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19 pages, 2069 KiB  
Article
A Spatiotemporal Fuzzy Modeling Approach Combining Automatic Clustering and Hierarchical Extreme Learning Machines for Distributed Parameter Systems
by Gang Zhou, Xianxia Zhang, Tangchen Wang and Bing Wang
Mathematics 2025, 13(3), 364; https://doi.org/10.3390/math13030364 (registering DOI) - 23 Jan 2025
Abstract
Modeling distributed parameter systems (DPSs) is challenging due to their strong nonlinearity and spatiotemporal coupling. In this study, a three-dimensional fuzzy modeling method combining genetic algorithm (GA)-based automatic clustering and hierarchical extreme learning machine (HELM) is proposed for DPS modeling. The method utilizes [...] Read more.
Modeling distributed parameter systems (DPSs) is challenging due to their strong nonlinearity and spatiotemporal coupling. In this study, a three-dimensional fuzzy modeling method combining genetic algorithm (GA)-based automatic clustering and hierarchical extreme learning machine (HELM) is proposed for DPS modeling. The method utilizes GA-based automatic clustering to learn the premise part of 3D fuzzy rules, while HELM is employed to learn spatial basis functions and construct a complete fuzzy rule base. This approach effectively captures the spatiotemporal coupling characteristics of the system and mitigates the information loss commonly observed in dimensionality reduction in traditional fuzzy modeling methods. Through experimental verification, the proposed method is successfully applied to a rapid thermal chemical vapor deposition system. The experimental results demonstrate that the method can accurately predict temperature distribution and maintain good robustness under noise and disturbances. Full article
(This article belongs to the Special Issue Intelligent and Fuzzy Systems in Engineering and Technology)
26 pages, 656 KiB  
Review
Agricultural Robotics: A Technical Review Addressing Challenges in Sustainable Crop Production
by Maria Spagnuolo, Giuseppe Todde, Maria Caria, Nicola Furnitto, Giampaolo Schillaci and Sabina I. G. Failla
Robotics 2025, 14(2), 9; https://doi.org/10.3390/robotics14020009 (registering DOI) - 23 Jan 2025
Abstract
The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The [...] Read more.
The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The study analyzes the current state of the art regarding the market trend of agricultural robots used in field and greenhouse operations. Several solutions are emerging, some already implemented and others still in the prototype or project stage. These solutions are beginning to spread, though they may still seem far from widespread field application, particularly given the peculiarities and heterogeneity of the global agricultural landscape. In the face of the many benefits associated with the use of agricultural robots, even today some technical bottlenecks and costs limit their widespread use by farmers. The review provides a fairly comprehensive and up-to-date overview of current trends in agricultural automation, suggesting new areas of research to improve the efficiency and adaptability of robotic systems to different types of crops and environments. Full article
(This article belongs to the Section Agricultural and Field Robotics)
13 pages, 2207 KiB  
Article
Inline-Acquired Product Point Clouds for Non-Destructive Testing: A Case Study of a Steel Part Manufacturer
by Michalis Ntoulmperis, Silvia Discepolo, Paolo Castellini, Paolo Catti, Nikolaos Nikolakis, Wilhelm van de Kamp and Kosmas Alexopoulos
Machines 2025, 13(2), 88; https://doi.org/10.3390/machines13020088 (registering DOI) - 23 Jan 2025
Abstract
Modern vision-based inspection systems are inherently limited by their two-dimensional nature, particularly when inspecting complex product geometries. These systems are often unable to capture critical depth information, leading to challenges in accurately measuring features such as holes, edges, and surfaces with irregular curvature. [...] Read more.
