Reviewerly/exHarmony huggingface dataset:
An Ontological Analysis and Redesign of the D3FEND Cybersecurity Model

Formal Ontology is a discipline whose business is to develop formal theories about general aspects of reality such as identity, dependence, parthood, truthmaking, causality, etc. A foundational ontology is a specific consistent set of these ontological theories that support activities such as domain analysis, conceptual clarification, and meaning negotiation. A (well-founded) core ontology specifies, under a foundational ontology, the central concepts and relations of a given domain. Foundational and core ontologies can be seen as ontology engineering frameworks to systematically address the laborious task of building large (more specific) domain ontologies. However, both in research and industry, it is common that ontologies as computational artifacts are built without the aid of any framework of this kind, often yielding modeling mistakes and representation gaps. In this paper, we analyze a case in the domain of cybersecurity, namely, the case of D3FEND - an OWL knowledge graph of cybersecurity countermeasure techniques proposed by the MITRE Corporation. Based on the Reference Ontology for Security Engineering (ROSE), a core ontology of the security domain founded in the Unified Foundational Ontology (UFO), our investigation reveals a number of semantic issues and opportunities for improvement in D3FEND, including missing concepts, semantic overload of terms, and lacking constraints that cause an under-specification of the model. As a result of our ontological analysis, we propose several suggestions for the appropriate redesign of D3FEND to overcome those issues.
TaBIIC: Taxonomy Building Through Iterative and Interactive Clustering

Building taxonomies is often a significant part of building an ontology, and many attempts have been made to automate the creation of such taxonomies from relevant data. The idea in such approaches is either that relevant definitions of the intension of concepts can be extracted as patterns in the data (e.g. in formal concept analysis) or that their extension can be built from grouping data objects based on similarity (clustering). In both cases, the process leads to an automatically constructed structure, which can either be too coarse and lacking in definition, or too fined-grained and detailed, therefore requiring to be refined into the desired taxonomy. In this paper, we explore a method that takes inspiration from both approaches in an iterative and interactive process, so that refinement and definition of the concepts in the taxonomy occur at the time of identifying those concepts in the data. We show that this method is applicable on a variety of data sources and leads to taxonomies that can be more directly integrated into ontologies.
Digital Contact Tracing for Pandemic Response: The Roles of Cultural Worldviews and Technology Awareness

Information technologies have been developed and used by government agencies and public authorities to address societal issues, but their effectiveness often hinges on public support and participation. This is evidenced in the use of digital contact tracing (DCT) technology to contain the spread of the coronavirus. Despite the efforts of public authorities and technology firms to develop and promote DCT, its adoption in the United States had been low and uneven. This research resolves the puzzle by showing that the public’s mixed views on DCT are caused by their cultural worldviews, which represent their values and attitudes toward collective responsibility in addressing personal needs as well as social hierarchies and established norms in regulating behaviors. These worldviews influence not only their perceptions of the risks and benefits of the technology but also how they interpret information about the technology. Being more aware of the technology may contribute to, rather than correct, the biases resulting from individuals’ prominent cultural worldviews. This research has practical implications for policymakers and technology developers, highlighting the importance of considering cultural worldviews in communication strategies and technology design. It offers a unique perspective on the interplay between worldviews, technology, and public perception, providing valuable insights for navigating the complex landscape of emerging technologies addressing diverse societal issues.
Modern Ukrainian Theatre in the Dimension of Internet Culture

The purpose of the article is to reveal the peculiarities of the functioning of the Ukrainian theatre of the second – beginning of the third decade of the 21st century in the dimension of Internet culture. Research methodology. The principle of scientific objectivity, analytical, cultural, systemic, typological, and structural-functional method was applied to generalise the theoretical and methodological foundations of the study of Internet culture, to identify the peculiarities of the functioning of modern Ukrainian theatre in the cultural environment of the Internet. Scientific novelty. The trends of the development of modern theatre culture were studied through the prism of the specifics of the Internet space. The cultural environment of the Internet was considered as an important factor in the functioning of theatrical culture in the modern digital society. The peculiarities of the representation of modern Ukrainian theatre in the Internet space were revealed using the example of interactive sites and virtual tours. The concept of "Internet culture" was clarified. Conclusions. Internet culture forms a high level of general human culture due to the property of representing modern progressive cultural practices; oriented on the principles interconnected with modern culture (montageability, clipability); characterised by dynamism, interactivity, variability, a special ratio of heterogeneity and unity. The Internet space represents a new dimension of interaction between the theatre and the audience, the discovery of new ways of creating and presenting theatre, as well as new forms of interaction between the actor and the audience in these theatrical contexts. It acts as a part of cultural communication, in which multimedia technologies allow creating a new type of communication, and the Internet is a channel for broadcasting. The consequence of this is the formation of theatrical content as a specific sphere of the Internet environment. The nature of these changes is a promising subject of further scientific reflection. At the current stage, the Internet space and its cultural environment lead to the emergence of innovative ways to satisfy the informational needs of potential theatre viewers, provide forms of presentation of Ukrainian theatre and opportunities for interactive engagement that are relevant for the modern digital society.&#x0D; Keywords: Internet culture, Internet, theatre culture, digital society, Ukrainian theatre, official sites, virtual tours.
Various Approaches of Convolutional Neural Network-Based Recognition of Handwritten Devanagari Characters

