Reviewerly/exHarmony huggingface dataset:
Remote data possession checking scheme with supporting efficient group user authority management for shared cloud data

Abstract Under the shared big data environment, the existing shared data auditing schemes rarely consider the authorization management of group users. Thus, in this paper, we propose a novel remote shared data checking possession scheme that support group authority management. To implement group user rights management, we firstly introduce a trusted entity group manager. To assist the group manager in authorization management, we formalize a new algebraic structure operator named authorization invisible authenticator (AIA). Meanwhile, we provide a basic AIA scheme for general security scenarios and a standard AIA scheme suitable for high-level security scenarios respectively. The standard AIA scheme can fully meet the needs of the group manager to safely perform rights management work. It is composed of the User Information Table (UIT) and the basic AIA scheme, which has higher security and is applicable to a wider range of scenarios. By distributing AIA through the standard AIA scheme, the group manager can easily carry out authority management, including enrolling, revoking, updating. After solving the problem of authorization management, the detailed design of the scheme based on identity-based encryption (IBE) is given. Furthermore, the security analysis and performance evaluation demonstrate that the scheme is safe and feasible.
Parabolic Cylindrical Description of Velocity and Acceleration Tensor in Bipolar Coordinate Using Tensor Analysis

Instantaneous velocity and acceleration are often studied and expressed in Cartesian, Circular Cylindrical, and Spherical Coordinate systems but it is a well-known fact that some bodies cannot be perfectly described in these coordinate systems, so they required some other curvilinear systems such as oblate spheroidal, parabolic cylindrical, elliptic cylindrical bipolar, and others. It is of important interest in theoretical physics to establish equations of motion in Bipolar Coordinate system, which is essentially suitable to accurately describe the motion of bipolar bodies such as hyperbolas, ellipses and other curves in the universe. In this work, we derived a new expression for the instantaneous velocity and acceleration vector of bodies and test particles in the bipolar coordinate system using tensor analysis. The Laplacian of a scalar field in this bipolar coordinate system was also derived which has applications in mechanics.
The Effectiveness of the Competence Approach in the Training of Chemistry Teachers

The most important problem for high-quality and effective education in a university is the creation of a set of competencies that reflect the results of the development of educational programs. The purpose of the study is to address the most important problem in achieving high-quality and effective education at a university, which is the development of a set of competencies reflecting the results of educational program development. The state educational standards for the educational program and the rules for drawing up the educational program were studied, and a review of the research of scientists on this problem and the work programs of various teachers of organic chemistry were conducted. The methods employed to determine the initial level of establishment of special and professional competencies among students of the educational programs 6B01515 "Chemistry" and 6B01516 "Chemistry-Biology" are specifically designed for the discipline of Organic Chemistry. These methods were implemented in practice at the Department of Biology, Geography, and Chemistry of the Institute of Natural Sciences, Korkyt Ata Kyzylorda University. Furthermore, pedagogical methods, tools, and technologies were utilized during practical application in the context of the discipline of Organic Chemistry to foster competency development among students. In conclusion, changes in the motivation of practicing students to study the discipline, working with a syllabus prepared by a teacher for study, the results of achieving the planned learning outcomes at lectures, in laboratory work, and the effectiveness and results of planning independent work of students by the research hypothesis were proved.
Analyzing decision-making in blockchain governance

Blockchain systems are a novel technology that allow for innovative business models. However, due to the decentralized nature of blockchains, new organizational challenges arise. Blockchains require intricate governance mechanisms to align all interests of the involved stakeholders. A crucial part of blockchain governance is decision-making, i.e., the way how a community of a blockchain system can reach decisions. While blockchain governance has received considerable interest of academia, decision-making in blockchains has not yet been sufficiently addressed. Through an exploratory multiple case study, we establish a framework for analyzing decision-making in blockchain systems and identify two dimensions along which decision-making in blockchains can be classified—namely community-driven vs. institution-driven as well as off-chain vs. on-chain decision-making. Even though blockchains are decentralized systems, we can show that there are often highly centralized elements present. The degree of this centralization varies across blockchains and might be connected to the business cases and origins of the different systems. Furthermore, many factors of decision-making processes in blockchains are still off-chain and only some factors are truly on-chain. We arrived at these insights through a structured approach for decision-making in blockchains. Thus, we provide new tools for researcher and practitioners and pave the way to novel blockchain applications with sound decision-making mechanisms.
A Novel JSF-Based Fast Implementation Method for Multiple-Point Multiplication

