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5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Nemade, Rohan Jha, Suraj Anand, Harsh Chandrasekaran, Saravanan Srm Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350379884

Galaxies in astrophysics are one of its fundamental, their morphological classification remains an essential key to unlock countless doors about the structure, formation and history of our Universe. For nearly a century, astronomers have assigned galaxies to perceptual categories such as ellipticals, spirals and irregulars. However, the extraordinary expansion of the galaxy database catalysed and instigated by sky surveys of ever-increasing scales rendered this classification more manual than practical. Because of the learning capability and its scaling nature, to learn hierarchical abstract features from the visual data Convolutional Neural Networks (CNN) are powerful tools to recognize complex patterns and structures in images, such as spiral arms or central bulges that contribute significantly to accurate morphological classification. That is why CNN are particularly well suited to the problem of galaxy classification. While traditional classification work used to solve the problem, it is not feasible for today's huge amounts of generated data. This attempt to build and train a CNN model using galaxy images as our domain. The Enhanced CNN model can achieve the high accuracy to morphological type of galaxies. The Enhanced CNN increase both efficiency and classification accuracy, particularly when processing large dataset. The Galaxy Zoo dataset indicated that our study can provide a tool for other astronomical research in future. The Enhanced CNN gain the overall accuracy rate are 95.29% with the performance indicator were calculated including average precision, recall, F1-score and Area under curve (AUC) is 0.9513, 0.9531, 0.9525 and 0.9853 respectively. The Enhanced CNN outperforms the various existing state-of-the models. © 2024 IEEE.

关键词： Convolutional neural networks

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TRS Scheduling for Improved QoS Performance in Cloud System

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computers, Materials & Continua 2023年第4期75卷 1547-1559页

作者： G.John Samuel Babu M.Baskar Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India Department of Computing Technologies School of ComputingCollege of Engineering andTechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadline, and popularity. However, the methods are inappropriate forachieving higher scheduling performance. Regarding data security, existingmethods use various encryption schemes but introduce significant serviceinterruption. This article sketches a practical Real-time Application CentricTRS (Throughput-Resource utilization–Success) Scheduling with Data Security(RATRSDS) model by considering all these issues in task scheduling anddata security. The method identifies the required resource and their claim timeby receiving the service requests. Further, for the list of resources as services,the method computes throughput support (Thrs) according to the number ofstatements executed and the complete statements of the service. Similarly, themethod computes Resource utilization support (Ruts) according to the idletime on any duty cycle and total servicing time. Also, the method computesthe value of Success support (Sus) according to the number of completions forthe number of allocations. The method estimates the TRS score (ThroughputResource utilization Success) for different resources using all these supportmeasures. According to the value of the TRS score, the services are rankedand scheduled. On the other side, based on the requirement of service requests,the method computes Requirement Support (RS). The selection of service isperformed and allocated. Similarly, choosing the route according to the RouteSupport Measure (RSM) enforced route security. Finally, data security hasgets implemented with a service-based encryption technique. The RATRSDSscheme has claimed higher performance in data security and scheduling.

关键词： Cloud task scheduling TRS quality of service RSM route security data security SDE RATRSDS

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A Hybrid Deep Learning Solution for Real-Time DDoS Mitigation in IIoT Environments 5

A Hybrid Deep Learning Solution for Real-Time DDoS Mitigatio...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Kamaleswari, S. Suganthi, N. SRM Institute of Science and Technology Department of Computer Science and Engineering Ramapuram India

ISBN: (纸本)9798331530013

The Industrial Internet of Things (IIoT) has revolutionized industrial operations by enhancing connectivity and automation. However, this interconnectivity also introduces significant vulnerabilities, particularly to Distributed Denial of Service (DDoS) attacks, which can disrupt critical industrial processes. This proposed model designed to fortify IIoT networks against DDoS threats. The proposed approach employs a hybrid model that integrates CNN and Bi-LSTMs networks to effectively capture spatial and temporal patterns in network traffic data. The framework encompasses including data collection, preprocessing, DDoS detection, and automated strategies. The framework using real-world IIoT traffic datasets, preliminary results prove that the work expressively improves DDoS detection capabilities while maintaining low false positive rates. This work ensuring the reliability and availability of industrial operations. Future research will explore advanced deep learning architectures and the integration of this framework with cutting-edge networking technologies for dynamic threat response. © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

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An Efficient Framework for Secure Agriculture Block Supply Chain for Farmer with Crop Yield and Demand Prediction 5

An Efficient Framework for Secure Agriculture Block Supply C...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Surya, M. Manohar, S. Srm Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385649

