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Rotation-Invariant Self-Supervised Representation Learning for Object Detection in Autonomous Driving 2

Rotation-Invariant Self-Supervised Representation Learning f...

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2nd International Conference on Computational Intelligence and Network Systems, CINS 2024

作者： Marathe, Aboli Roy, Sidharth Singh, Devansh Walambe, Rahee Kotecha, Ketan Machine Learning Dept. Carnegie Mellon University Pittsburgh United States Dept. of Computer and Information Science University of Pennsylvania Philadelphia United States Pune India Symbiosis Centre for Applied Artificial Intelligence Symbiosis International University Pune India

ISBN: (纸本)9798331504106

This paper describes a self supervised representation learning approach that can perform robust object detection in out-of-distribution rotated images for autonomous driving task. Keeping in mind the limitations of vehicle sensors we incorporate self-supervised rotation invariance for correcting rotational corruptions. We present a comprehensive analysis of observed label shifts, validate the results using holdout sets and provide explainability for the performance uisng GradCAM appaorach. We demonstrate results on real-world adversarial examples: (Autonomous Scenes - DAWN dataset) that significantly outperform common methods. The proposed framework outperforms the rotation-affected benchmark by 14.73 points of mAP for the OD task in autonomous driving applications. ©2024 IEEE.

关键词： Self-supervised learning

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Compromising insecure crypto implementations: A deep-learning based cryptosystem-agnostic testing framework

Compromising insecure crypto implementations: A deep-learnin...

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Artificial Intelligence, computer, Data sciences and Applications (ACDSA), International Conference on

作者： Leonard Hill Florian Schimanke Stefan Schiffner Robert Mertens Dept. of Computer Science HSW University of Applied Sciences Hameln Germany Dept. of Computer Science Berufliche Hochschule Hamburg Hamburg Germany

The use of insecure implementations of cryptographic systems makes encrypted communications vulnerable to practical attacks. Today, attacking, i.e. testing implementations requires human labour and an understanding of the cryptographic system. Automated systematic testing can reduce the insight needed to discover faulty implementations. The approach presented in this paper employs neural networks as the core of a universal framework for cryptographic attacks on arbitrary black-box encryption schemes. The framework trains a neuronal network to automatically perform decryption of ciphertext without knowing the corresponding decryption key. The network approximates the decryption function by encrypting randomly generated plaintext using an arbitrary encryption function and attempting to learn the relationship between plain-and ciphertext. If the decryption function for a certain key is successfully approximated by the framework, the plaintext of any message encrypted with this key can be restored.

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Improving Existing VANETs by Incorporating UAVS Using Ant Colony and PSO Algorithms 4

Improving Existing VANETs by Incorporating UAVS Using Ant Co...

引用

4th IEEE International Conference on Data Engineering and Communication Systems, ICDECS 2024

作者： Thangam, S. Dixit, Aniket Karn, Alok Kumar Thakur, Arnav Arunbalaji, Cg Jesy Janet Kumari, J. Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350393354

Vehicular Ad Hoc Networks (VANETs) are a type of wireless communication network that enable vehicles to communicate with each other and with roadside infrastructure in a peer-to-peer fashion;despite their vast applications, they come with several shortcomings. The key challenges in their real-world implementation include scalability, connectivity, and coverage issues. Unmanned Aerial Vehicles (UAVs), also known as drones, can complement existing VANETs in several ways to enhance their functionality and address some of their limitations. This paper studies the incorporation of UAVs in VANETs to overcome the challenges faced by the present networks. The approach is based on the dynamic deployment of UAVs in the most optimal positions, found by utilizing Particle Swarm Optimization (PSO) and Ant Colony algorithms which analyze the vehicle density, and previous coverage information in the network. The deployment of UAVs is intended to provide a seamless network coverage for ground vehicles. The impact of dynamic UAV mobility in communicating VANETs is comparatively studied. The simulation is done using Network Simulator-3 (NS3) simulator to evaluate the performance of 4 VANET protocols, AODV, DSR, OLSR, and DSDV, in terms of packet delivery ratio (PDR), Average End-to-End Delay, Throughput, Average Throughput per Packet, Packet Drop Rate, and Normalized Routing Load after incorporating the proposed modification designs. The paper concludes that the incorporation of Ant Colony is better suited to enhance VANETs than PSO. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Digital Twin and Industrial Internet of Things Architecture to Reduce Carbon Emissions 4

Digital Twin and Industrial Internet of Things Architecture ...

