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Ensemble methods-based comparative study of Landsat 8 operational land imager (OLI) and sentinel 2 multi-spectral images (MSI) for smart farming crop classification

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Multimedia Tools and Applications 2025年第17期84卷 18025-18068页

作者： Gupta, Priyanka Gupta, Prateek Singh, Suraj Kumar Thakur, Bhavna Kumar, Manoj Suresh Gyan Vihar University Jaipur India School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of Centre for Sustainable Development Suresh Gyan Vihar University Jaipur India School of Agriculture & Allied Science DBS Global University Dehradun India School of Computer Science FEIS University of Wollongong in Dubai Dubai Knowledge Park Dubai United Arab Emirates MEU Research Unit Middle East University Amman Jordan

Agriculture has a significant worldwide impact in terms of generating employment opportunities and stimulating economic growth. In India, agriculture plays a crucial role in development of food sources, boost up individual income of farmer and employment of the whole country. In the agriculture domain, meticulous machine learning-enabled crop classification is essential for production. Nowadays, for meticulous crop classification satellite images are used together with Geographical Information System (GIS) and remote sensing. Proposed ensemble methods are commonly used to estimate and examine the accomplishment of advanced machine learning concepts in the remote sensing community. In this paper, authors describe a framework with the combination of Support vector machine (SVM), Decision tree (DT), K-nearest neighbor (KNN), and Random forest (RF) and proposed ensemble method named as "SVM-DT-KNN-RF" that investigates the potential of crop mapping used to compare different architectures of machine learning as logistic regression (LR), RF, DT, KNN, SVM, bagging as well as boosting. The classifiers are tested on two remotely sensed datasets, one is Landsat 8 OLI (L8) and another is Sentinel 2 MSI (S2). The three primary findings based on our experiments are first, voting model proved to be the most accurate classifier. Second, bagging and boosting offer good accuracy in classification results. Finally, the results with two satellites i.e., S2 as well as L8 are compared. In the S2 dataset, the proposed ensemble method with a combination of two models i.e., SVM-DT, SVM-KNN and SVM-RF gave 89.1%, 89.8% and 89.7% results respectively, and the combination of four models i.e., SVM-DT-KNN-RF (for voting) is the better performer with 91.10% accuracy. In the L8 dataset, the proposed ensemble method which combines all four techniques SVM-DT-KNN-RF gave better results with a score of 90% while the worst performance was achieved by the decision tree with 79.58% accuracy. For KNN, th

关键词： Landsat

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Social Media Sentiment Analysis for Airline Customer Satisfaction 3

Social Media Sentiment Analysis for Airline Customer Satisfa...

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Chaudhary, Shivani Garg, Khushi Gupta, Purnima Dwivedi, Anshu Kumar Adhyatmik Nagar Ghaziabad India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (纸本)9798331519582

Among the most important subfields in natural language processing, one of the fields is sentiment analysis. Sentiment analysis focuses on recognizing and estimating emotions in text. It has gained more importance in aviation in the sense that it can present insights into customer satisfaction and brand reputation as well as operational efficiency. This work investigates the topic of the sentiment analysis of the Twitter US Airline Sentiment Dataset: more than 14,000 tweets regarding the major US airlines labelled as positive, neutral, or negative. By such approaches documented in the literature, challenges consisting of the noise and subtlety of sentiment in the given data largely remain unsolved. To address these deficiencies, this research will use the machine learning techniques in the form of Naive Bayes and Random Forest models, classifying sentiments by methods like class imbalances through SMOTE, and using TF-IDF vectorization in extracting features. Results for the experiment showed that the Random Forest model outperforms Naive Bayes as the former can classify more neutral and positive sentiments correctly. It is, therefore, concluded that sentiment analysis may be useful to airlines for enhancement in customer experience and future research should emphasize on advanced deep learning models with rich data sets for further potential enhancement. © 2025 IEEE.

