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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Jain, Sanat Jain, Garima Phulre, Ajay Kumar Pagare, Shreyas Singh Mathur, Jitendra Pratap Singh Bhati, Vishal Vit Bhopal University Kothri-Kalan School of Computer Science and Engineering Sehore India Chameli Devi Group of Institutions Computer Science Engineering Department Indore India

ISBN: (纸本)9798350375442

In recent decades, vascular disease - which includes a variety of heart-related conditions - has emerged as the primary cause of death worldwide. There are numerous risks associated with heart disease, and it is important to have accurate, trustworthy, and sensible techniques for early detection in order to promptly manage the condition. One popular technique for analyzing large volumes of data in the healthcare industry is machine learning. Machine learning is a widely employed method for analyzing vast amounts of data in the field of healthcare. This paper focused on hyper parameter tuning of multi-classifiers to forecast the occurrence of various heart illnesses in patients and reduce the problem of over fitting. The dataset comprises 14 primary attributes with a proposed framework driven by multi classifier to get predictions. The results indicate that the LGBM classifier achieves the highest accuracy score with 99.7%. © 2024 IEEE.

关键词： Adversarial machine learning

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Attack Detection on Internet of Things Devices using Machine Learning Techniques 7

Attack Detection on Internet of Things Devices using Machine...

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7th International Conference on Intelligent Computing and control Systems, ICICCS 2023

作者： Sharma, Yatharth Kumar, Vansh Chaudhary, Himanshi KIET Group of Institutions Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350397253

Today, the exponential growth of technology and the boom in connection demand has resulted in significant growth of Internet of Things (IoT) devices. In light of the enormous increase in smart devices, secure communication between them has become a major challenge due to an increase in cyberattacks. Adding hardware-based security is challenging due to the complex architecture of IoT devices and limited computation ability. Since IoT devices produce enormous amount of data, machine learning (ML) can be utilized to detect attacks on IoT devices. This study proposes some Machine Learning models to detect and prevent Botnet IoT attacks. The Network-based Detection of Bait-and-Switch IoT Attacks (N-BaIoT) dataset is used to train the models. The performance of models is analyzed using precision, recall and F1-score by carrying out multiclass classification. Experimental result shows that some of the proposed models are efficient in detecting botnet attacks with 99% accuracy. The model can also extend to use complete dataset and new ML techniques. © 2023 IEEE.

关键词： Internet of things

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Image Caption using CNN in computer Vision

Image Caption using CNN in Computer Vision

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Kumar, Rohit Goel, Gaurav Chandigarh Group of College Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350322309

Programmatic captioning is the system of making captions or textual content primarily based totally on picture content material. This is an AI challenge that consists of each everyday speech processing (producing textual content) and PC vision (information picture content material). Program captioning is presently a completely lagging and evolving examination topic. Different new techniques are discovered little by little to obtain perfect outcomes on this area. Still, it takes a number of price to get human-equal outcomes. This studies is supposed to discover precise and present day strategies and fashions used for imaging with deep mastering in a particular manner. What strategies are carried out to apply those fashions, and what strategies provide right outcomes? To this end, we performed an green paper seek of late-level research from 2017 to 2022 from noteworthy datasets (Scopus, Web of sciences, IEEEXplore). A overall of sixty one considerable research had been observed which can be applicable to the factors on this study. It seems that CNN is used to recognize picture content material and hit upon gadgets in images, even as RNN or LSTM is used withinside the age of languages. The maximum normally used datasets are MS COCO, utilized in all tests, and Glimmer 8k and Glint 30k. The maximum normally used grading framework is BLEU (1-4) that's utilized in all grading. It became additionally cited that LSTM with CNN beat RNN with CNN. We observed that the 2 maximum promising strategies for going for walks this version are encoder-decoders and attention tools. Combining those can power huge outcomes. This studies gives course and concept for researchers thinking about including programmed closed captioning. © 2023 IEEE.

关键词： Grading

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Adaptive Particle Swarm Optimization of U-net Parameters for Marine Aquaculture Image Segmentation 13

Adaptive Particle Swarm Optimization of U-net Parameters for...

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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Zhao, Jin Wang, Jun Han, Min Fan, Jianchao School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Department of Computer Science Department of Data Science City University of HongKong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798331516147

Marine aquaculture image segmentation plays a crucial role in managing aquatic resources and environmental protection. Traditional deep learning models rely on manual parameter tuning for image segmentation, which limits their efficiency and accuracy. This paper proposes an adaptive Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the U-net model automatically. The algorithm dynamically adjusts the PSO parameters based on the population’s entropy and clustering metrics and employs a hill-climbing algorithm to address the issue of the PSO easily falling into local optima, enhancing the algorithm’s adaptability. The proposed algorithm updates and iterates particles to automatically find suitable model parameters. The remote sensing data used in this experiment were from the Yellow Sea aquaculture area near Dalian, China, with a segmentation accuracy of 91.8%. This method improves segmentation accuracy, reduces the burden of manual parameter tuning, and provides an effective solution for optimizing deep learning models. © 2025 IEEE.

