Reviewerly/exHarmony huggingface dataset:
Financial stability implications from the crypto-asset market

A component of digital finance that has been developed with an aim to decrease the usage of cash payments and improve financial inclusion is the crypto-asset. Concerns have been raised about the preservation of financial stability, which stands in for one of the primary objectives of central banks - along with price stability - as a result of the significant growth of the market capitalization of crypto-assets, as well as the rise in the variety of crypto-assets instruments and the volatility of their prices. Operating outside of national borders, crypto-asset trading platforms could lead to a concentration of risk and a lack of business transparency. The market for crypto-assets is growing more quickly, which highlights the need for strict regulation of that sector of the market, data collection to effectively monitor transactions, as well as providing protection for consumers and investors. The safety of all partipicants, the efficient operation of the financial system, and the maintenance of financial stability should all be guaranteed by the regulation of the crypto-asset market.
Strategies for Building a Scientific Research Talent Team Based on Regression Models

As the cradle of talent cultivation, universities have a significant impact on the rise and fall of national development through the production and application of scientific research achievements. Based on data research on the research talent team of Yunnan Open University, statistical methods were used to analyze and process the data materials. Regression models were used to study the relationship between the output of scientific research results in the analysis of industry teaching research cooperation. The relationship between the output of scientific research results and the factors of industry teaching research cooperation, such as teachers' professional titles, research work time structure, as well as the investment in school enterprise cooperation funds, number of cooperative entities, and number of invested cooperative teachers, was tested, so as to provide countermeasures and suggestions for the allocation of various elements, in order to guide the institutional practice of vocational colleges in actual funding investment and talent resource allocation.
The Impact of Pre-Editing on the Quality of Machine Translation

Pre-editing; Translation quality; Translation quality assessment system
Design of a Course Teaching Management System based on “ZanXueNet”

Cloud platform; Course teaching; Management system; System design
The condition and prospects of teaching Regional History in the general education system of the Kabardino-Balkarian Republic

The article discusses the condition and objectives of teaching Regional History in the school education system. The purpose of the article is to identify the issues and prospects for the development of this direction in the system of general education in the KabardinoBalkarian Republic. The scientific relevance of the research is a comprehensive study of the condition of regional historical education in the Kabardino-Balkarian Republic, and the development of the model for the implementation of Regional History in the system of general education. During the study the current regulatory documentation and scientific literature were analyzed. As a result, the lack of unified approaches regulating the teaching of regional historical content are revealed. It can lead to a number of problems. Measures based on the analysis are proposed to contribute to improving the status of ethno-regional training courses and the formation of students' self-identity.
The Research of Cognitive Topological Mechanism on “Da+NP” Construction

“Da+NP”; Construction; Image schema; Cognitive topology
SOCIAL INFANTILISM AS A PEDAGOGICAL PROBLEM

Modern education sets itself the task of forming responsible and active personalities capable of being independent and creative individuals who can actively participate in the life of society and the country. It is important to take into account the problem of insufficient maturity of both the personality and the emotional sphere of the individual, especially in the context of social infantilism, while providing society with high-quality youth.
DIFFERENTIATED APPROACH TO TRAINING PHYSICAL EDUCATION MAJORS WITH DIFFERENT PSYCHOTYPES THROUGH SMALL GROUP WORK

The paper discusses the necessity of taking into account individual typological characteristics of physical education students in order to optimize their education. The conducted research allows to adjust the learning process to the needs of the specified student group. The authors employ the hardware-software complex “Psychological tests” to conduct the study. The paper presents the analysis of the results of the pedagogical experiment on the implementation of a differentiated approach to teaching students of the Institute of Physical Education and Sport with different psychotypes through small group work.
A Systematic Mapping review to Remote Data Integrity Verification Systems for Cloud Computing