Modern vision-based inspection systems are inherently limited by their two-dimensional nature, particularly when inspecting complex product geometries. These systems are often unable to capture critical depth information, leading to challenges in accurately measuring features such as holes, edges, and surfaces with irregular curvature. To address these shortcomings, this study introduces an approach that leverages computer-aided design-oriented three-dimensional point clouds, captured via a laser line triangulation sensor mounted onto a motorized linear guide. This setup facilitates precise surface scanning, extracting complex geometrical features, which are subsequently processed through an AI-based analytical component. Dimensional properties, such as radii and inter-feature distances, are computed using a combination of K-nearest neighbors and least-squares circle fitting algorithms. This approach is validated in the context of steel part manufacturing, where traditional 2D vision-based systems often struggle due to the material’s reflectivity and complex geometries. This system achieves an average accuracy of 95.78% across three different product types, demonstrating robustness and adaptability to varying geometrical configurations. An uncertainty analysis confirms that the measurement deviations remain within acceptable limits, supporting the system’s potential for improving quality control in industrial environments. Thus, the proposed approach may offer a reliable, non-destructive inline testing solution, with the potential to enhance manufacturing efficiency. Full article
(This article belongs to the Special Issue Application of Sensing Measurement in Machining)
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22 pages, 839 KiB  
Article
Multi-Agent Reinforcement Learning-Based Routing and Scheduling Models in Time-Sensitive Networking for Internet of Vehicles Communications Between Transportation Field Cabinets
by Sergi Garcia-Cantón, Carlos Ruiz de Mendoza, Cristina Cervelló-Pastor and Sebastià Sallent
Appl. Sci. 2025, 15(3), 1122; https://doi.org/10.3390/app15031122 (registering DOI) - 23 Jan 2025
Abstract
Future autonomous vehicles will interact with traffic infrastructure through roadside units (RSUs) directly connected to transportation field cabinets (TFCs). These TFCs must be interconnected to share traffic information, enabling infrastructure-to-infrastructure (I2I) communications that are reliable, synchronous and capable of transmitting vehicle data to [...] Read more.
Future autonomous vehicles will interact with traffic infrastructure through roadside units (RSUs) directly connected to transportation field cabinets (TFCs). These TFCs must be interconnected to share traffic information, enabling infrastructure-to-infrastructure (I2I) communications that are reliable, synchronous and capable of transmitting vehicle data to the Internet. However, I2I communications present a complex optimization challenge. This study addresses this by proposing the design, implementation, and evaluation of an automated management model for I2I service channels based on multi-agent reinforcement learning (MARL) integrated with deep reinforcement learning (DRL). The proposed models efficiently manage the routing and scheduling of data frames between internet of vehicles (IoV) infrastructure devices through time-sensitive networking (TSN) to ensure real-time synchronous I2I communications. The solution incorporates both a routing model and a scheduling model, evaluated in a simulated shared environment where agents operate within the TSN control plane. Both models are tested for different topologies and background traffic levels. The results demonstrate that the models establish the majority of paths in the scenario, adhering to near-optimal routing and scheduling policies. Recursively, for each individual request to create a service channel, the system establishes online an optimal synchronous path between entities with a limited time budget. In total, 71% of optimal routing paths are established and 97% of optimal schedules are achieved. The approach takes into account the periodic nature of the transmitted data and its robustness through TSN networks, obtaining 99 percent of compliant service requests with flow jitter levels below 100 microseconds for different topologies and different network utility percentages. The proposed solution achieves lower execution delays compared to the iterative ILP approach. Additionally, the solution facilitates the integration of 5G networks for vehicle-to-infrastructure (V2I) communications, which is identified as an area for future exploration. Full article
(This article belongs to the Special Issue Novel Advances in Internet of Vehicles)
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36 pages, 19162 KiB  
Article
Advancing Smart Construction Through BIM-Enabled Automation in Reinforced Concrete Slab Design
by Tandeep Singh, Mojtaba Mahmoodian and Shasha Wang
Buildings 2025, 15(3), 343; https://doi.org/10.3390/buildings15030343 (registering DOI) - 23 Jan 2025
Abstract
Building information modeling (BIM) has proven to be a valuable technology in the fields of architecture, construction management, and maintenance management. However, its full implementation in structural engineering remains unfulfilled due to the persistent use of outdated design methods. Insufficient automation in the [...] Read more.
