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检索条件"任意字段=2nd International Conference on Multidisciplinary Engineering and Applied Science, ICMEAS 2023"

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2023 2nd international conference on multidisciplinary engineering and applied science, icmeas 2023

2023 2nd International Conference on Multidisciplinary Engin...

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2nd international conference on multidisciplinary engineering and applied science, icmeas 2023

ISBN: (纸本)9798350358834

The proceedings contain 86 papers. The topics discussed include: malaria disease prediction using frequency-based machine learning algorithms and ensembles algorithms;utilizing earned value management for tracking and predicting the performance of a project at Nile University of Nigeria;overview of Fourier transform infrared (FTIR) spectroscopy for biomass and biofuel characterization;development of a hybrid near field communication payment system for a closed community;modeling and simulation of total attenuation of P2P NLOS 5G and beyond wireless communication systems operating in FR2 bands in Nigeria;microcontroller home-based security reporting system using GPS-enabled technology;and queuing system in e-commerce: an approach to strengthen its security.

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Optimized deep learning models based-sentiment analysis approach for identifying healthcare rumors over social media 2nd

Optimized deep learning models based-sentiment analysis appr...

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2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Kumar, Pramod Vashishtha, Ela Alghayadh, Faisal Yousef Wasim Bhatt, Mohammed Bala, Suchitra Sreejitha, T.S. Computer Science and Technology Ganga Institute of Technology and Management Haryana Kablana Jhajjar India Lead Analytics Texas Health Resources TX United States Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Model Institute of Engineering and Technology J&K Jammu India ICT & Cognitive Systems Sri Krishna Arts and Science College India St. Marys College Thrissur India

ISBN: (纸本)9781032738659

Research the mechanism of fake news refuting rumors in the real social network environment. Propose methods to evaluate the effect of rumor refuting and explore the factors that affect the impact of rumor refuting. Based on the current research results and assumptions, eight factors that affect the effect of rumor refuting are summed up, such as the proportion of the original fake news content. Experiments were conducted based on the rumor-refuting Weibo data. The experimental analysis showed that the proportion of the original fake news in the rumor-refuting information was negatively correlated with the rumor-refuting effect, and the explanation was positively correlated with the rumor-refuting effect suggestions for refuting rumors, including explaining why the original fake news is wrong to guiding social network fake news denying rumors. © 2025 The Author(s).

关键词： Sentiment analysis

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Deep learning-based cognitive digital twin system for wrist pulse diagnostic and classification 2nd

Deep learning-based cognitive digital twin system for wrist ...

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2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Chaudhary, Jitendra Kumar Parimalam, T. Alghayadh, Faisal Yousef Keshta, Ismail Soni, Mukesh Degadwala, Sheshang School of Computing Graphic Era Hill University Bhimtal Campus Uttrakhand India Department of Computer Science Nandha Arts and Science College Tamilnadu Erode India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

In analyzing and recognizing wrist pulse signals, it isn’t easy to mine the nonlinear information of wrist pulse signals using analysis methods such as time and frequency. Traditional machine learning methods require the manual definition of features and cannot perform self-learning of features. A cognitive digital twin technique for pulse analysis and recognition based on threshold-less recursive graph and CNN is proposed. The wrist pulse signal is converted into a threshold-free recursive graph based on the nonlinear dynamics’ theory. The VGG-16 CNN automatically extracts the nonlinear features of the recursive graph, and a pulse condition classification model is established. Experimental finding several that the classification of the proposed method accuracy can reach 98.14%, as compared with the existing pulse classification methods. This study offers a novel concept and strategy for classifying pulse signals, and it has application to the objectification of pulse diagnosis. © 2025 The Author(s).

关键词： Graphic methods

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An optimized CNN-based model for pneumonia detection 2nd

An optimized CNN-based model for pneumonia detection

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2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Sharma, Samridhi Seth, Suditi Rasheed Lone, Faisal Nazir, Azra School of Computer Science & Engineering VIT Bhopal University Madhya Pradesh India

ISBN: (纸本)9781032738659

Convolutional Neural Networks (CNNs) are a breakthrough paradigm shift in medical imaging and diagnostic approaches that can be used to detect pneumonia. CNNs have shown to be incredibly effective at automatically extracting complex and subtle picture features from CT scans and chest X-rays, making them an excellent choice for this task. With the help of deep learning, this initiative aims to improve pneumonia diagnosis accuracy and productivity. Creating an automated system to detect pneumonia is crucial for prompt treatment, especially in remote regions. Given the effectiveness of deep learning, Convolutional Neural Networks (CNNs) are widely recognised for accurately classifying diseases from medical images. The result is a diagnostic tool that may provide quick and precise assessments, giving medical practitioners the power to make educated decisions. This paper employs Transfer Learning and a CNN Model to ascertain the presence of pneumonia in individuals through chest X-ray analysis. The objective is to gain a comprehensive understanding of accurate detection. We built a CNN model from scratch and applied transfer learning to it. Compared to the transfer learning models we used, the CNN model we constructed yielded better results and was more accurate. © 2025 The Author(s)

关键词： Convolutional neural networks

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Exploration of Software Field Engineer Training Based on AI+Capability Model 24

Exploration of Software Field Engineer Training Based on AI+...