In the past, handwriting recognition systems based on handmade qualities and a great deal of historical data. An OCR system that depends on these specifications is challenging to train the HR research that has produced ground-breaking results recently is centered on deep learning techniques. However, the rapid expansion in the volume of written data and the accessibility of massive computing resources call for an improvement in detection performance and call for further research. The most effective approach to solve the handwriting identification problem challenges is to use CNNs, which are particularly adept to address the issue of handwriting recognition automated extraction of distinctive traits. The goal of the proposed study is to investigate different design choices for handwritten digit recognition using CNN, such as the quantity of layers, phase size, facility available, kernel size, padding and dispersion. Our objective is to achieve comparable accuracy using a pure CNN architecture. As a result, a CNN design is suggested to attain accuracy that is even greater than ensemble systems while also reducing operational complexities and expense.
Digital Financial Asset Management Using Blockchain for Succession Planning of Wealth

This paper surveys and implements the application of blockchain and related technology in digital financial asset management and succession planning of wealth. Digital financial assets, such as cryptocurrencies, NFTs, and digital real estate, have become increasingly popular in recent years, but their management and distribution after the death of the owner can be a difficult and complex process. Having conducted systematic research into the area of blockchain and its various use cases, we determined how it affects wealth creation, planning, management, succession planning, and portfolio performance. Blockchain, with its decentralized and immutable nature, provides a solution to this problem by enabling the creation of smart contracts and digital wills that can be programmed to automatically transfer ownership of digital assets to designated beneficiaries upon the death of the owner. This paper examines the current challenges in tracking and transferring ownership of digital assets after the death of the owner, and how this technology could be used to impact and improvise the succession planning of wealth for digital assets. The paper also explores the potential benefits and limitations of using blockchain for this purpose, as well as potential future developments in this field.
Knowledge Inference Over Web 3.0 for Intelligent Fault Diagnosis in Industrial Internet of Things

Collaboration through knowledge sharing is critical for the success of intelligent fault diagnosis in a complex Industrial Internet of Things (IIoT) system that comprises various interconnected subsystems. However, since the subsystems of an IIoT system may be owned and operated by different stakeholders, sharing fault diagnosis knowledge while preserving data security and privacy is challenging. While decentralized data exchange has been proposed for cyber-physical systems and digital twins based on the Web 3.0 paradigm, decentralized knowledge sharing in knowledge-based intelligent fault diagnosis is less investigated. To address this research gap, we propose a Web 3.0 application for collaborative knowledge-based intelligent fault diagnosis using blockchain-empowered decentralized knowledge inference (BDKI). Our proposed mechanism enables workers to self-evaluate their ability to contribute to the knowledge inference with their local knowledge graphs. The knowledge-sharing requestor can then choose a worker with the best evaluation result and initiate collaborative training. To demonstrate the efficiency and effectiveness of BDKI, we evaluate it using well-known datasets. Results show that BDKI delivers a favorable inference model with higher overall accuracy and less training effort compared to inference models trained using conventional knowledge inference with random training sequences.
Source-Free Active Domain Adaptation via Augmentation-Based Sample Query and Progressive Model Adaptation

