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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Gao, Junhui Wang, Qianru Zhang, Xin Shi, Juan Zhao, Xiang Han, Qingye Pan, Yan School of Computer Science Northwestern Polytechnical University China School of Computer Science and Technology Xidian University China Air Force Engineering University China National University of Defense Technology Laboratory for Big Data and Decision China School of Management Science and Real Estate Chongqing University China National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9798350317152

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Utilizing Machine Vision for Steerable Robotic Control 5th

Utilizing Machine Vision for Steerable Robotic Control

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Agarwal, Trapty Kavitha, R. Verma, Sunny Sasi, Archana Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

This paper describes the design and implementation of a steerable robot control device making use of machine imaginative and prescient. The machine consists of a robot car ready with a 3-d digital camera, a show and a manipulate panel. The camera captures 3-d intensity pix of the surroundings and the manage panel lets in the consumer to output instructions that manipulate the motion of the auto. The vision module of the system uses a Convolutional Neural community (CNN) to discover objects inside the environment and small variations in elevation and assign distinct that means to them. This facts is then utilized by the control module to formulate the commands in step with the person’s commands, which then get sent to the car’s pressure device. The system additionally uses an optimization set of rules to help become aware of most beneficial paths thru the environment and avoid limitations. Eventually, the gadget can be used to monitor the automobiles positioning within the surroundings permitting the user to benefit information which include the place, orientation and pace of the automobile. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Digital cameras

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Graph-based Analysis of the Algorand Blockchain Network 3

Graph-based Analysis of the Algorand Blockchain Network

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3rd International Conference on Blockchain technology and information Security, ICBCTIS 2023

作者： Zheng, Jiawen Yang, Liu Zhou, Wei Liu, Heng School of Computing and Artificial Intelligence Southwest Jiaotong University Sichuan Chengdu611756 China School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu611756 China

ISBN: (纸本)9798350340402

Over the past few years, Algorand has emerged as one of the prominent pure proof-of-stake (PPoS) blockchains, with a rapidly growing number of accounts and transactions. Despite its increasing significance, there is limited knowledge about its smart contracts, transaction activities, and other features. This paper^ presents the first comprehensive study of Algorand using graph analysis to investigate the creation of entities" payment of Algos, invocation of smart contracts, and Transfer of assets over time. By collecting and analyzing external transaction data, we have constructed graphs to gain insights into the behavior of the blockchain Our research has uncovered novel observations and insights by performing relevant graph analysis, and we have also proposed a solution to one security problem based on these grajhs. © 2023 IEEE.

关键词： Smart contract

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A Comprehensive Study of Convolutional Neural Networks for Medical Image Segmentation 5th

A Comprehensive Study of Convolutional Neural Networks for M...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Nautiyal, Kapish Augustine, Jacob Savita Rengarajan, A. Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

It affords an overview latest, the modern-day inside the field of modern-day clinical picture segmentation, after which highlights the gain of trendy CNNs in it. The paper then describes today's CNNs’ fundamentals, architectures, and education techniques. It similarly affords one-of-a-kind CNN fashions used for clinical image segmentation. It presents a comprehensive analysis of new research addressing modern-day CNNs’ utility for this assignment. In the end, the paper affords steering for destiny research guidelines in scientific photo segmentation, the use of CNNs, and an outlook for the ability of today’s this era. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Cross-chain Sharing of Personal Health Records: Heterogeneous and Interoperable Blockchains

Cross-chain Sharing of Personal Health Records: Heterogeneou...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Lv, Yongyang Li, Xiaohong Wang, Yingwenbo Chen, Kui Hou, Zhe Feng, Ruitao Tianjin University College of Intelligence and Computing Tianjin China Griffith University School of Information and Communication Technology Brisbane Australia Southern Cross University Faculty of Science and Engineering Gold Coast Australia

ISBN: (纸本)9798350386226

With the widespread adoption of medical informatics, a wealth of valuable personal health records (PHR) has been generated. Concurrently, blockchain technology has enhanced the security of medical institutions. However, these institutions often function as isolated data silos, limiting the potential value of PHRs. As the demand for data sharing between hospitals on different blockchains grows, addressing the challenge of cross-chain data sharing becomes crucial. When sharing PHRs across blockchains, the limited storage and computational capabilities of medical Internet of Things (IoT) devices complicate the storage of large volumes of PHRs and the handling of complex calculations. Additionally, varying blockchain cryptosystems and the risk of internal attacks further complicate the cross-chain sharing of PHRs. This paper proposes a scheme for sharing PHRs across heterogeneous and interoperable blockchains. Medical IoT devices can encrypt and store real-time PHRs in an InterPlanetary File System, requiring only simple operations for data sharing. An enhanced proxy re-encryption(PRE) algorithm addresses the differences in blockchain cryptosystems. Multi-dimensional analysis demonstrates that this scheme offers robust security and excellent performance. © 2024 IEEE.

