Reviewerly/exHarmony huggingface dataset:
Impressions on the incorporation of Kahoot in the university virtual classroom

The objective of this study was to know the impressions about the incorporation of Kahoot in the virtual classroom to strengthen the teaching-learning of Mexican university students. It is approached from a qualitative perspective through the application of a questionnaire of open-ended questions to students of the undergraduate degree in Administrative Computer Systems at the Universidad Veracruzana. The evidence indicates that the incorporation of tools with playful activities as part of the class sessions allows maintaining the interest and motivation of the students, generating a favorable environment for learning.
Students’ Perception of Distance Learning During COVID-19 Pandemic

The article investigates university students' perception of the distance learning during the COVID-19 pandemic. The authors surveyed 211 undergraduate students (ages 18–22) in different years of study at the Schools of Special Education of Yaroslavl State Pedagogical University named after K. D. Ushinsky to find out their level of satisfaction with distance learning. Participants were asked to evaluate various aspects of distance learning related to students' motivation for taking courses, the subjective difficulty of the courses and their suitability for online mode, and instructors' professional qualification and readiness for remote teaching. The survey data were used to establish significant statistical differences (Student's t-test) and correlations (Spearman's ρ-coefficient) between various parameters influencing students' perception of the online courses. Based on the correlation analysis of various factors, the authors suggest emphasizing the following aspects while creating and teaching an online course: novelty of the course content, its significance for professional development and career, clear structure and coherent presentation of the course content, carefully crafted sequence of assignments. It is highly recommended to consider creating an out-of-class space (online platform) where the students can communicate with the instructors and each other.
Using quantum computing to create efficient algorithms

Abstract The article presents a historical overview of the development of the mathematical idea of a quantum computing model - a new computational strategy based on the postulates of quantum mechanics and having advantages over the traditional computational model based on the Turing machine; clarified the features of the operation of multi-qubit quantum systems, which ensure the creation of efficient algorithms; the principles of quantum computing are outlined and a number of efficient quantum algorithms are described that allow solving the problem of exponential growth of the complexity of certain problems.
Data-Driven Gearbox Fault Severity Diagnosis Based on Concept Drift

Condition-based maintenance aims to determine the machine state in real time, by monitoring the signals it emits. Such signals are potentially unlimited, generated at a high rate, and can evolve over time. These conditions tend to produce changes in the distribution of the data, known as concept drift. This phenomenon is analyzed and used to establish changes in the state of the machine. The present article proposes a methodological framework for the diagnosis of fault severity based on concept drift. A parsimonious unsupervised algorithm based on KNN is proposed to detect concept evolution. The results show that the algorithm is quite effective in declaring a concept evolution that is associated with a change in the failure condition of the machine. Finally, the results show that there is a high correlation between the displacement of the centroids of the emerging concepts and the % of deterioration of the machine.
On theories of names and references in formal languages and implications for functional and object-oriented programming

The long-standing problem of adequate formalization of local names in mathematical formulae and semantics of references in object-oriented languages taken “as is” without objects, is discussed. Reasons why the existing approaches cannot be considered suitable solutions, are explained. An introduction to the relatively recent works on the theories of names and references of the group headed by Andrew Pitts, is given. The notion of referential transparency, in which contextual equivalence is used instead of the usual equality of values, is analyzed. This is the main property, which these theories are based upon: it is preserved when a purely functional language is extended with names and references as data. It is argued that such referential transparency, along with many others, can be preserved for mutable objects that change to a limited extent. This leads to a model of computation between functional and object-oriented ones, allowing for a deterministic parallel implementation.
Designing a Chatbot System for Recommending College Students to Counseling and Collecting Dialogue Data

In Japan, the number of college students suffering from changes in the communicative environment due to the COVID-19 pandemic is increasing. However, many college students do not use on-campus counseling services even though they are available. The reason for this is students’ psychological barriers to counseling. Therefore, we designed a chatbot to reduce the psychological barrier and recommend counseling services to college students. We defined dialogue tasks for maintaining mental health, i.e., lifelogging, confiding, and recommending counseling services. We also defined the required and optional slots for each dialogue task. We used crowdsourcing to collect an example dataset of ideal dialogues between chatbots and users. From the collected data, we categorized the chatbot's responses and design a task- and slot-based response-selection method that is based on Aspect-based Sentiment Analysis.
Development of Sandbox English Conversation Training Applications with Atomic Design

