Reviewerly/exHarmony huggingface dataset:
A Privacy-aware Electronic Medical Record Sharing Scheme based on Blockchain and Identity-based Cryptography

At present, blockchain has become the research focus in the field of medical information, especially in the storage and sharing of electronic medical records (EMR). With the advent of the era of big data, data privacy is particularly important for patients. However, in existing blockchain-based electronic medical record-sharing schemes, the transaction address in the blockchain is related, which poses the risk of privacy disclosure for patients. To to solve this problem, this paper proposes a privacy-aware sharing scheme of electronic medical records based on stealth address and smart contracts. We introduce a novel identity-based stealth address scheme that can ensure the privacy protection of patient data and avoid the complexity of certificate management under the PKI system. As far as we know, this is the first of its kind. The patient can control the data autonomously through a smart contract. We present the specific design process of the scheme and the security proof of the related algorithm. Compared with the existing schemes, the identity-based cryptosystem is more suitable for users. Meanwhile, the scheme uses the decentralized storage platform IPFS to store EMR data to avoid the limitations of centralized data storage.
Research on GPU-Based Parallel Processing for the Paillier Algorithm

The homomorphic encryption algorithm Paillier is a cryptographic method that can be applied in areas such as privacy-preserving computation and federated learning. However, due to the inherent complexity and computational overhead of the algorithm, it may affect real-time requirements when dealing with a large volume of encrypted data. In this paper, we propose a method to improve the efficiency of the encryption algorithm by combining GPU parallel processing technology with homomorphic encryption. Through experiments on encrypting and decrypting plaintexts of different sizes, the results show that the introduction of GPU significantly improves the encryption and decryption speed. Compared with other parallel processing methods, the acceleration effect of our proposed method is more significant.
Integrated Intelligence Model for Assessment Digital Transformation Project

Managing digital transformation projects based on an integrated intellectual model requires the creation of tools for evaluating the performance of creating value. A conceptual model is proposed that evaluates the entrepreneurial energy and competence of the project team. Such estimates are normalized and reduced to a scale of 1–10. The developed structure of assessments of competence contains three groups - models of creative thinking, behavioral traits, attitudes and self-realization. The proposed model is based on the general structure of competencies of the P2M knowledge system. The research of the developed tools was carried out on one of the digital transformation projects by a group of ten experts. The analysis carried out confirmed the adequacy of the models and tools proposed by the authors.
Exploring the Intersection of AI Art and Film: A Case Study of Giant

Artificial intelligence (AI) has recently been used as a tool for various visual storytelling, but text-to-image models are a stochastic machine learning process that requires human intervention to assist creation better. As we all know, pre-visualization is an important stage in film production, involving subjective choices by the creators. This paper investigates how AI can assist filmmakers during the pre-production stage by generating mood boards from text. We propose a novel preproduction pipeline and guidelines that leverage text-to-image models to create visual previews of film projects. We also conduct a case study to validate and evaluate our approach's effectiveness. Our case study suggests that following the guidelines we have developed can assist filmmakers in generating mood boards that effectively convey the desired atmosphere of their projects and potentially contribute to enhancing the creative process. Our paper aims to contribute to the field of AI art and the film industry.
Voice Recognition Methods and Modules for the Development of an Intelligent Virtual Consultant Integrated with WEB-ERP

There were explored the methods and modules of voice recognition for the development of an intelligent virtual consultant, which plays an important role as an auxiliary tool when working with business process information systems and more precisely with the ERP system in this article. This study is intended to characterize an intelligent virtual consultant in evaluating the usefulness and effectiveness of using specific functions in a simulated enterprise resource planning (ERP) business process software system. The intelligent virtual consultant is integrated with the Web-ERP prototype. The Mel-frequency-Cepstral coefficient algorithm was utilized in conjunction with the Levenberg-Marquardt (LM) and Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods as the underlying basis for the analysis and extraction of features. A comparative analysis of these methods was also given to identify the effectiveness of used methods. A great benefit of this virtual consultant is the voice input of long text data fields when working on Web-ERP. This system is relevant because it significantly expands the search for business workflows. The developed system makes it possible to convert speech into text by extracting information system instructions. These texts are passed to an ontological database in which a query is executed using terms in order to get a set of available commands for its execution. When implementing an intelligent virtual consultant, it increases the capabilities of the application using not only user navigation through the system, but also makes it possible to navigate and explain data using speech synthesis. This prototype developed in the research will be used in a combination of an intelligent virtual consultant and data analysis.
$\pi_{\mathbf{RA}}$: A $\pi\text{-calculus}$ for Verifying Protocols that Use Remote Attestation

