Application Of Innovative Technologies Research Articles

Innovative Application of Optoelectronic Control Engineering for Safety Assurance of Surgical Robots

As an emerging technology, optoelectronic control engineering has demonstrated a wide range of application potential in surgical robot safety and security. Through a literature review, this paper provides an in-depth discussion on the innovative applications of optoelectronics technology in enhancing the positioning accuracy, environment sensing, supple control and remote operation of surgical robots. At the same time, this paper summarizes the current research hotspots and future research directions, with a view to providing a reference for promoting the technological progress in this field. The current research focuses on improving the operating precision of surgical robots, enhancing the environment sensing ability and the application of force feedback system, while the future research will mainly focus on interdisciplinary cooperation and new technology development.

Exploring the Practical Teaching Mode of Language Laboratory based on Artificial Intelligence

With the rapid development of artificial intelligence (AI) technology, its application in the field of education is becoming more and more extensive, especially in the teaching mode of language laboratory, AI technology shows great potential and innovation space. The purpose of this paper is to explore the practical teaching mode of language lab based on artificial intelligence, and to reveal its advantages and challenges in language learning by analysing the current status of the application of AI technology in teaching. This study aims to explore the in-depth analysis of the research on the practical teaching mode of language labs based on artificial intelligence. Firstly, it introduces the problems of language labs and analyses the limitations and problems of traditional labs. Secondly, the language laboratory solution measures are elaborated in detail to construct the practical teaching mode of language laboratory based on artificial intelligence. Then, the practical teaching mode of language laboratory based on artificial intelligence is explored. Finally, the application value of the language laboratory of artificial intelligence in the aspects of linguistic research and teaching practicability is discussed. As an innovative application of educational technology, the language laboratory of artificial intelligence has a positive role in promoting the transformation of the modern language teaching mode, and provides new perspectives and methods for foreign language teaching. This paper focuses on the design and construction of the practical language teaching mode of artificial intelligence. With the rapid development of artificial intelligence technology, its application in the field of education has become increasingly widespread. In language teaching, the construction of an AI-based practical teaching model can help to improve teaching efficiency and quality and stimulate students’ interest in learning. This paper elaborates the design principles, construction elements, implementation process and effect evaluation of this teaching mode from various aspects.

Knowledge, attitudes, and practices of endoscopy among gastroenterologists in diagnosis and management of inflammatory bowel disease in China: a multicenter cross-sectional study

BackgroundThe aim was to assess the knowledge, attitudes, and practices (KAPs) of endoscopy among gastroenterologists in the diagnosis and management of IBD in China.MethodsA multicenter cross-sectional KAP study was performed. The questionnaire was developed and improved using feedback and opinions from a team of experienced IBD specialist professors and then distributed and collected online. In addition, eight fellow gastroenterologists participated in an IBD endoscopy training program were asked to review endoscopic images, and the consistency of the endoscopic scores before and after training was calculated.ResultsA total of 193 participants from 12 provincial-level administrative regions encompassing both the Northern and Southern parts of China completed the study questionnaire. The median age of the participants was 40 (36, 45) years, with the majority being female (70.5%). The median professional experience as gastroenterologists was 11 (7, 17) years, while the median experience as endoscopists was 8 (3, 15) years. The median knowledge score was 8 out of 10 points for single-choice questions; however, most gastroenterologists believed that some concepts in these endoscopic indices were vague, including those regarding deep ulcerations, ulcerated surfaces, affected surfaces and narrowing in open-answer questions. The UCEIS and SES-CD were considered most consistent with clinical activity score in the evaluation of UC and CD, respectively. IBD subspecialists and gastroenterologists who had previously received IBD endoscopy screening training were more likely to use endoscopic indices (p<0.001, p = 0.029, respectively). The Rutgeerts score demonstrated the most significant improvement in consistency before and after training, from 0.407 (95% CI: 0.025–0.999) to 0.909 (95% CI: 0.530–1.000).ConclusionsWe propose the elucidation of ambiguous definitions in endoscopic indices, enhancement of training, and the application of innovative technology to enhance the application of endoscopic evaluation and endoscopic indices in clinical practice.