An entire country's economy, population security, nutrition, and health all depend on its agricultural productivity. In an effort to increase agricultural output, farmers have been adopting new technologies like blockchain and the Internet of Things in recent years. Blockchain has been used to address issues in a variety of industries. Blockchain is being used in agriculture to speed up transaction times and improve food safety. The complex mechanism that keeps agricultural products moving throughout the market is called an agricultural supply chain. Agricultural commercial resources play a crucial role in meeting the demand for agricultural products and preserving their quality and safety as they transport agricultural items across the market. Many existing methods have explored the use of blockchains in the supply chain, although they are unable to enhance the process's overall efficiency. An efficient crop yield prediction and demand prediction system is proposed with secure block chain technology. The proposed system has the following three phases: 1) crop yield prediction system;2) supply chain process with blockchain;and 3) demand prediction system. The first phase consists of the following steps: dataset collection, preprocessing, feature extraction, feature selection, and training. In the second phase, farmers, distributors, retailers, and consumers are involved. Finally, for demand prediction, pre-processing, feature extraction, feature reduction, and prediction are carried out. All three phases are linked to a blockchain and securely stored in the cloud. © 2024 IEEE.

关键词： Internet of things

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Beyond chat-GPT: a BERT-AO approach to custom question answering system

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Multimedia Tools and Applications 2025年第13期84卷 12513-12530页

作者： Sophia, J. Jinu Jacob, T. Prem Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Sathyabama Institute of Science and Technology Chennai India

This work introduces a novel Custom Question Answering (CQA) model leveraging Adam optimized Bidirectional Encoder Representations from Transformers (BERT-AO). This model tackles the challenge of combining textual and visual information for accurate question answering. The core concept lies in understanding the intricate relationships between words in text and the visual features within images. The proposed CQA model with BERT-AO incorporates separate branches for processing text (BERT-AO) and images (CNN), both utilizing self-attention mechanisms. This enables a deeper understanding of context within both textual and visual data. Training is conducted on a comprehensive dataset encompassing factual, open-ended questions, answers, and images, providing a strong foundation for the model’s learning process. The performance of the proposed CQA Model with BERT-AO attains 20.46%, 36.86%, 43.98%, 19.97%, and 17.604% higher accuracy and 27.42%, 41.56%, 42.78%, 18.72% and 16.15% higher F-Score value compared with existing methods like Enhancing Bridge Inspection Visual Question Answering via Pre-Training with External Image-Text Data (VLP), LOIS: Exploring Instance Semantics for Visual Question Answering (LOIS), Bidirectional Multimodal Attention Networks for Visual Question Answering (BiGAN), A Pairwise Attention Framework with Word and Sentence Embedding for Visual Question Answering (DALNet-WSE) and Enhanced GNN Focused Attention and Hybridized Optimization Approach for Visual Inquiry Resolution (GNN-SA-MRFO) respectively. This highlights its effectiveness in combining textual and visual information for superior question answering capabilities. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Semantics

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Intelligent Automation and Monitoring of Environmental Characteristics for Hydroculture Systems using IoT 4

Intelligent Automation and Monitoring of Environmental Chara...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Seth, Saksham Mishra, Sachin Kumar Malarselvi, G. SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385793

The need for adopting Hydroculture systems (viz. hydroponics, aeroponics, aquaponics) is increasing subsequently with the increase in demand for Sustainable farming solutions for populous countries like India. Industrial Hydroculture systems do exist at this current time, but these systems are still far from the reach of smaller scale implementations in terms of cost. The Ambient temperature, temperature of water, pH of water and Electrical Conductivity are considered as the key factors for the growth of plants in such systems. Some of these factors can be controlled and governed as per the requirements of plants. This work aims to develop a proof of concept and automate the process of monitoring, logging and controlling these factors with IoT. The implementation eliminates rudimentary manual monitoring of environmental characteristics, while logging data on an Azure cloud server, with insights delivered via PowerBI. © 2024 IEEE.

关键词： Environmental monitoring

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COVID-19 Diagnosis through Chest X-Ray Images Leveraging VGG16 Architecture 1

COVID-19 Diagnosis through Chest X-Ray Images Leveraging VGG...

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1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Sharma, Shiwanki Singh, Abhilasha Srm Institute of Science & Technology Department of Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798350367720

The ongoing COVID-19 pandemic has demanded developing efficient and reliable diagnostic tools to combat the virus's dissemination. In this paper, we have put forward a novel approach based on deep learning for the automated recognition of COVID-19 from chest X-ray images, based on the VGG16 architecture. Utilizing a dataset containing X-ray images of the chest of people who are both COVID-19 positive as well as negative, we trained and evaluated the VGG16 model for its diagnostic performance. Through rigorous experimentation and validation, this proposed model has achieved an remarkable accuracy of 98.2%, demonstrating its worth in effectively differentiating between COVID-19 and non-COVID-19 patients. Furthermore, we conducted extensive comparative analyses with existing approaches, showcasing the superiority of our suggested model in terms of computing efficiency and accuracy. Achieved results highlight the prospective of methodologies based on deep learning, particularly the VGG16 model, as a valuable tool when combating the COVID-19 epidemic, offering rapid and reliable diagnosis to aid in effective patient management and community wellbeing interventions, and the precision, recall, and F1 score of the suggested model yield positive values of 0.98, 0.98, and 0.98. © 2024 IEEE.

