Reviewerly/exHarmony huggingface dataset:
GenAD: General unsupervised anomaly detection using multivariate time series for large‐scale wireless base stations

The reliability of wireless base stations is essential to guarantee the user experiences in wireless networks, thereby employing the anomaly detection on multivariate time series is indispensable for network operators to monitor the behaviours of large-scale wireless base stations. In this paper, a general unsupervised anomaly detection model is proposed using multivariate time series for large-scale wireless base stations, called GenAD. Firstly, multi-correlation attention and time-series attention are employed to learn the representations of the complex correlations and various temporal patterns of multivariate series. Secondly, a general model on large-scale wireless base stations is pre-trained with self-supervision, which can be easily transferred to a specific station with a small amount of training data. Experimentals show that GenAD boosts F1-score by total 9% on real-world datasets.
Digital Pathology

Digital pathology includes data acquisition, sharing and interpretation on the basis of digital images. Presently the entire slide is available on the computer as “whole slide imaging” with the help of whole slide scanning. In this whole slide imaging, a complete digital slide is generated and the observer can examine any part of the slide by increasing or decreasing the magnification. Digital pathology helps in the teaching, remote consultation, primary diagnosis, and quantitative assessment of the areas of interest. The main limitations of digital pathology are its cost, laboratory set up and storage space of the digital slides. The present chapter discusses the details of digital pathology and whole slide imaging.
Algorithmically Navigating Complex Tabular Structures in Images for Information Extraction

Computer vision has been in the forefront of automating workflows to replace manual repetitive tasks with convenience and accuracy. Recognizing text from images of commercial documents through optical character recognition (OCR) form the initial step of most such workflows where majority of their information are in the form of complex data structures such as tables and nested tables. Although OCR technology has evolved to effectively capture text from images, there is still room for improvement in recognizing complex data structures and extracting tabular data from images. This paper proposes an algorithmic approach based on keyword detection and the position of words relative to each other in order to recognize nested structures and successfully extract tabular data into a program and human readable format, which aims to take a different approach as opposed to using machine learning models or pre-defined templates for layout recognition. Furthermore, this approach is shown to yield successful results in correctly comprehending the layout and data of nested table structures in multiple rows in a table.
Creation of Parallel Medical and Social Domains Corpora for the Machine Translation and Speech Synthesis Systems

This paper represents the procedure of creating medical and social domains corpora in NooJ. It illustrates a primary analysis of the corpora. Based on the research, the Belarusian NooJ module has been supplemented and thematic dictionaries of medical and social areas in NooJ format have been prepared. Automatic text processing emphasized words’ linguistic peculiarities (mainly morphological) that the main module of Belarusian language for NooJ did not recognize. In addition, the article shows how the corpora help to improve the quality of translation, to identify heterogeneous translation options.
The Normal-Normal (NN) Distribution

The normal-normal (NN) distributionNormalnormal-normal (NN) distributions is not a subfamily of the pseudo-normal (PN), but an approximation to a distributionNormaldiscrete normal distribution in the PN using the discrete normal distribution in place of the usual normal underTruncationsectional sectional truncationSectional truncation. Though the discrete normal distributionNormaldistribution takes normal densities at finite/infinite points approximating the truncated normalTruncated normal, the discrete distribution is not necessarily a truncated one. Their moment generating functionMoment generating function (MGF) and representations by mixture, convolutionConvolution and regressionRegression are given.
Graph Convolution Networks for Unsupervised Learning

In recent years, graph convolution networks (GCN) have been proposed as semi-supervised learning approaches. In this paper, we introduce a new objective function to train a GCN in order to adapt it in unsupervised learning context. More precisely, we propose a loss function composed only of unsupervised terms, the first term is the kernel k-means objective function used to capture the shared features information between nodes, and the second is a regularization term that imposes the smoothness of the predicted clusters of the whole data. Thanks to the proposed objective function, we are able to keep the advantages of the classical semi-supervised GCN, while using it in an unsupervised way. Experiments on benchmark datasets show that our proposed unsupervised GCN achieves superior performance compared to state-of-the-art clustering algorithms.
Multi-level and Multi-modal Feature Fusion for Accurate 3D Object Detection in Connected and Automated Vehicles

