Reviewerly/exHarmony huggingface dataset:
Full-field dynamic response of low-velocity impact on an elastic plate using 3D digital image correlation

Measurement of the impact process is challenging due to its short duration and high frequency response. Due to the very small strain in low-velocity impacts, the requirements for the temporal and spatial resolution of test methods are extremely high. Traditionally, strain gauges or lasers are commonly used to measure the dynamic response of a single point, or quasi-static loading is used to achieve full-field response. To finely describe the transient full-field deformation process of low-velocity impacts, a high-speed imaging system combined with 3D digital image correlation (DIC) technique is set up to investigate the instantaneous responses of impact on a polyvinyl chloride (PVC) plate at the ms and με level. The full-field deformation of the contact surface and the whole process of elastic wave propagation are measured. The measurement by DIC closely matches the measurement by strain gauges and agrees well with the numerical simulation results. The measurement reveals that the “multi-micro-impacts” phenomenon may happen during a complete impact process due to the complex strain wave propagation. This work provides a benchmark case for low-velocity impact full-field testing, and the results show that 3D DIC can accurately evaluate dynamic behaviors of low-velocity impact between flexible bodies and can accurately describe the spatiotemporal propagation characteristics of strain waves.
Dual Process Theory for Large Language Models: An overview of using Psychology to address hallucination and reliability issues

State-of-the-art Large Language Models have recently exhibited extraordinary linguistic abilities which have surprisingly extended to reasoning. However, responses that are unreliable, false, or invented are still a frequent issue. It has been argued that scaling up strategies, as in increasing model size or hardware power, might not be enough to resolve the issue. Recent research has implemented Type 2 strategies (such as Chain-of-Thought and Tree-of-Thought), as strategies that mimic Type 2 reasoning, from Dual Process Theory, to interact with Large Language Models for improved results. The current paper reviews these strategies in light of the Predicting and Reflecting Framework for understanding Dual Process Theory and suggests what Psychology, drawing from research in executive functions, thinking disposition and creativity, can further contribute to possible implementations that address hallucination and reliability issues.
Enhancing HR Efficiency Through the Integration of Artificial Intelligence and Internet of Things: A Study on AI Implementation in Human Resource Management

The AI has a positive impact on the internet of things. Moreover, high development of the workplace is allowed to be determined. Therefore, innovation within the workplace is determined. Survey analysis plays an important role in this portion. Therefore, PLS SEM software tale spot in this research study. The big data analysis process is the important part determined in this portion. Therefore, proper planning in order to strengthen the foundation of the company is determined. Correlation between the variables takes important role in this finding portion. However, there are challenges related to data security, privacy, and the need for up skilling HR personnel. Overall, this study highlights the potential of AI and IoT to transform HR practices and suggests recommendations for organizations to overcome the challenges. Overall discussion about the research topic is highlighted in this portion, which helps to analyze the significance role of research findings.
Influence of Digital Literacy and Audiovisual Media During the Covid-19 Pandemic

The work included a cross-sectional quantitative study aimed at evaluating the incidence of competencies, skills and digital literacy in complex thinking in a sample of 238 students of various cycles of the engineering specialty at a university in Lima. Four instruments were applied and submitted to the judgment of five experts. The digital literacy questionnaire was made and validated by exploratory factor analysis (Aiken's V: 1.0, KMO test: 0.552, Cronbach's alpha: 0.946). The instruments on digital competencies and skills and complex thinking were adapted and validated by Cronbach's alpha (values 0.965, 0.814 and 0.941 respectively).
Exploring the Role of Artificial Intelligence in Facilitating Assessment of Writing Performance in Second Language Learning

This study examined the robustness and efficiency of four large language models (LLMs), GPT-4, GPT-3.5, iFLYTEK and Baidu Cloud, in assessing the writing accuracy of the Chinese language. Writing samples were collected from students in an online high school Chinese language learning program in the US. The official APIs of the LLMs were utilized to conduct analyses at both the T-unit and sentence levels. Performance metrics were employed to evaluate the LLMs’ performance. The LLM results were compared to human rating results. Content analysis was conducted to categorize error types and highlight the discrepancies between human and LLM ratings. Additionally, the efficiency of each model was evaluated. The results indicate that GPT models and iFLYTEK achieved similar accuracy scores, with GPT-4 excelling in precision. These findings provide insights into the potential of LLMs in supporting the assessment of writing accuracy for language learners.
Application of service MIRO in practical class of Fundamentals of Innovative En-gineering

