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14th International Conference on Educational and Information technology, ICEIT 2025

作者： Jin-Gang, Jiang Jiang-Long, Xiong Ya-Ping, Wang Kai-Rui, Wang Tao, Shen Yudong, Bao National Experimental Teaching Demonstration Center for Mechanical Engineering Experiment and Practice Harbin University of Science and Technology Harbin China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin China School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin China

ISBN: (纸本)9798331540883

Aiming to address the current problems in robot training teaching, this paper focuses on the construction of industry-teaching-innovation cases for robot training under the integration of virtuality and reality, such as the disconnection between training content and industry practice, delays in digital transformation, and the lack of training resources. Relying on the intelligent manufacturing industry academy (IMIA), the teaching model integrates virtual simulation training with practical operation to enhance students' practical skills and innovative abilities. The study introduces complex technical challenges faced by enterprises in production, combining a dual-mentor system and a collaborative resource-sharing mechanism between school and enterprises. This ensures that students can master key skills required by enterprises during training, while innovation and entrepreneurship education is integrated throughout the whole training process to stimulate students' creative thinking and entrepreneurial mindset. © 2025 IEEE.

关键词： Students

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Pneumatic Piping Leakage Flow Rate Classification Based on Transfer Learning

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IEEE Sensors Journal 2025年第10期25卷 17811-17822页

作者： Shi, Yan Chang, Jiaqi Li, Lei Ma, Yushan Wang, Yixuan Xu, Shaofeng Niu, Yanxia Ma, Dai Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Liupanshan Laboratory Yinchuan750000 China Beihang University Engineering Practice and Innovation Center Beijing100191 China Ningxia University School of Mechanical Engineering Yinchuan750021 China Zhejiang Easun Pneumatic Science and Technology Company Ltd. Ningbo315000 China

Leakage is the most common form of malfunction in pneumatic systems. When leakage occurs, the escaping gas creates a cooler area near the leakage point. Thermal imaging can visually capture these temperature variations, allowing assess the severity of the pneumatic system’s leakage. However, the accuracy of thermal imaging is often affected by varying background temperatures due to differing image feature distributions. To solve this problem, this article introduces a framework that combines key area extraction with discriminative feature transfer learning (KDFTL). First, to meticulously extract the core area of the leakage from the expanse of the image environment, the infrared images from both the source and target domains (TDs) are fed into the key area extraction (KAE) section. Subsequently, a distribution difference index is designed on class centers, and the inter class separability and intra class compactness are evaluated. Then, to make the features of samples with the same leakage rate at different temperatures similar for classification, the feature transfer matrix is calculated and the transferred features are obtained and classified. Finally, extensive experiments on the dataset of thermal images for pneumatic leakage show that KDFTL delivered an average classification accuracy of 72.59%, which is a significant improvement compared to 44.07% transfer joint matching (TJM). © 2001-2012 IEEE.

关键词： Thermography (imaging)

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The Influence of WC Content on the Microstructure and Wear Resistance of Laser Cladded WC/Co-Ni Matrix Composite Coating

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Lasers in engineering 2025年第4-6期59卷 259-281页

作者： He, W. Chen, X. School of Engineering practice teaching Department Liaoning University of Technology Liaoning Jinzhou121001 China

A WC/Co-Ni composite coating was prepared on the surface of high-speed steel by laser cladding technology. The effects of WC content on the microstructure, phase composition, microhardness and wear resistance of the coating were comparatively analyzed. The results showed that the surface of WC/Co-Ni composite coating was flat and uniform, with no obvious defects such as pores and cracks, and a benign bond was formed between the coatings. The cladding layer is dominated by WC, M12C (Fe6W6C, Co6W6C, Mo6Co6C) eutectic structure and γ-(Ni, Fe) phase. When the content of WC was 90%, the distribution of WC particles was uneven, there were more voids and microcracks in the surrounding tissue, and local segregation appeared in the coating. When WC content was 70%-80%, the precipitated tissue distribution was uniform, and Cr23C6, (Fe, Co, Mn)2C and other phases were added, which enhanced the hardness and wear resistance of the coating. When WC content 0.2 to 1066.58HV0.2, a decrease of 12.67%, while the hardness distribution of the coating tended to be uniform, and the overall standard deviation of hardness decreased from 153.26HV0.2 to 25.61HV0.2, a decrease of 83.29%;Under the same friction condition, the wear amount of the cladding layer decreases first and then increases with the decrease of WC. When WC content is 80%, the wear resistance of the coating reaches the best. The wear mechanism of the cladding layer is mainly abrasive wear, and the adhesion wear area gradually expands with the decrease of WC. ©2025 Old City Publishing, Inc.

