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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Gao, Jiannan Wang, Yigao Jiang, Zhihan Zhu, Hang Zhong, Qiyue Fan, Xiaoliang Chen, Longbiao Wang, Cheng Xiamen University Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen China The University of Hong Kong Faculty of Engineering Department of Electrical and Electronic Engineering Hong Kong

ISBN: (纸本)9798350346558

Traffic accidents, like rear-end collisions and vehicle-to-pedestrian accidents, bringing serious threats to traffic management and people's lives and property. Existing methods rely on historical traffic accident data and are not suitable for expanding cities. Against this background, we propose a framework to infer urban traffic accident hotspots by vehicle trajectory data and heterogeneous data. Firstly, we extract parking events from vehicle trajectories leveraging a map matching algorithm and obtain the parking hotspots under different weather and time periods by semantic segmentation and clustering. Secondly, we extract three sets of contextual features of parking hotspots, i.e., road names, POIs, and traffic flow. Finally, leveraging a graphical convolutional network, we build a model to infer whether a parking hotspot is a traffic accident hotspot based on contextual features. We evaluate our model leveraging real datasets in Xiamen. Results prove that our model accurately infers traffic accident hotspots in Xiamen with F1-Score of 0.794. © 2022 IEEE.

关键词： Trajectories

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SAM struggles in concealed scenes—empirical study on “Segment Anything”

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Science China(Information Sciences) 2023年第12期66卷 278-280页

作者： Ge-Peng JI Deng-Ping FAN Peng XU Bowen ZHOU Ming-Ming CHENG Luc VAN GOOL School of Computing Australian National University Computer Vision Lab(CVL) ETH Zurich Department of Electronic Engineering Tsinghua University College of Computer Science Nankai University

Large models open up new opportunities for artificial intelligence. In the past few months, there has been a boom in training foundation models on the vast linguistic corpus to produce amazing applications, e.g., Chat GPT, *** natural language processing and multimodal learning communities have been revolutionized. Large models' capacity for generalization and emergent makes it easy for users to believe that large models can solve anything.

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EMF Compliance Distance Calculation Enhancement for Multi-Technology Mobile Site 3

EMF Compliance Distance Calculation Enhancement for Multi-Te...

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3rd IEEE International Conference on Signal, Control and Communication, SCC 2023

作者： Elbasheir, Mohammed S. Saeed, Rashid A. Edam, Salaheldin Khalifa, Othman Odeh, Nidhal Ahmed, Zeinab E. School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan Taif University Department of Computer Engineering College of Computers and It Taif Saudi Arabia Intl. Islamic University Malaysia Dept. of Elect & Electronics Eng. Kuala Lumpur Malaysia Libyan Centre of Eng. Research & Information Bani Waleed Libya School of Electrical Computer Telecommunication Engineering University of Wollongong Wollongong Australia International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350326390

Mobile networks are growing rapidly, particularly in light of the advent of the 5G New Radio (NR). This growth requires installing more base stations (BSs) that increase overall electromagnetic field (EMF) emission. The International Commission on Non-Ionizing Radiation Protection (ICNIRP) has set maximum limits to control EMF levels. This paper studies the compliance boundary for a single site running with multiple technologies including the 2G/3G/4G/5G colocated in the same tower. An enhanced formula is proposed and used with a typical site configuration setup for the boundary calculations in the form of Compliance Distance (CD). Also, the study investigated the CD for the Macro site that is commonly used in live networks. Additionally, this paper investigated the power density (PD) and total exposure ratio (TER) for occupational workers (OW) and the general public (GP) at the site. The results show that the enhanced formula gives shorter CD distances when the power reduction factor is considered, and 5G has the highest contribution to TER. © 2023 IEEE.

