检索结果-内蒙古大学图书馆

Lightweight Ethylene-Vinyl Acetate Copolymer/Low-density Polyethylene/Carbon Nanotube Foams via Supercritical Carbon Dioxide Foaming for Piezoresistive Sensors

引用

Chinese Journal of Polymer Science (English Edition) 2025年 1-14页

作者： Hou, Hao-Hao He, Xin Ma, Hui Zhou, Hong-Fu Wen, Bian-Ying Wang, Xiang-Dong Deng, Ya-Feng Key Laboratory of Processing and Application of Polymeric Foams of China National Light Industry Council School of Light Industry Science and Engineering Beijing Technology and Business University Beijing100048 China School of Computer and Artificial Intelligence Beijing Technology and Business University Beijing100048 China

Flexible polymer-based foam sensors have significant potential for application in wearable electronics and motion monitoring. However, these prospects are hindered by the complex and unenvironmentally friendly manufacturing processes. In this study, we employed melt blending and supercritical carbon dioxide foaming to fabricate an ethylene-vinyl acetate copolymer (EVA)/low-density polyethylene (LDPE)/carbon nanotube (CNT) piezoresistive foam sensor. The cross-linking agent bis(tert-butyldioxyisopropyl) benzene and the conductive filler CNT were incorporated into the EVA/LDPE composite, successfully achieving a chemically cross-linked and physically entangled composite structure that significantly enhanced the storage modulus and complex viscosity. Additionally, the compressive strength of EVA/LDPE/CNT foam with 10 parts per hundred rubber (phr) CNT reached 1.37 MPa at 50% compression, marking a 340% increase compared to the 0.31 MPa of the CNT-free sample. Furthermore, the EVA/LDPE/CNT composite foams, which incorporated 10 phr CNT, were prepared under specific foaming conditions, resulting in an ultra-low density of 0.11 g/cm3 and a higher sensitivity, with a gauge factor of −2.3. The piezoresistive foam sensors developed in this work could accurately detect human motion, thereby expanding their applications in the field of piezoresistive foam sensors and providing an effective strategy for the advancement of high-performance piezoresistive foam sensors. © Chinese Chemical Society Institute of Chemistry, Chinese Academy of Sciences 2025.

关键词： Crosslinking

来源：评论

学校读者我要写书评

暂无评论

Reliable Communication in Opportunistic Network based on Trust: A Review 3

Reliable Communication in Opportunistic Network based on Tru...

引用

3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Ahmed, Mala Paul, Amrita Bose Prokash Goswami, Jyoti AEC Assam Science and Technology University Department of Computer Application Assam India

ISBN: (纸本)9798331523893

Communication plays a significant role in a network where the nodes get connected opportunistically. To establish reliable communication in such a network is very much challenging due to the intermittent node connectivity. Recent research work focuses on establishing trust relationship between the nodes for reliable communication in wireless networks. Generally trust of a node is calculated based on historical information or feedback given by other nodes that has previous communication with that particular node. This paper provides an overview of the trust models that are available in the literature and connote their issues and challenges for opportunistic network. The authors propose a trust based framework for reliable communication in opportunistic network. The framework signifies the importance of belief-trust for establishing reliable communication over the network. © 2025 IEEE.

关键词： Belief trust Direct trust Indirect trust Opportunistic network Recommender system Reliable communication Trust model

来源：评论

学校读者我要写书评

暂无评论

A Single-Loop Narrow-Band Force Rebalance Control Method with Temperature Self-Compensation for a MEMS Gyroscope 38

A Single-Loop Narrow-Band Force Rebalance Control Method wit...

