Reviewerly/exHarmony huggingface dataset:
Parametric model construction of solid mechanics based on wireless environment and cloud computing mode

Abstract Traditional parametric models of solid mechanics have disadvantages such as poor lightweight level of cloud data and low integrity of operations of solid mechanics. To solve the above problems, a parametric model for solid mechanics in engineering research based on cloud computing models is designed. By calculating the number of cloud data copy optimizations, the upper limit of resources required for engineering research is estimated, and the specific values is assessed by continuously cycling the demand, so as to complete the basic conflict analysis, and set up a cloud computing engineering research environment. On this basis, the modeling index is selected. By analyzing the sensitivity of the index, the purpose of optimizing the modeling parameters is achieved, and a new solid mechanics parametric model is constructed. Analyzing and contrasting the experimental data shows that after applying the parametric model of solid mechanics in the engineering research based on the cloud computing model, the lightweight level of cloud data can be increased by up to 24 levels, and the operational integrity of solid mechanics can be increased by about 30%.
Local subaperture compensation and stitching interferometry

This paper proposes an interferometry method based on a fixed interferometer structure and locally compensated stitching. The subaperture measurement is completed by applying a double-optical-wedge compensator in the "rugged" area of the surface that cannot be measured. The data of the measured area is stitched to obtain the local surface shape. The calibration of the double-optical-wedge compensator is performed by using a standard mirror. Surface figure error (SFE) of the standard mirror is measured by an interferometer beforehand. Compared with the SFE measured after adding the compensator in the optical path, the phase and aberration of the double-optical-wedge can be obtained. Measured data is processed by the subaperture stitching algorithm. Through the weighted fusion algorithm, the corresponding data values on the overlapping areas are weighted, and different weights are assigned to different areas to make the stitching transition smooth. Based on the principle of interferometry, a double-optical-wedge compensation measurement system is designed and implemented. A simulation model of the measurement experiment is presented, and the validity of the method is verified by simulation.
Libraries of Social Organizations of Kazan within the Cultural Environment of the Region in the middle of the 19th — early 20th century

The range of problems related to the research of regional features of librarianship development has not lost its significance, it urgently requires further consideration. The study of libraries as an integral part of the culture of Kazan and the results of their educational activities will allow identifying and understanding the unique experience of book veneration, national library construction and the culture of book reading in the region, in order to preserve it in the memory of further generations. Identification of patterns and contradictions in the organization of book service in the specific conditions of the national Republic will allow to see the comprehensive picture of the historical-book era from perspective of “library — society”. The author underlines the necessity to streamline and structure scientific information about the libraries of Kazan in the middle of the 19th — early 20th century with a view to its further extraction and use by local historians, librarianship historians and other humanitarian broad specialists in their scientific research. The phenomenon of libraries of public and social institutions of Kazan is an important page in the regional librarianship. Available publications on the topic cover only some of its fragments. Meanwhile, this component of the regional historical and cultural stratum contains rich material that needs further study and introduction into scientific circulation. The following information, extracted from various sources and being only introduction to the topic, is evidence of this. The author studied the development of library and educational activities through the prism of libraries of public and social institutions of Kazan. The research material allows concluding that before the Russian revolution there was created a very extensive, though disordered system of libraries of public and social organizations. The research is carried out on the basis of the Collection for Library Science of the National Library of Russia (NLR), the Department of Rare Books and Manuscripts and the Department of Tatar and Local Lore Literature of the National Library of the Republic of Tatarstan. The author studied the information, reflected in the electronic catalogues of the NLR, the Russian State Library and the Mayakovsky Central City Public Library in St. Petersburg, materials of scientific and practical conferences, publications in professional literature and archival documents. This study summarizes the results of this work. Based on the studied sources, the author revealed the trends of pre-revolutionary library-enlightenment activities as national, cultural and informational heritage of the region.
Structure interpretation of text formats

