检索结果-内蒙古大学图书馆

2022 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2022

作者： Miao, Yinan Wang, Xingjian Wang, Jiaqi Wang, Shaoping Gavrilov, Alexander I. School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Qingdao Research Institute Beihang University Qingdao266104 China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100191 China Bauman Moscow State Technical University Department of Automatic Control Systems Moscow105005 Russia

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

Nowadays, exoskeletons' ability to operate in complex environments is increasingly important. It is challenging to obtain an accurate gait phase under continuous multimodal locomotion. A hybrid gait phase recognition algorithm is proposed combining the adaptive-oscillator-based algorithm and the model-based algorithm. The modification law is adopted to make two algorithms amend each other reciprocally. The design of the modification law combines the advantages of oscillator-based algorithms and model-based algorithms. The gait phase estimation results are more accurate via the hybrid gait phase prediction algorithm (GPRA). Therefore, appropriate assistance actuation and higher efficiency are obtained under the complicated multimodal locomotion. An experiment was designed to verify the performance of the hybrid GPRA. As a result, the hybrid GPRA can still produce a high-precision gait phase with low latency even when the locomotion mode switches. The hybrid GPRA can provide accurate gait phase and assistance timing under continuous multimodal locomotion. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Exoskeleton (Robotics)

来源：评论

学校读者我要写书评

暂无评论

Gut Microbiome as a Risk Factor for Future CKD

引用

Kidney International Reports 2025年第6期10卷 1673-1682页

作者： Hellman, Tapio Yeo, Li-Fang Palmu, Joonatan Havulinna, Aki Jousilahti, Pekka Laitinen, Ville Pärnänen, Katariina Salomaa, Veikko Lahti, Leo Knight, Rob Niiranen, Teemu Kidney Center Turku University Hospital and University of Turku Turku Finland Division of Medicine University of Turku Turku Finland Department of Internal Medicine Turku University Hospital and University of Turku Turku Finland Department of Public Health Finnish Institute for Health and Welfare Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Department of Computing University of Turku Turku Finland Department of Pediatrics University of California San Diego La Jolla CA United States Center for Microbiome Innovation Joan and Irwin Jacobs School of Engineering University of California San Diego La Jolla CA United States Department of Bioengineering University of California San Diego La Jolla CA United States Department of Computer Science and Engineering University of California San Diego La Jolla CA United States Halıcıoğlu Data Science Institute University of California La Jolla San Diego CA United States

Introduction: Gut microbiome has been linked with chronic kidney disease (CKD) in several small cross-sectional studies. However, the relationship between baseline gut microbiome and long-term incident CKD remains unknown. Methods: We performed fecal sampling and measured serum creatinine (SCR) (N = 6699) and urine albumin-to-creatinine ratio (UACR) (N = 797) in a population-based cohort examined in the year 2002. We assessed the multivariable-adjusted associations of gut metagenome with baseline SCR, baseline UACR, and register-based incident CKD. Results: The mean age of the participants was 49.5 ± 12.9 years and 45.8% were men. During a median follow-up of 18.6 years, 108 participants developed incident CKD. In prospective analyses, increased baseline gut microbiome alpha diversity was associated with lower risk of incident CKD (hazard ratio per 1 SD: 0.84;95% confidence interval [CI]: 0.71–0.99;P = 0.04). Gut microbial beta diversity and taxa were not related to incident CKD (P ≥ 0.09 for all). In cross-sectional analyses, alpha diversity (beta per 1 SD: 1.28;95% CI: 0.64–1.98;P < 0.001) and beta diversity (P = 0.002;R² = 0.12%) were associated with SCR, whereas no associations were observed for UACR. In total, 43 significant species-level associations with SCR were observed and 16 negative associations (37.2%) for species belonging to the Lachnospiraceae family. Conclusion: Our results suggest that decreased gut microbial diversity may be related to risk of future CKD and that a potential link between the Lachnospiraceae family and desirable kidney health exists. Our results extend previous cross-sectional studies and help to establish the basis for examining gut microbiome as a CKD risk factor. © 2025 International Society of Nephrology

关键词： chronic kidney disease clinical study microbiology proteinuria

来源：评论

学校读者我要写书评

暂无评论

Fs-Woa-Stacking: A Novel Ensemble Model for Early Diagnosis of Breast Cancer

SSRN

引用

SSRN 2024年

作者： Xiao, Tianyun Kong, Shanshan Zhang, Zichen Liu, Fengchun Yang, Aimin Hua, Dianbo Hebei Key Laboratory of Data Science and Application North China University of Science and Technology Hebei Tangshan063210 China The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and Technology Hebei Tangshan063210 China College of Science North China University of Science and Technology Hebei Tangshan063210 China Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and Technology Hebei Tangshan China Tangshan Intelligent Industry and Image Processing Technology Innovation Center North China University of Science and Technology Hebei Tangshan China Beijing Sitairui Cancer Data Analysis Joint Laboratory Beijing101149 China