Cloud computing has totally changed the way information is put away and gotten to. However, it has moreover raised concerns, approximately the security and astuteness of that information. In arrange to address these concerns and make beyond any doubt that information put away on untrusted cloud servers remains solid and unaltered Remote Data Integrity Verification (RDIV) frameworks have ended up significant. This term paper presents a mapping think about of Inaccessible Data Integrity Confirmation frameworks within the setting of cloud computing. Its objective is to distinguish existing investigate categorize it reveal patterns and shed light on regions for inquire about. In the digital landscape, the Internet of Things (IoT) has created new opportunities and challenges as everyday objects are becoming interconnected, collecting large volumes of data. We interact with our surroundings and manage data in a whole new way thanks to cloud computing and IoT, which work in symbiotic harmony. Data generated by IoT devices can be harnessed and processed using cloud computing's robust infrastructure. Furthermore, IoT expands the reach of cloud computing to include a myriad of smart devices, sensors, and actuators that are all interconnected. By conducting a search handle, we have assembled a collection of inquire about papers and scholarly articles that particularly center on RDIV frameworks in cloud computing. These distributions were carefully analyzed utilizing incorporation and prohibition criteria to classify the Remote Data Integrity Verification frameworks based on their fundamental methods cryptographic strategies utilized, confirmation instruments utilized and sending models connected. By synthesizing the comes about, this paper highlights current investigate trends and gives experiences into potential inquire about crevices within the field of Remote Data Integrity Verification frameworks for cloud computing. We talk about the require for upgraded scalability and execution optimization to bolster large-scale cloud arrangements successfully. Besides, we recognize the require for assist investigation of privacy-preserving Remote Data Integrity Verification procedures to ensure sensitive information from unauthorized introduction.
Enhancing Security and Efficiency through QR Integration with Hybrid AES-ECC Algorithm in Mobile Apps for Cardless Data Transactions

&nbsp;To improve and facilitate transactions between customers and financial institutions, the utilization of Internet banking has been leveraged to deliver a heightened caliber of service characterized by heightened security and efficiency in contrast to traditional banking modalities. It is suggested in this research introduces an innovative security framework, designed to furnish a protected mechanism ensuring secure communication, authentication, confidentiality, and safeguarding of financial transactions between banking institutions and end-users, all without necessitating reliance on a physical card. The fundamental underpinning of this proposed system involves the amalgamation of a Quick Response (QR) code with a hybridized Advanced Encryption Standard-Elliptic Curve Cryptography (AES-ECC) model. Following the successful installation of the security application on the mobile device, and subsequent to an accomplished registration and encryption of data inputs, encoding and decoding processes are facilitated through the intrinsic encoding and decryption keys embedded within this hybrid algorithm. The clientele receives a QR code containing encrypted transaction details, and upon scanning this code via the designated Android application, the pertinent information is promptly displayed. Empirical assessments validate the effectiveness of the suggested approach, demonstrating superior outcomes when juxtaposed with prevailing methodologies.
A Federated Unsupervised Personalisation for Cognitive Workload Estimation

Accurate Cognitive Workload (CW) estimation, crucial in mobile healthcare and human-machine interaction, is impeded by client heterogeneity, data limitations, and privacy concerns, especially in the presence of Out-of-Distribution (OoD) clients. This study proposes a robust framework that is based on Federated Learning to protect data privacy, and utilizes context-based STRNet to enable joint cross-user learning on heterogeneous datasets, enhancing model generalisability. The framework includes a novel Unsupervised Client Personalisation strategy that prevents accuracy loss in OoD clients. We tested our framework on two publicly available CW datasets, COLET and ADABase. The framework improved the accuracy of centralized approaches while preserving data privacy. The framework is model-agnostic, efficient, and enables unsupervised personalisation for each client, bolstering the quality and robustness of the end-to-end deep learning models.
First Responders' Take on Technology: A Deep Dive into Mobile and AR Interface Preferences.

In an exploratory investigation into interface preferences among first responders, this study examines the usability of mobile and augmented reality (AR) interfaces among a mixed group of firefighters and paramedics. While prior studies predominantly assessed XR interfaces for civilian and single-domain user groups, this research is novel in its comparative analysis of two distinct professional groups. Through a combination of a 20-question survey and expert interviews, findings reveal a general preference for mobile interfaces over AR. Notably, firefighters highlighted the potential of AR when integrated into their protective gear, while paramedics leaned towards the practicality of mobile interfaces. This nuanced understanding of user needs underscores the importance of tailored technology solutions in emergency services.
VirtuSign: An AI-Powered, Gamified Virtual Reality Application for the American Sign Language Alphabet

