Reviewerly/exHarmony huggingface dataset:
Exploring predictors affecting quality control in higher education using AHP and Random forest

The purpose of this study is to explore predictive factors that affect quality control in higher education using random forest and AHP based on Higher Education Information Disclosure discosure data. Three research questions were investigated: 1) What is AHP model derived from the analysis of previous studies and literature review? 2) What is relative weight of each variable calculated through AHP? 3) What is a predictive model of quality management in Higher Education derived through random forest? To answer these questions, this study conducted literature review, AHP survey, and random forest analyses. The results of this study showed that the input AHP model constructed 5 factors, 31 indicators and the output AHP model constructed 2 factors, 11 indicators. Secondly, the AHP analysis indicated that the most important input variables were ‘educational restitution rate’, ‘cost of education per student’, and ‘retention rate of full-time faculty’. and the output variables with the highest global importance were ‘employment rate’ and ‘recruitment rate’. Finally, the results of random forest based on the AHP results showed that all target variables, excluding ‘employment rates’, were influenced by the ‘amount of governments financial program’, ‘educational restitution rate’, and ‘cost of education per student’. ‘Employment rate’ was related to ‘percentage of industry full-time faculty’, ‘filed training curriculum’, and ‘percentage of full-time faculty’.
A Study on the Symposium for Improving University Students' Communication Skills

This study is intended to reveal that it is possible to strengthen selfdirected class backhaul and cooperative learning communication capabilities through examples of symposium discussion classes using PBL. As for the research method, 64 college students in Chungcheongnam-do were trained as expert groups through discussions using PBL for five weeks, and symposiums were conducted by learners who became expert groups. Results, evaluation reports, and problem-solving reports of groups that became expert groups were submitted in the process of training expert groups using PBL, and symposiums could be conducted based on this report. Through this, learners' self-directed and communication skills were strengthened. In the process of training expert groups using PBL, it was confirmed that learners can cultivate self-directed teaching and communication skills through collaboration, and through symposiums, interpretation and solutions vary depending on the perspective of the same phenomenon. Through this, learners were able to expand their thinking and develop an exploratory attitude.
High-order spatial phase shift method realizes modulation analysis through a single-frame image

For the modulation-based structured illumination microscopy system, how to obtain modulation distribution with an image has been a research hotspot. However, the existing frequency-domain single-frame algorithms (mainly including the Fourier transform method, wavelet method, etc.) suffer from different degrees of analytical error due to the loss of high-frequency information. Recently, a modulation-based spatial area phase-shifting method was proposed; it can obtain higher precision by retaining high-frequency information effectively. But for discontinuous (such as step) topography, it would be somewhat smooth. To solve the problem, we propose a high-order spatial phase shift algorithm that realizes robust modulation analysis of a discontinuous surface with a single-frame image. At the same time, this technique proposes a residual optimization strategy, so that it can be applied to the measurement of complex topography, especially discontinuous topography. Simulation and experimental results demonstrate that the proposed method can provide higher-precision measurement.
Practical randomness amplification and privatisation with implementations on quantum computers

We present an end-to-end and practical randomness amplification and privatisation protocol based on Bell tests. This allows the building of device-independent random number generators which output (near-)perfectly unbiased and private numbers, even if using an uncharacterised quantum device potentially built by an adversary. Our generation rates are linear in the repetition rate of the quantum device and the classical randomness post-processing has quasi-linear complexity – making it efficient on a standard personal laptop. The statistical analysis is also tailored for real-world quantum devices. Our protocol is then showcased on several different quantum computers. Although not purposely built for the task, we show that quantum computers can run faithful Bell tests by adding minimal assumptions. In this semi-device-independent manner, our protocol generates (near-)perfectly unbiased and private random numbers on today&amp;apos;s quantum computers.
Virtual Reality and Augmented Reality in Education

Abstract: This paper’s objective is to show a framework for the VR and AR-based combined learning materials. VR and AR objects can stay incorporated into other educational material as by establishing effective education programmes, learning events, or other kinds of learning activities, learning objects can indeed be created. This essay reviews the study on both augmented and virtual reality and analyses holistic application techniques for the educational process. The proposed model supports the authors' findings and yields suggestions for its use.
THE CONCEPT OF HUMAN CAPITAL AND ITS PLACE IN PEDAGOGY

