检索结果-内蒙古大学图书馆

International Computer Science and Engineering Conference (ICSEC)

作者： Piyanut Tangmanussukum Thitipong Kawichai Apichat Suratanee Kitiporn Plaimas Faculty of Science Chulalongkorn University Bangkok Thailand Academic Division Chulachomklao Royal Military Academy Nakhon Nayok Thailand Faculty of Applied Science Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut's University of Technology North Bangkok Bangkok Thailand Advanced Virtual and Intelligent Computing (AVIC) Center Faculty of Science Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665411981

Identification of drug target proteins is an important process in drug discovery and development. To perform predictions of large-scale drug-target interactions, many computational methods have been proposed using the information of target-target and drug-drug similarities into a network. In this work, we propose an enhanced heterogeneous network model with various biological aspects of target-target and drug-drug similarities to predict drug-target associations. Network propagation was performed through the heterogeneous network to predict new potential targets of a certain drug. Cross-validation and the Area Under the Receiver Operating Characteristic curve (AUROC) were then used to qualify the best model in the drug-target association prediction. The result shows that the model using the similarity measures based on drug-disease associations and target protein sequences significantly outperforms the other models and the original model. Overall, our best model yields an accuracy of 93.5%. In conclusion, the heterogeneous model with optimal similarity measures is a well-suited approach to predict a new target for a certain drug.

关键词： Drugs Proteins Computer science Computational modeling Biological system modeling Receivers Predictive models

来源：评论

学校读者我要写书评

暂无评论

A generalization of Zakalyukin's lemma, and symmetries of surface singularities

arXiv

引用

arXiv 2021年

作者： Honda, Atsufumi Naokawa, Kosuke Saji, Kentaro Umehara, Masaaki Yamada, Kotaro Department of Applied Mathematics Faculty of Engineering Yokohama National University 79-5 Tokiwadai Hodogaya Yokohama240-8501 Japan Department of Computer Science Faculty of Applied Information Science Hiroshima Institute of Technology 2-1-1 Miyake Saeki Hiroshima731-5193 Japan Department of Mathematics Faculty of Science Kobe University Rokko Kobe657-8501 Japan Department of Mathematical and Computing Sciences Tokyo Institute of Technology Tokyo152-8552 Japan Department of Mathematics Tokyo Institute of Technology Tokyo152-8551 Japan

Zakalyukin's lemma asserts that the coincidence of the images of two wave front germs implies the right equivalence of corresponding map germs under a certain genericity assumption. The purpose of this paper is to give an improvement of this lemma for frontals. Moreover, we give several applications for singularities on *** Codes 53A10, 53A35, 53C42, 33C05 Copyright © 2021, The Authors. All rights reserved.

关键词： Wavefronts

来源：评论

学校读者我要写书评

暂无评论

A computational framework for Carreau nanomaterial induced by stretchy regime considering Brownian diffusion, viscous dissipation, ferromagnetism and thermophoresis

引用

Partial Differential Equations in applied Mathematics 2025年 13卷

作者： Hussain, Iftikhar Khan, Waqar Azeem Tabrez, Muhammad Waqas, M. Ibrahim, Talib K. Saidani, Taoufik Kausar, M.S. Zamri, Nurnadiah Abdullaeva, Barno Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Jammu and Kashmir Azad 12010 Pakistan School of Mathematics and Statistics Beijing Institute of Technology Beijing 100081 China NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (Kampus Gong Badak) Terengganu Kuala Terengganu 21300 Malaysia Department of Mathematics and Information Technologies Vice-Rector for Scientific Affairs Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