Remote attestation (RA) is a primitive that allows the authentication of software components on untrusted systems by relying on a root of trust. Network protocols can use the primitive to establish trust in remote software components they communicate with. As such, RA can be regarded as a first-class security primitive like (a)symmetric encryption, message authentication, etc. However, current formal models of RA do not allow analysing protocols that use the primitive without tying them to specific platforms, low-level languages, memory protection models, or implementation details. In this paper, we propose and demonstrate a new model, called <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pi_{\mathbf{RA}}$</tex> , that supports RA at a high level of abstraction by treating it as a cryptographic primitive in a variant of the applied <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pi- \mathbf{calculus}$</tex> . To demonstrate the use of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pi_{\mathbf{RA}}$</tex> , we use it to formalise and analyse the security of MAGE, an SGX-based framework that allows mutual attestation of multiple enclaves. The protocol is formalised in the form of a compiler that implements actor-based communication primitives in a source language <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\pi_{\text{Actor}})$</tex> in terms of remote attestation primitives in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pi_{\text{RA}}$</tex> . Our security analysis uncovers a caveat in the security of MAGE that was left unmentioned in the original paper.
Design and Research of Credit Sharing Model Based on Blockchain and Agent Re-encryption

The traditional credit investigation mode is often prone to data tampering and data leakage due to its centralized data storage, and once the data is damaged, it is difficult to recover the data, which will make the security of credit investigation data and personal privacy under serious threat. To solve the above problems, this paper proposes a credit-sharing scheme based on blockchain and agent re-encryption. Firstly, blockchain technology is used to solve the problems of data centralization, easy data tampering, easy data leakage, and other problems existing in traditional credit investigation platforms. Secondly, the SM2 encryption function is used to construct the proxy re-encryption algorithm, and the blockchain technology is combined to realize the safe sharing of credit data. Moreover, the interplanetary file system is used to effectively solve the problems of traditional credit centralized storage and the difficult recovery of data damage. Finally, the secure analysis and performance analysis show that this scheme not only realizes the security sharing of credit data but also has certain advantages in the aspect of computing cost.
Graph-based Analysis of the Algorand Blockchain Network

Over the past few years, Algorand has emerged as one of the prominent pure proof-of-stake (PPoS) blockchains, with a rapidly growing number of accounts and transactions. Despite its increasing significance, there is limited knowledge about its smart contracts, transaction activities, and other features. This paper presents the first comprehensive study of Algorand using graph analysis to investigate the creation of entities, payment of Algos, invocation of smart contracts, and transfer of assets over time. By collecting and analyzing external transaction data, we have constructed graphs to gain insights into the behavior of the blockchain. Our research has uncovered novel observations and insights by performing relevant graph analysis, and we have also proposed a solution to one security problem based on these graphs.
Unlocking the Power of Blockchain for Safe and Secure Electronic Personal Information and Health Record Management with the Use of Cloud Storage

Electronic Personnel Record (EPR) plays an important role in our lives. However, in most cases they are partitioned and stored in different databases owned by different institutions (hospitals, laboratories, clinics, offices, etc.) that are geographically dispersed in one or more countries. Due to this distributed and diversified nature of the various systems associated with accessing, sharing, protecting and tracking this personal data is difficult. Also, regular users cannot control their own private EPR. Recent scandals involving misuse of personal data by social media platforms and numerous breaches of user identity data have raised concerns about the technical, commercial, and ethical aspects of user data privacy and security. In this article, we introduced a management system architecture that is responsible for governing all electronic personal information and health record (EPIHR) of individual persons based on blockchain. Our proposed system architecture utilizes the tamper-proof attribute of the blockchain as well as overcomes the shortcomings of cloud-based data storage systems.
Test Design Methodology for Software Verification

