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ShieldSMS Sentinel: Guardian of Your Digital communication Bastion 2

ShieldSMS Sentinel: Guardian of Your Digital Communication B...

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2nd DMIHER international conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gourshettiwar, Palash Thakare, Rajesh D. Duddalwar, Prapti Shete, Rushikesh Gundewar, Swapnil Verma, Prateek Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha442001 India Yashavantrao Chavan College of Engineering Department of Electronics Engineering Maharashtra Nagpur440002 India Vishwakarma Institute of Technology Department of Electronics Engineering Maharashtra Pune411037 India St. Vincent Pallotti College of Engineering and Technology Department of Computer Science and Business Systems Maharashtra Nagpur440002 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India

ISBN: (纸本)9798331528713

The SMS spam detection Project provides a comprehensive framework for reliably identifying and classifying spam messages sent over SMS communication channels by fusing ML algorithms with NLP techniques. Using EDA, a dataset of labelled SMS messages identified as spam or ham is thoroughly studied to reveal patterns in the word count, sentence count, and message length distributions. Then, unstructured text is transformed into structured data that may be utilized with ML models through tokenization, punctuation and stop word removal, stemming, and other text preprocessing techniques. Feature engineering, which numerically represents text data using vectorization techniques like BoW and TF-IDF, plays a significant role. Various ML algorithms, including Gaussian Naive Bayes, Multinomial Naive Bayes, SVM, and ensemble approaches, are trained and evaluated. Performance metrics, including accuracy and precision, serve as standards for model selection. © 2024 IEEE.

关键词： Text messaging

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A Transfer Learning-Based Approach for Multi-class Classification of Pulmonary Diseases 2

A Transfer Learning-Based Approach for Multi-class Classific...

引用

2nd international conference on Advances in Computation, communication and Information technology, ICAICCIT 2024

作者： Bansal, Twinkle Gupta, Sheifali Jindal, Neeru Electronics and Communication Department Chitkara University Institute of Engineering and Technology Punjab Rajpura India Electronics and Communication Department Thapar Institute of Engineering and Technology Punjab Patiala India

ISBN: (纸本)9798331541217

The prevalence of pulmonary diseases is experiencing a notable escalation. The year 2019 witnessed a global phenomenon characterized by the swift emergence and expansion of COVID-19, which gave rise to a state of heightened concern on a worldwide scale. The timely detection of pulmonary diseases is of utmost importance due to the potential fatality associated with these conditions. The utilization of chest X-ray (CXR) is prevalent in the healthcare industry, as it offers a rapid and accurate diagnosis. This research paper presents a proposed deep learning (DL) architecture to achieve numerous classifications of COVID-19, Viral Pneumonia, as well as Normal cases. To ensure a balanced representation of data, a composite dataset was constructed by merging two publicly accessible datasets. The dataset utilized in our study constitutes a total of 4500 chest X-ray data, with an equal distribution of 1,500 images for each class. In the context of classification, our research has employed four pre-trained models, namely InceptionV3, InceptionResNetV2, ResNet101V2, and Xception. These models have been selected due to their established performance and effectiveness in various classification tasks. By utilizing these pre-trained networks, we aim to leverage their learned features and weights to enhance the accuracy and efficiency of our classification system. © 2024 IEEE.

关键词： Lung cancer

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IntegraSec: Securing IoT with an Integrated Lightweight Privacy-Aware Publish-Subscribe Framework 2

IntegraSec: Securing IoT with an Integrated Lightweight Priv...

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2nd IEEE international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Chamarajappa, Rashmi H. Dyamanna, Guruprakash C. Sri Siddhartha Institute of Technology Ssahe Department of Information Science & Engineering Tumkur India Sri Siddhartha Institute of Technology Ssahe Department of Computer Science and Engineering Tumkur India

ISBN: (纸本)9798350306415

Publish/subscribe(pub/sub) communication in IoT healthcare systems enables efficient and real-time dissemination of patient data, facilitating timely medical interventions and remote monitoring. Moreover, the pub/sub model has characteristics of loose coupling which could lead to security and privacy;this paper introduces a comprehensive security framework IntegraSec which integrates the lightweight design, LAA (Lightweight Authentication based on anonymity), LAC(lightweight access control), principle based on the AE(Asymmetric Encryption) based model integrated with different model such as anonymous authentication through, user registration and so on to enhance the access control and data privacy. Moreover, the proposed model secures the pub/sub model by safeguarding the content, securing the subscriber identity and publication authenticity for lightweight secure communication. Considering the lightweight approach IntegraSec improvises the overhead in terms of storage and communication. © 2024 IEEE.

关键词： IntegraSec IoT lightweight pub/sub model security

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Cloud-Enabled Wireless Gesture Control System for Humanoid Bionic Arm Using IOT 2

Cloud-Enabled Wireless Gesture Control System for Humanoid B...

