Complex Technology Research Articles

CHALLENGES AND OPPORTUNITIES IN IMPLEMENTING WEB 3.0 STRATEGIES

This article examines the problems and opportunities that organisations face in implementing a Web 3.0 strategy. It explores the decentralised and transparent characteristics of Web 3.0 technologies, including blockchain, smart contracts and decentralised apps (dApps), and their future impact on business operations. Methodology. The article applies a qualitative methodology using case studies of Fortune Global 500 companies to offer practical advice on Web 3.0 adoption, the obstacles they face and recommendations for overcoming these challenges. Results. Research shows that while the adoption of Web 3.0 offers significant promise for improving operational efficiency, transparency and customer trust, significant obstacles such as regulatory uncertainty, integration costs and technological complexity still need to be overcome. Overcoming industry-specific challenges and implementing customised solutions is crucial to the effective use of Web 3.0 technologies. Practical implications. The article offers practical solutions for businesses to effectively integrate Web 3.0 technologies, which will help increase operational efficiency, strengthen trust with consumers and open up new revenue opportunities through tokenisation and decentralised finance. Value/Originality. The article offers practical solutions for businesses to effectively integrate Web 3.0 technologies, which will help increase operational efficiency, strengthen trust with consumers and open up new revenue opportunities through tokenisation and decentralised finance.

Improvement of construction and technological properties of cement hardening systems for building composites

The article provides information on the formation of hardening systems of building composites (STSC) as a result of directional structure formation and the involvement of the active component of metallurgical slags. It is shown that the structures of the STSC can be represented as a consequence of formation (design and synthesis) of the structures of the particle addition system of the raw material mixture, and for more complex technologies – as a growth system. The main physico-chemical properties and characteristics of modifying additives for STSC are considered. The influence of slag additives on the main construction and technological properties of hardening systems based on man-made raw materials has been established. Special attention is paid to the kinetics of the grinding capacity of the designed hardening systems of building composites.

Does the service trade network impact on technological complexity of exports?——New perspective based on social network approach

ABSTRACT In the context of the digital economy, digital service trade has gradually become a new driving force for the high-quality development of foreign trade in various countries. Based on the bilateral data of digital service trade between 56 countries from 2005 to 2021, this paper constructs the global digital service trade network through social network analysis method. Also, this study examines the impact of the network characteristics on its export technology complexity. According to our research findings, first, in terms of the overall characteristics, the number of participating countries in digital service trade is increasing, and the density is overall low but showing an upward trend. Second, in terms of individual characteristics, the ranking is relatively stable, developed countries such as Europe and the United States with higher centrality, connectedness and heterogeneity are the dominant players in the digital service trade. But the indicators of each characteristic are decreasing over time, verifying the fact that the global digital service trade has become more open and inclusive. Third, we examined that centrality, connectedness, and heterogeneity all contribute significantly to export technological complexity. Technological innovation is the main path of action. The results still hold after performing a series of robustness tests.

Disability, digital technologies and the ambivalent allure of posthumanist/transhumanist futures

Technologies, both simple and sophisticated, have always played a major role in the negotiation of a range of disabilities that are assumed to impede the expression of autonomous selfhood. Whether deployed as mechanical aides to ideally normalise physical differences, as organic—and often internal—supplements to bolster the performance of body and mind, or as digital enhancements that override the supposed shortcomings of neurodiversity, the widely accepted claim is that such technologies have a clear therapeutic value. It conjures the illusion of an unproblematised sequence of more complex technologies leading to increasingly enhanced function and the advent of superior selfhood. Those who identify as having disabilities, either physical or cognitive, are assured of a better future in which anomalies are sufficiently offset to the extent that they no longer attract disvalue.My paper offers a less conventional perspective that leaves behind the desire for individual autonomy and opens up the question of the transhuman and the posthuman. Rather than focusing on the bounded self at the centre of humanist thought, I ask what is at stake when human embodiment becomes intricately entangled with non-human materialities and digital coding. It is likely that the major developments in such ‘prosthetic’ technologies will strongly impact the field of disability. Beyond a merely functional usage, which is likely to dominate in the short term, urgent questions arise about the extent to which the category of the human can or should be sustained as the anchor of continuing life. In exploring the practical, philosophical and bioethical implications of newly emerging technologies, I distinguish between the motivation of transhumanism, which focuses on self-perfectibility and mastery, and a posthumanism that in seeking to radically decentre the very notion of human privilege and hierarchical distinctions offers an optimistic view of disability futures.

