Automated Process Research Articles

Smart Contracts and Machine Learning: Exploring Blockchain and AI in Fintech

Background: The rapid evolution of technology in the financial technology (fintech) sector has necessitated the adoption of innovative solutions to address increasing demands for higher data rates, lower latency, and enhanced security. Traditional centralized systems are susceptible to data tampering, service disruptions, and man-in-the-middle attacks, compromising the integrity of sensitive financial transactions. Objectives: This paper aims to explore the convergence of blockchain technology, smart contracts, and machine learning to address security, transparency, and operational efficiency challenges in the fintech sector. It investigates the implications of these technologies for compliance, regulatory frameworks, and ethical governance. Method: The study reviews existing literature and data sources spanning the last decade, with a focus on blockchain applications in fintech. Inclusion criteria include studies on decentralized ledgers, smart contract automation, and machine learning algorithms for predictive analytics. Comparative analyses are presented through flowcharts, graphs, and tables to highlight operational improvements, security enhancements, and cost reductions. Findings: Blockchain technology provides a decentralized and immutable ledger that enhances transparency and security in financial transactions. Smart contracts automate processes, reducing operational costs and improving accessibility to underserved populations. Machine learning enhances blockchain applications by enabling predictive analytics and data-driven decision-making. Despite significant advancements, challenges remain, including the need for robust governance structures to ensure ethical implementation and compliance with regulatory standards. Significance: This review offers new insights by integrating blockchain and machine learning in the context of fintech, addressing critical aspects such as operational efficiency, security, and regulatory compliance that were underexplored in prior studies. It highlights the transformative potential of these technologies in fostering innovation while providing a roadmap for overcoming bottlenecks and paving the way for a secure, inclusive, and efficient financial ecosystem. Keywords: Fintech, AI in Finance, Smart Contracts, Distributed Ledgers, Blockchain

Use of AI and ML in Banking & Finance to Improve Decision-Making, Automate Processes, and Enhance Customer Experiences

Use of AI and ML in Banking & Finance to Improve Decision-Making, Automate Processes, and Enhance Customer Experiences

Blockchain Security in Financial Transactions: A Decentralized Approach

Blockchain technology has emerged as a pivotal solution for enhancing security in financial transactions through its decentralized architecture. Traditional financial systems are often vulnerable to fraud, data breaches, and single points of failure due to centralization. Blockchain, with its distributed ledger system, ensures transparency, immutability, and security by verifying transactions across a network of nodes without relying on a central authority. This decentralized approach mitigates the risks associated with centralized databases, such as hacking or unauthorized access. Blockchain’s cryptographic algorithms safeguard transaction integrity and protect sensitive financial information. Smart contracts automate processes, reducing human error and the need for intermediaries, thereby increasing efficiency while lowering operational costs. Despite its benefits, challenges remain, including scalability issues, regulatory hurdles, and energy consumption. As blockchain technology continues to evolve, it holds the potential to revolutionize financial transactions, offering a robust, secure, and transparent framework for future financial systems. This paper explores the mechanisms behind blockchain security and its impact on modern financial infrastructures.

Orchestration Workflows in Distributed Systems: A Systematic Analysis of Efficiency Optimization and Service Coordination

This article presents a comprehensive analysis of orchestration workflows in modern software architectures, examining their role in optimizing service efficiency and coordination across distributed systems. Through a systematic investigation of implementation patterns and operational strategies, we demonstrate how orchestrated workflows enhance service integration, automate complex processes, and improve system reliability. The article employs a mixed-method approach, combining quantitative performance metrics from real-world implementations with qualitative analysis of architectural patterns across diverse enterprise environments. The findings reveal that organizations implementing robust orchestration workflows experienced a 47% reduction in service integration failures, 35% improvement in resource utilization, and 62% faster deployment cycles. The article also identifies critical success factors in orchestration implementation, including dynamic resource management, automated error handling, and comprehensive monitoring frameworks. Furthermore, The article proposes a novel framework for evaluating orchestration effectiveness in cloud-native environments, considering factors such as service mesh integration, container orchestration, and distributed tracing. This article contributes to the growing body of knowledge in service optimization by providing empirical evidence of orchestration benefits and offering practical guidelines for implementing scalable, resilient software systems through advanced workflow orchestration strategies.