Strategic development of the innovative potential of industrial enterprises

The purpose of the article is to evaluate theoretical approaches to the study of various scientific and practical approaches of sustainable economic development. The author of the work has the following tasks: to conduct a comparative assessment of various scientists and economists studying theoretical approaches of sustainable strategic development of innovative potential of industrial enterprises; to identify the main directions of the theoretical approaches to its research of both Russian and foreign scientists; to determine the vectors of the strategic development of the innovative potential of companies in the industrial sector; to analyse and classify the methods that scientists use to study the essence and typology of the innovative potential of industrial enterprises within the economic system. Finally, the theoretical approaches to the study of the sustainable development of the innovative potential of enterprises of the regional industrial complex have been evaluated and used, the research results are formulated. The methods and techniques of application of various innovative technologies, ways, etc. are considered and evaluated. At the present stage of sustainable economic development this is of great importance. The results of the conducted research can be applied while formulating directions for the industrial and spatial development of the country’s economic sectors as well as for the strategic development of the innovative potential of industrial enterprises.

Shale Mechanics in Deep Drilling: Enhancing Stability and Efficiency Through AI and Hydraulic Fracturing

Shale mechanics is a critical field in the drilling process, especially during deep drilling and the development of unconventional resources, where shale formations present various challenges. Given the diverse and multi-scale nature of shale, mechanical characteristics such as brittleness, fracture toughness, and stress behavior must be effectively controlled to ensure wellbore stability, optimize fracture treatments, and enhance drilling efficiency. Key areas of interest in this review include wellbore stability, hydraulic fracturing methods, and the application of innovative technologies, such as artificial intelligence (AI) and machine learning (ML). The current literature was extensively reviewed, with an emphasis on major papers addressing various aspects of shale mechanics. The appropriate selection of fluid and mud weight has been identified as critical for maintaining wellbore stability. Despite advances in hydraulic fracturing technology that have improved production efficiency, environmental concerns - particularly regarding water usage and chemical management - remain significant. Furthermore, the integration of AI and ML has enhanced production forecasts and resource estimation, though challenges related to data quality and availability persist. A review of the current state of knowledge in shale mechanics indicates that further progress will require improved geomechanical models, advanced monitoring tools, and environmentally sustainable strategies.

Sustainability in Global Agri-Food Supply Chains: Insights from a Comprehensive Literature Review and the ABCDE Framework.

The sustainability of global agricultural produce supply chains is crucial for ensuring global food security, fostering environmental protection, and advancing socio-economic development. This study integrates bibliometric analysis, knowledge mapping, and the ABCDE framework to conduct a comprehensive qualitative and quantitative analysis of 742 relevant articles from the Web of Science core database spanning January 2009 to July 2023. Initially, bibliometric analysis and knowledge mapping reveal the annual progression of research on the sustainability of global agricultural produce supply chains, the collaborative networks among research institutions and authors, and the geographic distribution of research activities worldwide, successfully pinpointing the current research focal points. Subsequently, the ABCDE framework, constructed from the quantitative findings, helps us identify and comprehend the antecedents, barriers and challenges, impacts, and driving forces affecting the sustainability of these supply chains. The study identifies globalization and technological advancement as the primary forces shaping the sustainability of agricultural produce supply chains, despite them also posing challenges such as resource constraints and environmental pressures. Moreover, the application of innovative technologies, the optimization of organizational models, and active stakeholder engagement are key to propelling supply chains toward more sustainable development, exerting a profound impact on society, the environment, and the economy. In conclusion, this study suggests future research directions. The integrated methodology presented offers new perspectives and deep insights into the complexities of sustainable global agricultural produce supply chains, demonstrating its potential to foster knowledge innovation and practical applications, providing valuable insights for academic research and policy formulation in this domain.

