检索结果-内蒙古大学图书馆

Robust Adaptive Safety-Critical Control for Unknown Systems with Finite-Time Element-Wise Parameter Estimation

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Wang, Shengbo Lyu, Bo Wen, Shiping Shi, Kaibo Zhu, Song Huang, Tingwen School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Australian AI Institute Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia School of Information Science and Engineering Chengdu University Chengdu611040 China School of Mathematics China University of Mining and Technology Xuzhou221116 China Science Program Texas A & M University at Qatar Doha23874 Qatar

Safety is always one of the most critical principles for a system to be controlled. This paper investigates a safety-critical control scheme for unknown structured systems by using the control barrier function (CBF) method. Benefited from the dynamic regressor extension and mixing (DREM), an extended element-wise parameter identification law is utilized to dismiss the uncertainty. On the one hand, it is shown that the proposed control scheme can always guarantee the safety in the identification process with noised signal injection excitation, which was not considered in the previous study. On the other hand, the element-wise estimation process in DREM can minimize conservatism of the safe adaptive process compared to other existing adaptive CBF algorithms. The stability as well as the forward invariance of the presented safe control-estimation scheme is proved. Furthermore, the robustness of the scheme under bounded disturbances is analyzed, where a robust CBF with modest conditions is used to ensure safety. The framework is illustrated by simulations on adaptive cruise control, where the slope resistance of the following vehicle is robustly estimated in finite time against small disturbances and the potential crash risk is avoided by the proposed safe control scheme. © 2021, CC BY-NC-ND.

关键词： Parameter estimation

Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

学校读者我要写书评

暂无评论

Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

Magnetized and quadratic convection based thermal transport in ternary radiative bio-nanofluid via intelligent neural networks: Two hidden layers mechanism

学校读者我要写书评

暂无评论

Results in Physics 2024年 65卷

作者： Ayub, Assad Darvesh, Adil Shah, Syed Zahir Hussain Junjua, Moin-ud-Din Santos, Elizaldo Domingues dos Ahmad, Shabbir Hendy, Ahmed S. Ragab, Adham E. Department of Mathematics & Statistics Hazara University Manshera Pakistan School of Mathematical Sciences Zhejiang Normal University Zhejiang Jinhua 321004 China Programa de Pós-Graduação em Modelagem Computacional/LMCE Escola de Engenharia Universidade Federal do Rio Grande – FURG RS Rio Grande 96203900 Brazil FURG Escola de Engenharia RS Rio Grande Brazil Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan 60000 Pakistan Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University 19 Mira St. Yekaterinburg 620002 Russian Federation Department of Industrial Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Mathematics Ghazi University Dera Ghazi Khan 32200 Pakistan Graduate Program of Ocean Engineering School of Engineering Universidade Federal do Rio Grande Italia Avenue km 8 96201-900 Rio Grande Brazil Department of Mechanics and Mathematics Western Caspian University Baku 1001 Azerbaijan

Significance: The thermal analysis of nanofluid in a vertical cylinder (artery) in a magnetized environment holds significant implications in physiological and thermal regulation networks. This research is significant in biomedical engineering with applications like medical diagnostics and treatment strategies. Motive: This study investigates the thermal behavior of a magnetized blood-based ternary Carreau nanofluid flowing through a vertically bounded artery with quadratic convection. Velocity and heat transfer analysis is conducted within the artery, utilizing thermal radiation and quadratic convection in a magnetized setting. The base fluid consists of blood, augmented with three nanoparticles: CuO, Al₂O₃, and TiO₂. The investigation centers on examining the properties of blood nanofluid, arterial geometry, and thermal dynamics. Methodology: The physical model generates a set of partial differential equations (PDEs) and similarities mechanism is utilized to fetch its non dimensional form in terms of ordinary differential equations (ODEs). Furthermore, numerical outcomes are obtained with Matlab function bvp4c and obtained data set is trained through robust scheme Levenberg-Marquardt neural network (LMNN) procedure to predict the solution. Findings: Velocity of blood is reduced with increased values of wiessenberg number, magnetic parameter and mixed convection parameter and velocity increases for Second-order convection parameter. Temperature profile decreases with curvature parameter, mixed convection parameter and permeability parameter. © 2024