The impact of digital transformation of communities on the initiation and planning of social projects

The author analyzes the state of the art in the theory and practice of social project management. It is established that the digital transformation of communities creates prerequisites for improving the efficiency of the processes of initiating and planning social projects. The purpose of the study is to substantiate the prerequisites for increasing the efficiency of social project initiation and planning processes through the digital transformation of communities and, on their basis, to analyze the digital tools used to implement social development projects. The substantiated prerequisites for improving the efficiency of social project initiation and planning include 6 components, which are implemented by 9 types of digital tools. They provide quick access to information, automate management processes, increase the effectiveness of communication with the population of communities, and improve monitoring and evaluation of the effectiveness of social projects. An analysis of existing digital tools for the implementation of social projects for community development is carried out. It is established that they have both individual advantages and limitations for use in initiating and planning social projects. It has been proven that the use of specialized platforms for data collection and analysis helps to increase the efficiency of initiating and planning social projects. Also, the use of specialized platforms for initiating and planning social projects provides better control over resource and budget expenditures. Using the example of using open data on local initiative project competitions held in the Lviv region in 2018-2021, the article analyzes the indicators of implementation of social healthcare development projects in the Lviv region. These projects were funded from the regional budget. It was found that the results obtained are useful for project managers. Prospect for further research is the development of tools to support management decision-making on the implementation of social projects for community development using the proposed digital technologies.

Artificial intelligence as a mode of ordering. Automated-decision making in primary care

ABSTRACT This paper examines the process of organizing primary care from the increasing production of digital data and algorithms, leading to decision-making being delegated to automated processes. Based on a case study of primary care in Catalonia (Spain), we develop an interpretative framework to analyze the effects and controversies of the introduction of AI in primary care, stressing the need to understand these technologies as historically situated trends, as part of a growing automation process of ordering frontline clinical care. To foster a nuanced discussion on the mode of ordering of automation, we replace the notion of AI with Automated Decision-Making (ADM) and use the conceptual distinction between striated and smooth spaces, as developed by Deleuze & Guattari. With the analysis we identify four dynamics that order and organize health, illness, and public health systems: (1) The capacity of Electronic Health Records and associated software to shape the daily routines of primary care; (2) The dual role of healthcare professionals, who serve as both data users and data collectors; (3) The system of values and priorities configured by the network of classification systems in use and; (4) The emerging tensions during the progressive automation processes. These dynamics configure a mode of ordering characterized by diminishing the importance of experiential knowledge, the reduction of patient negotiation capacity, the professionals’ discomfort with being constantly monitored and controlled, as well as the gradual neglect of factors related to socio-economic determinants of health.

Онтологический подход в управлении адаптивной подготовкой групп специалистов

An integrated approach to solving the problems of managing the adaptive training process for groups of specialists is proposed, allowing for the consideration of changing external and internal factors, as well as the dynamics of changes in the specialists' training levels. This approach enables rapid adjustment of the training scenario to current situations. The implementation is based on ontological and predictive modeling of the adaptive training process. The article de-scribes the meta-ontology for adaptive training of specialist groups in organizational and technical systems for auto-mated training process management. It discusses an approach to solving problems of collecting, summarizing, and analyzing the cycle of intelligent management of adaptive training for specialist groups using meta-ontology. The de-veloped meta-ontology enables automatic determination of trainees' knowledge and skills, stored in their profiles and updated based on completed training stages. This increases the efficiency of forming control actions (educational and training tasks) and improves the quality of training.

A Delve into the Implementation of Data Quality Framework on Very Large Databases

In today’s data-driven landscape, the reliability and accuracy of information are paramount for informed decision-making and operational efficiency. A robust data quality framework provides a structured methodology for managing and maintaining the quality of data as-sets throughout their lifecycle. It in-troduces a comprehensive data qual-ity framework encompassing four key pillars: data governance, data profil-ing, data cleansing, and data monitor-ing. The foundation of the framework lies in establishing clear data governance policies and procedures, defining owner-ship, responsibilities, and accountability for data quality across the organization. Data profiling techniques are then em-ployed to assess the quality of data, iden-tifying anomalies, inconsistencies, and inaccuracies. Subsequently, data cleans-ing processes are implemented to rec-tify these issues, employing techniques such as deduplication, standardization, and validation to ensure data integrity. Continuous data monitoring is integral to the framework, enabling proactive de-tection of data quality issues and facil-itating timely corrective actions. Ad-vanced analytics and machine learn-ing algorithms may be leveraged to au-tomate monitoring processes, flagging anomalies and deviations from prede-fined quality thresholds.

