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15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sreenivasan, Mahalakshmi Selvaraj, P. Department of Computing Technologies Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India

ISBN: (纸本)9798331300579

Farmers and producers may suffer significant financial losses due to plant diseases. Effective control of plant diseases requires early identification and categorization of the illnesses. However, traditional plant disease detection techniques are frequently labor- and time-intensive. Plant disease detection has found a possible collaborator in deep learning and machine learning. Consequently, a novel deep-learning technique is proposed for classifying and diagnosing plant illnesses. It uses a transfer learning methodology built on a convolutional neural network architecture consisting of 5 convolutional, 2 fully- connected, and 3 max pooling layers. The algorithm has a 98% accuracy rate when tested on a publicly accessible dataset of images of plant diseases. The CNN model was trained with the PlantVillage dataset, which is available on Kaggle. From the results and a comparison with previous works, it is evident that the chosen approach performed well in classifying plant diseases with expected accuracy. © Grenze Scientific Society, 2024.

关键词： Plant diseases

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Leveraging HPC with GAN-CNN Integration for Enhanced Tuberculosis Detection using Synthetic Image Generation 3

Leveraging HPC with GAN-CNN Integration for Enhanced Tubercu...

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3rd International Conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Manasa, Pokala Veeramalla, Vaishnavi Vanusha, D. Vathana, D. Robinsha, Delsi S. Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chengalpattu603203 India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chengalpattu603203 India

ISBN: (纸本)9798331532420

Tuberculosis (TB) remains a significant global health challenge, especially in remote areas with limited medical resources. Early and accurate diagnosis is crucial to control its spread. This project harnesses high-performance computing (HPC) to address two key issues: managing unreliable medical data and improving TB diagnosis. Given the imbalance between healthy and TB-affected samples, Generative Adversarial Networks (GANs) are used to generate synthetic images, enriching the dataset and making it more diverse. This helps train Convolutional Neural Networks (CNNs), which are highly effective in medical image analysis. By leveraging HPC, we accelerate the training of CNNs on large, augmented datasets, significantly reducing processing time while maintaining accuracy. This system improves TB detection by combining GAN-enhanced data and CNN models, enabling faster and more reliable diagnosis. © 2024 IEEE.

关键词： X ray apparatus

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Enhanced Privacy in Data Aggregation with Secret Sharing Techniques 1

Enhanced Privacy in Data Aggregation with Secret Sharing Tec...

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1st IEEE International Conference on computing and Data science, ICCDS 2024

作者： Yugandhar, A.C.K. Hemanth, Mandyam Gnanavel, S. SRM Institute of Science and Technology Faculty of Engineering and Technology Dept of Computing Technologies Kattankulathur603203 India

ISBN: (纸本)9798350365337

The effectiveness of wireless sensor networks is greatly impacted by wireless spoofing attacks, which are simple to initiate. The difficult issues in Wireless Sensor Networks are locating many adversaries and eliminating them, identifying spoofing attackers, and estimating the number of attackers. The spoofing attackers are located and detected using the clustering approach. This method is unable to correctly identify the attackers. Intrusion Detection System (IDS) is suggested as a solution to this issue in order to identify spoofing attackers. In order to detect the misbehaving nodes in a wireless sensor network, VANET IDS monitors node behavior in their car, such as packet transfer. The simulation results clearly show that the proposed strategy effectively and consistently detects accidents in wireless sensor networks. © 2024 IEEE.

关键词： Cryptography

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engineering graduate attribute attainment measurement models

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Australasian Journal of engineering Education 2022年第2期27卷 77-87页

作者： Ngu, LockHei Sia, Charlie ChinVoon Lee, MingHa Lakshmanan, Rajeswari Lai, JiaChi Ling, TingSoon Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus Sarawak Malaysia

Various outcome-based education (OBE) performance measurement approaches demonstrate students’ attainment of a set of Graduate Attributes (GA) in the engineering programme. This paper presents four measurement models, namely the indicative, explicit, GA assessment, and culminating models, to measure GA attainment. The indicative model uses the total assessment mark as an indicator for GA attainment, whereas the explicit model utilises a specific mark from an assessment. The GA assessment and culminating models utilise the explicit approach from assessments that fulfil the GA requirement. The culminating model only consists of assessments from advanced and capstone courses. This research aims to determine whether the indicative model that uses an indicator approach can significantly represent GA attainment. This research also explores assessment selection differences in GA attainment. Statistical analysis was used to determine if the models were significantly different through the paired two-sample means t-test. The indicative model could not represent the GA attainment as it differed substantially from the explicit model. Both GA assessment and culminating models can be used to represent the attainment of students’ GA. GA assessment model provides monitoring of students’ progress in GA attainment, while the culminating models enable measurement at capstones and in advanced years. © 2023, Engineers Australia.

