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9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023

作者： Sahebgouda Sumana, M. B.L.D.E.AsV.P.Dr.P.G.Halakatti College of Engineering and Technology Dept. of Computer Science and Engineering Vijayapur India Msrit Dept. of Information Science and Engineering Bangalore India

ISBN: (纸本)9798350334395

The majority of the people in India is dependent on agriculture. Every crop the farmers cultivate has some sort of illness. The most successfully adopted subtropical fruit crop in India is the pomegranate. Pomegranates have the highest economic value of all the fruits. Pomegranate has very little immunity to infection during cultivation, especially in the early stages. As a result, it is particularly susceptible to the sickness. The detection of plant diseases is a beneficial use of image processing. Picture acquisition, picture pre-processing, Image segmentation, feature extraction, object recognition, and classification are all steps within the infection discovery handle. © 2023 IEEE.

关键词： Image segmentation

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An Overview of Protocols-Based Security Threats and Countermeasures in WLAN 4

An Overview of Protocols-Based Security Threats and Counterm...

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4th International Conference for Emerging Technology, INCET 2023

作者： Ojha, Nitish Kumar Baray, Elyas Indian Institute of Information Technology Dept. of Information Technology Allahabad211012 India Sharda University Knowledge Park - III Dept. of Computer Science and Engineering Greater Noida201310 India

ISBN: (纸本)9798350335750

WLAN security protocols are the most important section for wireless networks which controls all the security-related issues by securing the network with some pre-defined rules made by wireless-protected access organizations, further which makes it the main target of hacking and threats by interested parties and to be safe from such threats. There should be countermeasures for such threats where there will be a solution for any threat encountered and to mention. WIFI or wireless local area Network is a cost-effective easy deployment Network that makes users take advantage of vast data shared on the internet and by the network without the need for any cable for connections. Here in this overview paper by reviewing many researchers' techniques and works on the WLAN security topic, there are shared threats to WLAN and the ways of taking precautions against those threats as countermeasures and for which the tables are used. For comparison of techniques used by authors and some famous and highly dangerous threats are also defined further. WPA3's new security protocol is also defined with its newly found vulnerabilities and countermeasures except there is a conclusion on the downgrade attack problem with WPA3. Further, there are also countermeasures for that as well, nowadays people think the network is secured with standards defined by the IEEE organization but some know this is not the case so it makes it a more important area for research. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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RoseVision: An Android Application To Detect Rose Leaf Diseases Using Modified Convolutional Neural Network 26

RoseVision: An Android Application To Detect Rose Leaf Disea...

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26th International Conference on computer and information Technology, ICCIT 2023

作者： Nayan, Saidul Islamm Rahman, Syed Mahfuzur Mahbub, Nosin Ibna University of Global Village Dept. of Computer Science and Engineering Barishal8200 Bangladesh Islamic University Dept. of Information and Communication Technology Kushtia7003 Bangladesh

ISBN: (纸本)9798350359015

Every year 28% of the global cut rose production is hampered by various rose plant diseases. Early detection and classification could diminish the cost of cultivation lost. However, without proper knowledge and expert assistance, farmers are facing challenges to identify the diseases in time to take action. Previously, a few works have been conducted on this. So far, no study has been done to develop an efficient automatic mobile application detection system with faster, lighter, and more accurate predictions. In this study, we presented an artificially intelligent mobile application using image processing to identify rose leaf diseases. The primary goal of this work is to create a simple but exact identification with minimal computing power and time. We proposed a Modified Convolutional Neural Network (MCNN) to classify different rose leaf diseases. The proposed MCNN model outperforms the famous pre-trained models including VGG16, VGG19, DenseNet121, MobileNetV2, Resnet50, InceptionV3, and Extreme Inception (Xception) by achieving 97.94% test accuracy. Additionally, based on the trained MCNN model, we developed an android-based mobile application that will allow the farmers to quickly identify the disease using their android phones. © 2023 IEEE.

关键词： Convolutional neural networks

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Fault Analysis and Identification in Ubiquitous Networks using Cognitive Agents Approach

Fault Analysis and Identification in Ubiquitous Networks usi...

