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AI for Disaster Management: Predictive Models and Response Strategies

AI for Disaster Management: Predictive Models and Response S...

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Shameem, A. Saroja, Devupalli Hotkar, Damodar S. Nayak, Bijaya Bijeta Pandey, Anand Tripathi, Sachin Amet University Amet Business School India Department of Computer Science and Engineering Visakhapatnam India R.T.E. Society's Rural Engineering College Department of Computer Science and Engineering Karnataka Hulkoti582205 India Kiit Deemed to Be University School of Mechanical Engineering Odisha Bhubaneswar India Sharda University Computer Science and Application U.P Greater Noida India Wathoda Symbiosis Law School Nagpur Maharashtra Nagpur India

ISBN: (纸本)9798331508685

The application of artificial intelligence (AI) in managing severe weather events has become more necessary in recent years owing to their increased frequency. Disaster management is required to control and avoid such occurrences. To successfully aid in better and quicker reactions to catastrophes, AI is widely employed in prediction and disaster preparation, damage mitigation and minimization, and rescue phases. To determine how AI technology can be used to lessen the damaging impacts of different disasters, this article looks into the potential for connecting artificial intelligence methods based on technological innovation. The study potentially contributes in designing an effective framework for disaster management based on the predictive accuracy and response time. © 2025 IEEE.

关键词： Disaster prevention

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Building a Smart Virtual Chatbot Assistant with HTML, CSS, and JavaScript 2

Building a Smart Virtual Chatbot Assistant with HTML, CSS, a...

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2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Khonde, Tanvi Patle, Sneha Talvekar, Shreya Hajbe, Jahnavi Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442201 India

ISBN: (纸本)9798331505745

A virtual chatbot assistant is an interactive application designed to simulate human-like communication and respond to user inquiries promptly. It focuses on building an interesting user interface and putting simple conversational logic into practice;this article presents the development of a chatbot using HTML, CSS, and JavaScript. Developers can make these fundamental web technologies useful in the creation of accessible and user-friendly chatbot systems for any kind of application. The literature indicates that chatbot technology is under development, which includes the merging of AI and natural language processing to enhance the capabilities of conversations. This handbook is an invaluable tool in making useful chatbots by linking the needs of the users with contemporary online technology. © 2025 IEEE.

关键词： Chatbots

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Musical Genres Classification Utilizing the Pre-trained ResNet50 CNN Model and Deep Learning Techniques 4

Musical Genres Classification Utilizing the Pre-trained ResN...

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4th international conference on Innovative Practices in technology and Management, ICIPTM 2024

作者： Mittal, Khushi Gill, Kanwarpartap Singh Kumar, Mukesh Rawat, Ruchira Chythanya, Kanegonda Ravi Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun India Sr University School of Computer Science & Artificial Intelligence Warangal India

ISBN: (纸本)9798350307757

This research investigates the application of the ResNet50 Convolutional Neural Network (CNN) within a ResNet50 model framework for the purpose of classifying musical genres. The objective is to enhance the accuracy and efficiency of automated music genre categorization systems through the utilization of deep learning techniques. The proposed model employs a methodology that processes raw audio data, involving the extraction of relevant innovative features through convolutional layers. These layers are designed to capture hierarchical patterns inherent to specific genres. The incorporation of the ResNet50 architecture in machine learning facilitates the capture of temporal relationships, allowing the model to recognize subtle nuances and variations in musical compositions. The study utilizes a diverse dataset encompassing multiple genres to enhance the robustness and adaptability of the model. The primary goal is to validate the effectiveness of the CNN ResNet50 Model in accurately classifying musical genres. Through rigorous experimentation and assessment, this research aims to contribute significantly to the advancement of automated music analysis and classification systems. The findings of this study have noteworthy implications for various applications, including music recommendation systems, content tagging, and music streaming services. © 2024 IEEE.

关键词： Neural network models

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Research on sustainable development of ecological environment based on AHP-FCEM modeling 24

Research on sustainable development of ecological environmen...

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5th international conference on Artificial Intelligence and computer engineering, ICAICE 2024

作者： Zhou, Qinzhao Wang, Yanzhe Zhao, Haiyan Jia, Yizheng Su, Jiaer School of Art and Design Xi'an University of Technology Shaanxi Xi'an China National Security College People's Public Security University of China Beijing China School of Environmental and Chemical Engineering Nanchang Hangkong University Jiangxi Nanchang China Business College Southwest University Chongqing China School of Computer Science and Technology Guangzhou Institute of Applied Science and Technology Guangdong Guangzhou China

