Reviewerly/exHarmony huggingface dataset:
Measuring "Diversity" in Australian Publishing: An Overview and a Proposal

Currently there is no clear and comprehensive way to measure the "diversity" of literature in the Australian public sphere. After outlining and analyzing the current measures in use—such as proxies, industry-wide studies, and activist-led counts—this article proposes the expansion of metadata in order to provide richer data for the publishing industry and researchers into the sector. By improving the use of subject codes, increasing the scope and number of terms used in keywords, and strengthening the use of descriptions and biographies, metadata can serve as an elegant solution to the publishing industry's abiding lack of data. If this is done in an ethically sound way, using examples of data protocols and practices already in existence in Australia (e.g., to uphold Indigenous data sovereignty), publisher-supplied metadata can improve the ability of publishing houses and researchers to move the needle on the range, variety, and volume of voices in Australia's bibliosphere.
A Note on Principia’s *38 on Operations

Principia Mathematica ∗38 introduces what it calls “Relations and Classes Derived from a Double Descriptive Function”. The notion of a relation-e (relation in extension) so derived is called an operation, and of course all dyadic relation-e theorems rely ultimately on the comprehension axiom schema for relations in intension given at ∗ 12.11. But in attempting to give a general pattern of definition, ∗ 38 uses the odd-looking “x♀y” which lends itself to the misconception that ♀ is itself an operation sign. The informal summary makes matters worse, writing “E! (x♀y)” which is ungrammatical. This paper argues that with α, β and μ as relation-e variables and D, E, and P as class variables, operations are comprehended by wffs such as “P = x♀ y”, “μ = α♀β” and “P = R♀S”. Relying on triadic relations-e, I explain how the sign ♀ can be entirely avoided using comprehension. Along the way, puzzling cases such as [inline-graphic 01i] and [inline-graphic 02i] are resolved.
Mathematical modeling of the speed of the process of spreading viral disease COVID-19 in the conditions of megacities

As the main result of this study, a scheme is proposed to describe the process of the spread of COVID-19 disease caused by the SARS-Cov-2 virus through the territory of the city of Moscow. As a hypothesis for the creation of the scheme, an idea is put forward based on the currently proven mechanism of the spread of viruses in the form of aerosols during the breathing of sick people. The proposed mathematical model includes functionals that allow you to control the processes of the decline of the epidemic situation. The developed scheme can be useful for city governing bodies to make decisions on the elimination of the epidemic situation. As suggestions for improving the situation of residents, some factors arising from the analysis of the equations of mathematical models are discussed.
Retracted: Analysis of the Effect of Intensive Care Based on Lean Nursing Intervention

[This retracts the article DOI: 10.1155/2021/7805124.].
Formalizing and Reasoning About Supply Chain Contracts Between Agents

Inspired by the recent problems in supply chains, we propose an approach to declarative modeling of contracts between agents that will eventually support reasoning about resilience of and about ways to improve supply chains. Specifically, we present a high-level language for specifying and reasoning about contracts over action domains of agents. We assume that the behavior of the agents can be formally expressed through action theories and view a contract as a collection of constraints. Each constraint specifies the responsibility of an agent to achieve a certain result by a deadline. Each agent also has a mapping between constraints and the agent’s concerns, i.e. issues that the agent is concerned about, which are modeled in accordance with the CPS Framework proposed by the National Institute of Standards and Technology. We discuss how common questions related to the fulfillment of a contract or the concerns of the agents can be answered and computed via Answer Set Programming.
Using Hybrid Knowledge Bases for Meta-reasoning over OWL 2 QL

Metamodeling refers to scenarios in ontologies in which class-es and roles can be members of classes or occur in roles. This is a desirable modelling feature in several applications, but allowing it without restrictions is problematic for several reasons, mainly because it causes undecidability. Therefore, practical languages either forbid metamodeling explicitly or treat occurrences of classes as instances to be semantically different from other occurrences, thereby not allowing metamodeling semantically. Several extensions have been proposed to provide metamodeling to some extent. This paper focuses on the extension called Metamodeling Semantics (MS) over OWL 2 QL and the Metamodeling Semantic Entailment Regime (MSER). Reasoning over the latter requires more than an OWL 2 QL reasoner, and in the past a solution that transforms MSER to query answering over Datalog has been proposed. In this paper, we investigate the use of Hybrid Knowledge Bases for MSER. Hybrid Knowledge Bases have rule and ontology components, and we provide translations that keep some portion of the original metamodeling ontology in the ontology part. This is accompanied by a translation of SPARQL queries (including metaqueries) to queries over the Hybrid Knowledge Base. The target language is compatible with the hybrid reasoner called HEXLite-owl-api-plugin, allowing for an effective reasoning tool over metamodeling ontologies, which we evaluate experimentally.
UAV Compliance Checking Using Answer Set Programming and Minimal Explanations Towards Compliance (Application Paper)

