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IoT Based Control Networks and Intelligent Systems (ICICNIS), International Conference on

作者： Pradeep C Julia Punitha Malar Dhas Deva Priya Isravel Division of Computer Science and Engineering School of Computer Science and Technology Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

The rapid growth of the Internet of Vehicles (IoV) greatly enhances the communication and data exchange capability between vehicles, which allows the real-time transmission of critical information. The CAN bus is the backbone developed to transmit data between Electronic Control Units in the in-vehicle networks and it is prone to various cyberattacks that can breach its security and integrity. To identify cyberattacks on a CAN bus this paper proposes a deep learning model employing a Variational Autoencoder in conjunction with Long Short-Term Memory (LSTM) that features an integrated attention mechanism. The proposed model leverages the temporal characteristics of CAN bus traffic to detect anomalies by identifying the differences in the reconstruction loss. The CICIoV2024 dataset, containing benign and malicious messages for the CAN bus, was used for the proposed model, which achieved high effectiveness with the accuracy of 99.78%, precision of 99.81%, a recall of 99.32%, and F1 score of 99.56%. The results show that the model is strong in accurately detecting unusual behaviour and offers a flexible solution for improving cybersecurity in IoV systems.

关键词： Deep learning Attention mechanisms Accuracy Autoencoders Real-time systems computer crime Intelligent systems Long short term memory Anomaly detection Internet of Vehicles

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Spacecraft potential effects on low-energy ion measurements to be made by probe B1 of Comet Interceptor

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RAS Techniques and Instruments 2024年第1期3卷 333-346页

作者： Bergman, S. Kasahara, S. Stenberg Wieser, G. Division of Space and Plasma Physics School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Department of Earth and Planetary Science Graduate School of Science The University of Tokyo Swedish Institute of Space Physics

Spacecraft charging causes notorious issues for low-energy plasma measurements. The charged particles are accelerated towards or repelled from the spacecraft surface, affecting both their energy and travel direction. The latter results in a distortion of the effective field of view (FOV) of the instrument making the measurements. The Comet Interceptor mission, planned to be launched in 2029, will make a flyby of a long-period or interstellar comet that ideally is dynamically new. The mission comprises one main spacecraft A, developed by the European Space Agency (ESA), and two sub-probes B1 and B2, developed by the Japan Aerospace Exploration Agency and ESA, respectively. The low-energy plasma measurements made by Comet Interceptor will likely be affected by the spacecraft potential in the case of low relative flyby velocities. On probe B1, the Cometary Ion Mass Spectrometer (CIMS) of the Plasma Suite is an ion mass spectrometer, capable of measuring ions with energies down to 10 eV/q. In this work, we use the Spacecraft Plasma Interaction Software to study the influence of the spacecraft potential on the low-energy ion measurements to be made by CIMS in the inner cometary magnetosphere. The results show that the effective FOV of CIMS is distorted at low energies when the flyby velocity is low. The distortion level is highly geometry dependent, and the largest distortions are caused by the magnetometer boom. Furthermore, the results show that cold ions with bulk velocities in the range 1-10 km s-1, flowing both radially away from and inward towards the nucleus, are detectable by the instrument considering the nominal observation geometry. © 2024 The Author(s).

关键词： Comets Data Methods Instrumentation Numerical Methods Plasma SPIS

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Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

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computer Systems Science & engineering 2023年第6期45卷 3053-3077页

作者： Ernesto Lee Furqan Rustam Hina Fatima Shahzad Patrick Bernard Washington Abid Ishaq Imran Ashraf Department of Computer Science Broward CollegeBroward CountFloridaUSA Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Division of Business Administration and Economics Morehouse CollegeAtlantaGAUSA Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