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2nd international conference on Advances in Artificial Intelligence and Applications, AAIA 2024

作者： Zhou, Junjie Wu, Qian School of Information Wuhan Software Engineering Vocational College Wuhan Open University Hubei Wuhan China School of Computer Science Wuhan University Hubei Wuhan China Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts Wuhan China

ISBN: (纸本)9798400712883

With the rapid development of artificial intelligence technology, its application in the field of education and teaching is becoming increasingly widespread, bringing revolutionary changes to traditional education models. To cultivate high-quality software vocational skills talents, a digital management platform based on AI+capability model is constructed to explore the innovative application of artificial intelligence in education and teaching, realizing intelligent auxiliary learning functions such as personalized resource recommendation, student growth monitoring, and achievement label portrait. At the same time, a series of intelligent teaching tools such as"AI+Code Generation, AI+Inspection Assistant, AI+Process Map" will be developed to explore and promote the vertical application of big models in talent cultivation. Through innovative models such as"introducing enterprises into education, cultivating students through real-life situations, AI+empowerment, teaching according to students’ aptitude, trinity, innovative training, strengthening processes, and diverse evaluations", it has been fully applied to the talent training scene of software technology field engineers, and its teaching effectiveness is significant. © 2024 Copyright held by the owner/author(s).

关键词： Students

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Full velocity range cross-correlation angiography 2

Full velocity range cross-correlation angiography

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2nd international Academic conference on Optics and Photonics, IACOP 2024

作者： Huang, Haoran Hu, Yudan Lian, Yi Dong, Guanping Wu, Nanshou School of Optoelectronic Engineering Guangdong Polytechnic Normal University China School of Physics and Optoelectronic Engineering Foshan University China School of Information and Electromechanical Engineering Jiangxi Science and Technology Normal University China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong School of Mechanical and Electrical Engineering Jingdezhen Ceramic University China

ISBN: (数字)9781510688827

ISBN: (纸本)9781510688810

In this paper, a full velocity range cross-correlation angiography method is proposed. The time cross-correlation technique is used to estimate the frequency of particle motion, and the maximum value of cross-correlation is used to image the particles with the same motion velocity separately, so as to provide vascular images with different velocities and realize full velocity range angiography. Compared with traditional optical coherence tomography angiography, the method proposed in this paper has higher imaging sensitivity, and can independently image particles with different moving speeds. The wide range of velocity imaging and the higher connectivity of the extracted microvascular network make this method of potential application value for the study of blood flow diseases. © 2025 SPIE.

关键词： Optical coherence tomography

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Tumor microenvironment detection technology based on speckle spectrum contrast OCT 2

Tumor microenvironment detection technology based on speckle...

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2nd international Academic conference on Optics and Photonics, IACOP 2024

作者： Hu, Yudan Wu, Nanshou Jun, Dengli You, Guoping Huang, Haoran School of information and electromechanical engineering Jiangxi Science and Technology Normal University Nanchang330013 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China School of Physics and Optoelectronic Engineering Foshan University Foshan528225 China Key Labotory of Jiangxi Province for Advanced Electronic Materials and Device Jiangxi Science and Technology Normal University Nanchang330013 China

ISBN: (数字)9781510688827

ISBN: (纸本)9781510688810

Tumor growth induces changes in tumor microenvironment, including microvessel density, lymphangion density and lymphangiectasia. Therefore, tumor microenvironment detection is great significance in determining tumor types and evaluating tumor development. Based on speckle spectrum contrast optical coherence tomography (SSC-OCT) technique, this study achieved tumor microenvironment detection function. A mouse ear inoculated with H22 liver cancer cells was used to demonstrate the feasibility and efficiency of this method. The experimental results showed that microvessel and lymphangion density increased with H22 liver tumor growth which leaded to lymphangiectasia. Therefore, this method which provide new methods for clinical detection of tumors, can be used to determine tumor type and to evaluate tumor development trend. © 2025 SPIE.

关键词： Tumors Optical coherence tomography Speckle

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Forward electromagnetic modeling and inverse design of etch cylindrical holes using physics informed neural network 2

Forward electromagnetic modeling and inverse design of etch ...

