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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Mukesh, P. Jegatheesan, A. Saveetha University Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Chennai India

ISBN: (纸本)9798350384277

This study compares the Novel K-Nearest Neighbor's (KNN )algorithm's Local Forecast accuracy to the Decision Tree(DT) technique using meteorological data. This will be done by comparing the two predicting approaches. Using the Novel KNN approach and DT with a sample size of 25 at various time periods, the Local Forecast prediction is analysed for accuracy. Another method that is utilised is a G-power pretest, which has a confidence interval of 95% and a power of 80%. In terms of accuracy, the Novel KNN strategy is superior than the DT approach, which has an accuracy rate of 72.8%. The accuracy reached by the new KNN Algorithm is 83.61 percent. There is a statistical significance of p = 0.000 for the forecast difference, which is below the threshold of p © 2024 IEEE.

关键词： k-nearest neighbors

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Land Cover Classification for Polarimetric SAR Images Based on Global Membership Tensor 2

Land Cover Classification for Polarimetric SAR Images Based ...

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2nd IEEE International Conference on Signal, Information and data Processing, ICSIDP 2024

作者： Ren, Dawei Han, Songli Gao, Fan Yin, Junjun Yang, Jian Tsinghua University Department of Electronic Engineering Beijing China University of Science and Technology School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

The increasing resolution of PolSAR images makes it challenging to achieve satisfactory land cover classification performance with a single feature. Existing research considers combining multiple features to integrate polarimetric and multi-modal information from images, thereby better representing the diversity of land cover. Nevertheless, in the process of extracting multimodal information, the challenges of dimensionality disaster and dynamic range discrepancies persist, and how to effectively eliminate redundant information while preserving higher-order correlations among features remains a significant research challenge. This paper proposes a PolSAR land cover classification framework based on a global membership tensor, which avoids the dimensionality disaster and dynamic range difference issues by concatenating the pre-classified membership matrices, and utilizes Tucker decomposition to extract higher-order correlation information embedded in the tensor structure of the global membership tensor for final land cover classification. Experiments are carried out on the multi-frequency Hainan dataset acquired by the Aerospace Information Research Institute Chinese Academy of sciences (AIRCAS). The experimental results indicate that the proposed classification framework based on global membership tensors successfully integrates polarimetric and texture features for effective land cover classification. © 2024 IEEE.

关键词： Tensors

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Federated Learning With Massive Random Access

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IEEE Transactions on Wireless Communications 2024年第10期23卷 13856-13871页

作者： Xia, Shuhao Shi, Yuanming Zhou, Yong Wu, Youlong Yang, Lin F. Letaief, Khaled B. The School of Information Science and Technology ShanghaiTech University Shanghai201210 China The Department of Electrical and Computer Engineering University of California at Los Angeles Los AngelesCA90095 United States Hong Kong

In this paper, we propose an online federated learning framework with massive random access, aiming to learn a sequence of global models using local data that are sequentially collected by massive edge devices. As only a subset of devices is capable of collecting data and performing local model update at any specific moment, the communication pattern between the edge server and devices is random and sporadic, which is referred to as sporadic local updates. This motivates us to adopt a two-phase grant-free random access scheme that consists of the activity detection and model transmission phases to facilitate efficient communication between the edge server and devices. We first provide the regret analysis for online federated learning, and derive the optimality gap in terms of successful transmission probabilities. Then, we characterize the achievable transmission rate of each active device using random matrix theory and establish the relationship between the pilot length and the outage probability. Furthermore, we propose an optimal pilot length design by minimizing the optimality gap. To validate our scheme, we provide comprehensive experimental results that demonstrate the superiority of the proposed scheme over traditional schemes in various online tasks. © 2002-2012 IEEE.

关键词： Wireless sensor networks

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Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks 41

Structure-Aware E(3)-Invariant Molecular Conformer Aggregati...