With the increasing usage of drugs to remedy different diseases,drug safety has become crucial over the past few *** medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different *** diversification is both helpful and danger-ous as such medicine proves to be more effective or shows side effects to different *** clinical trials,side effects are reported when the medicine is used by the mass public,of which several such experiences are shared on social media platforms.A system capable of analyzing such reviews could be very helpful to assist healthcare professionals and companies for evaluating the safety of drugs after it has been *** analysis of drug reviews has a large poten-tial for providing valuable insights into these ***,this study proposes an approach to perform analysis on the drug safety reviews using lexicon-based and deep learning techniques.A dataset acquired from the‘***’contain-ing reviews of drug-related side effects and reactions,is used for experiments.A lexicon-based approach,Textblob is used to extract the positive,negative or neu-tral sentiment from the review *** classification is achieved using a novel hybrid deep learning model of convolutional neural networks and long short-term memory(CNN-LSTM)*** CNN is used at thefirst level to extract the appropriate features while LSTM is used at the second *** well-known machine learning models including logistic regression,random for-est,decision tree,and AdaBoost are evaluated using term frequency-inverse docu-ment frequency(TF-IDF),a bag of words(BoW),feature union of(TF-IDF+BoW),and lexicon-based *** analysis with machine learning models,long short term memory and convolutional neural network models,and state-of-the-art approaches indicate that the proposed CNN-LSTM model shows superior performance with an 0.96 *** also

关键词： Drug safety analysis lexicon-based techniques drug reviews sentiment analysis machine learning CNN-LSTM

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Future Intelligent Autonomous Robots, Ethical by Design. Lessons Learned from Autonomous Cars Ethics 14

Future Intelligent Autonomous Robots, Ethical by Design. Les...

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14th International Conference on Society and Information Technologies, ICSIT 2023

作者： Dodig-Crnkovic, Gordana Holstein, Tobias Pelliccione, Patrizio Thavarasa, Jathoosh Division of Computer Science and Software Engineering Mälardalen University Västerås Sweden Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Information Engineering Computer Science and Mathematics University of l'Aquila L'Aquila Italy Software Engineering Efrei Paris Villejuif France

ISBN: (纸本)9781950492701

The "ethical by design" approach involves examining all stages of a lifecycle of technology to ensure that they are ethically justifiable and socially sustainable. Building on our work on the ethics of autonomous intelligent robocars, and studies of the literature on the ethics of robotics, we propose for robot applications a set of values and ethical principles including safety, security, privacy, transparency, and explainability, accountability, fairness, human control, well-being, autonomy and freedom, and sustainability. This may help stakeholders in the field of intelligent autonomous robotics to connect ethical principles with their applications. Most ethical considerations we identified in our work on autonomous cars are relevant to all AI-powered robots, but robots require additional examination depending on their application domain, such as social robots (care robots, personal companions, robots used in education, health care, elderly care, education, entertainment, chat-bots), industrial robots, etcetera. Thus, existing ethical frameworks need to be applied in a context-sensitive way, by assessments in interdisciplinary, multi-competent teams through multi-criteria analysis. Furthermore, we argue for the need for continuous development of ethical principles, guidelines, and regulations, informed by the progress of technologies and involving relevant stakeholders. This implies designing the socio-technical system as an intelligent learning ecology. © 2023 Proceedings ICSIT, International Conference on Society and Information Technologies. All rights reserved.

关键词： Intelligent robots

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WU-Net++: A novel enhanced Weighted U-Net++ model for brain tumor detection and segmentation from multi-parametric magnetic resonance scans

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Multimedia Tools and Applications 2024年第28期83卷 71885-71908页

作者： Das, Suchismita Dubey, Rajni Jena, Biswajit Tsai, Lung-Wen Saxena, Sanjay Department of Computer Science and Engineering International Institute of Information Technology Bhubaneswar India School of Computer Engineering KIIT Deemed to Be University Bhubaneswar India Division of Cardiology Department of Internal Medicine Taipei Medical University Hospital Taipei111031 Taiwan Department of Computer Science and Engineering Institute of Technical Education and Research SOA Deemed to Be University Bhubaneswar India Department of Medicine Research Taipei Medical University Hospital Taipei111031 Taiwan Department of Information Technology Office Taipei Medical University Hospital Taipei11031 Taiwan Graduate Institute of Data Science College of Management Taipei Medical University Taipei11031 Taiwan