Bio-Optical Properties near a Coastal Convergence Zone Derived from Aircraft Remote Sensing Imagery and Modeling

Bio-optical and physical measurements were collected in the Mississippi Sound (Northern Gulf of Mexico) during the spring of 2018 as part of the Integrated Coastal Bio-Optical Dynamics project. The goal was to examine the impact of atmospheric and tidal fronts on fine-scale physical and bio-optical property distributions in a shallow, dynamic, coastal environment. During a 25-day experiment, eight moorings were deployed in the vicinity of a frontal zone. For a one-week period in the middle of the mooring deployment, focused ship sampling was conducted with aircraft and unmanned aerial vehicle overflights, acquiring hyperspectral optical and thermal data. The personnel in the aircraft located visible color fronts indicating the convergence of two water masses and directed the ship to the front. Dye releases were performed on opposite sides of a front, and coincident aircraft and unmanned aerial vehicle overflights were collected to facilitate visualization of advection/mixing/dispersion processes. Radiometric calibration of the optical hyperspectral sensor was performed. Empirical Line Calibration was also performed to atmospherically correct the aircraft imagery using in situ remote sensing reflectance measurements as calibration sources. Bio-optical properties were subsequently derived from the atmospherically corrected aircraft and unmanned aerial vehicle imagery using the Naval Research Laboratory Automated Processing System.

Technology of Intellectualization of Automated Process Control Systems Based on a Software and Hardware Complex

Technology of Intellectualization of Automated Process Control Systems Based on a Software and Hardware Complex

ПРИМЕНЕНИЕ ТЕХНОЛОГИЙ ИНТЕРНЕТА ВЕЩЕЙ (IOT) В МОНИТОРИНГЕ И УПРАВЛЕНИИ РАСПРЕДЕЛЕННЫМИ ЭНЕРГОСИСТЕМАМИ

The article is devoted to the study of the application of Internet of Things (IoT) technologies in the field of monitoring and managing distributed energy systems. The paper considers key aspects of using IoT to improve the efficiency of energy systems, automate control processes and improve the reliability of energy distribution. Practical examples of successful IoT implementations are given, the advantages and problems that arise are analyzed, and the prospects for further development of this technology in the energy sector are discussed.

Principles of Constructing a HIL Simulation Stand for Debugging Automated Process Control Systems based on the Baget PLC

The problem of constructing a HIL simulation stand for researching a technological process using programmable logic controller (PLC) "Baget" is described in this article. Issues of modeling technological processes are currently extremely relevant, since modeling is a mandatory stage in the automated process control systems development. An adequate model of the technological process allows debugging and verification of automated process control system algorithms without using real equipment, reducing financial costs and the probability of emergency situations. The HIL modeling method involves partial use of real equipment as part of the model. The inclusion of standard components of the original object in the model does not require detailed mathematical model and at the same time provides a more complete correspondence to the original. Due to using a computer from the original object, the stand software operates under conditions close to the real technological process, which improves the quality of the simulation results. The HIL modeling stand includes the following components: control computer of automated process control system; programmable logic controller PLC "Baget"; simulation computer. The stand for the basic element of an automated process control system allows to speed up the process of prototyping and debugging even in the case of complex systems, because it will be easier to build the entire system from correctly functioning elements. Another advantage of this approach is that the stand is not tied to a specific type of technological process or to a narrow area of production — the stand allows the use of ready-made models, the development of new models, and the inclusion of various function libraries. The simplicity of the stand design with this approach is combined with a full range of functionality. By connecting additional software, you can create more complicated and detaild model. This stand is also capable of serving both for debugging PLC algorithms and as a simulator for maintenance personnel of a real control object, because the stand operator can simulate failures and errors of standard equipment, emergency situations at the control object. Using C and JavaScript programming languages for development ensures portability and ease of expanding the capabilities of the modeling software. The development of complex systems based on HIL modeling allows saving resources and effectively solving assigned problems, therefore the proposed approach to building stands will be in demand in the process of developing an automated process control system based on the PLC "Baget".