Data repositories often consist of text files in a wide variety of standard formats, ad-hoc formats, as well as mixtures of formats where data in one format is embedded into a different format. It is therefore a significant challenge to parse these files into a structured tabular form, which is important to enable any downstream data processing. We present Unravel, an extensible framework for structure interpretation of ad-hoc formats. Unravel can automatically, with no user input, extract tabular data from a diverse range of standard, ad-hoc and mixed format files. The framework is also easily extensible to add support for previously unseen formats, and also supports interactivity from the user in terms of examples to guide the system when specialized data extraction is desired. Our key insight is to allow arbitrary combination of extraction and parsing techniques through a concept called partial structures . Partial structures act as a common language through which the file structure can be shared and refined by different techniques. This makes Unravel more powerful than applying the individual techniques in parallel or sequentially. Further, with this rule-based extensible approach, we introduce the novel notion of re-interpretation where the variety of techniques supported by our system can be exploited to improve accuracy while optimizing for particular quality measures or restricted environments. On our benchmark of 617 text files gathered from a variety of sources, Unravel is able to extract the intended table in many more cases compared to state-of-the-art techniques.
Frenzy Sneakers after Market: From Price Control to Block Chain

Speculators appear during the flourishing age of the sneaker trading tide, trying to profit from it by affecting the price of sneakers, which invokes discussions about how to eliminate the price premium.We conducted a survey to analyze the need for most consumers aged 15 -45 and found the biggest problem that most consumers care about: transaction transparency.Statistical data of more than 1000 pairs of shoes collected from the second biggest sneaker platform Nice also proves the correlation between sneakers' price and price influential factors-release time and demand-obey the basic price mechanism.An interview with the industry insider also takes a deeper perspective into the market structure.However, through our research, we supposed increasing transaction transparency through block chain should be the priority, so that we can keep pushing the flourishing market.
Analysis of Student Responses to E-learning Resources and Activities

In early 2020, the outbreak spread in the world. In response to this emergency condition, the world's higher education institutions have been forced to resort to e-learning and digital tools. This study was conducted to find out the studentsâ€™ responses to resources and activity e-learning. The sample was composed of 37 students. The data were collected by questionnaire and analyzed by mean score and Likert scale. Using ideal normal standards for the various data above, it can be concluded that the student response to e-learning used at the University of Sarjanawiyata Tamansiswa can be described as follows for the student response indicator to the resources in e-learning, has 4.1 mean scores, it can be concluded that students assess resources in e-learning are considered good. Then, the activities in e-learning have a mean score of 3.8. This indicates that it is in a fair category.
Measuring race bias in face recognition algorithms: a multi-factor assessment

Previous generations of face recognition algorithms show differences in accuracy for faces of different races (race bias) (O’Toole et al., 1991; Furl et al., 2002; Givens et al., 2004; Phillips et al., 2011; Klare et al., 2012). Whether newer deep convolutional neural networks (DCNNs) are also race biased is less well studied (El Khiyari et al., 2016; Krishnapriya et al., 2019). Here we present methodological considerations for measuring underlying race bias. We consider two key factors: data-driven and scenario modeling. Data-driven factors are driven by the data itself (e.g., the architecture of the algorithm, image quality, image population statistics). Scenario modeling considers the role of the “user” of the algorithm (e.g., threshold decisions and demographic constraints). To illustrate these issues in practice, we tested four face recognition algorithms: one pre-DCNN (A2011; Phillips et al., 2011) and three DCNNs (A2015; Parkhi et al., 2015), (A2017b; Ranjan et al., 2017), (A2019; Ranjan et al., 2019) on East Asian and Caucasian faces. First, for all four algorithms, the degree of race bias varied as a function of the identification decision threshold. Second, for all algorithms, to achieve equal false accept rates (FARs), Asian faces required higher identification thresholds than Caucasian faces. Third, dataset difficulty affected both overall recognition accuracy and race bias. Fourth, demographic constraints on the formulation of the distributions used in the test, impacted estimates of algorithm accuracy. We conclude with a recommended checklist for measuring race bias in face recognition algorithms.
PHYSICAL FOUNDATIONS OF UNIFIED KNOWLEDGE