Building information modeling (BIM) has proven to be a valuable technology in the fields of architecture, construction management, and maintenance management. However, its full implementation in structural engineering remains unfulfilled due to the persistent use of outdated design methods. Insufficient automation in the design process could lead to structural defects, construction rework, and structural clashes, each of which can have significant financial implications. Given the inherent complexity of large-scale construction projects, manual structural design and detailing are challenging tasks and are prone to human errors. This paper presents a novel BIM framework that leverages BIM, Industry Foundation Classes (IFC), Python scripting, the IfcOpenShell library, and Octave programming to automate the design of reinforced concrete (RC) slabs, benefiting design professionals and contractors by integrating automated processes into project workflows. The framework achieved a 40% reduction in design time and a 25% decrease in human errors, as demonstrated through case studies. In this study, a 3D structural model in BIM software is firstly created, extracting slab geometrical data that are linked to Microsoft (MS) Excel/.csv and Octave spreadsheets via Python and IfcOpenShell. Midspan and end span moment coefficients and floor perimeter data following Indian standards are then gathered in Octave, and this information is further processed with Python scripts. Octave programming is used to determine the most accurate, reliable, and economical design for the slab and its detailing. This design information is then pushed back to BIM software via FreeCAD using Python coding, which can be used to develop bar bending scheduling and 2D drawings of the reinforcement details. The proposed framework is validated through case studies, demonstrating its effectiveness in reducing design time, minimizing human errors, and improving overall project efficiency. The core finding of this research is an automated approach that offers a cost-effective and accurate solution to the limitations of traditional RC slab design, addressing structural errors and reducing rework through seamless BIM integration. This research presents a novel contribution to the integration of structural design, construction processes, and operational aspects within BIM. The findings highlight the potential for further advancements in BIM adoption, particularly in addressing the lag in structural engineering applications compared to architecture. Full article
(This article belongs to the Section Construction Management, and Computers & Digitization)
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15 pages, 4664 KiB  
Article
An Automated Hierarchy Method to Improve History Record Accessibility in Text-to-Image Generative AI
by Hui-Jun Kim, Jae-Seong Park, Young-Mi Choi and Sung-Hee Kim
Appl. Sci. 2025, 15(3), 1119; https://doi.org/10.3390/app15031119 (registering DOI) - 23 Jan 2025
Abstract
This study aims to enhance access to historical records by improving the efficiency of record retrieval in generative AI, which is increasingly utilized across various fields for generating visual content and gaining inspiration due to its ease of use. Currently, most generative AIs, [...] Read more.
This study aims to enhance access to historical records by improving the efficiency of record retrieval in generative AI, which is increasingly utilized across various fields for generating visual content and gaining inspiration due to its ease of use. Currently, most generative AIs, such as Dall-E and Midjourney, employ conversational user interfaces (CUIs) for content creation and record retrieval. While CUIs facilitate natural interactions between complex AI models and users by making the creation process straightforward, they have limitations when it comes to navigating past records. Specifically, CUIs require numerous interactions, and users must sift through unnecessary information to find desired records, a challenge that intensifies as the volume of information grows. To address these limitations, we propose an automatic hierarchy method. This method, considering the modality characteristics of text-to-image applications, is implemented with two approaches: vision-based (output images) and prompt-based (input text) approaches. To validate the effectiveness of the automatic hierarchy method and assess the impact of these two approaches on users, we conducted a user study with 12 participants. The results indicated that the automatic hierarchy method enables more efficient record retrieval than traditional CUIs, and user preferences between the two approaches varied depending on their work patterns. This study contributes to overcoming the limitations of linear record retrieval in existing CUI systems through the development of an automatic hierarchy method. It also enhances record retrieval accessibility, which is essential for generative AI to function as an effective tool, and suggests future directions for research in this area. Full article
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34 pages, 7894 KiB  
Review
Comprehensive Review of Bearing Currents in Electrical Machines: Mechanisms, Impacts, and Mitigation Techniques
by Tianyi Pei, Hengliang Zhang, Wei Hua and Fengyu Zhang
Energies 2025, 18(3), 517; https://doi.org/10.3390/en18030517 (registering DOI) - 23 Jan 2025
Abstract
The present paper deals with a review on bearing currents in electrical machines, with major emphasis on mechanisms, impacts, and mitigation strategies. High-frequency common-mode voltages from the inverter-driven system have been found to be the main reason for bearing current leading to motor [...] Read more.
The present paper deals with a review on bearing currents in electrical machines, with major emphasis on mechanisms, impacts, and mitigation strategies. High-frequency common-mode voltages from the inverter-driven system have been found to be the main reason for bearing current leading to motor bearing degradation and eventual failure. This paper deals with bearing currents—electrical discharge machining (EDM) currents, circulating bearing currents, and rotor-to-ground bearing currents—and the various methods of their generation and effects that are harmful to the bearings and lubricants of a motor. Mitigation techniques, among which the following have been taken into account, are studied in this context: the optimization of PWM modulation, and the use of shaft grounding brushes, insulated bearings, and passive or active filters. Finally, advantages, limitations, and implementation challenges are discussed. A review comparing three-phase and dual three-phase inverters showed that, due to the increased degree of freedom in modulation strategies, it is possible to eliminate common-mode voltages through active modulation techniques. Such added flexibility will reduce the risk of bearing currents effectively. It also highlights future research directions in bearing current suppression, including the development of multi-phase motor systems, real-time monitoring technologies with artificial intelligence, and the use of new insulation materials for the enhancement of bearing reliability. The results obtained should guide future research and engineering practices in suppressing bearing currents to improve motor durability with high performance. Full article
(This article belongs to the Section F1: Electrical Power System)
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22 pages, 1174 KiB  
Perspective
Trends in Snapshot Spectral Imaging: Systems, Processing, and Quality
by Jean-Baptiste Thomas, Pierre-Jean Lapray and Steven Le Moan
Sensors 2025, 25(3), 675; https://doi.org/10.3390/s25030675 (registering DOI) - 23 Jan 2025
Abstract
Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the [...] Read more.
Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the expense of the spatio-spectral resolution, allowing for the observation of temporal events. Designing, realising, and deploying such technologies is yet challenging, particularly due to the lack of clear, user-meaningful quality criteria across diverse applications, sensor types, and workflows. Key research gaps include optimising raw image processing from snapshot spectral imagers and assessing spectral image and video quality in ways valuable to end-users, manufacturers, and developers. This paper identifies several challenges and current opportunities. It proposes considering them jointly and suggests creating a new unified snapshot spectral imaging paradigm that would combine new systems and standards, new algorithms, new cost functions, and quality indices. Full article
(This article belongs to the Collection Advances in Spectroscopy and Spectral Imaging)
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5 pages, 163 KiB  
Editorial
Fractional-Order Complex Systems: Advanced Control, Intelligent Estimation and Reinforcement Learning Image-Processing Algorithms
by Jin-Xi Zhang, Xuefeng Zhang, Driss Boutat and Da-Yan Liu
Fractal Fract. 2025, 9(2), 67; https://doi.org/10.3390/fractalfract9020067 (registering DOI) - 23 Jan 2025
Abstract
In this Special Issue on “Applications of Fractional Operators in Image Processing and Stability of Control Systems”, more than 20 high-quality papers have been published [...] Full article
21 pages, 8608 KiB  
Article
Analysis of Cardiac Arrhythmias Based on ResNet-ICBAM-2DCNN Dual-Channel Feature Fusion
by Chuanjiang Wang, Junhao Ma, Guohui Wei and Xiujuan Sun
Sensors 2025, 25(3), 661; https://doi.org/10.3390/s25030661 - 23 Jan 2025
Viewed by 81
Abstract
Cardiovascular disease (CVD) poses a significant challenge to global health, with cardiac arrhythmia representing one of its most prevalent manifestations. The timely and precise classification of arrhythmias is critical for the effective management of CVD. This study introduces an innovative approach to enhancing [...] Read more.
Cardiovascular disease (CVD) poses a significant challenge to global health, with cardiac arrhythmia representing one of its most prevalent manifestations. The timely and precise classification of arrhythmias is critical for the effective management of CVD. This study introduces an innovative approach to enhancing arrhythmia classification accuracy through advanced Electrocardiogram (ECG) signal processing. We propose a dual-channel feature fusion strategy designed to enhance the precision and objectivity of ECG analysis. Initially, we apply an Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and enhanced wavelet thresholding for robust noise reduction. Subsequently, in the primary channel, region of interest features are emphasized using a ResNet-ICBAM network model for feature extraction. In parallel, the secondary channel transforms 1D ECG signals into Gram angular difference field (GADF), Markov transition field (MTF), and recurrence plot (RP) representations, which are then subjected to two-dimensional convolutional neural network (2D-CNN) feature extraction. Post-extraction, the features from both channels are fused and classified. When evaluated on the MIT-BIH database, our method achieves a classification accuracy of 97.80%. Compared to other methods, our approach of two-channel feature fusion has a significant improvement in overall performance by adding a 2D convolutional network. This methodology represents a substantial advancement in ECG signal processing, offering significant potential for clinical applications and improving patient care efficiency and accuracy. Full article
(This article belongs to the Section Biomedical Sensors)
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19 pages, 5153 KiB  
Article
Aluminum Reservoir Welding Surface Defect Detection Method Based on Three-Dimensional Vision
by Hanjie Huang, Bin Zhou, Songxiao Cao, Tao Song, Zhipeng Xu and Qing Jiang
Sensors 2025, 25(3), 664; https://doi.org/10.3390/s25030664 - 23 Jan 2025
Viewed by 101
Abstract
Welding is an important process in the production of aluminum reservoirs for motor vehicles. The welding quality affects product performance. However, rapid and accurate detection of weld surface defects remains a huge challenge in the field of industrial automation. To address this problem, [...] Read more.