Virtual Healthcare for Older Adults With Preventable Chronic Conditions: A Meta-synthesis of Quality Aspects.

Our study employed a six-step meta-synthesis approach to understand quality aspects of virtual healthcare trajectories and identify effective strategies for older adults with preventable chronic conditions across the world. Review of twenty-one articles revealed four key themes: functionality of virtual healthcare, equity in service delivery, satisfaction with care, and cost-effectiveness. Despite the challenges posed by technological and clinical complexities, virtual healthcare initiatives have significantly improved accessibility and availability of health services, thereby reducing disparities. Notably, telehealth saved an average of 166-minutes of travel time, demonstrating a clear benefit of virtual healthcare. While all parties expressed satisfaction with virtual healthcare, several challenges were reported, including a digital divide, limited access to digital devices, absence of a multidisciplinary approach, and lack of rural-specific programs.

Bioinspired cooperation in a heterogeneous robot swarm using ferrofluid artificial pheromones for uncontrolled environments

This article presents a novel bioinspired technology for the cooperation and coordination of heterogeneous robot swarms in uncontrolled environments, utilizing an artificial pheromone composed of magnetized ferrofluids. Communication between different types of robots is achieved indirectly through stigmergy, where messages are inherently associated with specific locations. This approach is advantageous for swarm experimentation outside controlled laboratory spaces, where localization is typically managed through centralized camera systems (e.g. infrared, RGB). Applying pheromone principles has also proven beneficial for various swarm behaviors. We introduce a detection methodology for the artificial ferrofluid pheromone using low-cost magnetic sensors, along with signal processing and parameter characterization. Experiments involved a heterogeneous swarm consisting of two types of robots: one equipped with camera and image processing capabilities and the other with basic sensor technologies. Validation in multiple uncontrolled environments (with varying floor surfaces, wind, and light conditions) demonstrated successful cooperation among robots with differing technological complexities using the proposed technology.

Machine learning, banking, industry, digitalization, innovation

Aim: The application of artificial intelligence (AI) offers an encouraging avenue for developments in the banking industry. Methods: The study adopted a scoping review of methodology to provide a comprehensive overview of relevant research regarding the potential uses and challenges of AI in banking. Consumer expectations have evolved, emphasizing features such as payment gateways, swift transactions, and resilient banking services. Results: Major utilization of the AI in banking industry includes enhanced customer engagement, satisfaction, and relationships, personalized financial guidance, smart digital wallets, regulation compliance and collaborative efforts, forecasting, tracking market trends, decision-making and problem-solving, anti-money laundering and fraud detection, automation of repetitive, large and time-intensive tasks, enhanced cybersecurity, and opportunity for digital financial inclusion. Conclusion: Users encounter challenges involving security issues, privacy concerns, and the complexity of technology in AI-driven banking services. Recommendation: While AI holds a crucial role in the banking industry, successful implementation demands ample allocation and consistent, predictable utilization of AI practices.

Satisfaction With the Use of a Mobile Application: Adopsi Teknologi pada Aplikasi Mobile PLN

The development of information technology has an impact on business growth in Indonesia. One example is PT PLN developing the PLN mobile application to facilitate customers in accessing the services provided. The purpose of this study is to determine the influence of Barriers (Resistance to change and Technological Complexity) and Facilitators (Technical Support, Compatibility, Performance Expectancy, and Easy of use) on Satisfaction with the use of a mobile application in the Mobile PLN app. The research method used in this study is a quantitative method by distributing questionnaires to users of the PLN mobile app. The results of the study indicate that resistance to change positively affects user satisfaction with the mobile PLN application, as users feel more satisfied when the application does not disrupt their routines. Conversely, technological complexity negatively affects user satisfaction; the higher the complexity, the lower the satisfaction. A stable and easy-to-use application increases satisfaction. Effective and responsive technical support also enhances user satisfaction. The application's compatibility with users' lifestyles has a significant impact; an application integrated with users' routines increases satisfaction. Fulfilled performance expectations, such as tangible benefits, efficiency, and productivity, also positively affect user satisfaction. Easy of use has a significant influence; an intuitive and user-friendly application increases overall user satisfaction.

