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Fundamental Limits of Two-Hop MIMO Channels: An Asymptotic Approach

IEEE Transactions on Information Theory 2025年第6期71卷 4069-4111页

作者： Zhuang, Zeyan Zhang, Xin Xu, Dongfang Song, Shenghui The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong The Hong Kong University of Science and Technology Division of Integrative Systems and Design Hong Kong

Multi-antenna relays and intelligent reflecting surfaces (IRSs) have been utilized to construct favorable channels to improve the performance of wireless systems. A common feature between relay systems and IRS-aided systems is the two-hop multiple-input multiple-output (MIMO) channel. As a result, the mutual information (MI) of two-hop MIMO channels has been widely investigated with very engaging results. However, a rigorous investigation on the fundamental limits of two-hop MIMO channels, i.e., the first and second-order analysis, is not yet available in the literature, due to the difficulties caused by the two-hop (product) channel and the noise introduced by the relay (active IRS). In this paper, we employ large random matrix theory, specifically Gaussian tools, to derive the closed-form deterministic approximation for the mean and variance of the MI. Additionally, we determine the convergence rate for the mean, variance and the characteristic function of the MI, and prove the asymptotic Gaussianity. Furthermore, we also investigate the analytical properties of the fundamental equations that describe the closed-form approximation and prove the existence and uniqueness of the solution. An iterative algorithm is then proposed to obtain the solutions for the fundamental equations. Numerical results validate the accuracy of the theoretical analysis. © 1963-2012 IEEE.

关键词： Iterative methods

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Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples

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Neural Computing and Applications 2024年第32期36卷 20067-20087页

作者： Saha, Mousumi Chakraborty, Mainak Maiti, Suchismita Das, Deepanwita Department of Computer Science and Engineering National Institute of Technology West Bengal Durgapur713209 India School of Innovation Design and Engineering Division of Intelligent Future Technologies Malardalen University Västerås Sweden Department of Information Technology Narula Institute of Technology West Bengal Kolkata700109 India Department of Computer Science and Engineering Narula Institute of Technology West Bengal Kolkata700109 India

Breast cancer is a prevalent and highly lethal cancer affecting women globally. While non-invasive techniques like ultrasound and mammogram are used for diagnosis, histological examination after biopsy is considered the gold standard. However, manual examination of tissues for abnormality is labor-intensive, expensive, and requires prior domain knowledge. Early detection, awareness, and access to specialized medical infrastructure in resource-constrained and remote areas are significant challenges but crucial for saving lives. In recent years, deep learning-based approaches have shown promising results in breast cancer detection, facilitated by advancements in GPU memory, computation power, and the availability of digital data. Motivated by these observations, we propose the Breast-NET deep convolutional neural network model for breast cancer detection and grading using histological images. Our model’s performance is evaluated on the BreakHis dataset, and we demonstrate its generalization ability on the Invasive Ductal Carcinoma (IDC) grading and IDC datasets. Extensive experimental and statistical performance analysis, along with an ablation study, validates the efficiency of our proposed model. Furthermore, we demonstrate the effectiveness of transfer learning with seven pre-trained convolutional neural networks for breast cancer detection and grading. Experimental results show that our framework outperforms state-of-the-art approaches in terms of accuracy, space, and computational complexity for the BreakHis, IDC grading, and IDC datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Grading

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Sign Language Vocabulary Recognition Only with Tactile Sensing Glove 17

Sign Language Vocabulary Recognition Only with Tactile Sensi...

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Kagami, Motoki Yu, Zeping Ceng, Sim Teck Jing, Lei The University of Aizu School of Computer Science and Engineering Aizu-Wakamatsu Japan The University of Aizu Graduate School of Computer Science and Engineering Aizu-Wakamatsu Japan University of Aizu Junior College Division Department of Management and Design Aizu-Wakamatsu Japan

ISBN: (纸本)9798331530471

A significant challenge in communication arises between deaf individuals and hearing individuals. Sign language recognition is expected to be an important research field for eliminating barriers. In this field, data collection is primarily conducted using two methods: sensor-based and vision-based approaches. In this study, we adopted a sensor-based approach by using a tactile sensing glove due to its portability, costeffectiveness, and ability to capture fine finger movements. Subsequently, we applied LSTM and k-NN respectively to evaluate the recognition accuracy using this method. As a result, LSTM achieved a test accuracy of approximately 76%, while k-NN demonstrated an average accuracy of 87%. These findings highlight the potential of sensor-based SLR technology in reducing communication barriers and advancing inclusively in communication tools. © 2024 IEEE.

