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5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Manhas, Vishal Singh Sahani, Prince Upase, Shankar Venkatrao Ashtagi, Rashmi Under Graduate Student Department Of Computer Engineering Vishwakarma Institute Of Technology Pune India Department Of Computer Engineering Vishwakarma Institute Of Technology Pune India

ISBN: (纸本)9798400709418

This paper explores the critical issue of driver drowsiness and its significant contribution to road accidents. A real-time drowsiness detection system that harnesses the power of computer vision and facial landmark recognition to enhance safety and prevent accidents in situations where drowsiness poses a significant risk, such as drowsy driving. This system combines various libraries and techniques, including Dlib for face detection and facial landmark identification and OpenCV for image processing. Its core functionality involves capturing video frames from a camera feed, locating faces within each frame, and then focusing on the eyes and eyebrows to assess the individual's level of alertness. This assessment is primarily based on the analysis of eye blinking patterns, with specific attention to the blink ratio, which serves as a key indicator. Depending on the calculated blink ratio, the system classifies the person's state into three distinct categories: "SLEEPING,""Drowsy,"or "Active."These categories are conveyed to the user through real-time text overlays on the video feed, each represented by a specific color. The value of this project lies in its potential to prevent accidents caused by drowsiness, a major factor contributing to road accidents worldwide. By continuously monitoring and evaluating the individual's state of alertness, this system provides immediate feedback and intervention when drowsiness is detected, thus contributing to safer driving and potentially extending its applicability to other domains where alertness is critical, such as operating heavy machinery or monitoring individuals in critical work environments. Furthermore, this project offers a foundation for further development and integration with advanced technologies, potentially evolving into a comprehensive safety system with broader applications in areas where real-time alertness assessment is essential for reducing risks and enhancing overall safety. © 2023 ACM.

关键词： computer vision

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UAV weaknesses against deauthentication based hijacking attacks 22

UAV weaknesses against deauthentication based hijacking atta...

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2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics, SAMI 2024

作者： Krasnyanszki, Bruno Brassai, Sandor Tihamer Nemeth, Andras Óbuda University Under Graduate Student in Computer Science Engineering Budapest Hungary Sapientia Hungarian University of Transylvania Department of Electrical Engineering Corunca Romania National University of Public Service Department of Electronic Warfare Budapest Hungary

ISBN: (纸本)9798350317206

Unmanned Aerial Vehicles (UAVs) and Unmanned Aerial Systems (UAS) are more important than ever before and we're using it daily for agriculture, photo making, film industry, Search & Rescue, long range cable quality control, Geo Informatics, cartography, and state use (including border protection, disaster recovery and the military). Most of the UAV/UAS devices are using digital communication protocols nowadays, especially the IEEE 802.11 Wireless Local Area of Network for the cheaper and middle price UAV/UAS. Unfortunately, the protocols specified by the previously mentioned IEEE standard are vulnerable against some attacks. This research paper proposes a method that can interrupt the normal operation of the UAV/UAS that are using the IEEE 802.11 protocol and hijack the interrupted UAV/UAS permanently. For this method, deauthentication attack has been performed against the UAV/UASs. The attack vector is capable of denying the communication between the UAV and the control station. With sufficient prior knowledge it is possible to hijack the UAV that communicates on a 802.11 based protocol. Deauthentication based attacks are much more sophisticated than for example traditional electronic jamming, because the target can be precisely chosen and the attack will not interrupt other devices using the same communication method. The research has unfortunately some limitations in equipment, measurements conducted only in three different types of UAVs from three price categories, but in the future the authors would like to extend the range of UAVs. From this three UAVs two are hijackable by this method and the third should also be hijackable with some modifications. This research could be a base later for UAV/UAS counter measure systems for the safety of all of us. © 2024 IEEE.

关键词： Drones

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Smart Cities: Transforming Urban Living with IoT

Smart Cities: Transforming Urban Living with IoT

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International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： Niveditha J D R Kumar Raja UM Ashwin Kumar Post Graduate Student dept of Computer Science and Engineering Reva University Bangalore India

The Internet of Things (IoT) is being used by smart cities to harness the power of the IoT and build more efficient and sustainable urban settings as they quickly adapt to the challenges of urbanization. This study examines the idea of “smart cities” and the different fields where Internet of Things-based technologies are being used to improve urban living. The article discusses several IoT use cases and applications for smart cities, including smart energy management, smart transportation, smart healthcare, and smart public safety. Discussions also cover the advantages and difficulties of IoT-based smart city initiatives, such as the necessity for reliable infrastructure, data privacy and security concerns, and cooperative strategies. The essay also emphasizes how crucial a favorable policy and regulatory framework is to the deployment of IoT-based smart city projects. The article's conclusion discusses potential paths for further research as well as how the Internet of Things may change urban living in the years to come

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MonuAR:M.A.R Application for Visualising 3D Monuments