Aiming at highly accurate object detection for connected and automated vehicles (CAVs), this paper presents a Deep Neural Network based 3D object detection model that leverages a three-stage feature extractor by developing a novel LIDAR-Camera fusion scheme. The proposed feature extractor extracts high-level features from two input sensory modalities and recovers the important features discarded during the convolutional process. The novel fusion scheme effectively fuses features across sensory modalities and convolutional layers to find the best representative global features. The fused features are shared by a two-stage network: the region proposal network (RPN) and the detection head (DH). The RPN generates high-recall proposals, and the DH produces final detection results. The experimental results show the proposed model outperforms more recent research on the KITTI 2D and 3D detection benchmark, particularly for distant and highly occluded instances.
A Double Adaptive Random Spare Reinforced Sine Cosine Algorithm

Many complex optimization problems in the real world can easily fall into local optimality and fail to find the optimal solution, so more new techniques and methods are needed to solve such challenges. Metaheuristic algorithms have received a lot of attention in recent years because of their efficient performance and simple structure. Sine Cosine Algorithm (SCA) is a recent Metaheuristic algorithm that is based on two trigonometric functions Sine & Cosine. However, like all other metaheuristic algorithms, SCA has a slow convergence and may fail in sub-optimal regions. In this study, an enhanced version of SCA named RDSCA is suggested that depends on two techniques: random spare/replacement and double adaptive weight. The first technique is employed in SCA to speed the convergence whereas the second method is used to enhance exploratory searching capabilities. To evaluate RDSCA, 30 functions from CEC 2017 and 4 real-world engineering problems are used. Moreover, a nonparametric test called Wilcoxon signed-rank is carried out at 5% level to evaluate the significance of the obtained results between RDSCA and the other 5 variants of SCA. The results show that RDSCA has competitive results with other metaheuristics algorithms.
Methodology of training of potential teachers of musical art (on the example of the materials of the virtual tour «Hryhoriy Skovoroda – an artist, philosopher, and educator»)

The chosen topic becomes especially relevant in terms of military situation in Ukraine, since some of the sights presented in the photos by the authors in the content of the virtual tour retain their original appearance, which may differ from today. The purpose of the article is to substantiate the practical value of a virtual excursion as an effective methodological aid for teaching the school subjects of the art education during pedagogical practice by potential music teachers in the process of providing distance and mixed forms of education.&#x0D; To select practical material, the authors use bibliographic, historical, systematic, concentric, and problem methods. The content structuring of the virtual excursion dedicated to the figure of H. Skovoroda is an example of a creative project for online work with students online made by the students of the specialty 014 Secondary Education (Musical Art), who will be able to implement it in the professionally oriented disciplines. It includes interesting tasks for high school students’ work upon the compositions of a famous poet, musician, and educator, organized in pair, group and individual forms.&#x0D; The didactic material of the virtual tour was filled based on a systematic analysis of the artist's creative heritage using reproductive and productive methods of high school students’ teaching.&#x0D; The authors took into account the algorithms for developing such a form of work with students as: a plan, choosing places for virtual stops, preparing questions and tasks for discussion and completing them independently or in groups. The online format makes it possible to combine various types of artistic activity of students, helps them find and process the artistic thesaurus faster: where, by whom, under what circumstances was the monument created, whether it was preserved intact, restored, or fully restored; what is the historical and artistic value of the monument.&#x0D; The presentation of the material enables to find answers to the questions raised by the authors during the journey through the virtual steps of the tour, to receive feedback between future teachers and students during the processing of the stops, which become a sort of didactic compass for the analysis of the texts of the musical and poetic heritage of Hryhoriy Skovoroda, the Kharkiv region role in the life and creativity of the world-famous philosopher and educator.
Utilizing Mobile Technology to Improve Writing Skill

Technology has improved rapidly, and new communication technologies emerge every day. Those technologies can be used in the educational field, including language education. Throughout history, language teaching has been assisted with various technological tools such as tape recorders, overhead projectors, DVD players, computers, smartboards, etc. If appropriately used, technology is a great help to develop language skills. The use of technology in language education can bring authenticity and fun to the classroom and can have a better impact on the learning/teaching process, especially when we think of Gen Z. This generation is known to be digital natives and uses any technological tools efficiently and effectively. They prefer to communicate by sending emails or using social media rather than face-to-face interaction. Therefore, it seems to be a need for language teachers to adopt a new perspective in language teaching. This chapter sheds light on the effectiveness of mobile-assisted language learning (MALL) in improving language learners’ writing skills. MALL provides invaluable sources to practice writing in and outside the classroom. After reviewing some studies investigating the impact of mobile technologies on language learning, randomly selected writing applications are introduced, and a sample activity for classroom practice is suggested.
An Asset Market Approach to the Conditions on the Usage of Cryptocurrencies with Fiat Currencies in a Coexistence Economy: The Land under Zero.