ISBN: (纸本)9798400718007

In this paper, an evaluation model of sustainable development of ecological environment is constructed by using Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation method (FCEM). First, through in-depth analysis and research, the main factors affecting the sustainable development of the ecological environment were identified, and a multi-level evaluation index system was established. Then, the weights of the indicators were determined by using AHP, and the fuzzy judgment matrix was constructed by blurring the indicators through FCEM. Finally, combining the weights and the fuzzy judgment matrix, the quantitative assessment of the sustainable development status of the ecological environment was carried out, and the comprehensive evaluation score was 88.193, indicating that the Sehampa has a better ability to resist sandstorms and dust storms in Beijing. The results of the study show that the model can comprehensively and objectively reflect the development status of the ecological environment and provide a scientific basis for ecological environmental protection and sustainable development. It aims to promote the continuous improvement and sustainable development of the ecological environment, and provide strong support for realizing the goal of harmonious coexistence between human beings and nature. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Natural environment

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Simulation of the Formation Process and Structural Optimization of JPC Destructive Elements in Dual-mode Combat Units 2

Simulation of the Formation Process and Structural Optimizat...

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2nd international conference on Electronic Information engineering, Big Data, and computer technology, EIBDCT 2023

作者： Guo, Wenfeng Jiao, Yuze Lan, Tian Han, Xianqi Equipment Engineering College Shenyang Ligong University China

ISBN: (纸本)9781510664968

To study the effect of multi-mode combat part destruction, in this paper, we use AUTODYN simulation software to simulate the effects of dual-mode combatants on the shaping of the destruction element under different structures of the charge cover, charge height, and detonation method, and determine the optimization scheme of dual-mode combatants through orthogonal optimization. This study has a certain reference value for the structural design of multi-mode warheads and the study of damage effects. © 2023 SPIE.

关键词： Detonation

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An Overview on IoT in Electric Vehicles: Efficiency and Sustainability 2

An Overview on IoT in Electric Vehicles: Efficiency and Sust...

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2nd IEEE international conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Gupta, Shashank Sounkhla, Indu Dubey, Ranjeet Kumar Yadav, Mithilesh Kumar Singh Yadav, Sandeep NIT Dept. of Computer Science and Engineering Jalandhar India KIPM Dept. of Computer Science and Engineering Gorakhpur India Buddha Institute of Technology Dept. of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Internal combustion engine (ICE) vehicles are very polluting and release high nitrogen oxides, carcinogens, and soot into the environment. ICE vehicles are the best choice in this era, but replacing ICE vehicles with electric vehicles (EVs) and automated vehicle control is a potential transition process. The most important turning point in the history of the automobile occurred with the entry of EVs into the vehicle market. The rise of the Internet of Things (IoT) paradigm in electric vehicles (EVs) has changed the way we look at large-scale transportation by making it intelligent and more sustainable. Recently, with the advent of connectivity through IoT platforms, IoT in EVs has improved performance and reduced environmental impact: from any on-off switch and adoption of IoT through our smartphones placed on the charging base. We can implement smart charging solutions for better energy consumption management, reduction of grid load, and battery life enhancement. IoT allows electric vehicles to communicate directly with charging stations and even the power grid, providing a better way to create balanced transportation networks. But implementing IoT in electric vehicles also raises some issues, including data security and user privacy. With all of these issues, there is huge potential in IoT usage with electric vehicles to help produce cleaner transportation and create a more sustainable future. © 2024 IEEE.

关键词： Electric Vehicles Internal Combustion engine Internet of Things

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MedNetV3: A Deep Learning Model for MRI Brain Tumor Detection with MobileNetV3 and Advanced Data Augmentation 21

MedNetV3: A Deep Learning Model for MRI Brain Tumor Detectio...

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21st international computer conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Tariq, Hussain Ahmed Fengli, Zhang Salim Shakib, Muhamud Md Javed, Iram School of Information and Software Engineering University of Electronic Science and Technology of China China University of Agriculture Department of Computer Science Faisalabad Pakistan

ISBN: (纸本)9798331519254

In this paper, we present a novel deep learning model medical network (MedNetV3) developed for brain tumor detection. It incorporates advanced data augmentation techniques based on the MobileNetV3 architecture. MedNetV3 is developed for higher classification accuracy at the cost of slightly lower computational efficiency and is therefore suitable for clinical use. The proposed model overcomes the class imbalance problem and can make the model robust to the variations of MRI scans included in the extensive data augmentation methods, such as random rotations, flips. The proposed model trained and evaluated using a publicly available MRI dataset. It achieved a high Area Under the Curve (AUC) value of 0.99 for both the Precision-Recall and Receiver Operating Characteristic (ROC) curves. The results show that MedNetV3 is effective in correctly distinguishing brain tumors and therefore has the potential to be used in medical image classification. © 2024 IEEE.

关键词： Deep learning

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Brain tumour Detection using a Modified Convolutional Neural Network 9

Brain tumour Detection using a Modified Convolutional Neural...