关键词： Aquaculture

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Designing and Developing a CanSat for Environmental Monitoring and Scientific Exploration

Designing and Developing a CanSat for Environmental Monitori...

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2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Sharma, Harsh Sehgal, Abhinav Jindal, Harsh Dutta, Aditi Sharma, Bhawna Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh Group of Colleges Landran Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350380880

This research paper outlines the technical requirements for designing and building a CanSat. The CanSat must be no more than 0.700 kg and fit inside a cylindrical body with a diameter of 0.125 m and a height of 0.310 m. The container must be designed to be launched from a rocket and withstand 15 Gs of launch acceleration and 30 Gs of shockwaves. The CanSat must include essential sensors and provide real-time data on position, altitude, pressure, temperature, orientation, and power information. It must also be designed with a readily accessible battery compartment and a descent control system that includes a first parachute and a second descent control device. Communications must be established through the use of an XBEE radio, and the ground station must be designed and operated by the team. Additionally, the CanSat must be designed to aid recovery and have an external power switch with an indicator light or sound for turning on or off. Overall, this research paper provides a comprehensive guide for designing and building a CanSat that meets all of the requirements for participation in an Indian competition. By following these guidelines, teams can ensure that their CanSat is safe, reliable, and capable of providing real-time data during flight. © 2023 IEEE.

关键词： Rockets

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AquaID: Authentication for Underwater Nodes with Decentralised Identity 24

AquaID: Authentication for Underwater Nodes with Decentralis...

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18th ACM International Conference on Underwater Networks and Systems, WUWNET 2024

作者： Altamura, Nicola Giona, Emanuele Nati, Michele Petrioli, Chiara Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science Sapienza University of Rome Italy WSense Srl Italy

ISBN: (纸本)9798400711602

The increasing pervasiveness of digital infrastructures, also extending into marine domains, makes Underwater Wireless Sensor Networks (UWSNs) an essential tool for the development of novel marine sustainability and monitoring paradigms. Applications in sensitive scenarios may require data encryption, non-repudiation, and provenance tracking. Moreover, the broadcast nature of the underwater acoustic channel makes the task of identifying and authenticating nodes of critical importance. To meet such requirements, we introduce AquaID, a protocol for resource-constrained hardware that leverages Distributed Ledger Technologies (DLTs) and Decentralised Identities. It guarantees confidentiality, authentication, and integrity using low bandwidth and CPU usage, while supporting high scalability and interoperability. We validate our solution in a threefold manner: via embedded board implementation, network simulation, and sea trials using commercially-available acoustic modems and underwater nodes. We also include a cost comparison among possible DLT choices. Results show AquaID to be robust to scaling, achieving low authentication delays and overhead, thus proving suitable even for large deployments. © 2024 Copyright held by the owner/author(s).

关键词： Authentication

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ElderEase AR: Enhancing Elderly Daily Living with the Multimodal Large Language Model and Augmented Reality 24

ElderEase AR: Enhancing Elderly Daily Living with the Multim...

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2024 International Conference on Virtual Reality Technology, ICVRT 2024

作者： Song, Tianyu Liu, Zhengyi Zhao, Ruibin Fu, Jie Department of Computer Science and Technology School of Computer Science and Technology Intelligent Perception Group Anhui University Anhui Hefei China Chuzhou University Anhui Chuzhou China Department of Computer Science and Technology School of Computer Science and Technology Artificial Intelligence Group Anhui University Anhui Hefei China Department of Computer Science and Technology School of Information Engineering Intelligent Perception Group Chuzhou University Anhui Chuzhou China

ISBN: (纸本)9798400710186

Elderly individuals often face challenges in independent living due to age-related cognitive and physical decline. To address these issues, we propose an innovative Augmented Reality (AR) system, "ElderEase AR", designed to assist elderly users in their daily lives by leveraging a Multimodal Large Language Model (MLLM). This system enables elderly users to capture images of their surroundings and ask related questions, providing context-aware feedback. We evaluated the system’s perceived ease-of-use and feasibility through a pilot study involving 30 elderly users, aiming to enhance their independence and quality of life. Our system integrates advanced AR technology with an intelligent agent trained on multimodal datasets. Through prompt engineering, the agent is tailored to respond in a manner that aligns with the speaking style of elderly users. Experimental results demonstrate high accuracy in object recognition and question answering, with positive feedback from user trials. Specifically, the system accurately identified objects in various environments and provided relevant answers to user queries. This study highlights the powerful potential of AR and AI technologies in creating support tools for the elderly. It suggests directions for future improvements and applications, such as enhancing the system’s adaptability to different user needs and expanding its functionality to cover more aspects of daily living. © 2024 Copyright held by the owner/author(s).