引用

38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： He, Chunhua Xu, Yingyu Wu, Heng Huang, Qinwen Zhao, Qiancheng Yan, Guizhen Guangdong University of Technology School of Computer China Ceprei Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory China Guangdong University of Technology School of Automation China Peking University School of Integrated Circuits Beijing China National Key Lab of Micro/Nano Fabrication Technology Beijing China

ISBN: (纸本)9798331508890

This paper presents a novel single-loop narrow-band force rebalance control method with temperature self-compensation for a MEMS gyroscope. The narrow-bandwidth force rebalance control for the sense mode is achieved using a simple bandpass filter (BPF) and without modulation or demodulation. The center frequency of the BPF is adjusted automatically to match the resonant frequency of the sense mode. Meanwhile, its gain is tuned based on the real-time quality factor of the sense mode. Experimental results demonstrate that the bias drift of the gyroscope with self-compensation is reduced from 1320 deg/h to 16 deg/h, while the scale factor drift is reduced from 0.616 mV/deg/s to 0.075 mV/deg/s. © 2025 IEEE.

关键词： Gyroscopes

来源：评论

学校读者我要写书评

暂无评论

Enhanced Electrocardiogram Data Compression and Classification Using 2D Convolutional Neural Networks 5

Enhanced Electrocardiogram Data Compression and Classificati...

引用

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

作者： Yadav, Amrendra Singh Mehta, Preeti Mishra, Deepti Barik, Rabindra Kumar AVM-Indian Institute of Information Technology and Management Department of Computer Science and Engineering Gwalior India National Institutes of Technology Delhi Department of Computer Science and Engineering Delhi India Kiit Deemed to be University School of Economics and Commerce Bhubaneshwar India Kiit Deemed to be University School of Computer Application Bhubaneshwar India

ISBN: (纸本)9798331522100

The task of electrocardiogram (ECG) classification is a combination of data compression and classification of signals based on the patient's health. This paper introduces a novel technique for compressing electrocardiogram (ECG) images and utilizing these compressed images for accurate classification. We transform ECG signals into images and compress them to reduce their size while preserving classification accuracy significantly. Our approach employs a 2-dimensional Convolutional Neural Network (2-D CNN) model and achieves an impressive accuracy of 97% even after compressing the images by up to 76%. The proposed technique was tested on the widely-used MIT-BIH Arrhythmia Dataset, demonstrating its robustness and efficacy. Maintaining high classification accuracy despite significant image compression is crucial for efficient storage and transmission in resource-constrained environments. This method holds substantial potential for real-time monitoring and diagnosis in telemedicine applications, emphasizing the importance of our contribution to the field. © 2025 IEEE.

关键词： Electrocardiography

来源：评论

学校读者我要写书评

暂无评论

Identification of Key Genetic Drivers in Multidrug Resistance: A Co-Expression Network Analysis of Pseudomonas aeruginosa

Identification of Key Genetic Drivers in Multidrug Resistanc...

引用

2025 International Conference on Ambient Intelligence in Health Care, ICAIHC 2025

作者： Routray, Sweta Padma Mahapatra, Saswati Nayak, Debasish Swapnesh Kumar Subudhi, Enketeswara Swarnkar, Tripti University Centre for Biotechnology Bhubaneswar India University Department of Computer Application Bhubaneswar India Centurion University of Technology and Management Department of Computer Science and Engineering Bhubaneswar India National Institute of Technology Department of Computer Application Raipur India

ISBN: (纸本)9798331530259

Antimicrobial resistance (AMR) in Pseudomonas aeruginosa, a critical pathogen in healthcare-associated infections, demands new insights into underlying genetic mechanisms. This study aimed to identify key regulatory genes contributing to multidrug resistance (MDR) through a comprehensive analysis of gene expression in clinical isolates. RNA-Seq data from 246 clinical isolates of P. aeruginosa was analyzed using Weighted Gene Co-Expression Network Analysis (WGCNA) to construct co-expression networks. Modules of co-expressed genes were identified, and hub genes with high connectivity were selected, focusing on those within and across modules, including the largest module enriched with resistance-related genes. Pathway enrichment was performed using STRING and ShinyGO, highlighting key resistance-associated pathways. Pathway enrichment analysis of hub genes identified polA as a central player in DNA repair and replication processes, crucial for bacterial survival under antibiotic stress. In addition to polA, other highly connected hub genes, such as dnaB, tatC, and ppnK, were enriched in pathways including protein transport and mismatch repair. Within the turquoise module, hub genes like dnaA, uvrD, and gyrA were primarily involved in ATP-binding, ligase activity, and biosynthetic processes, essential for antibiotic resistance. Network analysis further emphasized the centrality of polA and its role in bridging multiple resistance pathways, highlighting its potential as a therapeutic target. This research highlights polA and other critical hub genes as key regulatory elements within the MDR networks of P. aeruginosa, playing essential roles in pathways vital for bacterial survival. The identification of these genes provides promising biomarkers and potential therapeutic targets to counteract MDR in clinical settings. © 2025 IEEE.