关键词： Blood fluid Intelligent neural network Magnetized environment Ternary nanoparticles Thermal scrutiny

Packet warriors: An academic mobile action game for promoting OSI model concepts to learners

学校读者我要写书评

暂无评论

International Journal of Interactive Mobile Technologies

International Journal of Interactive Mobile Technologies 2019年第6期13卷 41-51页

作者： Uiphanit, Thanakorn Bhattarakosol, Pattarasinee Suanpong, Kwanrat Iamsupasit, Sompoch Technopreneurship and Innovation Management Program Chulalongkorn University Bangkok10330 Thailand Technopreneurship and Innovation Management Program Suan Sunandha Rajabhat University Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok10330 Thailand Department of Commerce Chulalongkorn Business School Chulalongkorn University Bangkok10330 Thailand Faculty of Psychology Chulalongkorn University Bangkok10330 Thailand

This research aims to develop a game to teach the theoretical concepts of the OSI reference model to students who must learn data communication and networking as a compulsory or an elective subject . The survey was administered to most students at Suan Sunandha Rajabhat University by a questionnaire to assess a suitable game for students of this generation. The result showed that action games are the most popular game for them. Then, a script of the OSI reference model was drawn based on the theoretical contents and the software design and implementation were performed. After finishing this development process, 19 third-year undergraduate students majoring in information sciences at Suan Sunandha Rajabhat University tested this system. The evaluation process was performed using pretest and posttest data analyzed by a paired samples t-test at a 95% confidence level. The result of this study shows that the action game 'Packet Warrior' is an efficient tool to help students improve their learning capabilities via fun and good relationships with friends. © 2019, International Association of Online Engineering.

关键词： Students

A Consensus Privacy Metrics Framework for Synthetic Data

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Pilgram, Lisa Dankar, Fida K. Drechsler, Jörg Elliot, Mark Domingo-Ferrer, Josep Francis, Paul Kantarcioglu, Murat Kong, Linglong Malin, Bradley Muralidhar, Krishnamurty Myles, Puja Prasser, Fabian Raisaro, Jean Louis Yan, Chao El Emam, Khaled School of Epidemiology and Public Health University of Ottawa ON Canada CHEO Research Institute ON Canada Department of Nephrology and Medical Intensive Care Charité – Universitätsmedizin Berlin Berlin Germany Department for Statistical Methods Institute for Employment Research Nuernberg Germany Institute for Statistics Ludwig-Maximilians-Universität Munich Germany Joint Program in Survey Methodology University of Maryland United States The Cathie Marsh Institute Research School of Social Sciences University of Manchester Manchester United Kingdom Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Tarragona Spain Max Planck Institute for Software Systems Germany Department of Computer Science Virginia Tech United States Department of Mathematical and Statistical Sciences University of Alberta Alberta Canada Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Biostatistics Vanderbilt University Medical Center NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Department of Marketing and Supply Chain Management University of Oklahoma Oklahoma United States Medicines and Healthcare products Regulatory Agency London United Kingdom Berlin Institute of Health at Charité Universitätsmedizin Berlin Medical Informatics Group Berlin Germany Biomedical Data Science Center University Hospital Lausanne Lausanne Switzerland

Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals’ privacy is adequately protected. There is no consolidated standard for measuring privacy in synthetic data. Through an expert panel and consensus process, we developed a framework for evaluating privacy in synthetic data. Our findings indicate that current similarity metrics fail to measure identity disclosure, and their use is discouraged. For differentially private synthetic data, a privacy budget other than close to zero was not considered interpretable. There was consensus on the importance of membership and attribute disclosure, both of which involve inferring personal information about an individual without necessarily revealing their identity. The resultant framework provides precise recommendations for metrics that address these types of disclosures effectively. Our findings further present specific opportunities for future research that can help with widespread adoption of synthetic data. © 2025, CC BY.