We describe a continuation of prior work on automated compliance checking process for Unmanned Aerial Vehicles using Answer Set Programming. We describe a new algorithm to perform minimal explanations for offending compliance rules. This explanation is also performed for predicate answer set programs and the paper provides an extension to the algorithm that supported only propositional answer set programs. This improvement increases the expressivity of rules that can be captured in the compliance checking process. We take advantage of the goal-directed execution and constraint-solving capabilities of the s(CASP) engine in order to both compliance check the rules and compute the minimal explanations for violating rules. We further aim to map more rules from the AMA safety code into ASP.
Integrating ASP-Based Incremental Reasoning in the Videogame Development Workflow (Application Paper)

Challenging fields like real-time videogames constitute an ideal, reproducible and controllable ground for researching and experimenting on the new developments of incremental reasoners for Answer Set Programming (ASP). On the other hand, declarative methods show potential in cutting down development costs in commercial videogames: nonetheless, fulfilling the strict time requirements of this type of stream reasoning-like application is still an unsurpassed obstacle. Incremental reasoning techniques might help in overcoming this latter. In this work we report about the integration of an incremental ASP engine in a framework conceived for adding declarative decision-making modules in the typical videogame development workflow. Namely, the two systems are Incremental-DLV2, a recently introduced multi-shot incremental solver based on the ASP semantics, and ThinkEngine, a tool for developing declarative modules working in the context of the Unity game engine. After describing the features of both systems, we give an example showing how to program a declarative-based videogame character. We discuss how we adapted the architecture of ThinkEngine for accommodating incremental reasoning, and report about experiments showing the impact in performance after the introduction of Incremental-DLV2.
Modern Approaches to Teaching and Assessment of Higher Education Seekers: A Conceptual Vision

The purpose of the academic paper lies in analysing the viewpoints of various scientists regarding the selection and features of the application of modern approaches to the organization of the educational process, teaching and assessment of the effectiveness of the educational activities of higher education seekers, as well as in practical investigating the main aspects of assessment and educational practice in higher education. In the process of conducting the research, an analytical and bibliographic method has been used in order to study the scientific literature on learning, teaching and assessment issues, as well as a questionnaire survey for the practical clarification of certain aspects of the evaluation and educational process in higher education. Based on the results of the research, the existing works of scholars on the use of modern approaches to the organization of educational activities in higher education and the latest trends in the assessment of the educational process have been analysed.
Key Performance Indicators (KPIs) as a Part of the Staff Performance Management at the University: A Case of Medical University

The main purpose of this research is to conduct the theoretical and applied study of KPIs as an evaluation tool of universities’ activity; to identify the issues of special organizational requirements for its use. In this study such basic methods as analysis, synthesis and comparison are used. Medical university and its staff are an object of the research. The article using the case of the medical university describes the Key Performance Indicators of the university, its principles and practices of application, provides a justification of the optimality of the selected system for the evaluation and development of the university’s staff and its efficiency to achieve the university’s strategic goals. KPIs are adapted in accordance with the requirements of the modern higher education and takes into account the main goals of the strategic plan of the university’s development. The article describes in detail the principles of KPIs construction, based on the decomposition of the strategic goals.
Using Fuzzy Influence Diagrams to Assess the Risk of Smart Grid Enterprise Architecture

The concept of smart grids affects both the topology of the grid and the IT infrastructure, leading to various heterogeneous systems, data models, protocols, and interfaces on different enterprise architecture levels.
Development of productivity of subjects of education by means &#x0D; of psychological training