关键词： Transcription

来源：评论

学校读者我要写书评

暂无评论

Dual-head alternating attention-based adaptive convolutional framework for improving low-resource and imbalanced text classification

引用

Neural Computing and applications 2025年 1-21页

作者： Agbesi, Victor Kwaku Chen, Wenyu Hossin, Md Altab Ukwuoma, Chiagoziem C. School of Computer Science and Engineering University of Electronic Science and Technology of China No. 2006 Xiyuan Ave West Hi-Tech Zone Sichuan Chengdu China School of Innovation and Entrepreneurship Chengdu University No. 2025 Chengluo Avenue 610106 Sichuan Chengdu China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan Chengdu610059 China Sichuan Engineering Technology Research Center for Industrial Internet Intelligent Monitoring and Application Chengdu University of Technology Sichuan Chengdu610059 China

Low-resource imbalance texts pose significant challenges due to class imbalance, adversely affecting the performance of deep learning approaches. To address this issue, we propose a dual-head alternating attention-based adaptive convolutional framework with label embedding (AltXLM-AdaCLE), a novel framework designed for imbalanced text classification in low-resourced datasets. Our framework features a new alternating attention model, which combines a dual-head attention mechanism with a bidirectional long short-term memory network, facilitating dynamic filter generation that adapts to the input data’s characteristics and enhances the capture of relevant features and long-range dependencies. A key innovation in this study is the dual-head attention mechanism, which utilizes an alternating reading sequence to extract information from multiple document segments, thereby minimizing information loss and improving the understanding of complex relationships. Furthermore, we introduce a method for embedding class labels in a shared vector space with the text, allowing the model to leverage label information throughout the classification process, which is particularly beneficial for imbalanced datasets. Our framework also incorporates an adaptive convolutional layer that processes text features and label embeddings, generating more representative features of the underlying data distribution and improving classification performance. Experimental results on six low-resourced imbalance text datasets validate the effectiveness of AltXLM-AdaCLE with an average AUC gain of 26.42%, demonstrating its superiority over existing methods. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

Structural Connectivity Analysis in Multiple Sclerosis Using Diffusion Tensor Imaging 5th

Structural Connectivity Analysis in Multiple Sclerosis Using...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Yadav, Dhyan Chandra Doda, Davendra Kumar Joshi, Apoorva Rengarajan, A. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Electrical Engineering Vivekananda Global University Jaipur India Master of Computer Application Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Structural connectivity evaluation (SCA) is a powerful tool for characterizing mind circuitry and assessing nearby structural adjustments in the mind. Diffusion Tensor Imaging (DTI) is a complicated magnetic resonance imaging technique used to determine the structural integrity of white be-counted tissue and to map the fiber pathways connecting excellent mind areas. This method allows for non-invasive exploration of structural connectivity for the motive of bdd5b54adb3c84011c7516ef3ab47e54, the underlying dynamics of mind networks. This paper uses SCA to sing the changes in mind networks due to more than one Sclerosis (MS) by measuring the integrity of white be-counted number pathways. The consequences of the evaluation display that SCA is useful in detecting close-by changes inside the corpus callosum structure that correlate with the development and severity of MS. Furthermore, it is well-known that MS induces adjustments inside the connectivity among wonderful mind regions that appear to be location unique. The findings display that SCA using DTI is a precious device for statistics of the impact of MS on neural networks at a few stages inside the thoughts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Analyzing the Effects of Coding and Compression on Network Performance 5th

Analyzing the Effects of Coding and Compression on Network P...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Agarwal, Ankita Kumar, Deepak Singh, Alka Preethi, D. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Mathematics Vivekananda Global University Jaipur India Department of Master of Computer Application Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bengaluru India

