Search Results (105)

Technology roadmapping is conducted by systematic mapping of technological evolution through patent analytics to inform innovation strategies. This study proposes an integrated framework combining hierarchical Latent Dirichlet Allocation (LDA) modeling with multiphase technology lifecycle theory, analyzing 113,449 Derwent patent abstracts (2008–2022) across three dimensions: technological novelty, functional applications, and competitive advantages. By segmenting innovation stages via logistic growth curve modeling and optimizing topic extraction through perplexity validation, we constructed dynamic technology roadmaps to decode latent evolutionary patterns in AI-powered programmable manipulators (B25J classification) within an innovation trajectory. Key findings revealed: (1) a progressive transition from electromechanical actuation to sensor-integrated architectures, evidenced by 58% compound annual growth in embedded sensing patents; (2) application expansion from industrial automation (72% early stage patents) to precision medical operations, with surgical robotics growing 34% annually since 2018; and (3) continuous advancements in adaptive control algorithms, showing 2.7× growth in reinforcement learning implementations. The methodology integrates quantitative topic modeling (via pyLDAvis visualization and cosine similarity analysis) with qualitative lifecycle theory, addressing the limitations of conventional technology analysis methods by reconciling semantic granularity with temporal dynamics. The results identify core innovation trajectories—precision control, intelligent detection, and medical robotics—while highlighting emerging opportunities in autonomous navigation and human–robot collaboration. This framework provides empirically grounded strategic intelligence for R&D prioritization, cross-industry investment, and policy formulation in Industry 4.0. Full article

Whether and how digital transformation affects innovation in small and medium-sized enterprises (SMEs) remains to be examined. This study aims to answer this question using a sample of SMEs listed on the Chinese National Equities Exchange and Quotations (NEEQ) market from 2012 to 2023. Employing textual mining techniques, this paper measures the degree of digital transformation through keyword frequency analysis of annual reports, while innovation is measured by the number of patent grants. Panel fixed effects models show that digital transformation significantly enhances corporate innovation in SMEs. This relationship remains robust after comprehensive endogeneity and additional robustness tests. Mechanisms analysis reveals that digital transformation alleviates financial constraints and enhances supply chain diversity, enabling SMEs to allocate more resources toward innovation activities. Heterogeneity analysis reveals that the positive effect of digital transformation on innovation is more pronounced for firms located in cities with higher digital finance coverage, in midwestern regions, and in industries with lower digitalization levels. These findings shed light on the power of digital technology, highlighting how its adoption can significantly bolster the innovation capacity of SMEs and drive their growth in a rapidly evolving digital economy. Full article

The tequila industry generates significant quantities of vinasse, a highly polluting byproduct that poses serious environmental challenges. Addressing this issue requires innovative solutions that align with the principles of bioeconomy, transforming waste into valuable resources. This article provides a comprehensive review of 688 scientific articles and 315 patent documents related to vinasse valorization technologies, retrieved from the Scopus and Espacenet databases. The review identifies key types of vinasse valorization, including bioethanol, biofertilizers, biogas, animal feed, biodiesel, and phenolic compounds, and evaluates trends, technical advances, and commercialization pathways. The findings highlight the feasibility of integrating these technologies within the tequila production process, promoting environmental sustainability and economic efficiency, and mention the current limitations of vinasse-based innovations. This study aims to guide researchers, industry stakeholders, and policymakers in developing strategies to harness the full potential of vinasse, contributing to a more sustainable and circular economy. Full article

This study employs text mining techniques to conduct a systematic quantitative analysis of cybersecurity-related scientific publications and technological research. It aims to break through the limitations of traditional unidirectional evolutionary research, reveal the knowledge evolution rules between scientific theories and technical practices in this field, and provide valuable references and decision-making support for optimizing the collaborative innovation ecosystem. Firstly, we took academic papers and patent research on cybersecurity from 2005 to 2024 as the research objects and divided them into ten stages according to the time series. Subsequently, we identified scientific and technological topics and formed science–technology topics to assess their similarity. Then, we selected 3040 pairs of collaborative topic pairs and categorized them into three distinct groups: weak, moderate, and strong correlation. Finally, we constructed a science–technology topic association evolution atlas and analyzed the types of evolutionary pathways of topic associations and their mechanisms of action accordingly. The results demonstrate five evolutionary patterns in science–technology topic associations: division, merging, inheritance, co-occurrence, and independent development. Additionally, the science–technology topics demonstrate a high degree of collaboration, exhibiting a collaborative effect of “initial accumulation–fluctuating differentiation–deep collaboration”. Meanwhile, the correlation evolution of strongly related science–technology topics presents a symmetrical effect of “technology–science–technology” and “science–technology/technology–science”. Full article

