Background: Detection of student engagement in a virtual learning environment has become paramount. The current systems are mostly based on visual facial features, ignoring contextual demographic features, which can undermine generalization and fairness across different groups of learners. Objective: The study introduces a contextually sensible deep learning system that combines visual facial features with demographic embeddings (age, gender) to enhance the classification rate of engagement and achieve fairness and real-time capabilities. Methods: A training set of 16,000 labeled images was formed of 17 institutional ethics-approved volunteers aged 5-21+ years. Baseline performance was set by fine-tuning of 4 pretrained CNNs (MobileNet, Xception, DenseNet201, NasNet Large). A custom model, OnEduNet, was developed, which integrated visual and contextual representations. Performance of models was measured using macro F1-score, confidence intervals, significance testing (McNemar), fairness metrics (Demographic Parity, Equalized Odds), ablation testing, robustness testing, and Grad-CAM interpretability. Results: Results: OnEduNet achieved a statistically significant validation accuracy of 92%, outperforming the best baseline, MobileNet (89%). The model demonstrated a minor lack of demographic difference (EOD<0.05) and maintained a real-time inference speed (18ms/image). Conclusion: Combining contextual demographic features with visual representations could contribute greatly to engagement detection accuracy, fairness, interpretability, and deployment feasibility, which can be used to support scalable and patent-oriented educational AI systems.
Introduction/Objective: Given the wide adoption of IoT in agriculture, real-time monitoring of crop yield can now be performed thanks to cloud-based systems. Traditional cloud computing systems have high latency compared to the required demands, limiting their use in agriculture. This research explores the extent to which the metaverse and digital twins can reduce data distribution latency in a hybrid cloud-edge-fog computing environment. Methods: This structured scoping review follows the PRISMA 2020 method. Studies were first collected through searches within the Scopus database. Subsequent selection criteria included language, document type, and year (papers published between 2020 and 2026). Next, 106 studies were selected using keywords, such as "metaverse," "digital twin," and "smart agriculture." A total of 24 papers were selected for further analysis. Results: The application of hybrid computing environments is common practice in present-day agriculture. Digital twins, combined with metaverse simulation tools, allow for real-time operation of agricultural enterprises through prediction and process synchronization. Future improvements can be achieved through innovations in 5G/6G wireless networking and artificial intelligence. Nonetheless, many problems arise when implementing them, especially in rural areas. Discussion: Combining metaverse simulation capabilities and advanced distributed computing environments provides an efficient solution for the implementation of smart agriculture. Concerns about compatibility, scalability, and potential differences between models and reality still exist. Moreover, the issue of the digital divide may be addressed through decentralized computing architectures. Conclusion: Metaverse technology, coupled with digital twins and distributed computing infrastructure, is a promising strategy for minimizing the data distribution latency in smart agriculture.
Background: Brain tumors refer to the growth of abnormal cells in the human brain, posing a significant risk to a person’s health and well-being. Therefore, early detection of brain tumors is essential for improving diagnosis and providing appropriate treatment. However, existing feature selection models fail to capture the intricate details of brain tumors, resulting in poor classification performance. This study aims to identify accurate tumor boundaries and learn fine-grained details about the brain tumor from the segmented region to enhance brain tumor classification using Magnetic Resonance Imaging (MRI) data. Methods: This research proposes a Spatially Constrained Attention Weighted Fuzzy C-Means (SCAW-FCM)-based tumor segmentation model by integrating spatial context and attention weight to achieve more accurate boundary detection. Brain tumor features exhibit complex relationships among textures, shapes, and intensities in MRI. Therefore, a Polynomial Differential Learning Strategy- based Hunter Prey Optimization (PDLS-HPO) algorithm is employed to capture these nonlinear relationships effectively. Furthermore, a Leaky Rectified Linear Unit (ReLU) activation function is incorporated into a Bidirectional Long Short-Term Memory (BiLSTM) model to address the vanishing gradient issue, which helps reduce misclassification by learning fine-grained details in the MRI images, resulting in accurate classification. Results: Experimental results of the SCAW-FCM with PDLS-HPO model demonstrate an accuracy of 99.56% on the Brats 2020 dataset, which is 2.45% higher than existing approaches, such as the Attention-guided Residual Multiscale convolutional neural Network (ARM-Net). Discussion: The proposed SCAW-FCM-based segmentation model efficiently segments tumor regions and addresses morphological heterogeneity. In addition, the proposed PDLS-HPO-based feature selection model enables the BiLSTM model to identify subtle and complex patterns, thereby efficiently addressing feature redundancy issues. Conclusion: The proposed model improved tumor type classification by learning subtle MRI features, such as tumor texture and boundary characteristics, which are crucial for accurate classification.
