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2022 International Workshop on Petri Nets and Software engineering, PNSE 2022

作者： Strand, Ruben D. Petrucci, Laure Kristensen, Lars M. Department of Safety Chemistry and Biomedical laboratory sciences Western Norway University of Applied Sciences Haugesund Norway LIPN CNRS UMR 7030 Université Sorbonne Paris Nord Villetaneuse France Department of Computer science Electrical engineering and Mathematical sciences Western Norway University of Applied Sciences Bergen Norway

Long periods of dry and cold weather conditions significantly increase fire risks for wooden buildings. Recent advances in predictive fire risk models combined with publicly available cloud-based weather data services have enabled the development of smart software systems for location-oriented fire risk notification. We have developed a Coloured Petri Net (CPN) model specifying the software architecture of a microservice-based predictive fire risk notification system. The CPN model captures the set of micro-services provided via REST APIs and the interaction between the constituent services for location tracking and subscription, fire risk computation, and data harvesting. As part of the work, we present a general modelling approach and pattern for REST-based APIs. We apply simulation and state space exploration to validate and verify key behavioural properties of the predictive fire risk notification system. © 2022 Copyright for this paper by its authors.

关键词： Petri nets

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Comparison of 3D Rice Organs Point Cloud Classification Techniques 25

Comparison of 3D Rice Organs Point Cloud Classification Tech...

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25th International computer science and engineering Conference, ICSEC 2021

作者： Rungyaem, Kanittha Sukvichai, Kanjanapan Phatrapornnant, Teera Kaewpunya, Amares Hasegawa, Shoichi Kasetsart University Department of Electrical Engineering Bangkok Thailand National Electronics and Computer Technology Center Thailand Science Park Pathumthani Thailand Tokyo Institute of Technology Department of Computational Intelligence and Systems Science Yakohama Kanagawa Japan

ISBN: (纸本)9781665411974

The performance of phenotypic evaluation is a hurdle in the rice breeding process. Because of manual evaluation, the traditional evaluation procedure is very slow. Therefore, this is the primary impediment to the development of new rice varieties. The focus of this research is to compare techniques for categorizing plant organs using 3D point clouds so that plant morphology and structure can be analyzed automatically. A 3D laser scanner was used to scan the rice plant and create the rice plant point cloud. The point cloud of the rice plant contains the rich information due to the enormous points in the cloud cluster. Therefore, the number of points in each cloud must be minimized via skeleton preprocessing technique before can be used for training the network. The skeleton approach is used to thin the cloud while keeping the vital information intact. We suggested two approaches for classifying rice organs in this study. Tensor-based classification is the first method. The second technique is PointNet. In comparison, the PointNet was the most successful for classifying rice organs and spent the least amount of time. © 2021 IEEE.

关键词： Scanning

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Electro-Optic Analog-to-Digital Converter Using Spectral Interferometry

Electro-Optic Analog-to-Digital Converter Using Spectral Int...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Linbo Shao Joseph G Thomas Bernadeta R Srijanto Kevin C Lester Ivan I Kravchenko Yizheng Zhu Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Virginia Tech Center for Quantum Information Science and Engineering Blacksburg VA USA Oak Ridge National Laboratory Center for Nanophase Materials Sciences Oak Ridge TN USA

We demonstrate an optical analog-to-digital converter (ADC) leveraging spectral interferometry of an integrated electro-optic Mach-Zehnder interferometer on thin-film lithium niobate. The ADC features a high dynamic r... 详细信息

ISBN: (纸本)9798350369311

关键词： Mach-Zehnder interferometers Integrated optics Optical interferometry Lithium niobate Lasers and electrooptics High dynamic range Electro-optical waveguides Analog-digital conversion

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Uncertainty Quantification and Quality Control for Heatmap-based Landmark Detection Models

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IEEE Transactions on Medical Imaging 2025年

