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computer, Communication and Control (IC4), International Conference on

作者： m. Ahsan Shariff S P Vimal B. Gopi A. Anbarasi R Tharun C. Srinivasan M.Tech Computer Science and Engineering Sri Sai Ram Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Muthayammal Engineering College (Autonomous) Rasipuram Tamil Nadu India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Civil Engineering Mother Theresa Institute of Engineering and Technology Palamaner Andhra Pradesh India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

To improve text input for motor-disabled people, this research uses the Internet of Things (IoT) and machine learning. Swipe-to-Type, a popular touch-based input technique, is the study’s focus. User swipe motions and contextual data are collected in real-time using IoT devices. A machine learning framework trains the algorithm to adapt to disabled users’ motor skills and preferences. Addressing motor impairment problems, the suggested method improves text input efficiency and personalization. The Swipe-to-Type algorithm is constantly adjusted based on learned patterns to maximize text input speed and accuracy. Integration of IoT devices allows continuous monitoring and adaption, guaranteeing a responsive and user-centric solution. The study technique includes motor disability data gathering, machine learning model creation, and algorithm refining. Preliminary text input performance enhancements may improve communication and accessibility for motor-disabled people. By using IoT and machine learning to empower motor-disabled persons, this research advances assistive technology. The results show that adjusting input techniques to varied user demands is feasible and successful, encouraging digital inclusion.

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Revolutionizing mouse Cursor Control for Enhanced User Interaction

Revolutionizing Mouse Cursor Control for Enhanced User Inter...

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Visual Analytics and Data Visualization (ICVADV), International Conference on

作者： L Sherin Beevi P. m. Joe Prathap Harsha G Jeeva N Jeevashree R W Vinil Dani Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai INDIA Department of EEE St. Peter's College of Engg.and Tech. Chennai INDIA

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

This research explores the innovative integration of eye and mouth-based interactions in Human-computer Interaction (HCI) to enhance user engagement and system responsiveness. Leveraging advanced technologies such as eye-tracking and lip detection, our study focuses on developing a multimodal interface that interprets users' gaze and lip movements for intuitive and efficient interaction with digital systems. The eye-tracking component of the device allows for precise tracing of users' visual focus, facilitating natural cursor control and attention-based interactions. Concurrently, the lips detection system captures nuanced lip movements, expanding the input modalities to include non-verbal cues, gestures, and expressions. The integration of eye and mouth-based interactions introduces a dynamic and expressive dimension to HCI, catering to users with diverse abilities and preferences. Through a series of experiments and usability evaluations, we assess the system's effectiveness in tasks ranging from navigation to expressive communication. The findings showcase the potential for a more inclusive and adaptive HCI paradigm, where users can seamlessly navigate digital environments using a combination of eye gaze and facial expressions. This study adds to the growing landscape of HCI by proving the feasibility and benefits of adding eye and mouth-based interactions, paving the path for more natural and personalized human-computer interaction.

关键词： Navigation Lips Visual analytics merging mouth Gaze tracking Speech recognition User experience Distance measurement Usability

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Hybrid Deep Learning model for Copy move Image Forgery Detection 6

Hybrid Deep Learning Model for Copy Move Image Forgery Detec...

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6th International Conference on I-SmAC (IoT in Social, mobile, Analytics and Cloud), I-SmAC 2022

作者： Prabakar, D. Ganesan, R. Leela Rani, D. Neti, Praveen Kalyani, N. mudradi, Shreesha Kalkoor Sns College of Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore641035 India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai600062 India Sree Vidyanikethan Engineering College Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Aditya College of Engineering Department of Computer Science & Engineering Andhra Pradesh Surampalem533437 India R.M.K College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Thiruvallur601206 India Sambhram Institute of Technology Department of Electronics and Communication Engineering Karnataka Bangalore560097 India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

Digital image processing software has progressed to the point where it is trivial to create forgeries by employing various manipulative tactics on the actual (real) images. Professions including law, health, and education are vulnerable to modified images. Hence, it is essential to be able to determine whether or not an image is fake. One form of image fraud is called 'copy-move,' in which a key object or objects are hidden from view by copying and pasting them into the same image. many Copy-move Forgery Detection (CmFD) models are rendered useless when the copied section contains noise or is resized before being pasted. Our goal of this research was to develop a highly effective and efficient detection method for this type of image forgery by utilizing a hybrid Deep Learning (DL) architecture. Firstly, the sample images are taken from mICCF2000. Second, alter the size of the images, and a filtering technique is used to eliminate any noise that may have been present in the original image. Finally, we combine Convolutional Neural Networks (CNN) and Support Vector machine (SVm) to build a hybrid DL model. measures such as accuracy, True Positive (TPR) and Negative Rate (TNR), False Positive Rate (FPR) and Negative Rate (FNR), Precision, and F1-score are used to verify the developed hybrid DL model. Using the proposed hybrid DL model, we were able to detect fake images with an accuracy of 95%. © 2022 IEEE.

关键词： Deep learning

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Exploring the Dark Web and Dark Nets: Contemporary Trends, Security Threats, and Future Research Directions

Exploring the Dark Web and Dark Nets: Contemporary Trends, S...

