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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea department of Computer Science and information systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia department of Computer Engineering and information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

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An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas department of information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

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Tracking the Moisture Sources of an Extreme Precipitation Event in Shandong,China in July 2007:A Computational Analysis

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Journal of Meteorological Research 2014年第4期28卷 634-644页

作者：张弛李琦 Institute of Remote Sensing and geographical information systems Peking University

This paper utilizes a modified Water Accounting Model （WAM） to track the moisture sources of an extreme precipitation event in Shandong during 18-20 July 2007. It is found that different methods in dealing with the residual of the water budget always produce different results in moisture recycling calculations. In addition, results from the backward tracking without the residual are in complete agreement with those from the forward tracking with the residual, and vice versa, implying a mathematical consistency. We thus analyze and derive the conditions under which the two tracking approaches equate with each other. We applied the backward tracking to the Shandong extreme rainfall case and obtained quantitative estimates of moisture contributions of three selected regions away from the rainfall area. The results indicate that the spatial pattern rather than numerical value of the recycling moisture is more reliable in tracking the moisture sources. The moisture of this Shandong rainfall event comes mostly from the nearby upwind area in Southwest China, which is of the terrestrial origin; while the moisture originating from the neighboring West Pacific contributes little to this event.

关键词： bulk model precipitation recycling moisture recycling backward tracking

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A semantic geographical knowledge wiki system mashed up with Google Maps

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Science China(Technological Sciences) 2010年第S1期53卷 52-60页

作者： GAO Yong,GAO Song,LI RunQiang & LIU YuInstitute of Remote Sensing and geographical information systems,Peking University,Beijing 100871,China 1. Institute of Remote Sensing and geographical information systems Peking University Beijing 100871 China

A wiki system is a typical Web 2.0 application that provides a bi-directional platform for users to collaborate and share much useful information ***,computers cannot well understand the wiki pages in plain *** user-generated geographical content via wiki systems cannot be manipulated properly and efficiently unless the geographical semantics is explicitly *** this paper,a geographical semantic wiki system,Geo-Wiki,is introduced to solve this ***-Wiki is a semantic geographical knowledge-sharing web system based on geographical ontologies so that computers can parse and storage the multi-source geographical ***,Geo-Wiki mashed up with map services enriches the representation and helps users to find spatial distribution patterns,and thus can serve geospatial decision-making by customizing the Google Maps APIs.

关键词： geo-ontology semantic wiki mashup Google Maps

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Core or edge? Revisiting GIScience from the geography-discipline perspective

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Science China Earth Sciences 2022年第2期65卷 387-390页

作者： Yu LIU Institute of Remote Sensing and geographical information systems School of Earth and Space SciencesPeking UniversityBeijing 100871China

As an inter-disciplinary area between geography and computer sciences, geographical information science(GIScience) inherits the spatial analysis tradition of the former. Together with other branches of information geography, it seeks the balance between universality and particularity of geographical laws by combining methods from neighboring disciplines(such as big data and artificial intelligence) with the special nature of geographical spaces. Meanwhile, at the core position of the geography discipline, GIScience makes geography stronger from two directions: "strengthening the theoretical foundation" and "improving technology and promoting the practical applications".

关键词： geographical information science information geography Geography Characteristics of geographical spaces

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Framework and development of digital China

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Science China(Technological Sciences) 2008年第S1期51卷 1-5页

作者： WU Lun & TONG QingXi Institute of Remote Sensing and geographical information systems,Peking University,Beijing 100871,China 1. Institute of Remote Sensing and geographical information systems Peking University Beijing 100871 China

Digital China (DC) has recently drawn much attention. It is a strategic project for China in response to the challenge of sustainable development of population,re-source,and environment. Intending to establish the national information infra-structure (NⅡ),the DC project forms a solid foundation for Chinese informatization. In such an NⅡ,multi-sourced spatial data are integrated. They focus on various themes and have different space and time features. Based on the NⅡ,numerous applications and services can be developed so that spatial information will benefit everyone. Since lots of organizations,such as governments,universities,and en-terprises,are involved in the implementation of DC,the DC project will significantly prompt the relevant scientific research as well as economic progress in China.

关键词： Digital Earth Digital China spatial information sciences and technology

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GIS-based cost distribution analysis of new consumer connections to an urban power grid

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Geo-Spatial information Science 2015年第4期18卷 183-192页

作者： Sergey V.KOSYAKOV Artur M.SADYKOV department of Software Engineering Ivanovo State Power Engineering UniversityIvanovoRussia department of geographical information systems Ivanovo State Power Engineering UniversityIvanovoRussia

In this paper,we propose a method of cost distribution analysis of new consumer connections to a city power grid by accounting for spatial restrictions and characteristics of existing *** practice,the calculation of connection costs for each new consumer includes the network design and financial *** suggest that connection costs should be calculated for the whole city based on the normative parameters at the stage when the object location is selected by investors and when power grid development is planned by power *** proposed method enables the modeling of new power line connection routes from every parcel of city land to possible points of connection to the operating networks based on the raster design of the *** optimal path is chosen by one criterion consisting of two components:the costs of both laying new power lines and providing sufficient power reserve in the chosen network connection *** as a computer program,the method has been used to calculate the costs of connections to low-voltage power lines.