Pedagogical conditions justification of professional multilingual personality building of non-language future specialists

Introduction. New guidelines in the development of economy, informatisation of society, the process of integration of cultures in the world have changed the requirements for the education of future specialists. One of the most important characteristics of modern society is the international interaction of organisations and specialists. This need necessitates the training of professional staff capable of working effectively in an open polylingual space. The purpose of the research is to substantiate the pedagogical conditions for the professional multilingual personality building of non-language future specialists and to develop a set of innovative teaching technologies in the multilingual educational space of higher education institution. Materials and methods. The study involved 43 teachers of Russian State Agrarian University – Moscow Timiryazev Agricultural Academy and National Research Mordovia State University, 255 student-respondents studying in the above-mentioned universities. The participants of the pedagogical experiment were provided with materials aimed at the professional multylingual personality building (teaching aids, reference materials, open mass online courses, digital resources). Technical means, digital tools were used to record the obtained results. Methods: analysis of theoretical sources, analysis and generalization of the experience of Russian universities in training non-language future specialists, results of students' and teachers' educational activities, pedagogical experiment, statistical processing of the results using the Pearson's chi-square test. Results. The pedagogical conditions of professional multilingual personality building of non-language future specialists were revealed and substantiated. The students training on the basis of the developed complex of technologies of professional multilingual personality building of future specialists was carried out. The results are summarised, which testify to the effectiveness of the identified pedagogical conditions and the potential of the applied complex of innovative teaching technologies in the polylingual educational space of the higher education institution. The results are summarised and the statistical significance of the differences in the qualitative changes in the results between the professional polylingual personality levels оf future specialists obtained before and after the experiment was determined (χ2 emp. = 19,987; p < 0,01). Conclusions. The identified pedagogical conditions and the proposed set of technologies for the professional polylingual personality building of future specialists of non-linguistic training profiles allow to increase their competitiveness in the labour market. The pedagogical potential of innovative teaching technologies in the multilingual educational space of higher education institution is aimed at the development of creative individual abilities of students, meeting their needs in moral, physical and intellectual improvement, their self-organisation. The developed set of technologies can be applied in the training of undergraduate, graduate, postgraduate students of non-language universities, students of further professional retraining.

Development of mathematical models of power consumption at coal plants

The object of research is coal enterprises where powerful electrical equipment is used (underground installations up to 3000 kW, tunneling complexes of 500–1500 kW, technological complexes of 6–10/0.4 kV, etc.). The deficit of generated capacities, caused by growing energy consumption, can be reduced by regulating power consumption modes. The relevance of this issue is determined by the need to conduct a research of the electricity consumption system, to determine the qualitative and quantitative characteristics of electricity consumption using mathematical models. The lack of mathematical models makes it difficult to analyze energy intensity and consumption modes of each technological operation in the overall balance of electricity consumption of coal enterprises. The article considers the structure and classification of the main technological groups of energy consumers, the development of mathematical models for each type of load modes, as well as a generalized model of electricity consumption of coal enterprises, with the use of mathematical apparatus of probability theory and mathematical statistics. As a result of the work, mathematical models of the electricity consumption process for the main technological groups and for models of daily electricity consumption of coal enterprises as a whole were developed, and it was also established that technological objects of electricity consumption are divided into three different values, in terms of power consumption modes: constant, uniform and pulse. For each class of consumers their statistical characteristics were obtained. The work results can be applied for managing power consumption modes of coal enterprises

Challenges and Opportunities in the Adoption of Flexible Manufacturing Systems in Indian Manufacturing Industries