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Trends in material science and Inventive materials (ICTmIm), International Conference on

作者： L Sherin Beevi Joe Prathap P. m. W Vinil Dani Adoni Nagendra Babu Yadav Bhumireddy Hitesh Annadanam Sudarshan Sharma Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai India Department of EEE St. Peter’s College of Engg.and Tech. Chennai India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

This research offers a thorough examination of the Dark Web's and Dark Nets' changing environment, highlighting the increasing influence these platforms have on online privacy, security, and criminal behaviour. This study investigates the revolutionary effect these hidden networks have on both lawful and illicit operations, with a focus on new trends like cryptocurrency-driven trade and sophisticated anonymization techniques. A thorough analysis of the Tor network and its changing function in preserving user anonymity in the face of sophisticated cyber threats and increased worldwide monitoring is part of the investigation. In addition, the study digs into the emerging security challenges—ransomware, AI-driven cyberattacks, and privacy risks—posed by these networks, providing insights into countermeasures such as blockchain-based security solutions and machine learning-based threat identification. The future course of the Dark Web and Dark Nets is also studied, taking into account ethical issues, legal obstacles, and possible developments like quantum-resistant encryption and decentralised anonymization methods. This study intends to contribute to a more nuanced understanding of these hidden online ecosystems, highlighting their current cybersecurity implications and anticipating future issues in an increasingly linked digital world.

关键词： Privacy Data privacy Ethics Dark Web Law market research Information filtering Encryption computer crime Information integrity

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Automated Semantic Interpretations in Web Applications via Cloud Computing Aspects

Automated Semantic Interpretations in Web Applications via C...

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Communication, computer sciences and engineering (IC3SE), International Conference on

作者： Preethi D Poornima mehta Devendra Sood Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of IT and M. Tech Integrated Noida Institute of Engineering and Technology Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Tula's Institute Dehradun India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

The creation and execution of applications in several disciplines have been greatly aided by the integration of cloud computing and semantic web technologies. Although they are independent entities, they may also be combined in many ways to provide answers—a subject that has been thoroughly researched lately. The number of “new cloud providers, applications, facilities, management systems, and data” has significantly increased in recent years. The complexity that has resulted from this expansion emphasises the need for new technology in order to efficiently manage and support these varied and many services and resources. As a result, difficulties with “cloud services and resources” transferability, compatibility, security, choice, negotiation, identity, and specification might arise. Semantic technologies are a vital tool for reassessing these issues because of their enormous “cloud computing” capacity. This study uses a variety of sources to examine and evaluate the impact of “Semantic-Web technology” in the cloud. moreover, a cloud-based engagement strategy shows how we may leverage the features and advantages of cloud computing to build the semantic web and provide automatic semantic annotations to online applications on a large scale.

关键词： Semantic Web Cloud computing Annotations Complexity theory Security Facilities management Semantic technology

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Comprehensive Approaches to Agricultural Intelligence: U-Net, YOLO, and Random Forest in Practice

Comprehensive Approaches to Agricultural Intelligence: U-Net...

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Communication, Control and Intelligent Systems (CCIS)

作者： Saharsh Gavas Pranali Kosamkar M. Tech Computer Science and Engineering (Data Science And Analytics) Dr. Vishwanath Karad MIT World Peace University Pune India Dept Computer Engineering and Technology Dr. Vishwanath Karad MIT World Peace University Pune India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

This paper seeks to implement and test advanced precision agricultural monitoring and detection systems derived from machine learning, remote sensing, and sensor technologies to improve pest detection, crop yields assessment, and animal husbandry management practices. The approach involves an automated and hierarchical framework integrating cutting edge machine learning technologies with fine spatial resolution remote sensing images and sensors. For instance, the authors apply CNN (convolutional neural networks) for pest identification; the deep learning models trained on Sentinel-2 images serve as yield predictors; UWB location coordinates and accelerometric measures combined form livestock behavior monitoring. This methodology encompasses the stages of implementation, testing and finally verification of the model. A variety of machine learning systems such as Faster-PestNet or deep semantic segmentation algorithms process data while remote sensing and the sensors’ data were used in predictions and classifications. This allows using different performance measures such as accuracy, precision recall rates and RmSE (root mean square error) to test the systems.

关键词： Precision agriculture YOLO Accuracy Estimation Production Livestock Convolutional neural networks monitoring Remote sensing Crop yield

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A Novel Framework for Efficient Handover mechanism in D2D Communication Using Networking Principles 4

A Novel Framework for Efficient Handover Mechanism in D2D Co...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Jayanthi, S. Raja, mandapati Jackson, Beulah Jayasree, S. Nithya, A. Jeneetha Jebanazer, J. R. M. D Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India CMR Engineering College Department of Electronics and Communication Engineering Telangana India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Chemistry Tamil Nadu India R. M. K College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Panimalar Engineering College Department of ECE Tamilnadu Chennai India