The paper raises the problem of attracting the attention of generation Z (buzzers) to the study of the educational program. The author argues in favor of the use of digital services in education to enhance attention to the subject being studied, as well as the formation of competence - the ability to solve professional problems using information and communication technologies. A list of digital services operating on the territory of the Russian Federation is presented. The analysis of scientific literature in foreign and domestic journals on the use of the MIRO online platform in educational practice is described. The paper is devoted to the presentation of the experience of using the MIRO online platform as a digital learning tool for organizing group and individual work in the study of the discipline "Fundamentals of Innovative Engineering" (FIE) at N. P. Ogarev Mordovian State University in classroom and self-study. The content of the FIE discipline for the specialty Operation of transport and technological machines and complexes" is shown in accordance with the Federal State Educational Standard of higher education. The paper describes the developed set of 9 practical works in MIRO in the discipline Fundamentals of innovative engineering activities which are carried out in the form of a business game A Firm, as well as the experience of performing these works by students. The practice of using MIRO in teaching FIE has shown that the online platform is accessible to teachers and students, the learning materials are easily placed on the platform, and neither students nor teachers had any difficulties in using it. There is a higher interest in performing practical work on FIE in MIRO, in contrast to paper media, and in improving student performance in this discipline. The practical significance of this study lies in the popularization of the use of digital services in the educational process.
Development of Engineering Thinking and Education in Secondary Schools of Russia and China

The relevance of the claimed research is determined by the insufficient knowledge of the development of engineering thinking and engineering education among high school students in Russia and China. The authors focus on the fact that recently in both countries there has been a literally “boom” in the development of engineering thinking and education in schools, starting from the initial stage and ending with high school. The purpose of the article is to identify and characterize the problem of the development of engineering thinking and engineering education among high school students in Russia and China. The authors analyze the main directions and describe a number of successful initiatives implemented in these countries that contribute to the successful development of engineering thinking and engineering education among high school students. Methodology and research methods. Analysis of scientific literature on the development of engineering thinking and engineering education among high school students, regulatory and program documentation and projects implemented in schools of the countries under study showed the importance of this area. Research results. The study confirmed that the development of engineering thinking and engineering education among high school students in Russia and China allows the younger generation to consciously make a professional choice and acquire motivation to study subjects of the natural science cycle. The development of engineering thinking and engineering education among high school students in Russia and China in the last decade has been under intense attention and support from the governments of these countries. A new system of technology parks is characterized, which contributes to the involvement of most of the school youth to a technical specialty. Conclusion. The study of the development of engineering thinking and education in secondary schools in Russia and China is of great theoretical and practical importance for preparing the younger generations for life and professional activity. The study of the positive experience of China can be important for understanding, enriching and the possibility of its use in domestic practice, taking into account the cultural characteristics of our country.
Process model of development of adolescents’ social initiative in educational organization environment

The paper presents theoretical and methodological grounds that actualize the development of a process model of development of adolescents social initiative in educational organization environment as a regulatory of productive stimulation of civil, patriotic, spiritual and moral development of young people, the basis for creative activity in a changing reality, for conscious opposition to the destructive influences of risky society. The problems and risks of insufficient attention to the development of adolescents social initiative in school by means of the opportunities of the educational environment have been identified. The content of the basic concepts of research is specified on the basis of interdisciplinary analysis of literature and advanced pedagogical experience. A designed process model of the development of adolescents social initiative in the educational organization environment is presented. Its block structure (target, methodological, content, productive blocks), optimally implemented in the sequence of stages (orienting, activating, reflexive) is described. The research also characterizes the target block of the model which sets guidelines for updating the study based on the social order of society, the requirements of regulatory legal documents in the field of education and the social sphere. The methodological block of the model was substantiated, reflecting the conceptual ideas of the environmental and activity scientific approaches and the general scientific principles arising from them (axiology, individuality and personal priorities, social cooperation, eventuality). The content block is aimed at the phased implementation of organizational forms and methods of the process model of the development of adolescents social initiative from the standpoint of using the capabilities of the educational organization environment (semantic, informational, activating) and its components (value-regulatory, informational, communicative, event, spatial). A productive block of the model has feedback functions and makes it possible to determine the productivity of the conducted study in the context of the sequential transition of the level of the components development of the adolescents social initiative (eposeological, axiological, praxeological) from low to medium and high.
ExhibitXplorer: Enabling Personalized Content Delivery in Museums Using Contextual Geofencing and Artificial Intelligence