关键词： Electronic health record

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Unlocking New Opportunities for Crop Management Through Hyper Spectral Image Analysis 5th

Unlocking New Opportunities for Crop Management Through Hype...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Kumar, R. M. Sunil Agarwal, Trapty Mehta, Deepak Singh, Arjun School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electronic and Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Hyper spectral imaging has emerged as a reliable and accurate method of crop management. The era involves the usage of a couple of sensors of varying bandwidths to collect records throughout the complete electromagnetic spectrum. By using collecting data in dozens or maybe masses of spectral bands, hyper spectral imaging allows for the extraction of a mess of particular characteristics, making an allowance for extra precise analysis and insights. This technology lets in for stepped forward measurement and yields, permitting higher crop identity and classifications, in addition to stepped forward crop overall performance and yields. It is able to also potentially help to discover undesirable characteristics of a crop, such as disorder, nutrient deficiencies, or pest infestations. The analysis of hyper spectra also can be useful for assessing in-season stress elements, together with water deficiency, high temperatures, or competition with weeds. The use of hyper spectral imaging to research crops offers a huge range of potential packages, from monitoring growers’ fields to developing irrigation recommendation. By way of capitalizing on this effective new era, growers can gain extraordinary perception into crop health, permitting them to make informed decisions on how excellent to optimize their management techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： First Keyword Second Keyword Third Keyword

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Measuring the Impact of Flexible Communications Software Design in Network Applications 5th

Measuring the Impact of Flexible Communications Software Des...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Alam, Intekhab Prabhu, A. Yadav, Renu Pravinthraja, S. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electronic and Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

This study studies the impact of bendy communications software design on network applications. Through a case observation method, it looks at how a community protocol like HTTP may be redesigned while permitted to modify elements of the protocol to suit the characteristics of a disbursed system. It examines the impact of particular protocol modifications, consisting of retransmission strategies, on person and device performance and the general effects of protocol flexibility. Such flexibility enables networks to alter and scale without problems, allowing for more excellent, innovative, dependable community packages. The consequences of this research will assist in understanding how redesigning the communications software program can benefit both customers and network packages. The results endorse that a better-stage verbal exchange layer could offer first-rate upgrades in designing community programs and conversation protocols. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： HTTP

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${\sf GoCrowd}$GoCrowd: Obliviously Aggregating Crowd Wisdom With Quality Awareness in Crowdsourcing

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IEEE Transactions on Dependable and Secure computing 2024年第1期22卷 710-722页

作者： Xiaoning Liu Yifeng Zheng Xingliang Yuan Xun Yi School of Computing Technologies RMIT University Melbourne VIC Australia School of Computer Science and Technology Harbin Institute of Technology Shenzhen Guangdong China School of Computing and Information Systems University of Melbourne Melbourne VIC Australia

Organizations these days capitalize on crowdsourcing to learn collective wisdom from a population of individuals. Vast amounts of data have been gathered, making the crowdsourcing platforms a lucrative target to steal data from and thus raising severe privacy concerns. Data contributed by workers may carry sensitive individual information. Meanwhile, organizations deem the aggregate statistics as intellectual property. In this paper, we propose, design, and evaluate GoCrowd, a system framework for obliviously aggregating wisdom with quality assurance in crowdsourcing. At its core, we propose constructions for two procedures. The starting point is a gold-standard based private worker quality control procedure that provides privacy-friendly worker quality assurance under the widely popular gold-standard mechanism. The subsequent procedure is an oblivious wisdom aggregation procedure that obliviously learns aggregate statistics over workers’ data while considering their quality. We securely realize these procedures with only lightweight secret sharing techniques. Our system is utterly oblivious to the service provider, and ensures that only the requester can learn the aggregate quality-aware statistics but nothing more. Extensive evaluations show that GoCrowd can produce quality statistics over data from 500 workers for 200 16-choice questions within 1 s.