关键词： Microhardness

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Characterization of Photonic Temperature Sensors by Comparative Human Body Measurements Using Waveguide Bragg Grating and Microring Resonator-Based Sensors

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IEEE Sensors Journal 2025年第9期25卷 15005-15012页

作者： Li, Xiaolin Li, Hongqiang Xie, Fanglin Han, Ming Zhang, Lizhen Zhang, Shanshan Li, Enbang Tiangong University Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems School of Electronics and Information Engineering Tianjin300387 China Tiangong University Shaoxing Keqiao Institute Zhejiang Shaoxing312030 China Tiangong University Engineering Teaching Practice Training Center Tianjin300387 China Nankai University Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Institute of Modern Optics Tianjin300071 China University of Wollongong Centre for Medical Radiation Physics School of Physics Faculty of Engineering and Information Sciences WollongongNSW2522 Australia

Human body temperature is an important indicator of physical health. Waveguide Bragg grating (WBG)- and microring resonator (MRR)-based polymer optical waveguide temperature sensors provide alternative methods for monitoring the human body temperature. In this study, optical waveguide temperature sensors, with a combination of polymethylmethacrylate (PMMA) and polydimethylsiloxane (PDMS) for the formation of waveguide structures, are designed and fabricated via a polymer-based fabrication process to achieve real-time temperature measurements in situ. We experimentally characterized and compared the sensor thermal properties within the temperature range of 35 °C–40 °C. Based on the results from our study, the WBG and MRR temperature sensors had high-sensitivity properties. The temperature sensitivity coefficient of the WBG temperature sensor was −177.6 pm/°C and that of the MRR temperature sensor was −0.03035 mW/°C. The error of these two temperature sensors did not exceed 0.1 °C. These sensors show great promise as basic sensing elements in optical waveguide sensor applications for the early detection and monitoring of heat-related illnesses. © 2001-2012 IEEE.

关键词： Optical waveguides

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Construction of Industry-Teaching-Innovation Cases for Robot Training under the Integration of Virtuality and Reality

Construction of Industry-Teaching-Innovation Cases for Robot...

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International Conference on Educational and Information technology (ICEIT)

作者： Jiang Jin-gang Xiong Jiang-long Wang Ya-ping Wang Kai-rui Shen Tao Bao Yudong National Experimental Teaching Demonstration Center for Mechanical Engineering Experiment and Practice Harbin University of Science and Technology Harbin China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin China School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin China

ISBN: (数字)9798331540883

ISBN: (纸本)9798331540890

关键词： Training Manufacturing industries Technological innovation Service robots Digital transformation Entrepreneurship Production Delays Manufacturing Problem-solving

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Energy Consumption Optimization using Big Data Analytics for Smart Grid Management 5

Energy Consumption Optimization using Big Data Analytics for...

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5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Devi, K. Sumithra Contractor, Dipenkumar Deepa, V. Lakshmi, T.K. Santhikala, M. Mounika, Kamati Kcg College of Technology Department of Computer Science and Engineering Chennai India Government Engineering College Department of Computer Engineering Dahod India Sri Ramakrishna College of Arts and Science Department of Information Technology Tamil Nadu Coimbatore India Malla Reddy University Department of Computer Science and Engineering Telangana Hyderabad India Ramco Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Rajapalayam India Mb School of Pharmaceutical Sciences Mohan Babu University Department of Pharmacy Practice Andhra Pradesh Tirupathi India

ISBN: (纸本)9798331522100

The application of big data analytics to improve energy usage efficiency in smart grids has been prompted by the rising need for power management. Adding to the above, it poses a big data solution for demand prediction, load consolidation, and fault diagnosis. Establishing the new and state-of-the-art innovative LSTM network that was employed in the forecast yielded a higher demand forecast accuracy of 94.2% compared to the previous systems. The load balancing index achieved 92% with an accuracy of 93.7% in fault detection, thus minimizing maintenance cost by 14.7% while improving grid reliability. The proposed model was found to give better results than previous conventional machine learning techniques and even modern ones which are more complex, especially for an ever-changing grid environment. Overall, these findings show the promise of big data solutions for handling the challenges of the contemporary smart grid while improving its efficiency through energy optimization. Consequently, this work lays a framework for subsequent studies on the remaining applications of advanced analytics in energy management systems. © 2025 IEEE.

关键词： Smart power grids

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Research on supply chain intelligent bid evaluation management system based on AHP-TOPSIS 24

Research on supply chain intelligent bid evaluation manageme...