Active domain adaptation (ADA), which enormously improves the performance of unsupervised domain adaptation (UDA) at the expense of annotating limited target data, has attracted a surge of interest. However, in real-world applications, the source data in conventional ADA are not always accessible due to data privacy and security issues. To alleviate this dilemma, we introduce a more practical and challenging setting, dubbed as source-free ADA (SFADA), where one can select a small quota of target samples for label query to assist the model learning, but labeled source data are unavailable. Therefore, how to query the most informative target samples and mitigate the domain gap without the aid of source data are two key challenges in SFADA. To address SFADA, we propose a unified method SQAdapt via augmentation-based Sample Query and progressive model Adaptation. In specific, an active selection module (ASM) is built for target label query, which exploits data augmentation to select the most informative target samples with high predictive sensitivity and uncertainty. Then, we further introduce a classifier adaptation module (CAM) to leverage both the labeled and unlabeled target data for progressively calibrating the classifier weights. Meanwhile, the source-like target samples with low selection scores are taken as source surrogates to realize the distribution alignment in the source-free scenario by the proposed distribution alignment module (DAM). Moreover, as a general active label query method, SQAdapt can be easily integrated into other source-free UDA (SFUDA) methods, and improve their performance. Comprehensive experiments on multiple benchmarks have shown that SQAdapt can achieve superior performance and even surpass most of the ADA methods.
Peningkatan Aktivitas Dan Hasil Belajar Tematik Dengan Menggunakan Strategi Synergetic Teaching Pada Siswa Kelas IV B SD Negeri 60 Kota Bengkulu

Abstract&#x0D; &#x0D; This research is motivated by several problems that occur in the learning activities of Elementary School of 60 Bengkulu City, so that the activities and learning outcomes obtained by students have not reached the KKM that has been set . Based on observations, it is known that the passive activity of students in following the learning process and the lack of variation of teachers in using methods affect the low learning outcomes and learning activities of students. The purpose of this study is to find out the increase in activity and learning outcomes of fourth grade students B SD N 60 Bengkulu City in learning theme 9 sub-theme 1 by using Synergetic Teaching Strategy. This research . included in the Classroom Action Research (CAR) which was carried out in two cycles. The results of this study indicate the average of the assessment of teacher activity observations in cycle 1, namely . 10 with the category Enough ( Range 7-10 ) . Furthermore, the results of observations in cycle II from the results of observer 1 obtained a value of 18 while the value of observer 2 obtained a value of 17. The average of the assessment of teacher activity observations in cycle 1 is . 17.5 with category Very Good ( Range 15-18 ) . Furthermore, in the assessment of learning outcomes in cycle 1. the assessment of learning outcomes in Civics subjects showed the lowest score of 60. Meanwhile, the highest score was 75. Then those who scored less than 70. as many as 12 students ( 57.14% ) . Meanwhile, for the range of values from 71-80, the number of students was the same, namely 4 students (19.04%). In cycle II . assessment of learning outcomes. in the Indonesian language subject, the lowest score was 70, while the highest score was 90. The number of students who scored less than 81 100 were 14 students (66.66%), then those for the 71-80 score range received the same number, namely 3 students (14.29 % ) , and students who scored 61-70 were 4 students ( 19.05 % ) . Thus it can be concluded that there is an increase in students' thematic learning outcomes using the Synergetic Teaching strategy for grade IV B students at SD Negeri 60 Bengkulu City. &#x0D; Keyword : Thematic Activities, Learning Outcomes, The Synercetic Teaching Strategy.
Conflict Management Types of Local Education Administration Officials and The Mediating Effect of Communication Skills in the Relationship between Job Satisfaction

Objectives The purpose of this study is to find an effective conflict management method and lead a successful professional life by increasing job satisfaction by verifying the mediating effect of communication ability in the re-lationship between conflict management type and job satisfaction of local education administrative officials.&#x0D; Methods To this end, a survey was conducted using the conflict management type scale, communication ability scale, and job satisfaction scale, targeting 404 grade 5 local education administration officials in 2023, and re-gression analysis was conducted using the SPSS WIN 23.0 program and the SPSS Macro.&#x0D; Results Research results are as follows. First, the conflict management type of local education administration of-ficials had a significant effect on communication ability. Second, the type of conflict management of local educa-tion administration officials had an effect on job satisfaction. Third, among the conflict management types of local education administrative officials, the cooperation, avoidance, and compromise types had a partial mediating ef-fect in which communication ability had a direct effect on job satisfaction, while the competition type had a com-plete mediating effect with only an indirect effect. However, in the dependent type, communication skills did not mediate job satisfaction.&#x0D; Conclusions These results require efforts to convert the conflict management type into a cooperative and com-promise type that seeks to obtain the best interests of both sides of the conflict situation through efficient com-munication skills and to resolve it rationally. This suggests the need for customized education that provides pro-grams that can enhance communication skills according to the conflict management type of the students.
A TECHNOLOGY SUPPORTED FALL PREVENTION INTERVENTION FOR OLDER ADULTS WITH MILD COGNITIVE IMPAIRMENT