Information technology for managing information risks for projects of digital business transformation

In the article, the authors revealed the problem of information risk management when implementing digital technologies in business and its relevance. Today creates new challenges for businesses: gathering and storing large volumes of information, transaction history and customer base, all of which can be subject to both cyber threats and technical failures, which can lead to serious financial and reputational losses. Modern information technologies allow businesses to instantly respond to market changes and automate business processes. That is why information technologies are responsible for solving the issue of management effectiveness, in particular, management of information risks in business (detection, analysis, assessment of risks based on available data). The authors proposed the structure of information technology for information risk management of digital transformation projects in business. This structure is built on the basis of the method of anti-risk management of digital transformation projects in business and creates opportunities for the most effective implementation of project activities. The article also proposes an algorithm for filling the information database of information risk management with a description of the relevant processes. The proposed algorithm allows you to manage information risks, reducing the likelihood of threatening situations, time and costs for project implementation. Information technology is one of the effective tools in the process of solving the problems of information risk management during the implementation of digital transformation projects in business. The work presents schemes of the structure of the information base and the algorithm for filling the information database of information risk management of digital transformation projects in business.

Identifying Mathematics Anxiety Through Automated Process (IMATAP): A Web-Based Screening Tool for Teachers

Mathematics anxiety (MA) is considered a potential barrier to success in science, technology, engineering, and mathematics (STEM) careers. A good number of students around the globe are terrified of mathematics. They do whatever they can to avoid math or math-related subjects. Therefore, the early identification of MA and its underlying factors is crucial in initiating timely interventions that can enhance positive attitudes in math, boost math performance, minimize math avoidance, and motivate students to pursue math-related careers. In this paper, we have presented a unique, multifaceted, and complete web-based MA screening tool called identifying mathematics anxiety through an automated process (IMATAP) to assess MA, its severity, and its deficiency. This assessment provides a detailed explanation of developing MA and helps teachers, parents, educators, and researchers design need-based intervention techniques (personalized or cluster-based) to reduce MA, which will ultimately help math-anxious students overcome math fear. Over the past two years (2021–2022), IMATAP has been successfully implemented in nine different primary and secondary level institutions in Bangladesh. Findings revealed that the effectiveness of the IMATAP system has been appreciated and highly accepted by both students and teachers.

Use of AI in Surveying Process of Land Measurement

We have seen a shift from traditional surveying techniques to more automated techniques and processes, such as the introduction of drones for surveying. For drone surveys, unmanned aerial vehicles (UAVs), also known as drones, are equipped with high-resolution cameras that capture data. Whilst facing initial resistance, drone surveys have been widely adopted within the surveying industry due to them allowing surveyors to collect data more quickly and efficiently than ever before. In land surveying, another automation process that we have seen being used over the past few years is the use of machine learning algorithms to effectively analyse data. Machine learning algorithms are used to automatically detect and map changes in land use over time, allowing for land surveyors to easily recognise areas that may be of interest or concern, and to provide clients with accurate data that enables them to make more informed decisions. One example of an automated process in land surveying is the use of drones. Drones equipped with cameras and sensors can be used to quickly and accurately survey large areas of land, capturing high-resolution images and data that can be used to create detailed maps. This can save time and money compared to traditional surveying methods, such as using a total station or GPS

Automated superconducting qubit characterization platform based on a modified 3D printer

Josephson Junctions are important components in superconducting qubits. It introduces anharmonicity to the energy level spacings of the qubit which allow us to identify two unique quantum energy states for computing. It is difficult to fabricate multiple junctions within the same desired parameter range. Characterisation of the junctions is, therefore, a necessary step after fabrication. In particular, the critical current of the junctions is determined by measuring their normal state resistance. This is done via two-point or four-point resistance measurement at a manual probe station which is a time-consuming process, especially for wafer-scale fabrication. This bottleneck can be circumvented by automation with object detection. The base of the automated probe station is a 3D printer modified with multiple Arduino Uno microcontrollers and motorized linear stages. The automation process is achieved via auto-alignment of the probes and an automatic measurement procedure. As a result, the fully automated process will take about 27–29[Formula: see text]s to measure the resistance of one junction which saves 28%–51% of the time compared to the manual probe station and can be unsupervised. Due to the reuse of a commercial 3D printer, the cost of this system is 800 SGD which is much less than comparable commercial solutions.