As the flow of innovation elements breaks through geographical boundaries, patent transfer and the resulting spatial knowledge spillovers have become a crucial pathway for cities to enhance their competitive advantages and foster collaborative innovation. This study crawls technology transfer data through Big Data mining and uses social network analysis to construct an intercity technology transfer network among 286 Chinese cities at the prefecture-level and above between 2000 and 2020. The study explores the influence of technology transfer networks and their spatial spillovers on urban innovation capacity. The results are as follows: (1) Moran’s I results indicate that technology transfer and innovation activities among Chinese cities exhibit significant spatial dependence. (2) The Markov chain analysis reveals that the technology transfer networks among Chinese cities exhibit significant spatial spillovers. (3) Spatial econometric analysis and effect decomposition demonstrate that technology transfer networks exhibit significant spatial dependence and spillover effects. Through the induced spatial knowledge spillovers, technology transfer networks contribute to enhancing the innovation capabilities of neighboring cities. Full article

Dealing with solid waste has always been a global concern, and construction waste is one of the most important parts. Addressing how to properly dispose of construction waste, reduce its negative environmental impact, and achieve effective resource recycling has emerged as an urgent problem to be solved. Technological innovation underpins efficient waste reduction, reuse, and recycling, but existing research often overlooks systematic and quantitative measurements of innovation initiatives. This study uncovers the development status and trends of construction waste recycling (CWR) technology, identifies key points and potential innovation directions for technological development, and also explores practical strategies to promote technological innovation and industrial growth. Through patent analysis, this study uncovers the current status of technological innovation within China’s CWR industry. A text mining approach is employed to analyze patent texts related to core technologies, explore topic contents, and identify topic intensities and evolution trends. A comparative analysis between China and the global dominant countries in CWR reveals China’s technological strengths and weaknesses. The results indicate that patent applications in China’s CWR industry are substantial, with a rapid growth rate, while its global competitiveness remains weak. The applicants are widely distributed, with traditional enterprises demonstrating strong innovation capabilities, while emerging and small-to-medium enterprises lack vitality. The industry has potential advantages in developing resource recycling devices and construction wastewater treatment technology, but the technological foundation in some other core technologies is weak. This study offers an overview of technological innovation initiatives in the CWR industry, representing a breakthrough in existing research. The findings will assist policymakers in formulating evidence-driven strategies to promote CWR. Full article

The floating liquefied natural gas (FLNG) system is an offshore facility that floats above a natural gas field, directly liquefying natural gas without the need for subsea pipelines. In recent years, there has been growing interest in exploring technological innovations for FLNG systems. As such, advancements could lead to breakthroughs in optimizing layout and operations within the limited space of these platforms. To address this, we first apply a patent mining method to cluster FLNG-related patent texts, identifying the key technological components. We then conduct a morphological analysis to pinpoint potential technological opportunities. In our case study, we identify seven such opportunities, which include a combination of plate-fin heat exchangers, horizontal LNG storage tanks, flexible flowlines, and tail loading methods. These findings offer valuable insights and directions for the future development of FLNG systems. Full article

Although safety technology has recently been shown to prevent occupational incidents, a systematic approach to identifying technological opportunities is still lacking. Incident report documents, containing large volumes of narrative text, are considered valuable resources for predetermining incident factors. Additionally, patent data, as a form of big data from technological sources, is widely utilized to explore potential technology solutions. In this context, this study aims to identify technology opportunities by integrating two types of textual big data: incident documents and patent documents. Text mining and self-organizingmaps are employed to discover applicable technologies for incident prevention, grouping them into five categories, as follows: machine tool work, high-place work, vehicle-related facilities, hydraulic machines, and miscellaneous tools. A gap analysis between incidents and patents is also conducted to assess feasibility and develop a technology strategy. The findings, derived from both types of big data, provide technology solutions that are essential for improving workplace safety and that can be used by business owners and safety managers. Full article

