Reviewerly/exHarmony huggingface dataset:
Teaching of STEM Subjects in Africa: Perspectives of Gender, Difficult Topics, School Ownership and Recommendation of CTCA

The new senior secondary computer studies curriculum for multilingual West African schools came into use in 2015. Since the beginning of its application, there have been few reported studies on the difficulty level of the content as perceived by students, gender equity, and school ownership. The study had two main purposes–to find out (a) the topics in the new computer studies curriculum that secondary school students perceive to be difficult; (b) if gender, and school ownership impact students’ perception of the difficulty of the computer studies topics. Participants were 1,501 computer studies students from nine public and 12 private senior secondary schools in Nigeria and Ghana. About 51% of the respondents were females. Three-quarters of the schools are in urban areas, the rest are in rural locations. Rich qualitative data on the sources of difficulty (unique for this study) are reported. Slight gender differences and marked rural/urban differences were found. Recommendations were made for improving the teaching and learning of computer studies in African schools with the use of Culturo-Techno-Contextual Approach (CTCA).
Federated Learning on Personal Data Management Systems: Decentralized and Reliable Secure Aggregation Protocols

The development and adoption of personal data management systems (PDMS) has been fueled by legal and technical means such as smart disclosure, data portability and data altruism. By using a PDMS, individuals can effortlessly gather and share data, generated directly by their devices or as a result of their interactions with companies or institutions. In this context, federated learning appears to be a very promising technology, but it requires secure, reliable, and scalable aggregation protocols to preserve user privacy and account for potential PDMS dropouts. Despite recent significant progress in secure aggregation for federated learning, we still lack a solution suitable for the fully decentralized PDMS context. This paper proposes a family of fully decentralized protocols that are scalable and reliable with respect to dropouts. We focus in particular on the reliability property which is key in a peer-to-peer system wherein aggregators are system nodes and are subject to dropouts in the same way as contributor nodes. We show that in a decentralized setting, reliability raises a tension between the potential completeness of the result and the aggregation cost. We then propose a set of strategies that deal with dropouts and offer different trade-offs between completeness and cost. We extensively evaluate the proposed protocols and show that they cover the design space allowing to favor completeness or cost in all settings.
TO SAVE MANKIND: PROPOSED IS AN ALTERNATIVE TO MINING BLOCKCHAINS

The concept of blockchains arouses an admiration due to its reasonableness and ease of implementation within existing infrastructure of Internet. The essential flawisan unacceptably big (from the point of view of ecology and common sence) power waste. The matter concerns the destinies of mankind, because uncontrollably expanding mining blockchains inevitably leads to overheating of Earth and thendeath of all living things. The solution being proposed is based on that follows: mining blockchains is not the goal in itself. The end goal is the reliable safekeeping of some valued constant (invariable) file. We propose not to RESIDE this file in the usual storage medium but to GENERATE it by a proper finite-state automaton. The principal singularity of the automaton circuit is an exeptional testability with respect to all multiple stuck-at faults. It is due to building the circuit according to the Theory of widened long flip-flop. The availis that mining is EXCLUSED as well as consumption of any significant power.
PEDAGOGICAL SIMULATION OF OFFICERS PROFESSIONAL INTEGRITY DEVELOPMENT IN ADVANCED TRAINING SYSTEM

The article proposes a pedagogical model for the development of officers professional integrity in advanced training system with the design and disclosure of the content of all its blocks - target-methodological, substantive, subject-subject, methodological and effective. The concept of "pedagogical simulation" in relation to the category understudy is substantiated. All the blocks of the model are interrelated and interconnected and only in the complex ensure the achievement of the research goal.The model consists of the following blocks: target-methodological, theoretical, subject-subject, methodological and effective: the target-methodological blockreflects the goal based on the leading requirements of modern methodological approaches to the development of officers professional integrity in advanced training system, taking in to account their military and professional training; theoretical – the content of its development; subject-subject – provides interaction of officers as subjects of educational activity, teachers as subjects of pedagogical activity, methodologyKeywords: pedagogical simulation, model, blocks, professional integrity, officer, development.
A Separation Logic with Histories of Epistemic Actions as Resources

We propose a separation logic where resources are histories (sequences) of epistemic actions so that resource update means concatenation of histories and resource decomposition means splitting of histories. This separation logic, called AMHSL, allows us to reason about the past: does what is true now depend on what was true in the past, before certain actions were executed? We show that the multiplicative connectives can be eliminated from a logical language with also epistemic and action model modalities, if the horizon of epistemic actions is bounded.
Using Personas to Raise Acceptance of Digital Tools in Social Organizations – Introducing the Easy Reading Framework

