Reviewerly/exHarmony huggingface dataset:
Semi-supervised Organ Segmentation with Mask Propagation Refinement and Uncertainty Estimation for Data Generation

We present a novel two-staged method that employs various 2D-based techniques to deal with the 3D segmentation task. In most of the previous challenges, it is unlikely for 2D CNNs to be comparable with other 3D CNNs since 2D models can hardly capture temporal information. In light of that, we propose using the recent state-of-the-art technique in video object segmentation, combining it with other semi-supervised training techniques to leverage the extensive unlabeled data. Moreover, we introduce a way to generate pseudo-labeled data that is both plausible and consistent for further retraining by using uncertainty estimation. Our code is publicly available at Github .
An Efficiency Coarse-to-Fine Segmentation Framework for Abdominal Organs Segmentation

U-Net has been proved as the most successful segmentation architecture for medical image processing in recent years. Based on this, ResUNet imported ResBlock with skip connection focuses more on the contextual information. In this work, we adopt the 3D ResUNet to build a whole-volume-based coarse-to-fine segmentation framework for the abdominal multi-organs segmentation task, and the mean Dice Similarity Coefficient (DSC) of the segmentation results has achieved 87.67%, the mean Normalized Surface Dice (NSD) has achieved 93.16% on the FLARE2022 validation set. Besides, for each case on the FLARE2022 validation set, the average running time is 19.5614 s, and the max gpu memory consumption is 2657 MB.
The FAIR concept in the context of Open Science

Research data management is an integral and vital part of global Open Science, and its advantages include: avoiding duplication of existing data, greater transparency of the process, and optimization of efforts in large research groups. The conference paper describes the concept of FAIR (Findable, Accessible, Interoperable, Reusable) as a tool to promote data openness.
Nearest Neighbor Algorithms

Most of the practical data sets are high-dimensional. A major difficulty with classifying such data is involved not only in terms of the computational demands but also in terms of classification performance. It is very obvious when the learning algorithms are dependent on distances. In this chapter, we present the difficulties and possible solutions to deal with such high-dimensional data classification.
Non-linear Schemes for Representation

In this chapter we deal with various nonlinear feature extraction schemes. In nonlinear feature extraction, the extracted features may be viewed as nonlinear combinations of the originally given features. Two popular neural network architectures employed are self-organizing map (SOM) and autoencoder (AE). We examine both of them in this chapter.
Representation Using Linear Combinations

This chapter deals with linear representations. Here, each new feature is a linear combination of the given input features. Even feature selection may be viewed as a special case of the linear representation schemes. We specifically consider, in this chapter, various types of feature selection schemes, principal components, random projections and non-negative matrix factorization.
Representation

Representation is an important step in building ML models. This chapter introduces how data items, classes and clusters are represented. It also discusses the importance of representation in both ML and AI. In the process it deals with both feature selection and feature extraction and introduces different categories of dimensionality reduction.
Cross-cultural validation of “Students' knowledge and use of digital technology during the COVID-19 pandemic” questionnaire to the Peruvian context

To obtain useful, valid, and reliable results, it is essential to carry out a cross-cultural adaptation process when using measurement instruments developed in other cultures, contexts, and populations with a different language from the original one. An instrumental study was conducted to determine the validity and reliability of the “Students' knowledge and use of digital technology during the COVID-19 pandemic” questionnaire, developed in another context and different culture from the original one. The participants were 139 students of the Communications program of a private higher education institute in Lima, selected by non-probabilistic convenience sampling. The study presents a proposal consisting of eight factors and 56 items, as opposed to the original structure composed of seven factors and 77 items. The analyses show that the instrument is valid and reliable among the population under study.
Technological tool to assess computational thinking

The educational challenges of society permeated by digital technologies are aimed at developing skills to identify and solve environment problems. In this context, computational thinking (CT) emerges as a set of skills to be developed from an early age, which requires the empowerment of programming and demands the use of technological tools. The purpose of this article is to present the design and implementation process of a computer tool for CT evaluation, as well as its validation with a sample of elementary school students from a public institution in Colombia. The methodology focuses on the phases of the SCRUM development process. The results show that women perceive less difficulty in understanding the activities to be solved. It is possible to obtain a web application type software taking into account the evaluated characteristics of the tools used for CT teaching, covering most of these, and with special emphasis on some such as the content in Spanish, instructional model, management of the course, learning activities, monitoring, feedback and gamification.
The Financial Sector