Advances in High-Efficiency Blue OLED Materials

Organic light-emitting diode (OLED) technology has rapidly emerged in the display and lighting sectors due to its high contrast ratio, wide viewing angle, and sleek design. Beyond these attributes, OLEDs have also demonstrated crucial applications in medicine, fashion, sports, and more, leveraging their emissive properties and flexible design. As the cornerstone of full-color displays, blue OLEDs, whose performance directly impacts color rendition and saturation, have garnered significant attention from both scientific researchers and industrial practitioners. Despite the numerous advantages of OLED technology, blue OLEDs still confront formidable challenges in terms of luminous efficiency, durability, and material stability. This review examines the evolution of blue OLED materials over recent years, specifically focusing on three generations: fluorescent, phosphorescent, and thermally activated delayed fluorescence (TADF). Through molecular design, device structure optimization, and the application of innovative technologies, remarkable advancements have been achieved in enhancing the luminous efficiency, lifetime, and color purity of blue OLEDs. However, to advance commercialization, future efforts must not only ensure high efficiency and long lifetime but also improve material stability, environmental sustainability, and reduce development costs. Emerging materials such as thermally activated exciton materials and the application of hyperfluorescent (HF) OLED technology represent vital driving forces for the continuous advancement of blue OLED technology. It is anticipated that significant milestones will continue to be achieved in the development of highly efficient blue OLEDs in the future.

Comprehensive Investigation of the Thermal Performance of an Electrically Heated Double-Glazed Window: A Theoretical and Experimental Approach

The thermal performance of windows is an important area of research to reduce the energy consumption of buildings and improve indoor comfort. The application of innovative glazing technologies can improve the energy performance of windows and transparent facades, resulting in significant energy savings. This paper presents research results on the energy performance of electrically heated windows. A comprehensive CFD and experimental analysis of the heat transfer processes in a window space depending on the size, power, and location of an electric heater was performed. The convective gas flows in the gas gaps and in the boundary layer were also analysed, and it is shown that a window with an electric heater can reduce the energy consumption of a room by 10–12%. This study is a pilot study to assess the feasibility and cost-effectiveness of electric local heating of a window or facade to minimise heat loss before full-scale implementation. The results of numerical modelling and experimental studies confirm the potential of the new technologies.

Research of the nature of implementation of environmental innovations as a factor of ensuring competitiveness of hotel hospitality business

&lt;p class="MsoNormal" style="line-height: 120%; mso-pagination: widow-orphan; layout-grid-mode: char; mso-layout-grid-align: none; margin: 12.0pt 0cm 6.0pt 147.4pt;"&gt;&lt;span lang="EN-US" style="font-size: 10.0pt; line-height: 120%; mso-fareast-font-family: 'Times New Roman'; color: black; mso-themecolor: text1; mso-font-kerning: 0pt; mso-fareast-language: JA;"&gt;In many countries of the world, sustainable tourism is developing rapidly, and therefore the application of innovative environmental technologies is becoming an integral part of the development strategies of hospitality industry enterprises, especially hotel business. This trend promotes the introduction of new management systems based on the principles of sustainable development, including resource-saving technologies. In the work, the existing environmental management tools are analyzed and comparative studies of the essence of the application of &amp;ldquo;green&amp;rdquo; innovations are conducted using the example of the hotel business enterprises of the Republic of Azerbaijan and the Russian Federation.&lt;/span&gt;&lt;span lang="EN-US" style="font-size: 10.0pt; line-height: 120%; mso-fareast-font-family: 宋体; mso-fareast-theme-font: minor-fareast; color: black; mso-themecolor: text1; mso-font-kerning: 0pt;"&gt; &lt;/span&gt;&lt;span lang="EN-US" style="font-size: 10.0pt; line-height: 120%; mso-fareast-font-family: 'Times New Roman'; color: black; mso-themecolor: text1; mso-font-kerning: 0pt; mso-fareast-language: JA;"&gt;Studies have shown that the implementation of such innovations and eco-technologies in hotels demonstrates their commitment to environmental responsibility, improves the guest experience, helps save resources and acts as an additional advertising tool. Technological re-equipment and the use of modern materials aimed at reducing the burden on the environment ensure the economic efficiency of hotel business enterprises and increase their competitiveness.&lt;/span&gt;&lt;/p&gt;

