Convergence Of Technologies Research Articles

Application of Structural Equation Modelling to Cybersecurity Risk Analysis in the Era of Industry 4.0

In the current digital transformation to Industry 4.0, the demands on the ability of countries to react responsibly and effectively to threats in the field of cyber security (CS) are increasing. Cyber safety is one of the pillars and concepts of Industry 4.0, as digitization brings convergence and integration of information technologies (IT) and operational technologies (OT), IT/OT systems, and data. Collecting and connecting a large amount of data in smart factories and cities poses risks, in a broader context for the entire state. The authors focus attention on the issue of CS, where, despite all digitization, the human factor plays a key role—an actor of risk as well as strengthening the sustainability and resilience of CS. It is obvious that in accordance with how the individuals (decision-makers) perceive the risk, thus they subsequently evaluate the situation and countermeasures. Perceiving cyber threats/risks in their complexity as a part of hybrid threats (HT) helps decision-makers prevent and manage them. Due to the growing trend of HT, the need for research focused on the perception of threats by individuals and companies is increasing. Moreover, the literature review points out a lack of methodology and evaluation strategy. This study presents the results of the research aimed at the mathematical modelling of risk perception of threats to the state and industry through the disruption of CS. The authors provide the developed factor model of cyber security (FMCS), i.e., the model of CS threat risk perception. When creating the FMCS, the researchers applied SEM (structural equation modelling) and confirmatory factor analysis to the data obtained by the implementation of the research tool (a questionnaire designed by the authors). The pillars and sub-pillars of CS defined within the questionnaire enable quantification in the perception of the level of risk of CS as well as differentiation and comparison between the analyzed groups of respondents (students of considered universities in SK and CZ). The convergent and discriminant validity of the research instrument is verified, and its reliability is confirmed (Cronbach’s alpha = 0.95047). The influence of the individual pillars is demonstrated as significant at the significance level of α = 5%. For the entire research set N = 964, the highest share of risk perception of CS threats is achieved by the DISRIT pillar (disruption or reduction of the resistance of IT infrastructure).

Predictive modeling for technology convergence: A patent data-driven approach through technology topic networks

Anticipating technology convergence is crucial for driving innovation and gaining a competitive advantage. Developing a method for forecasting the convergence of previously unrelated technology fields is necessary. Previous studies explored technology convergence using patents but focused on technology classes. However, these prior studies lacked clear insights because they relied on ambiguous technology classes. Therefore, this study seeks to define technology topics with precise technological meanings and develop model predictions using machine learning through technology topic networks to anticipate technology convergence potential. Specifically, it explores the use of text mining techniques to gain insights into technology topics, highlighting best practices and our research findings. This study constructs a network of technology topics derived from patent documents and maps their interactions using a topic network approach. Technology topic networks are constructed through dynamic topic modeling, and features extracted from these networks are used as input for training multiple classification models. By incorporating new link results and leveraging technological influence, the proposed approach can accurately anticipate technology convergence. The results of this research can have significant implications for firms seeking to gain a competitive advantage through innovation and technology convergence and contribute to the establishment of a next-generation R&D planning system.

Development and Performance Evaluation of a Smart Upper-Limb Rehabilitation Exercise Device.

User-friendly rehabilitation medical devices can enhance health and the quality of life through the convergence of information communication and medical technology. Muscle contraction enables bodily movement, and the assessment of muscle strength is crucial. Muscle contraction includes isometric, isotonic, and isokinetic types. Many individuals with physical disabilities rely on wheelchairs due to lower-limb paralysis. There is a substantial correlation between the level of upper-limb functional recovery and the quality of daily life. This study aimed to design and evaluate a device that utilizes various muscle contractions to enhance the effectiveness of upper-limb rehabilitation exercises. The results from the isometric performance assessment showed percentage error rates of >30% for 5-30 kg. Correction equations were employed, and the isometric performance assessment resulted in error rates below 2.1% for 5-30 kg. Isokinetic performance assessment using video analysis evaluated a consistent wire speed from 10 cm/s to 70 cm/s with an average error rate of 0.91% across all speeds. This study demonstrates the ability to accurately measure various muscle contractions and showcases the potential for real-time feedback. This highlights how such a device could be helpful for target groups, including older adults and individuals with disabilities, during upper-limb rehabilitation exercises.

