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Measurement-Based Channel Characterization in a Large Hall Scenario at 300 GHz

China Communications 2023年第4期20卷 118-131页

作者： Yejian Lyu Zhiqiang Yuan Huaqiang Gao Qiuming Zhu Xiang Zhang Wei Fan Deparment of Electronic Systems Aalborg UniversityAalborgØst 9220Denmark Beijing University of Posts and Telecommunications Beijing 100876China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space College of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China China Academy of Information and Telecommunications Technology(CAICT) Beijing 100191China Center for Wireless Communication-Radio Technology(CWC-RT) Oulu UniversityOulu 90570Finland

Sub-terahertz(Sub-THz),defined as the frequency bands in 100-300 GHz,is promising for future generation communications and sensing *** channel measurement and modeling are essential for development and performance evaluation of the future communication *** channel modeling relies on realistic channel data,which should be collected by high-fidelity channel *** paper presents the measurement-based channel characterization in a large indoor scenario at 299-301 *** firstly review the state-of-the-art channel measurements at sub-THz frequency *** then presented a VNA-based channel sounder for long-range measurements,which uses the radio-overfiber *** measurements using this channel sounder are conducted in a large hall *** on the measurement data,we calculated and analyzed key propagation channel parameters,e.g.,path loss,delay spread,and angular *** results are also analyzed both in the line-of-sight(Lo S)and noneLo S(NLo S)*** large delay components in the measurements demonstrate the possibility of the longrange channel measurement campaign at 300 GHz.

关键词： channel measurement sub-terahertz 300 GHz channel characterization

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A Supervised Method Base on Multi Labels for Vehicle Re-identification 3

A Supervised Method Base on Multi Labels for Vehicle Re-iden...

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3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Zhu, Jingmiao Deng, Shizhuo Chen, Dongyue College of Information Science and Engineering Northeastern University Liaoning Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Liaoning Shenyang110819 China Ministry of Education Liaoning Shenyang110819 China

ISBN: (纸本)9781510664814

With the rise of smart city construction, the importance of vehicle re-identification based on video surveillance has become increasingly prominent. The task of vehicle re-identification mainly focuses on recognizing the same vehicle image under different cameras. In this paper, we propose a multi-label fusion framework for vehicle re-identification based on VIT network. We design a method of anti-angle distortion data augmentation to solve the problem that the performance of VIT is limited by the relative position relationship inside the vehicle structure and the angle deviation caused by the different relative positions of camera and vehicle. At the same time, the key position weight information module is inserted into the coding layer to improve the network's attention to key information. Finally, in view of the insufficient use of the location information between patches in the VIT network, we design a location code based on the Minkowski distance metric to add the relative location relationships within the vehicle individuals to the network. The experiment shows that under the same conditions, our vehicle weight recognition system is superior to most of the more advanced work in vehicle-ID and VERI776 datasets compared with the most advanced supervised vehicle weight recognition work. © 2023 SPIE.

关键词： Cameras

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SG-RoadSeg: End-to-End Collision-Free Space Detection Sharing Encoder Representations Jointly Learned via Unsupervised Deep Stereo

SG-RoadSeg: End-to-End Collision-Free Space Detection Sharin...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhiyuan Wu Jiaqi Li Yi Feng Chengju Liu Wei Ye Qijun Chen Rui Fan College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai P. R. China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Collision-free space detection is of utmost importance for autonomous robot perception and navigation. State-of-the-art (SoTA) approaches generally extract features from RGB images and an additional source or modality of 3-D information, such as depth or disparity images, using a pair of independent encoders. The extracted features are subsequently fused and decoded to yield semantic predictions of collision-free spaces. Such feature-fusion approaches become infeasible in scenarios, where the sensor for 3-D information acquisition is unavailable, or just when multi-sensor calibration falls short of the necessary precision. To overcome these limitations, this paper introduces a novel end-to-end collision-free space detection network, referred to as SG-RoadSeg, built upon our previous work SNE-RoadSeg. A key contribution of this paper is a strategy for sharing encoder representations that are co-learned through both semantic segmentation and unsupervised stereo matching tasks, enabling the features extracted from RGB images to contain both semantic and spatial geometric information. The unsupervised deep stereo serves as an auxiliary functionality, capable of generating accurate disparity maps that can be used by other perception tasks that require depth-related data. Comprehensive experimental results on the KITTI road and semantics datasets validate the effectiveness of our proposed architecture and encoder representation sharing strategy. SG-RoadSeg also demonstrates superior performance than other SoTA collision-free space detection approaches. Our source code, demo video, and supplement are publicly available at ***/SG-RoadSeg.

