Reviewerly/exHarmony huggingface dataset:
Leveraging augmentation techniques for tasks with unbalancedness within the financial domain: a two-level ensemble approach

Abstract Modern financial markets produce massive datasets that need to be analysed using new modelling techniques like those from (deep) Machine Learning and Artificial Intelligence. The common goal of these techniques is to forecast the behaviour of the market, which can be translated into various classification tasks, such as, for instance, predicting the likelihood of companies’ bankruptcy or in fraud detection systems. However, it is often the case that real-world financial data are unbalanced, meaning that the classes’ distribution is not equally represented in such datasets. This gives the main issue since any Machine Learning model is trained according to the majority class mainly, leading to inaccurate predictions. In this paper, we explore different data augmentation techniques to deal with very unbalanced financial data. We consider a number of publicly available datasets, then apply state-of-the-art augmentation strategies to them, and finally evaluate the results for several Machine Learning models trained on the sampled data. The performance of the various approaches is evaluated according to their accuracy, micro, and macro F1 score, and finally by analyzing the precision and recall over the minority class. We show that a consistent and accurate improvement is achieved when data augmentation is employed. The obtained classification results look promising and indicate the efficiency of augmentation strategies on financial tasks. On the basis of these results, we present an approach focused on classification tasks within the financial domain that takes a dataset as input, identifies what kind of augmentation technique to use, and then applies an ensemble of all the augmentation techniques of the identified type to the input dataset along with an ensemble of different methods to tackle the underlying classification.
Towards A Standardized Aerial Platform: ICUAS’22 Firefighting Competition

Abstract This paper presents an Unmanned Aerial Vehicle (UAV) platform used for the competition held at the International Conference for Unmanned Aircraft Systems 2022 (ICUAS’22). The envisioned scenario in the competition is delivering an extinguishing ball to a fire with a UAV. Driven on that thought, the qualifying round of the competition is organized in a realistic simulation environment. The competitors are required to navigate through a cluttered environment into a free space, where they perform a search for the target and deliver the ball as close as possible to that target. The competition finals were organized as a part of the conference, with the same goal as in the simulation qualifiers. The UAVs used for the competition are prepared and provided by the organizers. A detailed description of the UAV software and hardware is outlined in the paper as a step towards standardizing aerial research platform.
A feasible semi-quantum private comparison based on entanglement swapping of Bell states

Semi-quantum private comparison (SQPC) enables two classical users with limited quantum capabilities to compare confidential information using a semi-honest third party (TP) with full quantum power. However, entanglement swapping, as an important property of quantum mechanics in previously proposed SQPC protocols is usually neglected. In this paper, we propose a feasible SQPC protocol based on the entanglement swapping of Bell states, where two classical users do not require additional implementation of the semi-quantum key distribution protocol to ensure the security of their private data. Security analysis shows that our protocol is resilient to both external and internal attacks. To verify the feasibility and correctness of the proposed SQPC protocol, we design and simulate the corresponding quantum circuits using IBM Qiskit. Finally, we compare and discuss the proposed protocol with previous similar work. The results reveal that our protocol maintains high qubit efficiency, even when entanglement swapping is employed. Consequently, our proposed approach showcases the potential applications of entanglement swapping in the field of semi-quantum cryptography.
Security in Digital Marketing

Digital marketing presents both challenges and opportunities when it comes to security. As more and more customer data is collected and stored digitally, the potential for sensitive information to fall into the wrong hands increases. Digital marketing also offers opportunities for improved security. Implementing two-factor authentication and using unique and complex passwords can also minimize the risk of unauthorized access to accounts and personal information. Overall, the key to maintaining security in digital marketing is to be proactive and stay informed about the latest threats and vulnerabilities. This includes staying up to date on best practices for data protection and regularly monitoring and testing your systems for security weaknesses. Based on this research gap, a systematic review of the bibliometric literature was performed, and data were synthesized from 80 documents identified through Scopus indexing. This research aims to assess the challenges and opportunities.
PEDAGOGICAL TECHNOLOGIES OF INTERACTIVE LEARNING IN THE FRAMEWORK OF THE STUDY OF HUMANITIES AS A FACTOR OF SPIRITUAL AND MORAL EDUCATION OF STUDENTS

This article analyzes the use of forms of interactive learning at lectures and seminars as part of the study of students of humanities disciplines on the example of two groups of pedagogical direction. The authors of the article presented the results of pedagogical technologies of interactive learning, which provide motivation, communication, freedom of expression, democracy, creativity, contribute to the spiritual and moral education of students.
Developing Educator-Specific Digital Competences With Serious Game Design