This paper provides outlines the main points covered in a paper that provides a brief summary of software testing research. While the information is concise and informative, there is certainly room for expansion and further elaboration on the topic. To begin with, software testing is a critical component of the software development process. It involves the evaluation of software to ensure that it meets specific requirements, functions correctly, and is free of defects. The role of testing is to identify potential issues or errors in the software before it is released to end-users. There are various methods and models used in engineering testing of data processing software. Each of these methods focuses on a specific aspect of the software and aims to identify potential issues at different stages of development. In addition to testing methods, it is essential to have a structured testing process in place. Moreover, it is necessary to evaluate the testing process to determine its effectiveness and identify areas that may need improvement. Overall, software testing is a complex process that requires careful planning, execution, and evaluation. It is essential to use appropriate testing methods and models to ensure that software meets its intended purpose and functions correctly. By implementing a structured testing process and evaluating its effectiveness, software development teams can improve the quality and reliability of their products, leading to greater user satisfaction and increased business success.
Defender-Attacker Model Based Secure Software Development Lifecycle for Common Web Vulnerabilities

In this paper, we propose a novel secure software development life cycle (SSDLC) algorithm for web applications by observing and demonstrating the 3 most popular web vulnerabilities from both the attacker's and defender's roles. This algorithm is based on the defender-attacker model and aims to provide confidentiality in data.
Fine-Tuning the Wav2vec2 Model for Kazakh Speech: A Study on a Limited Corpus

In this study, we developed a model for automatic recognition of Kazakh speech by fine-tuning the XLSR-Wav2Vec2 pre-trained model to a corpus of Kazakh speech. Our results show that fine-tuning the wav2vec2 model on a small corpus of Kazakh speech allows a significant increase in recognition accuracy. However, larger datasets are needed to further evaluate the effectiveness of this approach. The results of this study contribute to ongoing efforts to improve speech recognition technology for low-resource languages such as Kazakh.
A Cross-Chain Identity Authentication Scheme for WSNs Based on Relay Chain

Wireless Sensor Networks (WSNs) have been widely employed in the electric power industry, such as for power production data monitoring and power distribution data collection, due to their low overhead and swift deployment. Nonetheless, the massive data exchange requirements in the energy sector pose a tremendous challenge to data security. To address this issue, this paper proposes a multi-chain based authentication scheme for WSNs, wherein the WSNs are divided into numerous local private blockchains according to regions and cross-chain technology is utilized for scalability and global authentication requirements of the devices. In addition, fog computing nodes, located at the edge of WSNs, are utilized to make up for the inadequate computing powers for blockchain deployment and decrease data transmission latency. Through experiments, the security, attackresistance, throughput, and latency of the proposed scheme were evaluated. The results demonstrate that the proposed scheme guarantees anonymity, security, and Confidentiality and is applicable for deployment in WSNs systems.
Assessing the Risk of Currency Digitalization in Kazakhstan

Every year, new technologies in every industry change the model and structure of processes in human life. Including the economy, which interacts so closely with us. After the advent of blockchain technology, many years have passed to test the viability of digital currency and digital wallets. Many countries are already introducing digital currencies at the state level. Since 2021, a study has begun on the need to introduce a national digital currency. A pilot project with basic functions was also developed and test launches of the digital tenge were carried out.
Augmented Reality Application to Support Visualization of Physics Experiments

Teaching physics is going through groundbreaking digital transformation. Teaching methodologies are quickly changing because of pandemic situation, which took place two thousand twenty and increased demand for digital practices of teaching physics with augmented reality. In article, I considered teaching methods in mobile application named «Physics Lab Augmented Reality”, designed for using augmented reality based physics laboratory experiments and demonstrations on high school physics lessons. Application demonstrates augmented reality technologies with three dimensional graphics features and special effects. In addition, it shows unseen factors of physical phenomena such as waves and sounds. This application is developed at university with promoting development small forms of lab experiments in physics classes.
Topic Modeling for Recent Newspaper Publications on Blockchain Technology in Kazakhstan

This paper aims to investigate the recent discussions and trends related to blockchain technology in Kazakhstan through topic modeling of newspaper publications. Utilizing advanced text analytics techniques, the study provides an in-depth analysis of the themes and topics discussed in the Kazakhstani media regarding blockchain and its potential applications in various sectors. The results of the study will shed light on the current state of blockchain awareness and adoption in Kazakhstan, as well as provide insights into the areas that require further attention and investment. The paper aims to serve as a valuable resource for policymakers, businesses, and technology enthusiasts looking to understand the impact of blockchain on Kazakhstan's economy and society.
Information and Intelligent Forecasting Systems Based on the Methods of Neural Network Theory