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2022 International Conference on Electronics and Renewable Systems, ICEARS 2022

作者： Ayyannavar, Vasudha V. Bhajantri, Lokesh B. Basaveshwar Engineering College Dept. Computer Science and Engineering Bagalkot India Basaveshwar Engineering College Dept. Information Science and Engineering Bagalkot India

ISBN: (纸本)9781665484251

The ubiquitous network has set of heterogeneous networks such as wireless sensor networks, cellular networks, mobile adhoc networks, Bluetooth networks, etc. Each heterogeneous network communicates with other to perform ubiquitous computation, but there is a need of a fault tolerance mechanism. This kind of mechanism is used to provide continuous services to users in the presence of faults. The faults may be node, link, and memory level faults in the ubiquitous networks. Such levels faults are lead to the failure of the networks. However, there is a need for substantial time and sufficient resources for providing reliability in fault tolerance mechanisms. In this work, it has been proposed that cognitive agent based fault analysis and identification of types of faults using support vector machine algorithm. Also, the various types of cognitive agents are defined as network cognitive agents, heterogeneous node cognitive agents, gateway cognitive agents, ubiquitous cognitive agents, and fault analysis and identification cognitive agents. Each agent is communicating with other for analyzing the types of faults. Finally, the proposed work is simulated in terms of delay, probability analysis and identification, throughput, packet delivery ratio, and agent computation overhead. © 2022 IEEE.

关键词： Heterogeneous networks

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Exploring the Integration of Generative AI in Modern Education Systems: A Comprehensive Analysis

Exploring the Integration of Generative AI in Modern Educati...

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2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Dey, Avick Kumar Chauhan, Vineet Kumar Singh, Pradeep Kumar Sarkar, Ananya Dept. of Computer Applications West Bengal Durgapur India Galgotias College of Engg. & Tech Dept. of Information Technology Greater Noida India School of Computer Science and Engineering Galgotias University Greater Noida India DSMS College of Tourism and Management Dept. of Computer Applications West Bengal India

ISBN: (纸本)9798331517953

This paper aims at filling this gap through dissecting the applicability of the Generative AI in the current learning and teaching system. The paper offers an introduction to Generative AI technologies: GPT and DALL-E, and describes the chronological history and current progress of its educational applications. Other objectives include discussing about the uses of Generative AI in adaptive learning environment, smart learning systems, automation of organizational work and in talented minds improvement. Analyzing key successful AI cases, the paper reveals the challenges implementers encountered, and provides debates about the appropriate practices of AI. Research evidence points to the prospect of Generative AI benefiting students and educators in teaching and learning, which indicates the innovative potential of the technology, yet at the same time reveals the potential risks and challenges that need to be addressed concerning the ethical and privacy implications of Generative AI in education. Others may follow general recommendations for policymakers and educators on how to integrate artificial intelligence responsibly, as well as future work for this quickly burgeoning domain. © 2024 IEEE.

关键词： Contrastive Learning

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Designing Blockchain Based Consensus Mechanism for Smart Healthcare IoT

Designing Blockchain Based Consensus Mechanism for Smart Hea...

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2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023

作者： Kumari, Trishla Kumar, Rakesh Dwivedi, Rajendra Kumar Madan Mohan Malviya University of Technology Dept. of Computer Science and Engineering Gorakhpur India Madan Mohan Malviya University of Technology Dept. of Information Technology and Computer Application Gorakhpur India

ISBN: (纸本)9781665462631

In today's world, healthcare system is improving day by day by using smart IoT based system. Blockchain based system is totally a decentralized system due to which attackers are unable to access the confidential records easily. Blockchain play an important role in controlling and management of sensitive information in healthcare system and insurance sector. Consensus mechanisms used in blockchain technology to validate whichever block is going to be added next in the blockchain network. In this paper we proposed a hybrid based system which solves trust issues arises in the blockchain. Hybrid consensus mechanism provides reputation according to the activities of blocks in a blockchain network. Four layer architecture is designed in Hybrid model. Five algorithms are used to create, validate, fork handling, reward and punishment scheme and Markle tree is constructed respectively. This model is implemented on Ethereum based platform which shows that HCM model is better than a PoXR model as it consume less memory (50 percent) and consume less CPU(below 2 percent). © 2023 IEEE.

关键词： Blockchain

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BIDS: Blockchain and Intrusion Detection System Coalition for Securing Internet of Medical Things Networks

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IEEE Journal of Biomedical and Health Informatics 2023年 PP卷 1-9页

作者： Gupta, Karan Gupta, Koyel Datta Kumar, Devender Srivastava, Gautam Sharma, Deepak Kumar Department of Information Technology Netaji Subhas University of Technology New Delhi India Department of Computer Science and Engineering Maharaja Surajmal Institute of Technology New Delhi India Dept. of Math and Computer Science Brandon University Canada Department of Information Technology Indira Gandhi Delhi Technical University for Women Delhi India