作者： Feng, Yong Yang, Jinzhu Tang, Lingzhi Sun, Song Wang, Yonghuai Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang China Northeastern University School of Computer Science and Engineering Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China The First Hospital of China Medical University Department of Cardiovascular Ultrasound Shenyang China

Uncertainty quantification is a vital aspect of explainable artificial intelligence that fosters clinician trust in medical applications and facilitates timely interventions, leading to safer and more reliable outcomes. Although deep learning models have reached clinically acceptable accuracy in anatomical landmark detection, their predictions remain susceptible to contextual noise due to the small size of the target structures, making uncertainty quantification more challenging than in classification and segmentation tasks. This paper presents an end-to-end uncertainty quantification method tailored for heatmapbased anatomical landmark detection models, designed to improve both interpretability and controllability in clinical applications. Leveraging Dempster-Shafer Theory and Subjective Logic Theory, we implement probability assignment and uncertainty quantification through a single forward pass to ensure computational efficiency. We introduce an evidence map that captures the strength of landmark evidence, alongside an uncertainty map that calibrates predicted probabilities within the Subjective Logic framework. The interaction between these two components, facilitated by a cross-attention mechanism, further improves landmark detection accuracy and enhances the effectiveness of uncertainty quantification. Experimental results demonstrate that the proposed method maintains detection accuracy, even in noisy environments, while outperforming state-of-the-art methods in terms of uncertainty quantification and quality control. Furthermore, the model effectively identifies out-of-distribution data solely through calibrated probabilities when encountering inconsistencies in multi-center data and novel data, underscoring its potential for clinical applications. © 1982-2012 IEEE.

关键词： Model predictive control

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Aerial Secure Collaborative Communications under Eavesdropper Collusion in Low-altitude Economy: A Generative Swarm Intelligent Approach

arXiv

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arXiv 2025年

作者： Li, Jiahui Sun, Geng Wu, Qingqing Liang, Shuang Wang, Jiacheng Niyato, Dusit Kim, Dong In College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Information Science and Technology Northeast Normal University Changchun130117 China Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

The rapid development of the low-altitude economy (LAE) has significantly increased the utilization of autonomous aerial vehicles (AAVs) in various applications, necessitating efficient and secure communication methods among AAV swarms. In this work, we aim to introduce distributed collaborative beamforming (DCB) into AAV swarms and handle the eavesdropper collusion by controlling the corresponding signal distributions. Specifically, we consider a two-way DCB-enabled aerial communication between two AAV swarms and construct these swarms as two AAV virtual antenna arrays. Then, we minimize the two-way known secrecy capacity and maximum sidelobe level to avoid information leakage from the known and unknown eavesdroppers, respectively. Simultaneously, we also minimize the energy consumption of AAVs when constructing virtual antenna arrays. Due to the conflicting relationships between secure performance and energy efficiency, we consider these objectives by formulating a multi-objective optimization problem, which is NP-hard and with a large number of decision variables. Accordingly, we design a novel generative swarm intelligence (GenSI) framework to solve the problem with less overhead, which contains a conditional variational autoencoder (CVAE)-based generative method and a proposed powerful swarm intelligence algorithm. In this framework, CVAE can collect expert solutions obtained by the swarm intelligence algorithm in other environment states to explore characteristics and patterns, thereby directly generating high-quality initial solutions in new environment factors for the swarm intelligence algorithm to search solution space efficiently. Simulation results show that the proposed swarm intelligence algorithm outperforms other state-of-the-art baseline algorithms, and the GenSI can achieve similar optimization results by using far fewer iterations than the ordinary swarm intelligence algorithm. Experimental tests demonstrate that introducing the CVAE mechanism ach

关键词： Multiobjective optimization

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Switching between topological edge states using phase-change materials

Switching between topological edge states using phase-change...