关键词： Emotion Recognition

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Temporal Community Analysis Using Centrality Measures

Temporal Community Analysis Using Centrality Measures

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2024 IEEE Conference on engineering Informatics, ICEI 2024

作者： Rajeshkumar, Deepak Jaysankar, Pranav Yookeesh, M.R Sree Padma Chandrasekaran, Balaji Girijakumari, Smrithy Anna University College of Engineering Guindy Department of Computer Science and Engineering Chennai India Vellore Institute of Technology Sreekanatan Nair School of Computer Science and Engineering Chennai Campus Chennai India

ISBN: (纸本)9798331505776

This research explores temporal community detection to identify patterns in course grading and offerings at The university of Illinois from Spring 2010 to Spring 2020. Using a dataset that includes course grades, subject codes, instructors, and student enrolment, the study applies four community detection algorithms - Greedy Modularity, Louvain, Leiden, and Walktrap - to examine how courses group based on grading similarities over time. The data is pre-processed, split into time slices, and represented as graphs where nodes are courses and edges are weighted by cosine similarity of grading patterns. Key metrics such as modularity, community size, edge density, overlap, and persistence are used to evaluate algorithm performance. The results provide insights into the evolution of grading structures, course groupings, and instructional trends, offering a deeper understanding of the dynamics in educational data. This analysis contributes to improved decision-making in academic program development and resource allocation. © 2024 IEEE.

关键词： Resource allocation

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Research on the Layout of Electromagnetic Radiation Measurement Points for Explosion of Energetic Materials 3

Research on the Layout of Electromagnetic Radiation Measurem...

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3rd International Seminar on Artificial Intelligence, Networking, and Information technology, AINIT 2022

作者： Cui, Yuanbo Zhou, Hang School of Mechanical Engineering Nanjing University of Science and Technology Nanjing210094 China School of Computer and Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

The adaptability of an electromagnetic radiation measurement system in the explosive field environment of energetic materials is studied, the installation method of the instrument is demonstrated, and the measurement point layout is studied. The effective measurement area of the explosion field is determined from the radiation source field area, the antenna measurement field area, the radius of the explosion fireball, the sensitivity of the data acquisition instrument, etc. The number of layouts at the same distance is determined and the dislocation arrangement is adopted to achieve omnidirectional coverage of the measurement range, finally a complete electromagnetic radiation measurement system has been established. © 2023 SPIE.

关键词： Data acquisition

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An Efficient Approach of Brain Tumor Detection & Extraction using BWT with Auto Enhance Technique 3

An Efficient Approach of Brain Tumor Detection & Extraction ...

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3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Bahadure, Nilesh Bhaskarrao Gonge, Sudhanshu Patni, Jagdish Chandra Shah, Bhoomi Raju, Nagrajan Patil, Prasenjeet D. Department of Computer Science and Engineering School of Technology GSFC University Gujarat Vadodara India Maharashtra Pune India Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bengaluru India Department of Electrical and Electronics Engineering SASTRA University Tamil Nadu Thanjavur India Department of Computer Science and Engineering MIT ADT University Pune India

Brain tumor detection and extraction of infected areas with utmost accuracy is essential in medical image analysis. Despite ex- cessive research, segmentation operation for brain tumor detection remains an exigent issue because medical images have diverse image contents, non-uniformity object texture, occlusion, image noise, and other factors that consistently influence and affect per- formance analysis. This paper introduces the most efficient brain tumor detection and extraction technique, using Berkely Wavelet Transformation-based segmentation with auto-enhancement techniques. If the input images are too dark or their intensity is not good enough, the auto-enhance technique will automatically adjust the image quality. The extensive experimental analysis and sim- ulation, with a comparison of the results with other state-of-the-art techniques available, prove the significance and effectiveness of the proposed algorithm. The primary intent of this paper is to develop a simple but performance-oriented algorithm for brain tumor detection and extraction, which is suitable for most imaging modalities and gives the best performance even if images are of poor quality. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Image segmentation

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Human Activity Recognition Using Deep Learning Techniques for Healthcare Applications 15

