Reviewerly/exHarmony huggingface dataset:
USING EXPERT REVIEW METHODS TO SELECT TRUE CRITERIA FOR PUBLICATION COLLABORATIONS

The purpose of the scientific work is to assess the quality of a set of scientometric indicators to determine the degree of truth of publication scientific collaborations. The paper presents the definition of a publication collaboration of scientists. The main types of collaborations are described: true and false. A list of external and internal alternatives (indicators) for their assessment has been formed. As an analysis of the system for evaluating scientific activity, a ninescreen diagram of the system for evaluating activities in the field of publication activity of the FSBEI HE “Nosov Magnitogorsk State Technical University” (NMSTU). From the analysis of the scheme, it can be seen that today there is a traditional system for evaluating publication collaborations. It has been determined that the existing system for assessing the degree of truth of publication collaborations must be supplemented with decisionmaking scenarios and an updated list of indicators for assessing links between the authors of scientific papers. For this, a group of experts (heads of scientific and educational organizations) was selected, who formed a list of external and internal alternatives (indicators) to assess the truth of publication collaborations of scientists of a higher educational institution. For the reliability of the results of the formation of the list of alternatives, it was decided that it was necessary to assess the competence and consistency of experts. The list of external alternatives for evaluating the validity of publication collaborations was used as the initial data for peer review. Coefficients were calculated to assess competence and consistency. It is concluded that the generated list of external alternatives is considered qualitative for assessing the degree of truth of publication collaborations.
Beamshaping beacon light for satellite quantum key distribution: spatial separation and point ahead angle

Quantum Key Distribution (QKD) uses quantum states in an optical channel to grow a key with guaranteed security. Satellite QKD (SatQKD) is a proposed topology for QKD which provides unlimited terrestrial range for links and allows mobile access. SatQKD (and generally satellite optical communications) Optical Ground Stations (OGSs) require an optical beacon, a beam from OGS to satellite to assist pointing the satellite's telescope(s). Beaconing is challenging for SatQKD due to the single-photon sensitivity of the receiver to back-reflected beacon light and the need to point the outgoing beacon ahead of the downlink channel (the Point-Ahead Angle (PAA)). Hence, beacon light is often propagated through separate telescopes, increasing complexity. We describe a spatially separated beacon which reduces back-reflection errors and how its PAA is achieved. The far field beams of this and other beacon architectures are compared. Beaconing in this way can give greater up-time (due to less maintenance) and a lower cost barrier to development. A related system could have similar benefits for laser-guide-star telescopes.
PREDICTION OF THE PROGRESS OF UNIVERSITY STUDENTS BASED ON COLLABORATIVE FILTERING ALGORITHMS

Building an optimal individual educational trajectory for students is currently impossible without the use of recommender systems. The role of such a system for individual educational trajectory is to inform the student about the most useful disciplines for him, based on his interests and academic performance. An important factor for recommendations is the forecast of student progress. Through assessments, the student's inclination to a particular subject, as well as the level of his education, can be expressed. In addition, the success of mastering the discipline greatly affects the motivation of students. Thus, an important part of the recommender system is the prediction model. The article describes an approach to developing a system for predicting the progress of university students in elective disciplines. The predictive model is based on machine learning algorithms. Collaborative filtering was used as the main method. The sources for collecting data on the digital footprint of students are the electronic educational information environment of the university and the official portal, which hosts educational standards, work programs and annotations. Information about students and their progress is presented in the form of three tables – a rating plan, disciplines and a list of students. The data structure has the form of a double nested dictionary, where the keys are sections of the university from faculty to specialty and year of study, and the values are tables with the student identification number, course of study, subject, normalized grade, and elective and model labels. To solve the filtering problem, k-means algorithms, cosine proximity, and Pearson correlation were used. The applied approaches are able to work for small data and do not require large performance costs. The resulting predictive model has a sufficiently high accuracy and can be used in recommender systems to build individual educational trajectories of university students.
Cutting-Edge Trajectory Optimization through Quantum Annealing

