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2024 IEEE International Conference on Big Data, BigData 2024

作者： Ghosh, Aswini Sharma, Nelson Misra, Rajiv Indian Institute of Technology Department of Computer Science and Engineering Patna India

ISBN: (纸本)9798350362480

Rapid technical advancements in recent times have made it possible to produce a class of affordable unmanned aerial vehicles (UAVs), which can serve a wide range of public and private users for different industrial or non-industrial requirements. It is very complex to set up a communication network among the UAVs, which is very essential for completing any task like collecting data in extreme weather conditions. For UAV placement, we have suggested a distributed approach using PPO-based reinforcement learning;here, UAVs are utilized as aerial access points to create a mesh network that connects to ground nodes positioned in a designated area and can collect data from ground nodes to predict weather conditions. Our objective is to fulfill each ground node's data rate requirements while deploying the fewest number of UAVs possible to cover it. The convex hull formation of swarm uavs satisfy our objective, which arranges the n uavs on a convex hull's vertex. In this study, we present a deep reinforcement learning-based method for building swarm uavs with convex hull patterns in the euclidean plane. The existing research on convex hull pattern generation uses heuristic and combinatorial optimization techniques and evaluates performance in terms of time and space consumed. Convex hull patterns increase the mutual visibility of swarm UAVs, which helps in the cooperation of UAVs. In our research for the first time, convex hull pattern formation around a given target point is accomplished using PPO-based Deep Reinforcement Learning (DRL). © 2024 IEEE.

关键词： Combinatorial optimization

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A Hybrid Channel Access Mechanism for NR-U to Improve the Coexistence Performance 16

A Hybrid Channel Access Mechanism for NR-U to Improve the Co...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Akbar Basha, K.M. Gumasthi, Nikhil Baswade, Anand M. Indian Institute of Technology Bhilai Department of Computer Science and Engineering India

ISBN: (纸本)9798350383119

The saturated licensed spectrum is insufficient to meet the increasing demand for data traffic, which paves the path for exploring new bands. Since the unlicensed bands are free of cost, efforts are made to offload the cellular data to unlicensed bands, which results in unlicensed versions of cellular technologies. New Radio Unlicensed (NR-U) is the unlicensed version of New Radio (NR). Since anyone can access unlicensed frequency, the devices follow listen before talk (LBT) to gain access to the unlicensed band. Unlike WiFi, the dominant technology in unlicensed bands, the cellular node can not transmit data immediately after the LBT procedure. The node has to wait for the next licensed slot boundary to occur since it is scheduled technology. However, the LBT procedure can end before the occurrence of slot boundary;the period after LBT to the slot bound boundary by sending a reservation signal (RS) or staying idle using a gap. The RS approach yields high fairness with less efficiency, whereas the gap-based approach gives better fairness with comparatively less fairness. To deal with the tradeoff in fairness and efficiency, we have proposed a hybrid channel access method that uses both gap and RS approaches. In the proposed method, the duration of RS is limited by a threshold, and the RS is transmitted as fragments. The proposed method achieves 54 % to 128 % higher fairness than the gap-based approach and 10 % to 28 % than the RS-based approach for the given simulation scenario. © 2024 IEEE.

关键词： Channel access Coexistence LBT NR-U Unlicensed bands Wireless networks

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Analysis of environmental impact factors in urban road traffic accidents: logistic regression model

Advances in Transportation Studies

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Advances in Transportation Studies 2024年第Special issue期3卷 39-50页

作者： Zhao, X.J. Li, S.Y. Guan, H.B. College of Mathematics and Information Science Anyang institute of Technology Anyang455000 China School of Computer Science and Information Engineering Anyang Institute of Technology Anyang455000 China College of Mathematics and Information Science Zhengzhou University of Light Industry Zhengzhou450002 China

The traditional methods for analyzing environmental impact factors in urban road traffic accidents suffer from issues such as low recall, poor precision, and time-consuming processes. To address these challenges, a novel analysis method based on the logistic regression model is proposed. This method utilizes the MIFP-Apriori algorithm to collect urban road traffic accident data and incorporates the EM algorithm for data filling and processing. Principal component analysis is then employed to screen the environmental impact factors in urban road traffic accidents. These selected factors are input into the logistic regression model to conduct a comprehensive analysis. The results reveal that environmental impact factors like road conditions and meteorological factors have a significant influence on traffic accidents. Experimental results show that the proposed method achieves an average recall rate of 96.98%, an average precision rate of 97.66%, and the analysis time for environmental factors ranges from 0.12s to 0.52s. © 2024, Aracne Editrice. All rights reserved.