关键词： Electromagnetic fields

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Privacy-Preserving Data Evaluation via Functional Encryption, Revisited

Privacy-Preserving Data Evaluation via Functional Encryption...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Xinyuan Qian Hongwei Li Guowen Xu Haoyong Wang Tianwei Zhang Xianhao Chen Yuguang Fang School of Computer Science and Engineering University of Electronic Science and Technology of China Department of Computer Science City University of Hong Kong Chongqing Key Laboratory of Automated Reasoning and Cognition School of Computer Science and Engineering Nanyang Technological University Department of Electrical and Electronic Engineering University of Hong Kong

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

In cloud-based data marketplaces, the cardinal objective lies in facilitating interactions between data shoppers and sellers. This engagement allows shoppers to augment their internal datasets with external data, consequently leading to significant enhancements in their machine learning models. Nonetheless, given the potential diversity of data values, it becomes critical for consumers to assess the value of data before cementing any transactions. Recently, Song et al. introduced Primal (publish in ACSAC), the pioneering cloud-assisted privacy-preserving data evaluation (PPDE) strategy. This strategy relies on variants of functional encryption (FE) as the underlying framework, conferring notable performance advantages over alternative cryptographic primitives such as secure multi-party computation and homomorphic encryption. However, in this paper, we regretfully highlight that Primal is susceptible to inadvertent misuse of FE, and leaves much-desired room for performance amelioration. To combat this, we introduce a novel cryptographic primitive known as labeled function-hiding inner-product encrypted. This new primitive serves as a remedy and forms the foundation for designing the concrete framework for PPDE. Furthermore, experiments conducted on real datasets demonstrate that our framework significantly reduces the overall computation cost of the current state-of-the-art secure PPDE scheme by roughly 10× and the communication cost for the data seller by about 2×.

关键词： Costs Scalability Cement industry Machine learning Benchmark testing Iron Multi-party computation

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

Land Cover Classification for Polarimetric SAR Images Based ...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

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

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

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.

关键词： Tensors Correlation Disasters Diversity reception Land surface Dynamic range Feature extraction Radar polarimetry Data mining Matrix decomposition

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Neuro-OSVETA: A Robust Watermarking of 3D Meshes

arXiv

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arXiv 2023年

作者： Vasic, Bata Raveendran, Nithin Vasic, Bane Electronic Department Faculty of Electronic Engineering University of Nis Serbia Electrical and Computer Engineering Department University of Arizona Tucson United States

Best and practical watermarking schemes for copyright protection of 3D meshes are required to be blind and robust to attacks and errors. In this paper, we present the latest developments in 3D blind watermarking with a special emphasis on our Ordered Statistics Vertex Extraction and Tracing Algorithm (OSVETA) algorithm and its improvements. OSVETA is based on a combination of quantization index modulation (QIM) and error correction coding using novel ways for judicial selection of mesh vertices which are stable under mesh simplification, and the technique we propose in this paper offers a systematic method for vertex selection based on neural networks replacing a heuristic approach in the OSVETA. The Neuro-OSVETA enables a more precise mesh geometry estimation and better curvature and topological feature estimation. These enhancements result in a more accurate identification of stable vertices resulting in significant reduction of deletion probability. © 2023, CC BY-NC-SA.

关键词： Mesh generation

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Robust Quadratic Optimal Control of Linear Systems with Ellipsoid-Set Learning

Robust Quadratic Optimal Control of Linear Systems with Elli...

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European Control Conference (ECC)

作者： Xuehui Mal Yutong Chen Shiliang Zhang Yushuai Li Fucai Qian Zhiyong Sun School of Automation and Information Engineering Xi'an University of Technology Xi'an China Department of Electronic Engineering Tsinghua University Beijing China Department of Informatics University of Oslo Oslo Norway Department of Computer Science Aalborg University Aalborg Denmark Department of Electrical Engineering Eind-hoven University of Technology Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Despite the celebrated success of linear quadratic Gaussian control (LQG) for stochastic systems, LQG approaches are inefficient in handling systems with non-Gaussian noises. This paper is concerned with linear quadratic control of discrete-time systems with bounded noises and unobservable system states. We describe such noises and system states by ellipsoidal sets, enabling the establishment of boundaries for those uncertainties in the control. Further, we learn and update the ellipsoidal sets for the system states by an ellipsoidal set-membership filter. With the learned ellipsoidal sets, we derive a robust state-feedback optimal control law by solving a rendered semidefinite programming problem. Simulation results demonstrate the enhanced control performance by the proposed method.