In this paper, a new integrated scheme is proposed to accurately predict breast cancer, help doctors make early diagnosis and treatment plans, and improve the prognosis of patients. We selects five mainstream machine learning models: support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost) and adaptive boosting (AdaBoost). The Wisconsin Breast Cancer database (WBCD) and Wisconsin Diagnostic Breast Cancer (WDBC) are used as datasets to investigate the predictive performance of these single and ensemble models. Then, we use multiple linear regression method for feature selection (FS), the experimental results show that the change of feature subset will significantly affect the performance of the model. After that, we apply whale optimization algorithm (WOA) to optimize the hyperparameters of the model to improve their prediction performance. In addition, we ensemble these models by stacking, investigate the performance changes of the ensemble model when different models are used as meta learners. Finally, the FS-WOA-Stacking model achieves 99.56% accuracy on WBCD and 99.65% accuracy on WDBC. Compared with the existing breast cancer prediction models, the performance of the proposed model is at an excellent level. © 2024, The Authors. All rights reserved.

关键词： Adaptive boosting

来源：评论

学校读者我要写书评

暂无评论

BiKT: Unleashing the potential of GNNs via Bi-directional Knowledge Transfer

arXiv

引用

arXiv 2023年

作者： Zheng, Shuai Liu, Zhizhe Zhu, Zhenfeng Zhang, Xingxing Li, Jianxin Zhao, Yao The Institute of Information Science Beijing Jiaotong University Beijing100044 China The Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Qiyuan Lab Beijing China The Beijing Advanced Innovation Center for Big Data and Brain Computing School of Computer Science and Engineering Beihang University Beijing100083 China

Based on the message-passing paradigm, there has been an amount of research proposing diverse and impressive feature propagation mechanisms to improve the performance of GNNs. However, less focus has been put on feature transformation, another major operation of the message-passing framework. In this paper, we first empirically investigate the performance of the feature transformation operation in several typical GNNs. Unexpectedly, we notice that GNNs do not completely free up the power of the inherent feature transformation operation. By this observation, we propose the Bi-directional Knowledge Transfer (BiKT), a plug-and-play approach to unleash the potential of the feature transformation operations without modifying the original architecture. Taking the feature transformation operation as a derived representation learning model that shares parameters with the original GNN, the direct prediction by this model provides a topological-agnostic knowledge feedback that can further instruct the learning of GNN and the feature transformations therein. On this basis, BiKT not only allows us to acquire knowledge from both the GNN and its derived model but promotes each other by injecting the knowledge into the other. In addition, a theoretical analysis is further provided to demonstrate that BiKT improves the generalization bound of the GNNs from the perspective of domain adaption. An extensive group of experiments on up to 7 datasets with 5 typical GNNs demonstrates that BiKT brings up to 0.5% - 4% performance gain over the original GNN, which means a boosted GNN is obtained. Meanwhile, the derived model also shows a powerful performance to compete with or even surpass the original GNN, enabling us to flexibly apply it independently to some other specific downstream tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

来源：评论

学校读者我要写书评

暂无评论

The Comparative Experimental Study of Rehabilitation Program Decision for Spinal Cord Injury Based on Electronic Medical Records

SSRN

引用

SSRN 2024年

作者： Qie, Botao Guo, Xin Chen, Wei Yu, Suiran Wang, Zhengtao School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin300401 China Qinhuangdao Research Institute National Research Center for Rehabilitation Technical Aids Qinhuangdao066004 China Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin300401 China National Research Center for Rehabilitation Technical Aids Beijing100176 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

Objective: Electronic medical records (EMRs) contain patients' medical and health information. The Utilization of EMRs for assisted diagnosis is of significant importance for the rehabilitation of spinal cord injury (SCI) patients. Therefore, this study proposes a decision-making model for rehabilitation programs of SCI patients based on EMRs. Methods: First, an Electronic Medical Records (EMR) dataset comprising 1252 Spinal Cord Injury (SCI) patients was constructed, and data preprocessing was completed. Second, the Random Forest (RF) feature extraction algorithm was utilized to select case features with high contribution levels. Then, to address the imbalance issue in EMRs, a multi-label learning framework based on the improved MLSMOTE was adopted. Finally, seven multi-label classification models were employed to predict patients' physical therapy (PT) prescriptions. Results: The proposed improved MLSMOTE multi-label learning framework can solve the problem of class imbalance. Compared with the other six models, the CC model has improved significantly in many metrics. Its hamming loss and ranking loss were 0.1388 and 0.2467, and precision, recall, and F1-score were 83.33%, 81.20%, and 79.82% respectively. Conclusions: The improved MLSMOTE multi-label learning framework proposed in this study can make full use of the information in EMRs and effectively improve the decision-making accuracy of rehabilitation treatment programs. © 2024, The Authors. All rights reserved.