Welding is an important process in the production of aluminum reservoirs for motor vehicles. The welding quality affects product performance. However, rapid and accurate detection of weld surface defects remains a huge challenge in the field of industrial automation. To address this problem, we proposed a 3D vision-based aluminum reservoir welding surface defect detection method. First of all, a scanning system based on laser line scanning camera was constructed to acquire the point cloud data of weld seams on the aluminum reservoir surface. Next, a planar correction algorithm was used to adjust the slope of the contour line according to the slope of the contour line in order to minimize the effect of systematic disturbances when acquiring weld data. Then, the surface features of the weld, including curvature and normal vector direction, were extracted to extract holes, craters, and undercut defects. For better extraction of the defect, a double-aligned template matching method was used to ensure comprehensive extraction and measurement of defect areas. Finally, the detected defects were categorized according to their morphology. Experimental results show that the proposed method using 3D laser scanning data can detect and classify typical welding defects with an accuracy of more than 97.1%. Furthermore, different types of defects, including holes, undercuts, and craters, can also be accurately detected with precision 98.9%. Full article
(This article belongs to the Collection 3D Imaging and Sensing System)
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16 pages, 3643 KiB  
Article
Utility of Magnetic Bead-Based Automated DNA Extraction to Improve Chagas Disease Molecular Diagnosis
by Priscila S. G. Farani, Jacqueline Lopez, Amanda Faier-Pereira, Alejandro Marcel Hasslocher-Moreno, Igor C. Almeida and Otacilio C. Moreira
Int. J. Mol. Sci. 2025, 26(3), 937; https://doi.org/10.3390/ijms26030937 (registering DOI) - 23 Jan 2025
Viewed by 117
Abstract
Chagas disease, caused by Trypanosoma cruzi, remains a significant global health challenge, particularly in the molecular diagnostics of low parasitemia during the chronic phase. This highlights the critical need for enhanced diagnostic methodologies. In response, this study evaluates the effectiveness of an [...] Read more.
Chagas disease, caused by Trypanosoma cruzi, remains a significant global health challenge, particularly in the molecular diagnostics of low parasitemia during the chronic phase. This highlights the critical need for enhanced diagnostic methodologies. In response, this study evaluates the effectiveness of an automated magnetic beads-based DNA extraction method in improving the molecular diagnosis of Chagas disease compared to the traditional silica column-based extraction. Accordingly, this research seeks to enhance the DNA yield, purity, and sensitivity of real-time PCR (qPCR) assays for detecting T. cruzi satDNA. Blood samples spiked with guanidine–EDTA solution and varying concentrations of T. cruzi were used to compare the two extraction methods. The results indicated that the magnetic bead-based method outperformed the silica column in terms of DNA concentration, purity, and earlier detection of T. cruzi satDNA. Although both methods had similar limits of detection at a 95% confidence interval, the magnetic bead-based approach demonstrated higher sensitivity and reproducibility, particularly in low-parasitemia samples. The findings suggest that the magnetic beads-based DNA extraction method offers a more reliable, faster, and more sensitive alternative for diagnosing chronic Chagas disease, potentially improving clinical outcomes by enabling more accurate and earlier parasite detection. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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14 pages, 2762 KiB  
Article
Wave Motion Response Analysis of Flip-Type Ocean Aquaculture Platforms Based on AQWA
by Hongling Qin, Li Peng, Zhiyuan Wang, Siqi Wu, Wei He, Yuanping Yang, Jian Li and Hao Zhang
J. Mar. Sci. Eng. 2025, 13(2), 211; https://doi.org/10.3390/jmse13020211 - 23 Jan 2025
Viewed by 112
Abstract
The stability of deep-sea aquaculture equipment under extreme sea conditions such as typhoons directly affects the safety and operational reliability of the aquaculture platform, which in turn affects the economic benefits of fish farming. Therefore, it is particularly important to systematically analyze the [...] Read more.