This paper presents the development of a sandbox with atomic design to overcome the difficulty of developing features and harmonizes the design of an English conversation practice application. Our idea to implement a sandbox with atomic design in an English conversation practice application is how the sandbox can be used to maintain and continue the development of an English conversation practice application in a more organized manner and with the same principles as the application development rules. We implement sandbox development with an atomic design architectural model. The initial application system breakdown process begins to evaluate component consistency, then to determine the token value or design variable. After the breakdown process, we redesigned the UI using token variables, then compile it with an atomic design approach to create a complex interface composed of simple parts or vice versa. After the design process, we implement the application UI using atomic design UI design into components, then projected in the sandbox. Inside the sandbox, we isolate components for testing, documentation, and validation. The result of the component after going through the sandbox, we launch it as an application component. We created the system that we propose with the aim of providing a process flow so that managers have the same perception in application development as well as space for managers to be able to strengthen the system or feature before it is launched so that development problems are resolved properly. In a performance test, atomic design was able to accelerate page generation production by 49.9% and reduce interaction costs by 72.7%.
ESXi on Arm on Pi Use Cases

ESXi on Arm running on a Raspberry Pi is a low-cost entry point into the world of virtualization and VMware, but, as we discussed in the previous chapter, its hardware does limit what this setup can do. This said, it is still able to accomplish some remarkable feats for something so small. In this chapter, we’ll take a look at use cases for ESXi on Arm on Pi, some of which are actively being used, while others less so. Some are simple uses that I’ve seen for this setup but have not actually tried myself.
Searching business information in digital information systems of Russian libraries

The author continues with her study initially presented in the article “The possibilities of information search in electronic platforms of Russian libraries” (A. V. Kulikova. The possibilities of information search in electronic platforms of russian libraries // The Journal of Encyclopaedic Studies. – 2019. – No 2. – P. 30–52). She demonstrates the methods to be applied for business information search related to local encyclopaedic book publications and identifies the principles to find recent publications promptly and to satisfy user demands most effectively. The bibliographic search success depends upon how the user understands the system. Optimum query formulation saves time and excludes information noise. The key characteristics of library digital information retrieval systems are discussed. The computer systems of 113 regional libraries were analyzed within the study. The following automated library information were tested objectively: IRBIS, RUSLAN, OPAC-Global, Foliant, MacWeb. The author does not intend to advertise or subvertise any ALIS. Her main goal is to reveal the convenient and speedy retrieval methods with existing functionalities.
Optimal path decision algorithm based on data fusion

In this paper, an optimal path decision algorithm based on data fusion is proposed to solve the problem of trajectory trajectory modeling in Coal Mine Geographic information system due to missing locating points. Firstly, multiple paths satisfying time by using the K-shortest path algorithm are found out. Then, the time matching degree and travel habits of these paths are fused. Finally, the path with the largest fusion value is chosen as the supplement of the optimal path points. The experimental analysis shows that the algorithm can effectively find the optimal path under different conditions.
Clothoid curve optimization for parallel parking path planning and tracking control

Abstract In order to solve the problem of abrupt curvature change at the connection between arcs and straight lines in circle-line-circle (C-L-C) combined parallel parking paths, curvature optimization was carried out by using a cycloid curve, and the trajectory curvature and heading Angle were made to meet the pose requirements of parallel parking. By establishing the kinematics model state equation and taking the optimized C-L-C trajectory as the reference trajectory, the error model was obtained. The model predictive controller based on the error model was designed, and the effectiveness of the path planning and model predictive controller was verified on Carsim and Matlab/Simulink co-simulation platform.
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty

Since the rise of deep learning, many computer vision tasks have seen significant advancements. However, the downside of deep learning is that it is very data-hungry. Especially for segmentation problems, training a deep neural net requires dense supervision in the form of pixel-perfect image labels, which are very costly. In this paper, we present a new loss function to train a segmentation network with only a small subset of pixel-perfect labels, but take the advantage of weakly-annotated training samples in the form of cheap bounding-box labels. Unlike recent works which make use of box-to-mask proposal generators, our loss trains the network to learn a label uncertainty within the bounding-box, which can be leveraged to perform online bootstrapping (i.e. transforming the boxes to segmentation masks), while training the network. We evaluated our method on binary segmentation tasks, as well as a multi-class segmentation task (CityScapes vehicles and persons). We trained each task on a dataset comprised of only 18% pixel-perfect and 82% bounding-box labels, and compared the results to a baseline model trained on a completely pixel-perfect dataset. For the binary segmentation tasks, our method achieves an IoU score which is 98.33% as good as our baseline model, while for the multi-class task, our method is 97.12% as good as our baseline model (77.5 vs. 79.8 mIoU).
Optimization to the Rescue