Abstract Falls and fall-related injuries are significant public health issues for adults 65 years of age and older. Over a third of older adults (OA) fall each year and 10-20% of falls result in serious injuries. Cognitive impairment has been identified as a leading risk factor with over 60% of OA living with mild cognitive impairment (MCI) falling annually. Housing conditions are also a risk factor for falls. We have developed Sense4Safety, a technology-enhanced intervention that includes multiple components: 1) in-home assessment and action; 2) education and regular communication with a coach; 3) passive monitoring facilitated by depth sensors in the home; and 4) alerts. The goal of this study was to access the feasibility of Sense4Safety and its acceptability. We recruited 10 low-income OA with MCI; each participant received the intervention for 3 months. All participants completed all study procedures. The Short Physical Performance Battery (SPPB) scores which provide an objective assessment of lower extremity functioning based on clinical experts’ observation showed high correlation to the sensor system assessment (r=0.94, p&amp;lt; 0.01). Two fall alerts were generated during the study period that triggered a timely response. Participants and their family members found the intervention to provide peace of mind and empower OA to proactively address changes in fall risk through exercise and home modifications. The combination of passive sensing and personalized coaching offers an innovative ecological approach to continuously assess functional mobility and gait in the home and captures changes that provide an early warning for fall risk.
Penerapan Model PjBL Berbantuan Media Pembelajaran untuk Meningkatkan kreativitas dan Kerjasama Peserta Didik Kelas V SDN 171 Rejang Lebong

AbstractThis study aims to describe the application of the PjBL model assisted by instructional media, to increase the cooperation and activity of the fifth-grade students of elementary school 171 Rejang Lebong. This research is Classroom Action Research. The subjects in this study were 21 students with 9 boys and 12 girls. The research instrument used in this study was the Observation Sheet. The data analysis technique used is the Observation Sheet using formulas and ranges to determine each category. The results of this study indicate that the PjBL model assisted by learning media increases in cycle I to cycle II. So it can be seen from the increase in creativity in the first cycle 44.34% with a sufficient category, then the increase in the results of the observation of the second cycle was 72.61% in the good category. Meanwhile, the results of the observation of cooperation showed that the results in the first cycle were 48.40%, including in the sufficient category. Then it increased in the second cycle, namely 67.71%, which was included in the good category. Based on this result, the application of the PjBL model assisted by learning media can increase the creativity and cooperation of class V students of SDN 171 Rejang Lebong.Keywords: PjBL Model, Learning Media, Creativity, Cooperation.
Determinants of Profession Choice in Students’ Educational Strategies in the Context of the Reproduction of Human Capital

Introduction. The relevance of the study is determined by the necessity to optimize the process of reproduction and building up the human capital of the Russian Federation, where the primary place belongs to education. The article discusses the educational strategies of Russian students in the current conditions of transition to the sixth technological mode, when the formation of a learning society and knowledge economy is of particular importance, which requires additional investment in human capital and educational capital in particular. The purpose of the study is to describe the educational strategies of Moscow students as dynamic systems of perspective orientation of an individual, as well as constructing their future life in accordance with a certain plan. Materials and Methods. The empirical basis of the article constitute the findings of the online sociological survey “Students of Russia: civic culture and life strategiesˮ, conducted in April‒May 2022 with an additional representation of the array in Moscow. Having carried out an exploratory factor analysis by the method of principal components and rotation by the Varimax method, the authors identify factors that allow interpreting various educational strategies for choosing a direction of study by students. Results. Comparing the social practices of students in Moscow with those in the regions, identifying the dominant factors in choosing a speciality/academic specialism, the authors identify speciality choice indices that are determined by different factors and lead to studentsʼ adherence to different types of educational strategies: “rationalˮ strategy, “inner circle of trustˮ strategy and “random choiceˮ. Discussion and Conclusion. The study conducted by the authors made it possible to formulate a number of significant conclusions that make a significant contribution to understanding the structure of the social capital of today's youth. The development of the educational capital of the younger generation is an important task in the process of ensuring the development of the entire Russian society as a whole.
Deep Learning Approaches for Affective Computing in Text

The field of natural language processing (NLP) is one of the first to be addressed since artificial intelligence emerged. NLP has made remarkable advances in recent years thanks to the development of new machine learning techniques, particularly novel deep learning methods such as LSTM networks and transformers. This chapter presents an overview of how deep learning techniques have been applied to NLP in the area of affective computing. The chapter examines traditional and novel deep learning architectures developed for natural language processing (NLP) tasks. These architectures comprise recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and the cutting-edge transformers. Moreover, a methodology for NLP method training and fine-tuning is presented. The chapter also integrates Python code that demonstrates two NLP case studies specializing in the educational domain for text classification and sentiment analysis. In both cases, the transformer-based machine learning model (BERT) produced the best results.