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Land use and Land Cover Mapping for Rampura Agucha Mines, India, using Landsat 8 and Landsat 9: A Time Series Analysis

Land use and Land Cover Mapping for Rampura Agucha Mines, In...

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2024 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Verma, Kshitij Kumar Ghosh, Anisha Dutta, Dipanjan Halder, Tamesh Gayen, Rintu Kumar Chakravarty, Debashish Indian Institute of Technology Department of Mining Engineering Kharagpur721302 India Institute of Engineering and Management Kolkata700091 India Kiit Deemed to Be University School of Electronics Engineering Bhubaneswar751024 India Indian Institute of Technology Department of Mining Engineering Kharagpur721325 India

ISBN: (纸本)9798350348460

The study shows the variation in Land Use over the period of 2013-2021 in the region of Rampura Agucha Mines in Rajasthan, India. The study also presents the use of Geospatial Indices are NDVI, NDWI, NDMI and clay in mapping open cast mining areas. The comparison between two satellites' multispectral images and their performance metrics for Land Monitoring from 2013-2021 and Changes application is established. The results show the effectiveness of the approach which shows the improved radiometric resolution (Landsat 9-14bit vs. 12bit in Landsat 8), and it can be used for mapping various open cast mines. We monitor 2020 floodover open cast mines caused high vegetation andlow urbanization or fallow land. © 2024 ieee.

关键词： Geospatial Indices land cover classification Landsat 8 Landsat 9 mining area time series

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Research on Search Engine Optimization Strategies Based on Google Algorithm

Research on Search Engine Optimization Strategies Based on G...

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2023 international conference on computer science and automation Technology, CSAT 2023

作者： Zhang, Fan Philippine Christian University Manila Philippines Huanggang College of Science and Technology Huanggang China

ISBN: (纸本)9798350371437

Google is the world's largest search engine. Every update of its algorithm has a huge impact on the Internet. The operation of enterprise websites needs to keep abreast of algorithm updates, and at the same time, formulate a search engine optimization strategy that meets the requirements of the updates, and continue to optimize the website, so that only by gaining more attention and traffic can we create value for the enterprise. This article analyzes the core update algorithms launched by Google in 2020-2023, and formulates reasonable optimization strategies and implementation methods. It also uses the code optimization case of the 'How to apply for admission' page on the PCU website as an example to explain the optimization process, and provides reference for website operators. © 2023 ieee.

关键词： Websites

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A Comparison of the Impact of Current Priority Modes of Inverter-Based Resources on the Performance of Grid Protective Relays 18

A Comparison of the Impact of Current Priority Modes of Inve...

引用

18th international conference on Protection and automation in Power Systems, IPAPS 2024

作者： Jafarian, Peyman Aminifar, Farrokh Tehran Iran University of Tehran School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350350388

The dynamic response of inverter-based resources (IBRs) during fault-ride-though condition is driven by their control system, and it can be greatly different from that of synchronous generators (SGs). To standardize the fault response of IBRs, the recently published ieee Std. 2800-2022 has defined two different current control modes during abnormal voltage conditions, i.e. reactive current priority mode and active current priority mode. This paper compares these control modes based on their impacts on the grid protective relays. To do so, the reference currents generator of IBR is designed so as to utilize the maximum current capability of the IBR while complying with the requirements of the mentioned standard. Followed by modeling an IBR with its complete closed-loop control system, simulation studies are carried out on a test power system in the PSCAD/EMTDC software. The obtained results indicate that the reactive current priority mode is superior for the correct operation of grid protective relays. Whereas, the active current priority mode may lead to malfunction of some conventional protective relays. © 2024 ieee.

关键词： Relay protection

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IoT Based Smart Waste Monitoring System Envisioning a Sustainable Smart City

IoT Based Smart Waste Monitoring System Envisioning a Sustai...

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2024 ieee international conference on Computing, Applications and Systems, COMPAS 2024

作者： Aurko, Najmus Saquib Masum, S.M. Hossain, Md Sajid American International University Bangladesh Computer Science and Engineering Dhaka1229 Bangladesh American International University Bangladesh Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331529765

This paper introduces a smart approach to waste management through the integration of smart technologies. Our proposed system employs the ESP8266 Wi-Fi module to enable remote notification, ensuring efficient waste monitoring both indoors and outdoors. The core components include an Ultrasonic Sensor HC-SR04 for real-time monitoring of the waste bin's fill level, an IR sensor to facilitate automated lid opening upon user proximity, and a servo motor to control the lid mechanism. Upon detection of fullness of the waste bin, the system triggers a buzzer, providing an audible alert for the user and encouraging the user timely waste disposal. The innovation aimed for a more cost effective and economically beneficial system. The innovation extends beyond conventional waste monitoring because we are not only implementing it indoors but also outdoors to monitor waste disposal which will maintain a clean environment overall. The paper outlines the implementation of a client-server model, emphasizing its potential to foster a pollution-free society, good health, and a cleaner environment. © 2024 ieee.