Numerical investigation of welding deformation diminution for double shell structure using the layered inherent strain

Cyclotron is a key scientific tool and indispensable research platform for conducting cutting-edge research in nuclear equipment development as well as innovative applications of nuclear technology. The shell component has a double-layer thick-walled structure with intricate ribs and high-density, full-penetration welded joints. The mitigation of welding deformation is of profound significance to the performance of the cyclotron. The thick plate joint has many welding layers which will be divided into several steps to complete the backing, filler, and cap welding. The equivalent transverse and longitudinal plastic strains of different layers were extracted by the thermo-elastic-plastic method. The welding deformation generated by each layer of weld can be predicted by using the equivalent plastic strain, and the total distortion can be accumulated layer by layer. Numerical simulation and experimental studies were conducted on the welding deformation of the double shell specimen, and the welding sequence and design of the welding fixture were discussed in detail. The digital photogrammetry system was used to monitor the deformation state of the welded parts in real-time. The measured deformation was compared with the simulation results. Ultimately, the deformation of the specimen is controlled at 2.64 mm. The proposed method can flexibly evaluate the impact of each welding layer on welding deformation for multiple welds, which can provide technical guidance for cyclotron engineering manufacturing.

Research on the Influence of Firm Digital Intelligence Transformation and Management Innovation on Performance and Sustainable Development: Empirical Evidence from China

From the perspective of firm capability, this study explores the impact of digital intelligence transformation and management innovation on the performance and sustainable development of Chinese firms. On the basis of constructing an evaluation index system of firm digital intelligence transformation and management innovation, a comprehensive evaluation model of firm digital intelligence transformation and management innovation is constructed via the analytic network process (ANP) and fuzzy comprehensive evaluation method. Taking Chinese film and television firms as an example, this study selects 160 data samples from 85 firms and constructs a structural equation model to empirically analyze the impact of digital intelligence transformation and management innovation on the performance of firms. The study results show that, in the context of digitalization and intelligence, firm digital intelligence capability and dynamic capability have a significant positive effect on firm performance. Firm digital intelligence transformation and management innovation directly impact performance and can play a role through firm digital intelligence capability and dynamic capability as intermediaries, and the chain intermediary effect of digital intelligence capability and dynamic capability is significant. The research results show that firm digital intelligence and dynamic capabilities provide a functional path for firm digital intelligence transformation and management innovation to improve performance. Moreover, the innovative application of digital intelligence technology has an important impact on the sustainable development of firms. Digital transformation and management innovation can help firms enhance their ability to manage environmental uncertainties, improve firm performance and foster the achievement of sustainable development goals.

Innovative Applications of Intelligent Technology in Infant Care Products: A Study on the Design of Bottle Warmers and Milk Warmers

This paper delves into the innovative application of intelligent technology in the design of infant care products, with a particular focus on the design of smart bottle warmers and milk warmers, and their impact on user experience. The study begins by analyzing the current market demands and limitations of existing products in the field of infant care products, followed by a detailed discussion of the design features, technological advantages, and user experience of HAUTURE brand products. Through an in-depth analysis of the temperature control technology of the smart bottle warmer, the user interface design, and the dual-sealing system and vibration reduction and noise reduction technology of the milk warmer, this paper reveals how intelligent technology enhances product performance and user satisfaction. In addition, this paper examines the role of user feedback in product design improvement and proposes solutions to technical challenges. Finally, it provides an outlook on the future development trends of intelligent infant care products, predicting how intelligent technology will further shape innovation in this field.