In today's fast-paced digital world, equipping pre-service teachers with educator-specific digital literacy competencies is crucial to their ability to adapt to changes and effectively teach and guide their students. This chapter presents an innovative approach to teaching digital competencies to pre-service teachers, utilizing game design-based learning, trialogical learning, and problem-based learning principles. In this approach, students collaborate in groups to develop an educational computer game and work with their colleagues from other faculty. Authors describe each phase of game development and frame it in the broader context of the acquisition of digital competences defined in the DigCompEdu competences framework for teacher education students. Since creating an educational computer game is a complex process, the authors propose the use of a project management tool to manage the different project work phases, describe the selection process and provide an overview of its utilization.
Block-Chain Framework for Educational Domain and its Benefits

Blockchain technology has gained significant attention in recent years due to its potential to revolutionize various industries. In the educational domain, a blockchain-based framework has emerged as a promising solution with several benefits. This paper explores the concept of a blockchain-based framework for the educational domain and highlights its benefits. The framework focuses on areas such as credential verification, academic records and transcripts, anti-fraud measures, micro-credentialing, secure assessments, and efficient data sharing. By leveraging blockchain technology, educational institutions can enhance transparency, security, and efficiency in these areas. Credential verification becomes more reliable and tamper-proof as digital credentials are stored on the blockchain. Academic records and transcripts can be securely shared between institutions, simplifying the transfer process and reducing administrative burdens. Blockchain's immutability and cryptographic security features help combat issues like fake degrees or certificates, ensuring the authenticity of educational qualifications. The framework also enables the issuance and management of micro-credentials, reflecting specific skills or knowledge. By recording these credentials on the blockchain, individuals can have a comprehensive and verifiable record of their lifelong learning achievements. In the assessment process, blockchain technology enhances security and integrity by preventing data manipulation or cheating. The framework provides a decentralized and transparent platform for storing question banks, exam results, and assessments. Furthermore, blockchain-based frameworks facilitate secure and efficient sharing of educational resources, research findings, and collaborations. Smart contracts automate processes such as copyright permissions, royalty distributions, and collaborative project agreements, ensuring transparency and fairness. While the benefits of a blockchain-based framework in education are promising, challenges regarding technical implementation, scalability, cost-effectiveness, and privacy must be addressed. Further research and development are needed to explore these aspects and enable widespread adoption of blockchain solutions in the educational domain
Pattern Recognition, Imaging Models, and Artificial Intelligence

Machine learning and deep learning techniques are always compressed, convergence models. The most appropriate optimization would be the gradient descent, which is capable of finding the best solution with minimal cost. This algorithm can also be used with convolution neural network for better performance. Here a research work proposes a novel automatic image segmentation technique to discriminate between normal and acute lymphoblastic leukemia on bone marrow samples and has been done with the proposed GD_CNN. This method consists of background extraction and RBC separation. In the next stage, the median filtering and morphology technique is used to remove the noise and outliers. An improved GD_CNN model is used to classify normal or abnormal bone marrow samples. This proposed work is implemented using MATLAB 10.0 tool and tested on the bone marrow samples taken from ALL-IDB (Acute Lymphoblastic Leukemia Image Database for image processing) database. The proposed model provides high-quality classification accuracy to identify acute lymphoblastic leukemia.
Pre-Service Teachers' Cognition of STEM via 4IR Cognitive Principles

In the current Fourth Industrial Revolution (4IR), or Industry 4.0, learning—and consequentially learners' comprehension—either in a discipline-specific (science, technology, engineering, and mathematics- STEM disciplines) or general decision-making, can be marred by inappropriate use of the cognitive tenets, particularly so in the current 4IR or Industry 4.0. Accordingly, the current study is informed by this challenge and in part anchored upon theoretical disposition of 4IR or Industry 4.0 cognitive principles. The present research provides both theoretical and empirical examinations to improve mathematical discipline cognition as well as general decision making, thus aimed to enhance knowledge-building and subsequent development in discipline-specific.
EXPLORING THE CONTENTS OF OLD NEWSPAPERS USING AN AUGMENTED REALITY APPLICATION