The relevance of the research is justified by the fact that modernity requires an increase in the productivity of graduates of higher educational institutions in independently formulating and solving professional tasks, increasing the requirements for their quality and the products they create. A special area is teaching the culture of communication, speech (oral, written), the culture of establishing professionally appropriate relationships between the subjects of education, ensuring their productive formation. One of the signs of productivity is the creation of innovative educational technologies. The purpose of the study is to develop a justification and approbation of a system of psychological and pedagogical methods to identify indicators of the productivity of the subjects of education, their development in the professional, educational and scientific environment of the university. The hypothesis that psychological training of personal growth and productive interaction of educational subjects develops activity in communication, confidence, emotional stability, and internal locus control has been confirmed. Sample: 3440 people, including 290 teachers of higher education and 3150 students of psychological and pedagogical, economic, information technology, service, technical, agricultural specialties, as well as specialties in physical culture and sports (1860 years) for the period 20012022. To identify indicators of productivity of subjects of education, the following methods were used: a questionnaire to determine the communicative potential (R.A. Maksimova); express diagnostics of SAN (V.A. Doskina, N.A. Lavrentieva, V.B. Sharai, M.P. Miroshnikov); a test questionnaire of the level of subjective control (E.F. Bazhin, E.A. Golinkina, A.M. Etkind). Results: the differences in indicators of communicative properties and features of subjective locus control in the control and experimental groups prove the effectiveness of the psychological training program developed by us. Conclusions: it is determined that the creation of innovative educational technologies play an important role in the intensification of personal growth and productive interaction of subjects of education by means of psychological training
Pedagogical skill as a level of professional competence

The article describes philosophic reasons of origin of pedagogical skill as level of pedagogue`s professional competence. Since Ancient Greece time, when philosophers and thinkers got interest of art nature of human, problem of skill has been an important pedagogical question which defined by interpretation: is skill art or craft, theoretical knowledge or experience conclusion of practice? The resolution of the conflict between the understanding of pedagogical mastery as an art based on theoretical knowledge and practical activity, as a manifestation of a craft, revealed the need to determine the essence of pedagogical mastery as the main criterion of a teachers professional competence, as well as the level of his professional skills and abilities. The article analyzes the ancient ideas of ancient Greek philosophers about mastery, among which the arguments about art in the works of such famous thinkers of Ancient Greece as Aristotle and Plato are of greatest interest. Discussing mastery, technical and creative work, Aristotle introduced a concept that most accurately reflects legal art and which later became the basis for the emergence of pedagogical mastery techne. Later, already in the works of philosophers and the first teachers, together with the development of pedagogy as a separate branch of knowledge, pedagogical mastery became one of the main subjects for the thinking of prominent thinkers of the New Age. The results of the study testify to the necessity of understanding the pedagogical mastery, the formation of which is possible based on the scientific and practical training of the teacher. The obtained conclusions are the basis for further studies of pedagogical mastery and open a wider field for discussion of the question of what is primary for the formation of pedagogical mastery theory or practice
System of formation of project culture among the future state &#x0D; and municipal administration managers

The global challenges that the Russian society is facing nowadays, including the ones caused by external sanction pressure, necessitate the state and municipal administration managers to solve a number of problems, aimed at grading the named challenges; as project-making if often the key tool for solving these kind of problems, it underlies the importance of project culture building among the future state and municipal administration managers. In the article the structure of the project culture building system for the state and municipal administration managers is compared with the structure of the pedagogical system, where the latter is analyzed using the systematic pedagogical approach to single out the target, the contents, the tools and the framework components. The framework of the project culture building system for the state and municipal administration managers includes the following steps: introduction, formation, resulting. Within each of these steps the necessary courses and their contents were created. Project culture building for the state and municipal administration managers requires proactive educational methods. Systems approach, individual and activity approach, cultural approach were highlighted as key methodological basis for project culture building for the state and municipal administration managers. The work addresses the interdisciplinary and transdisciplinary approaches and studies their role in building project culture for the state and municipal administration managers. Interdisciplinary cohesion (academic and mentally intermediate cohesion) facilitated succession and consistency in studies, due to which the knowledge in one subject could be implemented in a different sphere. Transdisciplinary approach enables the educators to build long cohesion links addressing various subjects and practical aspects, which promotes project culture building for the state and municipal administration managers
Machine Learning for Arabic Text Classification: A Comparative Study

The ultimate aim of Machine Learning (ML) is to make machine acts like a human. In particular, ML algorithms are widely used to classify texts. Text classification is the process of classifying texts into a predefined set of categories based on the texts’ content. It contributes to improving information retrieval on the Web. In this paper, we focus on the "Arabic" text classification since there is a large community in the world that uses this language. The Arabic text classification process consists of three main steps: preprocessing, feature extraction and ML algorithm. This paper presents a comparative empirical study to see which combination (feature extraction - ML algorithm) acts well when dealing with Arabic documents. So, we implemented one hundred sixty classifiers by combining 5 feature extraction techniques and 32 machine learning algorithms. Then, we made these classifiers open access for the benefit of the AI and NLP communities. Experiments were carried out using a huge open dataset. The comparison study reveals that TFIDF-Perceptron is the best performing combination of a classifier.
A Customizable No-Code Realistic Motion Editor for VRM-Based Avatars