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4th International Conference on computer Communication and the Internet, ICCCI 2022

作者： Metallidou, Chrysi Psannis, Kostas E. Vergados, Dimitrios D. Dossis, Michael University of Macedonia University of Western Macedonia Dept. of Applied Informatics Dept. of Economics/Computer Science Kastoria Thessaloniki Greece University of Piraeus Dept. of Informatics Piraeus Greece University of Western Macedonia Dept. of Computer Science Kastoria Greece

ISBN: (数字)9781665469920

ISBN: (纸本)9781665469920

The rapid growth of digital technology implies the progress of industry, by utilizing Industrial Internet of Things and Digital Twins, in collecting data through sensors and digitally monitoring and testing a product, with a view to improving its features, before the production of the physical product, in real world. At the same time, industrial carbon emissions are a major issue to be confronted. Since, Digital Twin is a connection between the physical and digital world, transferring data bidirectionally and providing insights into the lifecycle of a production process, it also can be utilized for the reduction of industrial carbon emissions. In this paper, we implement a method for the reduction of carbon emissions, by applying the Industrial Internet of Things to collect past data from manufacturing factors and a Digital Twin architecture to monitor present data, compose a model and predict its future behavior, considering renewable energy resources and less carbon emissions. This method contributes in improved decision making regarding the manufacturing process and energy efficient industrial operation. © 2022 IEEE.

关键词： Energy efficiency

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Enhancing Reliability in Smart Agriculture: Detecting Failures and Anomalies in Irrigation System

Enhancing Reliability in Smart Agriculture: Detecting Failur...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Ahmed Dammak Yaser Al Mtawa Dept. of Applied Mathematics The University of Tunis Tunis Tunisia Dept. of Applied Computer Science The University of Winnipeg Winnipeg Canada

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Smart Agriculture (SA), a pivotal component of Industry 4.0, has revolutionized the agricultural sector by harnessing advanced technologies to optimize crop production, resource utilization, and environmental sustainability. However, integrating intelligent systems, particularly in Smart Irrigation (SI), introduces a complex network of interconnected assets susceptible to various failures. The realization of Industry 4.0’s potential in agriculture relies on the ability to detect and address these failures. This paper introduces the challenges and potential pitfalls encountered by SA, focusing on the critical domain of SI systems, notably concerning Water Pump failures and anomalies. We propose an innovative approach that combines both failure detection and anomaly detection in SA. By leveraging ML algorithms, we aim to develop tools capable of not only detecting failures but also detecting anomalies in irrigation systems and other vital components. Our interdisciplinary approach presents a clear roadmap to strengthen SA’s resilience and promote sustainable growth in the ever-changing landscape of Industry 4.0.

关键词： Smart agriculture Wireless communication Irrigation Analytical models Machine learning Water pumps Fourth Industrial Revolution

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Adaptive Strategies for Scalable and Heterogeneous VANET Network 5

Adaptive Strategies for Scalable and Heterogeneous VANET Net...

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

作者： Thangam, S. Jha, Priyanshu Hawari, Jawed Sah, Nabin Kumar Jain, Nikunj Jesy Janet Kumari, J.J. Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India College of Computing and Information Sciences University of Technology and Applied Sciences It Department Shinas Oman

ISBN: (纸本)9798350385649

Despite technological advancements, Vehicular Ad-hoc Networks (VANETs) continue to face challenges related to reliability and high-speed mobility. This study focuses on enhancing scalability, improving mobility, and addressing network heterogeneity in the context of data dissemination. Data dissemination involves the distribution or transmission of statistical data to users. Tools like NS3, SUMO utilizing OSM for realistic traffic simulations, MATLAB for Data Analysis and evaluation of various protocols like ADHOC, Dynamic Source Routing (DSR), Optimized Link State Routing Protocol (OLSR), Destination Sequenced Distance Vector Routing (DSDV). The research aimed to refine VANET simulations for effective decision making, as its primary objective data dissemination i.e. distribution or transmission of statistical data to users, forming the central focus of this investigation. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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An Adaptive Blockchain-Based Decentralized Network Computing and Performance Analysis 5

An Adaptive Blockchain-Based Decentralized Network Computing...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Seol, Jongho Kentner, Kyle Park, Indy N. Joshi, Shital Park, Nohpill Middle Georgia State University Dept. of Information Technology MaconGA United States Oklahoma State University Dept. of Computer Science StillwaterOK United States Vanguard University Dept. of Natural Science and Math Costa MesaCA United States