Newspapers are necessary for daily living because they provide information on a variety of topics, including the economy, trade, business, sports, and entertainment. Reading the news broadens one's perspectives and increases knowledge. Readers may interact with the information through digital elements including movies, animations, and other content with the use of an augmented reality application. A variety of augmented reality components, including buttons for videos, links, YouTube, and 3D models, can be utilised to increase the variety of information available in physical newspapers. Computers can identify and project things over the newspaper with the help of an augmented reality marker. A newspaper can set itself apart from other publications by using a marker and a smartphone with a non-standalone software that can recognise the marker, such as QR codes or photos. In an effort to make a newspaper more user-friendly, researchers are experimenting with the Vuforia Engine tool and Augmented Reality Tools.
An Approach to Identifying Best Practices in Higher Education Teaching Using a Digital Humanities Data Capturing and Pattern Tool

The aim of this paper is to provide an overview of the process of identifying effective teaching patterns by capturing relevant features of given digitally-supported teachings. The overall goal is to collect learning and instructional settings in a way so that they can be reused in different subject domains. First, this involves describing the development of a suitable data structure for capturing instructional data that results from a validated taxonomy. This paper also presents the integration of an application that was developed for modelling and capturing data in domain analysis.
Implementation of Digital Resources in the Teaching and Learning of English in University Students

ICT may be utilized to aid in the assimilation of a second language; since persons use technology on a daily basis, it is advantageous to extend this learning to ICT; nevertheless, integration is essential for increased interest. There are many reasons why it is vital to evaluate the interaction between ICT and English learning. That is why, with the broad objective of establishing a link between ICT and English acquisition, this research used a hypothetical deductive technique, a non-experimental cross-sectional design, and a sample of 60 university students from Enrique Guzman University and the surrounding valley. The sample was given two instruments made from the variables and dimensions using Spearman's rho statistician. It was discovered that there is a substantial association between ICT and English learning. Thus, increased usage of ICT will result in increased English language learning accomplishment for students enrolled in the second year of an English study program at a public university.
A Multimedia Resource Ontology for Semantic E-Learning Domain

The past decade has seen the growing up of multimedia technologies in the context of e-learning. Smarter platforms are needed to support lifelong learning anywhere, anytime. This paper presents a new multimedia resource ontology (MMRO). It first provides a background about knowledge bases, description logics and reasoning, and an overview of multimedia ontologies. After highlighting their limitations in the context of e-learning, MMRO is detailed in terms of main class hierarchy and assertions. Finally, we identify the next steps of possible future research works.
Key Point Detection of Power Tower Based on Improved Yolov5

Using UAV to accurately and quickly realize the three-dimensional modeling of power tower is an effective measure to promote the construction of smart grid. A tower target recognition algorithm based on yolov5 is presented to solve the problem of inaccurate tower 3D perception recognition by UAV. By improving the internal structure of the residual block to reduce the impact of steel intersection on the identification results and improve the accuracy of the algorithm, the exponential linear unit function is used as the activation function to accelerate the convergence speed of the network and improve the robustness of the algorithm, so as to realize the rapid and accurate identification of key points of power towers. By comparing the fast R-CNN and EfficientDet target detection methods through experiments, the improved algorithm has improved the recognition accuracy to a certain extent. The model maintains the lightweight characteristics of yolov5 and has a good prospect in application deployment.
Usability of Augmented Reality Assisted Commissioning of Industrial Robot Programs

Abstract This paper analyses the usability of Augmented Reality (AR) in the commissioning and programming of industrial robots. Conducting two individual studies with a total of 31 participants we analysed the three dimensions of usability: effectiveness, efficiency, and user satisfaction by comparing our developed AR system with the conventional Teach-In programming method during the commissioning and modification of offline created robot programs. The results indicate that, while less accurate and hence effective, the AR system is more efficient and has a higher user satisfaction. Beyond that a posture analysis indicates that during a timeframe of 30 min the additional weight of the AR device does not significantly worsen the posture of a worker. Complemented by the positive result of the System Usability Score (SUS) that rates the analysed AR system with a good usability, the overall results indicate that while still limited by its achievable accuracy AR is an intuitive medium to conduct robot programming and commissioning.
Input and Tracking System for Augmented Reality-Assisted Robot Programming

Abstract Augmented Reality-assisted robot programming systems (ARRPS) aim to make the programming of industrial robots more efficient by providing an AR-based human machine interface that allows operators to program robots intuitively and quickly. This work aims to contribute to the field by presenting an input and tracking system based on the VIVE Lighthouse technology that can act as a basis for ARRPS systems, improving maturity, costs and accessibility. To evaluate the system, ARRPS core functionality has been implemented so as to demonstrate its basic feasibility. An extensive evaluation of the system accuracy has been conducted, as this is one of the key criteria for potential adoption of the technology. The feasibility could be successfully demonstrated and it could be shown that the end-to-end mean absolute error of the robot path point placement amounts to 11 mm in a workspace of 0.6 × 0.6 × 0.25 m 3 volume. Finally, the robustness and setup time of the system still need to be improved.
Faust Programs in Csound