关键词： Ultrasonic sensors

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AI LipReader-Transcribing Speech from Lip Movements 6

AI LipReader-Transcribing Speech from Lip Movements

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6th ieee international conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Ajitha, D. Dutta, Disha Saha, Falguni Giri, Parus Kant, Rohan School of Computer Science and Engineering Vellore Institute of Technology Vellore Department of Software Systems Vellore India School of Computer Science and Engineering Vellore Institute of Technology Department of Database Systems Vellore India School of Computer Science and Engineering Vellore Institute of Technology Vellore Department of Information Security Vellore India

ISBN: (纸本)9798350306613

Lip Reading AI is a discipline that is rapidly changing and has numerous applications in security, accessibility and human-computer interaction. This paper proposes a model which combines Convolutional Neural Networks (CNNs) to capture spatial capabilities, Long Short-Term Memory (LSTM) networks to examine temporal dependencies, and an adaptive interest mechanism. Meticulous preprocessing of the MIRACL VC-l dataset addressing challenges including one of a kind lip moves and occlusions accompanied with the aid of transitioning this study effortlessly to LRS2 dataset to complement lexemic versatility is one of its key function. The effects verify its robustness throughout unique datasets with superior overall performance towards cutting-edge techniques. Ablation checks suggest the crucial significance of every element in phrases of improving lip analyzing accuracy. Our proposed model version additionally suggests flexibility in restricted and naturalistic language situations. © 2024 ieee.

关键词： Attention Mechanism Convolutional Neural Networks (CNNs) Deep Learning Lip Reading Long Short-Term Memory (LSTM) LRS2 Dataset MIRACLVC-J Dataset

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Synergizing CNN and Random Forest for Accurate Cattle Disease Identification

Synergizing CNN and Random Forest for Accurate Cattle Diseas...

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2024 ieee international conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Yashu Kukreja, Vinay Srivastava, Prateek Garg, Ashish Hariharan, Shanmugasundaram Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India Vardhaman College of Engineering Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350382693

The current research focuses on the essential undertaking of multiclass classification in the context of diagnosing skin disorders in cattle. It aims to provide a thorough assessment of a complete model. The introduction underscores the need of rapid illness diagnosis in veterinary practises. The aim of this study is to construct a robust model that can successfully identify a wide range of skin diseases in cattle with high accuracy. The precision values, which range from 88.12% to 97.57%, serve as indicators of the model's proficiency in accurately predicting distinct classes. The model's ability to make accurate predictions across several categories is highlighted by its overall accuracy of 91.56%, indicating a high level of competency and reliability. The research use a comprehensive dataset and incorporates sophisticated machine learning methods to improve the detection of diseases. The attainment of a high level of precision and accuracy plays a significant role in enhancing the dependability of the model in real-world scenarios, hence enabling timely intervention and treatment. The results indicate that the model that was created has potential for effective use in actual situations, offering a significant resource for veterinarians in the management and treatment of skin disorders in cattle. This research makes a valuable contribution to the continuous endeavours in using machine learning techniques to enhance cattle health and emphasises the potential for further breakthroughs in disease identification strategies. © 2024 ieee.

关键词： Animal CNN Deep Learning Disease Recognition Health Random Forest

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Enhancing Commonsense Reasoning with Entity Type Knowledge 5

Enhancing Commonsense Reasoning with Entity Type Knowledge

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5th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2024

作者： Guo, Yanjun Yue, Dengfeng Mao, Chenyang Leng, Tuo Shanghai University School of Computer Engineering and Science Shanghai China

ISBN: (纸本)9798350366174

Commonsense reasoning has long been a significant challenge in the field of natural language reasoning, requiring machines to possess ample commonsense knowledge for factual inference. In recent years, large-scale pre-trained models have been extensively employed in commonsense reasoning and question-answering tasks, demonstrating commendable comprehension capabilities. However, compared to traditional approaches that rely on conceptual knowledge graphs, these models not only lack commonsense knowledge resources but also lack dedicated modules for structured knowledge. The trend of integrating these two methodologies for inference is growing. Nevertheless, the overlap between the concepts of entities in knowledge graphs and the implicit knowledge embedded within pre-trained models often impedes the enhancement of commonsense reasoning capabilities. We observe that there is symmetry between the types of entities in questions and answers, which offers potential for further exploring the commonsense reasoning abilities of pre-trained models. Therefore, we incorporate entity types as external supplementary knowledge into the pre-training model. To better align with generative pre-training models, we employ syntactic tools to transform commonsense questions into structured declarative sentences, which serve as inputs to the model. We then resolve commonsense questions based on the scores generated by the model. Our research results show that, compared to baseline pre-trained models, our approach significantly improves inference accuracy. Specifically, on the CommonsenseQA dataset, accuracy increased from 72.9% to 81.1%, and on the OpenBookQA dataset, it rose from 79.3% to 82.8%. These improvements highlight the superiority of our method over baseline models and demonstrate its potential to enhance the commonsense reasoning capabilities of existing models. © 2024 ieee.