American Sign Language (ASL), an essential communication tool for the deaf and hard of hearing, has long relied on traditional teaching methods that may not fully leverage the potential of modern technology. Recognizing this gap, this paper introduces VirtuSign, an innovative solution that merges virtual reality (VR) with advanced gesture recognition to revolutionize ASL instruction. VirtuSign offers a tailored VR experience, immersing users in a gamified environment where they can interactively learn and practice signing the ASL alphabet. Enhanced by state-of-the-art artificial intelligence algorithms, the tool identifies and assesses user gestures in real-time through hand-tracking capabilities available in modern VR headsets, providing immediate feedback and corrections.
Decoding Optimization Algorithms for Convolutional Neural Networks in Time Series Regression Tasks

Optimization algorithms play a vital role in training deep learning models effectively. This research paper presents a comprehensive comparative analysis of various optimization algorithms for Convolutional Neural Networks (CNNs) in the context of time series regression. The study focuses on the specific application of maximum temperature prediction, utilizing a dataset of historical temperature records. The primary objective is to investigate the performance of different optimizers and evaluate their impact on the accuracy and convergence properties of the CNN model. Experiments were conducted using different optimizers, including Stochastic Gradient Descent (SGD), RMSprop, Adagrad, Adadelta, Adam, and Adamax, while keeping other factors constant. Their performance was evaluated and compared based on metrics such as mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), R-squared (R²), mean absolute percentage error (MAPE), and explained variance score (EVS) to measure the predictive accuracy and generalization capability of the models. Additionally, learning curves are analyzed to observe the convergence behavior of each optimizer. The experimental results, indicating significant variations in convergence speed, accuracy, and robustness among the optimizers, underscore the research value of this work. By comprehensively evaluating and comparing various optimization algorithms, we aimed to provide valuable insights into their performance characteristics in the context of time series regression using CNN models. This work contributes to the understanding of optimizer selection and its impact on model performance, assisting researchers and practitioners in choosing the most suitable optimization algorithm for time series regression tasks.
Beyond the Hype: A Proposed Model Based on Critical Analysis of Blockchain Technology’s Potential to Address Supply Chain Issues

This paper explores the proposed solutions based on blockchain technology's potential to solve supply chain management issues. The problems include lack of traceability and transparency, scalability and cost issues, sustainability, efficiency, patchwork logistics, and bullwhip effect issues. In this paper, we have suggested some solutions with the help of blockchain technology. The solutions can solve multiple significant issues in supply chain management. Our blockchain-based solutions can provide a secure and visible record of all transactions and data along the supply chain, which can improve traceability and transparency, a decentralized and efficient method of data processing and exchange that can also increase scalability and reduce cost, a transparent and accountable way to track and verify sustainability-related data. Our method can enable more streamlined and automated tracking and data sharing, helping to reduce the risk of delays and inefficiencies while mitigating the risk of the bullwhip effect by providing real-time visibility and enabling better communication and collaboration between parties. The paper discusses the implications and challenges of implementing blockchain in supply chain management.
Memory Enhancer Games: A General-purpose Game-based Intelligent Tutoring System

Students of today are exposed to technologies that are either educationally effective or distractive. Most of them are having a hard time learning in a traditional classroom setup, are easily distracted, and have difficulty remembering lessons just learned and prerequisite skills needed in learning new lessons. Game-Based Intelligent Tutoring System (GB-ITS) is a technology that provides an individualized learning experience based on student’s learning needs. GB-ITS mimics a teacher doing one-on-one teaching, also known as tutoring, which is more cost-efficient than human tutors. This study developed a general-purpose Memory Enhancer Games system, in a form of a GB-ITS. This study was conducted at Calasiao Comprehensive National High School, identified the game type that best enhances memory and the game features for this proposed system through a questionnaire by (9) ICT teacher respondents. The developed system in this study has undergone validity testing by (8) ICT teachers and professors from Schools Division I of Pangasinan, and of a University in Dagupan City, and acceptability testing by (100) senior high school students of Calasiao Comprehensive National High School, 1st semester of school year 2022-2023, using Likert scale to determine its appropriateness as an intelligent learning tool. The results of the game design questionnaire confirmed the studies of which elements were ideal for a GB-ITS, and both the validity and acceptability survey questionnaires with overall weighted means of 4.57 and 4.08, show that the system is a valid and acceptable intelligent learning tool. The developed MEG can also be of use for testing game features for educational effectiveness and can also contribute to any future study which will conduct to test whether a general-purpose GBL or GB-ITS model would compare; if won’t equal the effectiveness of GBLs designed for delivering specific contents or subjects.
PERMUTATION POLYNOMIALS IN ONE INDETERMINATE OVER MODULAR ALGEBRAS