In recent decade, the research in nanotechnology brought the idea of nanofluids which are highly conducting materials. Some important applications of nanofluids are justified in pharmaceutical industry, coolants in vehicles engine, preparation process of various medicines for treatment of fatal diseases like cancer, aircraft industry, latest heat exchangers etc. The ferro particles are special class of nanomaterial which attract variety of interest from the researchers. The objective of current research is to perform the investigation for heat and mass transfer subject to Carreau nanofluid to observe the enhancement of heat transmission phenomena. The induction of magnetic dipole has been observed for thermal transport phenomenon. The flow is causing by stretched surface. A simplified system is obtained by utilizing the dimensionless variables. Physical interpretation of results have been presented. Result showed that temperature profile in presence of ferrofluid fluid boosts up with escalation in thermophoresis parameter, while opposite behavior is noted for power law index. The concentration of ferrofluid showing declining behavior for Schmidt numbers and rises for thermophoresis parameter. © 2024

关键词： Carreau ferrofluid Heat and mass transfer Magnetic dipole Numerical solution

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Models for the Identification of Cardiovascular Diseases Using UK Biobank Data

arXiv

引用

arXiv 2024年

作者： Islam, Sheikh Mohammed Shariful Abrar, Moloud Tegegne, Teketo Loranjo, Liliana Karmakar, Chandan Awal, Md Abdul Hossain, Md. Shahadat Kabir, Muhammad Ashad Mahmud, Mufti Khosravi, Abbas Siopis, George Moses, Jeban C. Maddison, Ralph Institute for Physical Activity and Nutrition Deakin University Melbourne Australia School of Information Technology Deakin University Melbourne Australia Westmead Applied Research Centre The University of Sydney Sydney Australia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia School of Computer Data and Mathematical Sciences Western Sydney University Sydney Australia School of Computing Mathematics and Engineering Charles Sturt University Bathurst Australia Department of Computer Science Nottingham Trent University Nottingham United Kingdom Faculty of Medicine Health and Human Sciences Macquarie University Sydney Australia

Background: Machine learning models have the potential to identify cardiovascular diseases (CVDs) early and accurately in primary healthcare settings, which is crucial for delivering timely treatment and management. Although population-based CVD risk models have been used traditionally, these models often do not consider variations in lifestyles, socioeconomic conditions, or genetic predispositions. Therefore, we aimed to develop machine learning models for CVD detection using primary healthcare data, compare the performance of different models, and identify the best models. Methods: We used data from the UK Biobank study, which included over 500,000 middle-aged participants from different primary healthcare centers in the UK. Data collected at baseline (2006-2010) and during imaging visits after 2014 were used in this study. Baseline characteristics, including sex, age, and the Townsend Deprivation Index, were included. Participants were classified as having CVD if they reported at least one of the following conditions: heart attack, angina, stroke, or high blood pressure. Cardiac imaging data such as electrocardiogram and echocardiography data, including left ventricular size and function, cardiac output, and stroke volume, were also used. We used 9 machine learning models (LSVM, RBFSVM, GP, DT, RF, NN, AdaBoost, NB, and QDA), which are explainable and easily interpretable. We reported the accuracy, precision, recall, and F-1 scores;confusion matrices;and area under the curve (AUC) curves. Results: RBFSVM, GP, DT, and AdaBoost were the best performing models (accuracy: 96), and LSVM showed the weakest prediction performance (accuracy: 0.69). While RBFSVM and GP could significantly classify people with CVD better, LSVM and AdaBoost could classify healthy participants more accurately. The LSVM has a better false positive rate but a worse false negative rate. Moreover, the RBFSVM and GP have better performance in terms of false negatives. RBFSVM, GP, DT, NN, and AdaB

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Sensor-based authentication in smartphone: A systematic review

Journal of Engineering Research (Kuwait)

引用

Journal of Engineering Research (Kuwait) 2024年

作者： Shuwandy, Moceheb Lazam Jouda, A.S. Ahmed, M.A. Salih, Mahmood M. Al-qaysi, Z.T. Alamoodi, A.H. Garfan, Salem Albahri, O.S. Zaidan, B.B. Albahri, A.S. Computer Science Department College of Computer Science and Mathematics Tikrit University (TU) Tikrit Iraq Salahaddin Health Office Ministry of Health Tikrit Iraq MEU Research Unit Middle East University Amman Jordan Faculty of Computing and Meta-Technology (FKMT) Universiti Pendidikan Sultan Idris (UPSI) Perak Malaysia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Victorian Institute of Technology Australia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Applied Science Research Center Applied Science Private University Amman Jordan SP Jain School of Global Management Lidcombe Sydney 2141 NSW Australia International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Technical College Imam Ja'afar Al-Sadiq University Baghdad Iraq Iraqi Commission for Computers and Informatics (ICCI) Baghdad Iraq