关键词： Audition

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Secure-by-Construction Synthesis for Control Systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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science China Chemistry 2025年第5期68卷 2027-2034页

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer EngineeringThe Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

关键词： organometallic precursor magnetic nanoparticles block copolymer self-assembly nanoimprint lithography

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Robotic pendant drop:containerless liquid for μs-resolved,AI-executable XPCS

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Light(science & Applications) 2023年第9期12卷 1857-1866页

作者： Doga Yamac Ozgulbas Don Jensen Jr. Rory Butler Rafael Vescovi Ian T.Foster Michael Irvin Yasukazu Nakaye Miaoqi Chu Eric M.Dufresne Soenke Seifert Gyorgy Babnigg Arvind Ramanathan Qingteng Zhang Data Science and Learning Division Argonne National LaboratoryLemontIL 60439USA X-ray Science Division Argonne National LaboratoryLemontIL 60439USA Departement of Computer Science University of Chicago5801 S Ellis AveChicagoIL 60637USA XRD Design and Engineering Department Rigaku Corporation 3-9-12 Matsubara-choAkishima-shiTokyo 196-8666Japan Bioscience Division Argonne National LaboratoryLemontIL 60439USA

The dynamics and structure of mixed phases in a complex fluid can significantly impact its material properties,such as ***-angle X-ray Photon Correlation Spectroscopy(SA-XPCS)can probe the spontaneous spatial fluctuations of the mixed phases under various in situ environments over wide spatiotemporal ranges(10−6–103 s/10−10–10−6 m).Tailored material design,however,requires searching through a massive number of sample compositions and experimental parameters,which is beyond the bandwidth of the current coherent X-ray *** 3.7-μs-resolved XPCS synchronized with the clock frequency at the Advanced Photon Source,we demonstrated the consistency between the Brownian dynamics of~100 nm diameter colloidal silica nanoparticles measured from an enclosed pendant drop and a sealed *** electronic pipette can also be mounted on a robotic arm to access different stock solutions and create complex fluids with highly-repeatable and precisely controlled composition *** closed-loop,AI-executable protocol is applicable to light scattering techniques regardless of the light wavelength and optical coherence,and is a first step towards high-throughput,autonomous material discovery.

关键词： resolved sealed mounted

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Enhancing Drone Surveillance with NeRF: Real-World Applications and Simulated Environments 43

Enhancing Drone Surveillance with NeRF: Real-World Applicati...

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43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024

作者： Lindén, Joakim Burresi, Giovanni Forsberg, Håkan Daneshtalab, Masoud Söderquis, Ingemar School of Innovation Design and Engineering Mälardalen University Division of Intelligent Future Technologies Västerås Sweden Saab Aeronautics Stockholm Sweden School of Electrical Engineering and Computer Science Royal Institute of Technology Division of Electronics and Embedded Systems Stockholm Sweden

ISBN: (纸本)9798350349610

Machine Learning (ML) systems require representative and diverse datasets to accurately learn the objective task. In supervised learning data needs to be accurately annotated, which is an expensive and error-prone process. We present a method for generating synthetic data tailored to the use-case achieving excellent performance in a real-world usecase. We provide a method for producing automatically annotated synthetic visual data of multi rotor unmanned aerial vehicles (UAV) and other airborne objects in a simulated environment with a high degree of scene diversity, from collection of 3D models to generation of annotated synthetic datasets (synthsets). In our data generation framework SynRender we introduce a novel method of using Neural Radiance Field (NeRF) methods to capture photo-realistic high-fidelity 3D-models of multirotor UAVs in order to automate data generation for an object detection task in diverse environments. By producing data tailored to the real-world setting, our NeRF-derived results show an advantage over generic 3D asset collection-based methods where the domain gap between the simulated and real-world is unacceptably large. In the spirit of keeping research open and accessible to the research community we release our dataset VISER DroneDiversity used in this project, where visual images, annotated boxes, instance segmentation and depth maps are all generated for each image sample. © 2024 IEEE.