关键词： Environmental impact factors Logistic regression model Mifp-apriori algorithm Principal component analysis method Traffic accident Urban road

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Priority-Based MPTCP Scheduler for 5G and Beyond Heterogeneous Links 16

Priority-Based MPTCP Scheduler for 5G and Beyond Heterogeneo...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Gumasthi, Nikhil B. Baswade, Anand M. Indian Institute of Technology Bhilai Department of Computer Science and Engineering India

ISBN: (纸本)9798350383119

Modern cellular devices often have dual interfaces for providing high-speed data transfer. This dual-interface design enhances versatility and user convenience. Dual interface technology allows 5G NR devices to connect to the 5G core using two separate base stations. One base station operates in the mmWave frequency range, and the other operates in the sub-6 GHz frequency range. However, millimeter-wave (mmWave) signals face challenges in terms of limited penetration through obstacles, such as buildings, and susceptibility to atmospheric absorption, leading to reduced coverage and potential signal degradation in adverse weather conditions. On the other hand, sub-6 GHz waves offer better penetration through obstacles and a broader scope compared to mmWave, making them suitable for providing reliable and expansive wireless connectivity in urban and indoor environments. Both mmWave and sub-6 GHz frequencies have distinct advantages and limitations;mmWave provides high data rates but has limited coverage, while sub-6 GHz offers a broader range but at lower data rates. However, in a heavy data transfer scenario, frequent loss in the mmWave link while transmitting packets can lead to packet drops (wireless medium), reducing the congestion window size and increasing the flow completion time. To mitigate this, we propose to use analytical hierarchy process (AHP) and grey rational analysis (GRA) based priority allocation mechanism to schedule packets on the most reliable link, thereby reducing the packet drops and flow completion time. © 2024 IEEE.

关键词： 5G NR Multipath TCP (MPTCP) network simulator-3 (NS-3) network simulator-3-mmWave priority scheduling

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SPVPC: Smart Contract Based Publicly Verifiable Polynomial Computations 18th

SPVPC: Smart Contract Based Publicly Verifiable Polynomial C...

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18th International Conference on Network and System Security, NSS 2024

作者： Chakraborty, Partha Sarathi Tripathy, Somanath Department of Computer Science and Engineering Indian Institute of Technology Patna Patna India

ISBN: (纸本)9789819635306

The desire to delegate computation to the cloud arises from the proliferation of small, computational restrained devices. However, to ensure the security and privacy of the stored data in the cloud, data owners always encrypt their sensitive data before outsourcing it. Nonetheless, computation outsourcing proves beneficial only when the returned result is trustworthy. Moreover, it must ensure the security and confidentiality of the computation and data during execution. Thus, the challenge lies in efficiently verifying the correctness of computation results generated over encrypted data and maintaining practical computational time for verifying results. Blockchain emerges as a trustworthy entity, enabling fairness and transparency in the scheme. We propose a secure and efficient smart contract based publicly verifiable polynomial computation with an incentive mechanism to protect confidentiality. In the proposed scheme, the smart contract is a verifier that ensures trusted verification and manages incentive transfer. We demonstrate the proposed scheme’s effectiveness through security proofs and performance analysis, significantly reducing verifier computational costs and enhancing overall efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Polynomials

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HLS driven Hybrid GA-PSO for Design Space Exploration of Optimal Palmprint Biometric based IP Watermark and Loop Unrolling Factor 10

HLS driven Hybrid GA-PSO for Design Space Exploration of Opt...

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10th IEEE International Symposium on Smart Electronic Systems, iSES 2024

作者： Sengupta, Anirban Chourasia, Vishal Kumar, Nitish Computer Science and Engineering Indian Institute of Technology Indore Indore India

ISBN: (纸本)9798331533229

This paper proposes a novel high level synthesis (HLS) based hybrid Genetic Algorithm-Particle Swarm Optimization (GA-PSO) framework for concurrent design space exploration (DSE) of optimal palmprint biometric based intellectual property (IP) watermark and optimal loop unrolling factor. The proposed approach is a hybrid exploration framework that merges GA process with specific utility attributes of PSO based DSE framework such as mutation, local and global best design solution concepts, which aids in escaping getting stuck at local minima. The proposed approach is capable of providing low-cost robust detective security countermeasure against threats of IP ownership abuse and IP piracy using IP seller's optimal palmprint biometric watermark. The comparison of the proposed approach with related works demonstrated optimal quality palmprint watermark in terms of lower probability of coincidence (watermark collision) and stronger tamper tolerance ability, at zero design cost overhead. © 2024 IEEE.

关键词： Space research

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Point-To-Set Principle and Constructive Dimension Faithfulness 49

Point-To-Set Principle and Constructive Dimension Faithfulne...