Cyberbiosecurity Workforce Preparation

Cyberbiosecurity is an emerging field at the convergence of life sciences and the digital world. As technological advances improve operational processes and expose them to vulnerabilities in agriculture and life sciences, cyberbiosecurity has become increasingly important for addressing contemporary concerns. Unfortunately, at this time, educational opportunities for cyberbiosecurity workforce preparation are limited. Stakeholders’ perceptions may help guide cyberbiosecurity workforce preparation efforts and bridge the gap from the classroom to the field. Toward this end, we identified stakeholders in education, private industry, and state agencies in Virginia and sought their input through both an online survey and focus groups. Findings suggest limited awareness and understanding of cyberbiosecurity. Results indicate that both formal and non-formal learning components—including short modules and comprehensive standalone courses—are important for cyberbiosecurity education programming. Stakeholders tied potential success of education programming to systems thinking and collaborative designs. Moreover, results reveal insights into concerns at the convergence of information technology (IT) and operational technology (OT), which is central to effective workforce preparation for today’s agriculture and life sciences professionals. Continuous interdisciplinary collaboration and academia-industry partnerships will be critical for developing robust cyberbiosecurity education and securing the future of agriculture.

Digitalization of Family Planning Services: A Reality or Fantasy?

This position paper examines the changing environment of digitalizing family planning services, investigating how established healthcare paradigms might be transformed via the incorporation of new technology. The increasing use of digital technologies in the healthcare sector has brought attention to the provision of family planning services, leading to an examination of the practicality and achievability of this technological advancement. The study explores several aspects of this discussion, such as the present condition of family planning services, technical advancements, obstacles to digitalization, user viewpoints, and policy deliberations. The story begins by analysing the wider digitalization patterns in healthcare, setting the stage for the convergence of technology and reproductive health. The study critically examines the significance of digital technologies in family planning, including both the potential advantages and difficulties they may provide. It tackles the obstacles related to privacy, access, and cultural factors, in contrast to the optimistic potential of developing technology. The article showcases case studies and success stories that demonstrate the effectiveness of digital family planning, offering significant insights for future implementation. The report finishes by endorsing a series of policy proposals designed to navigate the complex interaction between technology, ethics, and healthcare infrastructure. These proposals prioritise the need of explicit rules, purposeful investments in digital literacy and accessibility, and smooth integration into current healthcare systems. This study examines the digitization of family planning services, highlighting its role as both a technical innovation and a potential driver of social change. It emphasises the importance of individual empowerment and well-being in discussions about reproductive health.

Digital Life Norway (DLN) Initiative to foster and boost transdisciplinary biotechnology research and innovation

Digital Life Norway (DLN) Initiative to foster and boost transdisciplinary biotechnology research and innovation Meeting the rapid developments in biotechnology by fostering transdisciplinarity, including digitalisation and big data, to create convergence for innovation in a virtual centre. The Centre for Digital Life Norway (DLN) is a strategic national initiative originally conceived in 2014 by the BIOTEK2021 programme of the Research Council of Norway (RCN). It is an ambitious and large-scale initiative to foster and boost transdisciplinary biotechnology research and innovation activities, combined with a novel framework of responsible research and innovation, to solve challenges of societal importance and create value. DLN departs from the traditional organisation of research and development among Norwegian research institutions. The centre aims to untangle and resolve some of the fundamental societal challenges facing new and emerging biotechnology by emphasising technological convergence and transdisciplinarity.

The Convergence of Islamic Law and Technology in The Enforcement of Citizen's Constitutional Rights in The Era Society 5.0

Globalization spreading across life spheres, especially in the fields of science and technology, also affects the digitalization of law through media convergence. This digitalization of the law is not exempt from the interference of Internet users in the form of criticism, dissemination of cases or social and legal issues, as well as advice to governments or the legal system through social media platforms used by the public, either in a national or international scope. The influence of people’s opinions on the Internet through social media has been remarkable in recent times on the law enforcement ruling of a case. In few cases, the decision was made due to the pressure of internet citizens on social media. The purpose of this study is to describe the convergence of Islamic law and technology in enforcing the constitutional rights of citizens in the era of Society 5.0 as an effort to create democracy and enforcement of the law that is fair and transparent through independence and freedom to express opinions, as well as the right to share and receive information by citizens of the Internet in electronic media, social media, in particular. This research is qualitative with methods of Law approach, conceptual approach, and case approach. The source of legal material used is secondary legal material, which is subsequently analyzed by deductive methods. The result of this study is that when society cannot be regulated primarily related to the use of social media, then the law can act as a law as a tool of social engineering.
 Keywords: convergence, Islamic law, constitutional rights, era Society 5.0