Objective: This study aims to propose an SMSDAE-based TSA approach to solve these issues. Method: The study proposes a TSA method based on stacked marginalized sparse denoising autoencoders (SMSDAEs), integrating noisy samples into model training and marginalizing noise interference. It uses the IEEE 39-bus system for validation, with samples generated via simulation and power flow calculations. The SMSDAE is compared with other machine learning models. Results: Validated on the IEEE 39-bus system, SMSDAE achieves 97.21% accuracy, outperforming models like SSAE (96.59%) and SVM (93.13%). It has faster convergence (107.25s training time) than SSDAE (192.43s) and maintains over 97% accuracy at 15dB SNR. Discussion: The testing is only based on the IEEE 39-node system and has not been validated in larger-scale power grids (such as IEEE 118 nodes) or actual power grid data; the impact of different types of noise on the model has not been explored. Further testing scenarios and comparison benchmarks need to be expanded to enhance the universality of the results. conclusion: The SMSDAE-based TSA method resolves noise and overfitting issues, with high accuracy, fast convergence, and strong robustness. It provides a reliable, patent-pending solution for real-time power system transient stability assessment. Conclusion: The SMSDAE-based TSA method resolves noise and overfitting issues, with high accuracy, fast convergence, and strong robustness. Additionally, the method aligns with existing power grid infrastructure, supporting the development of smart grids and providing stability assessments for high-proportion renewable energy integration, which aligns with energy transition and carbon neutrality goals.
IntroductionThe rapid rate of urbanization in modern cities is leading to growing operational complexity in Solid Waste Management (SWM), requiring the development of intelligent routing solutions for the sustainable management of urban infrastructure. This study presents an innovative methodological framework that combines a comprehensive analysis of the patent landscape with a comparative evaluation of three metaheuristic algorithms based on Artificial Intelligence (AI), such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), to optimize the Multi-Objective Vehicle Routing Problem (MO-VRP). MethodsThe research combines an in-depth analysis of patents filed between 2005 and 2024 that reveals major industrial trends in adaptive route optimization, and a synthetic case study was developed to evaluate three metaheuristic algorithms according to three performance indicators, namely total distance traveled, CO2 emissions, and patent-inspired indicator of CO2 per tonne-kilometer (CO2/t·km). ResultsThe comprehensive analysis of patents highlights major industry trends, including adaptive route optimization, real-time monitoring, and the use of GPS tracking. However, this approach reveals a notable absence of multi-objective environmental optimization. Computational experiments demonstrated that PSO provided the best balance between distance and emissions. DiscussionThe results obtained demonstrate the complementary advantages and strengths of metaheuristic algorithms and provide guidance for defining optimization strategies suitable for different municipal deployment scenarios. ConclusionThis work is not limited to a simple comparative analysis. It provides a reproducible simulation framework and outlines concrete areas for innovation in patentable, eco-efficient, and adaptive waste collection systems.
Introduction: Medical image fusion (MIF) integrates complementary information from multiple modalities to enhance diagnostic accuracy. However, existing approaches often struggle to suppress noise while preserving critical anatomical details. Materials and Methods: We propose ENCAF-NSST-AD, a fusion technique that combines the Non-Subsampled Shearlet Transform (NSST) with anisotropic diffusion (AD) refinement. Lowfrequency base layers (LFBL) are fused using an energy-based weighting strategy, while high-frequency detail layers (HFDL) are integrated through a contrast-aware rule. The reconstructed image is further enhanced using AD filtering with optimized parameters to improve clarity and preserve structural information. results: Experiments on standard medical image datasets demonstrate that ENCAF-NSST-AD consistently outperforms existing methods in both visual quality and quantitative metrics, including FMI, FF, entropy, and standard deviation. Results: Experiments on benchmark datasets demonstrate that ENCAF-NSST-AD achieves superior fusion quality compared with existing state-of-the-art methods, exhibiting enhanced visual clarity and higher values across standard quantitative metrics. Discussion: The proposed method effectively balances noise suppression with edge preservation, addressing limitations of traditional MIF schemes. By combining adaptive fusion rules with edgepreserving diffusion, ENCAF-NSST-AD preserves global contrast and fine anatomical boundaries, resulting in fused images more suitable for clinical interpretation. Its energy- and contrast- aware fusion with AD refinement represents a clinically relevant and patent-oriented advancement. Conclusion: The integration of NSST with adaptive fusion rules and AD refinement produces robust and diagnostically meaningful fusion outcomes. ENCAF-NSST-AD is an effective MIF approach that can enhance clinical decision support in medical imaging.