This study aims to construct a theoretical framework for the usage of cryptocurrencies together with fiat currencies in a coexistence economy to estimate the future effects of cryptocurrencies on the world economy. In this model, Bitcoin is used as a representative cryptocurrency, the uncertainties behind it are taken into consideration measuring by the variance of the expected returns on it. The model has three agents such as buyers, miners, and sellers. Buyers have to decide how much fraction of their initial wealth they spend either on Bitcoin or fiat money in the intention both to consume goods and services and to invest in the asset market. Buyers’ problem of choice is solved by considering their risk attitudes. Miners select the optimal mining effort to validate the transactions to have maximum gain. They gain rewards as Bitcoin and transaction fees, but they incur the cost of electricity as long as they exert effort to mine Bitcoin. Sellers sell their goods and services in the goods market to buyers and have no important effect on the usage of Bitcoin in this model. The study reveals the coexistence conditions of cryptocurrencies and fiat money based on the agents’ (buyers, miners, and sellers) optimization decisions. Overall, the “return-motive” creates the main intuition of using Bitcoin as a medium of exchange in the goods market. The uncertainties behind cryptocurrencies, the transaction and electricity fees, and people’s risk attitudes construct the main determinants of the condition of using cryptocurrencies together with the fiat currencies.
Quantitative Analysis of Emergent Narratives

Kybartas, QuinnEmergent narrativesEmergent Narrative (EN) modelModels the process of storytelling through the use of simulationSimulation (sim). The complexityComplexity and breadth of possible outcomes from a playthrough of an emergent narrative pose a number of unique challenges to authors. In this chapter, we survey the application of quantitative evaluationsEvaluation of emergent and narrativistic behavioursBehaviour, examining how they may be used to provide feedbackFeedback throughout the development processProcessDevelopment process of an emergent narrativeEmergent Narrative (EN) work. Four analysis techniques are also presented, which make use of quantitative analysisQuantitative analysis, benchmarkingBenchmarking, comparisons, verification and classification.
PERSEPSI PESERTA TENTANG KEMUDAHAN PENGGUNAAN LMS MOODLE PADA PELATIHAN JARAK JAUH PENDIDIKAN INKLUSI DI BALAI DIKLAT KEAGAMAAN PADANG

Padang Religious Education and Training Center has conducted Distance Training using the Moodle LMS since 2019. This study aims to determine the participants’ perceptions of the ease of using Moodle LMS among Inclusive Training participants by using descriptive statistics and degrees of achievement. The research subjects were 30 participants of the Inclusive Education Distance Training. The quantitative data in this study were obtained by means of a questionnaire assessment using the formula for the degree of achievement of the questionnaire. The results of the research on participants’ perceptions of the ease of use of the Moodle LMS as a whole was 78.83% so that it could be categorized in the fairly easy category. What was measured by indicators: ease of learning to use Moodle LMS, ease of getting what you want in Moodle LMS, using Moodle LMS does not require much thought and Moodle LMS is easy to understand and use. Keywords: distance training evaluation, post training evaluation, online training
Writing Lessons to Strengthen ‘Information Utilization Competency’ －Focused on a Team Project Using the Allo App

The extension of life expectancy and the development of science has required change and transformation, not only regarding a person’s quality of life but also the direction of liberal arts classes and their methods. From this point of view, the necessity of cultivating digital-based ‘information utilization competency’ that can respond to changes in social structure has increased, even in the writing classes of college liberal arts subjects, which are ‘communication’ based and which use ‘written language’ as a medium. The K University writing class was designed as a team project and conducted as a process-oriented curriculum. It used the Allo app to improve learners’ information utilization competency. During three weeks of classes team project conducted practical writing practice using personal writing to develop ‘information utilization competency’ related to the authenticity of students. The Allo-based team activity class was constructed to elevate the combined academic knowledge and procedural knowledge, both contextualized through ‘written language’ in the preceding individual writing process and to reproduce useful ‘information.’ It was done using various media, such as ‘voice language’ and ‘written language,’ and through team activities. It was a process focused on ‘re-contextualization,’ achieved by producing discussion, journal writing, product selection, and re-contextualization. Experiences necessary in developing the results were extended to using various media built into Allo, thereby deepening the learner’s functional information utilization competency. At the same time, through the process of the re-contextualization of academic content, such as journal writing, the critical interaction of team members, and the reflection that occurs in the process of the final production, all team members were able to directly or indirectly revise and modify their information utilization. Moreover, students were able to develop their information utilization competencies. In particular, the comprehensive thinking process, including the meta-cognitive domain, which contextualized one’s logic at the elementary level of data collection and the use of verified data, shared the writings of students and team members through a discussion process to produce outputs. The successful class showed that lifelong education and the ability to utilize information as a global civilian competency in a knowledge-based society should be cultivated through writing classes using various media. In particular, we can say that the meaning of competence lies in the ‘productivity’ of problem-solving through information as a response strategy for the future society. Another significant result was the reflection of students who had failed to develop proactively and actively in personal writing revised personal writing after the Allo-based team project. I end this article by leaving the lesson design for such learners as a follow-up task.
Historical epistemology: problems and prospects