关键词： Differential privacy

Large language models for diabetes training:a prospective study

学校读者我要写书评

暂无评论

science Bulletin 2025年第6期70卷 934-942页

作者： Haoxuan Li Zehua Jiang Zhouyu Guan Yuqian Bao Yuexing Liu Tingting Hu Jiajia Li Ruhan Liu Liang Wu Di Cheng Hongwei Ji Yong Wang Ya-Xing Wang Carol Y.Cheung Yingfeng Zheng Jihong Wang Zhen Li Weibing Wu Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan Ching-Yu Cheng Tien Yin Wong Huating Li Chun Cai Lijuan Mao Lee-Ling Lim Yih-Chung Tham Bin Sheng Weiping Jia Shanghai University of Sport Shanghai 200438China School of Clinical Medicine Beijing Tsinghua Changgung HospitalTsinghua MedicineTsinghua UniversityBeijing 100084China Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua MedicineTsinghua UniversityBeijing 100084China Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and EngineeringSchool of ElectronicInformationand Electrical EngineeringShanghai Jiao Tong UniversityDepartment of Endocrinology and MetabolismShanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for DiabetesShanghai 200240China MoE Key Lab of Artificial Intelligence Artificial Intelligence InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Cardiology the Affiliated Hospital of Qingdao UniversityQingdao 266011China CEMS NCMISHCMSMADISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematics University of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100049China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology and Visual Sciences Key LaboratoryBeijing 100730China k.Department of Ophthalmology and Visual Sciences The Chinese University of Hong KongHong Kong 999077China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular DiseasesGuangzhou 510060China Department of Renal Medicine Singapore General HospitalSingHealth-Duke Academic Medical CentreSingapore169

Diabetes poses a considerable global health challenge,with varying levels of diabetes knowledge among healthcare professionals,highlighting the importance of diabetes *** Language Models(LLMs)provide new insights into diabetes training,but their performance in diabetes-related queries remains uncertain,especially outside the English language like *** first evaluated the performance of ten LLMs:ChatGPT-3.5,ChatGPT-4.0,Google Bard,LlaMA-7B,LlaMA2-7B,Baidu ERNIE Bot,Ali Tongyi Qianwen,MedGPT,HuatuoGPT,and Chinese LlaMA2-7B on diabetes-related queries,based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC)and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United ***,we assessed the training of primary care physicians(PCPs)without and with the assistance of ChatGPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical *** found that ChatGPT-4.0 outperformed other LLMs in the English examination,achieving a passing accuracy of 62.50%,which was significantly higher than that of Google Bard,LlaMA-7B,and *** the NCE-CPFC examination,ChatGPT-4.0,Ali Tongyi Qianwen,Baidu ERNIE Bot,Google Bard,MedGPT,and ChatGPT-3.5 successfully passed,whereas LlaMA2-7B,HuatuoGPT,Chinese LLaMA2-7B,and LlaMA-7B ***-4.0(84.82%)surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%).In summary,LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language,and hold great potential to assist future diabetes training for physicians globally.

关键词： Diabetes Diabetestraining Largelanguagemodels Primarydiabetescare Prospectivestudy

On the Efficient Evaluation of the Azimuthal Fourier Components of the Green's Function for Helmholtz's Equation in Cylindrical Coordinates

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Garritano, James Kluger, Yuval Rokhlin, Vladimir Serkh, Kirill Program in Applied Mathematics Yale University New HavenCT06511 United States Yale School of Medicine New HavenCT06511 United States Dept. of Mathematics Yale University New HavenCT06511 United States Dept. of Math. and Computer Science University of Toronto TorontoONM5S 2E4 Canada

In this manuscript, we develop an efficient algorithm to evaluate the azimuthal Fourier components of the Green's function for the Helmholtz equation in cylindrical coordinates. A computationally efficient algorithm for this modal Green's function is essential for solvers for electromagnetic scattering from bodies of revolution (e.g., radar cross sections, antennas). Current algorithms to evaluate this modal Green's function become computationally intractable when the source and target are close or when the wavenumber is large. Furthermore, most state of the art methods cannot be easily parallelized. In this manuscript, we present an algorithm for evaluating the modal Green's function that has performance independent of both source-to-target proximity and wavenumber, and whose cost grows as $O(m)$, where $m$ is the Fourier mode. Furthermore, our algorithm is embarrassingly parallelizable. © 2021, CC BY.