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

作者： Geetha, S. Vichitra, S. Nithiya Shree, M. Sandhiya, V. Yuvarani, V. VSB Engineering College Computer Science and Engineering India

ISBN: (纸本)9798350368109

The Internet of Things (IOT) connects Tangible assets via data fusion facilitating information interchange. Ranging from basic temperature sensors to sophisticated industrial robots, IOT covers a wide range of applications. Cloud computing offers immediate access to computing services, reducing infrastructure expenses. Inclinometer sensors and cameras combine for advanced hand gesture recognition, capturing initial movements through real time video analysis. An innovative IR - based recognition system, supported by Intelli-cloud and AES (Advanced Encryption Standard) security, enhances the framework. Technological progress narrows the human-machine divide, highlighting gestures in communication. Hand-arm robotic research emphasizes freedom levels, grip efficacy, and adaptability using sensor-focused methods, shaping the evolution of human-robot interaction. © 2024 IEEE.

关键词： Human robot interaction

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Towards Designing an Information Superhighway for Neurological Disorders 2

Towards Designing an Information Superhighway for Neurologic...

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2nd international conference on Computational Intelligence, communication technology and Networking, CICTN 2025

作者： Mazumdar, Bireshwar Dass Gupta, Prashant K. Singh, Mohak Singh, Sujal School of Computer Science & Engineering Technology Bennett University Uttar Pradesh Greater Noida India

ISBN: (纸本)9798331530389

Neurological Disorders impact a subject's/person's nervous system in various ways and include a wide range of neurological conditions. More often than not, the impact is life altering and affects the subject's communication skills, social interaction capability, etc. If the condition is detected at an early age, it can significantly enhance the quality of life of the subject with focused training, treatment, etc. Detection through brain scans, behavioral analysis, etc. are costly and time consuming. Recently artificial intelligence (AI) models are being increasingly used for detection & classification of neurological disorders based on various parameters and datasets. However, for an end user, it's still very difficult to realize the power of these models end to end viz., from data acquisition to generating recommendations. Hence, in this paper, we present the architecture of an Information Superhighway in the form of AI pipeline. The task of the Information Superhighway is to enable capturing the multimodal data (image, video, etc.) of a subject from a smartphone of a laptop webcam, and send this through a secure information channel to a cloud storage. On the storage, the data is managed using various Big data technologies and is acted upon by the DL models. The generated recommendations are sent back through a different secure communication channel back to the mobile or laptop. We feel that our work is first of its kind which makes the technology transfer possible for the end user and utilize full the prowess of powerful AI models. © 2025 IEEE.

关键词： Diseases

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Next-Generation IoT Intrusion Detection: Leveraging Hybrid Deep Learning Algorithms for Enhanced Security 2

Next-Generation IoT Intrusion Detection: Leveraging Hybrid D...

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2nd international conference on Computational Intelligence, communication technology and Networking, CICTN 2025

作者： Urvashi Agarwal, Parul Raghuvanshi, Kamlesh Kumar Ahmed, Jawed Department of Computer Science and Engineering Jamia Hamdard University Delhi India Department of Computer Science University of Delhi Delhi India

ISBN: (纸本)9798331530389

Wireless sensor node and DDoS (Distributed Denial of Service) is a major attack way that can exhaust the energy of a sensor, disrupt the communication traffic of an IoT network. We must be on the lookout for these attacks. With the quantity of sensor nodes, traditional methods face difficulty in detecting network traffic analysis requiring big data analysis. This paper is dedicated to Network Traffic analysis using Big data environment and detecting attacks using Deep Learning. Implemented with PySpark in Google Colab, using Keras and Scikit-Learn built-in libraries. To be more specific, training and testing are conducted on the 'CICIoT2023'/'TON IoT' datasets, respectively. When we use a correlation feature reducer, it virtually considers the most significant features for inclusion and reduces all of our features. The first contains a hybrid deep leaning model combining one-dimensional EfficientDet and Gradient Boosting Machine (GBM), comparing it with ten other algorithms. It gen- erated 99.95% binary classification accuracy for the CICIoT2023 dataset and 99.75% for TON IoT data. © 2025 IEEE.

关键词： Network intrusion

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Revolutionizing Road Surface Classification: Integrating Vibration data and MCNN for Enhanced Pothole Detection 2

Revolutionizing Road Surface Classification: Integrating Vib...