The first foundation of human capital is the ability to understand whether professional competence is suitable or invalid for the quality of value, to be able to constantly ask questions and classify what they can and cannot do. Human psychology in the Soviet era has undergone a complete transformation, the intellectualization of its capital and the process of paradigmatic analysis of the benefits and disadvantages of orders and changes in society. At the same time, the essence of the formula of «matter», «time», «space» in the three corners of Pythagoras is to determine the dependence of material value on time and space, and to create its scientific basis. «Time» - 24 hours, how many of these 24 hours are spent sleeping, bathing, eating, working, resting. He proved in accordance with the science of logic that a person who does not take this into account is a prisoner of 100 percent of rarity. Our main goal is to create conditions for students to capitalize their knowledge and scientific intuition through psychological and pedagogical disciplines. One of the most pressing issues today is the formation and development of human capital from a pedagogical and psychological point of view. This topic analyzes the concept of modern human capital by reviewing research in the history of pedagogy.
Inspection Digital Literacy for School Improvement

Educational inspection, as an essential part of the current educational environment, supports its mission through more pragmatic and comprehensive processes, techniques, and models, which guarantee the right of students to quality education. The aim of the present study was to determine the causal effect of gender and age on the dimensions of the instrument in the inspector population. Specifically, 118 male and female inspectors from the Educational Inspection Service of Andalusia (Spain) participated, with an average age of 47.56 years (±5.70). In terms of gender, 30 were women (25.40%) and 88 were men (74.60%). An instrument was developed specifically for this study with the purpose of assessing the participants’ opinions of the extent to which their work contributes to educational improvement. The results evidenced the relationship between the dimensions of the instrument: attention to members of the educational community (AMEC), supervision of guidance and tutorial action (SGTA), attention and inclusion of diversity (AID), and technological resources (TR) (p &lt; 0.01). Similarly, the multigroup model obtained good structural validity (χ2 = 68.180; RMSEA = 0.078; GFI = 0.923; CFI = 0.959; IFI = 0.967). In terms of gender, no significant differences were obtained, although the results were moderately superior among males compared to females. In relation to age, younger inspectors had better TR results, and older inspectors had better AMEC and SGTA results. The conclusions strengthen the importance of the Education Inspection Service in educational establishments, highlighting the need to supervise the processes of attention and inclusion for diversity. A great deal of resistance was observed, especially as there is a lack of training in information and communication technology (ICT).
Speech Files Cryptography using Indices Keys and Blocking

Protecting speech file is a vital issue. In this paper research a simple method of speech cryptography will be introduced. The method will use indices key to perform simple replacement operations to apply speech encryption and decryption, the replacement operation will use the indexes and the indexes contents to apply speech cryptography. The proposed method will protect the speech signal by increasing the security level, the method will use a color image as an image_key, this key will be kept in secret between the sender and receiver and it will be used to generate the indices key. The proposed will sensitive to the selected image_key, changing this image will be considered as a hacking attempt by producing a damaged decrypted speech signal. The proposed method will be flexible, changing the image_key will not cause any changes in the proposed method algorithms. To increase the efficiency of the proposed method by decreasing the processing time the speech file will be divided into blocks, and each block will be treated separately. The proposed method will be tested and implemented using various speech files, the obtained results will be used to prove the quality, sensitivity and efficiency of the proposed method.
Image Measurement Attribute Extraction Method under Large Error Condition

Abstract In recent years, the rapid development of image processing based on deep learning has had a wide impact on industrial production and social life. In the field of information security, image content description as a kind of attribute has been used in authentication, access control and other technologies. In addition to describing what is in an image, fine-grained image content properties should also be able to express the relative size and position relationships between objects. Due to the strong fuzziness of the relative scale between objects in the image, it is not suitable for precise definition. This paper proposes a method to extract measurement attributes under large error to describe the relative size of two parts in an image. Based on image classification and object detection, the error range is estimated by statistical method, and a fuzzy set is constructed as the length unit. Then the contradictory critical points of measurement are used to determine the comparable scale range and similar regions. Finally, the measurement attribute of image content is given. Experiments show that the size description obtained by this method accords with people’s subjective feelings, and can effectively extract the fine-grained attributes of the image.
SATVSR: Scenario Adaptive Transformer for Cross Scenarios Video Super-Resolution

Abstract Video Super-Resolution (VSR) aims to recover sequences of high-resolution (HR) frames from low-resolution (LR) frames. Previous methods mainly utilize temporally adjacent frames to assist the reconstruction of target frames. However, in the real world, there is a lot of irrelevant information in adjacent frames of videos with fast scene switching, these VSR methods cannot adaptively distinguish and select useful information. In contrast, with a transformer structure suitable for temporal tasks, we devise a novel adaptive scenario video super-resolution method. Specifically, we use optical flow to label the patches in each video frame, only calculate the attention of patches with the same label. Then select the most relevant label among them to supplement the spatial-temporal information of the target frame. This design can directly make the supplementary information come from the same scene as much as possible. We further propose a cross-scale feature aggregation module to better handle the scale variation problem. Compared with other video super-resolution methods, our method not only achieves significant performance gains on single-scene videos but also has better robustness on cross-scene datasets.
Tandem: A discontinuous Galerkin method for sequences of earthquakes and aseismic slip on multiple faults using unstructured curvilinear grids