关键词： Students

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Peer To Peer Fund Raising using Blockchain 15

Peer To Peer Fund Raising using Blockchain

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15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Reddy, Boyapati Jane Prakeerth Vasu, Aaruni Mohankumar, Pradeep K. Department of Computing Technologies Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India

ISBN: (纸本)9798331300579

Crowdfunding has emerged as a transformative financial model in the contemporary business landscape, providing a decentralized avenue for entrepreneurs, creatives, and innovators to secure funding for a wide range of projects. This Project explores the multifaceted nature of crowdfunding, encompassing its origins, evolution, and the diverse platforms that facilitate this alternative form of financing. The study delves into the key mechanisms and principles that underpin successful crowdfunding campaigns, emphasizing the role of social media, community engagement, and trust-building in fostering financial support. Furthermore, the project investigates the impact of crowdfunding on traditional funding channels, examining how it has disrupted conventional investment models and empowered individuals and small businesses. The project also addresses the challenges and risks associated with crowdfunding, including issues of accountability, regulatory concerns, and the potential for project failure. © Grenze Scientific Society, 2024.

关键词： Decentralized finance

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Data Encryption in 6G Networks: A Zero- Knowledge Proof Model 8

Data Encryption in 6G Networks: A Zero- Knowledge Proof Mode...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Khamesra, Aryan Selvaraj, P. Singh, Isha Srm Institute of Science and Technology Faculty of Engineering and Technology School of Computing Department of Computing Technologies Chennai Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350376425

This work presents an innovative algorithm demonstrating the effectiveness of zero-knowledge proofs (ZKPs) in network security. By integrating Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA) for key generation, the algorithm showcases their applicability in enhancing security measures within 6G networks. It highlights the utility of ZKPs in bolstering data privacy and security by enabling entities to validate knowledge without compromising sensitive information. The algorithm shows its capability to ensure robust communication security through comprehensive simulations, thereby laying the groundwork for dependable next-generation communication infrastructures. © 2024 IEEE.

关键词： Ciphertext

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Cloud Detection and Nowcasting for Ship Navigation 15

Cloud Detection and Nowcasting for Ship Navigation

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15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sreenivasan, Mahalakshmi Sai Kumar, Kanuri S.V.S. Selvaraj, P. Department of Computing Technologies Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India

ISBN: (纸本)9798331300579

Navigating through oceans is challenging. Sailors are disadvantaged in determining the most appropriate and safe path, free from hurdles and extreme weather conditions, especially on pitch-dark nights. Ships rely on their communication with satellites for navigation. When this connection breaks, the ship loses its ability to navigate and follow the required path. In such scenarios, the Geographical Information System (GIS) and Satellite Imagery-based algorithms are best suited to assist. It is necessary to focus on cloud behavior to ensure the success of ocean endeavors. Cloud Detection is performed by the methods of K-Means clustering and MRCNN. The approach of Mean Path Adjustment (MPA) is used to trace the center of mass to predict Cloud Motion;thereby, building a convolutional LSTM model for Cloud Nowcasting. Collectively, these methods help in detecting clouds, predicting their motion, and helping sailors decide the route to follow, based on the weather conditions. This system works well when the communication between the ship and satellite breaks. A high similarity index of 0.8363 is achieved with the test images. © Grenze Scientific Society, 2024.