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41st International Conference on Machine Learning, ICML 2024

作者： Nguyen, Duy M.H. Lukashina, Nina Nguyen, Tai Le, An T. Nguyen, TrungTin Ho, Nhat Peters, Jan Sonntag, Daniel Zaverkin, Viktor Niepert, Mathias Department of Computer Science University of Stuttgart Germany Germany Germany Department of Computer Science Technische Universitat Darmstadt Germany School of Mathematics and Physics University of Queensland Australia Department of Statistics and Data Sciences University of Texas Austin United States Hessian.AI United States Department of Applied Artificial Intelligence Oldenburg University Germany NEC Laboratories Europe Germany

A molecule's 2D representation consists of its atoms, their attributes, and the molecule's covalent bonds. A 3D (geometric) representation of a molecule is called a conformer and consists of its atom types and Cartesian coordinates. Every conformer has a potential energy, and the lower this energy, the more likely it occurs in nature. Most existing machine learning methods for molecular property prediction consider either 2D molecular graphs or 3D conformer structure representations in isolation. Inspired by recent work on using ensembles of conformers in conjunction with 2D graph representations, we propose E(3)-invariant molecular conformer aggregation networks. The method integrates a molecule's 2D representation with that of multiple of its conformers. Contrary to prior work, we propose a novel 2D-3D aggregation mechanism based on a differentiable solver for the Fused Gromov-Wasserstein Barycenter problem and the use of an efficient conformer generation method based on distance geometry. We show that the proposed aggregation mechanism is E(3) invariant and propose an efficient GPU implementation. Moreover, we demonstrate that the aggregation mechanism helps to significantly outperform state-of-the-art molecule property prediction methods on established datasets. Our implementation is available at this link. Copyright 2024 by the author(s)

关键词： Molecular docking

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A Hyper-tuned Metrics based Augmented CNN Model for Accurate Prediction of Monkeypox Risk

A Hyper-tuned Metrics based Augmented CNN Model for Accurate...

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2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Mishra, Arpit Ayushman Mishra, Sahitya Shastri, Aditya A. Alkhayyat, Ahmed Kalinga Institute of Industrial Technology School of Computer Engineering Bhubaneswar India Pdeu Department of Computer Science and Engineering India The Islamic University College of Technical Engineering Najaf Iraq

ISBN: (纸本)9798331508432

Monkeypox, a zoonotic viral infection, has emerged as a global health concern. Early and accurate diagnosis is crucial for effective containment. This research investigates the application of Convolutional Neural Networks (CNNs) for the classification of monkeypox skin lesions from other pox types and normal skin. Leveraging a comprehensive dataset of skin images, we explored various CNN architectures, including pre-trained models and custom designs. data augmentation techniques were employed to enhance model robustness. The performance of the models was evaluated using metrics such as accuracy, precision, recall, and F1-score. Our findings demonstrate the potential of CNNs as a valuable tool for the rapid and accurate detection of monkeypox, aiding in public health efforts to control the spread of this disease. © 2024 IEEE.

关键词： Convolutional neural networks

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Secure Goods Storage and Anti-Theft Approach using Ethereum Blockchain 5

Secure Goods Storage and Anti-Theft Approach using Ethereum ...

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5th International Conference on Innovative data Communication Technologies and Application, ICIDCA 2024

作者： Amasala, Likhitha Ponnuru, Mahesh Srideviponmalar, P. School of Computer Science and Engineering Vellore Institute of Technology Amaravathi522237 India School of Computing SRM Institute of Science and Technology Potheri603203 India Department of Computational Intelligence School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Potheri603203 India

