Reviewerly/exHarmony huggingface dataset:
How Current Chatbots Applications Impact Education: An Overview

The implementation of chatbots in multiple platforms with which man interacts has allowed automating processes and being able to respond to requests, one of its applications is the educational field, where they are still experimenting with good results in some areas and in others analyzing their feasibility, the deployment of this technology has been used both in basic education and in higher education, the former mainly addresses the resolution of simple queries facilitating the work of the teacher, and the latter seeks to go further by offering itself as a learning assistant. This work focuses on understanding the impact that chatbots have on education and their integration in some areas of the educational process, analyzing the results offered by other research and real applications. Chatbots have proved to be effective and increase user efficiency by providing information and being a support, evaluation, and follow-up tool. They have even shown favorable results in several learning levels, being a source that centralizes information without the need for the user to access multiple sources to learn a subject or to monitor the level of learning of students or their own.
Metamorphic Cryptography Using Concept of Spiral Transposition and LSBs Approach Using Audio as Carrier Medium

Increasing digital communication over the internet has raised concerns related to information security. Cryptography and steganography are the two primary concepts that security researchers practice. Security researchers also practice hybrid approaches that are based on cryptography and steganography. This paper presents the idea that was based on a hybrid approach. For performing the encryption, the spiral transposition approach was used. To hide this encrypted message, the least significant bit substitution approach was used. The audio was chosen as a carrier medium. The paper also discusses the strength of various metamorphic methods. It was well established that there is still a scope of techniques that can overcome existing approaches’ limitations while simultaneously ensuring information security's primary objectives. The proposed work in this presented paper was an effort in this direction.
Towards Development of a Security Risk Assessment Model for Saudi Arabian Business Environment Based on the ISO/IEC 27005 ISRM Standard

Security risk assessment refers to the process of identifying, analyzing, and evaluating potential security risks for an organization.An organization's assets, personnel, and operations are protected through it as part of a comprehensive security program.Various security assessments models have been published in the literature to protect the Saudi organization's assets, personnel, and operations.However, these models are redundant and were developed for specific purposes.Hence, the comprehensive security risk assessment model used to safeguard Saudi organizations' assets, personnel, and operations is still omitted.Using a design science methodology, the objective of this study is to develop a comprehensive security risk assessment model called CSRAM to assess security risks in Saudi Arabian organizations based on the International Organization for Standardization and the International Electrotechnical Commission/Information security risk management (ISO/IEC 27005 ISRM) standard.CSRAM is made up of six stages: threat identification, vulnerability assessment, risk analysis, risk evaluation, risk treatment, and monitoring and review of the risk.The stages have many activities and tasks that need to be accomplished at each stage.Based on the results of the validation of the completeness of the CSRAM, we can say that the CSRAM covers the whole ISO/IEC 27005 ISRM standard, and it is complete.
Prior Guided Face Super Resolution Using Convolution LSTM

Face Super-Resolution (SR) is the process of restoring a high-resolution (HR) face image from a low-resolution (LR) input. Numerous deep learning-based face SR models utilized the facial prior to super-resolved the input images. They estimate facial prior from the LR input, which may be inaccurate and thus causes them to learn the incorrect facial details. Therefore, this paper presents a prior guided model in which deep features are retrieved by utilizing the Convolution LSTM layers to develop a high-quality super-resolved face image. Also, the coarse SR image is used to approximate the parsing map prior and concatenated with the coarse image, which results in improving the quality of the output HR face images. The proposed model attains better quantitative as well as qualitative scores as compared to existing SR models.
Brainstorming Game Technologies in the Teaching Practice of Higher Education Institutions

The article deals with the psychological and pedagogical foundations of using intellectual brainstorming didactic games in training professionals in different fields of study at higher education institutions. According to the principle of hidden didacticism, the concept of the universal and assisting type of intellectual games has been suggested – for the improvement of students' learning outcomes and for the forming of soft skills, team building, and optimization of personal and personal and collective professionally respective decision-making strategies as well. Based on the personal pedagogic experience of the authors in teaching non-related – medical and philological disciplines and on the empirical material of completed didactically neutral intellectual games, their efficiency in forming different types of competencies has been analyzed – common background knowledge, professional knowledge, and team-based soft skills.
Overview of Applications for the Development of Logical Thinking of Children of Primary School Age