With the widespread usage of smartphones, users not just using their smartphone for calls and messaging only, but they are using it for a variety of purposes such as banking transactions, e-mailing, chatting, online shopping, video conferencing, health monitoring, and many more. Most of these activities store personal and sensitive data of the user on the device, reaching this confidential information by unauthorized person may cause huge losses and bad consequences. Therefore, securing the smartphone's accessibility from unauthorized people became an extremely essential. With the advanced development in the area of sensor-based smartphone authentication methods, different methods were developed to be easily used by users through specific criteria. However, many aspects haven't been discovered yet in the area of sensor-based smartphone authentication methods. On the basis of that, this study aims to review the area of sensor-based smartphone authentication methods systematically to provide a comprehensive understanding of this new area and to discuss the current challenges and issues. To conduct this systematic review, four scientific digital databases were utilized;ScienceDirect, IEEE Xplore, Web of Science, and Scopus. The total number of studies found was n = 256 articles, only n = 46 articles were included based on our inclusion criteria. To provide a comprehensive understanding of the included studies, taxonomy was drawn. Also, this study provides a discussion on the current motivations, challenges and issues, and recommendations in sensor-based smartphone authentication methods. This review enlightens, encourage, and direct researchers to develop authentication solutions and reduce the current gaps in this area. © 2024 The Authors

关键词： Authentication MHealth Microphone Sensor Password Privacy Touch Sensor

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis of a Class of Variable Fractional-Order Uncertain Neutral-Type Systems with Time-Varying Delay

SSRN

引用

SSRN 2022年

作者： Aghayan, Zahra Sadat Alfi, Alireza Mousavi, Yashar Fekih, Afef Faculty of Electrical Engineering Shahrood University of Technology Shahrood36199-95161 Iran Department of Applied Science School of Computing Engineering and Built Environment Glasgow Caledonian University GlasgowG4 0BA United Kingdom Electrical and Computer Engineering Department University of Louisiana at Lafayette P.O. Box 43890 LafayetteLA70504 United States

Variable fractional-order (VFO) differential equations are a beneficial tool for describing the nonlinear behavior of complex dynamical phenomena. In comparison with the constant FO derivatives, it describes the memory properties of such systems that can vary in the time domain and spatial location. This article investigates the stability and stabilization of VFO neutral systems in the presence of time-varying structured uncertainties and time-varying delay. FO Lyapunov theorem is adopted to achieve order-dependent and delay-dependent conditions for both nominal and uncertain VFO neutral delay systems. The obtained conditions are given in respect of linear matrix inequality by designing a delayed state feedback controller. Simulations verify the main results. © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

SMILES-driven machine learning for high-throughput investigation of anti-corrosion materials

引用

Chemometrics and Intelligent Laboratory Systems 2025年 263卷

作者： Muhamad Akrom Harun Al Azies Wise Herowati Totok Sutojo Supriadi Rustad Hermawan Kresno Dipojono Hideaki Kasai Research Center for Quantum Computing and Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung 40132 Indonesia Department of Applied Physics Osaka University Suita Osaka 565-0871 Japan

