Reviewerly/exHarmony huggingface dataset:
Global implicit function theorems and the online expectation–maximisation algorithm

Summary The expectation–maximisation (EM) algorithm framework is an important tool for statistical computation. Due to the changing nature of data, online and mini‐batch variants of EM and EM‐like algorithms have become increasingly popular. The consistency of the estimator sequences that are produced by these EM variants often rely on an assumption regarding the continuous differentiability of a parameter update function. In many cases, the parameter update function is not in closed form and may only be defined implicitly, which makes the verification of the continuous differentiability property difficult. We demonstrate how a global implicit function theorem can be used to verify such properties in the cases of finite mixtures of distributions in the exponential family, and more generally, when the component‐specific distributions admit data augmentation schemes, within the exponential family. We then illustrate the use of such a theorem in the cases of mixtures of beta distributions, gamma distributions, fully visible Boltzmann machines and Student distributions. Via numerical simulations, we provide empirical evidence towards the consistency of the online EM algorithm parameter estimates in such cases.
Leakage-Resilient Revocable Certificateless Encryption with an Outsourced Revocation Authority

To resolve both certificate management and key escrow problems, a certificateless public-key system (CLPKS) has been proposed. However, a CLPKS setting must provide a revocation mechanism to revoke compromised users. Thus, a revocable certificateless public-key system (RCLPKS) was presented to address the revocation issue and, in such a system, the key generation centre (KGC) is responsible to run this revocation functionality. Furthermore, a RCLPKS setting with an outsourced revocation authority (ORA), named RCLPKS-ORA setting, was proposed to employ the ORA to alleviate the KGC’s computational burden. Very recently it was noticed that adversaries may adopt side-channel attacks to threaten these existing conventional public-key systems (including CLPKS, RCLPKS and RCLPKS-ORA). Fortunately, leakage-resilient cryptography offers a solution to resist such attacks. In this article, the first leakage-resilient revocable certificateless encryption scheme with an ORA, termed LR-RCLE-ORA scheme, is proposed. The proposed scheme is formally shown to be semantically secure against three types of adversaries in the RCLPKS and RCLPKS-ORA settings while resisting side-channel attacks. In the proposed scheme, adversaries are allowed to continually extract partial ingredients of secret keys participated in various computational algorithms of the proposed scheme while retaining its security.
Practical Teaching Strategies for College English Based on the Output-Driven Hypothesis

With the continuous development and innovation of higher education in China, the development trend of education, from the extension type to the connotative type, is prompting the reform of college English. At present, college English emphasizes more on students’ comprehensive English application skills and their comprehensive development in listening, speaking, reading, and writing, so that they can use English flexibly. The output-driven hypothesis is a teaching theory proposed in the current educational environment, which is devoted to solving many problems in English teaching, such as low efficiency and the separation of learning and application. This study makes a detailed analysis of the connotation of output-driven hypothesis and explores the problems existing in current college English teaching. The purpose of this paper is to put forward practical teaching strategies for college English under the concept of output-driven hypothesis.
INAS: Interactive Argumentation Support for the Scientific Domain of Invasion Biology

Developing a precise argument is not an easy task. In real-world argumentation scenarios, arguments presented in texts (e.g. scientific publications) often constitute the end result of a long and tedious process. A lot of work on computational argumentation has focused on analyzing and aggregating these products of argumentation processes, i.e. argumentative texts. In this project, we adopt a complementary perspective: we aim to develop an argumentation machine that supports users during the argumentation process in a scientific context, enabling them to follow ongoing argumentation in a scientific community and to develop their own arguments. To achieve this ambitious goal, we will focus on a particular phase of the scientific argumentation process, namely the initial phase of claim or hypothesis development. According to argumentation theory, the starting point of an argument is a claim, and also data that serves as a basis for the claim. In scientific argumentation, a carefully developed and thought-through hypothesis (which we see as Toulmin's "claim'' in a scientific context) is often crucial for researchers to be able to conduct a successful study and, in the end, present a new, high-quality finding or argument. Thus, an initial hypothesis needs to be specific enough that a researcher can test it based on data, but, at the same time, it should also relate to previous general claims made in the community. We investigate how argumentation machines can (i) represent concrete and more abstract knowledge on hypotheses and their underlying concepts, (ii) model the process of hypothesis refinement, including data as a basis of refinement, and (iii) interactively support a user in developing her own hypothesis based on these resources. This project will combine methods from different disciplines: natural language processing, knowledge representation and semantic web, philosophy of science and -- as an example for a scientific domain -- invasion biology. Our starting point is an existing resource in invasion biology that organizes and relates core hypotheses in the field and associates them to meta-data for more than 1000 scientific publications, which was developed over the course of several years based on manual analysis. This network, however, is currently static (i.e. needs substantial manual curation to be extended to incorporate new claims) and, moreover, is not easily accessible for users who miss specific background and domain knowledge in invasion biology. Our goal is to develop (i) a semantic model for representing knowledge on concepts and hypotheses, such that also non-expert users can use the network; (ii) a tool that automatically computes links from publication abstracts (and data) to these hypotheses; and (iii) an interactive system that supports users in refining their initial, potentially underdeveloped hypothesis.
Moving Object Detection in Video with Algorithms YOLO and Faster R-CNN in Different Conditions