The article sheds light on the problem of developing logical thinking of primary school students through the use of digital technologies, namely, mobile applications. A general overview of popular mobile applications that contribute to the productive development of logical thinking of elementary school students is conducted. It is analyzed how exactly mobile applications affect the educational activity of students, as well as what place mobile applications occupy at the current stage of information technology development. The degree of popularity of mobile applications and the level of their development are considered. It is analyzed how mobile learning (M-learning) affects the development of students' cognitive activity. Advantages and disadvantages of mobile learning in education are considered and characterized. Some applications that can be used during training are presented. Analyzed mobile applications, with low technical requirements, which are a powerful tool for studying digital technologies that are used in the world and take education to a new level, providing productive learning of the necessary knowledge. The article highlights which mobile applications have the potential to influence the development of logical thinking. It was studied how applications allow children to solve logical problems, puzzles, games, which directly affect the development of critical and spatial thinking, train memory and attention, and develop motor skills. Considered how mobile applications expand the capabilities of the teacher and serve as an excellent tool for the development and improvement of students' skills.
Design and Realization of Block Level Augmented Reality Three-Dimensional Map

In response to the construction needs of "Real 3D China", the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed.Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map.The augmented reality three-dimensional map is produced based on skyline software.Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized.The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map.Those lay the groundwork for the application of augmented reality three-dimensional map.
Features of the Centers of Academic Success in US Universities

The article reviews the peculiarities of Academic Success Centers (ASC) in US universities. In this regard, the concept of "student success" was analyzed, it was found that this concept is directly related to academic achievements, in particular, academic success. There is no single definition of the term "academic success center" in scientific discourse today. This is related to the academic autonomy of higher education institutions, which independently determine the range of services and support programs for students in such centers. A study of the practices of the best private and public universities in the United States showed that most of these institutions of higher education have centers of academic success in their structure. These structural subdivisions direct their activities, first of all, to ensure academic support and retention of the student contingent of the educational institution. It was found that the main technologies for supporting the academic success of students are tutoring, academic coaching and mentoring. Special attention is payed on interaction with students of the first year of study (freshmen), who most often face a number of problems in a new academic environment for them (adaptation to new conditions, change of lifestyle, choice of profession, new acquaintances). Centers for academic success provide an opportunity not only to learn, but also to teach. Senior students have the opportunity to become tutors, mentors and academic coaches. Such practice allows them to strengthen their own knowledge base, acquire new skills and take the first step in your career. Another feature of academic success centers is conducting career guidance work with applicants. Universities specially organize meetings of future freshmen with students, graduates, teachers and administration of the institution to provide complete information about admission, studies and further employment prospects. Attention is paid to the development of university campus culture and the involvement of education seekers in student communities. Providing socio-psychological support is one of the important areas of activity of centers of academic success, because it is important for students to develop self-awareness, self-confidence in order to become independent and fully reveal their academic, professional and personal potential. The conducted study actualized the need for a thorough research of the basic principles of the areas of activity of centers of academic success in US universities in order to introduce better experience into the educational practice of domestic universities.
Model Selection via Automated Machine Learning

Automated machine learning extends the search space to include hyperparameters and algorithm selection. We apply automated machine learning (AutoML) to cross sectional stock return prediction with factors. We formulate factor dimension reduction and hyperparameter tuning in conventional ML method as the model selection problem. we show that the optimal model improves the out-of-sample performance upon all the machine learning method implemented alone. The investment strategies generated by AutoML demonstrate significant improvements in terms of Sharpe ratio and Alpha. In addition, AutoML outperforms ensemble models. Compared to traditional machine learning, automated machine learning optimizes model parameters and chooses function forms within different families of machine learning models, providing a better fit for time-varying pricing rules.
Arbitrage Opportunities and Efficiency Tests in Crypto Options

For liquidity providers in the rapidly-growing crypto options market as well as potential institutional investors in crypto options, we test the joint efficiency of the bitcoin options and perpetual futures markets, and likewise for ether, and identify the frequency and magnitude of arbitrage opportunities. We introduce the necessary (fiat-currency-free) put-call parity relationship, including transaction costs, and thereafter develop a variety of strong and weak arbitrage boundaries for crypto option prices. Novel empirical analysis concludes that both bitcoin and ether derivatives markets are broadly evolving to a more efficient state. Longer-dated options (with maturity ≥ 15 days) are notable in that their price efficiency has improved very significantly over time. Bitcoin markets are more efficient than ether and efficiency of both markets shifts closely with prices of perpetual futures. Hence, periods of extreme volatility can result in highly profitable arbitrage opportunities.
A Data Set of Final Year High School Examination Texts of South African Home and First Additional Language Subjects