关键词： GIS least-cost path analysis grid-connections urban power grid

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Harmonisation requirements and capabilities towards a European spatial data infrastructure (ESDI): the HUMBOLDT protected areas scenario

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International Journal of Digital Earth 2012年第5期5卷 417-438页

作者： Paolo Villa Roderic Molina Mario A.Gomarasca Emanuele Roccatagliata CNR-IREA Institute for Electromagnetic Sensing of the EnvironmentMilanoItaly GISIG Geographical Information Systems International GroupGenovaItaly

The HUMBOLDT project has the aim of implementing a Framework for harmonisation of data and services in the geoinformation domain,under the Infrastructure for Spatial information in Europe(INSPIRE)Directive and in the context of the Global Monitoring for Environment and Security(GMES)*** two-pronged approach of HUM BOLDT comprises a technical side of software framework development and an application side of scenario testing and *** the HUMBOLDT Application Scenarios designed to demonstrate the capabilities of the Framework there is the one covering Protected Areas themes and use cases It aims to transform geoinformation,managed by park authorities,into a seamless flow that com bines multiple information sources from different governance levels(European,national,regional),and exploits this newly combined information for the purposes of planning,management and tourism *** Scenario constitutes a step further towards the integration of monitoring systems envisaged in the view of Digital *** Areas Scenario creates an examples of the use of the HUMBOLDT tools in Desktop and Web GIS environment,together with setting up a server environment exploiting HUMBOLDT harmonisation framework as taking into account user require-ments and needs and providing benefits for making the road to ESDI establish-ment easier.

关键词： data harmonisation geoinformation integration INSPIRE Digital Earth ESDI protected areas geo-spatial science spatial data infrastructure

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Fully Automated Density-Based Clustering Method

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Computers, Materials & Continua 2023年第8期76卷 1833-1851页

作者： Bilal Bataineh Ahmad A.Alzahrani information systems department College of Computers and Information SystemsMakkahSaudi Arabia

Cluster analysis is a crucial technique in unsupervised machine learning,pattern recognition,and data ***,current clustering algorithms suffer from the need for manual determination of parameter values,low accuracy,and inconsistent performance concerning data size and *** address these challenges,a novel clustering algorithm called the fully automated density-based clustering method(FADBC)is *** FADBC method consists of two stages:parameter selection and cluster *** the first stage,a proposed method extracts optimal parameters for the dataset,including the epsilon size and a minimum number of points *** parameters are then used in a density-based technique to scan each point in the dataset and evaluate neighborhood densities to find *** proposed method was evaluated on different benchmark datasets andmetrics,and the experimental results demonstrate its competitive performance without requiring manual *** results show that the FADBC method outperforms well-known clustering methods such as the agglomerative hierarchical method,k-means,spectral clustering,DBSCAN,FCDCSD,Gaussian mixtures,and density-based spatial clustering *** can handle any kind of data set well and perform excellently.

关键词： Automated clustering data mining density-based clustering unsupervised machine learning

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The vegetation feature and palaeoenvironment significance in the mountainous interior of southern China from the Last Glacial Maximum

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Science China Earth Sciences 2018年第1期61卷 71-81页

作者： XIAO JiaYi SHANG ZhiYuan SHU Qiang YIN JianJi WU XiaoShuang Jiangsu Center for Collaborative Innovation in geographical information Resource Development and Application Nanjing Normal University School of geographical Sciences Nanjing Normal University

Palynological records were selected from the profiles of three research sites in the mountainous interior of southern China(Dajiuhu at Shennongjia in the western part of Hubei Province, Dahu in the Nanling Mountains, and Gantang in the northern part of Fujian Province). It can be inferred that the forest vegetation growing in the south of the Qinling Mountains-Huaihe River was luxuriant during the late glaciation. The species succession with ecological significance in palaeoflora(Abies sp., Fagus sp. and Alnus sp.) revealed that there was a certain amount of precipitation and effective humidity in the mountain lands between Qinling Mountains-Huaihe River and Nanling Mountains. This ecological environment favored the zonal distribution of mountainous forest vegetation. The late glacial maximum featured a cold, wet climate that completely differed from the cold-dry climate on the Loess Plateau, and on the steppe and desert steppe of the Qinghai-Tibet Plateau. Besides being influenced by the predominant factors driving the Northern Hemisphere climate, the cold-wet climate feature of the mountainous interior of southern China was closely associated with some geographical factors such as the latitudinal position, proximity to the ocean, and the topography and landforms.

关键词： Southern China Mountainous vegetation Last Glacial Period Pollen record Palaeoenvironment

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