Reviewerly/exHarmony huggingface dataset:
Error Analysis and Accuracy Optimization for the Hand-eye Calibration of Line Structured Light

Abstract The rapid development of machine vision technology in recent years has resulted in applications in engineering scenarios such as weld tracking, visual measurement, and precision gripping. Focusing on the fundamental steps of applying machine vision technology, the “hand-eye calibration” process is analyzed based on scenarios with a line-structured light camera and calibration ball. We found out that noise and camera pose are the main sources of calibration error. To address these issues, an improved K-medoids noise pre-processing algorithm and a camera shooting attitude control scheme are proposed and applied. The experimental results showed that when the radius of the tangent circle/radius of the calibration sphere approximates 0.618, the root means a square error of the repeatability accuracy of hand-eye calibration could be controlled within 0.23 mm, which fully meets the application requirement. Considering the low cost of line-structured light cameras, the findings of this study contribute to the large-scale diffusion of machine vision technology in engineering practices.
Underwater image quality assessment

To obtain high-visual-quality underwater images by image post-processing, many underwater image restoration and enhancement methods have been proposed. Underwater image quality assessment (UIQA) methods have been developed to compare these restoration and enhancement methods. This paper comprehensively summarizes the subjective and objective UIQA methods, metrics, and datasets. Experiments are conducted on two underwater image datasets to analyze the performance of several typical UIQA metrics. Suggestions for further research directions are put forward as well.
MANIFESTATION OF EMOTIONAL ANXIETY IN STUDENTS

The manifestation of emotional anxiety among students, in particular, during exams, is considered. Techniques for overcoming anxiety are described
COMMUNITY MANAGEMENT IN A HIGHER EDUCATIONAL INSTITUTION

The article systematizes information about the concept of community management, its appearance in Russia and the possibility of using its principles to organize communities in higher education institutions. The author differentiates the tasks of community management in online and offline formats, which requires the university administration to involve different specialists for the or-ganization of communities
PREVENTION OF CORRUPTION IN THE STUDENT SPHERE

The concept of corruption in the system of higher education is considered. The measures aimed at preventing corruption in universities are listed. The practice of anti-corruption work among students at the Angarsk State Technical University is given
ENDOWMENT IN RUSSIAN UNIVERSITIES

The article discusses the concept of an endowment, highlights its stages. Based on the analysis of the experience of the formation of the endowment capital of Russian higher educational institutions, the difficulties encountered by the participants are formulated
DEVELOPMENT OF A MOBILE APP BASED ON ANDROID OS FOR INTERACTION OF STUDENTS AND PROFESSORS

In the course of the work, a mobile messenger application is being developed for the possibility of remote interaction between students and professors. Application development is carried out in the Android Studio development environment for mobile devices running the Android operating system
FORMATION OF COMMUNICATIVE COMPETENCE IN THE PROCESS OF TEACHING FOREIGN LANGUAGES AT SCHOOL

The article deals with one of the current issues of modern methods of teaching foreign languages – communicative competence. The author distinguishes three stages of the formation of communicative competence
DEVELOPMENT OF MOBILE APPLICATIONS USING THE QT FRAMEWORK

The paper discusses the process of developing a full-fledged mobile application (developing an interface using QML, using the functionality of the mobile platform using the QT Framework modules, building and testing the project, obtaining an APK file for distributing the application) using QT products such as "QT Creator" and "QT Framework", based on the C++
ABOUT MODELING BOOLEAN FUNCTIONS BY NEURAL NETWORKS

A neural network of perceptrons is constructed, modeling a Boolean function of four variables
A crowd clustering prediction and captioning technique for public health emergencies