This paper introduces an innovative approach to explore the capabilities of Quantum Annealing (QA) for trajectory optimization in dynamic systems. The proposed method involves transforming trajectory optimization problems into equivalent binary optimization problems using Quadratic Unconstrained Binary Optimization (QUBO) representation. The procedure is general and adaptable, making it applicable to a wide range of optimal control problems that entail the satisfaction of dynamic, boundary, and path constraints. Specifically, the trajectory is discretized and approximated using polynomials. In contrast to the conventional approach of determining the polynomial degree (n) solely based on the number of boundary conditions, a specific factor is introduced in our method to augment the polynomial degree. As a result, the ultimate polynomial degree is calculated as a composite of two components: n = l + (m−1), where m denotes the count of boundary conditions and l signifies the number of independent variables. By leveraging inverse dynamics, the control required to follow the approximated trajectory can be determined as a linear function of independent variables l. As a result, the optimization function, which is represented by the integral of the square of the control, can be formulated as a QUBO problem and the QA is employed to find the optimal binary solutions.
Chinese Fine-Grained Named Entity Recognition Based on BILTAR and GlobalPointer Modules

The task of fine-grained named entity recognition is to locate entities in text and classify them into predefined fine-grained categories. At present, Chinese fine-grained NER only uses the pretrained language model to encode the characters in the sentence and lacks the ability to extract the deep semantic, sequence, and position information. The sequence annotation method is character-based and lacks the processing of entity boundaries. Fine-grained entity categories have a high degree of similarity, which makes it difficult to distinguish similar categories. To solve the above problems, this paper constructs the BILTAR deep semantic extraction module and adds the GlobalPointer module to improve the accuracy of Chinese fine-grained named entity recognition. The BILTAR module is used to extract deep semantic features from the coding information of pretrained language models and use higher-quality features to improve the model performance. In the GlobalPointer module, the model first adds the rotation position encoding information to the feature vector, using the position information to achieve data enhancement. Finally, the model considers all possible entity boundaries through the GlobalPointer module and calculates the scores for all possible entity boundaries in each category. In this paper, all possible entity boundaries in the text are considered by the above method, and the accuracy of entity recognition is improved. In this paper, the corresponding experiments were carried out on CLUENER 2020 and the micro Chinese fine-grained NER dataset, and the F1 scores of the model in this paper reached 80.848% and 75.751%, respectively. In ablation experiments, the proposed method outperforms the most advanced baseline model and improves the performance of the basic model.
Numerical security analysis of the three-state quantum key distribution protocol with realistic devices

Quantum key distribution (QKD) is a secure communication method that utilizes the principles of quantum mechanics to establish secret keys. The central task in the study of QKD is to prove security in the presence of an eavesdropper with unlimited computational power. In this work, we successfully solve a long-standing open question of the security analysis for the three-state QKD protocol with realistic devices, i.e., the weak coherent-state source. We prove the existence of the squashing model for the measurement settings in the three-state protocol. This enables the reduction of measurement dimensionality, allowing for key rate computations using the numerical approach. We conduct numerical simulations to evaluate the key rate performance. The simulation results show that we achieve a communication distance of up to 200 km.
ChatGPT use among University Students: an exploratory study

The main purpose of this study is to analyze the use of ChatGPT, a language model developed by OpenAI, among university students. The study covers post graduate students from different academic disciplines of Sidho-Kanho-Birsha University, Purulia, West Bengal. For this study the necessary data have been collected though online questionnaire. The study finds that students use ChatGPT for their academic and research purpose and they also believe that ChatGPT is moderately effective in this case.
Decentralized Autonomous Organization Governance By Upgradeable Diamond Smart Contracts

Upgrading smart contracts allows DAOs and other Dapps to fix bugs and upgrade their functionality. The most widely used pattern for upgrading is the proxy pattern. However, the proxy pattern centralizes power in the one who has access to the admin address, which can be called admin centralization. In this article, we describe how the diamond pattern (ERC-2535) can be used to set up decentralized governance. We describe how the diamond pattern is configured and complemented by census governance. The proposed pattern has three advantages: 1) governance of smart contracts without admin centralization; 2) non-technical member participation in governance without smart contract knowledge; 3) user-friendly upgradeable DAO implementation using a graphical interface. To extend the use of the diamond pattern, we call for the creation of user-friendly tooling and smart contract facets.
Debiasing Machine-Learning- or AI-Generated Regressors in Partial Linear Models

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The use of high-frequency data in cryptocurrency research: A meta-review of literature with bibliometric analysis

As the crypto-asset ecosystem matures, the use of high-frequency data becomes increasingly common in decentralized finance literature. Using bibliometric analysis, we characterize the existing cryptocurrency literature that employs high-frequency data. Based on 189 articles collected from the Scopus database from 2015 to 2022, we highlight the most influential authors, articles, and journals. This approach enables us to identify the emerging trends and research hotspots with the aid of co-citation and cartographic analyses and shows the knowledge expansion through authors’ collaboration in the cryptocurrency research with co-authorship analysis. We identify four major streams of research: (i) return prediction and measurement of volatility in cryptocurrencies; (ii) (in)efficiency of cryptocurrencies; (iii) price dynamics and bubbles in cryptocurrencies; and (iv) diversification, safe haven and hedging properties of Bitcoin. We conclude that the investment features and the economic outcomes of highly trading cryptocurrencies would be analysed predominantly on tick-by-tick bases in the future. This paper provides recommendations for future research.
Free Speech is Incomplete? Big Tech in a Distant Mirror