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5th International Conference on Computer Science and Management technology, ICCSMT 2024

作者： Yang, Zheng Jin, Hao Chen, Shuai Sun, Jinzhou Tang, Fei Chen, Mo E-commerce Co. Ltd. Fujian Xiamen China Wuhan Hangke Logistics Co.Ltd. Hubei Wuhan China School of Information Management Wuhan University Hubei Wuhan China School of Electrical and Automation Wuhan University Hubei Wuhan China Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network Hubei Wuhan China College Students Engineering Training and Innovation Practice Center Hubei Wuhan China

ISBN: (纸本)9798400709999

The intelligent transformation of the bid evaluation process in supply chains has become a prominent area of *** paper analyzes the functional framework of the intelligent bid evaluation management system for supply chains and ranks the importance of functions involved in the evaluation ***, the paper examines the challenges faced by existing supply chain platforms during their intelligent *** then proposes an evaluation system for the functional importance of bid evaluation, utilizing the Analytic Hierarchy Process (AHP) and TOPSIS *** converting subjective judgments into objective data, this study comprehensively analyzes three key factors in the bid evaluation process: bid integrity, risk level, and evaluation *** weights are determined based on expert assessments, leading to the optimization and ranking of intelligent bid evaluation *** results reveal that tender integrity and supplier risk are critical in the evaluation process, with functions such as core term extraction, integrity detection, and format error identification playing essential *** research not only offers scientific decision support for the development of intelligent bid evaluation management systems in the supply chain but also provides a theoretical foundation for advancing supply chain intelligence. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： AHP

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Acceptability and usability of Drugs4dent®, a dental medicines decision tool – a pilot study

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BMC Oral Health 2025年第1期25卷 1-10页

作者： Teoh, Leanne Biezen, Ruby Taylor, Marietta Sinnott, Richard O. McCullough, Michael J. Melbourne Dental School University of Melbourne Carlton Australia Department of General Practice and Primary Care University of Melbourne Melbourne Australia Melbourne eResearch Group Faculty of Engineering and Information Technology University of Melbourne Melbourne Australia

While drugs have a limited role in the management of dental presentations, Australian dentists have high rates of inappropriate prescribing of antibiotics. There is also a lack of relevant drug resources for dentists in Australia. Our team developed Drugs4dent®, a medicines decision support tool, that provides dentists with relevant drug knowledge, assists with appropriate prescribing and provides safety checks to reduce prescribing errors. The aim of this pilot study was to improve Drugs4dent® with focus groups of dentists, and assess the acceptability, usability, and user experience, of Drugs4dent®. Focus groups of ten dentists were established to inform the improvement of Drugs4dent®. Acceptability and usability testing of Drugs4dent® was then undertaken with a further ten dentists using interviews and a survey. The survey was based on the Framework for Acceptability and System Usability Scale. Inductive thematic analysis was undertaken using Nvivo for the focus groups and interviews, and descriptive statistics for analysis of survey results. Dentists from the focus group and interviews found the content of Drugs4dent® acceptable and useful for dentistry, recognising that similar drug information is currently not available. The majority agreed that Drugs4dent® would improve their ability to prescribe according to guidance. Participants reported Drugs4dent® was intuitive, and information was easy to locate. Most dentists preferred Drugs4dent® integrated with their dental practice software. In the absence of this functionality, they preferred Drugs4dent® as a standalone resource, without needing to input patient data. Drugs4dent® was subsequently commercialised with MIMS Australia, to create the decision support tool: MIMS Drugs4dent®. Drugs4dent® is the first dental medicines decision tool in Australia. The high acceptability and usability of the tool, and subsequent commercialisation indicates that MIMS Drugs4dent® has substantial promise for the future, and can

关键词： Clinical decision Dental decision tool Dental prescribing Digital health Prescribing tool

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Effects of Different Fertilization Treatments on the Growth,Quality,and Microbial Community Structure of Grona styracifolia

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Phyton-International Journal of Experimental Botany 2025年第3期94卷 843-860页

作者： Bingbing Zhang Minghao Li Xiaoli Huang Siqi Zheng Guorong Lai Quan Yang Xiaomin Tang School of Chinese Materia Medica Guangdong Pharmaceutical UniversityGuangzhou510006China Guangdong Provincial Research Center on Good Agricultural Practice&Comprehensive Agricultural Development Engineering Technology of Cantonese Medicinal Materials Guangzhou510006China Comprehensive Experimental Station of Guangzhou Chinese Material MedicaChina Agriculture Research System(CARS-21-16)Guangzhou510006China Key Laboratory of Production&Development of Cantonese Medicinal Materials State Administration of Traditional Chinese MedicineGuangzhou510006China