Human Activity Recognition Using Deep Learning Techniques fo...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Shekhar, Raj Tomar, Deepak Singh Sharan, Bhagwati Pateriya, R.K. Maulana Azad National Institute of Technology Department of Computer Science and Engineering Bhopal India Srm University-AP School of Engineering and Sciences Department of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9798350370249

The idea of smart healthcare is gradually gaining traction with the rapid advancement in information technologies. Smart healthcare is the intelligent transformation of the current medical system to make it more reliable, efficient, and individualized through the intelligent use of next-generation technologies like artificial intelligence, and the Internet of Things (IoT). This study offered the recent advancement of Deep learning (DL) techniques for healthcare systems, and the use of DL techniques to identify human physical activity with wearable sensors. In this paper, convolutional neural networks (CNN), CNN-LSTM, Multi Headed CNN-LSTM, and Multi Headed CNNBiLSTM are used. The obtained outcomes of these Deep Learning models are compared in terms of accuracy, precision, recall and F1 score. The Multi-Headed CNN-BiLSTM model exhibits better performance than the rest of the models when applied to the UCI HAR dataset. © 2024 IEEE.

关键词： Convolutional neural networks

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A Blockchain-based Material Donation Platform

A Blockchain-based Material Donation Platform

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2022 International Conference on Blockchain technology and Information Security, ICBCTIS 2022

作者： Li, Tong Hu, Donghui Li, Meng Li, Yifan Zheng, Shuli School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei China

ISBN: (数字)9781665496919

ISBN: (纸本)9781665496919

The COVID-19 pandemic has led to a worldwide surge in demand for masks, protective clothing, and other epidemic prevention materials. The lack of epidemic prevention materials has put the lives of frontline health care workers at serious risk. However, epidemic prevention materials are not being distributed fairly and efficiently. This, coupled with the occasional scramble for scarce materials, makes epidemic prevention materials scarcer. The traditional centralized donation model makes it difficult to obtain the demand for materials in a timely manner, and the existing blockchain-based donation systems have not improved the efficiency of material donation. Moreover, most of the donation systems do not consider privacy and security issues. In this paper, we propose a blockchain-based material donation platform designed and implemented through the Ethereum platform. We solve the difficulty of demand acquisition and improve the transparency of the donation process through blockchain;reduce the possibility of a second disaster and improve the efficiency of material distribution through smart contracts;and protect the privacy and security of the donation process through zero-knowledge proof. We validate the security and efficiency of the proposed epidemic donation platform. © 2022 IEEE.

关键词： Blockchain

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Analysis and Impact of Electromagnetic Field Leakage in WPT on Central Nervous System: A Neural Network Approach 4

Analysis and Impact of Electromagnetic Field Leakage in WPT ...

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4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Shukla, Garima Awasthi, Vanshaj Goswami, Prafull Singh, Sofia Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Maharashtra Mumbai India Indian Institute of Information and Technology Department of Computer Science and Engineering Sonipat India Amity School of Engineering and Technology Amity University Department of Artificial Intelligence Uttar Pradesh Noida India

ISBN: (纸本)9798350383997

The potential for wireless power transfer (WPT) technologies to transform the charging capabilities of a wide range of applications, from consumer electronics to medical devices has attracted a lot of attention. But uncertainties remain about how these technology's electromagnetic field (EMF) leakage affects human health, especially the central nervous system (CNS). To find a way to assess and forecast all of these consequences, this study explores at the possible effects of EMF leakage from WPT systems on the central nervous system (CNS) and suggests a distinctive approach that employs the applications for neural networks. Using real- world data and computational models, this study will produce an accurate model of EMF absorption and propagation in biological tissues, with a specific focus on the central nervous system. By focusing insights into potential risks to health and informing the emergence of requirements which assure the safe implementation of wireless power technologies, the research will enhance our understanding of the connections between EMF exposure and the central nervous system. The ultimate objective of this study is to encourage safer and more sustainable wireless charging technologies by enhancing the accuracy and efficiency of risk assessment in circumstances of EMF exposure from WPT systems through the implementation of Machine Learning (ML) strategies © 2024 IEEE.