In order to solve the problem of insufficient design applicability in the field of lower limb rehabilitation, such as interaction, experience comfort, and modeling color, a biological excitation function system was used to guide the solution of the functional scheme of lower limb rehabilitation products, and the transformation of lower limb rehabilitation products in functional interaction, experience, and morphological color design driven by biological information-driven cross-domain mapping was improved. We used patent knowledge mining to study the product functional requirements of lower limb rehabilitation products. The results were used to screen the required biological prototypes, and the biological incentives were used to guide the design problems. According to the principle of analogy and similarity calculation, the similarity matrix was obtained, and then the strategy was analyzed. Through the analogy of functional system–product technology engineering systems, the engineering relationship between multi-biological and multi-design elements was determined. We realized the biological replacement and upgrading of product functions under biological stimulation to guide the design of lower limb rehabilitation products. The accurate quantitative biological information of multi-biological analogy fit has the significance of optimizing the training effect, improving the operation efficiency, and improving the morphology and modeling of the lower limb rehabilitation product engineering transformation and design. The acquisition rate of the functional design requirements of lower limb rehabilitation products based on text mining reached 95%, and the accuracy of the biological design prototype obtained through similarity calculation was higher than 79%, which verified the feasibility of the accurate bioinformatics design method and improved the rigor of the bioinformatics biomimetic design method. Full article

Cave automatic virtual environment (CAVE) technology provides a highly immersive experience in virtual reality (VR) environments, transcending traditional boundaries of VR head-mounted devices. CAVE is applied to many fields, including education, construction, healthcare, and manufacturing. Despite its relevance, studies examining CAVE technology evolution and research directions are still lacking. To address this research gap, we analyzed patents using CAVE to understand the technology’s development and identify opportunities for future research, development, and innovation. Patent data were collected from the Lens database and analyzed using data mining techniques. An increasing number of CAVE patents were granted, reflecting significant growth and investments in this field. The results highlight emerging trends in the development of CAVE systems, emphasizing various technical configurations and innovative applications across a wide range of fields. Full article

This study aims to understand the impacts of climate change and extreme climate events on residential buildings and explore how existing buildings can be adapted to resist these negative impacts. A bibliometric and scientometric analysis was conducted on resilient residential retrofits to highlight the prevalent themes, critical directions, and gaps in the literature, which can inform future research directions. The resilient residential retrofit publications from 2012 to 2023 were retrieved and analyzed using text-mining software. In all, 4011 publications and 2623 patents were identified. The analysis revealed an average annual publication growth rate of 11%, indicating increasing interest in resilient residential retrofits. Four central topics were explored specifically throughout the study, as they are known to be the most prevalent climate risks for residential buildings: Overheating, Flooding, Wind, and Wildfires. The research trends analysis reveals that emerging interests in resilient residential retrofit encompass nature-based solutions, energy efficiency, thermal comfort, microclimates, durability, post-disaster recovery, and extreme events. Nearly half of the publications reference urban context and over one-third mention costs. The building envelope is the most frequently discussed housing component. Although energy retrofit was not the primary focus of this study and was not specifically searched for, energy concerns were still prevalent in the dataset, highlighting the critical importance of energy efficiency and management in resilient residential retrofits. The analysis of R&D momentum revealed several research gaps. Despite high growth rates, there are low publication rates on key topics such as durability, holistic approaches, microclimates, nature-based solutions, and traditional homes, to name a few. These areas could benefit from further research in the context of climate-resilient residential retrofits. Additionally, the analysis indicates a lack of publications on cross-themed research specific to rural and suburban settings. There are also few studies addressing combinations of themes, such as overheating in high-rise buildings, wildfires in Nordic climates, and flooding risk in smart homes within the scope of resilient residential retrofits. The United States leads in publication output, followed by China and the UK, with China dominating the patent landscape. This scientometric analysis provides a comprehensive overview of the research landscape in resilient residential retrofit, systematically maps and analyzes the vast amount of research output, and identifies the key trends and gaps, enabling us to see a type of quantitative snapshot of the research in a field at a certain point in time and thus providing a unique point of view. This study helps stakeholders prioritize efforts and resources effectively for guiding future research, funding decisions, informing policy decisions, and ultimately enhancing the resilience of residential buildings to climate-related challenges. Full article