This chapter explains the evolution of Iran’s financial sector with a focus on the performance of the Central Bank of Iran (CBI) in terms of price stability and oversight on commercial banks and credit institutions. It discusses the performance and characteristics of commercial banks with a focus on financial depth and share of different sectors of the economy in outstanding bank loans. Finally, it presents an overview of the role of Iran’s sovereign wealth fund (National Development Fund of Iran, NDFI) in the management of oil revenues.
Computer Games – Are They New Technologies of the Humanities?

The article expresses a hypothesis about the possibility of using computer games as a tool for the social and human sciences (in particular, philosophical ones), which in the modern world are increasingly dealing with phenomena, practices and communicative acts caused by digital reality. Possible directions of such use are considered. For a long time, the humanities did not have the developed tech­nical infrastructure that the technical sciences had. As if without needing it, they mostly relied on a unique and inimitable experience, which, in principle, cannot be technicalized and modeled, but rather must be experienced, described, inter­preted. But today, the social and humanitarian reality is largely dictated by digi­tal and the transformations it is carrying out. Our life is largely open to new types of interaction, new types of objects, new subjective states, the reality of which is not conceivable outside of digital. Moreover, the numeric associated with control, order, and transparency introduces a significant amount of uncer­tainty into social reality. In this sense, the boundary between the unique and ordi­nary, conceivable experiment and the field of social interaction is blurred. We are increasingly open to uncertain scenarios. In such a situation, the humanities sim­ply need tools to explore possible worlds, rare and unique states and events that at any moment can not only be embodied in everyday life, but also determine its key meanings and values. Computer games allow you to connect a huge number of users and use their intuition and creativity in designing and living in possible worlds.
Multivariate Normal Distribution

IN THIS CHAPTER, we generalize the bivariate normal distribution from the previous chapter to an arbitrary number of dimensions. We also make use of the matrix notation. The mathematics is generally more dense and relies on the linear algebra notation covered in Chapter 4 . In Sect. 4.5 , we pointed out there is a limit on what computations we can reasonably perform by hand. For this reason, we illustrate these various operations with the help of R.
Bivariate Normal Distribution

THE BIVARIATE NORMAL DISTRIBUTION helpsBivariate normal distribution us make the important leap from the univariate normal to the more general multivariate normal distribution. To accomplish this, we need to make the transition from the scalar univariate notation of the previous chapter to the matrix notation of the following chapter.
A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. There exists a gamut of approaches to solving merging and intersection crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to solving these problems that is based on distributed cooperation between the UAVs/UASs and the infrastructure. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing UAVs/UASs to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them.
Assessing electronic educational cards (EECs) as a method of foreign language learning: An experimental design approach using kindergarten students

This study investigated the effects of Electronic Educational Cards (EECs) on Teaching English as a Second Language (ESL) in Kindergarten. The experimental group participants (N = 500) and the control group participants (N = 500) were observed for six months and did pre-and post-experimental tests. The results showed that children in the experimental group compared to the control group demonstrated significant improvements in learning English as a Second Language. This study concluded that there is irrefutable empirical evidence that modern teaching methods should be encouraged and embraced for the betterment of early education students' learning. It is recommended that the format and structure of implementing the electronic revolution in Jordan’s early education sector be premised closely with that of the experimental group used in this study and rolled out throughout all the kindergartens in the Ma’an Governorate, and the entirety of the Hashemite Kingdom of Jordan. Keywords: Electronic Educational Cards, Kindergarten, Teaching English as a Second Language;
Improving the quality of distance education of future teachers

This study aimed to investigate aspects of face-to-face and distance learning and create a model of distance education for university teachers. For this, theoretical methods of comparison, analysis and symbiosis were used. As a result of the study, differences in the characteristics of various types of education and the possibilities of creating an effective programme of distance education for university teachers were revealed. A model has been developed for organising distance learning in higher education. This model can be applied to any university curricula. As a recommendation, the authors put forward several proposals for changing the grading system: adopt criteria-based assessment and, based on criteria-based assessment, carry out educational monitoring.&#x0D; Keywords: online class, distance education, higher education, pandemic, quarantine.&#x0D; &#x0D;
Classifying bug reports to bugs and other requests: an approach using topic modelling and fuzzy set theory