QTL mapping of maize plant height based on a population of doubled haploid lines using UAV LiDAR high-throughput phenotyping data

Maize (Zea mays L.) is a globally significant crop that plays a crucial role in feeding the growing global population. Among its various traits, plant height is particularly important as it affects yield, lodging resistance, ecological adaptability, and other important factors. Traditional methods for measuring plant height often lack cost-efficiency and accuracy. In this study, we employed a light detection and ranging (LiDAR) sensor mounted on an unmanned aerial vehicle (UAV) to collect point cloud data from 270 doubled haploid (DH) lines. This innovative application of UAV-based LiDAR technology was explored for high-throughput phenotyping in maize breeding. We constructed high-density genetic maps and assessed plant height at both single-plant and row scales across multiple developmental stages and genetic backgrounds. Our findings revealed that for many varieties and small areas, single-plant-scale estimation accuracy was superior to row-scale estimation, with an R2 of 0.67 versus 0.56 and an RMSE of 0.12 m vs. 0.17 m, respectively. Two high-density genetic maps were constructed based on SNP markers. In Sanya and Xinxiang, the F1DH and F2DH populations identified 12 and 20 QTLs (quantitative trait loci) for plant height, respectively. The study successfully identified and validated QTLs associated with plant height, revealing novel genetic loci and candidate genes. This research highlights the potential of UAV-based remote sensing to advance precision agriculture by enabling efficient, large-scale phenotyping and gene discovery in maize breeding programs.

A digital twin system for centrifugal pump fault diagnosis driven by transfer learning based on graph convolutional neural networks

In industrial sectors such as shipping, chemical processing, and energy production, centrifugal pumps often experience failures due to harsh operational environments, making it challenging to accurately identify fault types. Traditional fault diagnosis methods, which heavily rely on existing fault datasets, suffer from limited generalization capabilities, especially when substantial labeled and specific fault sample data are lacking. This paper proposes a novel fault diagnosis approach for centrifugal pumps, utilizing a digital twin (DT) framework powered by a graph transfer learning model to address this issue. Firstly, a high-fidelity DT model is constructed to simulate the flow-induced vibration response of the impeller under different health states to enrich the type and scale of the dataset. Secondly, a graph convolutional neural networks (GCN) model is constructed to learn the knowledge of simulation data, and the Wasserstein distance between simulation data and measured data is optimized for adversarial domain adaptation, thereby achieving efficient cross-domain fault diagnosis. Experimental results demonstrate that the proposed algorithm delivers effective fault diagnosis with minimal prior knowledge and outperforms comparable models. Furthermore, the DT system developed using the proposed model enhances the operational reliability of centrifugal pumps, reduces maintenance costs, and presents an innovative application of DT technology in industrial fault diagnosis.

Enhancing estate governance through blockchain: An analysis of transparency, efficiency and security in estate management

This study investigates the impact of blockchain technology on estate governance focusing on enhancing transparency, efficiency and security within the sector. A structured questionnaire using a 5-point Likert scale was distributed to 317 estate management professionals to collect quantitative data which was subsequently analyzed using SmartPLS 4. The results underscore transformative potential of blockchain technology revealing strong correlations between its implementation and improved estate governance outcomes. This study demonstrates how blockchain can significantly enhance estate administration by addressing inefficiencies, bolstering security and fostering greater transparency. The proposed framework for integrating blockchain into estate governance offers a comprehensive strategy to manage frozen estates more effectively, reduce administrative delays and minimize disputes. The study's primary contribution lies in its innovative application of blockchain technology to solve prevalent issues in estate management providing a strategic blueprint for future implementations. This study offers actionable insights and practical recommendations for estate management stakeholders emphasizing the critical role of blockchain in ensuring more efficient, transparent and secured governance practices. This study highlights the profound impact blockchain can have on modernizing estate management practices and establishing robust governance frameworks by thoroughly examining the dimensions of transparency, efficiency, and security. This study concludes by advocating for the adoption of blockchain technology to enhance estate governance effectiveness and improve overall management outcomes.