关键词： Patient rehabilitation

来源：评论

学校读者我要写书评

暂无评论

The Development of the Mobile Interactive Virtual Nuclear Educator With AR and RAG for Learning Nuclear Energy in Indonesia

The Development of the Mobile Interactive Virtual Nuclear Ed...

引用

International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

作者： Rio Nurtantyana Sahara Eka Kencana Murni Halim Hamadi Wu-Yuin Hwang Research Center for Data and Information Sciences & Center of Excellence Artificial Intelligence for Learning and Optimization National Research and Innovation Agency (BRIN) & Telkom University Bandung Indonesia Electronic Instrumentation Polytechnic Institute of Nuclear Technology Yogyakarta Indonesia Faculty of Science and Engineering & Graduate Institute of Network Learning Technology National Dong-Hwa University & National Central University Hualien Taiwan

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

The conventional way to search the information on the internet usually uses search engines, however, the results only provide textual information. There has been a noticeable gap in student engagement, particularly among young generations like elementary to high school students, who prefer interactive learning methods. Specifically, there is a need to focus on disseminating information about nuclear energy, particularly its application in nuclear power plants in accordance with Indonesia’s master plan about nuclear energy as it is essential for the younger generation to be informed. Therefore, we developed an Android mobile app namely AR-Deni with Augmented Reality (AR) technology that interactively provides information through touch and voice chat with an animated 3D virtual educator. To answer the question, it utilizes retrieval-augmented generation (RAG) technology with verified documents that could elevate students' curiosity and understanding about nuclear energy information while ensuring the accuracy and reliability of the information provided. Further, we used extreme programming (XP) as a development methodology to plan and test the app. We test the app with user acceptance testing (UAT) and performance testing with 12 scenarios to interact in Q&A. The results showed that the AR-Deni developed with the XP method and passed the 100% scenario in UAT. Regarding the performance, the RAG needed more response time to find the answer from specific questions rather than general questions. Hence, the AR-Deni could be used as an interactive virtual nuclear educator for learning media.

关键词： Nuclear energy Three-dimensional displays Search engines Media Mobile applications Time factors Reliability Programming profession Power generation Testing

来源：评论

学校读者我要写书评

暂无评论

An improved Convolutional Neural Network model for human posture detection

An improved Convolutional Neural Network model for human pos...

引用

Chinese Control Conference (CCC)

作者： Xin Guo Jian Liu Yaoxu Lei School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China National Research Center for Rehabilitation Assistants Qinhuangdao Research Institute Qinhuangdao Hebei China Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin P. R. China

The classic OpenPose convolutional neural network model has excellent performance in the field of human posture detection. But it also has some shortcomings, such as poor accuracy and low accuracy of human posture detection partly. An improved OpenPose network model is proposed to solve these problems. First of all, the feature extraction network VGG -19 of OpenPose model is replaced by the residual network (ResN et) with residual learning structure to improve the training accuracy of the network. Secondly, at the same stage, the dual-branch parallel structure is changed to the single-branch serial structure to predict the part confidence maps (PCMs) and the part affinity fields (PAFs) of human joint points. Finally, the structure of the convolution kernel is optimized and the residual network is introduced. The accuracy of the algorithm is improved and the computational speed of the model is guaranteed as much as possible. Experimental verification on MPII data sets shows that the detection accuracy of the improved algorithm model in this paper can reach 79.5%, which is 3.9% higher than the original model. At the same time, it has a higher accuracy of detection compared with other human posture detection algorithms. It can be applied to human posture detection with a high pursuit of the accuracy of detection of the model, such as the field of intelligent driving and rehabilitation training and so on.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development of a Mental Health Chatbot Using Large Language Models for Indonesian Undergraduates

Development of a Mental Health Chatbot Using Large Language ...