Introduction: Introduction: Contemporary architectural discourse is defined by the tension between globalized technological unification and the need to preserve local cultural identity. This study aims to explore how "tectonics"—the meaningful articulation of structure and materials—serves as a marker of different trajectories of cultural self-identification in Western and Eastern European architecture after 1991. Methods: The research employs a comparative analysis of architectural practices in the two macroregions. The methodology integrates a theoretical framework based on tectonic culture (Frampton, Semper) with detailed case studies of landmark objects, including the Elbphilharmonie (Hamburg), Louis Vuitton Foundation (Paris), Szczecin Philharmonic, and DOX Centre (Prague). A quantitative assessment of production complexity (Ic) and an analysis of patent activity (using EPO and USPTO databases) were conducted to evaluate the engineering innovations associated with each project. objective: The purpose of this study is to identify and analyze the structural features of structural systems in Western and Eastern European architecture, to determine their role in the formation of the architectural appearance of these countries, as well as their contribution to the stability and durability of modern buildings. Results: The analysis reveals two distinct vectors. Western Europe is characterized by "tectonics as a technological manifesto," evidenced by high production complexity indices and project-specific patents (e.g., for vibration damping mechanisms or digital workflow management) to demonstrate engineering virtuosity. Conversely, Eastern Europe follows a strategy of "dialogue with heritage," utilizing standard technologies and materials to reinterpret local history, resulting in lower structural complexity without significant patent generation. Discussion: These differences reflect diverging socio-economic contexts. Western projects prioritize formal autonomy and the aestheticization of engineering power driven by global capital. Eastern projects use tectonics to root architecture in its context, where the absence of new patents represents a conscious focus on poetic expression through standard means rather than technological invention. result: A study among experts from Eastern Europe showed that in Western European countries, the emphasis is on combining historical elements with modern materials such as polycarbonate and carbon fiber to create visually dynamic and structurally sustainable buildings. The main tectonic system in Germany remains the post-and-beam structural system (reinforced concrete folds). Architectural structural systems continue to evolve, and architectural tectonics remains the foundation for creating spaces that support, inspire, and unify the intelligent interaction between the building and the environment. The features of the design of tectonic systems in the architecture of Western and Eastern Europe demonstrate a variety of approaches and solutions that combine technological innovations and respect for cultural traditions. These systems play a key role not only in the construction of functional and sustainable buildings, but also in creating a new, more harmonious relationship between people and the environment. Urban landscape is becoming increasingly important in terms of introducing new approaches to the aesthetics of architecture in the digital age, functional and aesthetic compliance of architecture with the new requirements of life. The post-and-beam system is known for its versatility and ability to take on a variety of shapes depending on functional and aesthetic requirements. The assembly of reinforced concrete structures is an effective solution that allows you to significantly reduce the consumption of materials while maintaining high strength and stability of the structure. In such structures, ribbed panels are used, which redistribute loads and provide high reliability. Such systems are especially effective in situations where large spans need to be covered without additional support, making them a popular choice for industrial and public buildings. On the other hand, the frame construction system embodies ancient architectural traditions that are finding new uses in modern architecture. Such a system uses wooden or metal frames filled with various materials, which gives the structure strength, but also visual lightness. Modern timber frame houses are designed with energy saving in mind and are developing sustainably in accordance with the latest environmental standards. The unique aesthetics of such a tectonic system, combining historical authenticity with modern technological advances, has made it popular in private housing construction. Arched or vaulted roofs are recognizable symbols in almost every culture and show an incredible variety of architectural designs. Such structural elements, due to their shape, have an excellent ability to withstand heavy loads, which makes them indispensable in the construction of both public and religious buildings. Modern technologies make it possible to make vaults and arches from a variety of materials: from traditional bricks to composite materials, which expands the possibilities of their use in urban architecture. Such trends in architecture and design make it possible to connect the past with the present and create buildings that are not only functional, but also tell a story. Historical elements such as Gothic arches, classical columns, and Baroque facades act as cultural markers, highlighting the rich heritage of the region. Modern materials such as polycarbonate are light and transparent, which allows you to create a feeling of spaciousness and openness in the space. The use of carbon fiber increases the strength and durability of the structure, allowing the building to withstand both time and the effects of the natural environment. Western European, especially German, architects often use contrasting techniques to emphasize the harmony of styles. For example, in ancient cities, we see how historical facades become a kind of frame for ultra-modern glass structures. This style gives the urban environment a dynamic character, further stimulates interest in cultural heritage and attracts tourists. The architectural solution, in which classics and modernity coexist, symbolizes the desire of society to find a balance between the preservation of tradition and innovation. Social and environmental aspects also have an impact on this architectural trend. Energy-saving technologies are often integrated into the project, resulting in buildings that are not only aesthetically beautiful, but also environmentally sustainable. Using recycled materials reduces our carbon footprint and highlights the importance of responsibly consuming resources. At the same time, architects strive to provide multifunctional spaces in buildings so that they can change in accordance with the needs of society and make an effective contribution to its development. In France, the half-timbered structural system is more popular, which is used mainly in the construction of entertainment and cultural and leisure institutions. Figure 1. Experts’ assessment of the frequency of tectonic systems in Western Europe Thus, the combination of historical elements and modern materials creates a unique architectural atmosphere in Western Europe. The movement reflects a broader cultural trend that emphasizes the importance of preserving historical identity and reinterpreting it in an innovative way. As a result, the cities of Western Europe not only preserve their cultural identity, but also become attractive role models in the international arena in the field of design and sustainability. In Eastern Europe, by contrast, architects face unique challenges that combine the use of traditional materials such as wood