MonuAR:M.A.R Application for Visualising 3D Monuments

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Networking and Communications (ICNWC), International Conference on

作者： Shanthi D Sorna B Bhuvaneswaran Adhithya R Manoj S Pooja Department of Computer Science of Engineering Rajalakshmi Engineering College Chennai Department of Computer Science of Engineering Under Graduate Student Rajalakshmi Engineering College Chennai

The Art and Heritage has been an integral part of our Indian Culture. These art forms and heritage are left unnoticed just because they are very much away. Therefore these sites can be brought back to life in any environment. The heritage properties of art and craft of India can be brought to life from anywhere by using an AR application on the phone. There are times when people visit the monuments and they are in need of a third party to show them the main attractions of the monument. Instead of relying on a third party, this can be done using this app where an AR marker appears on important tourist spots. The software that are used are Unity, Blender, Python and Visual Studio for C#. The software development kit used are Vuforia AR SDK and Mapbox *** software that are used are Unity, Blender, Python and Visual Studio for C#. The software development kit used are Vuforia AR SDK and Mapbox SDK

关键词： Visualization Solid modeling Art Three-dimensional displays Machine learning algorithms Chatbots Software

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Role-Playing Video Game: It’S Effectiveness in Ideal Gas Law Learning of Junior High School students

SSRN

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SSRN 2023年

作者： Dolipas, Bretel B. Dolipas, Thrysha Fabrigas, Christian Romero, Sebastien Duke Garcia, Marius Mactal, Aeron Silvio, Junel Benguet State University Philippines Environmental and Sanitary Engineer Graduate University of Cordilleras Philippines Business Administration Major in Digital Marketing Student University of the Cordilleras Philippines Computer Engineering Student University of Cordilleras Philippines Electronics and Communications Engineering Student Saint Louis University United States Electrical Engineering Student Saint Louis University United States Nursing Student Manila Central University Philippines

The study aimed to assess the effectiveness of role playing video game in the learning of Ideal Gas Laws of junior high school students. Specifically, the study determined the academic performance in Ideal Gas Laws of junior high school students when Ideal Gas Laws were taught through the conventional method and through role playing video game method of learning. The result indicated that academic performance in Ideal Gas Laws of students taught with the use of role playing video game was significantly higher compared to those taught using the conventional method of learning. In addition, the performance level of students taught using the role playing video game was fairly satisfactory or better regardless of sex. It is recommended that role playing video game technique could be an alternative and effective method in the teaching and learning of science concept. More research on role playing video game effectiveness to academic performance in other field is likewise recommended. © 2023, The Authors. All rights reserved.

关键词： students

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UAV weaknesses against deauthentication based hijacking attacks

UAV weaknesses against deauthentication based hijacking atta...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Brúnó Krasnyánszki Sándor Tihamér Brassai András Németh Under Graduate Student in Computer Science Engineering Óbuda University Budapest Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Corunca Romania Department of Electronic Warfare National University of Public Service Budapest Hungary

Unmanned Aerial Vehicles (UAVs) and Unmanned Aerial Systems (UAS) are more important than ever before and we’re using it daily for agriculture, photo making, film industry, Search & Rescue, long range cable quality control, Geo Informatics, cartography, and state use (including border protection, disaster recovery and the military). Most of the UAV/UAS devices are using digital communication protocols nowadays, especially the IEEE 802.11 Wireless Local Area of Network for the cheaper and middle price UAV/UAS. Unfortunately, the protocols specified by the previously mentioned IEEE standard are vulnerable against some attacks. This research paper proposes a method that can interrupt the normal operation of the UAV/UAS that are using the IEEE 802.11 protocol and hijack the interrupted UAV/UAS permanently. For this method, deauthentication attack has been performed against the UAV/UASs. The attack vector is capable of denying the communication between the UAV and the control station. With sufficient prior knowledge it is possible to hijack the UAV that communicates on a 802.11 based protocol. Deauthentication based attacks are much more sophisticated than for example traditional electronic jamming, because the target can be precisely chosen and the attack will not interrupt other devices using the same communication method. The research has unfortunately some limitations in equipment, measurements conducted only in three different types of UAVs from three price categories, but in the future the authors would like to extend the range of UAVs. From this three UAVs two are hijackable by this method and the third should also be hijackable with some modifications. This research could be a base later for UAV/UAS counter measure systems for the safety of all of us.

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Analysis of MRI Images for Brain Tumor Detection Using Fuzzy C-Means and LSTM 4th

Analysis of MRI Images for Brain Tumor Detection Using Fuzzy...