关键词： Accuracy Semantic segmentation Semantics Computer architecture Feature extraction Robot sensing systems Data mining

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An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks

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Alexandria engineering Journal 2024年 91卷 249-260页

作者： Hosseinzadeh, Mehdi Ali, Saqib Mohammed, Adil Hussein Lansky, Jan Mildeova, Stanislava Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Hassan Ahmed, Omed Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Computer Science and Mathematics Faculty of Economic Studies University of Finance and Administration Prague Czech Republic Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si13120 Korea Republic of

Flying ad hoc networks (FANETs) tackle diverse challenges, for example, dynamic topological structure, high mobility of nodes, low density, and energy restrictions. These challenges make problems in designing reliable and stable routing in FANETs. Hence, the design of a routing algorithm is essential for transferring data between drones. In this paper, an energy-aware routing scheme based on a virtual relay tunnel (EARVRT) is proposed in flying ad hoc networks. EARVRT includes a virtual relay tunnel (VRT) that manages relay nodes in the route discovery process and lowers network overhead. Moreover, three metrics, namely route energy, hop counts, and a new metric called path correlation are regarded in the path selection operation. Note that correlation is defined with regard to two scales, including the cosine similarity of two nodes and their distance. EARVRT is evaluated according to delay, network longevity, consumed energy, and packet delivery rate. Then, our scheme is compared with three methods, namely LoCaL, O-LAR, and PSO-GLFR. These results show the superiority and success of EARVRT in comparison with other algorithms. © 2024 The Author(s)

关键词： Drones

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A Multi-Carrier Deep Learning CSK Communication System

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IEEE Communications Letters 2025年第6期29卷 1191-1195页

作者： Mobini, Majid Kaddoum, Georges Herceg, Marijan Babol Noshirvani University of Technology Department of ECE Babol Iran University of Québec École de technologie supérieure Département de génie électrique MontréalQC Canada Lebanese American University Cyber Security Systems and Applied AI Research Center Beirut Lebanon University of Osijek Faculty of Electrical EngineeringComputer Science and Information Technology Department of Communications Croatia

A new Multi-Carrier Deep Learning Chaos Shift Keying (MC-DLCSK) modulation is designed in this paper. The proposed receiver includes a Neural Network (NN)-based classifier that recovers MC-DLCSK signals. The results demonstrate that the MC-DLCSK system achieves a considerable Bit Error Rate (BER) gain compared to all existing similar systems under both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. © 1997-2012 IEEE.

关键词： White noise

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Improved SocialVAE: A Socially-Aware Ship Trajectory Prediction Method for Port Operations 2

Improved SocialVAE: A Socially-Aware Ship Trajectory Predict...

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2nd International Conference on Machine Learning, Cloud Computing, and Intelligent Mining, MLCCIM 2023

作者： Gao, Wei Liu, Jin Zhi, Jiamao Wang, Junxiang College of Information Engineering Shanghai Maritime University Shanghai China China Shipping Telecommunication Co. Ltd. Shanghai Ship and Shipping Research Institute Shanghai China COSCO SHIPPING TECHNOLOGY Co. Ltd National Engineering Research Center of Ship Transportation Control Systems Shanghai China

ISBN: (纸本)9798350328530

In comparison to other regions, the traffic dynamics observed in port waters are more unclear. Given the complexity of maneuvering in multi-vessel encounter scenarios, accurate prediction of vessel trajectories in port waters is crucial for preventing accidents and improving port operations. To address the highly dynamic navigational environment and the uncertainty of navigational patterns such as heading and path selection, we propose an improved SocialV Ae(Variational Autoencoder) method. The approach use local ship observations to comprehend traffic patterns between ships in order to make ship navigation decisions. Furthermore, we present a socially aware regression module that evaluates the compatibility between past trajectory interaction codes and forecast trajectories, and then uses the resulting offsets to adjust the predicted trajectories. Additionally, for the problem of non-random missing data in port waters AIS (Automatic Identification System) data, we use a shift-corrected data interpolation method to fill in the missing values. We utilize two real AIS datasets of waterways surrounding ports to test the efficacy of our method: Copenhagen Port and Shanghai Yangshan Port. When compared to existing methods, our Improved SocialV Aedelivers excellent prediction performance on these two datasets. © 2023 IEEE.

关键词： Trajectories

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Quantifying Collective Emotions: Japan’s Societal Trends Through Enhanced Sentiment Index Using POMS2 and SNS

arXiv

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arXiv 2025年

作者： Tamura, Koutarou Sano, Yukie Shiozaki, Junichi Center for Strategic Management & Innovation Nomura Research Institute Ltd. Tokyo Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Japan

In this study, we constructed an emotion index that quantitatively represents the collective emotions present in the Japanese web space by utilizing Social Networking Service (SNS) post data. Building upon previous research that used blog data and the Profile of Mood States (POMS), we restructured the methodology using posts from X (formerly Twitter) and updated the model by adding the "Friendliness" indicator from the POMS2 metrics. Through periodic and trend analyses of the emotional indicators derived from X’s post data, we found that the extension is consistent with results previously reported using blog data. This suggests that our methodology effectively captures typical emotional fluctuations in Japanese society, independent of specific SNS platforms, and is expected to serve as an index to visualize societal trends. Copyright © 2025, The Authors. All rights reserved.