This investigation delves into the viability of the simplified molecular input line entry system (SMILES)-based machine learning (ML) approach as the sole input feature for predicting the corrosion inhibition efficiency (CIE) of pyridine-quinoline compounds to replace various quantum chemical properties (QCP). Employing the molecular access system (MACCS) fingerprint techniques simplifies the processing of molecular structures, enhancing data efficiency. The ML algorithm, notably the gradient boosting (GB) model, showcases superior predictive capabilities, as evidenced by R 2 and RMSE values of 0.92 and 0.07, respectively. This outcome is akin to predictions employing 20 QCP features, yielding R 2 and RMSE values of 0.90 and 0.08, respectively. The study substantiates SMILES as a robust single feature for accurate CIE prediction, revealing a moderate correlation between SMILES-represented structures and CIE values. This underscores the effectiveness of SMILES-based ML in assessing corrosion inhibition potential, thereby advancing predictive modeling in corrosion science. Integrating machine learning and SMILES notation presents an efficient approach for evaluating the corrosion inhibition capacity of diverse molecular structures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis of a Class of Variable Fractional-Order Uncertain Neutral-Type Systems with Time-Varying Delay

SSRN

引用

SSRN 2022年

关键词： Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

Effect of endogenous and anthropogenic factors on the alkalinisation and salinisation of freshwater in United States by using explainable machine learning

引用

Case Studies in Chemical and Environmental Engineering 2024年 10卷

作者： Wimalagunarathna, N.D. Dharmarathne, Gangani Ekanayake, I.U. Rathanayake, Upaka Alwatugoda, Janaka Meddage, D.P.P. Department of Zoology Faculty of Applied Sciences University of Sri Jayewardenepura Gangodawila Nugegoda Sri Lanka Australian Laboratory Services Global Water and Hydrographic Hume 2620 ACT Australia School of Computing Technologies Royal Melbourne Institute of Technology Melbourne VIC Australia Ceylon Institute for Artificial Intelligence Research (CIAIR) Colombo Sri Lanka Department of Civil Engineering and Construction Faculty of Engineering and Design Atlantic Technological University Sligo Ireland Research and Innovations Centers Division Rabdan Academy Abu Dhabi United Arab Emirates Institute for Integrated and Intelligent Systems Griffith University Nathan QLD Australia School of Engineering and Technology The University of New South Wales Canberra 2600 ACT Australia

Freshwater salinisation and alkalinisation strongly depend on human and natural factors. We used an explainable machine learning approach to investigate the impact of natural and human factors on the salinity and alkalinity in rivers in the United States. The model achieved coefficient of determination of 0.89 for salinity predictions and 0.92 for alkalinity predictions. Shapley additive explanations revealed salinisation is driven mainly by human factors like population density (18 %) and impervious surface percentage (13 %) and natural factors like run-off (14 %). The alkalinisation is mainly influenced by natural processes such as runoff (36 %) and soil-pH (20 %). © 2024 The Authors

关键词： Alkalinity Ecosystem Machine learning Rivers Salinity

来源：评论

学校读者我要写书评

暂无评论

Magnetic phase diagrams of the spin-12 Heisenberg model on a kagome-strip chain: Emergence of a Haldane phase

引用

Physical Review B 2021年第22期104卷 224417-224417页

作者： Katsuhiro Morita Shigetoshi Sota Takami Tohyama Department of Applied Physics Tokyo University of Science Tokyo 125-8585 Japan Department of Physics Faculty of Science and Technology Tokyo University of Science Chiba 278-8510 Japan RIKEN Center for Computational Science (R-CCS) Kobe Hyogo 650-0047 Japan RIKEN Center for Quantum Computing (RQC) Wako Saitama 351-0198 Japan

Frustrated one-dimensional quantum spin systems are known to exhibit a variety of quantum ground states due to the effects of quantum fluctuations and frustrations. In a spin-12 kagome-strip chain, which is one of the frustrated one-dimensional spin systems, many quantum phases have been found. However, the magnetic phase diagrams of the kagome-strip chain under magnetic field have not been fully understood. We construct magnetic phase diagrams at 0, 1/5, 3/10, 1/3, 2/5, 7/15, 3/5, and 4/5 magnetization ratio in the kagome-strip chain and investigate magnetic properties in each phase using the density matrix renormalization group method. We find 15 magnetization-plateau phases, one of which is equivalent to the spin-1 Haldane phase.

关键词： Magnetic phase transitions Magnetism 1-dimensional spin chains Kagome lattice Heisenberg model Quantum spin chains

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：