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4th International Conference on Information and Communication Technology for Intelligent Systems, ICTIS 2020

作者： Thapa, Sobit Panday, Sanjeeb Prasad Graduate Student Faculty of Engineering Nepal College of Information Technology Pokhara University Lalitpur Nepal Department of Electronics and Computer Engineering Pulchowk Campus Institute of Engineering Tribhuvan University Lalitpur Nepal

ISBN: (纸本)9789811570612

The collection and identification of medical images are the most important scientific task. MRI processing is also one of the reliable methods underpinning medical diagnosis. In this research, segmentation is performed by fuzzy C-means that detects the infected region from the images of brain MRI. Gray-level co-occurrence matrix (GLCM) is used to extract the features from the MRI images of the brain which gives the better result for classification than existing system. Long short-term memory (LSTM), a recurrent neural network extension method is used to identify brain MRI images. It gives a more precise and effective outcomes for image of MRI image classification. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance imaging

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Artificial intelligence in the detection and classification of dental caries

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Journal of Prosthetic Dentistry 2025年第5期133卷 1326-1332页

作者： Ahmed, Walaa Magdy Azhari, Amr Ahmed Fawaz, Khaled Ahmed Ahmed, Hani M. Alsadah, Zainab M. Majumdar, Aritra Carvalho, Ricardo Marins Assistant Professor Department of Restorative Dentistry Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Associate Professor Department of Orthopedic Surgery Faculty of Medicine Cairo University Cairo Egypt Assistant Professor Department of Civil Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia Consultant in Restorative Dentistry Dental Department East Jeddah General Hospital Ministry of Health Jeddah Saudi Arabia Graduate student Department of Computer Science Computer Science and Applications Virginia Polytechnic Institute and State University Blacksburg VA United States Professor Department of Oral Biological and Medical Sciences Faculty of Dentistry University of British Columbia Vancouver BC Canada

Statement of problem: Automated detection of dental caries could enhance early detection, save clinician time, and enrich treatment decisions. However, a reliable system is lacking. Purpose: The purpose of this study was to train a deep learning model and to assess its ability to detect and classify dental caries. Material and methods: Bitewings radiographs with a 1876×1402-pixel resolution were collected, segmented, and anonymized with a radiographic image analysis software program and were identified and classified according to the modified King Abdulaziz University (KAU) classification for dental caries. The method was based on supervised learning algorithms trained on semantic segmentation tasks. Results: The mean score for the intersection-over-union of the model was 0.55 for proximal carious lesions on a 5-category segmentation assignment and a mean F1 score of 0.535 using 554 training samples. Conclusions: The study validated the high potential for developing an accurate caries detection model that will expedite caries identification, assess clinician decision-making, and improve the quality of patient care. © 2025 Editorial Council for The Journal of Prosthetic Dentistry

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Prediction of the Impact of Covid-19 Vaccine on Public Health Using Twitter

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2022年第1期49卷 19-29页

作者： Syed, Ayesha Ayub Gaol, Ford Lumban Suparta, Wayan Abdurachman, Edi Trisetyarso, Agung Matsuo, Tukoro Ph.D. student at the Department of Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Associate Professor at Informatics Engineering and Information System at Bina Nusantara University Jakarta Indonesia Malaysia Associate Professor at the Department of Doctor of Research in Management at Bina Nusantara University Jakarta Indonesia Assistant Professor at the Department of Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Professor at the Graduate School of Industrial Technology Advanced Institute of Industrial Technology Japan and Department of M-Commerce and Multimedia Applications Asia University Taiwan

Social media is a source of big data. Media like Twitter and Facebook has been used for collecting and analyzing user data for different purposes. The data can be used to analyze people opinions towards certain topics and incidents by applying sentiment analysis and then certain useful insights can be drawn from the analyzed data. During the current time of Covid-19, people have been sharing information regarding Covid-19 statistics, vaccines, and discussing the effects of the vaccine concerning public health. The purpose of this study is to analyze tweet data regarding the Covid-19 vaccine by applying sentiment analysis and predicting the impact of the vaccine on public health. Also, the tweets are analyzed for hidden topics by applying Topic Modelling using Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA). The source of data for this study is Twitter API. The coding and data analysis is done using Python programming language in the Spyder (Scientific Python Development Environment) that is an integrated development environment for scientific programming, testing, and data analysis. The results of the study indicate a greater positive sentiment reflecting a healthy public discussion about the Covid-19 vaccine, information, awareness, and public acceptance. With these results, a positive impact of the Covid-19 vaccine on public health is predicted. The results of topic modeling discovered 10 hidden topics from the tweet dataset. © 2022. All Rights Reserved.

关键词： Vaccines

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Intelligent Analysis of Big Data in the Information Flow

Intelligent Analysis of Big Data in the Information Flow

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Information Computing and Processing (ICP), Seminar on

作者： Petr V. Chetyrbok Marina A. Shostak Candidate of Science Engineering and Associate Professor at the Department of Computer Studies and Information Technologies V.I. Vernadsky Crimean Federal University Simferopol Russia Graduate student at the Faculty of Tourism and Service Sochi State University Sochi Russia

The article considers the use of AI methods for creation of a knowledge base in the field of recreation using a national interactive map of local cultural trends. The map contains thousands of brands classified into 9...

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