ISBN: (纸本)9798350339239

This paper presetns an adaptive chain as one of the most trustworthy blockchain-based network solutions for security and privacy for industrial applications and a Variable Bulk Arrival and Variable Bulk Service (VBAVBS) model in order to provide a quantitative method to support demonstration of the validity, feasibility, and further the potential performance benefits of the adaptive chain. The model assumes variable bulk arrivals of transactions in Poisson distribution, i.e., M1,n, where n represents the number of slots across all the mined transactions, and variable bulk services of transactions, each of which applies to a block potentially of different capacity in terms of the number of slots in it, in exponential time, i.e., M1,i,n, for posting in the current block, namely, VBAVBS. The difference between VBASBS [22] and VBAVBS is that in VBASBS, the state Pn is the only state to transition back into P0 while in VBAVBS, every state Pi,0 © 2023 IEEE.

关键词： Blockchain

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QoS CBSC: An Enhanced Metaheuristic Strategy on QoS-Cloud-based Service in Cloud 5

QoS CBSC: An Enhanced Metaheuristic Strategy on QoS-Cloud-ba...

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

作者： Jesy Janet Kumari, J. Thangam, S. Saleem Raja, A. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas It Department Oman

ISBN: (纸本)9798350385649

Due to the growing number of cloud users working on various cloud apps on specific infrastructure, resource allocation in cloud computing is implicitly difficult. Most resource allocation strategies currently in use focused on delivering efficiency determined by the workload of applications across many domains, such as business and scientific. Cloud service brokers compete strongly with one another to provide quality of service improvements based on the need, demand and the rapid growth of the services that are offered. Such conflict makes it difficult and complex to provide simple service selection and composition services in the cloud, this needs to be addressed to lighten the load on local resources. Because cloud-based services are too sophisticated and scalable, it is preferable to use an optimization strategy to choose the services that will meet the needs of the clients. To do this, a hybrid algorithm Modified Ant Colony System Cloud Services Composition (MACSCSC) is proposed to employ Ant Colony Optimization (ACO) incorporated with Genetic Algorithm (GA) to smoothly increase cloud-based services. When allocating cloud resources these meta-heuristic algorithms can achieve significantly better performance, lower costs and instances, better utilization of resources, and increased energy efficiency. The empirical findings on different real datasets have been demonstrated to show the improvements of the suggested method to overcome the drawbacks such as allocation of resources and high power consumption. © 2024 IEEE.

关键词： Quality of service

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Advantages of brain parcellation in Multiple Sclerosis Lesion Segmentation

Advantages of brain parcellation in Multiple Sclerosis Lesio...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Dario Samuele Pishvai Alessia Rondinella Francesco Guarnera Sebastiano Battiato Dept. of Math and Computer Science University of Catania Catania Italy

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Segmentation of multiple sclerosis lesions plays an important role in understanding disease status. In this work, we focus on the effectiveness of brain parcellation in enhancing the performance of segmentation for multiple sclerosis lesions in Magnetic Resonance Imaging. Brain parcellation does not improve the segmentation performance, but make the results more robust in terms of overall variability (e.g. standard deviation), by dividing the brain into physically significant sub-regions that the model can concentrate on. Our approach combines parcellation with the existing diffusion-based model to increase sensitivity, particularly in regions with small anomalies. We conducted a thorough evaluation of a reference dataset on the field using all available modalities. Our results show how the parcellation of the brain when integrated into a diffusion-based pipeline, makes the segmentation of MS more stable, lowering deviations from the average, and improving some of the results w.r.t. state-of-the-art. This method achieves good segmentation capabilities even with small datasets, providing promising indications for further research.

关键词： Image segmentation Multiple sclerosis Sensitivity Magnetic resonance imaging Biological system modeling Pipelines Brain modeling Lesions Standards Biomedical imaging

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OLBR: Optimization of Location-Based Routing Protocols in Vehicular Ad Hoc Networks

OLBR: Optimization of Location-Based Routing Protocols in Ve...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Srikar Reddy, M. Vivek Ullas, Karthik Khadar Jilani, N. Abdul Venkatesh, K. Janet Kumari, J. Jesy Saleem Raja, A. Amrita School of Computing Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350309140

The proposed work employs ns-3, SUMO, and NetAnim to create geographical routing in vehicular ad hoc networks (VANETs). The research attempts to assess the performance of three well-known protocols AODV, DSDV, and OLSR in VANET settings. Utilizing SUMO's realistic mobility models and NS3's simulation capabilities, the project simulates node communication, protocol behaviour, and vehicle movement. The main purpose is to know how well various routing techniques work in dynamic vehicular situations. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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