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2023 Active Photonic Platforms, APP 2023

作者： Veronis, Georgios Huang, Yin Shen, Yuecheng School of Electrical Engineering and Computer Science Louisiana State University Baton RougeLA70803 United States Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States Department of Optoelectrics Information Science and Engineering School of Physics and Electronics Central South University Hunan Changsha410012 China State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-Sen University Guangdong Guangzhou510275 China

ISBN: (纸本)9781510665088

We introduce non-Hermitian plasmonic waveguide-cavity structures based on the Aubry-Andre-Harper model to realize switching between right and left topological edge states using the phase-change material germanium-antimony-tellurium (GST). The structure unit cells consist of a metal-dielectric-metal (MDM) waveguide side-coupled to MDM stub resonators with modulated distances between adjacent stubs. In such structures the modulated distances introduce an effective gauge magnetic field. We show that switching between the crystalline and amorphous phases of GST leads to a shift of the dispersion relation of the optimized structure so that a right topological edge state for the crystalline phase, and a left topological edge state for the amorphous phase occur at the same frequency. Thus, we realize switching between right and left topological edge states at that frequency by switching between the crystalline and amorphous phases of GST. Our results could be potentially important for developing compact reconfigurable topological photonic devices. © 2023 SPIE.

关键词： Gages

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Ultralow thermal conductance across the [FePt/h- BN/FePt] interface

arXiv

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arXiv 2024年

作者： Xu, Chengchao Zhang, Enbo Yang, Bo-Yuan Varaprasad, B.S.D.C.S. Laughlin, David E. Zhu, Jian-Gang Data Storage Systems Center Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Materials Science and Engineering Carnegie Mellon University PittsburghPA15213 United States

Heat transfer in nanocomposite materials has attracted great interest for various applications. Multilayer structures provide an important platform to study interfacial thermal transport and to engineer materials with ultralow thermal conductivity. Here we report on the fabrication and thermal characterization of [h-BN/L10-FePt]×N multilayers, where hexagonal boron nitride (h-BN) nanosheets (2.5 nm thick) and L10-FePt layers (6.5 nm thick) alternate periodically. Differential three-omega(3ω) measurements reveal an ultralow effective thermal conductivity of 0.60 ± 0.05 W m-1K-1across the multilayer films, and a low thermal boundary conductance (TBC) of 67.9 ± 6.6 MW m-2K-1for the [FePt/h-BN(2.5nm)/FePt] interface at room temperature. We attribute the ultralow thermal conductivity to the weak van der Waals bonding at h-BN/FePt interfaces, which dominates the thermal resistance of the multilayer structure. These findings provide insights into the thermal transport in 2D-material/metal multilayer nanostructures and suggest the [h-BN/FePt] superlattice as a promising material for nanoscale thermal barrier coating. Furthermore, the obtained TBC lays the foundation for analyzing heat transfer in FePt-(h-BN) nanogranular films, a promising magnetic recording media which can potentially provide high thermal gradient for heat-assisted magnetic recording (HAMR). This work advances the understanding of thermal transport in 2D-material/metal nanocomposites and demonstrates interface engineering as an effective approach to achieve materials with ultralow thermal conductivity. Copyright © 2024, The Authors. All rights reserved.

关键词： Nanocomposites

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UAV-Assisted Downlink-and-Uplink Communication in the Presence of Multiple Malicious Jammers

UAV-Assisted Downlink-and-Uplink Communication in the Presen...

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IEEE Conference on Wireless Communications and Networking

作者： Zhiyu Huang Zhichao Sheng Ali A. Nasir Cheng Yin Antonino Masaracchia Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University Shanghai China Department of Electrical Engineering and Center for Communication Systems and Sensing KFUPM Dhahran Saudi Arabia Institute for Communication Systems University of Surrey U.K. School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast U.K.