&amp;lt;p&amp;gt;Seismic cycle modeling has advanced to the point where 3D models could be connected to geodetic and seismic observations to test hypotheses about controls on the depth and along-strike extent of ruptures, and interactions between seismic and aseismic slip events in geometrically complex fault systems. Such an undertaking does however require a greater degree of geometrical flexibility, material behaviors, code performance, and community participation than has so far been the standard.&amp;lt;br /&amp;gt;&amp;lt;br /&amp;gt;In this light we present tandem, an open-source C++ code for 3D earthquake sequence modeling (Uphoff et al., 2022a). Tandem solves the elasticity problem with a discontinuous Galerkin finite element method on unstructured tetrahedral meshes. It can handle multiple, nonplanar faults and spatially variable elastic properties (Figure 1). The method can be extended to nonlinear off-fault material response (e.g., power-law viscoelasticity). The code is parallelized with MPI and uses the PETSc-TAO library (Balay et al., 2022) for time-integrators and preconditioned Krylov methods to solve the static elasticity problem. Faults are governed by rate- state friction and adaptive time-stepping permits modeling of dynamic rupture, the postseismic period, and interseismic loading, all across multiple earthquake cycles. The code is developed with best practices for open-source community software and includes documentation and tutorials to facilitate use by the community (github.com/TEAR-ERC/tandem).&amp;lt;br /&amp;gt;&amp;lt;br /&amp;gt;Uphoff, C., D. A. May, and A.-A. Gabriel (2022a), A discontinuous Galerkin method for sequences of earthquakes and aseismic slip on multiple faults using unstructured curvilinear grids, Geophysical Journal International.&amp;lt;br /&amp;gt;Balay, S., et al. (2022), PETSc/TAO users manual, Tech. rep., Argonne National Lab., Argonne, IL, USA (petsc.org/).&amp;lt;/p&amp;gt;
Decentralized E-KYC Blockchain Network for Central Bank

Abstract: Know Your Customer or KYC processes are the backbones of a financial institution’s anti-money laundering efforts. KYC processes are mandatory in most of Europe and India. Almost all countries have their own process for identifying and keeping a record of their citizens like the USA has Social Security Protocol. According to current estimates, the amount of KYC spending rose to up to $1.8 Billion in 2021 on a global level. Despite the importance of the process, KYC continues to operate inefficiently. KYC processes are labor-intensive and time-consuming tasks. It is estimated that 80% of KYC efforts go in gathering information and processing while only 20% of efforts are evaluating and monitoring focused. This centralization of data is causing an inefficient KYC process and creating issues like :- Misidentification of fraudulent data , Inability of tracking customers, customers entering fake data(address, age etc) , delayed processing time and very high cost of processing. Reimagining KYC Using Blockchain Technology will enable seamless and secure data exchange at a fraction of the cost. A decentralized blockchain network will Facilitate near real-time data exchange. Blockchain when used with other technologies can indicate great potential to help organizations reduce the cost and time linked with the KYC process. The introduction of blockchain in KYC brings data on a decentralized network which also has its own pros like distributed data collection ,higher operational efficiency , validation of accuracy of the information. The customer will build their profile on the DCT KYC network. There are multiple options to store the data like Centralized encrypted servers, DCT platforms like IPFS(Interplanetary File System). Customers will perform transactions with Financial Institutions by giving them access to users profile( restricted non-appendable access),Using hashing and cryptographic processes the data would safely be called and returned to the DCT network . Thus making sure the whole process is immutable .
Activity Recognition System for Smart Campus

Abstract: Long video data resulted from the use of cameras lab activities as a action recording. We present a new framework for recognizing student activities from the class. In this system we improve intelligent mechanism, top low level motion detection algorithm and feature extraction. We recognize the frame difference and feature selection for human activities that permits recognition. The detection of human activity from videos is very complicated appropriate to the complex reality of events, the situation in which activities took place, the require of available size of abnormal ground truth training data and other factors correlated to environmental disparity, light conditions and the working position of the captured cameras. The objective of this paper is to research and inspect machine and deep learning techniques by using videos for recognition of students lab activities . The importance has been on a variety of activity detection systems with machine learning techniques as their prime move toward
Promote proportional reasoning through digital technology