1.1OverviewBug Tracking Systems like Bugzilla, Gnats and Jira [1,2] are a type of systems that are used to support the maintenance activities during the lifecycle of software systems [3].They are a communication mean between users and developers to report and fix issues [4].In particular, these systems commonly manage the following two types of reported requests: corrective requests (bugs), and perfective requests (non-bugs) such as new feature request, improvement request, documentation, and so on [3][4][5][6][7].Software bugs are unavoidable.Therefore, more and more bug reports are continually submitted to bug tracking systems.Specifically, statistical information in [8] states that more than 30 maintenance requests are reported daily.
ANALYSIS AND REVIEW OF HANDWRITTEN TEXT RECOGNITION TECHNIQUES IN DEEP LEARNING

Numerous academic and business interests exist in automatic handwritten text recognition.Deep learning approaches now excel in teaching the ability to detect handwritten text.The key issue in computer vision is handwriting recognition, and the biggest obstacle in this discipline is dealing with the great range of handwriting styles used by different writers in various languages.The difficulty of text recognition is made more difficult by the similarities between the nearby characters.It is extremely difficult to precisely describe the handwritten characters due to the wide range of writing styles used by different authors and the complicated properties of those characters.This research offers a thorough analysis of the handwritten recognition approach using different classifier, different feature extraction techniques and different parameters.
Academic Debt in Higher Education: An Analysis of the Causes and Opportunities to Overcome

Academic debt can cause a significant damage to the Russian economics and the higher education system in the medium term (on the horizon of 5–10 years). The purpose of the study is to identify the key problems based on the results of a comprehensive empirical analysis of the situation of the formation of massive academic debt (using the example of the “Business Informatics” direction at a Russian university) and to substantiate ways to improve the activities of universities in order to overcome them and reduce students’ academic dept. Research methods are general scientific (deduction, induction, generalization, comparative analysis, etc.), as well as special ones (correlation and regression, statistical, sociological surveys, etc.). Analytics and visualization of quantitative data were carried out using MS PowerBI software. Research results. It was revealed that: a) high incoming scores do not guarantee trouble-free education at the university; b) students with low scores (but not less than 160–170) are also able to master quite complicated university programs; c) the presence of academic debts does not depend on the type of disciplines studied (economics / information technology). The number of student dropouts in the studied sample (up to 50% of those who entered with a non-linear dependence on the total USE scores) testifies to the presence of reasons that are not related to the incoming educational potential of students. The results of the study made it possible to structure them into three groups: insufficient motivation, self-organization problems, and “incomplete maturation”. Five groups of students have been identified with an increased risk of accumulating academic debt. The article substantiates the use of indirect educational influence on the students through a special mobile application.
Legal Framework for Output Based on Artificial Intelligence: Ukraine’s Place on the Global Search Path

This chapter outlines the Ukrainian discussion on providing a legal framework for output based on artificial intelligence (AI) with a view to identifying its place and embedding it in the global debate. To this end, the author briefly sets out a common theoretical basis together with practical insights of copyrightability requirements under Ukrainian copyright law and then proceeds to examine output based on AI against them. This assessment reveals the particularities of scholarly approaches to treating such output in Ukraine and other jurisdictions. While the threshold of human involvement sufficient for a work to obtain copyright protection is yet to be clarified, the Ukrainian academic sector generally considers that Ukrainian copyright law does not protect a considerable part of output based on AI. Further, the more sophisticated AI systems in creative industries will become, the more output based on AI will be non-copyrightable. Under these circumstances, Ukrainian scholarly circles have actively embarked on a search for a legal framework for such output. The chapter offers an overview of ideas put forward in this regard and puts them in an international context. Particular attention is paid to the initiative on introducing a new sui generis right for non-original computer-generated objects as the only proposal that has so far made its way to the legislative initiative level. By shedding light on the Ukrainian ideas, the chapter shows the way for future considerations and perspectives.
Protection of Works Posted on the Internet Under Ukrainian Copyright Law