Brain tumor detection and segmentation from multi-parametric magnetic resonance (MR) scans are crucial for the prognosis and treatment planning of brain tumor patients in current clinical practice. With recent technological advancements, artificial intelligence-based deep learning has proven its indispensable image analysis capability in the most challenging tasks. This study proposes an automated WU-Net + + deep learning model for brain tumor segmentation using multiparametric structural MR scans obtained from the BraTS 2018 dataset. The model was validated through cross-dataset testing for intracranial hemorrhage (ICH) classification (ATLAS V2.1 dataset) and multi-organ segmentation from abdominal images of TCIA and BTCV datasets. The WU-Net++ model, a novel version of U-Net, was developed by adjusting its pooling operation as a weighted function of max and average pooling for brain tumor segmentation. The proposed model (WU-Net + +) achieved an F1 score of 0.94 ± 0.124, a dice score of 0.91 ± 0.132, and an AUC value of 0.915 for whole tumor segmentation. The model also achieved a high accuracy of 0.9949 ± 0.121 in ICH classification and dice scores of 0.912 ± 0.21, 0.844 ± 0.25, and 0.893 ± 0.17 for spleen, esophagus, and portal and splenic vein segmentation, respectively. Our study revealed that WU-Net + + has significant potential to improve the accuracy of segmentation and could be an effective method in the era of precision medicine. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Magnetic resonance imaging

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Medilocker: Transforming Healthcare Management with Role-Based Coordination and Real-Time Emergency Response

Medilocker: Transforming Healthcare Management with Role-Bas...

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International Conference on Trends in Electronics and Informatics (ICEI)

作者： Babish B Deva Priya Isravel Julia Punitha Malar Dhas Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

Medilocker is a role-based healthcare management system designed to enhance communication, coordination, and service efficiency across various healthcare roles, including patients, doctors, emergency responders, chief doctors, and administrators. The system integrates advanced emergency response capabilities, enabling real-time allocation of medical resources for rapid intervention in critical situations. Medilocker also offers a unified platform for prescription and medication management, with oversight by chief doctors to ensure consistent, high-quality care and reduce errors. Integrated geolocation services identify nearby hospitals and pharmacies, facilitating timely medical assistance and medication access to address patient needs. This comprehensive solution aims to streamline healthcare operations, reduce response times in emergencies, and improve patient outcomes by offering an accessible, coordinated platform for all stakeholders, ultimately advancing healthcare delivery standards.

关键词： Geology Medical services Emergency services Market research Real-time systems Time factors Resource management Stakeholders Informatics Standards

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Real-Time Birds Breed Classification and Health Monitoring Using YOLOv8

Real-Time Birds Breed Classification and Health Monitoring U...

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International Conference on Trends in Electronics and Informatics (ICEI)

作者： D Gowtham Deva Priya Isravel Julia Punitha Malar Dhas Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

The advancement of computer vision technologies has revolutionized pet health management by enabling real-time detection systems that can classify pet breeds and identify disease symptoms with high accuracy. A real-time detection system using the YOLOv8 algorithm offers significant potential for automated breed classification of pet birds and the detection of disease symptoms; aiding veterinarians in health monitoring and helping pet owners better manage their pets' well-being. By recognizing the general characteristics and features from images or live video feeds from multiple sources, this system can accurately identify the breed of a pet and detect visible signs of common illnesses such as avian influenza. This capability enables early intervention, allowing for a more proactive approach to pet health management. The integration of computer vision techniques overcomes challenges associated with manual assessments, enhancing the accuracy and consistency of health monitoring. Additionally, the system's design incorporates adjustable parameters to accommodate a wide variety of pet breeds and health conditions, ensuring adaptability and comprehensive coverage for effective pet health management.

关键词： computer vision Accuracy Streaming media Birds Real-time systems Classification algorithms Reliability Monitoring System analysis and design Diseases

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Machine Learning-based Immune Cell Classification for Enhanced Immunological Analysis

Machine Learning-based Immune Cell Classification for Enhanc...