关键词： Crowdsourcing Cryptography Quality control Servers Task analysis Aggregates Data privacy

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Dependence of thermodynamic quantities at freeze-out on pseudorapidity and collision energy in p-p collisions at LHC energies

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Chinese Physics C 2024年第10期48卷 235-246页

作者： Murad Badshah Yahia A.H.Obaidat Haifa I.Alrebdi M.Waqas Muhammad Ajaz Refka Ghodhbani Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan Department of Physics College of ScienceUniversity of BishaBisha 61922Saudi Arabia Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia School of Mathematics Physics and Optoelectronic EngineeringHubei University of Automotive TechnologyShiyan 442002China Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafhaSaudi Arabia

The transverse momentum distributions of charged hadrons produced in proton-proton collisions at center-of-mass energies(√s)of 0.9 TeV and 2.36 TeV,as measured by the CMS detector at the Large Hadron Collider(LHC),have been analyzed within various pseudorapidity classes utilizing the thermodynamically consistent Tsallis *** fitting procedure resulted in the key parameters,namely,effective temperature(T),non-extensivity parameter(q),and kinetic freezeout volume(V).Additionally,the mean transverse momentum()and initial temperature(T_(i))of the particle source are determined through the fit function and string percolation method,*** alternative method is employed to calculate the kinetic freezeout temperature(T_(0))and transverse flow velocity(β_(T))from ***,thermodynamic quantities at the freezeout,including energy density(ε),particle density(n),entropy density(s),pressure(P),and squared speed of sound(C_(s)^(2)),are computed using the extracted T and *** is also observed that,with a decrease in pseudorapidity,all thermodynamic quantities except V and q *** trend is attributed to greater energy transfer along the mid pseudorapidity.q increases towards higher values of pseudorapidity,indicating that particles close to the beam axis are far from ***,V remains nearly independent of *** excitation function of these parameters(q)shows a direct(inverse)correlation with collision *** ε,n,s,and P show a strong dependence on collision energies at low *** verification of the thermodynamic inequality ε≥3P suggests the formation of a highly dense droplet-like Quark-Gluon Plasma(QGP).Additionally,the inequality T_(i)>T>T_(0)is explicitly confirmed,aligning with the evolution of the produced fireball.

关键词： charged hadrons tsallis statistics effective temperature non-extensivity parameter pseudorapidity kinetic freeze-out stage multiple freeze-out scenario QGP QCD matter squared speed of sound

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Deep Fake Image Classification Engine Using Inception-ResNet-V1 Network 1

Deep Fake Image Classification Engine Using Inception-ResNet...

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1st IEEE International Conference on computing and Data science, ICCDS 2024

作者： Kothandaraman, D. Narayanan, S. Sankara Mohamed Iqbal, M. Yekopalli, Ayesha Sri Krishnadevarayalu, S. School of Computer Science & Engineering VIT-AP University Andhra Pradesh Amaravati India SRM Institute of Science and Technology Department of Computing Technology Chennai India Sri Sivasubramaniya Nadar College of Engineering Department of Information Technology Tamilnadu Chennai India School of Electronics & Communication Engineering G. Pulla Reddy Engineering College GPREC AP Kurnool India

ISBN: (纸本)9798350365337

The goal of this project is to develop a real or fake facial image classification system using deep learning techniques. The main focus is on the InceptionResnetVl model pretrained on the VGGFace2 dataset and Kaggle DeepFake Classification Dataset for face classification. The application uses the facenet_pytorch library to perform face detection and preprocessing. Main features of the project include predicting the authenticity of a given facial image as either "real"or "fake". This is achieved by implementing the InceptionResnetVl model, which is fine-tuned for binary classification with a single output representing the probability of authenticity. The system is designed to run on the GPU when available, enabling faster computing. Grad-CAM (gradient-weighted class activation mapping) technique is used to ensure the explainability of classification decisions. This method creates class activation maps that visually highlight the regions of the input image that influenced the classification decision. The Grad-CAM printout is then superimposed on the original facial image, creating an interpretable visualization of the model's decision-making process. The Gradio user interface is used for the interactive presentation of the project. Users can upload their face and get real vs. false predictions and visual explanations generated by the Grad-CAM algorithm. The user interface also displays a confidence score for each forecast, giving users an idea of how reliable the model is. In general, this project provides a comprehensive system to classify real and fake faces, and the proposed method reaches the accuracy of 97% both in training and testing. © 2024 IEEE.

关键词： User interfaces

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