This paper investigates the unmanned aerial vehicle (UAV)-assisted communication network with multiple downlink users (DLUs) and uplink users (ULUs) in the presence of multiple malicious jammers. To guarantee fairness among the users and their uplink and downlink communication throughput, we aim to maximize the minimum average throughput by jointly optimizing the scheduling of ULUs/DLUs, three dimensional (3D) trajectory and the UAV transmission power. Although the optimization problem is computationally intractable due to its non-convexity, we develop an iterative algorithm based on the block coordinate descend approach and the successive convex approximation technique to solve the problem efficiently. Numerical outcomes show that our proposed algorithm can improve throughput significantly over several benchmark schemes.

关键词： Three-dimensional displays Processor scheduling Benchmark testing Throughput Autonomous aerial vehicles Downlink Scheduling

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Robust Phase Retrieval from Quantized and Noisy Measurements

Robust Phase Retrieval from Quantized and Noisy Measurements

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2025

作者： Gao, Yihong Zhu, Luteng An, Zhuoyang Shao, Mingjie The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Shandong University School of Information Science and Engineering Qingdao China Beijing Information Science and Technology University Computer School Beijing China Chinese Academy of Sciences Key Laboratory of System and Control Amss Beijing China

ISBN: (纸本)9798331519315

The phase retrieval (PR) problem involves recovering a signal from amplitude-only measurements and has been extensively studied in various physical measurement and signal processing systems. Recently, there has been increasing interest in the quantized phase retrieval (QPR) problem, where the observed amplitude is quantized to binary values. The existing studies have focused on the noiseless case. In this paper, we address a robust QPR problem that accounts for both quantization and noise. We formulate the robust QPR problem using maximum-likelihood estimation (MLE), which results in a non-convex and challenging optimization problem due to the complexity of its likelihood function. To obtain a high-quality solution, we develop an expectation-maximization (EM) algorithm combined with the Wirtinger flow, allowing us to convert the problem into a more manageable form at each iteration. Our method is implemented on both randomly generated synthetic data and image reconstruction tasks. The results demonstrate that our approach significantly enhances signal recovery performance under the combined effects of quantization and noise. Additionally, the proposed method exhibits better runtime efficiency compared to existing approaches. © 2025 IEEE.

关键词： Maximum likelihood estimation

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GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa

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Horticulture Research 2023年第8期10卷 97-108页

作者： Michael F.Nagle Jialin Yuan Damanpreet Kaur Cathleen Ma Ekaterina Peremyslova Yuan Jiang Bahiya Zahl Alexa Niño de Rivera Wellington Muchero Li Fuxin Steven H.Strauss Department of Forest Ecosystems and Society Oregon State University3180 SW Jefferson WayCorvallisOR97331United States Department of Electrical Engineering and Computer Science Oregon State University110 SW Park TerraceCorvallisOR97331United States Statistics Department Oregon State University103 SW Memorial PlaceCorvallisOR97331United States Biosciences Division Oak Ridge National Laboratory1 Bethel Valley RdOak RidgeTN37830United States Center for Bioenergy Innovation Oak Ridge National Laboratory1 Bethel Valley RdOak RidgeTN37830United States Bredesen Center for Interdisciplinary Research University of Tennessee821 Volunteer Blvd.KnoxvilleTN37996United States

Adventitious rooting(AR)is critical to the propagation,breeding,and genetic engineering of *** capacity for plants to undergo this process is highly heritable and of a polygenic nature;however,the basis of its genetic variation is largely *** identify genetic regulators of AR,we performed a genome-wide association study(GWAS)using 1148 genotypes of Populus *** are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale;to help overcome this limitation,we developed a computer vision system to measure an array of traits related to adventitious root development in poplar,including temporal measures of lateral and basal root length and *** was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical *** analyses yielded a total of 277 unique associations,suggesting that genes that control rooting include regulators of hormone signaling,cell division and structure,reactive oxygen species signaling,and other processes with known roles in root *** genes with uncharacterized functions and/or cryptic roles were also *** candidates provide targets for functional analysis,including physiological and epistatic analyses,to better characterize the complex polygenic regulation of AR.

关键词： GWAS breeding overcome

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