This article describes a data set of reading comprehension and summary writing texts that were used in final-year high school examinations in South Africa between 2008 and 2020. It contains texts for eleven official South African languages. PDF versions of the texts stem from South Africa&rsquo;s Department of Basic Education&rsquo;s online public access repository. Plain text is extracted from the PDFs and the texts are tokenized. The data set contains 429 full-text files with 929 manually extracted comprehension and summary writing texts. The data is useful for studies investigating, e.g., linguistic properties, text readability, text properties, and linguistic complexity in any of the eleven languages. Furthermore, both intra-language and inter-language comparisons or investigations can be made.
An Unconventional Look at a Historical Monograph. Analysis with Artificial Intelligence (AI) Tools

Goal and theses: The article aims to check the applicability of methods based on processing large sets of information in research in social sciences.&#x0D; Conception/research methods: The dynamic development of new research methods based on the automated processing of large data sets using artificial intelligence (AI) means that they are used in an increasingly wide range of disciplines, going beyond the field of exact and natural sciences. Text mining was combined with available CLARIN web applications and keyword extraction and analysis strategy, a combination of the YAKE! written in Python with the VOSViewer program for the visualisation of bibliometric networks.&#x0D; Results and conclusions: The study showed how automatic keyword extraction creates opportunities in social science research. The use of CLARIN and Google Pinpoint web tools in the analysis significantly facilitates working with a large body of texts and accelerates its analysis.&#x0D; Cognitive value/originality: The study indicates new research methods that can contribute to the development of social sciences. The perspectives for the implementation of the ways of dealing with large data sets are presented in work in research on society, and conclusions regarding the development of digital social sciences are formulated.
Incidental language and culture learning through mobile technologies: a multi-case study

Abstract Incidental learning is a human learning paradigm that takes its form as a response to unplanned initiatives, potentially occurring at any time and at any place. It is emerging as very promising in the case of learning a second language, as it multiplies the occurrence of unexpected and unintentional learning situations. Still open, and subject of debate, is the issue of which is the right methodology to be applied when mobile computer-based technologies are exploited to provide support to such kind of a learning paradigm. Drawing on the results of an international Project (ILOCALAPP), in this paper we provide our reflections on a specific incidental learning methodology we have adopted, based on the use of a mobile application (the UniOn! App) that was developed at the University of Bologna to support mobility students in their daily activities. Our main goal was to understand if such an approach was effective to let individuals incidentally learn the Italian language and culture driven by our mobile application, while conducting informal and daily activities. Specifically, we aimed to measure how much students have learned Italian, by means of self-evaluation and self-assessment tools and statistical analysis, involving 95 students who incidentally improve their Italian language skills, supported by the app. In particular, we adopted a quasi-experimental design, and we focused our investigation on four different dimensions: target users, users’ language background, duration and frequency of use, context of use. The 95 participants were grouped into 5 case studies, based on the four different dimensions. After having used the app, the participants were asked to answer a survey. The obtained results confirm the viability of our approach, showing that incidental learning is enhanced if certain conditions (i.e., integrated guidance) are met, where more than 55% of the participants reported to be more confident about their acquired skills.
CLASSICAL DETERMINATE TRUTH I

Abstract We introduce and analyze a new axiomatic theory $\mathsf {CD}$ of truth. The primitive truth predicate can be applied to sentences containing the truth predicate. The theory is thoroughly classical in the sense that $\mathsf {CD}$ is not only formulated in classical logic, but that the axiomatized notion of truth itself is classical: The truth predicate commutes with all quantifiers and connectives, and thus the theory proves that there are no truth value gaps or gluts. To avoid inconsistency, the instances of the T-schema are restricted to determinate sentences. Determinateness is introduced as a further primitive predicate and axiomatized. The semantics and proof theory of $\mathsf {CD}$ are analyzed.
HIGHER MATHEMATICS IN TECHNICAL UNIVERSITIES TAKING INTO ACCOUNT THE DIRECTION OF PREPARATION