关键词： Augmented reality

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Early Prediction of Coronary Artery Disease Using Data Mining Techniques

Early Prediction of Coronary Artery Disease Using Data Minin...

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2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Sharma, Harsh Jindal, Harsh Sehgal, Abhinav Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh Group of Colleges Landran Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350380880

Data mining can be defined as a process of extracting and discovering required data or patterns from big data sets, sorting them through large data sets and finding relationships that can help solve business problems through data analysis to predict the desired outcomes. Gregory Piatetsky-Shapiro coined the term 'knowledge discovery in databases' for the first workshop on the same topic (KDD-1989) and this term became more popular in AI and machine learning community. This paper gives a lightning overview of data mining and its relation to statistics discusses the emerging applications and techniques of the data mining that has been adapted by some of the healthcare organizations to predict and analyse the heart related disease and businesses for the efficient and predictable outcome. This paper also describes how to apply the different data mining techniques such as prediction, classification, regression, clustering, and association mining onto the patterns for the future excellent results. The term 'data mining' is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself. © 2023 IEEE.

关键词： Data mining

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EcoRoute: Ecosystem of Electric Vehicle by Optimizing Route for Long-Distance Travel 3

EcoRoute: Ecosystem of Electric Vehicle by Optimizing Route ...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Sharma, Harsh Jindal, Harsh Sehgal, Abhinav Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh Group of Colleges Department of Computer Science and Engineering Landran Mohali India

ISBN: (纸本)9798350302288

Electric vehicle (EV) owners in India are facing dissatisfaction due to the limited availability and reliability of charging infrastructure. One of the main concerns is the inadequate range of EVs, which creates difficulties for long-distance travel. For instance, if a user needs to travel inter-statefor 1000 km but their EV's range is limited to 350 km, they need to stop multiple times at charging stations to complete the trip. Unlike traditional petrol or gasoline-based cars, EVs require a considerable amount of recharge, meaning users must manuallyplan their charging stops and search for available charging stations. This problem statement highlights the challenge of ensuring that EVs are viable and convenient for long-distance travel in India, where the availability and accessibility of charging infrastructure remain a significant concern. These issues can be resolved by eliminating human intervention in the route planning process of any trip. To minimize human interference an algorithm is required that can generate a route plan for long-distance travel based on the real-time stats of the electric vehicle. Various parameters need to be considered to optimize the travel route, and to minimize the overall travel time by reducing the total charging time in between. © 2023 IEEE.

关键词： Travel time

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Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones

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Journal of Electronic science and Technology 2024年第4期22卷 19-36页

作者： Didar Yedilkhan Abzal E.Kyzyrkanov Zarina A.Kutpanova Shadi Aljawarneh Sabyrzhan K.Atanov Department of Computer Engineering Astana IT UniversityAstana010000Kazakhstan Department of Computer and Software Engineering L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Automation and Control Systems L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Software Engineering Jordan University of Science and TechnologyIrbid22110Jordan

The growing field of urban monitoring has increasingly recognized the potential of utilizing autonomous technologies,particularly in drone *** deployment of intelligent drone swarms offers promising solutions for enhancing the efficiency and scope of urban condition *** this context,this paper introduces an innovative algorithm designed to navigate a swarm of drones through urban landscapes for monitoring *** primary challenge addressed by the algorithm is coordinating drone movements from one location to another while circumventing obstacles,such as *** algorithm incorporates three key components to optimize the obstacle detection,navigation,and energy efficiency within a drone ***,the algorithm utilizes a method to calculate the position of a virtual leader,acting as a navigational beacon to influence the overall direction of the ***,the algorithm identifies observers within the swarm based on the current *** further refine obstacle avoidance,the third component involves the calculation of angular velocity using fuzzy *** approach considers the proximity of detected obstacles through operational rangefinders and the target’s location,allowing for a nuanced and adaptable computation of angular *** integration of fuzzy logic enables the drone swarm to adapt to diverse urban conditions dynamically,ensuring practical obstacle *** proposed algorithm demonstrates enhanced performance in the obstacle detection and navigation accuracy through comprehensive *** results suggest that the intelligent obstacle avoidance algorithm holds promise for the safe and efficient deployment of autonomous mobile drones in urban monitoring applications.

关键词： Drone swarms Fuzzy logic Intelligent solution Smart city Urban monitoring

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