The manufacturing sector is increasingly adopting automation technologies to enhance productivity and flexibility. Among these technologies, Flexible Manufacturing Systems (FMS) offer substantial benefits, such as reduced lead times, improved production flexibility, and lowered operational costs. Despite its advantages, FMS adoption in Indian manufacturing industries has been slow due to several barriers, including high capital costs, technological complexity, and inadequate government support. This study investigates the current status of FMS adoption in India, identifies the key barriers hindering its implementation, and proposes a decision-making model to facilitate its wider adoption. The research gap highlights the lack of a comprehensive framework to quantify the barriers and assess the performance of FMS adoption. To address this, a two-phase Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology was used. This approach allowed for the classification and prioritization of barriers, as well as the development of a model for FMS selection based on statistical analysis. A case study was conducted using this methodology to evaluate various FMS models and provide a systematic decision-making framework for manufacturers. The results revealed that the most significant barriers to FMS adoption in India include high upfront costs, insufficient infrastructure, and the challenges posed by rapidly advancing FMS technology. By applying the AHP-TOPSIS approach, this study offers insights into overcoming these barriers and presents actionable recommendations for manufacturers and policymakers. The findings emphasize the need for increased government support and industry collaboration to accelerate FMS adoption in India. This research contributes to the development of a structured decision-making framework, which could help manufacturers implement FMS more effectively, thereby enhancing competitiveness in an increasingly dynamic global market. Keywords— Flexible Manufacturing Systems, Barriers to FMS, Indian Manufacturing, AHP-TOPSIS, Decision-Making Model

The Impact of AI on International Trade: Opportunities and Challenges

This study aims to explore the transformative potential of Artificial Intelligence (AI) in international trade, focusing on its key roles in optimizing trade operations, enhancing trade finance, and expanding market access. In trade optimization, AI leverages advanced machine learning and predictive analytics to enhance demand forecasting, route optimization, and customs procedures, leading to more efficient logistics and inventory management. In trade finance, AI can automate document processing and risk assessment, increasing access to finance and enhancing transactional transparency, particularly through integration with blockchain technology. In terms of market access, AI-driven analytics can identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. Due to the lack of quantitative data, this study employed qualitative research methods, specifically a multiple-case-study approach. The case studies of leading companies such as Alibaba, DHL, and Maersk showcase how they leverage AI to optimize their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI’s practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include issues around data quality, ethical concerns, technological complexity, and public perception. Policy recommendations highlight the need for a robust data infrastructure, establishing ethical AI guidelines, and fostering international cooperation to align data protection regulations.

Construction of a generalized mathematical model and fast calculations of plane-parallel rotating magnetic fields in process reactors with longitudinal currents of cylindrical inductors on a graphical calculator

The object of research is a quasi-stationary rotating magnetic field (RMF) generated by cylindrical inductors with longitudinal windings in the working space of process reactors, in particular reactors designed to work with magnetic particles (MP). The RMF theory in the working space of reactors has not yet been sufficiently developed, which hinders the widespread introduction of the considered, rather complex technologies into practice. The RMF of a specific reactor can be calculated accurately and completely using modern programs based on the finite element method, but it does not replace the general theory and theoretical analysis. In the literature, special cases of circular and elliptical plane-parallel RMF in reactors of the type under consideration have been studied, however, analytical formulas for a plane-parallel RMF for the general case of m-phase cylindrical inductors of external and internal design with symmetrical longitudinal windings are not presented. In this paper, a mathematical model is constructed and generalized analytical formulas for magnetic induction are obtained, linking the characteristics of a plane-parallel RMF in the working space of reactors at idle speed with the main parameters of external and internal cylindrical inductors with an m-phase symmetric longitudinal winding. A physical analysis is carried out and the adequacy of the model is confirmed. Using the proposed formulas and a free, easy-to-use Desmos graphical calculator, quick trial calculations and analysis of RMF in several reactors with two-pole external inductors and various windings for three phases (for 6 and 42 slots) and for six phases (12 slots) are carried out. The calculation results are consistent with experimental and literary data. New analytical formulas, as well as the demonstrated methods of quick evaluation calculations, analysis and experimental studies are recommended for practical implementation in the research, development and operation of reactors of this type. To carry out the calculations, it is enough to have a laptop or smartphone connected to the Internet, the time costs are insignificant. The results of the work will be useful to technologists, engineers and developers of both the reactors of the type under consideration and other devices with a similar purpose with an RMF.

