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LeafViT: Vision Transformers-Based Leaf Disease Detection 1

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3rd international conference on Innovations in computational Intelligence and Computer Vision, ICICV 2022

作者： Keerthan Bhat, H. Mukund, Aashish Nagaraj, S. Prakash, R. RV College of Engineering Bengaluru India Noesys Software Pvt. Ltd. Bengaluru India

ISBN: (数字)9789819926022

ISBN: (纸本)9789819926015

Diseases in plant leaves deplete crop quality and reduce yield. Monitoring the crops periodically is important to mitigate these risks and preserve food integrity. Traditional methods of detecting diseases in plants involve visual inspection by humans which is error-prone and cumbersome. Advances in deep learning architectures rely on convolutional neural networks (CNNs) and have achieved promising results in agricultural domain. However, detecting diseases in leaves requires the model to capture finely grained attributes in the leaf. Toward this, this paper proposes a vision transformer (ViT)-based approach which leverages self-attention mechanism to identify subtle yet discriminative regions and learn by amplifying them. The methodology also involves data augmentation and sampling strategies to combat the class imbalance problem in datasets. The proposed framework is tested on Plant Pathology 2020 dataset, and experimental results show an accuracy of 97.15% achieved which is significantly better than the performance of state-of-the-art CNN-based models on plant disease detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Crops

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Analyse the Critical Success Factor of Green Manufacturing for Achieving Sustainability in Automotive Sector 3rd

Analyse the Critical Success Factor of Green Manufacturing f...

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3rd international conference on computational and experimental methods in mechanical engineering, ICCEMME 2021

作者： Singh, Punj Lata Sindhwani, Rahul Sharma, Bhupendra Prakash Srivastava, Priyank Rajpoot, Praveen Lalit Rahul Kumar, Rajender Department of Civil Engineering Amity University Uttar Pradesh Noida India Department of Mechanical Engineering Amity University Uttar Pradesh Noida India Department of Mechanical Engineering FET MRIIRS Faridabad India

ISBN: (纸本)9789811633294

Problems with the environment are constantly increasing. The general public is also worried about this subject. The government of India has been making continuous efforts to implement green manufacturing in industries in many ways. So that the environment can be saved from getting worse. With regards to the environment, the awareness among consumers is also increasing and they buy the same products which do not harm the environment. Sustainability can be achieved by the implementation of Green Manufacturing (GM) in various business sectors like the automotive industry, green supply chain management, marketing, and information management. The aim of this research paper is to identify and analyze the Critical Success Factor (CSFs) of green manufacturing sustainability in the automotive industry. In this research paper, the CSFs of GM are derived from extensive literature reviews. The reliability of these factors is derived from the calculation of Cronbach’s alpha. Pair-wise comparison of these factors is done by Fuzzy-AHP (Analytic Hierarchy Process) method after prioritization of CSFs. This key area recommends various measures for improvement and implementation of GM in the automotive industry. With the help of this study result, identification of CSFs, weightage of identified CSFs of GM in the automotive industry has been realized. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry Critical success factors (CSFs) Fuzzy-analytical hierarchy process (AHP) Green manufacturing (GM) Reliability and analysis Sustainability

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experimental study of a novel technique of data hiding with high PSNR

Experimental study of a novel technique of data hiding with ...

引用

Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), international conference on

作者： Sakit Verdiyev Ababil Naghiyeva Ajay Kumar Dept. Computer Engineering and Telecommunication Azerbaijan Technological University Ganja Azerbaijan Dept. Enginering and Technology Adi Shankara Institute Kalady India

The task of concealment of information is an important challenge in the context of an advance infrastructure of open and uncontrolled Internet users' communication through computer networks. Various steganographic methods have been developed to solve the problem of the protection of transmitted information. The aim of the present paper is the experimental study of the robustness of the algorithm developed by authors for the concealment of information. The reliability of the algorithm for stego analytics attacks has been investigated by the RS method of steganalysis. In addition, the computational complexity of the algorithm is investigated which in turn should not exceed a certain *** results of the experimental studies demonstrate the algorithm’s high robustness and minimal computational time.

