检索结果-内蒙古大学图书馆

Analysis of Variance Application in the Construction of Classifier Ensemble Based on Optimal Feature Subset for the Task of Supporting Glaucoma Diagnosis 21st

Analysis of Variance Application in the Construction of Clas...

引用

21st International Conference on Computational science, ICCS 2021

作者： Sulot, Dominika Zyblewski, Pawel Ksieniewicz, Pawel Department of Biomedical Engineering Wroclaw University of Science and Technology Wroclaw Poland Department of Systems and Computer Networks Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9783030779665

The following work aims to propose a new method of constructing an ensemble of classifiers diversified by the appropriate selection of the problem subspace. The experiments were performed on a numerical dataset in which three groups are present: healthy controls, glaucoma suspects, and glaucoma patients. Overall, it consists of medical records from 211 cases described by 48 features, being the values of biomarkers, collected at the time of glaucoma diagnosis. To avoid the risk of losing information hidden in the features, the proposed method – for each base classifier – draws a separate subset of the features from the available pool, according to the probability determined by the anova test. The method was validated with four base classifiers and various subspace sizes, and compared with existing feature selection methods. For all of the presented base classifiers, the method achieved superior results in comparison with the others. A high generalization power is maintained for different subspace sizes which also reduces the need to optimize method hyperparameters. Experiments confirmed the effectiveness of the proposed method to create an ensemble of classifiers for small, high-dimensional datasets. © 2021, Springer Nature Switzerland AG.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Metagenomic Data Analysis with Machine Learning to Discover Colorectal Cancer-Associated Enzymes

Metagenomic Data Analysis with Machine Learning to Discover ...

引用

IEEE Signal Processing and Communications Applications (SIU)

作者： Nur Sebnem Ersoz Cihan Kuzudisli Malik Yousef Burcu Bakir-Gungor Department of Bioengineering Faculty of Life and Natural Science Abdullah Gul University Kayseri Turkey Department of Computer Engineering Faculty of Engineering Hasan Kalyoncu University Gaziantep Turkey Department of Information Systems Galilee Digital Health Research Center Zefat Academic College Zefat Israel Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri Turkey

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

The human gut microbiome comprises over 10 trillion microbes and plays important roles in maintaining metabolism, body homeostasis, impacting immune function. Metagenomics which studies genomic data from clinical and environmental samples is crucial in understanding the interplay between the host and the gut microbiome. Recently, functional profiling of metagenomes helps to identify alterations in microbial functions, particularly enzyme-encoding genes. Colorectal cancer (CRC) is known as one of the leading causes of cancer-related deaths. In this study, we aimed to find the CRC-associated enzymes by analyzing metagenomic data with different machine learning methods. A total of 1262 samples including CRC and control groups from different countries were used in this study. This dataset was obtained by functionally profiling metagenomics data and estimating community level enzyme commission (EC) abundance values. For the analysis of this dataset, RCE-IFE and SVM-RCE machine learning methods, which are group-based feature selection methods, were compared with 6 different individual feature selection methods. 10 times Monte-Carlo Cross Validation was used in our experiments. It was observed that RCE-IFE, Extreme Gradient Boosting and Select K Best methods similarly provided the best performances. Especially in this study, besides the its high performance, the group-based feature selection method RCE-IFE grouped enzymes into clusters unlike TFS, and then identified biologically relevant CRC-associated enzymes.

关键词： Enzymes Metagenomics Microorganisms Monte Carlo methods Colorectal cancer Signal processing Homeostasis

来源：评论

学校读者我要写书评

暂无评论

A Refractive Distortion Correction Method for 3D Root Reconstruction 6

A Refractive Distortion Correction Method for 3D Root Recons...