The paper considers historical epistemology as a relevant direction of philosophical reflection on the historical foundations of scientific cognition. The researcher emphasizes the identity of historical epistemology in a number of other historical and philosophical studies of science, explores the matters of ontological turn in historical epistemology, reflexivity and relativism. The paper demonstrates that historical epistemology, making an ontological turn, offers an original way to solve the problem of relativism regarding science, which arises in the context of a historical approach to scientific foundations. The research considers the historical epistemology not only as a subject of philosophical research, but also as a special strategy for the study of science, which has its own methods. The possibilities and prospects of this strategy use, in particular, related to the constructive interdisciplinarity are also in the focus of this research.
Grassl–Rötteler cyclic and consta-cyclic MDS codes are generalised Reed–Solomon codes

We prove that the cyclic and constacyclic codes constructed by Grassl and Rötteler in International Symposium on Information Theory (ISIT), pp. 1104–1108 (2015) are generalised Reed–Solomon codes. This note can be considered as an addendum to Grassl and Rötteler International Symposium on Information Theory (ISIT), pp 1104–1108 (2015). It can also be considered as an appendix to Ball and Vilar IEEE Trans Inform Theory 68:3796–3805, (2022) where Conjecture 11 of International Symposium on Information Theory (ISIT), pp 1104–1108 (2015), which was stated for Grassl–Rötteler codes, is proven for generalised Reed–Solomon codes. The content of this note, together with IEEE Trans Inform Theory 68:3796–3805, (2022) therefore implies that Conjecture 11 from International Symposium on Information Theory (ISIT), pp. 1104–1108 (2015) is true.
Gli studi italiani di lessicografia e la scuola tedesco-danese

Abstract Investigation about Greek lexicography is very important for the Byzantine culture and for the knowledge of classical authors. The German-Danish school has studied lexicography with a historical view and in particular in the nineteenth century it reconstructed lost lexicons. In contrast, the Italian school had a functionalist and structuralist approach. In recent years, however, scholars have adopted the best aspects of both schools. Indeed, now the method of lexicographic studies is unitary.
Theoretical and Methodological Provisions of Quality Management of Professional Activity of The Teaching Staff of Higher Educational Institutions

The article substantiates the relevance of assessing the quality of professional activity of the teaching staff of higher educational institutions in the context of the transformation of the educational process. A study of theoretical and methodological aspects of assessing the quality of work of teaching staff has been conducted. The key components of the category “quality of professional activity of the teaching staff” are identified and a definition based on the essential aspects of the selected components is formulated. The main trends characterizing the modern system of higher education (elements of the transformation of the higher education system) are also highlighted, their impact on the activities of teaching staff of higher educational institutions is analyzed and the emerging demands of the external environment for the qualification of teaching staff are highlighted. As a result of the study, the authors identified inconsistencies in the theoretical and methodological provisions of the assessment of the quality of teaching staff, in particular, inconsistencies between the normative and actual qualification and competence requirements for teaching staff in the conditions of transformation of the educational system.
Civil Society Participation Model: Forest and Land Fire Prevention Policy in Jambi Province

This study aimed to analyze the factors that influence community participation in forest and land fire prevention. The focus of this research is on Jambi Province. This study used a qualitative descriptive method, and the data sources were obtained through interviews, online media, online news, and research-related journals. Data analysis used the NVivo 12 plus data processing application, a qualitative document analysis tool with the help of a computer. They are easy to use and can process words and explore word frequency, attributes, and cases from big data, generating factor categories in journalistic and research applications related to the research topic. The results showed that the government made a strategy to encourage community participation in environmental management cooperation, especially in overcoming the problem of forest and land fires in Jambi Province. Informal reactions from the community can be seen through the government's policy to create a Fire Care Group program that is motivated by community aspirations for forest and land fires. The government formed the Fire Care Group to reduce the number of forest and land fires.