Avatar actions can be captured using certain gesture sensors or can be predefined by game designers through desktop applications. In other words, developing an online avatar editor could be necessary to specify the detailed actions for use by people who are not game creators. Our research team proposed a web-based toolset, myKLA, to construct and design avatar actions with editor and player features. The goal of myKLA is to help users define the required behaviors of avatars within a set time frame without codes. We used cyber–physical system theory in a software reconstruction initiative. Additionally, an exchangeable JSON file format for predefining the avatar actions was opened and shared here. Furthermore, the cyclomatic complexity of the main code blocks in our toolset was measured and changed using the McCabe approach to fine-tune the performance. An algorithm was proposed for quickly calculating an integrated activity diagram from several sub-activity diagrams. Our research showed that it is easy to create an avatar head and embed it in other web-based applications for additional interaction utilization. Therefore, our findings will be useful in creating and designing new educational tools.
LILP: A Lightweight Enciphering Algorithm to Encrypt Arbitrary-Length Messages

The advancement of the Internet of Things (IoT) has promoted the development of embedded devices. It is important to ensure data transmission security on embedded devices with limited computing power and storage space. However, the traditional block encryption algorithm cannot run efficiently on embedded devices because of the large amount of computation. In this paper, a lightweight length-preserving-encryption algorithm (LILP) is proposed to convert an n-bit block cipher into a special block cipher that supports an arbitrary length of no less than 2n bits as input. LILP adopts the involution design method based on a Lai–Massey structure and lightweight components to adapt to the limited computing power of embedded devices. In particular, a lightweight compression function (LCF) is designed to process the data during iteration, which improves security without reducing the efficiency of the algorithm. The experimental results show that LILP is more efficient than traditional similar algorithms in encrypting data for resource-constrained devices while ensuring data security in the IoT.
Gradient-Based Automatic Exposure Control for Digital Image Correlation

Digital image correlation (DIC) is widely used in material experiments such as ores; the quality of a speckle image directly affects the accuracy of the DIC calculation. This study aims to acquire high-quality speckle pattern images and improve the calculation accuracy and stability. A gradient-based image quality metric was selected to evaluate the image quality, and its validity was verified by a rigid body experiment and a numerical experiment. Based on the maximum image quality metric, an automatic exposure control algorithm and the control procedure were proposed to obtain the optimal exposure time. Finally, nine sets of images with different poses and illuminations were captured, and displacement and strain fields were calculated at the fixed exposure time and the optimized exposure time. The results of the rigid-body motion experiment show that the calculated data at the optimized exposure time is smoother and less noisy, and the error is smaller, which verifies the effectiveness of the exposure control procedure and its algorithm and improves the accuracy and stability of DIC calculation.
Enhanced Hierarchical Prediction for Lossless Medical Image Compression in the Field of Telemedicine Application

Color images play a vital role in today’s multimedia formats. Due to hierarchical prediction, we can utilize the limited storage for the bulky medicinal representations along with maintaining a satisfactory visual form of medical images for analysis. In this proposed method, brightness component (Y) is encoded using the conventional encoding and gray scale compression algorithm, while chrominance components are processed further using the proposed Modified Hierarchical Prediction and Context Adaptive (MHPCA) algorithm. We have suggested two algorithms of MHPCA for high frequency regions which improve coding efficiency and temporal scalability. These proposed algorithms beat the problem of massive estimation inaccuracy near the boundaries as well as maintain the precision of the pictures. As per the trials and investigation outcomes, there is refinement in PSNR while reducing BPP. We have also demonstrated compression efficiency by compression ratio as a measurement parameter
Applications of Artificial Intelligence in Medical Images Analysis

There are several imaging modalities used for obtaining the images of the internal parts of the human body. Some modalities such as angiography require invasive procedure to obtain images using contrast agent for clear visualization of the tissue of interest. The images obtained using different modalities are highly unstructured, which makes it difficult for inexperienced medical practitioner to derive the value of the unstructured data. Consequently, the use of artificial intelligence (AI) in medical imaging research has tremendously increased over the past few years for deriving the value out of data of interest. However, the obtained images must be processed before performing deep learning based analysis, since the images may contain noise or may be of poor quality due to capturing devices or technicians. In addition, several image augmentation methods can also be applied to prepare the augmented data. The AI serves for several purposes such as classification of patients into normal and abnormal categories, detection of lesions in the image or segmentation of detected lesion. The use of AI has shown promising results in the field of radiology, where the disease can be diagnosed and assessed accurately for efficient decision making and planning of the treatment procedures.