关键词： Satellite imagery

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Comparative study on thermogravimetric analysis of banana fibers treated with chemicals

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Materials Today: Proceedings 2023年 78卷 458-461页

作者： Lai, Tasha Sie Ming Jayamani, Elammaran Soon, Kok Heng Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus Jalan Simpang Tiga Sarawak Kuching 93350 Malaysia

Natural fibers have shown to have exceptional properties and as excellent reinforcing agents in composite materials, both of which are solutions to environmental problems. However, due to its hydrophilic nature, it tends to swell and degrade when exposed to moisture. Therefore, it will result in poor interfacial bonding with polymer matrix, and poor mechanical and thermal properties. Surface chemical treatment of fibers improved the properties of the fibers by destroying the hydrogen bond in the fiber network. An investigation has been made to study the effects of thermogravimetric analysis (TGA) on three different chemically treated banana fibers from Island of Borneo. TGA is an effective technique for performing thermal analysis. In this technique, the mass of a certain material that needs to be analyzed is observed in relation to temperature. The banana fibers obtained were subjected to chemical treatment of 5 wt% of sodium hydroxide (NaOH), 5 wt% of potassium hydroxide (KOH), and 5 wt% of calcium carbonate (CaCO3) for 24 h. The thermogravimetric analysis shows an improved thermal stability after the fibers were being treated. Besides that, it shows higher thermal stability with sodium hydroxide treated banana fiber and the least weight loss of 48% compared to other treated banana fibers. © 2022

关键词： Thermogravimetric analysis

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CFD Simulation of Smart Adaptive HVAC Vents for Efficient Cooling in Buildings

CFD Simulation of Smart Adaptive HVAC Vents for Efficient Co...

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ASEAN Australian engineering Congress, AAEC 2022

作者： Chan, Phil S. T. Wong, Basil T. Bong, Victor N. S. Chong, Kok-Hing Boniface, Christopher J. Faculty of Engineering Computing and Science Swinburne University of Technology Kuching Sarawak Malaysia

ISBN: (纸本)9789819955466

In recent years, various novel control methods have been shown to improve the energy efficiency of HVAC systems significantly, utilizing feedback from the cooled location to control the cooling effects. Despite this, the inflexibility of standard HVAC systems limits the potential energy savings. In this work, the performance of an easily retro-fitted smart adaptive vent system which was designed to overcome this inflexibility is studied. Computational fluid dynamics (CFD) was used to evaluate and compare the smart adaptive vent system against a standard diffuser. The directed airflow possible with the smart adaptive vent improved occupant thermal comfort under the same airflow rates at a cost of increased draft rates. The average PMV for all occupants were noted to reach a comfortable value at ~58% faster timeframe. The results demonstrate that the smart adaptive vent is capable of achieving greater thermal comfort at a similar or lower airflow rate, consequently improving the energy efficiency of the HVAC system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational fluid dynamics

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A Task-Driven Visualization Framework for Diabetes Management

A Task-Driven Visualization Framework for Diabetes Managemen...

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ASEAN Australian engineering Congress, AAEC 2022

作者： Low, Lip Shen Vong, Wan Tze Loh, Brian Chung Shiong Then, Patrick Hang Hui Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Kuching Malaysia

ISBN: (纸本)9789819955466

Diabetes are chronic diseases that require patients to regularly manage their own health conditions. The goal is to have their blood glucose levels under control by making frequent changes to their diabetes therapy, diet, and lifestyle behaviour. As a result, patients are advised to use personal health devices such as glucometers and blood pressure meters to collect their own health data. These multi-source health data are presented by patients to their health care providers during clinical visits in separate visualizations and are often complicated by the variety of data sources and formats. To address this issue, TaskVisDMa conceptual task-driven visualizations framework for diabetes management—is proposed in this paper to produce advanced visualizations that can provide both informative and actionable insights for health care providers to make correct reasoning for treatment plan adjustments and to better communicate with patients. The framework is composed of a collection of data pre-processing, design choices and visualization strategies to handle multi-source and multi-dimensional patient-generated health data, and is divided into five modules: an input module that receives multiple health datasets, a data pre-processing module that processes and integrates the input datasets, an data-idiom-task linking module that uses a task base to determine the data attributes and visualization idioms that best represent the data-analysis tasks identified from the pre-processed dataset, a visualization generation module that uses a strategy base to generate a holistic visual representation of the multi-source and multi-dimensional datasets, and an output layer that presents an interactive and holistic visual representation to users. Our future work will focus on: (1) expanding the task base and strategy base to formulate if–then rules for the automated selection of design choices and visual and analytic strategies;and (2) advancing the framework as a tool for creating visu

关键词： Data visualization

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