Editorial: Enabling technologies and business models for energy communities

This Research Topic on “Enabling Technologies and Business Models for Energy Communities” presents a comprehensive exploration of critical facets in the realm of sustainable energy transitions. The Research Topic encompasses diverse topics, ranging from smart energy frameworks for urban communities and off-grid renewable energy deployment in Mexico to the impact of institutional support on the coalbed methane industry. It further investigates complex grid investment decisions, solar-based irrigation adoption in water-scarce regions, and risk management in power supply projects. Additionally, the Research Topic delves into financial aspects, exploring the pricing of Public-Private Partnership (PPP) project Asset-backed Securities (ABS) products, the impact of managerial competence on corporate carbon performance, and equity-based predictions for the energy industry. The influence of innovation on fossil fuel abandonment in low and middle-income countries and the significance of climate risk for green innovation in heavy-polluting industries are also examined. A regional perspective is provided on the technological convergence of hydrogen energy, and the interplay between renewable energy, Gross Domestic Product (GDP), and CO2 emissions in highly-globalized countries is scrutinized. Lastly, the effects of green credit policy on the risk of stocks prices crash are investigated. Together, these contributions offer a holistic understanding of the challenges and opportunities in enabling technologies and business models for energy communities, contributing valuable insights for researchers, policymakers, and industry stakeholders striving for a sustainable energy future.

MODELING THE RELATIONSHIP OF STRUCTURAL SHIFTS IN INDUSTRY AND THE IMPACT OF EXPORTS OF HIGH-TECH PRODUCTS ON THE DOMESTIC MARKETS OF THE UNITED STATES AND CHINA

The relevance of identifying the relationship between structural shifts in industry and the impact of exports of high-tech products on the price and cost parameters of the domestic markets of the leading countries of the modern world economy is caused by the need for a comprehensive study of uncertainty and imbalance under the influence of structural-cyclical factors of market development. The development of relevant models that contribute to the identification and empirical justification of the desired relationship from the standpoint of partial equilibrium in the external and internal markets of the United States and China has both theoretical and applied significance in the context of the reindustrial turn based on convergent technologies. The purpose of modeling is to establish and substantiate the possible relationship between structural shifts in the industry and the impact of exports of high-tech products on the domestic markets of the United States and China. On the basis of previous experience, a complex econometric model has been developed, including computational-mathematical and regression-functional tools that allow analyzing dependent and factor variables within two successive cyclical waves of the current century. The interrelations of structural shifts in industry and the impact of exports of high-tech products on the domestic markets of the leading countries of the world industrial and technological rivalry – the USA and China – have been identified and substantiated. The modeling performed allows not only to identify comparative advantages at the country, national-economic level in terms of the impact of convergent technologies on the structure of production and exports in various cyclical variations, but also reflects the utility function for consumers of high-tech products in the domestic market of the United States and China. The dependences revealed as a result of modeling not only empirically, but also conceptually link the competition between manufacturers of high-tech products of each of the countries, alternately correlated as an exporting country and a global exporting country of the corresponding commodity groups. This creates a unique opportunity to show the multi-level relationship in the system "structural shifts - exports - domestic market" by comparing the dependent and factor variables of econometric and regression calculations. The results obtained correspond to the current practice in the world economy, revealing the desired relationships more consistently than when analyzing the competition of specific companies operating in the oligopolistic markets of the compared exporting countries.

Apropos Technophany

This article aims to reconstruct Simondon’s concept of technophany, which disperses throughout different writings that appeared posthumously and suggest how elaborating this concept could be understood as a significant philosophical task today. Technophany, namely the manifestation of technicity, is central to Simondon’s thought on techno-aesthetics and, more importantly, his intellectual project of reintegrating technology into culture. However, when we place Simondon’s concept of technophany in today’s context, namely the convergence of technology, art and design since the second half of the 20th century, we see that technophanies are becoming more or less ordinary marketing phenomena of the tech industry. Then, could the concept of technophany still take up this task of reconciling technology and culture? Or, instead, is it reduced to a mere economic category, and Simondon’s techno-aesthetics is only a forerunner of today’s industrial marketing strategies? In order to respond to these questions, this article returns to the source of Simondon’s concept of technicity. It shows that there is an intimacy between technophany and Mircea Eliade’s concept of hierophany, and indeed, Simondon’s genesis of technicity vividly mirrors Eliade’s analysis of sacrality and its crisis in modern times. The concept of technophany acquires a new meaning, and it refuses to be a mere phenomenon of publicity as one might easily misread it. Technophany has the task of occupying the “no man’s land” between technicity and sacrality. However, what exactly does it mean? Through the reconstruction of the concept of technophany in Simondon’s thought, this article hopes to examine the limit of the concept and, at the same time, reconceptualise and prolong it.