Today, computer vision technology has been continuing to develop in many different areas such as object detection from video, motion tracking and object identification.It is difficult to detect moving objects such as pedestrians, cars, buses, and motorcycles in bad weather conditions or at night, especially in adverse weather conditions such as rain, fog, and snow.In this study, two types of object detection algorithms were utilized to identify objects under different conditions.These types can be identifed as one-step object detection algorithms and the two-step object detection algorithms.In this study, from the one-step algorithms YOLOv3 and YOLOv4, and from the two-step object detection algorithms Faster R-CNN were preferred.These algorithms were trained to identify four objects (pedestrians, car, bus, motorcycle) in bad weather and low light conditions.Then, comparisons of these three algorithms in all conditions was performed.By comparing YOLO versions (v3 and v4), it was aimed to observe the performance differences between these versions.By comparing YOLO and Faster R-CNN algorithms, the differences between the types one-step and two-step algorithms were evaluated.The algorithms were trained with open-image datasets.According to the results, YOLOv4 had the highest performance at 40,000 iterations, 72% mAP, and 63% recall.YOLOv3 has achieved the best result at 36,000 iterations, 65.53% mAP, and 54% recall, Faster R-CNN has achieved the best result at 36,000 iterations, 51% mAP, and 49% recall.To conclude, YOLOv4 performed the best compared to YOLOv3 and Faster R-CNN.
Understanding social relationships with person-pair relations

Social relationship understanding infers existing social relationships among individuals in a given scenario, which has been demonstrated to have a wide range of practical value in reality.However, existing methods infer the social relationship of each person pair in isolation, without considering the context-aware information for person pairs in the same scenario.The context-aware information for person pairs exists extensively in reality, that is, the social relationships of different person pairs in a simple scenario are always related to each other.For instance, if most of the person pairs in a simple scenario have the same social relationship, "friends", then the other pairs have a high probability of being "friends" or other similar coarse-level relationships, such as "intimate".This context-aware information should thus be considered in social relationship understanding.Therefore, this paper proposes a novel end-to-end trainable Person-Pair Relation Network (PPRN), which is a GRU-based graph inference network, to first extract the visual and position information as the person-pair feature information, then enable it to transfer on a fully-connected social graph, and finally utilizes different aggregators to collect different kinds of person-pair information.Unlike existing methods, the method-with its message passing mechanism in the graph model-can infer the social relationship of each person-pair in a joint way (i.e., not in isolation).Extensive experiments on People In Social Context (PISC)-and People In Photo Album (PIPA)-relation datasets show the superiority of our method compared to other methods.
Automated Aircraft Dent Inspection via a Modified Fourier Transform Profilometry Algorithm

The search for dents is a consistent part of the aircraft inspection workload. The engineer is required to find, measure, and report each dent over the aircraft skin. This process is not only hazardous, but also extremely subject to human factors and environmental conditions. This study discusses the feasibility of automated dent scanning via a single-shot triangular stereo Fourier transform algorithm, designed to be compatible with the use of an unmanned aerial vehicle. The original algorithm is modified introducing two main contributions. First, the automatic estimation of the pass-band filter removes the user interaction in the phase filtering process. Secondly, the employment of a virtual reference plane reduces unwrapping errors, leading to improved accuracy independently of the chosen unwrapping algorithm. Static experiments reached a mean absolute error of ∼0.1 mm at a distance of 60 cm, while dynamic experiments showed ∼0.3 mm at a distance of 120 cm. On average, the mean absolute error decreased by ∼34%, proving the validity of the proposed single-shot 3D reconstruction algorithm and suggesting its applicability for future automated dent inspections.
The Requirements for Knowledge and Skills of Managers in ICT Modified Fourth Industrial Revolution