In 1961, Alexander Meiklejohn claimed that the First Amendment, the US provision guaranteeing free speech, is an absolute. Echoing this in the context of the rise of fake news, Tim Wu has recently asked whether the First Amendment might have become obsolete. Yet, with the growing power of Big Tech, concerns are also voiced that their impact on free speech may go too far. However, there is tension here: on the one hand, the unprecedented role of Big Techs provides incentives for regulation; on the other, free speech is such a sensitive subject that there are reasons for limiting government interference. Against this backdrop, this article investigates whether the current situation is indeed unprecedented: it looks into the past, present, and future of market-situated free speech. It concludes that free speech might be incomplete, since while the impact of Big Techs is not unprecedented, it involves (historically) unresolved features.
Closing the Gap: Automated Distractor Generation in Japanese Language Testing

Recent advances in natural language processing have increased interest in automatic question generation, particularly in education (e.g., math, biology, law, medicine, and languages) due to its efficiency in assessing comprehension. Specifically, multiple-choice questions have become popular, especially in standardized language proficiency tests. However, manually creating high-quality tests is time-consuming and challenging. Distractor generation, a critical aspect of multiple-choice question creation, is often overlooked, yet it plays a crucial role in test quality. Generating appropriate distractors requires ensuring they are incorrect but related to the correct answer (semantically or contextually), are grammatically correct, and of similar length to the target word. While various languages have seen research in automatic distractor generation, Japanese has received limited attention. This paper addresses this gap by automatically generating cloze tests, including distractors, for Japanese language proficiency tests, evaluating the generated questions’ quality, difficulty, and preferred distractor types, and comparing them to human-made questions through automatic and manual evaluations.
Blockchain-based decentralised Common Data Environment: user requirements and conceptual framework

The ISO19650 standard proposed a common data environment (CDE) as a single source of truth for all project information that facilitates continuous collaboration between stakeholders. In practice, multiple CDEs are used simultaneously, leading to a lack of data integrity, traceability and transparency. Moreover, current centralised cloud-based CDEs are vulnerable to security risks such as data manipulation which magnifies the lack of trust among project stakeholders. Previous studies, proposing blockchain for information management focus on narrow use cases and do not encompass the whole lifecycle of a built asset. This work aims to develop a framework for decentralised information management in relation to all phases of the lifecycle. First, we identify the needs of the users for a CDE using desk research and an empirical approach including semi-structured interviews with industry experts. It is found that the top user requirement is integrating data scattered across multiple CDEs along the built asset's lifecycle in a single source of truth. A CDE should provide an accountable and transparent record of the entire project history integrating data from various tools utilised during the lifecycle. In the final step, we propose a conceptual framework for a blockchain-based CDE where transactions from various tools used along the entire lifecycle of a built asset are recorded on a blockchain linked with Inter-Planetary File Storage (IPFS) to increase the security of the files. Three illustrative use-case scenarios demonstrate the framework's applicability in design, construction, and operation phases. The utilisation of blockchain technology ensures an immutable, independent, and reliable record of all transactions, offering a comprehensive and tamperproof history. This approach not only addresses existing gaps in previous studies but also lays the foundation for establishing trustworthy Product and Material Passports.
Voice-Controlled Intelligent Personal Assistant for Call-Center Automation in the Uzbek Language

The demand for customer support call centers has surged across various sectors due to the pandemic. Yet, the constraints of round-the-clock human services and fluctuating wait times pose challenges in fully meeting customer needs. In response, there’s a growing need for automated customer service systems that can provide responses tailored to specific domains and in the native languages of customers, particularly in developing nations like Uzbekistan where call center usage is on the rise. Our system, “UzAssistant,” is designed to recognize user voices and accurately present customer issues in standardized Uzbek, as well as vocalize the responses to voice queries. It employs feature extraction and recurrent neural network (RNN)-based models for effective automatic speech recognition, achieving an impressive 96.4% accuracy in real-time tests with 56 participants. Additionally, the system incorporates a sentence similarity assessment method and a text-to-speech (TTS) synthesis feature specifically for the Uzbek language. The TTS component utilizes the WaveNet architecture to convert text into speech in Uzbek.
Implementation of an Efficient Image Transmission Algorithm for Unmanned Surface Vehicles Based on Semantic Communication