Recent work suggests that it may be possible to determine the author of a binary program simply by analyzing stylistic features preserved within it. As this poses a threat to the privacy of programmers who wish to distribute their work anonymously, we consider steps that can be taken to mislead such analysis. We begin by exploring the effect of compiler optimizations on the features used for stylistic analysis. Building on these findings, we propose a gray-box attack on a state-of-the-art classifier using compiler optimizations. Finally, we discuss our results, as well as implications for the field of binary stylometry.
Broadening the scope of error categories in translation assessment through screen recording

Abstract To date, the assessment of student translations has been largely based on configurations of error categories that address some facet of the translation product. Focal points of such product-oriented error annotation include language mechanics (punctuation, grammar, lexis and syntax, for example) and various kinds of transfer errors. In recent years, screen recording technology has opened new doors for empirically informing translation assessment from a more process-oriented perspective (Massey and Ehrensberger-Dow, 2014; Angelone, 2019). Screen recording holds particular promise when tracing errors documented in the product back to potential underlying triggers in the form of processes that co-occur on screen in their presence. Assessor observations made during screen recording analysis can give shape to process-oriented error categories that parallel and complement product-oriented categories. This paper proposes a series of empirically informed, process-oriented error categories that can be used for assessing translations in contexts where screen recordings are applied as a diagnostic tool. The categories are based on lexical and semantic patterns derived from a corpus-based analysis of think-aloud protocols documenting articulations made by assessors when commenting on errors made in student translations while watching screen recordings of their work. It is hoped that these process-oriented error categories will contribute to a more robust means by which to assess and classify errors in translation.
Achieving Privacy and Security Using QR-Code through Homomorphic Encryption and Steganography

Security is a most concerning matter for client's data in today's emerging technological world in each field, like banking, management, retail, shopping, communication, education, etc. Arise in cyber-crime due to the black hat community, there is always a need for a better way to secure the client's sensitive information, Security is the key point in online banking as the threat of unapproved online access to a client's data is very significant as it ultimately danger to bank reputation. The more secure and powerful methods can allow a client to work with untrusted parties. Paper is focusing on how secure banking transaction system can work by using homomorphic encryption and steganography techniques. For data encryption NTRU, homomorphic encryption can be used and to hide details through the QR code, a cover image can be embed using steganography techniques.
Stability of Dependencies of Contingent Subgroups with Merged Groups: Vaccination Case Study

The answers to extreme phenomena both in nature and in business sectors are the constructions of the distribution of random variables with extreme values. Another area in which appropriate theoretical research is conducted regarding the influence of suppressor (third) variables in categorical data. When examining dependencies in PivotTables, we often find it necessary to merge data into larger sets (e.g., due to a greater number of theoretical frequencies lower than their critical value). A phenomenon many exist wherein the partial relation is stronger than the zero relation. For example, in such a combination, instability may occur, which indicates contingent subgroups with the merged group. The dependence of dependencies is practically manifested because the data of contingent subgroups indicate inconsistent (inverted) conclusions compared to the associated group. For this reason, this paper aimed to find the critical ratios of partial probabilities in the contingency table of subgroups of the original variables, and to determine the conditions of result consistency and contingency stability, including the proof. For practical use and for the ease of repeating the proposed procedure, the solution is based on a case study that compares the effectiveness of vaccination.
A Consortium Blockchain-Based Platform for Academic Certificate Verification