The COVID-19 pandemic has come to the end. People have started to consider how quickly different industries can respond to disasters due to this public health emergency. The most noticeable aspect of the epidemic regarding news text generation and social issues is detecting and identifying abnormal crowd gatherings. We suggest a crowd clustering prediction and captioning technique based on a global neural network to detect and caption these scenes rapidly and effectively. We superimpose two long convolution lines for the residual structure, which may produce a broad sensing region and apply our model's fewer parameters to ensure a wide sensing region, less computation, and increased efficiency of our method. After that, we can travel to the areas where people are congregating. So, to produce news material about the present occurrence, we suggest a double-LSTM model. We train and test our upgraded crowds-gathering model using the ShanghaiTech dataset and assess our captioning model on the MSCOCO dataset. The results of the experiment demonstrate that using our strategy can significantly increase the accuracy of the crowd clustering model, as well as minimize MAE and MSE. Our model can produce competitive results for scene captioning compared to previous approaches.
E-BiT: Extended Bio-Inspired Texture Descriptor for 2D Texture Analysis and Characterization

This paper presents an extended bio-inspired texture (E-BiT) descriptor for image texture characterization. The E-BiT descriptor combines global ecological concepts of species diversity, evenness, richness, and taxonomic indexes to effectively capture texture patterns at local and global levels while maintaining invariance to scale, translation, and permutation. First, we pre-processed the images by normalizing and applying geometric transformations to assess the invariance properties of the proposed descriptor. Next, we assessed the performance of the proposed E-BiT descriptor on four datasets, including histopathological images and natural texture images. Finally, we compared it with the original BiT descriptor and other texture descriptors, such as Haralick, GLCM, and LBP. The E-BiT descriptor achieved state-of-the-art texture classification performance, with accuracy improvements ranging from 0.12% to 20% over other descriptors. In addition, the E-BiT descriptor demonstrated its generic nature by performing well in both natural and histopathologic images. Future work could examine the E-BiT descriptor’s behavior at different spatial scales and resolutions to optimize texture property extraction and improve performance.
Measuring 3- and 4-Moduli Sets Delay Per Bit in Residue Number System: A Survey

Given the efficiency of the residue number system in high-speed and low-power applications, a wide variety of moduli sets have been introduced in the literature. Selecting an appropriate moduli set is one of the most important issues of using a residue number system. Moduli sets can be evaluated by several factors such as dynamic range, balanced channels, fast and low-power modular operations, and efficient reverse converter. In this paper, 3- and 4-moduli sets are separately reviewed and compared from a different perspective. Furthermore, the most efficient 3- and 4-moduli sets are suggested. A new parameter for average delay comparison is introduced, which shows the delay of every bit in the dynamic range providing a fair comparison of moduli sets with different numbers of moduli. Our comparison showed that either balanced channels or the delay of computations are essential factors for designing an efficient new moduli set.
A randomness device to create the conditions of uncertainty

The experimental study of decision-making under uncertainty typically builds on Ellsberg-type settings. Yet, as the total number of balls is known in standard Ellsberg’s urns, an implicit constraint is put on the specification of the probability models to consider. In practice, this restricts the ability of Ellsberg’s urns to characterize situations going beyond those of model ambiguity. In this note, I present a simple and easy-to-implement device that creates the initial conditions of uncertainty, which constitute a critical prerequisite for the study of model misspecification.
Formulaicity of fictional quotative<i>ga itteta</i>and its functions in Japanese social media posts

Abstract Relatively longer formulaic sequences are often subject to syntactic, lexical, and semantic variability, and this variability presumably connects to the development of constructional schemata and to language creativity. The present paper focuses on the formulaicity, variation, and communicative effects of the quotative phrase X ga itteta ‘X was saying’ in Japanese social media posts, whose situation would become fictional or less factual depending on the nature of the subject X . Twitter data suggest that X ga itteta with certain subjects (e.g., high school girls, cats, moms; see below) is more conventionalized compared to the counterpart Y-tte itteta ‘was saying that Y’, where Y is a quoted statement, with the same subject. Additionally, the construction accepts variation of surrounding elements to raise its fictional level. In Japanese online platforms, the schema X ga itteta and its formulaic instances possibly distance the quoter from the quoted statement and avoid arguments and criticisms.
Virtual Reality Methods. A Guide for Researchers in the Social Sciences and Humanities. PhilJones and TessOsborne with CallaSullivan‐Drage, NatashaKeen and EleanorGadsby, Bristol, 2022: Bristol University Press, Policy Press, 158 pp., ISBN 978‐1‐4473‐6075‐9 hardcover, 978‐1‐4473‐6077‐3 ePdf, 978‐1‐4473‐6076‐6 ePub.