Analysis the Functions for James Webb Telescope on THESAN Project

The THESAN simulation project is a method used to understand the universe. However, the usage of such simulations often requires a lot of computation, complex technology, and high-end equipment, among which James Webb Telescope (JWST) is one of the most important devices in the simulation. The purpose of this study is to analyze and introduce the function and impact of JWST in the THESAN simulation project. First of all, this article briefly introduces the THESAN simulation project and JWST. Then, the study presents the JWST observation mission of galaxy clusters, clusters of galaxies, nebulae and exoplanets in the specific data, as well as the strategy of ERO program in detail. Finally, the paper describes the impact and improvement of the observations made after the JWST launch on the THESAN simulation project and various related data. According to the analysis, these results help stakeholders understand the function of JWST in the THESAN simulation project more quickly.

Data-Driven Personalization : Revolutionizing User Experience

Data-driven personalization has emerged as a transformative approach in digital user experience design, leveraging advanced analytics and machine learning to tailor content and interfaces to individual users. This article explores five key aspects of data-driven personalization: user behavior analysis, segmentation and targeting, machine learning algorithms, real-time adaptation, and privacy and ethical considerations. It examines the significant impact of personalization on business outcomes, including increased revenue and customer engagement, while also addressing implementation challenges, such as technological complexity and privacy concerns. The article provides insights into the methodologies, processes, and best practices for effective personalization, supported by industry statistics and case studies, offering a comprehensive overview of how organizations can harness this powerful approach to create more engaging, relevant, and effective digital experiences.

Understanding What Drives the Adoption of Data Analytics Among Academic Leaders and Supervisors in a Jewish Higher Education Institution

This study explores the determinants influencing the adoption of Big Data Analytics (BDA) within the Jewish higher education system centered in the Northwestern United States of America, emphasizing the impact of six key factors: Absorptive Capacity, Technological Resource Competency, Competition Intensity, Complexity, Compatibility, and Relative Advantage, alongside participants' age. Utilizing a quantitative methodology, the research surveyed 64 managerial role employees across the academic institution. Results from multiple regression analysis indicate a statistically significant relationship between these factors and the behavioral intention toward BDA adoption, with Compatibility emerging as the predominant predictor. This finding underscores the critical role of perceived consistency with existing needs and practices in influencing BDA adoption intentions. Moreover, Marketing Department Leadership exhibited significantly lower ratings in both Absorptive Capacity and behavioral intention toward BDA adoption based on a MANOVA analysis compared to other types of academic institutional leaders, suggesting a discrepancy in recognizing and leveraging new external information for competitive advantage within this group. The study concludes with recommendations for higher education institutions aiming to transition towards data-driven decision-making, highlighting the importance of fostering an organizational culture that values data literacy and aligns BDA initiatives with institutional goals. Limitations and directions for future research are also discussed, advocating for a broader investigation into behavioral intentions and the potential benefits of applying the Decomposed Theory of Planned Behavior in understanding BDA adoption.

Integrating Artificial Intelligence into ESG Practices: Opportunities, Challenges, and Strategic Solutions for Corporate Sustainability

Environmental, social, and governance (ESG) practices have become increasingly important in corporate strategy in recent years, while the rapid development of artificial intelligence (AI) has created new opportunities and challenges for corporate sustainability. AI technology driving companies for ESG time is getting more and more attention. This study examines the application of AI technologies in environmental management, social responsibility, and corporate governance, demonstrating their potential to optimize resource utilization, reduce carbon emissions, improve recruitment fairness, and prevent fraud. However, integrating AI with ESG faces many challenges, including technological complexity, high costs, data privacy and ethical issues, and organizational and cultural resistance. To address these challenges, this study proposes solutions to reduce financial burdens, secure data, and enhance cultural buy-in through strategies such as technology partnerships, open-source tools, and employee training. By delving into the convergence of AI and ESG, this study provides companies with a guiding direction to fully utilize the potential of AI while maintaining long-term sustainability.