Design control and management of intelligent and autonomous nanorobots with artificial intelligence for Prevention and monitoring of blood related diseases

The effective management of human bloodstream remains to be the prime focus for the clinicians over years and it impose greater challenges when it comes to real-time solution. In particular managing hypoxemia and detection of blood clots is most pertinent. One major challenge faced is the existence of limited training data generated from real-world scenarios. On the other hand, creating an efficient model is often time consuming and expensive. This paper focusses on effective convergence of artificial intelligence and nanorobotics technologies to design and implement autonomous intelligent nanorobots to deal with blood related diseases. The major contribution of the research is two-fold, first we define an efficient architecture of the nanorobotics system with appropriate design parameter. Next, we develop a novel semi-supervised learning model using stochastic gradient descent method and kernel space that efficiently control and manage the nanorobots and helps in earlier prognosis and treatment of blood related diseases. The proposed model is novel and efficient as it enables working at nanoscale, providing resourceful understanding on physical and chemical properties associated with human body. The use of artificial intelligence techniques further makes the system to work more intelligently and independently. COSMOL with integrated MATLAB environment is used for experimental setup and simulation. MNIST dataset is compared with online RP tree method and other conventional batch related techniques. The performance analysis is compared based on performance, error rates and risk related factors. The proposed approach provides significant improvement in terms of performance with minimal error rate and improved accuracy measures.

Research on Sentiment Analysis of Tourism Review in The West Lake Scenic Area

With the advent of the digital tourism era, the convergence of information technology and tourism resources has become pervasive, with tourists relying on Internet-based tools as an essential part of their travel experience. In this study, we select the tourism reviews of The West Lake Natural Scenic Area as our research sample and conduct an in-depth analysis of its current situation through the sentiment analysis. A total of 3,376 data points related to reviews on Hangzhou’s West Lake Scenic Area was extractedtrip website using the “Octopus” web crawler software. After preprocessing, this study employed word frequency analysis, generation of word clouds, and other data visualization charts to analyze ROST EA and micro. Additionally, the LDA thematic clustering algorithm and SnowNLP sentiment analysis were utilized. The findings revealed that overall, tourists predominantly expressed positive emotions towards The West Lake Scenic Area compared to negative emotions. Positive sentiments primarily stemmed from factors such as the natural beauty of The West Lake, management practices, service quality, and charges. Furthermore, different tourists exhibited varying emotional tendencies.

Decentralizing spatial data: the convergence of Geographic Information Systems and Web 3.0 technologies


 
 
 Geographic Information Systems (GIS) have long served as pivotal tools for map- ping and understanding spatial relationships. However, the dawn of Web 3.0 technologies has catalyzed a transformative shift in the geospatial domain. This research meticulously investigates this transformation, focusing on the integration of decentralized spatial data storage, blockchain, Artificial Intelligence (AI), and Machine Learning (ML) with traditional GIS frameworks. Decentralized systems, un- derpinned by the principles of Web 3.0, present a promising alternative to centralized data storage, addressing challenges related to scalability, data sovereignty, and system vulnerabilities. Blockchain technology, traditionally associated with financial transactions, emerges as a cornerstone in this new GIS paradigm, ensuring unparalleled data integrity, transparency, and security. Its decentralized ledger system, combined with consensus mechanisms, offers a robust and transparent framework for managing diverse spatial data- sets, ranging from land registries to intricate environmental monitoring systems. The incorporation of AI and ML technologies further augments the capabilities of GIS. Beyond mere visualization, GIS, when powered by AI and ML, can process vast datasets, discern complex patterns, and even predict future spatial trends with remarkable accuracy. This research emphasizes the role of real-time and dynamic queries, highlighting the transition from static GIS analyses to more adaptive and predictive geospatial evaluations. While the potential advantages of this technological convergence are substantial, the research also sheds light on inherent challenges, espe- cially those related to the management of high-volume real-time data and ensuring data consistency across diverse sources. Building upon foundational works in the field, this study offers a holistic and comprehensive perspective on the synergistic potential of Web 3.0 technologies, AI, ML, and blockchain within GIS. It not only extends the findings of prior research but also paves the way for future explorations, setting the stage for innovative advancements in geospatial analysis.
 