In recent years, there has been an increasing demand for personalized experiences in various domains, including the cultural and educational sectors. Museums, as custodians of art, history, and scientific knowledge, are seeking innovative ways to engage their visitors and provide tailored content that enhances their understanding and appreciation of the exhibits. This article presents ExhibitXplorer, a distributed architecture service that leverages geofencing, artificial intelligence, and microservices to enable personalized content delivery in museums. By combining implicit and explicit segmentation of museum visitors and utilizing the GPT API for content generation, ExhibitXplorer offers a dynamic experience to different visitor segments, including researchers, students, casual visitors, and children. The system utilizes push notifications triggered by visitor location changes, allowing seamless delivery of personalized information both indoors and outdoors. Tests were conducted to evaluate the user experience of visitors to an outdoor ethnographic museum. The results showed that 55% of the test participants were satisfied and 45% very satisfied with the way personalized content was delivered.
Preparing future teachers for the organization of pedagogical education of parents based on the implementation of psychological and pedagogical mechanisms

This paper discusses the effectiveness of the use of psychological and pedagogical mechanisms for the preparation of future teachers for the organization of pedagogical education of parents. The work of school teachers to educate parents in respect of education, upbringing and development of children always remains relevant and requires special attention, since modern parents often experience problems associated with the organization of family education. The use of such mechanisms as stimulation of emotional experience, saturation and pedagogical support of motivation in work with future teachers is the most effective and easily implemented in the format of educational training. Training is a method of active learning, the purpose of which is to develop knowledge, skills and various social attitudes. After analyzing various sources and conducting a study on the implementation of psychological and pedagogical mechanisms for stimulating emotional experience and motivating future teachers to interact with parents, the training Positive Interaction and Motivation was developed. The use of the materials proposed by us in the organization of educational activities in a pedagogical university allows to solve the problem of preparing future teachers for the organization of pedagogical education of parents, as well as to create a positive emotional mood and increase the level of students' motivation for this type of activity.
Radix-22 Algorithm for the Odd New Mersenne Number Transform (ONMNT)

This paper introduces a new derivation of the radix-22 fast algorithm for the forward odd new Mersenne number transform (ONMNT) and the inverse odd new Mersenne number transform (IONMNT). This involves introducing new equations and functions in finite fields, bringing particular challenges unlike those in other fields. The radix-22 algorithm combines the benefits of the reduced number of operations of the radix-4 algorithm and the simple butterfly structure of the radix-2 algorithm, making it suitable for various applications such as lightweight ciphers, authenticated encryption, hash functions, signal processing, and convolution calculations. The multidimensional linear index mapping technique is the conventional method used to derive the radix-22 algorithm. However, this method does not provide clear insights into the underlying structure and flexibility of the radix-22 approach. This paper addresses this limitation and proposes a derivation based on bit-unscrambling techniques, which reverse the ordering of the output sequence, resulting in efficient calculations with fewer operations. Butterfly and signal flow diagrams are also presented to illustrate the structure of the fast algorithm for both ONMNT and IONMNT. The proposed method should pave the way for efficient and flexible implementation of ONMNT and IONMNT in applications such as lightweight ciphers and signal processing. The algorithm has been implemented in C and is validated with an example.
Modeling noncovalent interatomic interactions on a photonic quantum computer

Noncovalent interactions are a key ingredient to determine the structure, stability, and dynamics of materials, molecules, and biological complexes. However, accurately capturing these interactions is a complex quantum many-body problem, with no efficient solution available on classical computers. A widely used model to accurately and efficiently model noncovalent interactions is the Coulomb-coupled quantum Drude oscillator (cQDO) many-body Hamiltonian, for which no exact solution is known. We show that the cQDO model lends itself naturally to simulation on a photonic quantum computer, and we calculate the binding energy curve of diatomic systems by leveraging Xanadu's strawberry fields photonics library. Our study substantially extends the applicability of quantum computing to atomistic modeling by showing a proof-of-concept application to noncovalent interactions, beyond the standard electronic-structure problem of small molecules. Remarkably, we find that two coupled bosonic QDOs exhibit a stable bond. In addition, our study suggests efficient functional forms for cQDO wave functions that can be optimized on classical computers, and capture the bonded-to-noncovalent transition for increasing interatomic distances.
Communication over entanglement-breaking channels with unreliable entanglement assistance