ISBN: (纸本)9798350300888

Software Defined Networking (SDN) technology utilizes software to manage and alter the current networks to improve the networking and interfacing capabilities. It does this by providing a split between the control plane and the data plane. On the SDN controller, each function is run as an application. This paper suggests a structure made up of a unified RAN and an SDN-based core network. For mobile terminals to access the services of the network operator, as well as the Internet and other cloud-based apps, all radio access points in the RAN are connected with the aid of OpenFlow interfaces. Decentralized Content Delivery Networks (CDN) manage mobility without requiring data to pass via the core network, which minimizes signaling. To gauge the signaling burden, traffic steering between the framework's different entities is examined. The suggested work establishes criteria based on a combination of fundamental factors, such as Signal Strength, Distance, and Speed, to assure service continuity of mobile nodes in heterogeneous networks. The parametric analysis of the handover is contrasted with that of the current designs. The suggested framework also provides ProSe capability for a select number of desirable mobile devices in the network and is configured for D2D connection. © 2023 IEEE.

关键词： Heterogeneous networks

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Digital twin and IOT technology for secure manufacturing systems

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measurement: Sensors 2023年 25卷

作者： Gopal, Lisa Singh, Harbaksh mounica, Panguluri mohankumar, N. Challa, Nagendra Panini Jayaraman, P. Computer Science and Engineering Graphic Era Hill University Dehradun M.Tech Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India BITS Pilani India Department of CSE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vijayawada India Department of Electronics and Communication Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India Department of Mechanical Engineering Prathyusha Engineering College Aranvoyalkuppam Tiruvallur Tamil Nadu Chennai602025 India

The Digital Twin (DT) method offers new concepts for choosing the context of information technologies and smart production systems. This research focuses on low-price, extremely effective defect diagnosis methods, low-efficiency, high-cost devices to obtain timely feedback and accurate fault detection results, and secure manufacturing systems. The data structure, control plane, and output units are the three components of the manufacturing system that creates a data link between the virtual model using micro-Electro-mechanical (mEm) devices and the Zigbee wireless transmission system in the database layer. This study acquired DT information from the control plane using the Internet of Things (IoT) through sensors for secure manufacturing information. It separates and calls the pertinent data by the attribute processor and transfers it to the outcome units. To produce the classification and outcomes of work build features information, the evaluation method analysis the output nodes that split the test set and learning group using a dynamic database. The hybrid IoT with DT technology to examine the consequences of defects detected efficiently predicted and secures the manufacturing system. © 2023 The Authors

关键词： Internet of things

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Automated Email Notifications and Security monitoring for Cloud Storage Access using Cloud Function

Automated Email Notifications and Security Monitoring for Cl...

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International Conference on Innovative mechanisms for Industry Applications (ICImIA)

作者： N Renuka m Panneer Selvam P Ponmurugan S Kiruthika N Selvam N Kannan Department of Information Technology KSR Institute for Engineering and Technology Tiruchengode India Department of Electrical and Electronics Engineering Sona College of Technology Salem India Dean - IPR Meenakshi Academy of Higher Education & Research Deemed to be Univeristy Chennai India Department of M.Tech - Computer Science and Engineering Erode Sengunthar Engineering College Thudupathi Erode India Department of Electrical and Electronics Engineering M.Kumarasamy College of Engineering Karur India

To monitor a specified Google Cloud Storage bucket for any changes or accesses made to its contents. When an access or change is detected, the cloud function will automatically send an email notification to a specified email address with information about the access or change, including the time of access, the user who accessed the data, and the specific data that was accessed. The paper represents the Google Cloud Platform services, which includes Cloud Storage and Cloud Functions. The Cloud Function will be triggered by a Cloud Storage whenever an object is accessed. The Cloud Function will then parse the notification message and extract the relevant information, such as the object name and access time, and send an email notification. The automated email notification system will help cloud storage administrators monitor access to their storage buckets, identify potential security breaches or unauthorized access, and take appropriate action in a timely manner. It also provides a record of all access activity, which can be useful for audit purposes and compliance requirements.

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Static Eccentricity Fault Analysis in Three-Phase Induction motors Using Current Signal

Static Eccentricity Fault Analysis in Three-Phase Induction ...

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metrology for Extended Reality, Artificial Intelligence and Neural engineering (metroXRAINE), IEEE International Conference on

作者： Shady S. Refaat Ahmed Al-Shemmery Kais Abdulmawjood Sayed mohammad Kameli Abdelaziz Abuelrub Electrical and Computer Engineering Department Texas A&M University at Qatar Doha Qatar School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Department of Electrical Computer and Software Engineering Ontario Tech University

Preventing mechanical faults in motors is often impossible, early detection of air gap eccentricity faults in induction motors is critical in preventing damage to the machine. Therefore, designing a reliable, effective fault detection system can help to improve its operation. This paper presents an analysis of static eccentricity fault for induction motors. This paper proposes the use of the empirical mode decomposition (EmD) followed by the implementation of wavelet packet decomposition (WPD) on current signals to extract and identify static eccentricity fault frequency signatures. The accuracy in fault detection and diagnosis of the effects of static airgap eccentricity using stator current based monitoring with WPD based on EmD is experimentally verified.

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