 

An Approach to Construct Technological Convergence Networks Across Different IPC Hierarchies and Identify Key Technology Fields

The technological convergence network (TCN) is an effective method to identify the advancement of technology convergence. However, the previous TCN investigations are limited to a single level of International Patent Classification (IPC) rather than different IPC hierarchies, which can only provide decision support for policy makers with one dimension instead of various ones. In this article, we propose a new approach to construct TCNs across different IPC hierarchies based on technology coclassification analysis, and further identify key technology fields by employing the indicator of betweenness centrality in the TCNs from any IPC hierarchy. This article makes two important contributions. First, theoretically, our article is to contribute to understanding the advancement of technological convergence from various IPC hierarchies, rather than a single IPC level. Second, methodologically, the new approach we propose can benefit decision makers serving at various levels of technology management agencies. We conclude possible implications and future directions.

The challenges and opportunities of offering and integrating training in clinical molecular genetics and clinical cytogenetics: A survey of LGG Fellowship Program Directors

PurposeThe specialty of Laboratory Genetics and Genomics (LGG) was created in 2017 in an effort to reflect the increasing convergence in technologies and approaches between clinical molecular genetics and clinical cytogenetics. However, there has not yet been any formal evaluation of the merging of these disciplines and the challenges faced by Program Directors (PDs) tasked with ensuring the successful training of laboratory geneticists under the new model. MethodsAn electronic multi-question Qualtrics survey was created and was sent to the PD for each of the Accreditation Council for Graduate Medical Education–accredited LGG fellowship programs at the time. The data were collected, and the responses were aggregated for each question. ResultsAll of the responding PDs had started training at least 1 LGG fellow. PDs noted challenges with funding, staff shortages, molecular/cytogenetics content integration, limited total training time, increased remote work, increased sendout testing, and a lack of prior cytogenetics knowledge among incoming fellows. ConclusionThis survey attempted to assess the challenges that LGG PDs have been facing in offering and integrating clinical molecular genetics and clinical cytogenetics fellowship training. Common challenges between programs were noted, and a set of 6 concluding comments are provided to facilitate future discussion.

Drivers and Barriers of National Innovation Ecosystems for Implementing Sustainable Development Goals: A Latvian Case Study

Research examining the drivers and barriers of implementing sustainable development goals (SDGs) in national innovation ecosystems (NIEs) is scarce. This study proposes a framework of drivers and barriers to NIEs for SDGs implementation used in the Latvian context. An exploratory qualitative approach based on the Latvian case study is used to generate in-depth information on the drivers and barriers of NIEs for implementing SDGs. Our results show that at the NIE level, drivers for actors and institutions, such as legislative compliance, eco-innovations, cross-sector cooperation, and talent pools, are hindered by some barriers, such as lack of networking skills, institutional voids, totalitarian power, and academic rigidity. Despite attempts at technological convergence that facilitated distance learning, remote work, and telehealth solutions during the pandemic, the lack of collaborative platforms hinders the development of artifacts. Sustainable innovation is hindered by a lack of resources and openness that also blocks open innovation. Beyond coevolution and co-specialization initiatives, friction between the public and private sectors hinders complementary and substitute relations. Our results provide a systemic and holistic NIE tool to analyze the drivers and barriers of the SDGs.

Identifying promising technologies considering technology convergence: A patent-based machine learning approach

Identifying promising technologies considering technology convergence: A patent-based machine learning approach

Link Prediction Revisited: New Approach for Anticipating New Innovation Chances Using Technology Convergence

Link prediction has been actively used to anticipate future technology convergence. However, previous related studies have focused on anticipating within the current network only and fail to predict convergence with possible innovation chances. Hence, a new method is suggested herein for anticipating new innovation chances, where a method for adding innovation signals to the current network is suggested, and link prediction is conducted to the revised network. This article comprises three sections: current network construction, innovation signal detection, and link prediction to the revised network. The suggested framework is applied to mobile financial services as an illustrative example. This article is expected to serve as a systematic method for investigating innovation chances and anticipating possible associations within innovation networks.

Sources of Disruptive Technologies: Progressive Convergence of Artificial Intelligence and Quantum Technologies for Next Revolution

Sources of Disruptive Technologies: Progressive Convergence of Artificial Intelligence and Quantum Technologies for Next Revolution

AI Governance in Neom City: Exploring Legal Personality for Smart Robots and a Framework for Ethical Innovation

Neom City, a burgeoning smart city in Saudi Arabia, exemplifies the convergence of cutting-edge technology and unique cultural contexts. As AI-powered smart robots permeate service sectors, novel legal and ethical challenges emerge. This paper delves into these challenges, analyzing the intersection of AI with Islamic legal principles and exploring the concept of advanced legal personality for smart robots. Drawing upon comparative legal frameworks and governance models, the study proposes a framework for responsible AI innovation in Neom, balancing technological progress with ethical considerations and societal values.