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experimental Studies on Corrosion Performance of Reheated AZ31 Magnesium Alloy 3rd

Experimental Studies on Corrosion Performance of Reheated AZ...

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3rd international conference on Recent Advances in mechanical engineering Research and Development, ICRAMErd 2022

作者： Mohapatra, Pabak Kund, N.K. Sahu, S.K. Department of Production Engineering VSS University of Technology Burla768018 India

ISBN: (纸本)9789811994920

Mg alloy possesses established immense importance as a promising biomaterial for the substitution of damaged bones and other solid tissues within the body, because of biocompatibility alongside physical characteristics that are matching to the human bone. The present investigation is rooted in corrosion rate estimation for the AZ31 Mg alloy. To evaluate the corrosion rate, two different methods like weight loss analysis and electrochemical test were employed. The corrosion rate of Mg alloy is significantly high at the beginning, and it gradually becomes stable over a period of time as obtained from the open circuit potential curve of the electrochemical corrosion test. The electrochemical corrosion analysis results showed further negative OCP development for AZ31 alloy. It shows their lively performance, perhaps oxidation of Mg2+ ion by varying stability potential further negative. SEM micrograph of corroded surface conforms presence of oxides as a result of corrosion reaction in the solution. To further this research work, surface coating will be done in an attempt to reduce the corrosion to the desired level, which has been a critical issue associated with magnesium alloy. EDS analysis of the alloy specimen confirms that throughout the processing, about 84.75% (wt.) of Mg stays present in reheated AZ31 alloy. Moreover, throughout the processing, the average grain size of reheated AZ31 Mg alloy stays nearly 75 µm as against 50 µm for casted AZ31 alloy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Corrosion rate

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Deep Learning-based Automatic 3D Printer Anomaly Detection during the Printing Process 3

Deep Learning-based Automatic 3D Printer Anomaly Detection d...

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3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Lalitha, T. Anushkannan, N.K Shreepad, Sarange Sasireka, S. Anandaram, Harishchander Razia, Shaik Vellore Institute of Technology Department of Computer Science and Engineering Tamil Nadu Vellore632014 India Kathir College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore641062 India Ajeenkya Dy Patil School of Engineering Department of Mechanical Maharashtra Pune412105 India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India Amrita VishwaVidyapeetham Centre for Excellence in Computational Engineering and Networking Tamil Nadu Coimbatore641112 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522302 India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

3D printing is a technology which is expected to be one of the most used technologies in the upcoming time. This technology allows to print out products that are designed using 3D modeling software. Though this is an effective technology, it also has its disadvantages. The disadvantages include anomalies. Anomaly is a defect that is often found when the printer finishes the printing process. Thus, it cannot be rectified when found during the process. To resolve this issue, this study aims in developing a deep learning model using the UNet algorithm. A dataset of pictures of various possible anomalies is gathered from Kaggle. The Kaggle data is then preprocessed using three different methods. The images are initially applied using the target format. The images are then multiplied and shrunk to keep the balance. The UNet method is employed to create a deep learning model. The preprocessed dataset is then used to train the model. To guarantee improved performance, the trained model is subsequently put to the test to assess the model's final accuracy and loss. In all three instances, the model's output is determined to be satisfactory. The model produced an accuracy of 98% during the testing and produced a loss value of 0.54%. This loss value is so small that it can be neglected. The model developed is found to be one of the best algorithms that can be used in anomaly detection. © 2022 IEEE.

关键词： Anomaly detection

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A Filter-Based Learning Approach for Intrusion Detection using The NSL-KDD Network Dataset 3

A Filter-Based Learning Approach for Intrusion Detection usi...