Digitalisation and new technologies transform current world into digital one and thus leading towards changes of customer behaviour, business models, innovations, methods of operation, as well as new generation of people, so called "Digital Natives".Management of human resources should create conditions for application of Industry 4.0 principles into practice in advance, based on analysis of digitalisation impact on their own business and its strategy, adapt processes of human resource planning.In order to acquire employees with digital qualification and thinking, it will be necessary to alter their recruitment, especially with orientation on social media and mobile variations of traditional recruitment channels.This scientific article points out a change in human capital competence impacted by the fourth Industrial revolution.This scientific article eventuates into proposal of requests for skills and knowledge of managers on different levels of management determined by fourth industrial revolution.
Decentralized, Privacy-Preserving, Single Sign-On

In current single sign-on authentication schemes on the web, users are required to interact with identity providers securely to set up authentication data during a registration phase and receive a token (credential) for future access to services and applications. This type of interaction can make authentication schemes challenging in terms of security and availability. From a security perspective, a main threat is theft of authentication reference data stored with identity providers. An adversary could easily abuse such data to mount an offline dictionary attack for obtaining the underlying password or biometric. From a privacy perspective, identity providers are able to track user activity and control sensitive user data. In terms of availability, users rely on trusted third-party servers that need to be available during authentication. We propose a novel decentralized privacy-preserving single sign-on scheme through the Decentralized Anonymous Multi-Factor Authentication (DAMFA), a new authentication scheme where identity providers no longer require sensitive user data and can no longer track individual user activity. Moreover, our protocol eliminates dependence on an always-on identity provider during user authentication, allowing service providers to authenticate users at any time without interacting with the identity provider. Our approach builds on threshold oblivious pseudorandom functions (TOPRF) to improve resistance against offline attacks and uses a distributed transaction ledger to improve availability. We prove the security of DAMFA in the universal composibility (UC) model by defining a UC definition (ideal functionality) for DAMFA and formally proving the security of our scheme via ideal-real simulation. Finally, we demonstrate the practicability of our proposed scheme through a prototype implementation.
On the issue of partnerships in the teacher-student dyad in the conditions of the educational space of a modern university

This article presents the results of an empirical study on the formation of partnerships in the teacher-student dyad. A broad review of literary sources on the issues under consideration has been carried out. The features of pedagogical communication in the conditions of modern higher education have been studied. It is concluded that at present there is a tendency to democratize relations in the teacher-student system, their transition to a new level of partnership and cooperation. The problem includes the question of the readiness of the teachers themselves for this format of interaction with students. The study included the use of a questionnaire specially developed by the author, the use of which made it possible to identify the most significant indicators characterizing the optimal relationship between the teacher and students, as well as criteria that are markers of non-developed relationships. The main conditions were noted, which, in the opinion of teachers, favorably influence the formation of teacher-student relationship. Along with this, the main professional and personal qualities of a teacher were identified, which are important in establishing favorable relationships with students and, conversely, hindering them. Shown are the personal qualities of students that contribute or, conversely, hinder the development of these relations. The results of this study can find further practical application in pedagogy, in educational and social psychology, and are also necessary for the psychological and pedagogical improvement of the educational process in higher education.
Modelling of Energy Storage System from Photoelectric Conversion in a Phase Change Battery

The essence of the research was to model the actual energy storage system obtained from photoelectric conversion in a phase change accumulator operating in a foil tunnel. The scope of the work covered the construction of four partial models, i.e., electricity yield from solar radiation conversion for three types of photovoltaic cells (mono- and polycrystalline and CIGS), energy storage in a PCM battery, heat losses in a PCM battery and energy collection from photoelectric conversion in PCM battery. Their construction was based on modelling methods selected on the basis of literature review and previous analyses, i.e., artificial neural networks (ANN), random forest (RF), enhanced regression trees (BRT), MARSplines (MARS), standard multiple regression (SMR), standard C&amp;RT regression trees (CRT), exhaustive CHAID for regression (CHAID). Based on the analysis of the error values (APE, MAPE, ΔESRt), the best quality models were selected and used in the further part of the work. Based on the developed models, a simulation of the influence of the size of the photovoltaic power plant and the type of cells on the process of storing energy from photoelectric conversion in a PCM battery was carried out. For the battery under study, a PV power output of 9 kWp for mono and polycrystalline panels and 13 kWp for CIGS panels is recommended for reasons of energy storage efficiency. The obtained results made it possible to develop a model determining the amount of energy stored in a phase change battery depending on the power of a photovoltaic power plant and variable solar conditions. In order to store the greatest amount of energy, we should choose a source with a capacity to produce at least 70 kWh of electricity per day. In the final stage of the work, the indicators of solar radiation energy storage in the tested phase change accumulator were determined. For the battery tested, the solar energy storage efficiency can reach 12–13% for mono and polycrystalline panels and less than 7% for CIGS panels.
Toward Designer Modeling Through Design Style Clustering