The Easy Reading Framework is a digital tool that can be used to make existing web pages accessible to the individual needs of a wide range of people. The core of this Framework is a toolbar, which currently includes 13 different functions. The potential for multiple applications of the Easy Reading Framework is being investigated and promoted in the recent Easy Reading follow-up project “EVE4all”. In this project, Personas play an important role in the first project phase to raise end-user acceptance. Personas represent specific target groups and share the same characteristics, traits, social environments, and circumstances as the intended target group. Working with this method enables developers and project participants to identify with the users of their products and their lifeworld. Our project shows that this method can be used to reflect on and use the introduction of any technology in institutions in a theoretically well-founded way. Thus, this paper aims to illustrate how this method can be successfully transferred into the pedagogical context and show how this method’s usage can contribute increasing user acceptance.
Design and Prototyping of a Serious Game on Interactive Tabletop with Tangible Objects for Disability Awareness in Companies

This paper presents elements of user-centered design and prototyping of a serious game. Produced within the framework of the SG-HANDI project, the serious game aims to raise awareness about integration, prevention of professional displacement and job retention of people with disabilities. This serious game is developed on an interactive RFID tabletop with tangible objects. It is intended to be used in a collective context involving one or more facilitators specialized in employment and disability, as well as the company’s stakeholders to be made aware of the issue.
Enhancing the Transaction Mechanism for Blockchain Application: A Business Perspective

This research study analyzes the blockchain-based social media platform from a technical point of view and compares current technologies with real-world scenarios such as Facebook, Twitter, and YouTube. Moreover, this study comprehends the present social DApps trend and highlights the important characteristics that should be considered in a blockchain-based social media scenario. In this study, the Proof of Authentication and consensus protocol are used. In the age of Internet, quickly evolving new media platforms are continually influencing the market share from established media and the advantages are utilized.
FBRA360: A Fuzzy-Based Bitrate Adaptation Scheme for 360° Video Streaming

Bitrate adaptation is a classic research problem in video streaming. In a tile-based 360° video streaming system, the problem becomes even more complicated because the system needs to conduct viewport prediction (VP) except for traditional bitrate selection (BS). Existing methods usually treat VP and BS separately, which is sub-optimal and thus limits performance improvement. Inspired by our observation of the bidirectional dependency between VP and BS, we propose FBRA360, a fuzzy-based low-complexity joint optimization scheme, to tackle this problem. A fuzzy logic controller has been devised to control simultaneously: (1) the weighted combination of VP from individual users' historical trajectory and multi-user attention distribution, and (2) the expected buffer occupancy after each download. Experimental results show that FBRA360 improves the VP accuracy by 16.2% and the video quality by 7.5%, compared with the state-of-the-art algorithms.
Joint Application of Analytic Hierarchy Process (AHP) and Bayesian Networks (BN) to Electromagnetic Environment Effects (E3) Assessment

The electromagnetic environment effect (E3) mainly concerns the risk of the system function impacted by the exterior intense radio signal. The E3 assessments try to capture the potential weakness of systems with tests, computations and estimations. The method of Analytic Hierarchy Process (AHP) is helpful to divide the large systems into smaller parts. On the other hand, AHP has disadvantages of subjectivity and loss of the original connectivity. The Bayesian Networks (BN) from the field of statistical causality or explainable artificial intelligence (AI) can absorb not only the advantages of AHP, but also permit the objective data obtained by the test and computations. So the primary trial indicates that the BN can remedy these shortcomings. And the joint Application of AHP) and BN provide us a whole hierarchical view of the E3 assessment activities.
Supplemental Material: Anomalous thermal structures of subduction zones revealed by thermal properties of clinochlore at high temperature and pressure

&lt;p&gt;Supplemental Text S1: Descriptions and governing equations for the finite element numerical model. Supplemental Text S2: Measurement error analysis of thermal diffusivity and thermal conductivity. Figure S1: Images of the clinochlore, assembly, and BSE before and after the experiment. Table S1: Chemical components of the natural clinochlore and production after experiments; measurement data for clinochlore at high temperature and pressure; and data on the thermal structures of the simulations.&lt;/p&gt;
IoT with Cloud Based Breast Cancer Diagnosis Using Deep Learning Techniques