1. Introduction Csound (Boulanger, 2000) is a Music-N language that was first released in 1986 as a C-port of the Music 11 language, originally developed for the DEC PDP-11 computers at MIT in the 1970s. Since its release, it has undergone a number of changes, and in 2006, a completely re-engineered system, Csound 5, was launched. This system had a number of new possibilities, as it was designed as a library that could be embedded in a variety of environments. It also included the possibility of plugin opcodes, which would extend the language without the need for the whole re-compilation of the code base. In 2013, a further review of the system was carried out, and a new major version, Csound 6 (Cabrera et al., 2013), was launched, with substantial improvements and additions. This is the current system, discussed in this article. Faust (Orlarey, 2009) is a functional language designed to translate signal processing flowcharts into C++ or Javascript source code, or into LLVM bitcode. It allows plugins to be designed and then translated to C++ code that can be compiled into dynamic libraries, which can then be loaded into Csound as new unit generators (opcodes). This is done by the Faust compiler, which can be executed from the command-line, from the IDE Faustworks or on-line, via a web-based frontend. Recently, however, a new version of the system, Faust 2, has been developed where the Faust compiler is now provided as a library (libfaust) that can be embedded into another pro
Gamified English Language Learning in Ukraine: Critical Divide between Tradition and Innovation

The article aims to describe gamification and educational technologies integrated into English teacher education as impactful and novel practices in Ukraine. Therefore the study briefly reviews educational technologies and gamification research and presents empirical evidence from Kyiv National Linguistic University. Since Ukraine is determined to be in line with the world’s progressive tendencies and is striving for digital humanistic pedagogy, the significance of this study lies in proving that technology-assisted gamified English learning essentially transforms Ukrainian education and positively affects Ukrainian schools where the quality of English is on the agenda. The study’s central question addresses the benefits of gamified learning for building English proficiency in preservice teachers and developing necessary teacher competencies, projecting the effect on their in-service teaching at Ukrainian schools in the future. Collecting the data and carrying out the research employed mixed methods, engaging 43 future teachers of English in the 1st and 2nd years of training and 11 language instructors. The findings prove that the study is relevant and deserves further investigation for a successful application in English teacher preparation in Ukraine to make school classrooms motivating and engaging for enhancing English language education and reaching ambitious goals to meet the world’s standards in teacher training.
ESL Learners’ Qualitative Perspective on Learner-to-Instructor Interaction in Blended Environment

English language proficiency exceptionally verbal communication is essential in achieving Sustainable Development Goal four, which is a good quality higher education. Nevertheless, past literature reported a lack of verbal communication among the graduates of English as a second language. Due to the emphasis on technology integration in Malaysian Education Blueprint 2015-2025, blended learning has been widely implemented in most tertiary institutions. However, learners complain they face challenges during verbal communication learning, particularly in learner-to-instructor interaction in a blended environment. Therefore, this study explores the learners’ opinions regarding learner-to-instructor interaction for verbal communication learning in a blended environment. The result of this research is substantial to English language instructors, curriculum designers, and English language learners as the input provides the information to understand the phenomenon in-depth and suggestions to improve verbal communication problems in learner-to-instructor interaction in the blended learning environment. The research question this study intends to answer is “What are the informants’ opinions on learner-to-instructor interaction for verbal communication learning in a blended environment?”.This study employed qualitative research inquiry, particularly phenomenological design, and the data was collected through semi-structured interviews, written accounts, and a focus group discussion. The data was then analyzed using thematic analysis. The findings revealed two significant themes related to the phenomenon: the roles of the instructor and the issues in the learner-to-instructor interaction as well as six sub-themes. Future studies might consider including English language instructors to obtain different perspectives.
Photon-added deformed spin coherent states and bipartite entanglement

In present manuscript, we build the photon-added deformed spin coherent states (PA-DSCSs) according to deformed spin algebra (DSA). We present the way for solving the unity operator problem and we give the solution for some particular cases. The obtained states are developed through the Holstein-Primakoff (HP) realization of the DSA. The statistical features of the obtained coherent states are examined through the variation of the Mandel’s parameter. By using the PA-DSCSs, we investigate the bipartite entanglement with respect to different parameters of these states.