Future Trends of Open-Source AI in Libraries: Implications for Librarianship and Service Delivery

This paper explores the future trends and implications of open-source artificial intelligence (AI) for libraries, focusing on predicted technological advancements, long-term impacts on library operations, and the evolving role of librarians. Key advancements, such as enhanced natural language processing, intelligent recommendation systems, and advanced data analytics, are expected to significantly improve user experience and operational efficiency. The implications of these technologies include more personalized and responsive service delivery, streamlined operations, and an evolution in the roles and responsibilities of library staff. Librarians will need to develop new skills and advocate for ethical AI use, ensuring that AI applications align with the library’s values of inclusivity and accessibility. Additionally, the paper discusses the challenges of adopting open-source AI, including technological complexity, resource constraints, and data privacy concerns. The paper concludes that embracing open-source AI fosters innovation and collaboration, positioning libraries as vital hubs of knowledge and community engagement in the future.

A Methodological Framework for High-Resolution Surface Urban Heat Island Mapping: Integration of UAS Remote Sensing, GIS, and the Local Climate Zoning Concept

The urban heat island effect (UHI) is among the major challenges of urban climate, which is continuously intensifying its impact on urban life and functioning. Against the backdrop of increasingly prolonged heatwaves observed in recent years, practical questions about adaptation measures in cities are growing—questions that traditional meteorological monitoring can hardly answer adequately. On the other hand, UHI has long been the focus of research interest, but due to the technological complexity of providing accurate spatially referenced data at high spatial resolution and the requirement to survey at strictly defined parts of the day, information provision is becoming a major challenge. This is one of the main reasons why UHI research results are less often used directly in urban spatial planning. However, advances in geospatial technologies, including unmanned aerial systems (UASs), are providing more and more reliable tools that can be applied to achieve better and higher-quality information resources that adequately characterize the UHI phenomenon. This paper presents a developed and tested methodology for the rapid and efficient assessment and mapping of the effects of surface urban heat island (SUHI). It is entirely based on the integrated use of data from unmanned aerial systems (UAS)-based remote sensing methods, including thermal photogrammetry and GIS-based analysis methods. The study follows the understanding that correct SUHI research depends on a proper understanding of the urban geosystem, its spatial and structural heterogeneity, and its functional systems, which in turn can only be achieved by supporting the research process with accurate and reliable information resources. In this regard, the possibilities offered by the proposed methodological scheme for efficient geospatial registration of SUHI variations at the microscale, including the calculation of intra-urban SUHI intensity, are discussed in detail. The methodology builds on classical approaches for using local climate zoning (LCZ), adding capabilities for precise delineation of individual zone types and for geostatistical characterization of the urban surface heat island (SUHI). Finally, the proposed scheme is based on state-of-the-art technological tools that provide flexible and automated capabilities to investigate the phenomenon at microscales, including by enabling flexible observation of its dynamics in terms of heat wave manifestation and evolution. Results are presented from a series of sequential tests conducted on the largest residential area in Bulgaria’s capital city, Sofia, in terms of area and population, over a relatively long period from 2021 to 2024.

Identifying and Managing Risks in High-Tech Supply Networks using Explainable Artificial Intelligence

Supply chains have become vital in enabling the smooth movement of material and information in the swiftly changing high-tech industries. By utilising technological innovations like automation and AI, supply chains may improve both safety and effectiveness at every level of the process, from manufacturing to sustainability. The necessity to adjust operations, give the adoption of technology top priority for resilience, and improve supply chain management efficiency. Transformation of the Supply Chain is becoming a choice of subject, when it comes to maintain the ideal inventory levels and Just in Time service deliveries. Both AI and ML are the utmost importance for the maintenance of the inventory or service through the technology. It not only helps in reducing the loss of opportunity costs, but also it resolves the issue of overstocks of any inventory and the enhanced level of service delivery. This ultimately results in the optimum utilization of the resources through the help of technology. Moreover, it is the win-win situation for the customer and provider. Even while technology has only recently begun to be incorporated into supply chains, the manufacturing and distribution sectors have adopted it more quickly, emphasising the need for effective risk identification and mitigation techniques. Notwithstanding the possible advantages of transforming the supply chain, there are obstacles and limitations that make an entire technological shift complex. The chapter also explores the concept explainable AI which can be understood as the set of techniques that makes the decision-making processes of AI systems comprehensible to humans. Acknowledging the inherent complexities and relationships within these chains, the goal of this chapter is to explore risk identification and management in high-tech supply networks. A competent and nimble stakeholder base can manage the complex landscape of the high-tech world through the incorporation of innovative technologies, proactive actions, and constructive alliances.