The article discusses the problems arising in the implementation of mathematical training of bachelors and masters in technical areas that meet the requirements of the time in terms of digitalization of education, including the use of computer technology
Survey-scale discovery-based research processes: Evaluating a bespoke visualisation environment for astronomical survey data

Next generation astronomical surveys naturally pose challenges for human-centred visualisation and analysis workflows that currently rely on the use of standard desktop display environments. While a significant fraction of the data preparation and analysis will be taken care of by automated pipelines, crucial steps of knowledge discovery can still only be achieved through various level of human interpretation. As the number of sources in a survey grows, there is need to both modify and simplify repetitive visualisation processes that need to be completed for each source. As tasks such as per-source quality control, candidate rejection, and morphological classification all share a single instruction, multiple data (SIMD) work pattern, they are amenable to a parallel solution. Selecting extragalactic neutral hydrogen (HI) surveys as a representative example, we use system performance benchmarking and the visual data and reasoning (VDAR) methodology from the field of information visualisation to evaluate a bespoke comparative visualisation environment: the encube visual analytics framework deployed on the 83 Megapixel Swinburne Discovery Wall. Through benchmarking using spectral cube data from existing HI surveys, we are able to perform interactive comparative visualisation via texture-based volume rendering of 180 three-dimensional (3D) data cubes at a time. The time to load a configuration of spectral cubes scale linearly with the number of voxels, with independent samples of 180 cubes (8.4 Gigavoxels or 34 Gigabytes) each loading in under 5 minutes. We show that parallel comparative inspection is a productive and time-saving technique which can reduce the time taken to complete SIMD-style visual tasks currently performed at the desktop by at least two orders of magnitude, potentially rendering some labour-intensive desktop-based workflows obsolete.
Development of the Android-Based Educational Game Media “Perjalanan Si Maya” as a Formative Assessment to Improve Critical Thinking Skills and Interest in Learning Science for Elementary School Students

Objective: This research aims to develop an android-based educational game media, "Perjalanan Si Maya," as a formative assessment to improve critical thinking skills and interest in learning elementary school students. Method: This research is a type of development research (R&amp;D). The development method used in this research is ADDIE (Analyse, Design, Development, Implementation, and Evaluation). Results: The results showed that the development of an android-based educational game media, "Perjalanan Si Maya," as a formative assessment was declared valid based on acquiring the very valid category. The result of practicality is classified as very good (very practical). The result of effectiveness Based on N-Gain, the mean value of the control class obtained a mean value in the "less effective" category. In contrast, the experimental class obtained a mean value in the "moderately effective" category. The results of student learning interest have increased from before learning to after learning using educational game media “Perjalanan Si Maya. Novelty: Teachers can carry out formative assessments through educational games to train students' critical thinking skills and interest in learning to become more qualified, effective, and efficient.
Point cloud-based scene flow estimation on realistically deformable objects: A benchmark of deep learning-based methods

Flow estimation on 3D point clouds is a challenging problem in the field of computer vision, which has great significance in many areas, such as autonomous driving and human interaction applications. Within the last years, the field of motion analysis has made great progress. The evaluation of the existing approaches mostly focuses on scenarios where objects are affected by rigid transformations. However, in many application areas such as gesture recognition or pose tracking, the detection of shape changes is essential and breaking them down to local rigid transformations is accompanied by loss of information. One component of our contributions is that we specifically prepared existing datasets for scene flow estimation on deformable objects. Additionally, we benchmark existing methods and analyze their behavior on various subtasks. The results show that already close to 80% of correct correspondences can be found on synthetic hand data, while only around 50% are found on real hand data. Our experimental validation and analysis help to build an understanding of new possibilities in broader areas. Furthermore, they should help to inspire possible further research directions.
Analysis of audit methods for high security cross-region video conference

The persistence of the epidemic has made inter-regional teleconferencing one of the main ways for organizations to work. As a special information system, the conventional auditing method can not cover the key points of information security of video conference service. Therefore, this paper analyzes the characteristics of organization video conferencing services, and analyzes a special audit method for high security cross-region video conferencing services. This method includes pre-meeting, mid-meeting and post-meeting behavior audit, and designs a variety of data models to support comprehensive audit analysis. Secondly, it puts forward two key audit items of abnormal meeting and illegal meeting, which provides a comprehensive and practical business behavior audit method for high-security organization video conference services.