This article explores alternative teaching methods that promote proportional reasoning in Mexican students aged fourteen to fifteen using digital technology. To this end, a sequence of didactic activities has been designed to give meaning to the concepts of ratio and proportion in their different representations from the approach of linear functions. For the design of the tasks, elements of the theory of Realistic Mathematics Education and the Didactics of Cuevas-Pluvinage were used, coinciding with several didactic points. The proposed learning objectives and activities have been organized through a hypothetical learning trajectory. The analysis and detailed evaluation of the responses allowed us to identify: the didactic advantages of the design, the learning difficulties, and the vital role played by technology in the learning process.
Community Detection by Node Betweenness Using Optimized Girvan-Newman Cuckoo Search Algorithm

Due to technological development, social media platforms like forums and microblogs allow people to share their experiences, thoughts, and feelings. The organization, shopping groups etc. has major discussions regarding their business advertisements and product reviews. Also, there are certain followers for particular person or group due to their interests. Here the major issue is to know who or which group in social media is more influenced. The social media analysis needs to perform for identifying influenced person in the social media. The influencer node/person detection in a certain community is already done using greedy algorithm, genetic algorithm, ant colony optimization, cuckoo search algorithms. These existing techniques takes more time for diffusion and accuracy in prediction is not satisfied by users. To overcome this issues, in this research influencer node is identified using optimized Girvan Newman Cuckoo Search Algorithm (GNCSA). First Grivan Newman is used to identify the community and perform community detection. Cuckoo search algorithm uses host bird strategy in finding cuckoo eggs in his nest. Based on the centrality measure it decides whether the node is an influencer or not. This paper proposed Influencer detection by forming community first and measures angular centrality using optimized Girvan Newman cuckoo search algorithm. Our proposed work GNCSA gives a better accuracy rate for the data sets of Dolphin 0.89, for Facebook dataset got 0.93, Twitter data set got 0.94 and for YouTube data set 0.92, karate club and football got 0.91. This proposed work increases the intracommunity of the social network and improves its performance accurately by detecting the influencer in the social network.
Resource reduction in multiplexed high-dimensional quantum Reed-Solomon codes

Quantum communication technologies will play an important role in quantum information processing in the near future as we network devices together. However, their implementation is still a challenging task due to both loss and gate errors. Quantum error-correcting codes are one important technique to address this issue. In particular, the quantum Reed-Solomon codes well suited to communication tasks as photons can naturally carry more than one qubit of information. The high degree of physical resources required, however, makes such a code difficult to use in practice. A recent technique called quantum multiplexing has been shown to reduce resources by using multiple degrees of freedom of a photon. In this work, we propose a method to decompose multicontrolled gates using fewer controlled-x ($\mathrm{CX}$) gates via this quantum multiplexing technique. We show that our method can significantly reduce the required number of $\mathrm{CX}$ gates needed in the encoding circuits for the quantum Reed-Solomon code. Our approach is also applicable to many other quantum error-correcting codes and quantum algorithms, including Grovers and quantum walks.
Medical image encryption using multi chaotic maps

Over the last twenty years, chaos-based encryption has been an increasingly popular way to encrypt and decrypt data using nonlinear dynamics and deterministic chaos. Discrete chaotic systems based on iterative maps have gotten a lot of interest because of their simplicity and speed. In this paper, three kinds of chaotic maps are utilized to build a digital image encryption strategy depending on a chaotic system. These chaotic maps are the logistic map, Arnold Cat’s map, and Baker’s map. In addition to using the triple data encryption standard (3DES) encryption scheme with the chaotic maps mentioned. The results of the experiments revealed that the suggested digital image encryption technique is both efficient and secure, making it ideal for usage in insecure networks. The transmission control protocol (TCP)/internet protocol (IP) protocol was used for the purpose of transferring data from server to client through the network and vice versa.
Graduate student perspectives on online teaching of writing

The aim of this study is to characterize the gra¬duate student perspectives on a virtual dialogic teaching initiative oriented to the revision of dissertation chapters written by the students themselves. Within an exploratory qualitative study in-depth interviews are taken with 12 stu-dents from three seminar editions. The analy¬sis shows three relevant categories regarding online dialogic teaching of writing: time ma¬nagement, synchronous exchange and digital technologies. There are three senses of the tem¬poral dimension: times relative to the seminar schedule, to the student daily life, and to the in¬tellectual process of writing practices. Further-more, a combination of heavy asynchronous load with synchronous encounters is valued. Re¬garding the technologies, the students generate environments that take advantages of devices’ technological potential based on the physical environment possibilities and also value the pedagogical relevance of the applications. The category properties show some changes of gra¬duate writing, and its dialogic teaching in the digital world.