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Electronics and Renewable Systems (ICEARS), International Conference on

作者： Naveen Pranouv S S Deva Priya Isravel Julia Punitha Malar Dhas Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

The automated classification of immune cells plays a vital role in advancing immunological research, diagnostics, and therapeutic monitoring. This paper leverages machine learning and image processing techniques to accurately classify various immune cell types from microscopic images by analyzing cellular features such as shape, size, and texture. The proposed Convolutional Neural Networks (CNN) based system integrates digital pathology workflows to provide a reliable and efficient tool for immune cell classification, reducing reliance on manual inspection. The model trained on a diverse dataset of labeled immune cell images to ensure high classification accuracy and adaptability across different cell types and imaging conditions. The proposed model provides a proactive solution to immunology research challenges, enhancing both the precision and efficiency of immune cell classification.

关键词： Deep learning Pathology Adaptation models Renewable energy sources Accuracy Shape Manuals Streaming media Convolutional neural networks Cancer

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Developing a Temperature and Humidity Diagnostic System for the Optical and Electronic Infrastructure of a Primary Caesium Quantum Clock 1

Developing a Temperature and Humidity Diagnostic System for ...

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1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Gahlawat, Devansh Basu, Rikmantra Sharma, Ajay Kumar Arora, Poonam Kaur, Jaspinder National Institute of Technology Delhi Department of Electronics and Communication Engineering New Delhi India Institute of Technology Delhi Department of Computer Science and Engineering National New Delhi India CSIR-National Physical Laboratory Indian Standard Time Division New Delhi India

ISBN: (纸本)9798350364590

Caesium quantum clocks, pivotal in defining the SI second since the 13th General Conference on Weights and Measures in 1967, rely on intricate electronic and optical systems for precise timekeeping. Ensuring the accuracy of these systems requires monitoring and controlling environmental parameters like temperature and humidity, as fluctuations can lead to errors and potential damage. This paper presents the development of a diagnostic system using an Arduino UNO connected to a DHT11 sensor and ESP8266 Wi-Fi module to continuously monitor and transmit environmental data. The collected data is analyzed to maintain optimal operating conditions for the quantum clock infrastructure. Implementations using the IoT platform ThingSpeak demonstrate the system's capability for real-time data visualization and analysis. Statistical analysis of sampled data over a 30-minute interval shows a mean temperature of 23.45°C and a mean humidity of 51.30%, with a strong correlation coefficient of 0.99 between the two parameters. A linear regression analysis further supports this relationship, indicating that for every 1°C increase in temperature, humidity increases by approximately 5.11%. This diagnostic system not only ensures environmental stability but also aids in preventing inaccuracies in timekeeping, enhancing the reliability of caesium quantum clocks. © 2024 IEEE.

关键词： Optical correlation

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MEMS Design Process Based Simulation and Analysis of a Hypothetical Sensor Design with Electromechanics Interface 2nd

MEMS Design Process Based Simulation and Analysis of a Hypot...

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2nd International Conference on Data Security and Privacy Protection, DSPP 2024

作者： Sathish, K. Ravikumar, C.V. Su, Chunhua Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Deemed University Chennai602105 India School of Electronics Engineering Vellore Institute of Technology Vellore632014 India Division of Computer Science University of Aizu Aizuwakamatsu City Fukushima965-8580 Japan

ISBN: (纸本)9789819785452

This study simulates and examinesthe MEMS design process for a hypothetical sensor with an electromechanical interface. Conceptualizing the sensor entails establishing its purpose, operational environment, and capacitive sensing mechanism for sensitivity and precision. Geometric and physical models are developed using advanced COMSOL Multiphysics software to create a moveable proof mass supported by micro-fabricated beams. Static and dynamic finite element analysis (FEA) simulations can be used to evaluate the sensor’s mechanical reaction to input signals and electrode electrostatic forces. This guarantees that mechanical signals are properly transformed into electrical signals. These data are evaluated to determine the best performance criteria such as sensitivity, linearity, and thermal stability, resulting in iterative design improvements. Robustness analysis, including tolerance and FMEA, ensures dependability. Additionally, typical MEMS manufacturing technologies are being examined for fabrication. This simulation-driven strategy prioritises electro-mechanical interface issues throughout the design process, resulting in high-performance, and dependable MEMS sensors for a wide range of applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Microchannels

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