A physical model of the Universe is proposed, which is based on the idea of the world as two interconnected branches of a single evolutionary process. One branch is the creation of a postulated primary particles - forms and their cells of a multilevel oscillating structure - a Unified set of forms (USF), which, in the model, is space; second, the formation of material realities by combining the same forms in a structured space. The interaction of the same particles representing “matter” and “space” gives a strict coordination of their development at all scale levels, from elementary particles, atoms, up to Homo sapiens. USF is the "constructor" of all material realities, and is responsible for their interactions - the forces that arise between them. So, gravitational forces are the stresses in the USF caused by its deformation (“space curvature”) by material objects. This explains its long-range and high-speed performance, which was clearly shown by experiments on elastic models. USF also gives wave properties to all particles moving along its corridors, which determine the transmission properties of space. At this stage of knowledge, USF provides a clear physical explanation for the de Broglie hypothesis, the Heisenberg uncertainty principle, and some other physical phenomena. The constant interaction and mutual development of the USF and the material world give the direction of the evolution process of the Universe.
Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise

Sensitivity to adversarial noise hinders deployment of machine learning algorithms in security-critical applications. Although many adversarial defenses have been proposed, robustness to adversarial noise remains an open problem. The most compelling defense, adversarial training, requires a substantial increase in processing time and it has been shown to overfit on the training data. In this paper, we aim to overcome these limitations by training robust models in low data regimes and transfer adversarial knowledge between different models. We train a meta-optimizer which learns to robustly optimize a model using adversarial examples and is able to transfer the knowledge learned to new models, without the need to generate new adversarial examples. Experimental results show the meta-optimizer is consistent across different architectures and data sets, suggesting it is possible to automatically patch adversarial vulnerabilities.
Recognition of The Rearview Image Pattern of a Motorcycle for a System to Detect Current Violations on a One-Way Street

This study aims to detect traffic violations, especially motorbikes that go against the flow on a one-way street by recognizing the pattern of rearview images of vehicles. The method used is Faster-RCNN. This system uses an IP camera with a pole height of 2.5 m with a tilt angle of 45 degrees. Recognition of the rear view of the vehicle using the Labeling method using Labelling and TensorFlow with the Faster-RCNN model for classification. The result of system accuracy is as much as 88%.
Parallel Monte Carlo Tree Search in General Video Game Playing

Monte Carlo Tree Search (MCTS) parallelization is one of the many possible enhancements for MCTS algorithms. However, no work has been done on evaluating these methods in the rather new area of General Video Game Playing (GVGP), an area that challenges the creation of agents that can play any videogame even without prior knowledge about the video game they are going to play. To address this gap, this paper proposes the implementation and evaluation of the three main MCTS parallelization methods as agents of the General Video Game AI framework, a popular framework for GVGP agents evaluation. This paper is not focused on comparing the parallel MCTS agents to other existing GVGP agents, but rather on exploring how the MCTS parallelization methods compare between themselves. This paper also presents a testing methodology for evaluating these agents, which is based on a set of three experiments focused on different aspects of the parallel MCTS algorithms. In these experiments, the overall best results were achieved by the root parallelization method using the sum merging technique and the UCT’s sigma value of \( \sqrt 2 \).
MOTIVATIONAL BASIS FOR THE FORMATION OF UNIVERSAL COMPETENCIES OF UNDERGRADUATE STUDENTS OF A TECHNICAL UNIVERSITY

Представлено исследование мотивационной сферы студентов младших курсов технического вуза. Проведен анализ связи учебных, малоосознаваемых личностных мотивов студентов с группами универсальных компетенций, а также определены дефициты персональных навыков, которые влияют на формирование универсальных компетенций. Были сделаны следующие выводы: изучение и анализ мотивационной сферы студентов младших курсов позволяют своевременно актуализировать дефициты персональных навыков в освоении универсальных компетенций, закрепленных в образовательной программе подготовки специалистов; разработав модель формирования универсальных компетенций на базе полимотивационной структуры учебных мотивов, можно получить инструмент подготовки специалиста, отвечающего современным требованиям профессиональной среды. The paper presents a research of motivational sphere of undergraduate students of a technical Universi-ty. The connection of educational, poorly realized personal motives of students with groups of universal competencies was analyzed, and the deficiencies of personal skills that affect the formation of universal competencies were identified. Personal skills are more closely related to psychological characteristics, preferences, experience, environment, and so on. They develop more slowly and more difficult. In the motivational sphere of university students contains two main groups of motives. The first group is the motives inherent in the training itself. They determine the educational and cognitive motivation of stu-dents. The second group includes motives associated with what lies outside the learning process. In the process of developing a student’s professional competence, one can observe a different combination of the first and second groups of motives. The following conclusions were drawn: the study and analysis of the motivational sphere of undergrad-uate students allows timely updating of personal skill deficiencies in the development of universal com-petencies enshrined in the specialist training curriculum; having developed a model of the formation of universal competencies based on the poly-motivational structure of educational motives, you can get a tool to train a specialist meeting modern requirements of the professional environment.
From Verified Compilation to Secure Compilation: a Semantic Approach