Tijdschrift voor Economische en Sociale GeografieEarly View Book Review Virtual Reality Methods. A Guide for Researchers in the Social Sciences and Humanities. Phil Jones and Tess Osborne with Calla Sullivan-Drage, Natasha Keen and Eleanor Gadsby, Bristol, 2022: Bristol University Press, Policy Press, 158 pp., ISBN 978-1-4473-6075-9 hardcover, 978-1-4473-6077-3 ePdf, 978-1-4473-6076-6 ePub. Claudia van der Laag Yamu, Corresponding Author Claudia van der Laag Yamu [email protected] orcid.org/0000-0002-2847-4975 Oslo Metropolitan UniversitySearch for more papers by this author Claudia van der Laag Yamu, Corresponding Author Claudia van der Laag Yamu [email protected] orcid.org/0000-0002-2847-4975 Oslo Metropolitan UniversitySearch for more papers by this author First published: 03 May 2023 https://doi.org/10.1111/tesg.12558Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. References Bergvall, V.L. (2020), Essentialism, Empathy, and Economics in Silicon Valley: A Feminist-Vigilant Critical Discourse Analysis. In: P. Sotirin, V.L. Bergvall & D.L. Shoos, eds., Feminist Vigilance, pp. 165– 192. Cham: Springer. Robertson, A. (2021), Three Big Questions About Facebook's New VR Ads. Available at <https://www.theverge.com/2021/6/17/22537349/facebook-vr-oculus-quest-ads-privacy-questions-analysis> [Accessed 29 March 2023]. Szpak, A., S.C. Michalski & T. Loetscher (2020), Exergaming with Beat Saber: An Investigation of Virtual Reality Aftereffects. Journal of Medical Internet Research 22(10), p. e19840. Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation
Commas as a constructional resource: the use of a comma in a formulaic expression in Japanese social media texts

Abstract This paper examines the use of punctuation in Japanese in order to investigate its role in formulaic expressions. Specifically, we will study the use of a comma before the copula complex dakedone at the end of an utterance. Typically, punctuation is considered a matter of style in written representations and is generally not included in studies about the structure of formulaic expressions. However, in a corpus-based study on language use on social media (e.g., blogs, Twitter, online forums), we found that this comma is frequently used for a distinct pragmatic effect. The patterns of use, both structural and functional, are observed to be regular and predictable, enough to suggest that the comma is part of a fixed formal complex that has a unique meaning, i.e., a construction. This in turn suggests that commas, even though they are punctuation, can be a formal resource that constitutes part of a formulaic expression.
Selection of Digital Watermarking Techniques for Medical Image Security by Using the Fuzzy Analytical Hierarchy Process

Background: The watermarking technique is a security algorithm for medical images and the patient's information. Watermarking is used for maintaining the robustness, integrity, confidentiality, authentication, and complexity of medical images. Objective: The selection of medical image watermarking technique is multi-criteria decision-making and an automatic way of algorithm selection for security and privacy. However, it is difficult to select a better watermarking technique through traditional selection techniques. Methods: To deal with this problem, a multicriteria-based fuzzy analytic hierarchy process (FAHP) was proposed. This method is applied for algorithm selection for the security of medical images in healthcare. In this method, we first determined the list of criteria and alternatives, which directly affect the decision of the medical image security algorithm. Then, the proposed method was applied to the criteria and alternatives. Results: We provided the rank according to the obtained weights of the algorithm. Furthermore, the overall results and ranking of the algorithms were also presented in this article. Conclusion: Integrity was found to have the highest weight (0.509) compared to the other criteria. The weight of the other criteria, namely authentication, was 0.165, robustness was 0.151, confidentiality was 0.135, and complexity was 0.038. Thus, in terms of ranking, integrity was reported to be of the highest priority among the five criteria attributes.
MENTORSHIP AND TEACHING CAREER TRAINING