and brick with innovative building systems. This is especially noticeable in the restructuring of urban spaces, which requires not only functionality, but also respect for the historical past of the territory. Here, structural ideas are embodied in the form of adaptive structures capable of responding to environmental changes while maintaining the importance of cultural authenticity. Architects in Eastern Europe strive to integrate integrated solutions within arched and vaulted roofs that can maintain a balance between nature and urbanization in a changing climate and diverse landscapes. Such design solutions require a deep understanding of not only the physical aspects of building materials, but also the cultural characteristics of the region. Of particular note are projects that offer a hybrid use of buildings, shifting the focus from narrow use to multifunctionality and harmony with the natural environment. One example is the implementation of projects that combine traditional wooden architecture with modern technologies, such as energy-efficient glass facades and automated climate control systems. Such buildings not only provide comfortable living and working conditions, but also minimize the impact on the environment. The practice of adapting old buildings to modern requirements is another important task facing the architectural community of the region, requiring both technical knowledge and an understanding of the historical context. In addition, the emotional aspect of architecture also plays an important role. Buildings should not only serve a function, but also create a sense of belonging and pride in their heritage. An architect is also required to be able to work with historical layers, as he restores and integrates old elements into a new structure, forming a bridge between the past and the future. This approach ensures that the created objects become an integral part of the urban fabric, maintaining its identity and uniqueness. Figure 2. Experts’ assessment of the frequency of tectonic systems in Eastern Europe Finally, special attention will be paid to the creation of public spaces that stimulate social interaction and contribute to the development of society. The use of green spaces, open spaces and sizes proportional to human perception has become an integral part of living spaces aimed at creating a comfortable and sustainable urban environment. This testifies to the desire of the Eastern European architecture not only to follow global trends, but also to anticipate them, to find original solutions dictated by the situation and time. Thus, by studying the structural features of tectonic systems in the architecture of Western and Eastern Europe, it becomes possible to identify evolutionary trends in response to various socio-cultural and technological factors. The analysis shows that Western Europe is moving towards a futuristic minimalist aesthetic, while Eastern Europe is striving for a synthesis of the old and the new in a spatial context. Ultimately, this research will not only shed light on the dynamics of contemporary architecture, but also provide a comprehensive understanding of how architectural practices in these regions can serve as a basis for the search for a sustainable future. Figure 3. Experts’ assessment of the frequency of tectonic systems in the countries of Western and Eastern Europe The survey among experts made it possible to establish that in Western Europe special attention is paid to sustainable development, energy efficiency and minimizing the impact of construction on the environment. Countries such as Germany and France are actively implementing green building systems and eco-technologies that optimize the use of resources. Examples include innovative projects such as smart facades, which adapt to changing weather conditions and provide natural ventilation, as well as the use of renewable materials in construction. This will allow not only to preserve the cultural heritage, but also to develop new architectural solutions that meet the requirements of the time. In Germany, the beam tectonic system is developing towards the integration of modern technologies to improve the energy efficiency and durability of structures. For example, innovative materials such as nano-coated composite beams are used in design and construction, which are able to adapt to changes in temperature and humidity. Modern engineering solutions make it possible to create buildings that efficiently use solar energy and reduce the need for artificial sources of heating and lighting. Moreover, active work is underway to use smart building management systems that can reduce energy consumption to the minimum necessary level. As the experts noted, in France, the half-timbered structural system combines traditional methods with modern approaches to sustainable construction. The architects strive to preserve the historical atmosphere while introducing innovative elements. The half-timbered buildings, which date back to medieval traditions, adapt to modern eco-friendly standards through the use of environmentally friendly materials such as bioconcrete and recycled wood. Such initiatives support not only the construction of new facilities, but also the reconstruction of existing ones, allowing them to meet modern energy efficiency standards. In addition, both countries are actively working on the development of urban infrastructure with a focus on sustainable transport and ecological public spaces. For example, in large cities in Germany and France, plans are being implemented to expand green areas and park areas, as well as to integrate bicycle and pedestrian paths into the urban environment. This approach undoubtedly contributes to reducing air pollution and improving the quality of life of citizens. These measures, supported at the state and municipal levels, reflect a common desire to create environmentally sustainable and comfortable urban spaces. In general, the architectural tectonic systems of Western Europe continue to evolve, taking into account modern challenges related to ecology and energy resources. The German emphasis on reliability and technological solutions in the beam system, as well as the French approach that combines cultural tradition and environmental awareness in half-timbered construction, show how historical experience can coexist with innovation. Meanwhile, Eastern European countries such as Poland and the Czech Republic are increasingly combining their national architectural methods with modern technologies for the restoration of their historic buildings. This is evident in the reconstruction of old city quarters, where architects are faced with the task of preserving the historical appearance while introducing modern standards of safety and comfort craftsmen and ensures the durability and functionality of structures in modern conditions. Such differences can be explained by different historical and cultural backgrounds, as well as by the economic and political prerequisites for the development of European countries. However, in Western and Eastern Europe, there is a common desire to use architecture as a means of expressing national identity and cultural diversity. The study of the structural features of the Earth systems of these regions will contribute to a deeper understanding of the influence of historical and contemporary factors on the development of architectural practice and will contribute to the further development of innovative solutions on a global scale. Such research allows you to identify opportunities for development and implementation. Conclusion: The study confirms that tectonic strategies differ fundamentally between the regions. The engineering logic of a building is integral to its cultural message, serving either as a demonstration of technological dominance or a tool for historical reflection.