We propose modeling designer style in mixed-initiative game content creation tools as archetypical design traces. These design traces are formulated as transitions between design styles; these design styles are in turn found through clustering all intermediate designs along the way to making a complete design. This method is implemented in the Evolutionary Dungeon Designer, a research platform for mixed-initiative systems to create adventure and dungeon crawler games. We present results both in the form of design styles for rooms, which can be analyzed to better understand the kind of rooms designed by users, and in the form of archetypical sequences between these rooms, i.e., Designer Personas.
Measuring Digital Capital: Methodological Approaches

The relevance of this study is determined by the ongoing digital transformation of Russian society. The formation and accumulation of digital capital influences the effectiveness of social actors and is a way to overcome social inequality. Researchers are actively engaged in investigating the phenomenon of digital capital and in developing models and methods for its measurement. The purpose of this article was to study methodological approaches to measuring the level of digital capital and to conceptualizing the idea itself. The main methodological foundations of the work were the theory of the information society, the concept of the digital economy, the theory of social capital (Bourdieu), the theory of digital capital (Ragnedda), the theory of digital capitalism (Fuchs), and the theory of digital inequality (digital divide). Theoretical sources were analyzed in this empirical analysis. In modern science, there is no common concept of digital capital and there are numerous possibilities for its measurement and impact on the digital divide. This article discusses the main theoretical approaches to measuring digital capital based on basic theories. Existing methods for measuring digital capital were analyzed, and the advantages and disadvantages of these methods were identified.&#x0D; Keywords: digital capital, measurement of digital capital, digital divide, information society, digital capitalism
Geology and gold content of carbonaceous shale in Baikal mineralization site, Southern Ural

The authors analyze gold mineralization in Baikal site inside Kumak ore field, adjoined to Bredin black shale sediments (С1bd).It is found that the gold mineralization within the site adjoins mostly bands of quart-micaceous-tourmaline metasomatically altered carbonaceous shale.Float sampling of all local rock varieties shows commercial content of gold (to 6.5 g/t) and stable high content of silver (to 7.6 g/t).Gold is mostly finely dispersed, and is connected with two basic mineral associations: gold-bismuth-telluride and native gold intergrown with tourmaline.The analysis of compositions of gold particles reveals their high carat type.Chemically, tourmaline belongs to dravite and foitite, and is similar to tourmaline from the deposits of orogenic gold and goldbearing sulfide ores.Tight accretion of fine needle-like tourmaline and gold implies their synchronous formation, and allows assessing Baikal site as the quartz-tourmaline gold ore formation.
An Efficient Variant of Pollard’s p − 1 for the Case That All Prime Factors of the p − 1 in B-Smooth

Due to the computational limitations at present, there is no efficient integer factorization algorithm that can break at least 2048 bits of RSA with strong prime factors in polynomial time. Although Shor’s algorithm based on a quantum computer has been presented, the quantum computer is still in its early stages of the development. As a result, the integer factorization problem (IFP) is a technique that is still being refined. Pollard’s p − 1 is an integer factorization algorithm based on all prime factors of p − 1 or q − 1, where p and q are two distinct prime factors of modulus. In fact, Pollard’s p − 1 is an efficient method when all prime factors of p − 1 or q − 1 are small. The aim of this paper is to propose a variant of Pollard’s p − 1 in order to decrease the computation time. In general, the proposed method is very efficient when all prime factors of p − 1 or q − 1 are the members of B-smooth. Assuming this condition exists, the experimental results demonstrate that the proposed method is approximately 80 to 90 percent faster than Pollard’s p − 1. Furthermore, the proposed technique is still faster than Pollard’s p − 1 for some values of modulus in which at least one integer is a prime factor of p − 1 or q − 1 while it is not a member of B-smooth. In addition, it is demonstrated that the proposed method’s best-case running time is O(x),where x is represented as bits length of n.