The stability of deep-sea aquaculture equipment under extreme sea conditions such as typhoons directly affects the safety and operational reliability of the aquaculture platform, which in turn affects the economic benefits of fish farming. Therefore, it is particularly important to systematically analyze the hydrodynamic response of aquaculture facilities using numerical methods. This paper employs the hydrodynamic analysis software AQWA, integrating the boundary element method of three-dimensional potential flow theory with the Morison equation, to conduct hydrodynamic research on a flip-type aquaculture platform. The calculations include the platform’s amplitude response operators (RAOs), added mass, as well as motion responses and mooring line tensions under extreme sea conditions. The results indicate that the platform’s sway, surge, and heave motions are highly sensitive to wave frequency in the low-frequency range, with a significant resonance phenomenon occurring at a wave frequency of 0.84 Hz. The main wind and wave responses of the platform manifest as surge and roll motions. To address this issue, it is recommended to add additional anchor chains on the short sides of the platform to effectively reduce the amplitude of surge and roll motions. Furthermore, under extreme sea conditions when the platform faces the windward waves on the short side, its motion response frequency is lower than when facing the windward waves on the long side, but the difference in response amplitude between the two conditions is small. Full article
(This article belongs to the Section Coastal Engineering)
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13 pages, 2669 KiB  
Article
Evaluation of Grading Estrogen Receptors in Breast Cancer Using Fully Automated Rapid Immunohistochemistry Based on Alternating-Current Electric Field Technology
by Chiaki Kudo, Kaori Terata, Hiroshi Nanjo, Kyoko Nomura, Yuko Hiroshima, Eriko Takahashi, Ayuko Yamaguchi, Hikari Konno, Masaaki Onji, Yuki Wakamatsu, Yoshihiko Kimura, Shinogu Takashima, Akiyuki Wakita, Yusuke Sato, Yoshihiro Minamiya and Kazuhiro Imai
Cancers 2025, 17(3), 363; https://doi.org/10.3390/cancers17030363 - 23 Jan 2025
Viewed by 131
Abstract
Background: Immunohistochemistry (IHC) is crucial for determining cancer treatments. We previously developed a rapid IHC method and have now developed a fully automated rapid IHC stainer (R-Auto). This study aimed to evaluate the clinical reliability of the R-Auto protocol for staining estrogen receptors [...] Read more.
Background: Immunohistochemistry (IHC) is crucial for determining cancer treatments. We previously developed a rapid IHC method and have now developed a fully automated rapid IHC stainer (R-Auto). This study aimed to evaluate the clinical reliability of the R-Auto protocol for staining estrogen receptors (ERs) in breast cancer specimens and evaluate the staining performance. Methods: Between January 2015 and June 2020, 188 surgical specimens collected from breast cancer patients treated at our hospital were evaluated via ER staining using R-Auto, conventional manual IHC, and a commercial autostainer. The specimens were scored using Allred scores, after which the staining results were compared between R-Auto and conventional IHC or the commercial autostainer. Weighted kappa coefficients and AC1 statistics were used to assess the agreement between the methods. Results: The AC1 statistic for comparison between R-Auto and conventional IHC was 0.9490 (0.9139–0.9841), with a 95.7% agreement rate, and that for comparison between R-Auto and the commercial autostainer was 0.9095 (0.8620–0.9570), with a 92.6% agreement. There was, thus, substantial agreement between R-Auto and both conventional IHC and the commercial autostainer. However, R-Auto shortened the time required for IHC from 209 min with conventional IHC to 121 min. Conclusions: R-Auto enables a good staining performance in a shorter time with less effort. Full article
(This article belongs to the Special Issue Advances in the Molecular Biology and Pathology of Breast Cancer)
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13 pages, 708 KiB  
Article
Enhancing Decision-Making and Data Management in Healthcare: A Hybrid Ensemble Learning and Blockchain Approach
by Geetanjali Rathee and Razi Iqbal
Technologies 2025, 13(2), 43; https://doi.org/10.3390/technologies13020043 - 23 Jan 2025
Viewed by 191
Abstract
Currently, big data is considered one of the most significant areas of research and development. The advancement in technologies along with the involvement of intelligent and automated devices in each field of development leads to huge generation, analysis, and the recording of information [...] Read more.
Currently, big data is considered one of the most significant areas of research and development. The advancement in technologies along with the involvement of intelligent and automated devices in each field of development leads to huge generation, analysis, and the recording of information in the network. Though a number of schemes have been proposed for providing accurate decision-making while analyzing the records, however, the existing methods lead to massive delays and difficulty in the management of stored information. Furthermore, the excessive delays in information processing pose a critical challenge to making accurate decisions in the context of big data. The aim of this paper is to propose an effective approach for accurate decision-making and analysis of the vast volumes of data generated by intelligent devices in the healthcare sector. The processed and managed records can be stored and accessed in a systematic and efficient manner. The proposed mechanism uses the hybrid of ensemble learning along with blockchain for fast and continuous recording and surveillance of information. The recorded information is analyzed using several existing methods focusing on various measurement outcomes. The results of the proposed technique are compared with existing techniques through various experiments that demonstrate the efficiency and accuracy of this technique. Full article
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