IntroductionThe reactivation of water-flooded gas wells in low-porosity, low-permeability carbonate reservoirs remains a significant challenge in the natural gas industry. This study aims to establish a quantitative evaluation method to assess the unblocking potential of such wells, providing a key theoretical basis for targeted measures. Recent patents have focused on chemical methods for wettability alteration, yet a comprehensive quantitative chart linking reservoir conditions to well performance is still lacking. MethodsThis research utilized a series of core physical simulation experiments, including porosity-permeability tests, gas breakthrough pressure measurements, and nuclear magnetic resonance (NMR) analysis. Data from 31 core samples from the Longmen Block were integrated with production dynamic data from typical wells (TD-12# and TD-19#) to establish quantitative relationship charts. ResultsThe results indicate that: (1) The reservoir is typical low-porosity (avg. 2.24%) and low-permeability (avg. 2.06 mD), requiring water saturation within 10 m of the well to be reduced below 80% for effective gas flow; (2) NMR experiments revealed a power-function relationship between the critical pore throat radius of movable water and the pressure gradient; (3) Evaluation based on the chart showed that TD-12# is difficult to unseal under current conditions, while TD-19# could increase its movable reservoir volume by 872.55 m3 through wettability reversal (contact angle from 30° to 83°). DiscussionThe “pressure gradient - residual water saturation - breakthrough pressure gradient” chart formed in this study demonstrates good applicability and aligns with production data. It effectively bridges the gap between laboratory core data and field-scale well performance. ConclusionThe quantitative evaluation chart provides a reliable tool for screening candidate wells and optimizing drainage gas production and wettability reversal measures in water-flooded carbonate gas reservoirs.
Introduction: In the automotive industry, integrating connected and autonomous vehicles through the Internet of Vehicles and wireless communication has gained prominence. Secure communication and data privacy are the primary concerns in wireless communication. A weak privacy mechanism allows non-legitimate users to spoof for illegal or malicious activities or to manipulate the vehicular network. The robust Distributed Denial of Service (DDoS) detection and mitigation alone is required, as the risk of Distributed Denial of Service (DDoS) attacks is increasing in vehicular communication. The primary aim of this study is to design a secure and intelligent system for detecting and mitigating DDoS attacks in IoV. Specifically, the study aims to develop a hybrid detection model comprising Decision Tree and Random Forest classifiers to effectively analyze real-time network traffic. Another core goal is to ensure data privacy by implementing ElGamal encryption for all inter- vehicular communications. Additionally, the study proposes a trust-based algorithm that evaluates the reliability and trustworthiness of messages received by Roadside Units (RSUs) from registered vehicles. Methods: The proposed system analyses the vehicular network traffic to detect DDoS attacks using the hybrid approach combining Decision Tree and Random Forest algorithms. A trust-factor- based algorithm is designed to validate the event information the RSU receives from the registered vehicle. Depending on the trust factor and validation process, RSU checks for DDoS attacks and blocks vehicles that support the event. Privacy is ensured by encrypting all messages and information, including vehicle IDs and driver and passenger information, using the ElGamal encryption technique. Results: Experimental evaluation of the proposed hybrid model demonstrates superior performance in DDoS detection. The accuracy of the hybrid model is 99.81%, while those of logistic regression, kNN, and the Naive Bayes algorithm are 97.30%, 97.81%, and 97.10%, respectively. These results affirm the effectiveness of combining classification models with trust management and encryption for secure vehicular communication. Discussion: The proposed hybrid Decision Tree–Random Forest model achieves superior accuracy over existing methods while preserving data privacy through ElGamal encryption. Trust-factor validation strengthens detection but may lead to rare false blocks of legitimate vehicles. Future work includes restoration mechanisms, blockchain-based trust, and quantum computing for faster detection and post-quantum privacy. Conclusion: The proposed framework addresses critical vulnerabilities in current vehicular networks and offers a scalable, efficient, and patentable solution for intelligent transportation systems and vehicular cybersecurity.