Fertilization is essential for high yield and quality in Chinese *** styracifolia(Osbeck)***,a distinctive medicinal plant in the Lingnan region,currently encounters cultivation issues stemming from the overuse of chemical *** organic and microbial fertilizers presents a sustainable solution for its cultivation *** study compared a no-fertilization control group with eight treatment groups using various concentrations of compound,organic,compound microbial,and Bacillus amyloliquefaciens fertilizers to evaluate their effects on *** and soil microbial *** results demonstrated that the different fertilization treatments significantly enhanced plant growth and quality of ***,while also increasing the activity of soil enzymes such as urease,invertase,and cellulase,as well as the levels of effective soil *** affiliation function analysis demonstrated that applying Bacillus amyloliquefaciens fertilizer(15 g/kg)exhibited optimal performance in enhancing the growth of *** and improving soil fertility *** sequencing of the soil indicated that under the application of Bacillus amyloliquefaciens fertilizer(15 g/kg),the relative abundance of Actinobacteria and Ascomycota increased significantly by 27.42%and 74.91%,respectively(p<0.05).The application of microbial-based fertilizers significantly enriched the abundance of ***,LEfSe analysis identified distinct microbial biomarkers associated with different ***,redundancy analysis identified Invertase and available potassium(AK)as the primary drivers of soil bacterial and fungal community structures,*** study demonstrated that the application of Bacillus amyloliquefaciens fertilizer(15 g/kg)significantly enhanced soil fertility and restructured microbial *** improvements led to increased yield and quality of ***,providing a s

关键词： Grona styracifolia(Osbeck)H.Ohashi growth active ingredients enzyme activity soil microorganisms

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Predictive nomogram for early detection of invasive fungal disease deterioration --- a 10-year retrospective cohort study

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BMC Infectious Diseases 2025年第1期25卷 1-14页

作者： Wang, Wei Li, Yan Wang, Hua Du, Yumeng Cheng, Mengyuan Tang, Jinyan Wu, Mingliang Chen, Chaomin Lv, Qingwen Cheng, Weibin Institute for Healthcare Artificial Intelligence Application The Affiliated Guangdong Second Provincial General Hospital of Jinan University Guangzhou 510317 China School of Biomedical Sciences and Engineering South China University of Technology Guangzhou International Campus Guangzhou 511442 China Department of General Medicine The Affiliated Yongchuan Hospital of Chongqing Medical University Chongqing 402160 China General Practice Medicine Zhujiang Hospital Southern Medical University Guangzhou 510282 China Department of Intensive Care Medicine Zhujiang Hospital Southern Medical University Guangzhou 510282 China School of Biomedical Engineering Southern Medical University Guangzhou 510515 China Department of Information Zhujiang Hospital Southern Medical University Guangzhou 510282 China School of Data Science City University of Hong Kong Hong Kong

Background: Invasive fungal disease (IFD) is characterized by its capacity to rapidly escalate to life-threatening conditions, even when patients are hospitalized. However, the precise prognostic significance of baseline clinical characteristics related to the progression outcome of IFD remains elusive. Methods: A retrospective cohort study spanning a duration of 10 years was conducted at two prominent tertiary teaching hospitals in Southern China. Patients with proven IFD were queried and divided into serious and non-serious groups based on the disease deterioration. To establish robust predictive models, patients from the first hospital were randomly assigned to either a training set or an internal validation set, while patients from the second hospital constituted an external test set. To analyze the potential predictors of IFD deterioration and identify independent predictors, the study employed the least absolute shrinkage and selection operator (LASSO) method in conjunction with binary logistic regressions. Based on the outcomes of this analysis, a predictive nomogram was constructed. The performance of the developed model was thoroughly evaluated using the training set, internal validation set, and external test set. Results: A total of 480 cases from the first hospital and 256 cases from the second hospital were included in the study. Among the 480 patients, 81 cases (16.9%) experienced deterioration, and out of those, 45 (55.6%) cases resulted in mortality. Seven independent predictors were identified and utilized to construct a predictive nomogram. The nomogram exhibited excellent predictive performance in all three sets: the training set, internal validation set, and external test set. The area under the receiver operating characteristic curve (AUC) for the training set was 0.88, for the internal validation set was 0.91, and for the external test set was 0.90. The Hosmer–Lemeshow test and Brier score indicated a high goodness of fit for the model. Further

关键词： Independent predictor Invasive fungal disease Nomogram Prediction probability

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