Breast cancer is a significant public health issue affecting women worldwide. Early detection and accurate diagnosis are crucial for improving survival rates and reducing mortality. Deep learning, an instance of machine learning, has yielded encouraging results in a variety of medical applications, especially breast cancer detection. Deep learning algorithms can automatically learn and identify patterns in medical images, such as mammograms, to detect breast cancer. Moreover, deep learning can also assist in predicting breast cancer sub-types and prognoses. This proposed study provides a review of the current state-of-the-art in deep learning for breast cancer detection and prognosis, including the use of convolutional neural networks (CNNs). To address the issue of breast cancer detection, a deep learning architectures named ResNet-50 and EffNet-50 are used to detect the affected portion. In this proposed method, the Dicom mammogram image is used for diagnosis. The designed architectures are tested with the training dataset of size 19,994 and a validation set of size 8,333 and its accuracy is found separately for both models and also by combining them. The combined ResNet50 and EffNet50 architectures are found to provide a highest accuracy of 98.6% whereas the individual models accuracy is 96.2% and 96.8% for ResNet-50 and EffNet-50 respectively
Human Detection With Fisheye Camera

Most of the human detection and tracking studies in camera images are done by means of cameras with normal viewing angles. Detection and tracking in images of overhead cameras with fisheye angle of view involve various difficulties. Due to the wide field of view cameras with overhead view providing a 360° angle of view, the shapes of the objects on the edge of the image are distorted. Detection algorithms have difficulty detecting deformed objects. In this study, it is aimed to obtain a model suitable for fish-eye cameras by training human samples taken from fish-eye camera images with CNN algorithm and to measure the performance of the model with YOLO detection algorithm. A simple interface design has been made to facilitate the tracking of the image frames from the YOLO detection algorithm.
Report of Meeting Researches in Didactics of Mathematics and Computer Sciences

The meeting Researches in Didactics of Mathematics and Computer Sciences was held in Oradea, Romania, at Partium Christian University, from 31 March to 2 April, 2023. It was organized by the Doctoral School of Mathematical and Computational Sciences of the University of Debrecen and Partium Christian University. The 85 participants – including 18 PhD students – came from 9 countries and represented 30 institutions of higher and secondary education. There were 4 plenary and 53 session talks in the program.
INCLUSIVE PROJECTS IN SCIENCE AND TECHNOLOGY TO SECONDARY AND HIGHER EDUCATION

The purpose of this work is to bring science and technology and its applicability closer to secondary school and university students through the development of cooperative projects with people with functional and cognitive diversity.Through a teaching and learning methodology based on inclusive projects, professors from Higher Education aim to promote scientific and technological vocations and involve people with diversity in the advances in science and technology while making their condition visible to young people.This work shows both qualitative and quantitative indicators that allow us to evaluate the impact of those proposals.The degree of satisfaction of all the agents involved is very high, not only with the teaching and learning but also with the quality of the solutions developed to meet the needs of those people with diversity.The incorporation of projects based on both socially inclusive technological challenges and fairs increases motivation, participation and interest in science and technology, as we will demonstrate from obtained results.In addition, we would like to point out that these proposals mainly achieve three different sustainable development goals: number 4 (quality education), number 10 (reduction of inequalities) and number 12 (responsible consumption and production).
THE TYPES AND FUNCTIONS OF SWITCHING AND MIXING CODES IN ENGLISH STUDENTS’ ONLINE DISCUSSIONS

This study aims to discover the switching and mixing code types and their functions that are dominantly used in student online discussions. This research was designed in descriptive-qualitative method by using video recordings and interviews from Pragmatics class of postgraduate degree students as the data sources. The obtained data were then analyzed using Miles and Huberman model of analysis by involving data reduction, data display, and conclusion drawing. The results showed that students frequently switched and mixed codes during the discussions. In this case, ode mixing was dominantly occurred compared to code switching. There were 78 occurrences of code changes in total, with the proportions of 44 mixings and 34 switchings. Dealing with the types, insertion code mixing was found to be the mostly used in the discussions whereas intersentenential switching becomes the least. The phenomena of code switching and mixing in the classroom discussions has various functions, i.e.: for communication strategy, for delivering the meaning, for making clarification of the information, for defining specific terms, and for increasing understanding. This study also reflects the students' positive attitudes toward using switching and mixing codes in classroom discussion activities. It is recommended for further research to ensure the appropriate strategies for the teachers in switching and mixing codes for both offline and online classes.
Soft Actor Critic Swing Up of a Real Inverted Pendulum on a Cart

The inverted pendulum, is a classical experiment widely used as a benchmark for research in control systems, due to its challenging dynamics. In this paper, Deep Reinforcement Learning is used to control a real inverted pendulum on a cart. The Soft Actor Critic algorithm with automatic entropy tuning is used to train an agent capable of acting as a controller. The agent is trained on real data collected on an episodic basis and learns to carry out the swing up control task successfully.
Multi-Task Gradient Boosting