Abstract: Matching eligible patients to appropriate clinical trials remains a major challenge in healthcare due to large, heterogeneous datasets and complex eligibility criteria. This paper proposes a novel Quantum Machine Learning (QML) algorithm integrated with Natural Language Processing (NLP) techniques to optimize clinical trial matching. Unlike traditional methods, the proposed framework introduces a hybrid quantum–classical pseudocode workflow that combines quantum feature mapping with NLP-based data extraction to improve accuracy and efficiency in patient–trial matching. To strengthen the foundation of the proposed approach, key patented technologies, such as US20200005906A1 (intelligent patient–trial data matching) and US20220068443A1 (NLP-based eligibility interpretation), have been considered, demonstrating the growing feasibility of automated matching systems. The novelty of our work lies in unifying these advances within a scalable QML–NLP framework that reduces manual workload, shortens trial recruitment times, and improves overall research efficiency. By integrating quantum computing with NLP, this study moves beyond existing reviews and provides a concrete, implementable methodology to accelerate patient recruitment and advance personalized medicine. discussion: By leveraging the computational power of quantum computing, current limitations in managing big data for clinical trials can be overcome. The synergy of quantum machine learning and NLP enhances trial efficiency, reduces costs, shortens trial durations, and stabilizes research methodologies.
Introduction/Objective: The integration of IoT, edge intelligence and Digital Twin (DT) technologies within Unmanned Aerial Vehicle (UAV) operations has the potential to revolutionize missions through real-time monitoring, predictive analysis and proactive decision making. In this paper, a patent edge-enabled DT framework is proposed for IoT-based UAVs and experimentally verified by the DJI Tello drone. Methods: Telemetry streams are received by a laptop acting as an edge device where DT mirrors drone states and predicts trajectory, as well as detects anomalies. As opposed to cloud-based DTs, the edge deployment makes a tradeoff between low-latency synchronization and commodity-- grade hardware operability. Results: The experimental results show that DT hosted on edge reduces the latency of telemetry by more than 75% comparing to a baseline running in the cloud, realizes trajectory prediction accuracy at MAE of 0.01 m. Anomaly detection experiments also demonstrate that the implemented methodology is able to detect motion spikes, slow drifts, packet loss, or drastic depletions with an F1-score of 0.89 and delays in the detection of lower than 0.1 seconds. Discussion: The integration of AI-enhanced modules is explored high level for trajectory forecasting using LSTM networks and autoencoders for anomaly detection. The DT matures into an intelligent Digital Twin (iDT). These AI–based extensions enhance predictive accuracy and detection sensitivity, making a proactive, pre-emptive AI-based security infrastructure. Conclusion: The results illustrate the feasibility and efficiency of patent edge-based UAV iDTs as predictive tools for early warning systems.
Introduction: Gas wave ejectors have broad application prospects in natural gas extraction and transportation. The axial gas-wave ejector performs poorly at high compression ratios. Therefore, the centrifugal effect of the rotating radial oscillator tube can be utilized to improve the ejector performance. This paper has maximized the performance of the radial gas-wave ejector through a well-designed pressure port. Methods: Computational Fluid Dynamics (CFD) commercial software FLUENT was used for numerical simulation in this study, and a three-dimensional numerical model was employed to improve computational accuracy. This paper combines numerical simulation and experimental analysis to study the influence mechanism of pressure port position on the ejector performance of the radial oscillator tube. Results and Conclusion: When the port position is deviated, the optimal functional wave system is disrupted, leading to a return flow from the medium-pressure port or insufficient gas intake at the low-pressure port, which in turn reduces ejector performance. The delayed opening of the medium-pressure port, early closure of the high-pressure port, and early closure of the medium-- pressure port have a particularly significant effect on device performance, leading to strong reflected compression waves within the wave rotor and a large amount of backflow when the flow path is connected to the low-pressure port. A deviation of 10° from the medium-pressure port in the experimental range results in a decrease of more than 60% in the ejector rate and the overall device efficiency. Under the comprehensive experimental design conditions, the highest ejector and isentropic efficiencies of the device can be achieved when αHM=12°, αHP=20°, αHL=7°, αMP=23°, αLP=14°, which are 29.75% and 53.26%
Introduction: The coal industry in China plays a vital role in the national economy, yet safety production remains a significant challenge. Although coal mine accidents have decreased in number, their complexity and the diversity of accident types have increased. The government has implemented regulations to improve safety, and leveraging big data and intelligent technologies for digital transformation is seen as a key path for enhancing safety production. This study introduces a novel deep learning model, Tri-Input-BERT-MLP, to enhance relation extraction in coal mine accident reports, which is also being developed into a patented system for improving safety monitoring. Methods: The paper proposes a hybrid architecture that combines Tri-Input-BERT with Multilayer Perceptron (MLP) to extract relations between entities in coal mine safety reports. The model integrates semantic features from BERT, entity pair representations, and positional encodings. The study also builds a specialized dataset from publicly available accident reports from China between 2010 and 2020, focusing on handling complex and unstructured data. Results: Experimental results show that the Tri-Input-BERT-MLP model significantly outperforms baseline models like BERT-BiLSTM, BERT-CNN, and others. It achieves the highest precision (91.29%), recall (91.32%), and F1 score (91.30%) in relation extraction tasks. The model handles class imbalance by augmenting data and adjusting loss weights, improving performance, especially on minority relations like “R-belong_to” and “R-located_in.” Discussion: The Tri-Input-BERT-MLP model demonstrates substantial improvements in relation extraction for coal mine accident reports. It excels in handling industry-specific terminology and complex entity relationships. However, challenges remain in dealing with long-tail categories due to limited data. Future research should expand the dataset, apply data augmentation, and explore advanced techniques like Graph Neural Networks to further enhance model performance. Conclusion: This study presents the Tri-Input-BERT-MLP model, which effectively extracts relationships in coal mine accident reports, outperforms traditional methods, and offers significant improvements in precision, recall, and F1 score. The model's success provides valuable support for the development of intelligent supervision systems in coal mine safety, helping to reduce accidents and improve safety standards. Future research will focus on expanding the model's capabilities to handle long-tail relations and improving its generalization to diverse real-world scenarios.
