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CurricularVPR: Curricular Contrastive Loss for Visual Place Recognition

CurricularVPR: Curricular Contrastive Loss for Visual Place ...

引用

2024 IEEE/RSJ international conference on Intelligent Robots and Systems, IROS 2024

作者： Zhang, Dongshuo Chen, Nanhua Wu, Meiqing Lam, Siew-Kei Nanyang Technological University College of Computing and Data Science 50 Nanyang Ave 639798 Singapore Beijing Institute of Technology School of Aerospace Engineering Beijing100081 China

ISBN: (纸本)9798350377705

Visual Place Recognition (VPR) techniques commonly utilize Contrastive Losses (CL) to train models that generate compact and discriminative global descriptors for images. These models often result in poor performance due to one of the following reasons during training: 1) loss functions that focus primarily on easier samples, 2) reliance on time-consuming hard sample mining methods to identify informative supervisory samples, which hinders effective learning from large-scale datasets. To enhance both learning efficiency and effectiveness, we propose a Curricular Contrastive Loss (CCL) and use graded similarity labels as a measure of sample difficulty. Inspired by human learning that begin with easier concepts and progressively tackle more challenging ones, our CCL dynamically emphasizes easier samples during the initial training stages to achieve rapid convergence. The learning gradually focuses on harder samples in later training stages to bolster robustness of the models under challenging conditions. Our proposed method has been extensively evaluated on popular datasets, and the results demonstrate its superior performance compared to the CL and Generalized CL functions. © 2024 IEEE.

关键词： Contrastive Learning

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Safe Route Recommendation based on Crime Risk Prediction with Urban and Crime Data 9

Safe Route Recommendation based on Crime Risk Prediction wit...

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9th IEEE international conference on Big Data computing Service and Applications, BigDataService 2023

作者： Kim, Daye Baek, Juwon Yang, Jihu Roh, Hyun Jeong, Heewon Ruiz, Bryanna Lee, Minji Matson, Eric T. Kyung Hee University Software Convergence Yongin Korea Republic of Handong Global University Computer Science and Electrical Engineering Pohang Korea Republic of Chungbuk National University Computer Engineering Cheongju Korea Republic of Purdue University Computer and Information Technology West LafayetteIN United States Purdue University Technology West LafayetteIN United States

ISBN: (纸本)9798350333794

Public safety is an escalating concern in the United States, given the rising crime rates. However, existing research paper on recommending safe routes often overlooks crucial factors essential for assessing road risk. In contrast to prior studies, this study introduces an innovative approach that recommends safe routes based on road risk prediction. By employing Gaussian Kernel Density Estimation, the study estimates the densities of crime and urban data for each coordinate in Chicago while considering the severity of crimes. These estimated densities are then utilized to predict future crime density using a machine learning model. The predicted crime density is assigned to each node and edge of the Chicago graph map, serving as an indicator of road risk. Four types of weighted graphs are generated by combining road risk and road length in different ratios, which are subsequently applied in the Dijkstra shortest path algorithm. The proposed application of this study is expected to decrease the likelihood of crime incidents, thereby fostering a safer environment. Furthermore, the results analyzed in this paper can serve as valuable reference material for community safety initiatives. © 2023 IEEE.

关键词： Crime

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Efficient Federated Learning with Cost-Adjustable Generative AI over Heterogeneous Edge Devices 20th

Efficient Federated Learning with Cost-Adjustable Generativ...

引用

20th IFIP WG 10.3 international conference on Network and Parallel computing, NPC 2024

作者： Zhang, Hanwen Li, Peichun Kang, Jiawen Qian, Liping Wu, Yuan Niyato, Dusit State Key Laboratory of Internet of Things for Smart City University of Macau China School of Automation Guangdong University of Technology Guangzhou China College of Information Engineering Zhejiang University of Technology Hangzhou China Zhuhai UM Science and Technology Research Institute Zhuhai China Nanyang Technological University Block N4-02a-32 Nanyang Avenue Singapore Singapore

ISBN: (纸本)9789819628636

Federated learning (FL) on edge devices often faces critical challenges, such as slow convergence rates and suboptimal performance, largely attributed to limited local data availability and data heterogeneity across participating devices. Recent advancements in generative artificial intelligence (AI) have demonstrated exceptional proficiency in synthesizing realistic data, offering potential solutions to these issues. In this paper, we present an innovative approach that enables edge devices to enhance their datasets by leveraging generative AI models. Recognizing varying resource capacities among edge devices, we propose a flexible data synthesis strategy, allowing each device to customize the quantity and quality of generated data according to its specific resource conditions and operational requirements. Building on this strategy, we formulate an optimization problem to maximize training accuracy while meeting the local resource constraints and task completion timelines. Experimental results reveal that our model can effectively enhance global accuracy compared to conventional FL algorithms, with even more pronounced improvements observed under skewed data distributions. © IFIP international Federation for Information Processing 2025.