引用

International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

作者： Mukhamad Angga Gumilang Hayuning Titi Karsanti Ria Wiyatfi Linsiya Kimi Dandy Yudanarko Lisa Novita Sari Ariz Saputra Naela Zahwa Salsabila Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia National Research and Innovation Agency Research Center for Data Science and Information Science Jakarta Indonesia Faculty of Psychology Universitas Muhammadiyah Jember Jember Indonesia Department of Information Technology Politeknik Negeri Jember Jember Indonesia Departement of Health Politeknik Negeri Jember Jember Indonesia

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

Mental health issues among university students are an escalating global problem, especially in Indonesia. Young adults, especially college students, are a vulnerable demographic due to academic pressures, social transitions, and the challenges of independent living. This paper describes the development of a mental health chatbot specifically for Indonesian university students, utilizing large language models (LLMs). The development encompassed three essential phases: establishing a knowledge base, refining the LLM with culturally pertinent Indonesian data, and assessing the system. The findings demonstrated notable enhancements in the chatbot's precision, with training accuracy rising from 0.6 to 0.85 and validation accuracy from 0.5 to 0.79 due to fine-tuning and regularization. User acceptability testing including 58 students resulted in an acceptance percentage of 87.38%, indicating substantial satisfaction with the chatbot's response and usefulness. This research highlights the efficacy of AI-driven interventions in addressing the mental health requirements of Indonesian university students.

关键词： Training Digital control Accuracy Large language models Refining Knowledge based systems Mental health Chatbots Informatics Testing

来源：评论

学校读者我要写书评

暂无评论

Cooperative guidance strategy for multiple hypersonic gliding vehicles system

引用

Chinese Journal of Aeronautics 2020年第3期33卷 990-1005页

作者： Jianglong YU Xiwang DONG Qingdong LI Zhang REN Jinhu LV School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100083China Shananxi Key Laboratory of Integrated and Intelligent Navigation Xi’an 710068China

Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is *** paper mainly cares about the coordination of the entry glide flight phase and driving-down *** from the existing results,both the attack time and the attack angle constraints are considered ***, for the entry glide flight phase, a two-stage method is proposed to achieve the rapid cooperative trajectories planning, where the control signal corridors are designed based on the quasi-equilibrium gliding *** the first stage, the bank angle curve is optimized to achieve the attack angle *** the second stage, the angle of attack curve is optimized to achieve the attack time *** optimized parameters can be obtained by the secant ***, for the driving-down phase, the cooperative terminal guidance law is designed where the terminal attack time and attack angle are *** guidance law is then transformed into the bank angle and angle of attack *** cooperative guidance strategy is summarized as an ***, a numerical simulation example with three hypersonic gliding vehicles is provided for revealing the effectiveness of the acquired strategy and algorithm.

关键词： Attack angle constraints Attack time constraints Cooperative guidance Cooperative path planning Entry guidance Hypersonic vehicles

来源：评论

学校读者我要写书评

暂无评论

Estimating the value of a statistical life in China: A contingent valuation study in six representative cities

引用

Chinese Journal of Population,Resources and Environment 2023年第4期21卷 269-278页

作者： Chaoji Cao Xinke Song Wenjia Cai Yichao Li Jianhui Cong Xueying Yu Mengzhao Gao Can Wang Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing100084China Tsinghua Urban Institute Tsinghua UniversityBeijing100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Center for Statistical Science Tsinghua UniversityBeijing100084China Department of Industrial Engineering Tsinghua UniversityBeijing100084China School of Economics and Management Shanxi UniversityTaiyuan030000China School of Economics and Management Beihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang UniversityBeijing100191China Key Laboratory of Big Data-Based Precision Medicine(Beihang University) Ministry of Industry and Information TechnologyBeijing100191China

The value of a statistical life(VSL)is a crucial tool for monetizing health *** explore the VSL in China,this study examines people’s willingness to pay(WTP)to reduce death risk from air pollution in six representative cities in China based on face-to-face contingent valuation interviews(n=3936)from March 7,2019 to September 30,*** results reveal that the WTP varied from CNY 455 to 763 in 2019(USD 66-111),corresponding to a VSL range of CNY 3.79-6.36 million(USD 549395-921940).The VSL in China in 2019 is estimated to be CNY 4.76 million(USD 689659).The statistics indicate that monthly expenditure levels,environmental concerns,risk attitudes,and assumed market acceptance,which have seldom been dis‐cussed in previous studies,significantly impact WTP and *** findings will serve as a reference for ana‐lyzing mortality risk reduction benefits in future research and for policymaking.

关键词： Air pollution Contingent valuation method Willingness to pay Value of a statistical life China

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：