引用

6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Li, Mu-Wei Wu, Po-Lung Lo, Shuen-Fang Chan, Yung-Kuan Yu, Shyr-Shen National Chung Hsing University Department of Computer Science and Engineering Taichung40227 Taiwan Ling Tung University Department of Digital Content Design Taichung40852 Taiwan National Chung Hsing University Biotechnology Center Taichung40227 Taiwan National Chung Hsing University Department of Management Information Systems Taichung40227 Taiwan

ISBN: (纸本)9798350301953

Measurement of plant root system architecture (RSA) traits is an important task for botany. Usually, the botanists put the plants in a transparent gel container for easy observation. Under this configuration, an easy-to-use way to measure RSA traits is to take images for observation. However, in single-view-angle 2D image often has problems such as occlusion and lack of depth information, so it is not convenient for measurement. Therefore, the reconstruction of the 3D root model from multi-view-angle images is a better solution. Under the above-mentioned planting configuration, the refractive distortion problem usually arises. This will lead to serious distortion of model reconstruction, so in this paper, a method based on ray tracing for correcting refraction distortion of objects in cylindrical containers is proposed. © 2023 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

An Advanced Data Fabric Architecture Leveraging Homomorphic Encryption and Federated Learning

arXiv

引用

arXiv 2024年

作者： Rieyan, Sakib Anwar News, Raisul Kabir Muntasir Rahman, A.B.M. Khan, Sadia Afrin Jawad Zaarif, Sultan Tasneem Alam, Golam Rabiul Hassan, Mohammad Mehedi Ianni, Michele Fortino, Giancarlo Department of Computer Science and Engineering School of Data and Sciences BRAC University 66 Mohakhali Dhaka1212 Bangladesh Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Department of Informatics Modeling Electronics and Systems University of Calabria CS Rende87036 Italy

Data fabric is an automated and AI-driven data fusion approach to accomplish data management unification without moving data to a centralized location for solving complex data problems. In a Federated learning architecture, the global model is trained based on the learned parameters of several local models that eliminate the necessity of moving data to a centralized repository for machine learning. This paper introduces a secure approach for medical image analysis using federated learning and partially homomorphic encryption within a distributed data fabric architecture. With this method, multiple parties can collaborate in training a machine-learning model without exchanging raw data but using the learned or fused features. The approach complies with laws and regulations such as HIPAA and GDPR, ensuring the privacy and security of the data. The study demonstrates the method’s effectiveness through a case study on pituitary tumor classification, achieving a significant level of accuracy. However, the primary focus of the study is on the development and evaluation of federated learning and partially homomorphic encryption as tools for secure medical image analysis. The results highlight the potential of these techniques to be applied to other privacy-sensitive domains and contribute to the growing body of research on secure and privacy-preserving machine learning. © 2024, CC BY.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

FFNET: An End-To-End Framework Based on Feature Pyramid Network and Filter Network for Pulmonary Nodule Detection

FFNET: An End-To-End Framework Based on Feature Pyramid Netw...

引用

IEEE International Symposium on Biomedical Imaging

作者： Xiaoxi Lu Na Zeng Xingyue Wang Jingqi Huang Yan Hu Jiansheng Fang Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China CVTE Research Guangzhou China

Accurate nodule detection with high sensitivity is essential for early lung cancer diagnosis. Focusing on small nodule detection, we propose an end-to-end framework, which includes a backbone, a candidate detection network, and a filter network. The backbone learns multi-layer features so that the region proposal network with feature pyramid structure detects nodules of various sizes, especially small ones. Moreover, the filter net is designed to further classify the proposals with low confidence, which utilizes the decoupled feature maps to make the features of nodules more discriminative. We validate our framework on the LUNA16 dataset. The results show that our framework detects more small nodules, and achieves a comparable performance with other CAD systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effect of Environment Temperature and Relative Humidity on Thermal Emissivity: Study Case of Mango Fruit 22

Effect of Environment Temperature and Relative Humidity on T...