ECC is a popular public-key cryptographic algorithm, but it lacks an effective solution to multiple-point multiplication. This paper proposes a novel JSF-based fast implementation method for multiple-point multiplication. The proposed method requires a small storage space and has high performance, making it suitable for resource-constrained IoT application scenarios. This method stores and encodes the required coordinates in the pre-computation phase and uses table lookup operations to eliminate the conditional judgment operations in JSF-5, which improves the efficiency by about 70% compared to the conventional JSF-5 in generating the sparse form. This paper utilizes Co-Z combined with safegcd to achieve low computational complexity for curve coordinate pre-computation, which further reduces the complexity of multiple-point multiplication in the execution phase of the algorithm. The experiments were performed with two short Weierstrass elliptic curves, nistp256r1 and SM2. In comparison to the various CPU architectures used in the experiments, our proposed method showed an improvement of about 3% over 5-NAF.
ADDA: An Adversarial Direction-Guided Decision-Based Attack via Multiple Surrogate Models

Over the past decade, Convolutional Neural Networks (CNNs) have been extensively deployed in security-critical areas; however, the security of CNN models is threatened by adversarial attacks. Decision-based adversarial attacks, wherein an attacker relies solely on the final output label of the target model to craft adversarial examples, are the most challenging yet practical adversarial attacks. However, existing decision-based adversarial attacks generally suffer from poor query efficiency or low attack success rate, especially for targeted attacks. To address these issues, we propose a query-efficient Adversarial Direction-guided Decision-based Attack (ADDA), which exploits the advantages of transfer-based priors and the benefits of a single query. The transfer-based priors provided by the gradients of multiple different surrogate models can be utilized to suggest the most promising search directions for generating adversarial examples. The query consumption during the ADDA attack is mainly derived from a single query evaluation of the candidate adversarial samples, which significantly saves the number of queries. Experimental results on several ImageNet classifiers, including l∞ and l2 threat models, demonstrate that our proposed approach overwhelmingly outperforms existing state-of-the-art decision-based attacks in terms of both query efficiency and attack success rate. We show case studies of ADDA against a real-world API in which it is successfully able to fool the Google Cloud Vision API after only a few queries.
Ethics and Online Education

Before the pandemic, both in Ecuador and in the world, e-learning was not widely used, although it was known. This proposal is since in the post-pandemic period there has been an increase in the use, in general, of distance education, in its different modalities, with very little experience on the part of teachers in the design of courses for online or virtual education, in the various educational platforms. However, ethics, mainly from the teacher’s point of view, has not been wholly developed. The teachers’ training in the design of virtual events is necessary, together with their human capacity to relate to students and their preparation to properly use educational platforms with their dozens of internal facilities and the hundreds of existing and free Open Educational Resources (OER). This document discusses the teachers’ ethics, especially for the online modality, as an essential point, in its various perspectives.
BGPy: The BGP Python Security Simulator

The security of Border Gateway Protocol (BGP), and inter-domain routing in general, remains a challenge, in spite of its well-known importance, repeated attacks and incidents, and extensive efforts and research over decades. We present BGPy, an open-source, extensible, robust, easy-to-use and efficient BGP security simulator, to be used for research and education. BGPy allows realistic simulations of a large variety of BGP attacks and defenses. It is provided as a Python package, and can be further customized and extended, e.g., to investigate new attacks and new defense mechanisms. We describe how BGPy is currently used by multiple BGP security projects.
Features of the Transformation of the Regional University Library in Contemporary Conditions

The article reveals the peculiarities of the transformation of modern university libraries in connection with the ongoing changes in the sphere of higher education. The main difficulties in the implementation of integration into the electronic space are named (including such as limitations of the literature used in the university by year of publication, low attendance, a decrease in the level of information processing, an increase in the library funds the proportion of low-quality editions, the formalization of scientific knowledge, the lack of digital culture among users). This research is fulfilled on the basis of scientific articles and publications of the last years. The author emphasizes the necessity to support the idea of continuing education in the frames of the transformation of the university library as a multi-resource center for preparing materials for scientific researches and ensuring the educational process.
The History of Bibliography in the Works of A.Yu. Samarin