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9th IEEE international conference for Convergence in technology, I2CT 2024

作者： Kotnala, Mili Dangwal, Pranjal Chauhan, Rahul Devliyal, Swati Sunil, G. Kumar, Amit Graphic Era Hill University Computer Science And Engineering Uttarakhand Dehradun India Graphic Era Deemed To Be University Computer Science And Engineering Uttarakhand Dehradun India Sr University School of Computer Science & Artificial Intelligence Warangal India Chitkara University Institute of Engineering And Technology Chitkara University Punjab India

ISBN: (纸本)9798350394474

Brain tumors represent a formidable healthcare challenge worldwide, and their early detection is critical for timely intervention and improved patient outcomes. This survey research explores the realm of deep learning algorithm with direct attention to convolutional neural networks (CNN) for the timely detection of patients with brain tumor. The paper explores the 5-layer cnn model, which has been a widely used approach in previous research, with a 9-layer CNN-model within the framework of brain tumour detection. a comparative analysis is presented, highlighting the strengths and limitations, architectural intricacies, model complexity, performance assessments and other significant features. The findings from the 5-layer cnn serve as a baseline for comparison in our research. This study uses the 2020 brat's dataset and the experimental result are the proof the model's efficacy that surpasses the performance of existing models with an accuracy of 99.74%, previously unmatched. Paper concludes by emphasizing the relevance and importance of utilizing deep learning, specifically a 9-layer CNN model, for early and accurate detection of brain tumours. This research contributes valuable insights to the field of medical imaging and deep learning, providing a basis for future work in the development of more accurate and effective tools for early brain tumor detection, ultimately leading to improved patient care and outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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Development of Science Virtual Reality Lab Simulation (SVLS): Enhancing Immersive Experiences 9

Development of Science Virtual Reality Lab Simulation (SVLS)...

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Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Litchaweerat, Supanat Khenda, Prasopsuk Intayoad, Wacharawan Tongpaeng, Yootthapong Putjorn, Pruet Mae Fah Luang University Software Engineering Chiang Rai Thailand Mae Fah Luang University Center of Excellence in Ai and Emerging Technologies School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9798350318241

In order to improve student learning in primary science laboratories, this pilot study explores the development and application of a Virtual Reality (VR) simulation system called Science Virtual Lab Simulation (SVLS). Unlike traditional teaching approaches, SVLS is designed to provide an engaging and interactive environment that helps young learners better understand scientific concepts. Three crucial components of virtual reality (VR) in education are highlighted by the study's methodology: the system's overall usability, the interaction between users and VR technology, and the learning experience itself. The results showed students' desire and enthusiasm to learn were increased by the VR environment, which made scientific concepts easier to understand. The study suggested that the active use of VR technology may contribute to enhancing science education by potentially making learning more engaging and enjoyable. The user-friendliness and intuitiveness of the VR system appeared to play a role in its effective integration into learning environments. Additionally, the research highlighted the importance of designing VR systems with interfaces and instructions that are considerate of the cognitive and physical abilities of young students, though further studies are recommended to fully understand these impacts. To summarize, the SVLS prototype showcases how VR may revolutionize the teaching of primary science. It highlights how well built VR systems can greatly enhance various elements of education, including learning engagement, technological interaction, and overall academic outcomes. © 2024 IEEE.

关键词： Virtual reality

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Preventing Shoulder Surfing Attacks-Matrix Based Graphical Technique 2

Preventing Shoulder Surfing Attacks-Matrix Based Graphical T...

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2nd IEEE international conference for Women in Innovation, technology and Entrepreneurship, ICWITE 2024

作者： Goyal, Ashtha Matta, Priya Lohumi, Yogesh Graphic Era Hill University Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Tula's Institute Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350383287

Shoulder Surfing Attacks (SSA) cause a serious risk to user security and privacy in a variety of settings, including sensitive transactions, password entry, and access to personal information. Effective defenses that can stop unauthorized viewing of sensitive data are necessary for mitigating these threats. This proposed model leverages the concept to create an additional layer of protection during user interactions. It utilizes a dynamic matrix consisting of randomized elements to confuse the visual representation of sensitive data, such as passwords or PINs, displayed on a user interface. The matrix introduces visual noise delaying shoulder surfers' ability to decipher the actual input. A software application or model is designed to overlay a randomized matrix on the user input area. This matrix is unique to each interaction session and constantly changes in real-time, making it difficult for shoulder surfers to determine the true input values. The matrix-based scheme presents a novel approach to prevent shoulder surfing attacks by incorporating dynamic matrices that obfuscate sensitive user inputs. This scheme enhances user privacy and security in various sensitive scenarios. Further research and development are required to refine and validate the effectiveness of this approach in real-world deployment scenarios. © 2024 IEEE.

关键词： Matrix algebra

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