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3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Madala, Chandu Jagan Sekhar Patil, Anita M Santhosh Srinivasan, P. Kousar, Heena Sultanuddin, Sj Sangeeth Kumar, M. Lendi Institute of Engineering & Technology Department of Computer Science & Engineering Andhra Pradesh Vizianagaram535005 India Bharati Vidyapeeth Yashawantrao Mohite Institute of Management Karad Department of Mca Maharashtra Malkapur415539 India Panimalar Engineering College Department of Mathematics Tamil Nadu Chennai600123 India East Point College of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore560049 India Measi Institute of Information Technology Department of Mca Tamil Nadu Chennai600014 India Sona College of Technology Department of Mechanical Engineering Tamil Nadu Salem636005 India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

Wireless sensor network (WSN) attacks seek to disrupt or eliminate the network's ability to execute its expected duties. Penetration testing is a wireless sensor network defence that detects unknown threats. Because of the significant advancement in computer based products and widespread Internet utilization, it is critical to guarantee hosting and information systems. A hacking technique has been proposed to breach computer security with infiltration. An intrusion detection system (IDS) identifies network breaches with machine learning (ML) methods. Classic ML methods based feature extraction frequently resulted in low efficiency and misreading incursions. To address these challenges, this research provides a novel architecture for IDS that may be facilitated by the filter-based learning methodL The anticipated model performance is comparable to ML techniques. The appropriate solution was built and evaluated using network security laboratories - discovering dataset information (NSL-ICDD). The experimental data reveal that the suggested model filter-based learning detects assaults with more accuracy (i.e., 99 percent) than LDA, CART, and other current approaches. © 2022 IEEE.

关键词： Wireless sensor networks

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Analyzing the effect of Process Parameters on Amaranth Popping and Puffing in the Lahi Machine using the Taguchi Method 3

Analyzing the effect of Process Parameters on Amaranth Poppi...

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3rd international conference on Intelligent Robotics, Mechatronics and Automation Systems, IRMAS 2023

作者： Khot, Aniket B. Patil, Sagar Dnyandev Patil, Vikas S. Department of Mechatronics Engineering Sharad Institute of Technology College of Engineering Kolhapur India Department of Mechanical Engineering Sharad Institute of Technology Polytechnic Kolhapur India Department of Mechanical Engineering Sharad Institute of Technology College of Engineering Kolhapur India Ichalkaranji Kolhapur India

Purpose - Amaranth grains are popped by various methods of heating like Oven puffing, Gun puffing, Extrusion puffing, Oil puffing, Pan Popping, etc. Popping of amaranth grains in an oven, gun, extrusion, oil, pan, etc. are having the limitation due to its size, puffing quality, low volume expansion ratio, etc. In this research work the Special Purpose Machine (SPM) with a heating plate was used to pop/puff the amaranth grains. This machine was designed to overcome all the above limitations mentioned earlier. The quality of amaranth grains are depending on temperature, angle, hole size of the nozzle, the material of the heating plate, etc. The impact of these process parameters is analyzed on the Popping Yield (PY), Ratio of Volume Expansion (VER), and Sensory Score (SS) of amaranth grains. The Popping Yield (PY), Ratio of Volume Expansion (VER), and Sensory Score (SS) are major quality parameters of amaranth grains. Therefore these parameters are finalized to carry out further research. The intent of this study is to analyze the more significant process parameters which are impacting PY, VER, and SC. Methodology - The Taguchi approach was adopted for analyzing the impact of process parameters on the quality of Amaranth grains. The Minitab 17 software was used to detect the significant factors. Findings - To identify the significant process parameters the design of the experiment (DOE) has been done. L16 Orthogonal Array (OA) has been obtained to carry out the experimental investigation. It was observed that temperature and material of the heating plate are the more significant parameters on PY, VER, and SS. Through investigation of the S/N ratio and ANOVA, it was detected that the temperature and Material are significant parameters and contributed 29.93%, 44.34%, 49.06%, and 44.58%, 28.73%, 29.33% respectively on Popping Yield, Ratio of Volume Expansion and Sensory Score. © Published under licence by IOP Publishing Ltd.

关键词： Taguchi methods

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Recyclability of Tractor’s Engine Component: A Case Analysis of Failure 3rd

Recyclability of Tractor’s Engine Component: A Case Analysi...