关键词： Federated learning

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Protocol-based Security Mechanism for Satellite Networks 3

Protocol-based Security Mechanism for Satellite Networks

引用

3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Srivastava, Arun Pratap Pokhariya, Hemant Singh Shrivastava, Anurag Kumar, Yogendra Singh, Surendra Ranjan, Abhijeet Lloyd Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida201308 India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Gla University Department of Electrical Engineering Mathura India Quantum University Uttarakhand Roorkee India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350322842

A completely linked world with sixth generation (6G) networks is anticipated as a result of the convergence of terrestrial radio and satellite communications. Satellite physical restrictions on the amount of available power and space results in low computing power, constrained storage capacity, and compromised security. Data may therefore be susceptible to modification and contamination by others. Security concerns have arisen as satellite communications have become increasingly important to international communications networks. In satellite networks, it can be difficult to efficiently use storage and secure information access. With regard to satellite communication networks, this proposal suggests a privacy and authentication system based on QKD protocol. This is accomplished by implementing a wireless, heterogeneous network connectivity architecture that combines both open-source and commercially available devices. Registration, authentication, and revocation are the three processes that enable communication. Satellites transmit the gathered data to ground stations, which then record all significant parameters on the system's decentralized blockchain. All certificates from malicious nodes are removed from the blockchain by ground stations. It has been suggested for use with 6G networks in the future and beyond the Internet of Things, self-driving cars, and other quickly developing applications. Excellent security levels are provided by satellite-based blockchain and QKD systems. © 2023 IEEE.

关键词： Satellites

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Human-Led Robotic Transportation of Elastic Objects with Adaptive Control 9

Human-Led Robotic Transportation of Elastic Objects with Ada...

引用

9th international conference on Robotics and Automation Engineering, ICRAE 2024

作者： Cui, Zhenxi Lai, Jiewen Lu, Bo Guo, Yi Chu, Henry K. University of West London School of Computing and Engineering London United Kingdom Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Soochow University School of Mechanical and Electrical Engineering Suzhou China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States The Hong Kong Polytechnic University Department of Mechanical Engineering Hong Kong

ISBN: (纸本)9798331518301

The perception and transportation of soft objects are critical tasks in daily life, and recent sensor advancements enable robots to safely perform these tasks in human-shared environments. This study advances elastic linear object transportation by introducing a collaborative framework where a human leads, providing task-specific instructions to guide the robot. Unlike conventional methods focused on fixed object manipulation, our approach dynamically controls and converges feature points of the elastic object into desired configurations during transportation. We developed an online model estimation technique using a least-squares optimization algorithm, with an exponential forgetting mechanism to adaptively update the model under disturbances from sensors and human interaction. Validated in experiments with a 6-DOF robot and depth camera, our method demonstrated robustness across varied scenarios, achieving faster convergence and reduced positional fluctuation compared to conventional gradient descent approaches. © 2024 IEEE.

关键词： Adaptive control systems

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Traffic-Efficient Split computing Mechanism for Internet of Things

Traffic-Efficient Split Computing Mechanism for Internet of ...

引用

international conference on Information and Communication technology convergence (ICTC)

作者： Hojin Yeom Haneul Ko Sangheon Pack Department of Electronics and Information Convergence Engineering Kyung Hee University Yongin-si Korea School of Electrical Engineering Korea University Seoul Korea

In the split computing approach, channel coding can be exploited to transmit the intermediate data, balancing the tradeoff between accuracy and traffic overhead. In this paper, we propose a traffic-efficient split computing mechanism (TESC) in which the IoT device decides whether to exploit channel coding and its error correction capability according to the channel condition to transmit the intermediate data to the edge cloud. Evaluation results show that TESC can reduce the traffic overhead by over 80% while maintaining the accuracy of the model at a high level compared to the retransmission-based scheme.

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SimuPrint: A Printing Path Simulation Tool for Additive Manufacture 13

SimuPrint: A Printing Path Simulation Tool for Additive Manu...

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13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Sampedro, Gabriel Avelino Rachmawati, Syifa Maliah Ugli, Khurboev Shakhzodbek Dilshodbek Kim, Dong-Seong Lee, Jae-Min College of Computing and Information Technologies National University Manila Philippines Conception Co. Ltd. Gumi Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

With the rise of additive manufacturing, various methods for quick manufacturing are used to recreate tangible versions of objects modeled using computer-aided design (CAD) software. Additive manufacturing machines use fused deposition modeling and powder bed fusion in the development process. These devices take in Standard Tessellation Language (STL) files and convert them into a low-level language, Geometric Code (G-code), and list each step the printer would have to move to produce the tangible model. Often, the manufacturing process is done without the user visualizing how the process would take place. There is still a lack of a universal way to simulate how a machine would move to produce the object. This research aims to solve the gap by designing a system that simulates the additive manufacturing process. The system shall accept a G-code file and create a simulation of the development process. In testing the system, a match rate of 100% was seen in the recreation of various G-code files. Through this research, various opportunities shall be opened to explore improvements to the additive manufacturing process. © 2022 IEEE.

