanying meanings expressed by meaningful parts of speech. The author’s lexical valence of the word “duty” in Vasiliy A. Sukhomlinsky does not include a civil or patriotic component. Nuclear positions in the structure of the concept under study are occupied by such meanings and values as human personality, morality, and feeling. The use of non-traditional methods for pedagogical research led to the conclusion that Sukhomlinsky was committed to truly humanitarian values, contrary to the party and class values characteristic of the era.
V.A. SUKHOMLINSKY ABOUT THE AGE FORMATION OF SCHOOLCHILDREN’S VALUE ORIENTATIONS. LOGIC, MECHANISMS, TECHNOLOGIES

The rich pedagogical heritage of V.A. Sukhomlinsky by virtue of its depth and uniqueness makes it possible to identify the axiological constants of pedagogy, relevant at each stage of society development. The purpose of this article is to reveal the logic of formation of value orientations of schoolchildren in the age aspect on the basis of V.A. Sukhomlinsky’s work experience as a teacher and director of Pavlyshskaya secondary school. To achieve this goal, the article addresses the following tasks: an attempt is made to identify those parts of V.A. Sukhomlinsky’s heritage that reflect the regularities of age and value development of schoolchildren; synthesis on their basis of the age logic of the formation of value orientations; filling the values realized in the pedagogical process by V.A. Sukhomlinsky with the content relevant for modern schoolchildren. In V.A. Sukhomlinsky’s pedagogical system it is possible to distinguish a special line of development of a schoolchild’s personality — age-specific features of the formation of his value orientations, which determine the subsequent life of a person: his future choices, successes and failures. The strength of V.A. Sukhomlinsky’s axiological ideas lies in building a system of school work on basic universal values, including the universal triad: Truth — Goodness — Beauty. Having proclaimed and realized first in the experience of his school and then in the pedagogical theory the cult of Book, Knowledge, Beauty, — he actually created a basic classification of values-objectives in pedagogy. According to the authors, this hierarchy of values of an adult can be relevant today, if we fill these values with actual content within the pedagogical process. The changed realities of the first third of the XXI century require the rejection of formal analysis of Sukhomlinsky’s heritage, since extrapolation of the great pedagogue’s ideas to the realities of the modern school in an unchanged form has become impossible. Gamification, neural networks and avalanche-like flow of information, which modern schoolchildren face, require adaptation of the great teacher’s ideas and change of approach to education, departure from value neutrality.