引用

22nd IEEE International Symposium on Intelligent systems and Informatics, SISY 2024

作者： Sirisomboon, Panmanas Sripinyowanich Jongyingcharoen, Jiraporn Junto, Apiwat Phanomsophon, Thitima Dachoupakan Sirisomboon, Cheewanun Rerngsamran, Panan Pokhrel, Dharma Raj Sharma, Sneha Posom, Jetsada Pornchaloempong, Pimpen Terdwongwarakul, Anupun Chongstitvatana, Prabhas School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Agricultural Engineering Bangkok Thailand School of Engineering and Innovation Rajamangala University of Technology Tawan-Ok Department of Agricultural Engineering Chon Buri Thailand School of Agricultural Technology King Mongkut's Institute of Technology Ladkrabang Office of Administrative Interdisciplinary Program on Agricultural Technology Bangkok Thailand Chulalongkorn University Faculty of Science Department of Microbiology Bangkok Thailand University of Melbourne Department of Infrastructure Engineering Victoria Australia Khon Kaen University Faculty of Engineering Department of Agricultural Engineering Khon Kaen Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Food Engineering Bangkok Thailand Kasetsart University Faculty of Engineering at Kanpangsan Department of Agricultural Engineering Thailand Chulalongkorn University Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350385601

This research was to study the effect of the environment condition during image captured including temperature and relative humidity in the packaging house of the mango exporting factory and in the orchard on the emissivity of mango fruit. The result showed that in the controlled environment of the packaging house in factory, the emissivity was increased (the mango emitted more energy) when the surface temperature was lower and the emissivity of mango is 0.71-0.84 and in the uncontrolled environment of open-air packaging yard in the mango orchard, the different transpiration rates of mango effected mainly by ambient temperature and relative humidity make the morning condition emissivity of 0.44-0.66 and the afternoon condition of 0.72-0.98. There was the effect of the different measured positions on the fruits where the physiology was different and the fluctuated environment in the latter condition made the wide range of emissivity of mangoes. This indicated the shortcoming of thermal imaging of horticultural product if the correct emissivity varied and difficult to set in the thermal camera setting, hence the inaccurate thermogram to be obtained. © 2024 IEEE.

关键词： Fruits

来源：评论

学校读者我要写书评

暂无评论

Controllable Structure Planning for Energy Internet

Controllable Structure Planning for Energy Internet

引用

Cyber-Energy systems and Intelligent Energy (ICCSIE), International Conference on

作者： Yushuai Li Tianyi Li Yonghao Gui David Wenzhong Gao Yan Zhang Department of Informatics University of Oslo Oslo Norway Department of Computer Science Aalborg University Aalborg Denmark Department of Electronic Systems Aalborg University Aalborg Denmark Department of Electrical and Computer Engineering University of Denver Denver USA

Secure system operations rely on reliable network structures. The loss of controllability may be the main reason to cause cascaded failures for complex network, e.g., Energy Internet (EI). However, the existing studies do not consider the network controllability to guide the system reconfiguration. To address this issue, the paper proposes a new structuring planning method for EI with consideration of controllability and economy. Firstly, the structure planning problem is modeled as a dynamic optimization problem with the tradeoff objectives of maximum social welfare and minimum driven nodes for long-term period. Then, a mixed maximum matching and deep deterministic policy gradient method is presented to obtain the approximate optimal planning solution with strong adaptability. Finally, simulation results demonstrate the effectiveness of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Control-oriented modeling and passivity analysis of thermal dynamics in a multi-producer district heating system

引用

IFAC-PapersOnLine 2023年第1期56卷 175-180页

作者： Saeed Ahmed Juan E. Machado Michele Cucuzzella Jacquelien M.A. Scherpen Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen 9747 AG Groningen The Netherlands Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

Climate change and geopolitics have led to the conception of plans for reducing greenhouse gas emissions and improving the sustainability of existing fossil-based energy systems. In this respect, district heating has been identified as an indispensable player for its potential to integrate seamlessly environmentally-friendly heat sources. To improve the efficiency of these district heating systems, optimal operation schemes can be devised and enforced through control systems. To this end, we present a control-oriented nonlinear ODE-based model of temperature dynamics in a multi-producer district heating system. The model features a modular design and comprises the thermal dynamics of heat exchangers of producers and consumers interconnected by a distribution network of meshed topology. Then, we establish passivity properties and zero-state detectability for the modeled temperature dynamics that could be exploited for controller design and solving constrained optimization problems.