Technology transfer represents a critical avenue for addressing the challenges associated with carbon emission reduction, warranting thorough investigation into the effects of both domestic and international technology transfer on carbon emissions. This study employs data mining techniques to extract comprehensive data on patent transfers across 334 prefecture-level cities in China from 2000 to 2021, analyzing the influence of technology transfer on carbon emissions from both domestic and international perspectives. The findings indicate that domestic technology transfer and international technology transfer significantly contribute to carbon emission reduction, with international technology transfer exerting a more substantial effect than its domestic counterpart. To mitigate endogeneity concerns, the study utilizes the shortest distance from each city to the telegraph lines established during the late Qing Dynasty as an instrumental variable and the resulting conclusions remain robust. Heterogeneity tests reveal significant regional disparities, particularly in areas located southeast and northwest of the Hu Huanyong line, as well as between regions inside and outside the five major urban agglomerations. The mechanisms underlying carbon reduction suggest that improvements in energy efficiency and upgrades in industrial structure serve as the primary pathways for carbon emission reductions resulting from both domestic and foreign technology transfers. These conclusions provide a theoretical foundation and empirical insights to facilitate the acceleration of technology flow within the context of high-quality development, particularly concerning environmental protection. Full article

Prefabricated construction (PC) plays a critical role in advancing the sustainable and high-quality transformation of the construction industry. Nevertheless, the fragmented and variable nature of technological innovations in PC complicates their acquisition, comprehension, and practical application, thereby hindering the process of innovation transformation. In response to these challenges, this study applies knowledge graph techniques to aggregate, correlate, and store knowledge pertaining to PC technological innovations. Specifically, using patent data from the past five years, and grounded in knowledge management and complex network theories, this study employs text mining, topic modeling, and association rule algorithms to perform clustering, evolutionary, and association analyses. The extracted entities and relationships obtained from the analyses are then stored in a Neo4j graph database for the construction and interactive visualization of a knowledge graph for PC technological innovation. According to the knowledge graph, a question-and-answer system framework is further proposed, providing practical application guidance. This research provides a comprehensive overview of the technological landscape, key nodes, and development trends in PC. It makes a meaningful contribution to knowledge management theory and complex network theory, advancing innovative applications in PC technology. Full article

Coal mine water hazards are one of the five major natural disasters in mines, and water in depleted areas is the most serious form of water hazard causing casualties. The exploration of depleted areas, especially old tunnels, presents significant challenges, and achieving the required borehole density for exploration in depleted areas is difficult in reality. The authors of this paper previously applied for a patent titled “Water Injection Exploration Method for Depleted Areas Based on Stress Seepage Principle”. In order to theoretically analyze the feasibility of the patented results and validate them in practice, we first analyze the stress distribution and seepage phenomena around the goaf theoretically, construct boreholes underground in Renlou Coal Mine, conducting on-site water injection tests for different zones (depleted areas, old tunnels, and general boreholes), and perform transient electromagnetic observations during the water injection tests. A total of 355 sets of water injection flow rate and pressure data were obtained from different zones in three different boreholes; permeability coefficients were calculated based on the measured data, and relevant diagrams were drawn. Through the analysis of water injection test data and theoretical analysis, the following conclusions were drawn: there are disturbances and stress reduction zones around depleted areas (old tunnels), and when the equivalent normal stress induced by water injection pressure is greater than zero, the permeability of fractures will increase significantly. Whether it is a borehole aimed at depleted areas or old tunnels, it shows the characteristic that the closer the distance to the depleted areas (old tunnels) is, the smaller the water injection pressure, and the larger the permeability coefficient. When water is injected into the disturbance and stress reduction zones of the depleted areas (old tunnels), the water injection pressure can decrease from 9–10 MPa to 3–4 MPa, and the permeability coefficient may even increase in quantity value. The phenomena of pressure reduction and increased permeability during water injection are significantly observable, indicating that the water injection exploration method for depleted areas based on the stress seepage principle is feasible and has practical significance. Full article

In the dynamic field of robotics engineering, nanorobot technology has witnessed rapid advancements. Developing a technology roadmap is essential for quickly identifying the trends and key technological aspects of nanorobotics from an array of multi-source data. Traditional research methods, such as Delphi surveys, bibliometrics, patent analysis, and patent paper citation analyses, often fail to capture the rich semantic information available. Moreover, these approaches generally provide a unidimensional perspective, which restricts their capacity to depict the complex nature of technological evolution. To overcome these shortcomings, this paper introduces a novel framework that utilizes the ALBERT method combined with multi-source data for critical theme extraction. It integrates varied data sources, including academic papers and patents, to explore the interrelation within the nanorobot technology roadmap. The methodology begins with text feature extraction, clustering algorithms, and theme mining to identify dominant technological themes. Subsequently, it applies semantic similarity measures to connect multiple themes, employing a “multi-layer ThemeRiver map” for a visual representation of these inter-layer connections. The paper concludes with a comprehensive analysis from both the technological research and industrial application perspectives, underscoring the principal developmental themes and insights of nanorobot technology, and projecting its future directions. Full article