With the increasingly maturing technology of unmanned surface vehicles (USVs), their applications are becoming more and more widespread. In order to meet operational requirements in complex scenarios, the real-time interaction and linkage of a large amount of information is required between USVs, between USVs and mother ships, and between USVs and shore-based monitoring systems. Visual images are the main perceptual information gathered from USVs, and their efficient transmission and recognition directly affect the real-time performance of information exchange. However, poor maritime communication signals, strong channel interference, and low bandwidth pose great challenges to efficient image transmission. Traditional image transmission methods have difficulty meeting the real-time and image quality requirements of visual image transmissions from USVs. Therefore, this paper proposes an efficient method for visual image transmission from USVs based on semantic communication. A self-encoder network for semantic encoding which compresses the image into low-dimensional latent semantics through the encoding end, thereby preserving semantic information while greatly reducing the amount of data transmitted, is designed. On the other hand, a generative adversarial network is designed for semantic decoding. The decoding end decodes and reconstructs high-quality images from the semantic information transmitted through the channel, thereby improving the efficiency of image transmission. The experimental results show that the performance of the algorithm is significantly superior to traditional image transmission methods, achieving the best image quality while transmitting the minimum amount of data. Compared with the typical BPG algorithm, when the compression ratio of the proposed algorithm is 51.6% of that of the BPG algorithm, the PSNR and SSIM values are 7.6% and 5.7% higher than the BPG algorithm, respectively. And the average total time of the proposed algorithm is only 59.4% of that of the BPG algorithm.
Usable Security: A Systematic Literature Review

Usable security involves designing security measures that accommodate users’ needs and behaviors. Balancing usability and security poses challenges: the more secure the systems, the less usable they will be. On the contrary, more usable systems will be less secure. Numerous studies have addressed this balance. These studies, spanning psychology and computer science/engineering, contribute diverse perspectives, necessitating a systematic review to understand strategies and findings in this area. This systematic literature review examined articles on usable security from 2005 to 2022. A total of 55 research studies were selected after evaluation. The studies have been broadly categorized into four main clusters, each addressing different aspects: (1) usability of authentication methods, (2) helping security developers improve usability, (3) design strategies for influencing user security behavior, and (4) formal models for usable security evaluation. Based on this review, we report that the field’s current state reveals a certain immaturity, with studies tending toward system comparisons rather than establishing robust design guidelines based on a thorough analysis of user behavior. A common theoretical and methodological background is one of the main areas for improvement in this area of research. Moreover, the absence of requirements for Usable security in almost all development contexts greatly discourages implementing good practices since the earlier stages of development.
Optimized Protocols for Duplex Quantum Transduction

Quantum transducers convert quantum signals through hybrid interfaces of physical platforms in quantum networks. Modeled as quantum communication channels, performance of unidirectional quantum transduction can be measured by the quantum channel capacity. However, characterizing performance of quantum transducers used for duplex quantum transduction where signals are converted bidirectionally remains an open question. Here, we propose rate regions to characterize the performance of duplex quantum transduction. Using this tool, we find that quantum transducers optimized for simultaneous duplex transduction can outperform strategies based on the standard protocol of time-shared unidirectional transduction. Integrated over the frequency domain, we demonstrate that the rate region can also characterize quantum transducers with finite bandwidth.
Dynamic Analysis of Impulsive Differential Chaotic System and Its Application in Image Encryption

In this paper, we study the dynamic behavior of an impulse differential chaotic system which can be applied to image encryption. Combined with the chaotic characteristics of the high dimensional impulsive differential equations, the plaintext image can be encrypted by using the traditional Henon map and diffusion sequences encryption algorithm. The initial values and control parameters serve as keys for encryption algorithms, and the algorithm has a larger key space. The key is resistant to minor interference and the accuracy can reach 10−12. The simulation results show that the impulsive differential chaotic system has a good application prospect in image encryption.
Criticism of the digital ruble project

During the search for a worthy candidate for the BRICS currency, such digital means of payment that are understandable and acceptable to all participants in financial relations begin to play a special role. For this reason, innovations in the field of the digital ruble should be objectively subjected to scrupulous analysis and constructive criticism, which can eliminate a significant part of doubts about the correctness of the practical implementation of this project. The historically determined period of the beginning of the transition to a new material carrier of value, which takes the form of a digital signal, should make maximum use of high-quality scientific support and in no way discredit the relevant scientific approaches.