关键词： District heating thermal dynamics Krasovskii passivity shifted passivity zero-state detectability

来源：评论

学校读者我要写书评

暂无评论

Merging UAV-Derived Metrics with Crop Physiology to Estimate Sunflower Yield

Merging UAV-Derived Metrics with Crop Physiology to Estimate...

引用

Frontiers of Information Technology (FIT)

作者： Usama Athar Muhammad Ali Zuhair Zafar Haris Khurshid Karsten Berns Muhammad Moazam Fraz School of Electrical Engineering and Computer Science National University of Sciences and Technology (NUST) Islamabad Pakistan Oilseeds Research Program National Agricultural Research Center (NARC) Islamabad Pakistan Department of Computer Science Rheinland-Pfälzische Technische Universität Kaiserslautern Germany

ISBN: (数字)9798331510503

ISBN: (纸本)9798331510510

Accurate and timely estimation of sunflower yield is crucial for agricultural researchers, farmers, and breeders. Use of Unmanned Aerial Vehicles (UAVs) with multi-spectral sensors has been adopted to meet the need for precise sunflower seed yield predictions. This study proposes a combined approach that integrates 12 remotely sensed vegetation indices (VIs) with 3 key physiological traits - fresh weight, dry weight, and moisture factor - to capture the complex dynamics affecting sunflower crop. Predictive performance of VIs alone and in combination with physiological traits is evaluated using Root Mean Squared Error (RMSE). Our results show that incorporating these two sets of features, along with their temporal, spectral, and statistical characteristics, leads to consistent improvements in sunflower seed yield estimation that can reduce the root mean squared error to as low as 0.4075 ( $\text{kg} / \text{plot}$ ).

关键词： Vegetation mapping Moisture Autonomous aerial vehicles Physiology Seeds (agriculture) Sensors Yield estimation Reliability Vehicle dynamics Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Queue Management Priority-Based Traffic engineering Method 9

Queue Management Priority-Based Traffic Engineering Method

引用

9th IEEE International Conference on Problems of Infocommunications science and Technology, PIC S and T 2022

作者： Lemeshko, Oleksandr Yeremenko, Oleksandra Persikov, Anatoliy Yevdokymenko, Maryna Mersni, Amal Harkusha, Serhii Kharkiv National University of Radio Electronics V.V. Popovskyy Department of Infocommunication Engineering Kharkiv Ukraine International University of Sarajevo Department of Engineering Computer Sciences and Engineering Program Sarajevo Bosnia and Herzegovina Poltava University of Economics and Trade Department of Document Studies and Information Activities in Economic Systems Poltava Ukraine

ISBN: (纸本)9798350398915

The work proposes the improvement of queue management priority-based Traffic engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calculations is responsible, firstly, for the distribution and aggregation of packet flows between the macro queues and sub-queues organized on the router interface (congestion management task), and, secondly, for the balanced distribution of interface bandwidth among sub-queues, weighted relative to their priorities (resource allocation task). The upper level of the method's calculations is accountable for distributing the interface's bandwidth between macro queues by performing the iterative procedure. The numerical research results of the proposed two-level queue management method confirmed its effectiveness in ensuring high scalability, balanced priority- based distribution of packet flows and interface bandwidth between the macro queues and sub-queues organized on it. The method demonstrated high coordination procedure convergence and the final quality of centralized calculations. © 2022 IEEE.

关键词： Bandwidth

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：