Known results about permutation polynomials in connection with coefficients in a finite field extend to algebras of the form Lv = K[X]/(p(X)v)\), where K is a finite field,(p(X) ∈ ‍ K[X] is an irreducible polynomial, and v = 1,2,..., and to the algebra of power series L[[Z]], where L = K[X]/(p(X)). Analogues of Dickson polynomials are also studied in this context.
Analysis and design of UI and UX of the Taring application using goal-directed design and cognitive walkthrough methods

Taring is a web-based application used for online administrative services for both Indonesian citizens and foreign nationals in the field of population administration. It is published by the Denpasar Population and Civil Registration Office. The taring application was released on June 8, 2020, and includes features such as managing Family Cards, e-IDs, Change of Residence Letters, and Legalization. Analysis and evaluation of the Taring application are necessary to improve usability, quality of use, and the provided information. This is achieved through the utilization of the Goal-Directed Design method and the Cognitive Walkthrough method in its process. The employed analysis and design method is Goal-Directed Design, which focuses on designing and developing interactive systems to make them more useful, with a focus on the diverse goals of the users. The evaluation methods used are the Cognitive Walkthrough and the System Usability Scale questionnaire, which assess usability and the application's usage based on observations of the users. The results of the Cognitive Walkthrough testing revealed 20 issues related to user interface and user experience, while the research findings indicated an increase in effectiveness and efficiency. The research also demonstrated an improvement in usability using the System Usability Scale method, with the score rising from 50.8 (E) to 88.9 (A).
The Control of reflectance and Transmittance of glass using External Magnetic Field and Sound Waves Through Electrical Permittivity

Optical properties of matter are important in solar cells and smart windows design. The properties like reflection and transmition are very important in these applications. Therefore, this work is concerned with studying these properties using Maxwell’s equations. Using the expression of reflection and transmition coefficient useful relations were found. It was found that complete transmittance occurs when one applies a strong magnetic field. While applying an appropriate magnetic field leads to complete reflection and generation of amplified light in a direction normal to the incident one.&#x0D; Also, the thermal radiation can be reflected completely by applying sound wave having a certain frequency. &#x0D;
The Role of Teachers in Developing Poetry Reading Skills at SDIT Cordova 3 Class 4

This research is motivated by the researcher's observations regarding the role of teachers in developing poetry reading skills in class 4 at SDIT Cordova 3. The purpose of this research is to obtain information or an overview of the role of teachers in developing poetry reading skills carried out by SDIT Cordova 3 with the hope of good results. achieved by grade 4 students. This research uses qualitative research using a descriptive approach method by obtaining data from interviews, observation and documentation. Based on the research results, there are several difficulties experienced by students, including lack of self-confidence and lack of motivation. To solve this problem, SDIT Cordova 3 uses the demonstration method so that learning becomes more active and fun.
Analysis of Learning Difficulties in Reading and Writing in Class III Students at SDN Batok Bali

This research was motivated by the researcher's observations regarding difficulties in learning to read and write among students in class III which occurred at SDN Batok Bali. This research aims to obtain information or a clear picture of how difficult it is to learn to read and write which is carried out at the SDN Batok Bali school with the learning outcomes achieved by class III students. The research population included all class III students consisting of one class with 41 students. This type of research is qualitative research using a descriptive approach research method, where data collection uses interview, observation and documentation techniques. Based on the results of this research, several difficulties experienced by students were found, including: (a) Difficulty recognizing letters when reading, (b) Difficulty with spelling and unclear reading pronunciation among students, (c) Many errors in reading among students, (d) Difficulty distinguishing several letters when writing, (e) Lack of letters when writing words, (f) The time required to write is too long, and several solutions that can be done to overcome difficulties in learning to read and write in students that have been found in class III at SDN Batok Bali.