关键词： Knowledge graph

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FIFA Dataset Analysis and Match Prediction 7

FIFA Dataset Analysis and Match Prediction

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7th international conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Tamboli, Salil Anand, Aman Galgotias University School of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350372816

The world of football, with its vast player database and intricate gameplay, has been a subject of fascination for enthusiasts and analysts alike. The FIFA video game series, developed by EA Sports, provides an opportunity to delve into this world from a data science perspective. In this research, we embark on a comprehensive analysis of FIFA player data using Python to uncover insights and patterns that can enhance our understanding of the virtual football world. Findings: Data visualization is the process of representing data using common graphics, like charts, plots, infographics, and even animations, prediction of overall rating of football players using Linear Regression and Win prediction of EPL teams using Random Forest classifier. © 2024 ieee.

关键词： Logistic regression

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Implementation of various AI techniques for Autism Spectrum Disorder Detection 7

Implementation of various AI techniques for Autism Spectrum ...

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7th international conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Asha, P. Raj, Aditya Ramani, Bhavyam Vijay Padma Suresh, L. Prince Mary, S. Mary Posonia, A. Sathyabama Institute of Science and Technology Computer Science and Engineering Chennai India Baselios Mathews II College of Engineering Computer Science and Engineering Kollam India

ISBN: (纸本)9798350372816

A complex neurological disorder affecting behavior, communication, and social interactions is known as autism spectrum disorder (ASD). For people with ASD, improving outcomes requires primordial detection and intervention. The diagnosis of ASD has been transformed by the combination of AI and ML, particularly in young children. In order to create reliable autism screening tools, researchers have explored a variety of machine learning algorithms, including Decision Trees, XGBClassifier, Random Forest, AdaBoost Classifier, CatBoost Classifier, KMeans to Artificial Neural Networks (ANN). Artificial Neural Networks, energised by the intricacies of the human brain, stand out for their remarkable ability to decipher complex patterns within data, thus proving effective in ASD prediction tasks. Nonetheless, ANN models often necessitate substantial data and computational resources for training. It is imperative to undertake rigorous comparative analyses based on accurate and efficient results to determine the most suitable algorithm for ASD prediction. Furthermore, continuous refinement and validation of these varied algorithms along with the representative and comprehensive datasets are vital to ensure their factuality and applicability in real world problems. © 2024 ieee.

关键词： Random forests

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Image Processing: Unlocking the Secrets of Visual Information 2

Image Processing: Unlocking the Secrets of Visual Informatio...

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2nd ieee international conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Lavanya, D. Bhushan, Kavi Kant, Gur Sharan Sountharraj, A.C. Srivastav, Akanksha Begum, M. Sharmila Sri Venkateswara College of Engineering Computer Science and Engineering Department Andhra Pradesh Tirupati India Ccs University Sir Chhotu Ram Institute of Engg. & Technology Department of Computer Science U.P Meerut India Dr. Ngp Art's and Science College Department of Computer Science with Data Analytics Coimbatore-48 India Tula's Institute Department of Computer Science and Engineering Dehradun India Maharaja Institute of Technology Department of Computer Science Mysore India

ISBN: (纸本)9798350384277

In the age of image processing, the hidden ability can be encoded with visual information that is not only observed but also painstakingly carried out;in this way, the complex secrets that are encoded in each pixel have been made clear. Image processing is the magic that has increased the amount of clarity, significance, and utility while transforming stationary arrays of images into dynamic narratives. The image's quality is typically influenced by several variables, such as temperature, light, and noise. Due to its persistent presence in various digital photographs, noise plays a crucial function in the image. Throughout the image coding, transmission, and development procedure, noise consequences could arise. The field of noise removal in image processing has grown to be quite interesting and vibrant. Recently, there has been a notable advancement regarding the filtering of various noise types for image processing in digital format. This research paper aims to discuss image processing and denoising various noises in images to improve overall quality. In terms of methodology systematic qualitative research has been conducted that helps the research gather information from a wide range of sources. Moreover, this paper finds that image processing has significant potential in this digital age. By denoising images, this phenomenon can be applied in different applications in every sector. © 2024 ieee.

关键词： Image denoising

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