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3rd international conference on computational and experimental methods in mechanical engineering, ICCEMME 2021

作者： Sharma, Bhupendra Prakash Sindhwani, Rahul Srivastava, Priyank Malhotra, Pranav Singh, Harkirat Gupta, Shorya Singh, Priyanka Department of Mechanical Engineering Amity University Noida Uttar Pradesh India

ISBN: (纸本)9789811628566

Structuring items for recyclability is driven by ecological and monetary objectives. A few Design for Assembly (DFA) rules and boundaries can be used to check the recyclability plans. These lists can be utilized for near examination of the recyclability of various items. This helps the designers in settling on structure decisions identified with the item's finish of life. In the present research work, the boundaries will be explored from the existing DFA time gauge tables. The aftereffects of the examination showed the recyclability of the item, as characterized by set up recyclability metrics. A contextual analysis is performed to decide whether DFA boundaries could be used to decide product/part recyclability. A TODIM approach is applied to evaluate the recyclability of a tractor’s engine component based on the data obtained from "X" company. Furthermore, TODIM results were examined using MATLAB software. This exploration investigates how designers can utilize the (DFA) boundaries to foresee the recyclability list of an item. The recyclability list will be created utilizing the standards of plan for dismantling and material recyclability. The examination prompted the advancement of a method that an expert could use to decide item recyclability during the reasonable plan period of the fabrication process. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： MATLAB

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Federated Dynamic Client Selection Based on Comprehensive Performance Evaluation

Federated Dynamic Client Selection Based on Comprehensive Pe...

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Cloud Computing, Big Data Applications and Software engineering (CBASE), international conference on

作者： Jianqing Tang Guangdong Open University (Guangdong Polytechnic Institute) Guangdong China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

Federated Learning, as a distributed machine learning approach, enables the full exploitation of data value while protecting data privacy. However, traditional Federated Learning methods are significantly impacted in terms of model accuracy and convergence speed when dealing with Non-Independent and Identically Distributed (Non-IID) data. This paper introduces a Federated Dynamic Client Selection method based on Comprehensive Performance Evaluation (FedDCP), which dynamically adjusts the probability of client participation in training by integrating the clients' computational capabilities, historical performance, and current performance. This approach optimizes model accuracy, convergence speed, and runtime. experimental results indicate that the FedDCP method outperforms existing Federated Averaging optimization methods in terms of model accuracy and convergence speed on the MNIST, Fashion-MNIST, and Cifar-10 datasets, with a similar runtime, demonstrating its effectiveness.

关键词： Training Performance evaluation Accuracy Runtime Federated learning computational modeling Distributed databases Optimization methods Data models Convergence

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Structural Assessment Based on computational Models and Digital Twin Technologies 28

Structural Assessment Based on Computational Models and Digi...

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28th international Scientific conference on Transport Means 2024

作者： Duarte, J. Ribeiro, J. de Castro, P.M.S.T. Tavares, S.M.O. TEMA - Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Aveiro3810-193 Portugal Faculdade de Engenharia Universidade do Porto Rua Dr. Roberto Frias Porto4200-465 Portugal LASI - Intelligent Systems Associate Laboratory Guimarães Portugal

Modern structural design and assessment of aerospace and automotive structures relies on numerical modelling for the analysis of complex components under diverse loading conditions and material properties, reducing the reliance on costly experimental testing. However, these models often struggle to fully replicate the intricate real-world behavior of structures. Discrepancies arise due to factors like variable loading, environmental effects, material properties scatter, manufacturing imperfections, and other effects that can only fully observable in operation. This paper explores the potential of digital twins to bridge this gap, enhancing the accuracy and reliability of structural assessments. As virtual replicas integrating numerical models with sensor data, operational history, and machine learning, digital twins offer a dynamic and comprehensive understanding of structural behavior throughout a structure's lifecycle. Approaches to enable model updating, real-time structural health monitoring, and the development of new methods for model calibration and validation that combine simulations with experimental data are proposed in this paper. This path can revolutionize design, evaluation, and maintenance processes, optimizing structures for performance and lightweight while upholding rigorous safety factors. © 2024 Kaunas University of Technology. All rights reserved.

关键词： aircraft structures artificial intelligence damage tolerance digital twins machine learning

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