At present, technological systems lack a secure and transparent method for tracking goods and preventing theft in e-commerce, leading to trust issues and data vulnerabilities. There is a pressing need for a comprehensive solution that integrates Ethereum blockchain, IPFS, and advanced cryptographic techniques to address these challenges and enhance the security and transparency of transactions. This research paper presents a robust system that harnesses the Ethereum blockchain, IPFS (Interplanetary File System), and advanced cryptographic algorithms to create a secure, decentralized approach for tracking goods and preventing theft incidents. Unique identifiers and related information will be sent to the mail of the customer and same should entered by the customer for successful transaction. By assigning unique identifiers to purchased products and employing cryptographic techniques to encrypt sensitive data, our system ensures both user privacy and the creation of an immutable transaction ledger. Users can efficiently manage their purchased goods, block stolen items, and communicate with sellers through an intuitive interface. Additionally, the system provides sellers with a comprehensive transaction history, enhancing accountability and transparency within the supply chain. Through this research, we demonstrate the effectiveness of our blockchain based anti-theft measures, underpinned by Ethereum, IPFS, and cutting-edge cryptographic algorithms, in fostering secure, trustless transactions. This work highlights the transformative potential of blockchain technology and decentralized protocols in revolutionizing security and transparency across diverse sectors. © 2024 The Authors. Published by Elsevier B.V.

关键词： Smart contract

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SSL4Q: Semi-Supervised Learning of Quantum data with Application to Quantum State Classification 41

SSL4Q: Semi-Supervised Learning of Quantum Data with Applica...

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41st International Conference on Machine Learning, ICML 2024

作者： Tang, Yehui Yang, Nianzu Long, Mabiao Yan, Junchi School of Artificial Intelligence Department of Computer Science and Engineering MoE Lab of AI Shanghai Jiao Tong University Shanghai China

The accurate classification of quantum states is crucial for advancing quantum computing, as it allows for the effective analysis and correct functioning of quantum devices by analyzing the statistics of the data from quantum measurements. Traditional supervised methods, which rely on extensive labeled measurement outcomes, are used to categorize unknown quantum states with different properties. However, the labeling process demands computational and memory resources that increase exponentially with the number of qubits. We propose SSL4Q, manage to achieve (for the first time) semi-supervised learning specifically designed for quantum state classification. SSL4Q’s architecture is tailored to ensure permutation invariance for unordered quantum measurements and maintain robustness in the face of measurement uncertainties. Our empirical studies encompass simulations on two types of quantum systems: the Heisenberg Model and the Variational Quantum Circuit (VQC) Model, with system size reaching up to 50 qubits. The numerical results demonstrate SSL4Q’s superiority over traditional supervised models in scenarios with limited labels, highlighting its potential in efficiently classifying quantum states with reduced computational and resource overhead. Copyright 2024 by the author(s)

关键词： Qubits

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Exploring the concept of multi-modality using grounding dino with evaluation of its performance in the context of different types and complexity of input text prompts

Exploring the concept of multi-modality using grounding dino...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Rahim, Abdul Singh, Amanjot Sharma, Ankur Garg, Rachit Ravisankar, Ch Yamsani, Nagendar Malla Reddy Engineering College for Women Department of ECE Hyderabad India Lovely Professional University School of Electronics and Electrical Engineering Punjab Phagwara India Institute of Technology and Science Mohan Nagar Ghaziabad India Lovely Professional University School of Computer Science and Engineering Punjab Phagwara India SR University School of Computer Science and Artificial Intelligence Warangal India

ISBN: (纸本)9798350394412

We have known artificial intelligence, deep learning models can be trained with a certain type of input format to perform a task e.g., OCR models takes input in the form of image to read the text characters from the image, a weather prediction model can take weather data like wind speed, moisture, etc. as an input which is in text format to predict future weather data. But the multi-modality concept which is comparatively newer in the market paves the way for models to be built which can take more than one type of inputs e.g., text and audio, text and image, etc. In the same concept one of the popular architectures is specially designed for detection of any hindrance, model grounding dino about which we will be discussing in this setting. It is a zero-shot object detection model which can perform inference just by taking a text prompt input from the user describing what they want the model to detect in the provided image. In this study, we will be discussing about its capabilities, architecture and also its performance. We will be testing and quantifying its performance using standard self-created input text prompts with variations including description of the object, complexity of the object, etc. on a standard image. © 2024 IEEE.