引用

2nd international conference on Advances in Computation, communication and Information technology, ICAICCIT 2024

作者： Imran Hussain, S. Athunan, M. Maadesh Sivam, S. Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9798331541217

The existing techniques for categorizing road surfaces mainly rely on visual inspection or image analysis whose reliability and performance are limited in ugly climate ones. The unique contribution of the study is a proposed learning based novel solution that combines accelerometer-based vibration data fed into multiple channels of features to accurately identify potholes and rigid surface irregularities via multi-channel neural network (MCNN). Using motion responses detected by the accelerometer in conjunction with live imagery taken from a Raspberry Pi camera, the system provides accommodating detection of variations under different scenarios. Testing reveals the proposed configuration attains a precision of 94.5% and an exceptionally low false positive rate of only 5.4%, handily outperforming past solutions. The creative integration of diverse inputs not only strengthens detection capabilities but also enables quick processing, permitting immediate feedback to optimize upkeep, fundamentally changing infrastructure management and ensuring enhanced safety for all road users. © 2024 IEEE.

关键词： Vibration analysis

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Study on Underwater Acoustic Network Fairness Transmission Method Based on Deep Reinforcement Learning 24

Study on Underwater Acoustic Network Fairness Transmission M...

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2nd international conference on Artificial Intelligence, Systems and Network Security, AISNS 2024

作者： Bi, Zhicheng Xiao, Jinfeng Wang, Chaofeng School of Electrical Engineering University of South China Hunan Hengyang China

ISBN: (纸本)9798400711237

Underwater acoustic communication networks can satisfy the need for long-distance reliable communication for underwater node, serving as a key technology for the informatization and intelligentization of such communication. However, due to the use of sound waves as a carrier for information, underwater acoustic networks face complex challenges such as long propagation delays, severe channel attenuation, multipath effects, and environmental noise. To enhance the communication efficiency and reduce network congestion of underwater acoustic networks, this study proposes a MAC protocol based on deep reinforcement learning to adaptively adjust the transmission strategy of network nodes. Each network node collaboratively decides the optimal transmission slot based on its own data buffer status and the history of transmission conflicts, to suppress transmission conflicts and thereby maximize transmission rates. Simulation results show that the designed protocol significantly improves the network throughput while ensuring the fairness of transmission among nodes, providing an important foundation for the rapid exchange of information between underwater nodes. © 2024 Copyright held by the owner/author(s).

关键词： Deep reinforcement learning

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Implementation of Medium Current Control for Grid-Connected PV for Maximum Power Point Tracking 2

Implementation of Medium Current Control for Grid-Connected ...

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2nd international conference on Intelligent data communication Technologies and Internet of Things, IDCIoT 2024

作者： Satish, G. Muthuraman, A. Tripathy, Prashanta Kumar Hemachandu, P. Kumar, Kallakunta Ravi Singh Bohra, Narendra Sree Dattha Institute of Engineering and Science Department of Electrical and Electronics Engineering Hyderabad501510 India Mailam Engineering College Department of Electrical and Electronics Engineering Mailam604304 India Srinix College of Engineering Department of Electrical Engineering Balasore756003 India Sasi Institute of Technology and Engineering Department of Electrical and Electronics Engineering Tadepalligudem534101 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communications Engineering Andhra Pradesh Vaddeswaram522302 India Graphic Era Deemed to Be University Department of Management Studies Dehradun248002 India

ISBN: (纸本)9798350327533

This research study describes a grid-connected photovoltaic (PV) system that uses medium current management and the Disturb & Observe approach to find the Maximum Power Point Tracking (MPPT) with varying solar radiation levels. PSIM was used to model the circuit. A sinusoidal waveform was possible for the current injection with the use of a passive series LC filter. With a low harmonic distortion rate (HDR) of 10%, the power factor remains high 0.99. © 2024 IEEE.

关键词： Grid injection Harmonic Distortion Rate Photovoltaic Solar Energy

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Blockchain-Driven Blood Donation: Overcoming Challenges and Building Trust in Healthcare 2

Blockchain-Driven Blood Donation: Overcoming Challenges and ...

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2nd international conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Malhotra, Manav Mukherjee, Pratyusa Aich, Madhurima Chhawan, Saksham School of Computer Engineering Kiit Deemed to Be University Bhubaneswar751024 India

ISBN: (纸本)9798350370188

Blockchain technology has been a fascinating research topic for a very long time because of its security, privacy, secrecy, and decentralization, blockchain technology has a lot to offer the healthcare sector. Electronic health record (EHR) systems have challenges with data management, security, and integrity. Because of problems like duplicate data and insufficient records, the accuracy of patient information is in jeopardy and make it difficult to communicate data and coordinate care. We offer a framework that can transform EHR systems by enhancing data management, improving interoperability, boosting security and privacy, and reducing costs. It ensures data accuracy, facilitates communication between EHR systems, enhances data security, and streamlines operations, making it a promising solution for EHR challenges. © 2024 IEEE.

关键词： Blockchain

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