This chapter examines copyright protection and enforcement regarding works posted on the internet in light of the current Ukrainian and EU case-law practice. Along with the process of using a copyrighted work on the internet, the chapter focuses on four legal issues. First, the “making available of a work to the public” is discussed. This should be defined as a type of communication to the public in such a way that members of the public may access this work from a place and at a time individually chosen by them. Unlike current Ukrainian legislation, this interpretation corresponds with the provisions of the WIPO Copyright Treaty and the EU–Ukraine Association Agreement. The chapter goes on to examine the key issue of exhaustion of rights for works uploaded to the internet and provides reasons why exhaustion should not apply to posting works on the internet. Thirdly, the chapter analyzes copyright infringement types susceptible to taking place on the internet. In particular, it discusses the conditions under which the act of placing hyperlinks/framing/hotlinking to other websites and objects can be considered as the use of a work and, therefore, as copyright infringement. Finally, the chapter describes copyright enforcement for works posted on the internet by extrajudicial measures, including the Ukrainian version of the “notice and takedown” procedure.
Copyright and Its Exceptions and Limitations in Ukraine

This chapter outlines the main provisions of the copyright law of Ukraine in the light of the Berne Convention for the Protection of Literary and Artistic Works, WIPO models, EU legislation and TRIPS. On this basis, the chapter enquires deeper into the peculiarities of exceptions and limitations as a mechanism for balancing the interests of the author and society. As a member of the Berne Convention, Ukraine applies the three-step test to copyright exceptions and limitations. At the same time, each type of free use of works has its own specific conditions which determine the scope and characteristics of the lawful free use of works: for some exceptions and limitations, the use of works must be exclusively non-commercial; in other cases, the possibility of obtaining a commercial benefit is irrelevant. Some types of copyright exceptions and limitations that are provided for in the legislation of EU Member States do not yet apply in Ukraine, although they are mentioned in the EU–Ukraine Association Agreement. The study of the types of free use of works allows one to characterize the system of copyright exceptions and limitations, the rules of their application, and their further development in Ukrainian copyright law.
An advanced optimization technique for integrating IoT and cloud computing on manufacturing performance for supply chain management

The discipline of Supply Chain Management (SCM) is getting more difficult to master. It is necessary to address information silos on the demand and production frontiers of goods in order to execute the de-coupling factor in the preferences of customers who are engaged in a supply chain to optimize business performance, which in today's world has become a difficulty. The so-called Amazon Effect has, once again, compelled competitors to rethink their approaches to achieving maximum efficiency. The Analytic Hierarchy Process (AHP), which is part of the Multi-Criteria Decision Making (MCDM) Approaches, has been used to offer the preferences of clients of various criteria versus various features (products). AHP is used to compute the weights of criteria, then rank the various alternatives. The AHP method is used to build the pairwise comparison between criteria to check the importance of these criteria. The AHP method checks the consistency of the experts to ensure all data is consistent.
CHALLENGES FOR TEACHER EDUCATION IN INDIA: A STUDY OF FACULTY PERCEPTIONS WITH SPECIAL REFERENCE TO GENDER AND TYPE OF INSTITUTIONS

This study investigated the various challenges for teacher education in India as perceived by the staff of tertiary institutions conducting teacher education programmes. A descriptive survey research design was adopted for the study. A stratified sampling technique was used to select eighteen tertiary institutions from the six-geo-political zones in India. A structured questionnaire was designed and validated for the study. This instrument was administered on 450 respondents in the sampled tertiary institutions. The instrument was complemented with oral interview with the Dean of Faculties of Education, Directors of Institutes of Education and Provosts of the Colleges. The data collected were analysed using frequency count, percentage score and t-test statistic. The hypotheses formulated were tested at 0.05 level of significance. The study revealed that the various perceived challenges facing teacher education in India include professionalisation of teaching, socio-economic and political environments, personnel in terms of quality and quantity, instructional resources and infrastructures. Moreover, the respondents’ perceptions of the challenges were significantly influenced by gender and type of institution. All stake holders of education in India must intensify efforts in meticulously addressing these challenges to enhance effective delivery of teacher education in the country.