Gradient Boosting Machines (GBMs) have revealed outstanding proficiency in various machine learning applications, such as classification and regression. Gradient boosting builds a set of regression models in an iterative process, in which at each iteration, a regressor model is trained to reduce a given loss on a given objective. This paper proposes an extension of gradient boosting that can handle multi-task problems, that is, problems in which the tasks share the attribute space but not necessarily the data distribution. The objective of the proposed algorithm is to split the GB process into two phases, one in which the base models learn the multiple interconnected tasks simultaneously, and a second one, in which different models are built to optimize the loss function on each task. The performance of proposed model shows a better overall performance with respect to models that learn the tasks independently and all tasks together in several multi-task regression and classification problems.
The Problem of Concept Learning and Goals of Reasoning in Large Language Models

Modern large language models (LLMs) show good performance in the zero-shot or few-shot learning. This ability ability is a significant result even on tasks for which the models have not been trained is in part due to the fact that by learning from textual internet-scale data, such models build a semblance of a model of the world. However, the question of whether the entities on which that the model operates are concepts in the psychological sense remains open. Relying on conceptual reasoning schemes allows to increase the safety of models in solving complex problems. To address this question, we propose to use standard psychodiagnostic techniques to assess the quality of conceptual thinking of models. We test this hypothesis, by conducting experiments on a dataset adapted for LLMs from the psychological techniques of Kettel and Rubinstein and comparing the effectiveness of each of them. In this paper, we have shown that it is possible to distinguish several types of model errors in incorrect answers to standard tasks on conceptual thinking and to evaluate the type according to the classifications of distortions of conceptual thinking adopted in cultural and historical approaches in psychology. This makes it possible to use the tool of psychodiagnostic techniques not only to evaluate the effectiveness of models, but also to develop training procedures based on such tasks.
INTELLIGENCE QUALITY IN VERONICA ROTH’S ALLEGIANT

This study aims to determine the intelligence quality revealed in Veronica Roth's Allegiant. The author conducted this study using qualitative research based on Lincoln, and the data collection used two ways: Primary sources and secondary sources. The primary data collection was from the novel, and secondary data collection used references from articles, journals, books, and the internet. In analyzing the data, the author used a reader-response approach based on Cagri Tugrul Mart. The results of this study showed that Tris, the main character, used her intelligence qualities against the leader of the city of Chicago, Evelyn, and the leader of the Genetic Welfare Bureau, David. When Evelyn became the new city leader, the people expected her could stop the disputes between factions. However, Evelyn used her power for other purposes. Tris felt she had to do something to stop Evelyn from her act of cruelty that ruled over the city by unilateral decisions. In the end, they successfully stopped David and saved the city of Chicago
Spatiotemporal Parameters of the Hand and Wrist in Rehabilitation using a 3D Tracking Optical Module

The hand and wrist play a very important role in activities of daily living, and a variety of injuries can result in disability. Common treatments to recover the functions of the upper limb use physiotherapy, which is an intensive manual process, the evaluation of the progress of the patients and the performance of the rehabilitation therapy is a challenge. The objective this study is to have in the rehabilitation therapies of the affected hand and wrist there is a system to assist therapists collects data, processes and controls the movements joint during rehabilitation tasks, this data or movement spatiotemporal parameters joints can measure the joint positions hand and wrist using a 3D tracking optical module. The metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints are used to calculate movement spatiotemporal parameters joints such as angles between fingers and wrist, this data is stored in a sequence of consecutive movements. In addition, a segmentation algorithm was developed to extract the movement data for each specific joint along the axis of interest.
Automatic Construction the Russian Corpus of Verbal Government

This paper presents further development of the Russian Verb Co-occurrences Corpus. The first version of the corpus was improved using a variety of methods, including the application of frequency thresholds to filter out irrelevant information, identification of parenthetical expressions, adoption of a semantics-based approach to differentiate between arguments and adjuncts, and the clustering of verbs based on their semantic frames.
Blockchain Based E-Medical Data Storage for Privacy Protection

Electronic Medical Data (E-Medical Data) is sensitive and the privacy should be preserved. E-Medical Data is easily stolen, altered, or even deleted entirely. Accordingly, the healthcare organizations must guarantee that their medical data is treated confidential, secure, and private. If the situation happens like medical data cannot be logged or retrieved reliably, which delays treatment progress and even endangers the patient’s life. Conventional method of medical data storage led to threating of data by the attackers. Many medical applications face security problems like data stealing. Blockchain technology provides a solution to the security issue in many applications. As, the Blockchain features such as decentralization, cryptography-based security, immutability, and consensus algorithms open a solution to store e-medical data in a secure way with blocks and shared key. Our work highlights the decentralized E-medical data storage with consensus algorithms and its performance.