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2nd international Academic conference on Optics and Photonics, IACOP 2024

作者： Xiao, Li Li, Renxian Tang, Huan Jiao, Yuexiao Shi, Zhuoyuan Zhang, Yuan Wei, Bing Gong, Shuhong Yang, Ruiping Minin, Igor V. Minin, Oleg V. School of Physics Xidian University Xi'an710071 China School of Physics and Electrical Engineering Weinan Normal University Weinan714099 China Siberian State University of Geosystems and Technologies Novosibirsk630108 Russia Novosibirsk Branch of Rzhanov Institute of Semiconductor Physics SBRAS "Technological Design Institute of Applied microelectronics" Lavrentieva ave. 2/1 Novosibirsk630090 Russia

ISBN: (数字)9781510688827

ISBN: (纸本)9781510688810

This paper discusses the forward modeling and inverse design of the electromagnetic scattering characteristics of two-dimensional etched holes in the nanometre band based on the physics-informed neural network (PINNs). This study focuses on the electromagnetic behavior of randomly etched holes at micro- and nanoscales. It presents a novel approach for accurately calculating and optimizing the electromagnetic scattering characteristics of etched holes. This is achieved by skillfully integrating the simplified Finite-Difference-Frequency-Domain (FDFD) difference matrix and PINNs technology. The findings demonstrate the powerful potential and innovative applications of PINNs in solving complex electromagnetic problems. © 2025 SPIE.

关键词： Inverse problems

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A Bibliometric and Social Media Analysis of the Nexus Between Blockchain Technology and Finance 2nd

A Bibliometric and Social Media Analysis of the Nexus Betwee...

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2nd international conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Ayodele, Olamide Emmanuel Ajibade, Temiloluwa Iyanuoluwa Oyebode, Oluwadare Joshua Akintoye, Kayode Akinlekan Ajayi, Babatunde Adedotun Adediran, Anthonia Oluwatosin Ajibade, Samuel-Soma M. Majeed, Anwar P. P. Abdul Luo, Yang Department of Banking and Finance Ekiti State University Ekiti State Ado Ekiti Nigeria Department of Business Management Scholar School System Birmingham United Kingdom Civil and Environmental Engineering Afe Babalola University Ekiti State Ado Ekiti Nigeria Department of Computer Science The Federal Polytechnic Ekiti State Ado Ekiti Nigeria Department of Cyber Security Faculty of Computing and Informatics Ladoke Akintola University of Technology Ogbomoso Nigeria Department of Real Estate Faculty of Built Environment Universiti Malaya KL Kuala Lumpur Malaysia Department of Data Science and Artificial Intelligence Faculty of Engineering and Technology Sunway University Selangor Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkey Suzhou Taicang215400 China

ISBN: (纸本)9789819639489

This study explores Blockchain technology in the global financial industry using trends analysis, bibliometric analysis, and a literature appraisal using Elsevier Scopus data from 2016 to 2023. The Blockchain in Finance (BCF) study produced 185 publications: 53.5% papers, 45.4% conference proceedings, and 1.1% reviews. Analysis of the subject area revealed three important Computer science, engineering, and Decision sciences articles. However, source title analysis showed that ACM international conference Proceeding Series, Sustainability Switzerland, and E3S Web of conferences publish BCF research most often. According to the stakeholders study, Jon M. Truby and Qatar University (Qatar) are the top BCFin researchers and affiliations with 4% and % publications, respectively. China produces the most research on the topic. Due to active support from funding sources like the Chinese National Natural science Foundation (NNSF), 18 publications have been funded. Co-occurrence of keywords The investigation indicated that BCFin’s top keywords include Blockchain, Finance, and Supply Chain Finance. Three clusters with 4–8 keywords, 132 linkages, and 866 TLS were found via cluster analysis. Keywords classify the clusters as Integrated Business Solutions (Cluster 1), Digital Commerce Infrastructure (Cluster 2), and Decentralized Financial Network (Cluster 3). The findings indicate that BCFin is a dynamic and influential multidisciplinary study field. BCFin has transformed the global financial sector by improving trust, transaction security, and communication. It still struggles with interoperability, system integration, and sustainability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decentralized finance

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Fuzzy TOPSIS Method for Resource Planning Selection Incorporating Correlation Measure 2nd

Fuzzy TOPSIS Method for Resource Planning Selection Incorpor...

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2nd international conference on Mathematical Analysis and Applications in Modeling, ICMAAM 2023

作者： Mahapatra, B.S. Golui, S. Mondal, M.K. Bera, M.B. Mahapatra, G.S. School of Applied Science and Humanities Haldia Institute of Technology Haldia721657 India Department of Engineering Sciences and Humanities Siliguri Institute of Technology Siliguri734009 India Department of Mathematics National Institute of Technology Puducherry Karaikal609609 India

ISBN: (纸本)9789819791934

This research offers a distance measure alternative to the TOPSIS approach to solving uncertain multi-criteria decision-making (MCDM) problems. A novel correlation coefficient is proposed, considering the hesitancy function of fermatean fuzzy sets (FFSs) for this purpose. A fermatean fuzzy TOPSIS (F-TOPSIS) method is suggested to solve MCDM problems in uncertain situations using the suggested correlation measure. The proposed F-TOPSIS is demonstrated using the ranking of enterprise resource planning packages for an organization. The sensitivity and comparison analyses are provided to ensure the proposed technique is consistent and robust. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Fuzzy sets

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