Introduction: Objective assessment of pain is important for clinical diagnosis and therapeutic intervention. But traditional scales like the Visual Analogue Scale (VAS) or Numeric Rating Scale (NRS) depend on patients reporting their own symptoms, which may be difficult for some people. Methods: An EEG short-time window pain detection model with Fusion of Mutual Information‐Based Recursive Feature Elimination (MI-RFE) + Gradient Boosting (GB) is proposed in this study. By comparing slide window lengths from one to five seconds, we found that a one-second window provided the optimal balance between capturing transient pain signals and increasing the size of the dataset. The dataset is enlarged 15 times by a one-second window. This paper proposes a classification model that fuses the Mutual Information-based RFE method (MI-RFE) with the Gradient Boosting classifier. The MI-RFE is used to select high-dimensional features, then the resulting subset is used to train a Gradient Boosting classifier. Results: Finally, this EEG short-time window pain detection model of MI-RFE + GB achieved an accuracy of 93.41%, an F1 score of approximately 93.54%, and a maximum ROC AUC of 97.96%, better than other methods such as SVM. Discussion: The results show that the one-second window more effectively captures transient pain signals while maintaining temporal resolution and improving model training accuracy. MI-RFE + Gradient Boosting model fully exploits the non-linear relationship between EEG features and pain labels, demonstrating strong generalization capabilities. Conclusion: This study provides a novel technical solution with significant patent potential, offering practical insights for developing objective pain assessment systems and demonstrating promising applications in clinical pain management.
Background: One-way bearings are important components in transmission systems. Their function is to rotate freely forward and stop in reverse. They are widely applied in machines that need to eliminate reversal, vibration, oscillation, and reduce friction. One-way bearings are also called one-way clutches or overturning clutches. With the rapid development of global industrial technology, the requirements for the performance of one-way bearings applied in mechanical equipment are becoming more and more stringent. As a result, there is increasing demand for oneway bearings with advantages such as wear-reducing, wear-resistant, high bearing capacity, high efficiency, high precision, and the ability to withstand high speeds Objective: This paper aims to classify and summarize the theoretical research as well as patents of one-way bearings, analyze the working principles as well as the role of various new types of oneway bearings. It also analyzes the functions and improvements of the structure and performance of one-way bearings, which provides references for scholars and researchers in the future. Methods: This paper reviews the patents and papers related to one-way bearings in recent years. It categorizes the one-way bearings according to the structure and working principle, including roller-type, wedge-type and new structure one-way bearings. It also analyzes the patents of various one-way bearings, and summarizes the problems existing in the development of one-way bearings in recent years. Results: Conclusions are drawn by analyzing the structure and characteristics of different kinds of one-way bearings. The development trends of present one-way bearings and the direction of improvement are summarized. The main problems existing in one-way bearings and the future development trends are pointed out. Conclusion: One-way bearings feature numerous innovative designs. A large number of patents have proposed structural improvements to their components, which reduces friction, extends service life, ensures accurate reverse locking, and enhances reliability
In the originally published article [1], the reference section contained an incomplete reference [5]. It has now been corrected, which leads to the accessible online search. The original article can be found online at: https://www.eurekaselect.com/article/145481 The specific correction details are as follows: Original: [5] "Reimagining plastics waste as energy solutions: Challenges and opportunities", NPJ Mater. Sustain. Corrected: [5] Jaffurullah MA, Mariadhas A, Raj DJ and Jayaraman J. Transforming Plastic Waste into Biofuel Oil: An Evaluation and Conceptual Outlook with Implications for Transitional Energy. Recent Patents on Engineering. 2026; 20(2): E18722121331855. [https://doi.org/10.2174/0118722121331855241212031631] The article has been updated to reflect this correction. The authors apologize for any inconvenience caused to the readers.