关键词： Drones

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Reducing congestion and emissions via roadside unit deployment under mixed traffic flow

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International Journal of Coal science & Technology 2023年第1期10卷 197-211页

作者： Yuhao Liu Zhibin Chen Siyuan Gong Han Liu Shanghai Key Laboratory of Urban Design and UrbanScience NYU ShanghaiShanghaiChina Division of Engineering and Computer Science NYUShanghaiShanghaiChina The Joint Laboratory for Internet of Vehicles Ministryof Education-China Mobile Communications CorporationXi’anShaanxiChina School of Information Engineering Chang’an UniversityXi’anShaanxiChina Central Research Institute China Coal Technologyand Engineering Group(CCTEG)BeijingChina

It is expected that for a long time the future road trafc will be composed of both regular vehicles(RVs)and connected autonomous vehicles(CAVs).As a vehicle-to-infrastructure technology dedicated to facilitating CAV under the mixed trafc fow,roadside units(RSUs)can also improve the quality of information received by CAVs,thereby infuencing the routing behavior of CAV *** paper explores the possibility of leveraging the RSU deployment to afect the route choices of both CAVs and RVs and the adoption rate of CAVs so as to reduce the network congestion and *** this end,we frst establish a logit-based stochastic user equilibrium model to capture drivers’route choice and vehicle type choice behaviors provided the RSU deployment plan is ***,CAV users’perception error can be reduced by higher CAV penetration and denser RSUs deployed on the road due to the improved information *** the established equilibrium model,the RSU deployment problem is then formulated as a mathematical program with equilibrium *** active-set algorithm is presented to solve the deployment problem *** results suggest that an optimal RSU deployment plan can efectively drive the system towards one with lower network delay and emissions.

关键词： Roadside unit deployment Connected autonomous vehicle Information quality Congestion and emission

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360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos

arXiv

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arXiv 2024年

作者： Xu, Yinzhe Huang, Huajian Chen, Yingshu Yeung, Sai-Kit The Division of Integrative Systems and Design The Department of Computer Science and Engineering The Division of Integrative Systems and Design The Department of Computer Science and Engineering The Department of Ocean Science The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360° images. To alleviate these problems, we introduce a novel representation, extended bounding field-of-view (eBFoV), for target localization and use it as the foundation of a general 360 tracking framework which is applicable for both omnidirectional visual object tracking and segmentation tasks. Building upon our previous work on omnidirectional visual object tracking (360VOT), we propose a comprehensive dataset and benchmark that incorporates a new component called omnidirectional video object segmentation (360VOS). The 360VOS dataset includes 290 sequences accompanied by dense pixel-wise masks and covers a broader range of target categories. To support both the development and evaluation of algorithms in this domain, we divide the dataset into a training subset with 170 sequences and a testing subset with 120 sequences. Furthermore, we tailor evaluation metrics for both omnidirectional tracking and segmentation to ensure rigorous assessment. Through extensive experiments, we benchmark state-of-the-art approaches and demonstrate the effectiveness of our proposed 360 tracking framework and training dataset. Copyright © 2024, The Authors. All rights reserved.

关键词： Statistical tests

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Understanding, Implementing, and Supporting Security Assurance Cases in Safety-Critical Domains

arXiv

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arXiv 2025年

作者： Mohamad, Mazen Department of Computer Science & Engineering Division of Interaction Design and Software Engineering Chalmers University of Technology University of Gothenburg Gothenburg Sweden

The increasing demand for connectivity in safety-critical domains has made security assurance a crucial consideration. In safety-critical industry, software, and connectivity have become integral to meeting market expectations. Regulatory bodies now require security assurance cases (SAC) to verify compliance, as demonstrated in ISO/SAE-21434 for automotive. However, existing approaches for creating SACs do not adequately address industry-specific constraints and requirements. In this thesis, we present CASCADE, an approach for creating SACs that aligns with ISO/SAE-21434 and integrates quality assurance measures. CASCADE is developed based on insights from industry needs and a systematic literature review. We explore various factors driving SAC adoption, both internal and external to companies in safety-critical domains, and identify gaps in the existing literature. Our approach addresses these gaps and focuses on asset-driven methodology and quality assurance. We provide an illustrative example and evaluate CASCADE's suitability and scalability in an automotive OEM. We evaluate the generalizability of CASCADE in the medical domain, highlighting its benefits and necessary adaptations. Furthermore, we support the creation and management of SACs by developing a machine-learning model to classify security-related requirements and investigating the management of security evidence. We identify deficiencies in evidence management practices and propose potential areas for automation. Finally, our work contributes to the advancement of security assurance practices and provides practical support for practitioners in creating and managing SACs. Copyright © 2025, The Authors. All rights reserved.

关键词： Automotive industry

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