检索结果-南通市图书馆

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

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

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

引用

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

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

L1/2正则子在Lq(0 徐宗本1郭海亮1王尧1张海1,2 1. Institute of information and System Science, Xi'an Jiaotong University2. department of Mathematics, Northwest University

引用

自动化学报 2012年第7期 1225-1228页

作者：徐宗本郭海亮王尧张海 Institute of information and System Science Xi’an Jiaotong University department of Mathematics Northwest University

Recently, regularization methods have attracted increasing attention. Lq (0 < q < 1) regularizations were proposed after L1 regularization for better solution of sparsity problems. A natural question is which is the best choice among Lq regularizations with all q in (0, 1)? By taking phase diagram studies with a set of experiments implemented on signal recovery and error correction problems, we show the following: 1) As the value of q decreases, the Lq regularization generates sparser solution. 2) When 1/2 ≤ q < 1, the L1/2 regularization always yields the best sparse solution and when 0 < q ≤ 1/2, the performance of the regularizatons takes no significant difference. Accordingly, we conclude that the L1/2 regularization can be taken as a rep- resentative of Lq (0 < q < 1) regularizations.

关键词： Lq regularization phase diagram signal recovery error correction

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Molecular simulation study of the microstructures and properties of pyridinium ionic liquid[HPy][BF_(4)]mixed with acetonitrile

引用

原子与分子物理学报 2025年第4期42卷 27-32页

作者： XU Jian-Qiang MA Zhao-Peng CHENG Si LIU Zhi-Cong ZHU Guang-Lai department of Physics School of Physics and Electronic InformationAnhui Normal UniversityWuhu 241002China

The microstructures and thermodynamic properties of mixed systems comprising pyridinium ionic liquid[HPy][BF_(4)]and acetonitrile at different mole fractions were studied using molecular dynamics simulation in this *** following properties were determined:density,self-diffusion coefficient,excess molar volume,and radial distribution *** results show that with an increase in the mole fraction of[HPy][BF_(4)],the self-diffusion coefficient ***,the excess molar volume initially decreases,reaches a minimum,and then *** rules of radial distribution functions(RDFs)of characteristic atoms are *** increasing the mole fraction of[HPy][BF_(4)],the first peak of the RDFs of HA1-F decreases,while that of CT6-CT6 rises at first and then *** indicates that the solvent molecules affect the polar and non-polar regions of[HPy][BF_(4)]differently.

关键词： Pyridinium ionic liquids Thermodynamic properties Molecular dynamics simulation Radial distribution functions

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Small cell lung cancer with peripheral neuropathy as the first symptom:Two case reports

引用

World Journal of Clinical Cases 2025年第9期13卷 30-40页

作者： Man Luo Xiao-Xi Lu Dan-Yang Meng Jin Hu department of Neurology Affiliated Hospital of Jiaxing UniversityJiaxing 314000Zhejiang ProvinceChina department of information Technology Affiliated Hospital of Jiaxing UniversityJiaxing 314000Zhejiang ProvinceChina

BACKGROUND Small cell lung cancer(SCLC)is the most malignant type of lung *** in the latent period and early stage of the tumor,SCLC is prone to produce distant metastases with complex and diverse clinical *** is most closely related to paraneoplastic syndrome,and some cases present as paraneoplastic peripheral neuropathy(PPN).PPN in SCLC appears early,lacks specificity,and often occurs before diagnosis of the primary *** is easy to be misdiagnosed as a primary disease of the nervous system,leading to missed diagnosis and delayed diagnosis and *** SUMMARY This paper reports two cases of SCLC with limb weakness as the first *** first symptoms of one patient were rash,limb weakness,and abnormal *** patient was repeatedly referred to the hospital for limb weakness and rash for>1 year,during which time,treatment with hormones and immunosuppressants did not lead to significant improvement,and the condition gradually *** patient was later diagnosed with SCLC,and the dyskinesia did not worsen as the dermatomyositis improved after antineoplastic and hormone *** second case presented with limb numbness and weakness as the first symptom,but the patient did not pay attention to ***,the patient was diagnosed with SCLC after facial edema caused by tumor thrombus invading the ***,he was diagnosed with extensive SCLC and died 1 year after *** The two cases had PPN and abnormal electromyography,highlighting its correlation with early clinical indicators of SCLC.