This paper is dedicated to the problem of the research of the information and intelligent forecasting systems which solve the problems of regression analysis. This class of the systems includes the systems that use different mathematical apparatus for forecasting, for the implementation of which a wide range of methods and algorithms is used. The paper also deals with the problems of regression analysis using elements of neural network theory. Developing a set of functions to form an approximating function allows you to create models that work efficiently. In existing information and intelligence systems, either implemented functions adapted to solve specific forecasting tasks, or, as in the case of neuropackages, it is considered that the proposed functions can be used to solve a wide range of tasks, adaptation to the conditions of the task occurs during the design of the neural network architecture. To create an approximating function, it is possible to implement linear and non-linear functions, which have proven themselves well in neural network analysis for solving a wide range of tasks and are obtained within the framework of deterministic chaos theory. To implement the function that approximates the dependence of the predicted value on the forecast arguments, the use of a two-layer heterogeneous, artificial neural network without feedback is proposed.
Payment Channel Network Optimization Composed of Merkle Tree with Election Mechanism

On-chain methods fail to improve the scalability of cryptocurrencies since they are constrained by block size and block creation rate. As a result, Payment Channel Networks (PCNs) have surfaced as a vital off-chain alternative for achieving scalability. In our prior research, we introduced a scheme called Accountable Assertions Performance optimization (A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PO) designed to identify malicious users in PCNs while optimizing computational efficiency and maintaining security. The original A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PO scheme assumed the third-party supervisor to be trustworthy; however, the potential for malicious behavior exists in reality. Consequently, we present an improved A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PO framework that incorporates an election mechanism. Supervisors for each transaction are automatically elected by calculating user balances. We offer a thorough security analysis, as well as the results of our evaluation show that the suggested scheme keeps the original A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PO’s benefits in terms of computing performance while enhancing security to thwart hostile supervisor operations.
Transforming Cognitive Maps into Markov Process Models for Software Development Projects

The complexity of managing software development projects in organizational and technical systems is due to a number of features. Such projects are weakly structured systems. The parameters of weakly structured systems form a complex “web” of connections and states that change over time. The development of projects in such a multifactorial environment can only be represented in the form of qualitative models. The use of cognitive maps with their subsequent presentation in the form of Markov chains allows quantifying the course of project processes, which are the main condition for the success of the project. At the same time, quantitative estimates represent not only a multi-vector picture of the state of projects, but also have the property of forecasting. The scope of the proposed method can be significantly expanded through the use in the educational process in the training of professionals in the field of programming and project management.
Research and Development of Enterprise Data Warehouse Based on SAP BW Modeling

The data warehouse is based on the development of relational databases, parallel processing and distributed processing technologies, as well as online analytical processing technologies. SAP BW is widely used in many enterprise data warehouses. It can issue reports of enterprises at the group level, manage the group's business operations, help find the laws and trends behind the performance of corporations and ultimately provide decision-making support for decision makers of enterprises. Therefore, how to use the SAP BW model architecture to better realize enterprise data warehouses is one of the hot topics in the data warehouse industry today. For a large corporation, its branches and subsidiaries have deployed multiple sets of enterprise data warehouses. At the same time, because there are multiple sets of data warehouse systems, when the data model needs to be modified at the group level, the data model of the branch also needs to be modified accordingly, and the flexibility of maintenance is poor. Finally, every time the corporation needs to upgrade the version of the data warehouse, it needs to maintain and upgrade the version of the data warehouse of each branch and the maintenance cost is high. Therefore, how to integrate multiple sets of data warehouses distributed in various subsidiaries into a corporation enterprise data warehouse by designing the model hierarchy, so as to ensure the reliability of data, enhance the flexibility of model modification and reduce the cost of data warehouse. This paper completes the design of an enterprise data warehouse of a large corporation, which can be used for the summary and collation of data from multiple branches such as finance and sales of a corporation, effectively improving the efficiency of data utilization and ensuring the authenticity of data. At the same time, through hierarchical design, the problems of poor flexibility in model modification and high system maintenance costs are solved.