The paper presents the results of a qualitative study carried out -PROF" (POCU/904/6/25/146587) focused on the critical-reflexive analysis of the perceptions of mentor teacher trainers, students of the Prof I training program regarding the experience of their training and the values shared as mentor teachers. Trainers' training for the teaching career mentorship aimed to complete an up-to-date continuous training program, well-articulated, and structured on six topics. These are as follows: teaching career mentorship - from concept to action; elements of adults' education and the teaching career mentorship -values, principles, and characteristics; planning the mentoring activity; the management of the teaching career mentorship process; counselling for training and professional development in the teaching career mentorship, and assessment and validation of professional teaching skills. The conclusions of the study highlight the personal conceptions of the mentor teacher trainers participating in the study as regards the role and the importance of teaching career mentorship to ensure the quality of the work of novice teachers and of teachers who are in professional evolution. Moreover, it focuses on the skills and qualities required for the teaching career mentorship, supported by relevant examples from mentor teachers' teaching experience.
Styling Classification of Group Photos Fusing Head and Pose Features

Group photo images are everywhere and vary greatly by the shooting scene. Compared with common images, the Image Aesthetic Quality Assessment (IAQI) of group photo pays more attention to the relevant characteristics of the main population. Still, the existing methods do not make further special research on group photos. Therefore, we propose a new concept of group photo styling based on analyzing group photos and photographic theory. Besides that, by comparing and analyzing many group photos, we classify the group photos into five categories. In this paper, the main factors of the head and pose are considered simultaneously, and the method of Group Photo Styling Classification (GPSC) can classify different group photos automatically. To verify the effectiveness of our method, we collected a Group Photo Styling Dataset (GPSD). The dataset contains 998 group photo images, and each image’s group photo styling category is marked. The experimental results on GPSD show that the fusion of head features and pose features can classify different group photos well. The accuracy of GPSC reaches 93.9%, much higher than the previous classification model.
‘Relatively civilized, relatively European’: Offence and online (de)normalization of media racism

The paper explores the interplay of offence, (de)normalization and moral conflict triggered by media racism. The paper is premised on the assumption that public interventions to moral transgressions occasion moral conflicts in which transgressions can be (de)normalized through impoliteness, more specifically the acts of offence taking and causing. A YouTube video discussing the racist media coverage of the Ukrainian refugee crisis was analyzed along with a sizable amount of related user-generated comments. The analysis showed that offence taking and offence causing have morally restorative and (de)normalizing functions in moral conflict. This highlights the fact that the relationship between morality and impoliteness is much more complex than is usually theorized, wherein impoliteness is often perceived as a morally norm-disruptive behavior or a negatively valenced evaluation thereof. Not only can impoliteness be morally justified in moral conflicts, it can also be a necessary form of restorative public intervention. This necessitates greater attention to (de)normalization in (im)politeness theorizing.
Triply invertible scarf sewing adventures (and instructions)