关键词： Bodies of revolution

Meta-control of social learning strategies

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Yaman, Anil Bredeche, Nicolas Çaylak, Onur Leibo, Joel Z. Lee, Sang Wan Computer Science Department Vrije Universiteit Amsterdam Amsterdam Netherlands Institut des Systèmes Intelligents et de Robotique Sorbonne Université CNRS Paris France Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands DeepMind London United Kingdom Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Center for Neuroscience-Inspired AI Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of KI for Health Science and Technology Korea Advanced Institute of Science and Technology Daejeon Korea Republic of KI for Artificial Intelligence Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Computer Science Department Vrije Universiteit Amsterdam Amsterdam Netherlands

Social learning, copying other's behavior without actual experience, offers a cost-effective means of knowledge acquisition. However, it raises the fundamental question of which individuals have reliable information: successful individuals versus the majority. The former and the latter are known respectively as success-based and conformist social learning strategies. We show here that while the success-based strategy fully exploits the benign environment of low uncertainly, it fails in uncertain environments. On the other hand, the conformist strategy can effectively mitigate this adverse effect. Based on these findings, we hypothesized that meta-control of individual and social learning strategies provides effective and sample-efficient learning in volatile and uncertain environments. Simulations on a set of environments with various levels of volatility and uncertainty confirmed our hypothesis. The results imply that meta-control of social learning affords agents the leverage to resolve environmental uncertainty with minimal exploration cost, by exploiting others' learning as an external knowledge base. Copyright © 2021, The Authors. All rights reserved.

关键词： Learning systems

Esophageal microbiome correlates with post-esophagectomy anastomotic leak in cancer patients

学校读者我要写书评

暂无评论

ESMO Gastrointestinal Oncology

ESMO Gastrointestinal Oncology 2025年 8卷 100172-100172页

作者： R. Naddaf H. Shmilovich S. Carasso R. Keshet-David R. Herren T. Gefen T. Goshen-Lago Y. Zwang I. Livyatan N. Shental O. Haberfeld R. Straussman S.R. Markar M. Nilsson H. Kashtan I. Ben-Aharon N. Geva-Zatorsky Rappaport Faculty of Medicine Technion Haifa Israel Division of Surgery Rabin Medical Center Petach Tikva Israel Department of Division of Oncology Rambam Health Care Center Haifa Israel Department of Molecular Cell Biology Weizmann Institute of Science Rehovot Israel Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Department of Mathematics and Computer Science The Open University of Israel Ra’anana Israel Department of Thoracic Surgery Rambam Health Care Center Haifa Israel Nuffield Department of Surgery University of Oxford Oxford UK Division of Surgery Department of Clinical Science Intervention and Technology Karolinska Institute Stockholm Sweden Department of Upper Abdominal Diseases Karolinska University Hospital Stockholm Sweden CIFAR Humans & the Microbiome Program CIFAR Toronto Canada

Background Despite continuous improvement in long-term survival after esophagectomy, potential serious post-operative complications, such as anastomotic leaks (ALs), still occur. Several risk factors for ALs have been proposed, including environmental factors. Our main objective was to examine the correlation of esophageal tumor microbiome composition and functional profile with ALs. Additionally, we analyzed the microbiome of esophageal tumors and their potential correlation with clinical features of the patients. Materials and methods Surgical specimens of esophageal tumors and adjacent normal tissues were collected from consecutive patients who underwent an esophagectomy. Formalin-fixed paraffin-embedded (FFPE) tissue samples were processed using 16S ribosomal DNA multiple fragments amplicon sequencing to characterize bacterial microbiome composition. The tumor and normal tissue microbiome and bacterial functional profile were analyzed based on the clinical outcome of ALs. Results Out of 60 patients who met the inclusion criteria, 52 (86.7%) patients had both normal adjacent tissue (NAT) and tumor (T) FFPE samples included with sufficient bacterial DNA extracted for analysis. A total of 28% of participants had esophageal ALs. Proportion tests [ P < 0.05, false discovery rate (FDR) < 0.25] revealed operational taxonomic units (OTUs) significantly present in T samples as opposed to NAT samples, as well as significantly present OTUs in patients with AL as opposed to patients without AL complication. Conclusions In this study, we provide a profile of the understudied esophageal microbiome and its connection to ALs. Our results can provide potential clues on how to avoid ALs by considering a patient’s personal microbiome when providing perioperative care.

关键词： microbiome tumor microbiome esophageal cancer esophagectomy anastomotic leak