Entanglement assistance can improve communication rates significantly. Yet its generation is susceptible to failure. The unreliable assistance model accounts for those challenges. Previous work provided an asymptotic formula that outlined the tradeoff between the unassisted and excess rates from entanglement assistance. We derive a full characterization for entanglement-breaking channels and show that combining entanglement-assisted and unassisted coding is suboptimal. From a networking perspective, this finding is nontrivial and highlights a quantum behavior arising from superposition.
A Novel Complex-Valued Hybrid Neural Network for Automatic Modulation Classification

Currently, dealing directly with in-phase and quadrature time series data using the deep learning method is widely used in signal modulation classification. However, there is a relative lack of methods that consider the complex properties of signals. Therefore, to make full use of the inherent relationship between in-phase and quadrature time series data, a complex-valued hybrid neural network (CV-PET-CSGDNN) based on the existing PET-CGDNN network is proposed in this paper, which consists of phase parameter estimation, parameter transformation, and complex-valued signal feature extraction layers. The complex-valued signal feature extraction layers are composed of complex-valued convolutional neural networks (CNN), complex-valued gate recurrent units (GRU), squeeze-and-excite (SE) blocks, and complex-valued dense neural networks (DNN). The proposed network can improve the extraction of the intrinsic relationship between in-phase and quadrature time series data with low capacity and then improve the accuracy of modulation classification. Experiments are carried out on RML2016.10a and RML2018.01a. The results show that, compared with ResNet, CLDNN, MCLDNN, PET-CGDNN, and CV-ResNet models, our proposed complex-valued neural network (CVNN) achieves the highest average accuracy of 61.50% and 62.92% for automatic modulation classification, respectively. In addition, the proposed CV-PET-CSGDNN has a significant improvement in the misjudgment situation between 64QAM, 128QAM, and 256QAM compared with PET-CGDNN on RML2018.01a.
Multi-Camera Person Re-Identification Based on Trajectory Data

This study presents a trajectory-based person re-identification algorithm, embedded in a tool to detect and track customers present in a large retail store, in a multi-camera environment. The customer trajectory data are obtained from video surveillance images captured by multiple cameras, and customers are detected and tracked along the frames that compose the videos. Due to the characteristics of a multi-camera environment or the occurrence of occlusions, caused by objects such as shelves or counters, different identifiers are assigned to each person when, in fact, they should be identified with a unique identifier. Thus, the proposed tool tries to solve this problem in a scenario where there are constraints in using images of people due to data privacy concerns. The results show that our method was able to correctly re-identify the customers present in the store with a re-identification rate of 82%.
Demystifying Web-based Mobile Extended Reality Accelerated by WebAssembly

By combining various emerging technologies, mobile extended reality (XR) blends the real world with virtual content to create a spectrum of immersive experiences. Although Web-based XR can offer attractive features such as better accessibility, cross-platform compatibility, and instant updates, its performance may not be on par with its standalone counterpart. As a low-level bytecode, WebAssembly has the potential to drastically accelerate Web-based XR by enabling near-native execution speed. However, little has been known about how well Web-based XR performs with WebAssembly acceleration. To bridge this crucial gap, we conduct a first-of-its-kind systematic and empirical study to analyze the performance of Web-based XR expedited by WebAssembly on four diverse platforms with five different browsers. Our measurement results reveal that although WebAssemlby can accelerate different XR tasks in various contexts, there remains a substantial performance disparity between Web-based and standalone XR. We hope our findings can foster the realization of an immersive Web that is accessible to a wider audience with various emerging technologies.
Music through Curve Insights

This manuscript endeavors to establish a framework for the mapping of music onto a three-dimensional structure. Our objective is to transform the guitar choruses of Beatles songs into curves, with each chorus corresponding to its respective curve. We aim to investigate and characterize the intricacy of each song by employing mathematical techniques derived from differential geometry, specifically focusing on the total curvature of the chorus curve. Given that a single song may possess varying chord progressions in different verses, the performer can determine the geometric representation they aim to convey through the number of loops and the direction of the curve. The overarching objective of our study is to enable viewers to identify specific songs or motives by visually examining an object and exploring its geometric properties. Furthermore, we posit that these ideas can provide composers with a fresh perspective on their own musical compositions while also granting non-professional audiences a glimpse into the intricacies involved in the process of composing.