The benefits of the Internet of Medical Things (IoMT) in providing seamless healthcare to the world are at the forefront of technological advancement. However, security concerns of any IoMT systems are high since they threaten to compromise personal information of patients and can even cause health hazards. Researchers are exploring the use of various techniques to ensure a high level of security of IoMT systems. One key concern is that the computing power of any Internet of Things (IoT) device is relatively low, hence mechanisms that require low computational power are appropriate for designing Intrusion Detection Systems (IDS). In this research work, a blockchain IDS coalition is proposed for securing IoMT networks and devices. The blockchain ledger is compact and uses less processing resources. Additionally, the ledger requires less communication overhead. The cryptographic hashes in the suggested architecture ensure complete data secrecy and integrity between parties who are trusted and those who are untrustworthy. Peer-to-peer networks in both central and cluster networks are also included in this work for complete decentralization. The proposed model can counter various attacks, including Denial of Service (DoS), anonymity attacks, impersonation attacks, Man-In-The-Middle (MITM), and Cross-Site Scripting (XSS). The proposed method achieved an F1- score as high as 100% and reported an AUC value of over 99%. IEEE

关键词： Blockchain

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Anti-Aliased Convolutional with Data Augmentation for Speech Emotion Recognition

Anti-Aliased Convolutional with Data Augmentation for Speech...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Le, Linh-Chi Le, Hoai-Bao Le, Phuong Thi Wang, Jia-Ching Dept. Computer Science and Information Engineering National Central University Taiwan Dept. Computer Science and Information Engineering Fu Jen Catholic University Taiwan

ISBN: (纸本)9798331521165

In this work, we propose a comprehensive framework for speech emotion recognition that combines advanced data augmentation techniques and an innovative deep learning architecture to enhance model performance. Our data augmentation strategies, including noise addition, time stretching, pitch shifting, and time shifting, significantly diversify the training dataset, leading to improved generalization and robustness against real-world variations in speech. We introduce a novel deep learning model architecture based on Anti-Aliased Convolutional (AA-Conv1D) layers, which preserves spatial hierarchies and enhances the model's ability to capture fine-grained emotional nuances in speech signals. Experimental results demonstrate that our model outperforms state-of-the-art methods, achieving a weighted accuracy of 79.38%, which surpasses the performance of existing models, SepTr + LeRaC and EMix-NS. © 2025 IEEE.

关键词： Speech enhancement

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Recognition of American sign language using modified deep residual CNN with modified canny edge segmentation

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Multimedia Tools and Applications 2025年 1-28页

作者： Hariharan, U. Devarajan, Devikanniga Kumar, P. Santhosh Rajkumar, K. Meena, M. Akilan, T. Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Mohali140413 India Department of Computer Science and Engineering GITAM University Karnataka Bengaluru561203 India Department of Information Technology Faculty of Engineering and technology SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai600089 India Department of Data Science and Business Systems School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India Department of Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Tambaram602109 India Research Coordinator Dept. of IQAC Amity University Kolkata West Bengal 700135 India

American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algorithms still have some drawbacks, such as difficulty recognizing hand movements and low recognition accuracy for most sign language recognition. A Modified Convolutional Neural Network (MCNN) deep residual 101 classifier-based American Sign Language identification system has been developed to address this problem. There are three main parts presents in the method. The first part is pre-processing the images to remove the noise, enhance the contrast of the picture, adjust the contrast level and smoothen the picture using various filters. The second part is the segmentation, and it’s used to partition the image using a modified canny edge detection method by removing all weak edges present in the image. Finally, classification will be done using the Modified CNN deep residual 101 classifiers. By classifying the image, the American Sign Language is accurately identified. This process is conducted through images. The outcome shows that the suggested approach has a 0.97% accuracy and a 0.05% False Positive Rate. Other CNN architectures such as resNet 50 and resNet 18 reached 0.90% and 0.80% accuracy, respectively, which is lower than our proposed method. In addition, the resNet 101 classifier effectively recognizes the difficult hand gestures through the image data. It obtains high recognition accuracy for 36 signs is 0 to 9 numbers and a to z alphabets from American Sign Language. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Anti-Aliased Convolutional with Data Augmentation for Speech Emotion Recognition

Anti-Aliased Convolutional with Data Augmentation for Speech...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Linh-Chi Le Hoai-Bao Le Phuong Thi Le Jia-Ching Wang Dept. Computer Science and Information Engineering National Central University Taiwan Dept. Computer Science and Information Engineering Fu Jen Catholic University Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

关键词： Deep learning Training Emotion recognition Accuracy Convolution Speech recognition Speech enhancement Data augmentation Data models Robustness

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