The article discusses the issues of the history of Russian bibliography, researched by Doctor of Historical Sciences A.Yu. Samarin and presented in his scientific publications. Drawing different archival documents this researcher made a great contribution into studies of the activities of the prominent figures of the Russian bibliorgraphy: V.S. Sopikov, metropolitan Evgeny (Bolkhovitinov), N.F. Bokachev, N.P. Smirnov, P.K. Simoni, D.V. Ulyaninsky, N.Yu. Ulyaninsky, N.N. Orlov, M.N. Kufaev, P.N. Berkov, E.L. Nemirovsky, L.I. Fursenko as well as historians dealing with the problems of bibliography such as A.A. Novoselsky, B.F. Porshnev, S.S. Ilizarov and others. The works by A.Yu. Samarin also present a new look on the formation of mandatory copy system in Russia and the results of studying the bibliographic activities of the Russian State Library in the field of rare book.
Time-optimal trajectory planning for autonomous parking of tractor-semitrailer vehicle based on piecewise Gauss pseudospectral method

For the autonomous parking problem of the tractor-semitrailer vehicle, a piecewise Gauss pseudospectral method is proposed as a trajectory planning scheme in this paper. Firstly, the trajectory planning problem is transformed into an optimal control problem by establishing a vehicle kinematics model for the low-velocity scene, the dynamic constraints including the physical constraints, the collision avoidance constraints, and the endpoint constraints. The optimal control problem are discretized into a nonlinear programming problem by piecewise Gauss pseudospectral method according to the movement area during parking process. The shortest time to complete parking is taken as the objective function. The Gauss pseudospectral method is further adopted to solve the nonlinear programming problem in the two parking stages. Three parallel parking conditions with different lengths of parking spaces and three vertical parking conditions with different widths of parking spaces are set for simulation verification based on Matlab/Simulink. The simulation results show that the proposed method can uniformly and effectively solve the trajectory planning problem of the tractor-semitrailer vehicle. Compared with the traditional pseudospectral method, a shorter parking time and a significantly higher convergence rate can be got with the method, which further indicates that the proposed method has good effectiveness and robustness.
The level of trust in science teachers among students of the scientific stream at secondary education and its relationship to some variables

The study aimed to investigate the level of trust in science teachers among students of the scientific stream at secondary education and its relationship to gender, future orientation, school type, and teachers' specialization variables.The descriptive correlational approach was used in addition to a questionnaire applied to (1030) male and female students from the scientific stream in public and private schools in Irbid Kasbah Directorate of Education.The results indicated that the level of students' trust in science teachers was medium.There were statistically significant differences in the level of students' trust in science teachers attributed to gender and teachers' specialization in favor of males and life science teachers respectively.While there were no statistically significant differences attributed to the variables of students' future orientation and school type.In light of the results, the study recommended educating teachers about the importance of having a strong bond of trust with their students, holding training courses that foster teachers' communication skills and giving students appropriate guidance and support according to their needs.The study further recommended conducting more research on the concept of trust, taking into account other variables such as stress, tension, and academic achievement.
Virus control optimizer based on the prevention and control mechanism of COVID-19 for engineering optimization problems

Metaheuristic algorithms have been widely used in many application fields and have achieved some good results, but there is still a strong demand for these algorithms in different engineering application fields. In this paper, a novel metaheuristics algorithm named Virus Control Optimizer (VCO) is proposed to solve engineering optimization problems. The algorithm is inspired by the prevention and control mechanism of COVID-19, which designed an effective solution space partition strategy and a multi-subpopulation collaborative search framework. This framework will maintain the whole population’s diversity while making an accurate search on the local optimal region. Compared to other existing algorithms, VCO has a unique search mechanism and can achieve better convergence efficiency, especially in engineering optimization problems. The search capabilities of VCO are assessed by testing on 12 classical benchmark functions, 29 unconstrained benchmark functions obtained from CEC 2017, 4 constrained engineering optimization problems, 5 real-world constrained problems from CEC 2020 and 3 simulation test of multi-UAVs path planning problems. In addition, VCO is compared with other typical and state-of-the-art heuristic algorithms, our results reveal that VCO can obtain better solutions than the comparison algorithms.
A novel open-set clustering algorithm