关键词： Zero-shot learning

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Software Re-Engineering using Cloud Computing Platform 5

Software Re-Engineering using Cloud Computing Platform

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Raja, A. Ravi Raghunandan, K.R. Dodmane, Radhakrishna Dixit, Asmita Kumar, M. Sunil Kapila, Dhiraj Velagapudi Ramakrishna Siddhartha Engineering College Ece Department Vijayawada India Department of Computer Science and Engineering Nitte India Abes Engineering College Department of Informaton Technology Ghaziabad India Mohan Babu University School of Computing Department of Computer Science and Engineering Vijayawada India Lovely Professional University Department of Computer Science and Engineering Phagwara India

ISBN: (纸本)9781665474672

Economic and technological progress in the cloud are the main topics of this article. The essay examines the question of whether or not it makes financial sense to build software in the cloud, vs in-house. This research work provides an overview of the current model-based re-engineering practises. A novel and more thorough method is outlined in Business Process Model and Notation (BPMN) with some example activities, inputs, and outputs. As an integral element of the primary re-engineering process, reverse engineering is also something to be considered. Therefore, it expands on the concept of 'SBSE for the cloud,' providing actionable formulations of problems associated with cloud computing. The system has been built in the cloud to track the health of analytical services while they are being called into use. As an example of analytical services, a number of implementations of data mining methods are hosted from a number of packages. Their Quality of Service (QoS) values are also sampled by running them on certain real datasets. Based on the analysis of the KSEA National Math Competition event management system, this project will suggest some guidelines for software reengineering using AWS cloud computing services and web application technologies. Using these best practises, the informational gaps in software reengineering are bridged for web applications built in with cloud computing frameworks. © 2023 IEEE.

关键词： Cloud computing

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Quantum Cryptography Techniques for Enhancing Security in IoT Communications

Quantum Cryptography Techniques for Enhancing Security in Io...

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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Naga, Suresh Bysani Venkata Kotiyal, Arnav Battula, R.S.S. Raju Patil, Harshal Dharangutti, Yogesh Natrayan, L. Eightfold.ai Ex - Cohesity CA United States Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Aditya University Department of Computer Applications Surampalem India Iilm University School of Computer Science & Engineering Greater Noida India Department of Law Pune India School of Engineering Simats Department of Mechanical Engineering Saveetha Kuthambakkam India

ISBN: (纸本)9798350375442

A system of wirelessly communicative sensors embedded in a person's clothing. In order to remotely monitor and treat a patient's health, sensor devices are embedded in clothing, skin, and the human body itself. Healthcare, the military, sports, and remote treatment are just a few of the modern WBSN applications. It improves people's quality of life by allowing for more precise and quicker disease diagnosis as well as more timely care and more effective treatment. Even if a patient is far away from medical care, WBSN can still save their life. Despite the numerous benefits that WBSN technology brings to healthcare systems, there are legitimate concerns about security and privacy when it comes to collecting and transmitting physiological data about humans in an open setting. Ensuring the security of physiological data during transmission in a wireless environment is a challenging but crucial task. Key distribution, authentication, data integrity, and data confidentiality are just a few of the many security issues plaguing the WBSN. In tackling the WBSN security issues, this research contributes significantly. Secure transmission in wireless networks and high attack resistance are both provided by the cryptographic computational process. Nevertheless, the unsecure transmission of keys across networks is the sole vulnerability of public and private key cryptography methods. Attackers can easily crack traditional key sharing protocols used by communicating parties. Intruders can compromise the system's security in its entirety if they obtain the secret key. In WBSN, a secure way to generate and distribute secret keys is required. The EBB84QCP is a method for creating and sharing secret keys between communicating parties. Rather than using two prime numbers, the Enhanced and Modified RSA Cryptosystem (EMRSACS) suggests using four prime numbers for key generation, encryption, and decryption. data transmission in wireless networks still involves a secret quantum key that is

关键词： Quantum cryptography

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