Modern methods of searching in systems of archiving scientific works

In the conditions of digitization of the economic and educational sectors, artificial intelligence appears as one of the trending areas of technology development and penetrates into the lives of both specialists of various fields and scientists. Artificial intelligence, being a component of the development of modern society, is gaining momentum in its use in the context of solving industrial and educational problems through its integration into key digitization technologies. Every day dozens of new tools based on artificial intelligence are created that automate processes for various needs. One of the central challenges for artificial intelligence IT solutions is the task of "understanding" text, or rather, extracting meaning from text written in natural language. Practical solutions of smart language technologies aimed at analyzing the content of the text and can be used to solve local problems when building an information system for depositing the results of intellectual activity are ultimately reduced to this task. In particular, artificial intelligence technologies can be used for: automated determination of the scientific direction to which the content of the scientific document submitted for deposit belongs; further classification of scientific work; formation of a set of metadata; development of the search module of the system. The article is devoted to the study of various methods of searching and analyzing information in a document, based on artificial intelligence, and analyzing the functional capabilities of ready-made software solutions that can be useful in building an information system for depositing the results of intellectual activity.

Block-Chain Framework for Educational Domain and its Benefits

Blockchain technology has gained significant attention in recent years due to its potential to revolutionize various industries. In the educational domain, a blockchain-based framework has emerged as a promising solution with several benefits. This paper explores the concept of a blockchain-based framework for the educational domain and highlights its benefits. The framework focuses on areas such as credential verification, academic records and transcripts, anti-fraud measures, micro-credentialing, secure assessments, and efficient data sharing. By leveraging blockchain technology, educational institutions can enhance transparency, security, and efficiency in these areas. Credential verification becomes more reliable and tamper-proof as digital credentials are stored on the blockchain. Academic records and transcripts can be securely shared between institutions, simplifying the transfer process and reducing administrative burdens. Blockchain's immutability and cryptographic security features help combat issues like fake degrees or certificates, ensuring the authenticity of educational qualifications. The framework also enables the issuance and management of micro-credentials, reflecting specific skills or knowledge. By recording these credentials on the blockchain, individuals can have a comprehensive and verifiable record of their lifelong learning achievements. In the assessment process, blockchain technology enhances security and integrity by preventing data manipulation or cheating. The framework provides a decentralized and transparent platform for storing question banks, exam results, and assessments. Furthermore, blockchain-based frameworks facilitate secure and efficient sharing of educational resources, research findings, and collaborations. Smart contracts automate processes such as copyright permissions, royalty distributions, and collaborative project agreements, ensuring transparency and fairness. While the benefits of a blockchain-based framework in education are promising, challenges regarding technical implementation, scalability, cost-effectiveness, and privacy must be addressed. Further research and development are needed to explore these aspects and enable widespread adoption of blockchain solutions in the educational domain

AI Machine Vision based Oven White Paper ColorClassification and Label Position Real-time Monitoring System to Check Direction

We develop a vision system for batch inspection by oven white paper model color by manufacturing a machine vision system for the oven manufacturing automation process. In the vision system, white paper object detection (spring), color clustering, and histogram extraction are performed. In addition, for the automated process of home appliances, we intend to develop an automatic mold combination detection algorithm that inspects the label position and direction (angle/coordinate) using deep learning.

ANALYSIS OF TENDENCY DEVELOPMENT OF ENTERPRISES ISSUES AND THEIR INFLUENCE ON THE FORMATION OF ARCHITECTURAL SPACE

At the current stage, the restaurant industry is one of the most profitable spheres of economic activity in the world. And although historically it is one of the oldest spheres of human activity, it is quite innovative. It should be noted that there is no reference model for the formation of the architectural environment of catering establishments. Changes in the social, economic, and cultural environment affect the restaurant industry. However, this area has its own patterns. The specificity of this type of activity, the insufficient study of ego development trends have significant practical significance.
 In this article, an analysis of the main trends in the development of public housing and their direct influence on the organization of the architectural environment of these objects is carried out. Trying to be competitive, domestic catering enterprises are engaged in the search for new market segments, widely use innovations in the architecture and design of the establishment, high technologies and modern trends. Such trends include the intellectualization of the artificial environment and its acquisition of interactive properties; automation and contactless interaction; environmental friendliness and care for the environment; creation of monoproduct-type food establishments; national style; novelty impressed.
 It is noted that the interior of the dining hall is of great importance when deciding on a catering establishment. It should satisfy the aesthetic needs of visitors, give them new impressions and emotions, carry a meaningful load in accordance with the price segment and concept of the establishment. The methods of functional zoning of the interior space of the dining hall are highlighted: functional, aesthetic, spatial. It is noted that those catering establishments that improve their format according to modern development trends and make a significant bet on novelty are promising. Today, we can note the powerful implementation of the latest technologies in the architectural space, efforts to partially or maximally automate processes, introduce contactless interaction, and give the space intellectualization and interactive properties.