关键词： Tweets

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Build-It-Here: Utilizing 2D Inpainting Models for On-Site 3D Object Generation

Build-It-Here: Utilizing 2D Inpainting Models for On-Site 3D...

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International Conference on Computational Intelligence and Applications (ICCIA)

作者： Zhennan Wu Hiroyuki Sato Graduate School of Engineering The University of Tokyo Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Japan Tokyo Japan

ISBN: (数字)9798350352214

ISBN: (纸本)9798350352221

Significant progress has been made in both 2D and 3D content creation recently. In order to integrate the advantages of both, we present Build-it-here, a novel 3D generation method for open vocabulary furniture creation and placing inside empty rooms. By modulating textual input, we achieve few-shot prompting large language models for layout planning. The output room layout is represented by bounding boxes in the empty house. Upon sampling camera view around bounding-box for rendering, we perform text-guided inpainting on masked 2D images. The inpainted object is then reconstructed in 3D and back projected to the room. Qualitative experiments have demonstrated that our method not only achieved open vocabulary diversity but also ensuring the rationality of placements. The scenes generated through this method is photo-realistic and ready for applications like game industry asset usage.

关键词： Industries Vocabulary Solid modeling Three-dimensional displays Large language models Layout Games Rendering (computer graphics) Planning Image reconstruction

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Bidirectional Polarization-Multiplexing Fiber Laser Enabling Tunable-Repetition-Rate Dual Combs

Bidirectional Polarization-Multiplexing Fiber Laser Enabling...

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Optoelectronics Global Conference (OGC)

作者： Bowen Liu Maolin Dai Takuma Shirahata Shinji Yamashita Sze Yun Set Department of Electrical Engineering and Information Systems Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan

Ultrafast laser is an ideal playground for the study of precise spectroscopy and microscopy that heavily rely on the high-performance optical frequency combs, which is the unique nature of mode-locked fiber lasers. In particular, dual-comb fiber lasers can greatly improve system performance while reducing complexity by developing self-referencing combs and coupling pulse trains with different repetition rates. Whereas the repetition rate is generally determined for a certain lasing resonator, which creates additional constraints in dual-comb applications. Here, we developed a bidirectional polarization-maintaining fiber laser, where the repetition rate of mode-locked pulse trains can be tuned continuously inside the cavity. The proposed laser outputs mutually orthogonal polarization states in opposite directions, and the maximum tuning range of the repetition rate reaches 681.6 kHz. Compared with referencing CW loop, the RF difference reaches 978.2 kHz, almost equal to 1 MHz. Meanwhile, the two directions generate pulses with nearly the same central wavelength, enabling excellent capacity in self-referencing dual-comb generation. This tunable-repetition-rate dual-comb source is promising for two-photon fluorescence microscopy, precise metrology of wavelength and synchronization of other combs based on fiber lasers with different repetition rate, etc.

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Robust Indoor Localization and Map Matching Algorithm with Visual SLAM

Robust Indoor Localization and Map Matching Algorithm with V...

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2023 China Automation Congress, CAC 2023

作者： Wang, Zhebin Xue, Zhenfeng Xie, Siyi Zhang, Xiongtao Liu, Yong School of Information Engineering Huzhou University Huzhou313000 China Huzhou Institute of Zhejiang University Intelligent Perception and Control Center Huzhou313098 China Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China College of Mechanical and Automotive Engineering Xiamen University of Technology Xiamen361000 China

ISBN: (纸本)9798350303759

With the rapid development of intelligent robotic technology, global positioning and localization algorithm is attracting much more attention in recent years, especially for unknown indoor environments. In such case, global positioning system (GPS) will lose its effect, and relative positioning systems become more important, including UWB, IMU and VIO, which exist drift phenomenon with time. In this paper, we propose a novel global localization and map matching algorithm suitable for indoor and outdoor unseen environments. Its core algorithm is based on visual SLAM to generate the sparse map point cloud as well as historical trajectory path. After simply annotating the site drawings, a two-dimensional semantic map of the environment can be obtained. Then the point cloud and trajectory path are matched with the semantic map through a global search algorithm. Finally, the global localization in unknown environment can be easily achieved and the historical trajectory path can be displayed accurately on the site drawing. Real-world experiment shows the effectiveness and robustness of the method. © 2023 IEEE.

关键词： Trajectories

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