Introduction: With the growing demand for wind power generation, hybrid tower wind turbines are increasingly being deployed in mountainous regions with abundant wind energy resources. To improve the adaptability and structural safety of hybrid tower foundations under complex geological conditions, such as those in mountainous regions, this study proposes the use of a rock bolt composite foundation. In this configuration, rock bolts are installed around the hybrid tower foundation, forming a composite system in which the foundation and the bolts jointly resist external loads. Methods: To evaluate the effectiveness of the addition of rock bolts and to investigate the mechanical performance of the composite foundation. Finite element models of both the hybrid tower foundation and the rock bolt composite foundation were developed using ABAQUS. These models were subjected to identical design loads, and their structural responses—including concrete stress, foundation displacement, and reinforcement stress—were compared and analyzed. Based on the results of the response analysis, an optimized design was proposed to further reduce the foundation dimensions and overall material consumption, thereby enhancing both structural performance and cost-efficiency. Results: The results indicate that, under the condition of constant total rock bolt usage, a slight improvement in the mechanical performance of the rock bolt composite foundation is observed as the diameter of the rock bolts decreases; however, the enhancement is not substantial. After the installation of additional rock bolts, the mechanical performance of the foundation was significantly improved. Discussion: Specifically, the tensile stress in the concrete decreased by 27.81%, the compressive stress decreased by 11.88%, the foundation displacement was reduced by 35.39%, and the reinforcement stress was reduced by 42.74%. After reducing the dimensions of the hybrid tower foundation and incorporating additional rock bolts, the mechanical performance of the foundation was further enhanced, while construction costs were effectively reduced. Conclusion: The rock bolt composite foundation demonstrates significant advantages not only in structural mechanical performance but also in reducing construction costs and optimizing resource allocation, thereby showing strong potential for engineering applications—particularly in mountainous regions with complex terrain and limited accessibility for material transportation. This study may also provide a valuable reference for the patent-oriented design and further innovation of hybrid tower foundations in such environments.
Bearings, as critical mechanical transmission components, play a vital role in the reliability and efficiency of mechanical systems. Under high-speed operation and heavy-load conditions, the heat generated by bearings must be effectively controlled to prevent temperature increases, lubrication failure, or even bearing damage. Therefore, bearing cooling technology is essential for ensuring their stability and extending their service life. As modern industry places increasing demands on the operational efficiency and load-bearing capacity of machinery, bearings—as critical rotating components within mechanical equipment—- play a pivotal role. The performance of bearings directly impacts the stability and lifespan of the entire system. Under high-load and high-speed operating conditions, bearings generate significant amounts of heat. If this heat is not effectively managed and dissipated, it can lead to increased bearing temperatures, reduced lubrication performance, accelerated material fatigue, and potentially cause equipment failures or safety incidents. Therefore, the cooling structure of bearings plays a crucial role in maintaining their efficient operation and extending their service life. This paper analyzes the cooling structure of bearings. This paper aims to summarize the bearing cooling devices of different structures in recent years, identify the main problems, and provide a reference for researchers in related fields. By reviewing relevant patents related to bearing cooling devices in recent years, comparing and analyzing their advantages and disadvantages, and identifying areas for improvement. This paper analyzes the characteristics of different cooling methods, examines the main issues in their development, and provides an outlook on their prospects. The existing bearing cooling structure sacrifices part of the shaft's service life and equipment safety, or makes the overall structure more cumbersome to achieve better heat dissipation. Therefore, the existing bearing cooling structure needs to be further optimized to achieve better heat dissipation without changing the bearing load capacity and overall volume.
Abstract: Despite the extensive application of waste tires in asphalt modification, there is a distinct lack of systematic research regarding high-content (>20%) crumb rubber and its coupled modification mechanisms. Consequently, this study employed 70# base asphalt and 15%–27% recycled crumb rubber (20–100 mesh) to evaluate their interaction and performance evolution. Correlation mechanisms between process parameters and performance were revealed through macroscopic performance tests (e.g., penetration, softening point, ductility) and microscopic characterizations (e.g., SEM, EDS, FTIR). The results indicated that as the modification temperature increased, the penetration increased linearly from 4.2 ± 0.33 mm to 6.2 ± 0.25 mm, the softening point remained stable initially and then decreased (with a peak value of 65.8 ± 4°C), and the ductility increased continuously from 5.1 ± 0.61 cm to 8.96 ±0.64 cm. The optimal process parameters were determined as follows: temperature of 210-220°C, time of 90 min, dosage of 21%, and mesh size of 60 mesh. Under these conditions, Marshall stability reached 8.6 kN, and dynamic stability was 5382 ± 106.4 cycles/mm, exhibiting both excellent mechanical properties and environmental adaptability. Microscopic analysis showed that a uniformly dispersed system was formed by physical blending of crumb rubber with base asphalt. A desulfurization effect was observed under high- -speed shearing (with sulfur content reduced by 12%-15%). FTIR confirmed the absence of new functional groups, indicating that the modification was primarily physical cross-linking. This study provided process parameters and Theoretical foundation for the engineering application of asphalt modified with high-content recycled crumb rubber, promoting the high-value utilization of waste tires in green pavement materials and reducing carbon emissions.