关键词： 3D printers

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Research on Tow Surface Defects Detection technology Based on YOLOv5 7

Research on Tow Surface Defects Detection Technology Based o...

引用

7th international conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Li, Zhuochen Liu, Xin Li, Min Bai, Hua Fu, Yutong Beijing Research Institute Of Machinery Industry Beijing China

ISBN: (纸本)9798350361445

In the process of tow manufacturing, due to the high consistency of the color and material of the tows, the traditional manual detection method often has the problem of missing detection and false detection. Aiming at defects in tow images, an improved YOLOv5 tow defect detection algorithm is proposed based on YOLOv5 algorithm. Firstly, ODConv dynamic convolution is used in the backbone network to refine the local feature mapping to achieve full extraction of local fine-grained features of the strands, and the convolution layers and BN layers are fused to reduce the number of network layers and improve the problem of reduced computing efficiency caused by the addition of dynamic convolution. Secondly, the Biformer attention mechanism is introduced into the Head structure to retain the fine-grained details of the detected object as much as possible. Next, in order to further improve the detection effect of small targets, a new bounding box similarity measure (Normalized Gaussian Wasserstein Distance, NWD) is introduced into the loss function to combine with the original IOU-Loss and improve the convergence speed. Finally, experiments are carried out on tow defect datasets to verify the performance of the improved model. The conclusion shows that although the number of parameters and calculation time of the improved model are increased, the detection effect of small target defects of the tow is improved, and the detection requirements of tow defects in the production process are better met, which provides a new method and idea for the research of tow detection in the field of deep learning. © 2024 IEEE.

关键词： Object detection

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Synthesis of Non-Integer Order Uncertain Thau-Luenberger Observer for Non-Integer Order Multiple Model with Unknown Inputs

Synthesis of Non-Integer Order Uncertain Thau-Luenberger Obs...

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2024 international conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Djeddi, Abdelghani Azar, Ahmad Taher Fekik, Arezki Kamal, Nashwa Ahmad Njima, Chakib Ben Echahid Cheikh Larbi Tebessi University Faculty of Sciences and Technology Tebessa12002 Algeria Prince Sultan University College of Computer & Information Sciences Riyadh11586 Saudi Arabia Riyadh Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Benha Egypt University Akli Mohand Oulhadj-Bouria Department of Electrical Engineering Rue Drissi Yahia Bouira 10000 Algeria Nantes Université École Centrale Nantes Cnrs LS2N Umr 6004 NantesF-44000 France Cairo University Faculty of Engineering Giza Egypt University of Sousse Tunisia

ISBN: (纸本)9798350361025

The present work introduces a novel method for state estimation of physical systems represented by an uncertain Non-Integer Order Multiple Model (NIO-MM) model with unknown inputs. The key concept underlying this approach involves formulating a non-integer order Thau-Luenberger Observer (NIO-TLO) designed specifically for the NIO-MM. This observer is developed to handle situations where both known and unknown inputs are subject to uncertainties, and the model itself incorporates bounded unknown inputs. The analysis of the convergence of the error of the state estimation is presented through the formulation of linear matrix inequalities (LMIs). To validate the proposed approach, an academic example is examined. © 2024 IEEE.

关键词： Linear matrix inequalities

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An Extended DeLone and McLean Model: A Systematic Literature Review of Citizens' E-Government and E-Participation on Social Media Platforms 7

An Extended DeLone and McLean Model: A Systematic Literature...

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7th international conference on Internet Applications, Protocols, and Services, NETAPPS 2024

作者： Haruna, Isyaku Uba Awang, Hapini Mansor, Nur Suhaili Ghazali, Osman Almashahdani, Abdulrazak F. Khamis, Shakiroh Institute for Advanced & Smart Digital Opportunities School of Computing Universiti Utara Malaysia Sintok Malaysia Faculty of Business Sohar University Sohar Oman Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Malaysia

ISBN: (纸本)9798331519513

This paper delves into the convergence of electronic government (E-Government) and citizen electronic participation (E-Participation) within the realm of social media platforms through a comprehensive systematic literature review (SLR). It focuses on understanding the determinants of citizen participation in digital government revolutions. The review covers studies from 2017 to 2023 in Scopus and Web of Science, finding 27 primary studies that highlight the current knowledge landscape and research gaps. By analyzing critical success factors, challenges, and opportunities, the study identifies key aspects shaping e-participation in the digital age. It suggests future research directions, policy implications, and strategies to improve citizen-government collaboration. Using the DeLone and McLean Model (D&M) and relevant theories, the study establishes a theoretical framework encompassing technological, personal, and organizational factors. This review significantly enhances understanding in e-government, information systems (IS), and citizen e-participation, benefiting researchers, policymakers, and practitioners. © 2024 IEEE.

关键词： citizens’ e-participation success D&M Model E-government initiatives social media

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