关键词： Paraneoplastic peripheral neuropathy Small cell lung cancer Peripheral neuropathy Electromyography Dermatomyositis Case report

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Ru/NiMnB spherical cluster pillar for highly proficient green hydrogen electrocatalyst at high current density

引用

Journal of Energy Chemistry 2025年第01期 397-408页

作者： Md Ahasan Habib Shusen Lin Mehedi Hasan Joni Sumiya Akter Dristy Rutuja Mandavkar Jae-Hun Jeong Jihoon Lee department of Electronic Engineering College of Electronics and Information Kwangwoon University

Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen ***,Ru/NiMnB spherical cluster pillar （SCP）,denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal *** investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic *** Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm2in 1 M KOH,making them highly competitive with state-of-the-art ***,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm2in 1 M KOH,outperforming the standard benchmark electrodes of RuO2||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional *** SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm2high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial *** a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction ***,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H2production.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

The Relation of department Components and Activity in Spatial information Infrastructure

引用

Wuhan University Journal of Natural Sciences 2001年第Z1期6卷 460-466页

作者： Yi Shan zhen 1, Zhou Li zhu 1,Cheng Ji cheng 2, Li Qi 2 1.department of Computer Science and Technology,Tsinghua University, Beijing 100084, China 2.Institute of Remote Sensing and Geographical information System,Peking University,Beijing 1008 department of Computer Science and Technology Tsinghua University Beijing 100084 China

Spatial information Infrastructure (SII) facilitates the sharing, interoperability and integration of geographical information among department components of a region or a country. The SII is developed and shared by different department components. The relation of department components is a fundament for collaborating tasks and information exchange in SII. There are two kinds of department components, one is the provider which produces geospatial data of SII, other is the consumer which uses geospatial data of SII. The consumer includes two kinds of user, one is the user which only uses and does not produce geospatial data in SII, other is the special user which not only uses but also produces geospatial data in SII. The provider includes different hierarchies corresponding to different kinds of geospatial data in SII. All providers in the hierarchies form provider actor set PA. All consumers also form consumer actor set CA. The sender recipient relation SR and SRI are defined on Cartesian product of PA and CA. Five tasks and information flow in SII demonstrate the geospatial data acquisition, information production, management, and application among department components. The tasks and their sub tasks are subdivided activities. Each activity corresponds to the relation SR or RSI. The activity along with the relation of provider and consumer forms a scheme of geographical information exchange between department components.

关键词： geographical information exchange relation activity information infrastructure

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Unraveling the mechanism of action of Shangxia Liangji formula for treating insomnia:a metabolomics and network pharmacology approach

引用

Traditional Medicine Research 2025年第2期10卷 16-29页

作者： Xia-Jie Quan Hao Liang Yong-Hong Tang Li Jiang Xiong-Ying Ji Feng-Ying Zhang Ping Zhang Bo Ouyang department of information The Affiliated Nanhua HospitalHengyang Medical SchoolUniversity of South ChinaHengyang 421002China department of Neurology The Affiliated Nanhua HospitalHengyang Medical SchoolUniversity of South ChinaHengyang 421002China department of Gastroscopy The Affiliated Nanhua HospitalHengyang Medical SchoolUniversity of South ChinaHengyang 421002China department of Traditional Chinese Medicine The Affiliated Nanhua HospitalHengyang Medical SchoolUniversity of South ChinaHengyang 421002China

Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of ***,the specific mechanism of action of SXLJF remains ***:The mouse model of insomnia was established by intraperitoneal injection of ***-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive *** open field test and pentobarbital-induced sleeping test were ***-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating ***,key targets were validated using ***:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep *** and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of ***,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,***-qPCR results supported the role of TH in the mechanism of SXLJF in treating ***:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.

关键词： Shangxia Liangji formula insomnia metabolomics network pharmacology tyrosine hydroxylase tyrosine metabolism

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Modified Multivariate Process Capability Index Using Principal Component Analysis

引用

Chinese Journal of Mechanical Engineering 2014年第2期27卷 249-259页

作者： ZHANG Min WANG G Alan HE Shuguang HE Zhen department of Industrial Engineering Tianjin University department of Business information Technology department of information Management and Management Science Tianjin University

The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.

关键词： process capability index multivariate specification region principal component analysis confidence interval

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

引用

Computer Modeling in Engineering & Sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data Science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics Engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia department of Computer Science and information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：