Parametric Design Method of Buildings Based on Convolutional and Deep Neural Networks

The application of AI technology in architectural software has brought various innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them, and analyzes the application of these technologies in architectural image recognition, generation, design optimization and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design. The application of AI technology in architectural software has brought numerous innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them; it also analyzes the application of these technologies in architectural image recognition, generation, design optimization, and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design.

Application of Innovative Digital Medical Technologies of Bioquantum Medicine and Therapy in Elimination of Allergy Symptoms

In recent years, there has been an increasing integration of alternative medical technologies, particularly those involving digital medical technologies based on quantum and bioquantum medicine, frequency and wave therapy, and bioquantum therapy, for treating COVID-19, post-COVID, and long-COVID conditions as outlined in ICD-11. This study aimed to experimentally evaluate the latest digital medical technologies, specifically focusing on bioquantum therapy, for allergy treatment. A comprehensive review of existing literature on the application of bioquantum medicine in allergy therapy was conducted. The findings confirm that bioquantum therapy is an effective treatment option for mild to moderate allergies, significantly enhancing symptoms and overall quality of life. BICOM devices are recommended for managing mild to moderate allergies and associated complications. Furthermore, the study highlights that BICOM therapy is not only effective but also safe, with no serious adverse effects observed throughout the year-long study period. Given these promising results, it is recommended that healthcare professionals pursue specialized training, including master classes and continuous professional development in bioquantum medicine and therapy. Obtaining the necessary licenses and permits to work with BICOM devices is essential for ensuring the safe and effective application of this innovative treatment method. As the field continues to evolve, staying updated on the latest advancements in bioquantum medicine will be crucial for medical practitioners.

Computer vision solution for uniform adherence in gastronomy schools: An artificial intelligence case study

This research study presents an innovative application of computer vision technology in culinary education to ensure consistent student uniform adherence, crucial to accomplishing hygiene, safety, and professionalism standards. The proposed approach utilizes the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to generate a computer vision application prototype to identify specific culinary uniforms components, such as chef's jackets, aprons, hats, and pants. The development process using LandingLens, a code-free platform, involves several stages: business and data understanding, preparation, modeling, evaluation, and deployment. The final model was training with 77 images, and the application deployment was tested using 38 images. Results demonstrate the potential of artificial intelligence to enhance operational efficiency and uphold professional standards in culinary education. Integrating computer vision addresses the challenges associated with manual monitoring and opens opportunities for broader adoption of technology in culinary pedagogy and training.

Methodology And Application of Innovative Technologies to Ensure Sustainable Development: Formation of Eco-Awareness Through the Prism of Ecotourism

Methodology And Application of Innovative Technologies to Ensure Sustainable Development: Formation of Eco-Awareness Through the Prism of Ecotourism

A recyclable, interchangeable optical switch with a PDLC-PVA-PSCLC structure and a low-voltage drive system

ABSTRACT Polymer dispersed liquid crystals (PDLC) and polymer stabilised cholesteric liquid crystals (PSCLC) are an indispensable class of electrically switchable materials, which have been widely applied in the fabrication of efficient and systematic smart windows. And doping nanoparticles in PDLC films can greatly improve their properties. In this study, PDLC films doped with zirconia nanoparticles were prepared by polymerisation-induced phase separation (PIPS) method, PSCLC films with nematic liquid crystals as the main part (reflecting wavelengths in the range of 400–600 nm) were prepared by UV curing method, and a novel optical switch was developed by combining these two liquid crystal films. The optimal bilayer sample was developed through a comparative analysis of properties among samples with varying formulations for each liquid crystal layer. This study represents a novel advancement in PSCLC and nanoparticle-doped PDLC bilayer structures, showcasing fully actuatable properties in the visible wavelength range. These structures exhibit excellent electro-optical properties and demonstrate stable, sustainable performance that can be regenerated. The findings underscore the potential of PDLC and PSCLC for applications in smart curtains and flexible materials, opening up new avenues for innovative technological applications.