AbstractWe provide relevant math and detailed sewing instructions for constructing a toroidal scarf that reverses three ways and whose design uses the unique inversion properties of a particular torus geometry and particular 3-component link. We explain how the scarf’s sewing instructions are guided by the mathematics underlying its construction.KEYWORDS: Torustopologyknot theorylinkstorus knotsinversiontoroidal scarfMöbius scarffibre artssewing AcknowledgmentsWe would like to thank the editors and anonymous reviewers for their many helpful suggestions. The torus knot images in Figures 9 and 20 were produced using Robert Scharein’s KnotPlot (1998–2023), which is a marvellous tool. Thank you to Kent Christman for helping diagnose the misstep the first time Ellie tried to sew a (1,1) torus knot seam on a rhombus layout, and for his excellent active listening in general.Disclosure statementNo potential conflict of interest was reported by the author(s).
Deep learning for denoising High-Rate Global Navigation Satellite System data

High-rate global navigation satellite system (HR-GNSS) data records ground displacements and can be used to identify earthquakes and slow slip events. One limitation of such data is the high amplitude, cm-level noise which make it difficult to identify processes that produce surface displacements smaller than these values. Deep learning has proven adept at performing many useful tasks in seismology and geophysics. Here we explore using deep learning to denoise HR-GNSS data. We develop three different convolutional neural networks with similar architectures but different targets. Training data are synthetic HR-GNSS records and actual noise recordings that are superimposed to generate noisy signals. We train each of the three models to output masks that can be used to reconstruct the true signal. We use a set of performance metrics that quantify the models’ ability to denoise the testing data and find that denoising significantly improves the signal-to-noise ratio and the ability to identify first arrivals. Finally, we test the models on HR-GNSS records from the Ridgecrest earthquakes recorded at stations that have nearly colocated strong-motion sites used ground-truth the denoising results. We find that the models greatly improve the signal-to-noise ratios in these records and make the P-wave onset clearly identifiable.
Trusted and privacy-preserving sensor data onloading

To personalize their services (e.g., advertisement, navigation, healthcare), mobile apps collect sensor data. Typically, they upload the collected sensor data to the cloud, which returns the inferred user profiles required to personalize mobile services. However, privacy concerns and network connectivity/congestion issues can render cloud-based processing inapplicable. If different apps collect the same type of sensor data, app providers can collaborate by combining their data collections to infer on-device the user profiles required for personalization. Although major mobile platforms provide on-device data sharing mechanisms, these direct data exchanges provide no privacy protection. As an alternative to direct data sharing, we present differentially privatized sensor data onloading for app providers' collaboration. With our approach, app providers can safely collaborate by using shared sensor data to personalize their mobile services. We realize our approach as a middleware that acts as a trusted intermediary. The middleware aggregates the sensor data contributed by individual apps, which execute statistical queries against the combined datasets. Furthermore, the middleware's adaptive privacy-preserving scheme (1) computes and adds the required amount of noise to the query results so as to balance utility and privacy; (2) introduces a Trust-Data Theory so as to detect and remove spurious data from the combined collections; (3) rewards active contributing app providers so as to incentivize data contribution; (4) integrates a Trusted Execution Environment (TEE) so as to secure all data processing. Our evaluation shows that it is feasible and useful to personalize mobile services while protecting data privacy: queries' execution time is within 10 ms; participants' dissimilar privacy/utility requirements are satisfied; untrustworthy data are effectively detected; mobile services are personalized, and data privacy of both app providers and users are preserved.1
Space characterizations of complexity measures and size-space trade-offs in propositional proof systems

We identify two new clusters of proof complexity measures equal up to polynomial and log⁡n factors. The first cluster contains the logarithm of tree-like resolution size, regularized clause and monomial space, and clause space, ordinary and regularized, in regular and tree-like resolution. Consequently, separating clause or monomial space from the logarithm of tree-like resolution size is equivalent to showing strong trade-offs between clause space and length, and equivalent to showing super-critical trade-offs between clause space and depth. The second cluster contains width, Σ2 space (a generalization of clause space to depth 2 Frege systems), ordinary and regularized, and the logarithm of tree-like R(log⁡) size. As an application, we improve a known size-space trade-off for polynomial calculus with resolution. We further show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4, and introduce a measure intermediate between depth and the logarithm of tree-like resolution size.