DOS (Delta Open Set) is an interesting clustering algorithm that transforms cluster identification into set identification. It identifies the objects whose neighborhoods coincide as an open-set, and an open-set corresponds to a cluster. However, once the dataset is complex, DOS tends to identify overlapping clusters as one category. We believe the main reason is that DOS unifies the neighborhood radius by a specific function, resulting in the inability to cope with various object distributions. To improve DOS, we propose DOS-IN (Irregular Neighborhoods). Specifically, DOS-IN generates irregular neighborhoods based on the similarity between objects to self-adapt to diverse object distributions. As a result, DOS-IN not only can accurately distinguish overlapping clusters but also has fewer input parameters. In addition, DOS-IN introduces the small-cluster merging mechanism to address the shortcoming of DOS in recognizing Gaussian clusters. The experimental results show that DOS-IN is completely superior to DOS. Compared with baseline methods, DOS-IN outperforms them on 7 out of 10 datasets, with at least 13.8% (NMI) and 2.4% (RI) improvement in accuracy. The code of DOS-IN is available at https://github.com/Youth-49/2023-DOS-IN.
Efficient lattice-based traceable ring signature scheme with its application in blockchain

Traceable ring signatures (TRSs) were proposed by Fujisaki and Suzuki (PKC 2007), which is a variant of ring signatures that aims to restrict excessive anonymity of them. If the signer signs two identical messages about the same group of ring members and issue, the two signatures will be detected, but the identity of the signer will not be disclosed; if the signer signs two different messages about the same group of ring members and issue, it allows to reveal the identity of the signer. This primitive is very useful in scenarios that require anonymous protection and avoid duplicate signatures, such as electronic voting, blockchain and Internet of Things. However, the existing post-quantum TRS schemes all have a long signature and low computational efficiency, which is far from practical application. In this paper, we propose an efficient lattice-based TRS scheme by improving DualRing that is a short ring signature scheme proposed by Yuen et al. (CRYPTO 2021). Among all existing post-quantum TRS schemes, the proposed scheme has the shortest signature for a ring size between 5 and 2000, and it is also the fastest one in signature generation, taking only about 0.4 s for a ring size of 1024. In the random oracle model, the proposed scheme is proved to satisfy anonymity, tag-linkability and exculpability under the Module Short Integer Solution and Module Learning With Errors hardness assumptions over lattice. In addition, to demonstrate the applicability of the proposed scheme, we develop a post-quantum blockchain model with access control based on it, which can be extended to Internet of Medical Things (IoMT), e-commerce, education, banking and other systems.
APPLYING PHET SIMULATIONS IN TEACHING MECHANICAL OSCILLATIONS AND WAVES AT SECONARY SCHOOL

STEM educational technology is attracting more and more educators from different countries around the world. It is innovative educational technology. The 21st century competences such as creativity, communication, collaboration and critical thinking are formed in its application. Educational simulations are a basic didactic tool of STEM technology in teaching natural sciences and in particular Physics. Тhe Physics Education Technology (PhET) project creates useful simulations for teaching and learning Physics. They are freely available on the PhET web site: https://PhET.colorado.edu. Some ideas for the application of PhET simulations in the study of mechanical oscillations and waves are presented. They are interactive, animated and visual. As a result students develop permanent and profound knowledge about them and about related quantities and laws.
“I do not know! but why?” — Local model-agnostic example-based explanations of reject

Machine learning based decision making systems in safety critical areas place high demands on the accuracy and generalization ability of the underlying model. A common strategy to deal with uncertainties and possible mistakes is offered by learning with reject option, i.e. a model can refrain from prediction in ambiguous cases and leave the decision to a human expert. Yet, as for the models themselves, human decision-making is hampered by the fact that reject options are often implemented as black-box rules: Experts cannot readily understand the reasons for rejection. In this work, we propose a model-agnostic framework that enriches classification with reject option by explanation mechanisms. More specifically, we combine conformal prediction as a popular mathematically based technology of certainty estimation with local surrogates derived for the region of interest. This allows us to provide local explanations in terms of example-based explanation methods, including counterfactual, semi-factual, and factual methods. We demonstrate the performance of this technology through a series of benchmarks using 6 different data sets; the associated code is open source.1
Quasi-maximum likelihood-based estimator of the hyperbolic frequency modulated signals

The quasi-maximum likelihood (QML) algorithm has been extended to estimate the phase parameters and the instantaneous frequency (IF) of the hyperbolic frequency modulated (HFM) signals. The Nelder-Mead simplex algorithm (NMSA) is adopted for a fine estimation. The obtained accuracy is excellent with the estimates achieving the Cramer-Rao lower bound (CRLB) above the signal-to-noise (SNR) threshold of 0 dB. The proposed technique is capable of functioning with signals that are sampled below the requirements of the sampling theorem, which is particularly important for HFM signals. Additionally, there are no limitations for signals with monotonic IF and/or group delay (GD) functions.