关键词： COVID-19

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Node Deployment Strategies and Challenges in Underwater Wireless Sensor Network 5

Node Deployment Strategies and Challenges in Underwater Wire...

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5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Layolin Benisto, L.C. Sukumaran, Rajeev Agnel Shyam kumar, C. SRM Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur India

ISBN: (纸本)9798350395235

Underwater Wireless Sensor Networks (UWSNs) are gaining importance for a wide range of applications, from environmental monitoring to underwater exploration. However, the challenging underwater environment poses significant obstacles to reliable data transmission. This study focuses on the role of deployment nodes in UWSNs, addressing the need for extended communication range, signal amplification, and data reliability. The study presents an in-depth exploration of node deployment, communication protocols, and the unique challenges faced in underwater environments. By strategically placing and managing nodes, UWSNs can overcome these challenges and improve overall network performance. UWSNs integrate a number of critical deployment strategies designed for land-based sensor networks. However, because to the unique 3-D properties of UWSNs, not all of these methodologies are immediately relevant. Underwater networks function in three dimensions, posing additional issues such as sensor node mobility driven by water currents and significant communication delays. The goal of this research is to look at various node deployment methodologies in order to shed light on the difficulty of sensor node deployment. The study intends to investigate various node deployment strategies in order to shed light on the complexities of sensor node deployment in UWSNs. Furthermore, the research performs an exhaustive literature analysis on node deployment, diving into difficulties and obstacles faced during deployment, and extensively analyzing the performance of various node deployment approaches. This research provides useful insights for optimizing node deployment in UWSNs, opening the path for increased communication efficiency in the difficult underwater realm. © 2024 IEEE.

关键词： Sensor nodes

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Effect of MHD on Porous Circular Stepped Plate Lubricated With Micropolar Fluid

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IAENG International Journal of Applied Mathematics 2024年第9期54卷 1847-1854页

作者： Johny, A. Sujatha, E. Sree, M. Geetha Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India

An analysis is made on the effect of magneto hydrodynamics on poro-circular stepped plates lubricated with micropolar fluid. The modified Reynold’s equation leads to the development of a closed form expression for pressure, load sustaining capacity, and squeezing time. The impact of porosity is analyzed using the modified Darcy’s equation, and the outcomes are compared with the cases of the presence and absence of porosity on the same circular stepped plate. The external magnetic field influences the bearing’s efficiency by increasing the pressure, load sustaining capacity, and squeezing time performance. In the presence of porosity, the pressure, load sustaining capacity and squeezing time decrease compared to the absence of porosity, and the comparisons are shown in the tables. The variation of the highly influenced parameter of the bearing system is represented graphically. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Porosity

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Magnesium-incorporated biocomposite scaffolds:A novel frontier in bone tissue engineering

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Journal of Magnesium and Alloys 2024年第6期12卷 2231-2248页

作者： Abinaya Shanmugavadivu Sundaravadhanan Lekhavadhani Sushma Babu Nivetha Suresh Nagarajan Selvamurugan Department of Biotechnology School of BioengineeringCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia

Nonunion represents a crucial challenge in orthopedic medicine,demanding innovative solutions beyond the scope of traditional bone grafting *** the various strategies available,magnesium(Mg)implants have been recognized for their biocompatibility and ***,their susceptibility to rapid corrosion and degradation has garnered notable research interest in bone tissue engineering(BTE),particularly in the development of Mg-incorporated biocomposite *** scaffolds gradually release Mg2+,which enhances immunomodulation,osteogenesis,and angiogenesis,thus facilitating effective bone *** review presents myriad fabrication techniques used to create Mg-incorporated biocomposite scaffolds,including electrospinning,three-dimensional printing,and sol-gel *** these advancements,the application of Mg-incorporated biocomposite scaffolds faces challenges such as controlling the degradation rate of Mg and ensuring mechanical *** limitations highlight the necessity for ongoing research aimed at refining fabrication techniques to better regulate the physicochemical and osteogenic properties of *** review provides insights into the potential of Mg-incorporated biocomposite scaffolds for BTE and the challenges that need to be addressed for their successful translation into clinical applications.

关键词： Magnesium Bone tissue engineering Immunomodulation Osteogenesis Angiogenesis

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