Academic certificates have a great impact on the job market as they are considered an indicator of the bearer’s capability. Therefore, individuals or companies are trying to falsify their certificate information or even produce fake certificates. Until now, there is no efficient way to verify academic credentials in Vietnam. There is no centralized point for academic certificate verification and only a few educational institutions offer an online verification system. If there is such a system, the information provided may not be very reliable due to the mutable characteristic of the traditional database system used in the developed systems. There are also a small number of systems that use blockchain technology to improve the trustworthiness of verifications. However, most of them have been developed for use by individual institution which makes verification inconvenient. Therefore, this study proposes a consortium blockchain-based academic certificate verification platform that allows educational institutions to join the system to enable centralized verification and make verification more convenient. The system prototype was developed based on the Hyperledger Fabric, NodeJS, and AngularJS framework that provides the essential functions of a typical certificate verification system. The system evaluation with Hyperledger Caliper also shows the feasibility of the proposed model.
SHORE: Hardware/Software Method for Memory Safety Acceleration on RISC-V

Memory corruption vulnerabilities can lead to software attacks. Pointer-based memory safety protection has been shown as a promising solution covering both out-of-bounds and use-after-free errors. Software only approaches have significant performance overhead. Existing hardware/software implementations are largely limited to proprietary closed-source microprocessors, simulation-only studies or require changes to the input source code.In this paper, we present a novel hardware/software co-design methodology consisting of a RISC-V based processor extended with new instructions and microarchitecture enhancements, enabling faster memory safety checks. A compiler is instrumented to provide security operations taking into account the changes to the processor. The entire system is realized by enhancing a RISC-V Rocket-chip system-on-chip (SoC) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . The resultant processor SoC is implemented on an FPGA and evaluated with applications from SPEC 2006 (for generic applications), MiBench (for embedded applications), and Olden benchmark suites for performance. Our experiments show that the proposed approach achieves up to 3. 79X speedup (average 2. 6X) in comparison to the traditional software-based approach for SPEC2006 while possessing an overhead of 6.33% in terms of area. This speedup is better than the state-of-the-art approach. Our security coverage using the NIST Juliet test suite shows better coverage than the software only method.
The asymmetric effect of internet access on economic growth in sub-Saharan Africa

This article investigates the asymmetric effect of internet access (index of the internet) on economic growth in 42 sub-Saharan African (SSA) countries over the period 2008-2018. The estimation procedure is obtained following a dynamic panel threshold regression technique via 1000 bootstrap replications and the 400 grids search developed by Hansen (1996, 1999, 2000). The investigation first explores the presence of inflection points in the relationship between internet access and economic growth through the application of Hansen's threshold models. The finding from the nonlinearity threshold model revealed a significant internet threshold-effect of 3.55 percent for growth. The article also examines the linear short-run effect of internet access on economic growth while controlling for the effects of private sector credit, trade openness, government regulation, and tariff regimes. The marginal effect of internet access is evaluated at the minimum, and the maximum levels of government regulation and tariffs regime are positive. On the other hand, the minimum and maximum levels of private sector credit and trade openness are negative via the interaction terms. The article advances the literature by its nonlinear transformation of the relevance of internet access on economic growth by exploring interactive mechanisms of: internet access versus financial resource, internet access versus trade, internet access versus government regulation, and internet access versus the tariff regimes from end-user subscriptions. In policy terms, the statistical significance of the joint impact of government regulations and tariff regimes is relevant in the operation of the telecommunication industry in SSA countries.
A Novel Principal Component Analysis Based Fragile Watermarking Technique for Sensitive Dataset

One of the leading concerns for the cumulative group of content creators, editors, media forensics, military networks and medical communities, is the effective attestation of digital media. With the exponential growth in technology, especially in the field of image processing, mishandling of computerized images has become increasingly customary. Additionally, the tampered images look inconceivably close to the originals. The process is not only quick but also effortless and, in most cases, quick and hassle-free. There exists a provocative need to come up with a streamlined technique to not only confront these difficulties but more importantly, aid in their resolution. Content confirmation, copyright assurance, and insurance are some of the most potent techniques that can help to tackle these perils that exist in the field of computerized data. One such strategy that holds precedence is ‘Computerized picture watermarking’. The watermark information is introduced into a picture. Later on during attestation, the same information is either removed or identified in the watermarked item.The premise of this paper revolves around the use of PCA (Principal component analysis) for watermarking an image dataset. PCA is a machine learning algorithm. The watermarking is done in the projection space, i.e. Eigenvectors. The entire process relies on the effective use of ‘picture pixels’. By controlling the pixel esteems, the watermark can be embedded. In order to maintain the originality of the dataset images, the watermark used is exceedingly fragile. Medicine and forensics serve as the primary market for the deployment of such technique.