关键词： Robust control Linear systems Discrete-time systems Semidefinite programming Uncertainty Stochastic systems Simulation

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Customized toolbox in VR Design 22

Customized toolbox in VR Design

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Proceedings of the 26th Pan-Hellenic Conference on informatics

作者： Georgia Drampalou Nikolaos Kourniatis Ioannis Voyiatzis Department of Informatics and Computer Engineering University of West Attica Greece Department of Civil Engineering University of West Attica Greece

ISBN: (纸本)9781450398541

Designing in an environment of Virtual Reality is a field that gains ground. Although more and more applications are constantly released, the majority of designers have not yet been introduced into Virtual Reality. A widely used tool for designing is Rhino which has been released by McNeel and Rhino Developer encourages the users to create plug-ins for custom use of the software. In parallel, Meta's developing tools offer their users the chance to customize their own applications. Towards the direction of Virtual Reality integration, both have already released new products for their users. RhinoVR is an open source plug-in for Rhino, while at the same time Meta provides Oculus hardware and platform solutions for users to turn their concept into reality. What is yet to be developed is a model that encourages the customization of a VR design platform, focusing mainly on developing a personalized toolbox for designing.

关键词： plug-in SDK Rhino Developer Oculus Quest 2 VR Design OpenVR API

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Multimodal Rumor Detection via Multimodal Prompt Learning

Multimodal Rumor Detection via Multimodal Prompt Learning

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International Joint Conference on Neural Networks (IJCNN)

作者： Fan Chen Xiuhong Li Zhe Li Chenyu Zhou Jiabao Sheng School of Computer Science and Technology Xinjiang University Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Department of Electrical Engineering Stanford University Department of Health Technology and Informatics The Hong Kong Polytechnic University Department of Radiation Oncology Stanford University

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Pre-trained vision-language (V-L) models exhibit significant generalization capabilities in detecting rumors. However, their reliance on single-modality prompts—either language or vision—limits their flexibility for dynamic adjustments in both representation spaces during rumor detection. To address these limitations, we propose a multimodal rumor detection framework that uses prompt learning in both the vision and language domains to align their representations better. Inspired by recent advances in efficiently tuning large language models, we introduce a set of trainable parameters in the input space, keeping the model backbone frozen. Additionally, we use distinct prompts at various early stages, which helps progressively model the relationships between features, enhancing comprehensive context learning. Extensive experiments with two real-world multimodal datasets demonstrate our framework’s superior ability to distinguish rumors from facts.

关键词： Accuracy Large language models Neural networks Tuning Context modeling

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Automating Object Sorting by Color with a Robotic Arm and Conveyor Belt System

Automating Object Sorting by Color with a Robotic Arm and Co...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Faisal Aziz Punam Bhattacharjee Mrinmoy Modak Md. Sanaul Rabbi Department of Mechanical Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh Department of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh Department of Electrical and Computer Engineering University of Hawaiʻi at Mānoa Honolulu Hawaii USA

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

This paper focuses on two main aspects in industrial production: material handling and material sorting. The aim was to design and fabricate a mechatronic device that is able to sort different objects in a specific order based on their appearance. First, a conveyor belt does the material handling. The control unit will get specific sensor values for different colored objects. The robotic arm will then pick and place the object in a certain angular position and sort them out. Nowadays, robotic arms are very common in almost all kinds of industries. But most of the arms can only perform some predetermined kinematic action. In this work, the robotic arm will be able to make its decision based upon the color of the object and place them in different final positions. This technology can be used in a variety of sectors, such as food processing, waste handling, raw material handling, object sorting, packaging, etc. This can greatly minimize human efforts, manufacture time, and hence the production cost.

关键词： Industries Service robots Materials handling Color Inspection Manipulators Belts Robot sensing systems Servomotors Sorting

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