A formally verified compiler is a compiler that comes with a machine-checked proof that no bug is introduced during compilation. This correctness property states that the compiler preserves the semantics of programs. Formally verified compilers guarantee the absence of correctness bugs, but do not protect against other classes of bugs, such as security bugs. This limitation partly arises from the traditional form of stating compiler correctness as preservation of semantics that do not capture non-functional properties such as security. Moreover, proof techniques for compiler correctness, including the traditional notions of simulation, do not immediately apply to secure compilation, and need to be extended accordingly.
Measurement of Wafer Focus by Grating Shearing Interferometry

A method applied for improving the measurement precision and efficiency of wafer focusing in an optical lithography instrument (OLI) is introduced. Based on grating shearing interferometry, the defocus and tilt of the wafer are measured by testing the phase difference in the interference pattern. To validate the feasibility, an experiment is implemented, of which the measurement precision is indicated as 30 nm due to the high precision of phase-resolving arithmetic after analyzing the measurement uncertainty and indicating the precision by interferometer.
An exactly solvable toy model

In an attempt to regularize a previously known exactly solvable model [Yang and Zhang, Eur. J. Phys. \textbf{40}, 035401 (2019)], we find yet another exactly solvable toy model. The interesting point is that while the Hamiltonian of the model is parameterized by a function $f(x)$ defined on $[0, \infty )$, its spectrum depends only on the end values of $f$, i.e., $f(0)$ and $f(\infty )$. This model can serve as a good exercise in quantum mechanics at the undergraduate level.
Hybrid Optimized Image Steganography with Cryptography

This paper proposes a hybrid optimized steganography algorithm for color image using LSB, parity checker steganography techniques with AES, Blowfish, RC2 and RC4 a combination of steganography and cryptography to improve the security of information hiding, by using peak signal-to-noise ratio (PSNR) as a performance metric. The hybrid optimized steganography algorithm with cryptography is better than traditional image steganography methods with more security and greater value of PSNR.
Problems and possibilities of distance education use among students, who study according to “Physical culture” profile

Digital technologies introduction into the sphere of education is an urgent problem. Nowadays specialists both underline positive and negative sides of transfer into digital sphere. However, in terms of coronovirus infection pandemic most part of educational establishments was forced to use distance education. The aim of the present research work was to reveal the attitude of students to distant form of education, the difficulties and possibilities of this direction development. As the research methods we used survey, statistical instruments of data handling and Google Forms. On the basis of the survey we revealed the attitude of students to distance education in general and to lectures and practical lessons, including the disciplines of sports orientation. During the survey we defined the main reasons. They prevent effective educational process realization using distant technologies. We defined the problems, possibilities and conditions for an effective use of distant forms of education.
Research on the Motion Control Trajectory and Structure Design of a Lower Limb Standing Rehabilitation Training Device

Aiming at the problem of standing rehabilitation of lower limb motor dysfunction patient. Firstly, the standing movement process of human body is analyzed. Secondly, the exercise trajectory test and pressure distribution measurement test of healthy human body are studied. Thirdly, the structure of the lower limb standing rehabilitation training device is designed according to the collected joint trajectory. Finally, the movement control trajectory simulation of the lower limb standing rehabilitation training device is carried out according to the collected regional pressure. The simulation results of virtual prototype coincide with the test trajectory, which shows that the structure of the designed lower limb standing rehabilitation training device is reasonable, and the hybrid control method of force and position can realize the standing rehabilitation training for lower limb motor dysfunction patient in the light of the set exercise trajectory.