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49th International Symposium on Mathematical Foundations of computer science, MFCS 2024

作者： Nandakumar, Satyadev Pulari, Subin Akhil, S. Department of Computer Science and Engineering Indian Institute of Technology Kanpur India

ISBN: (纸本)9783959773355

Hausdorff Φ-dimension is a notion of Hausdorff dimension developed using a restricted class of coverings of a set. We introduce a constructive analogue of Φ-dimension using the notion of constructive Φ-s-supergales. We prove a Point-to-Set Principle for Φ-dimension, through which we get Point-to-Set Principles for Hausdorff dimension, continued-fraction dimension and dimension of Cantor coverings as special cases. We also provide a Kolmogorov complexity characterization of constructive Φ-dimension. A class of covering sets Φ is said to be "faithful" to Hausdorff dimension if the Φ-dimension and Hausdorff dimension coincide for every set. Similarly, Φ is said to be "faithful" to constructive dimension if the constructive Φ-dimension and constructive dimension coincide for every set. Using the Point-to-Set Principle for Cantor coverings and a new technique for the construction of sequences satisfying a certain Kolmogorov complexity condition, we show that the notions of "faithfulness" of Cantor coverings at the Hausdorff and constructive levels are equivalent. We adapt the result by Albeverio, Ivanenko, Lebid, and Torbin [1] to derive the necessary and sufficient conditions for the constructive dimension faithfulness of the coverings generated by the Cantor series expansion, based on the terms of the expansion. © Satyadev Nandakumar, Subin Pulari, and Akhil S.

关键词： Geometry

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Tolerant Testing and Distance Estimation for Distributions Under Memory Constraints 50th

Tolerant Testing and Distance Estimation for Distributions...

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50th International Conference on Current Trends in Theory and Practice of computer science, SOFSEM 2025

作者： Roy, Sampriti Vasudev, Yadu Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai India

ISBN: (纸本)9783031826962

We investigate tolerant testing and distance estimation problems in distribution testing when the amount of memory is limited. In particular, our aim is to provide a good estimate of the distance measure (in total variation distance) using constant memory words. Though the problems are well understood in the standard access model with an Ω(nlogn) lower bound, it has not been explored under memory constraints. We propose algorithms that require O(nϵ7) queries for estimating distance to a known distribution and O(nϵ6) queries (where ϵ∈(0,1) is an error parameter) for estimating distance to uniformity that use only O(1) memory words. Our algorithms match the Ω(nϵ4) lower bound established by [19] in terms of the dependence on n. Additionally, we present an (ϵ,cϵ) tolerant closeness tester in terms of 2 distance for all c≥3, which requires O(n3mϵ2) samples and O(m) bits of memory for logn/ϵ4≤m≤n/ϵ2. Furthermore, we outline an O(n2ϵ12mϵ24) trade-off for (ϵ1,ϵ2) tolerant closeness testing problem (0121 distance, where logn≤m≤nlogn is the available memory in bits. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Distribution testing Property testing Streaming

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Exploring Transformer-Based Approaches for Hyperspectral Image Classification: A Comparative Analysis 3rd

Exploring Transformer-Based Approaches for Hyperspectral Ima...

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3rd International Conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Arya, Rajat Kumar Srivastava, Rajeev Department of Computer Science and Engineering Indian Institute of Technology-BHU Varanasi India

ISBN: (纸本)9789819743582

Hyperspectral imaging (HSI) is a technique that captures and analyzes multiple spectral bands for each pixel in an image. Convolutional neural networks (CNNs) effectively extract local features for HSI classification but struggle with capturing sequential spectral signatures. To address this, we conducted a comparative study to assess the performance of transformers, which can handle sequential information, in HSI classification. We reviewed a few models in the literature, analyzing their architecture and performance. Using the indian Pines dataset, we evaluated models like ViT, SSRN-ViT, SpectralFormer, and Double-ViT. Our results show that Double-ViT models outperform transformers for HSI classification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Tracking of Ship and Plane in Satellite Videos Using a Convolutional Regression Network with Deep Features 3rd

Tracking of Ship and Plane in Satellite Videos Using a Convo...

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3rd International Conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Sharma, Devendra Srivastava, Rajeev Computer Science and Engineering Department Indian Institute of Technology BHU Varanasi India

ISBN: (纸本)9789819743582

Object tracking is one of the latest research topic in various applications of computer vison. Satellite videos are provided by the commercial satellite makes it possible to extend into earth observation. Moving objects are occupy the small region of pixel and they are confused with neighboring regions also with objects. Due to the resolution constraints, the nearest similar objects can rarely be distinguished by appearance features. Conventional tracking techniques in satellite videos with hand-crafted features do not give better results. Deep learning-based techniques have proven to be superior in visual tracking benchmarks, but this is not fully explored for the object tracking in the satellite videos. Regression network is used to integrate the regression model with convolutional layers. Both motion feature and appearance feature are taken from pre-trained deep neural networks VGG16, VGG19, and ResNet50. When tracker faces obscure appearance information, motion features of object are used for discrimination and complementary information to improve the performances of model. Experimental analysis on ship and plane represents the ResNet50 feature extractor gives better tracking result. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep neural networks

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