关键词： Inductive power transmission

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Rational screening of metal coating on Zn anode for ultrahigh-cumulative-capacity aqueous zinc metal batteries

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Journal of Energy Chemistry 2023年第9期84卷 81-88页

作者： Dan Lv Huili Peng Cheng Wang Hongxia Liu Dongdong Wang Jian Yang Yitai Qian Key Laboratory of Colloid and Interface Chemistry Ministry of EducationSchool of Chemistry and Chemical EngineeringShandong UniversityJinan 250100ShandongChina School of Chemistry and Chemical Engineering Wuhan Textile UniversityWuhan 430200HubeiChina Hefei National Laboratory for Physical Science at Microscale Department of ChemistryUniversity of Science and Technology of ChinaHefei 230026AnhuiChina

Aqueous zinc metal batteries feature intrinsic safety,but suffer from severe dendrite growth and water-derived side *** metal coatings have been explored for stabilizing Zn metal anode via a trialand-error ***,we propose an exercisable way to screen the potential metal coating on Zn anodes in view of de-polarization effect and dendrite-suppressing ability *** an output of this screening,cadmium(Cd) metal is checked ***,symmetric ZnllZn cells using Cd coated Zn(Zn@Cd) exhibit an ultra-long cycle life of 3500 h(nearly 5 months) at a high current density of 10 mA cm^(-2),achieving a record-high cumulative capacity(35 A h cm^(-2)) compared to the previous *** full cells of Zn@Cd‖MnO_(2) display a markedly improved cycling performance under harsh conditions including a limited Zn supply(N/P ratio=1.7) and a high areal capacity(3.5 mA h cm^(-2)).The significance of this work lies in not only the first report of Cd coating for stabilizing Zn metal anode,but also a feasible way to screen the promising metal materials for other metal anodes.

关键词： Zinc metal batteries Cadmium coating Redox potentials Surface energy Cumulative capacity

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Specific Ion Effects on the Enzymatic Degradation of Polyester Films

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Chinese Journal of Polymer science 2023年第4期41卷 476-482,I0005页

作者： Jian Zhang Jie Zhu Zan Hua Guang-Ming Liu Department of Chemical Physics Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education InstitutesUniversity of Science and Technology of ChinaHefei230026China Key Laboratory of Yarn Materials Forming and Composite Processing Technology of Zhejiang Province College of Material and Textile EngineeringJiaxing UniversityJiaxing314001China Biomass Molecular Engineering Center and Department of Materials Science and Engineering School of Forestry and Landscape ArchitectureAnhui Agricultural UniversityHefei230036China

Soil environment on earth contains a variety of ions,which are expected to play a vital role in the biodegradation of plastics discarded in the *** this work,poly(butyleneadipate-co-terephthalate)(PBAT)is employed as a model biodegradable plastic to study the specific ion effects on the enzymatic degradation of polyester *** results show that the specific ion effects on the enzymatic degradation rate of the PBAT films and on the catalytic rate constant for the enzymatic hydrolysis of the ester bonds are strongly dependent on temperature and ionic *** the enzymatic degradation rate and catalytic rate constant decrease following the trends Na^(+)>K^(+)>Ca^(2+)and Cl^(-)>SO_(4)^(2-)>NO_(3)^(-)for cations and anions,respectively,indicating that the ion-specific enzymatic degradation of the PBAT films is closely correlated with the specific ion effects on enzymatic hydrolysis of the ester *** study shows that the specific ion effects on the enzyme activity can be understood by taking into account the ion-specific cation-anion interaction,ionic dispersion force,salting-out effect and salting-in *** study of specific ion effects on the enzymatic hydrolysis of the ester bonds and the resultant enzymatic degradation of the PBAT films would offer us a new clue to develop new biodegradable,environmentally friendly synthetic plastics.

关键词： Specific ion effects Biodegradable films Ion-enzyme interactions Enzyme activity

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