ISBN: (纸本)9789819780426

This paper objectives to research the consequences of coding and compression on network performance. Network coding is the technique of encoding information before it is despatched over a network and has become an outstanding method to enhance community overall performance. Compression then again is used to reduce the size of the data before transmission, ensuing in quicker transmission time. This observe evaluates the effect those techniques have on network overall performance by measuring the bandwidth utilization, throughput, latency, and packet losses. A test becomes conducted to have a look at how the strategies have an effect on one of kind mixtures of information speeds, packet sizes, and facts loading. Results display that both strategies had a fine impact at the community overall performance, with network coding and compression having an extra effect on networks with higher facts hundreds. Moreover, the effects show that community coding had a greater impact on networks with larger packets, while compression had a more effect on networks with smaller packets. This studies gives insight into how community coding and compression can be used to enhance network overall performance. Coding and compression are important components of network performance that have been studied and tested to have a full-size influence on network pace, scalability, and reliability. Coding is used to reduce the amount of data that is sent over a community, by way of reducing the quantity of records frames that need to be sent and growing the performance of the records transfer technique. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

Disease Detection Using Ensemble Model in Machine Learning

引用

SN computer Science 2025年第3期6卷 1-15页

作者： Mohapatra, Rojalin Giri, Parimala Kumar Sayyad, Irfan Sahu, Amaresh Brahma, Biswajit Kamila, Nilayam Kumar Department of Computer Science and Engineering Gandhi Institute for Technological Advancement Odisha Bhubaneswar India Department of Information Technology and Computer Application Vignan’s Foundation for Science Technology and Research (Deemed to be University) Andhra Pradesh Vadlamudi India Department of MCA Ajay Binay Institute of Technology Odisha Cuttack India McKesson Corporation San Francisco CA United States Capital One Wilmington DE United States

Disease detection is a vital issue in the healthcare system. Few diseases need to be tested early if any patient discovers any disease-related symptoms in their body. Although various methods are used to test several diseases based on the symptoms, it is necessary to improve the experimental testing for disease detection through various machine learning (ML) methods. Thus, the ensemble ML Model is proposed to enhance the experimental performance per the methods. Different machine learning methods such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Gaussian Naive Bayes (GNB) and Logistic Regression (LR) are used to make ensemble models based on the combination of two or three methods. The experiment is demonstrated on the proposed ensemble model using a diabetes data set and performed with various evaluation metrics. As per the performance of the ensemble method, (SVM + RF) performed well than other methods with an accuracy of 99%. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ensemble model Logistic regression Machine learning Naïve Bayes Random forest SVM Voting classifier

来源：评论

学校读者我要写书评

暂无评论

Impact of Glucocorticoid Toxicity Index on Immunosuppressive Management of Inflammatory Bowel Disease 5th

Impact of Glucocorticoid Toxicity Index on Immunosuppressive...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Yadav, Dhyan Chandra Sharma, Sunil Agarwal, Chhaya Mehta, Deepak Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Glucocorticoid toxicity index (GTI) is a useful degree proposed by using a meta-evaluation to assess the chance of systemic glucocorticoid exposure in sufferers laid low with inflammatory bowels illnesses (IBD). The GTI is computed based totally on cumulative glucocorticoid cumulative dose and duration within the first yr. After a prognosis of IBD. The contemporary take a look at objectives to check the literature to decide the utility of GTI in predicting the danger of glucocorticoid toxicity in IBD patients. A literature search turned into conducted to pick out research that evaluated the predictive price of GTI for toxicity in IBD patients. The retrieved articles suggest that cumulative glucocorticoid dose and length prior to three hundred and sixty five days of the diagnosis of IBD have been massive factors related to the prevalence of glucocorticoid toxicity in IBD sufferers. However, different next elements may additionally have an effect on the toxicity of glucocorticoid exposure in IBD patients, along with age, comorbidities, and genetic polymorphisms. Moreover, some of the research, the outcomes validated that GTI can be a valuable device for immunosuppressive management in IBD sufferers to be able to discover patients who're much more likely to revel in systemic toxicity at some stage in immunosuppressive treatment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cumulative Exposure Glucocorticoid

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：