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arXiv 2022年

作者： Lymperaiou, Maria Stamou, Giorgos Artificial Intelligence and Learning Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Heroon Polytechniou 9 Zografou Attica15780 Greece

Multimodal learning has been a field of increasing interest, aiming to combine various modalities in a single joint representation. Especially in the area of visiolinguistic (VL) learning multiple models and techniques have been developed, targeting a variety of tasks that involve images and text. VL models have reached unprecedented performances by extending the idea of Transformers, so that both modalities can learn from each other. Massive pre-training procedures enable VL models to acquire a certain level of real-world understanding, although many gaps can be identified: the limited comprehension of commonsense, factual, temporal and other everyday knowledge aspects questions the extendability of VL tasks. Knowledge graphs and other knowledge sources can fill those gaps by explicitly providing missing information, unlocking novel capabilities of VL models. At the same time, knowledge graphs enhance explainability, fairness and validity of decision making, issues of outermost importance for such complex implementations. The current survey aims to unify the fields of VL representation learning and knowledge graphs, and provides a taxonomy and analysis of knowledge-enhanced VL models. © 2022, CC BY-NC-ND.

关键词： Decision making

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Optimal Task Offloading Policy in Edge Computing systems with Firm Deadlines

arXiv

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arXiv 2022年

作者： Doan, Khai Araujo, Wesley Kranakis, Evangelos Lambadaris, Ioannis Viniotis, Yannis Carleton University Department of Systems and Computer Engineering OttawaON Canada Carleton University School of Computer Science OttawaON Canada North Carolina State University Department of Electrical and Computer Engineering RaleighNC United States

The recent drastic increase in mobile data traffic has pushed the mobile edge computing systems to the limit of their capacity. A promising solution is the task migration to remote servers. Key factors to be considered in the design of offloading schemes must include the number of tasks waiting in the system as well as their corresponding deadlines. An appropriate system cost which is used as an objective function to be minimized comprises two parts. First, an offloading cost which can be interpreted as the cost of using computational resources at the external server. Second, a penalty cost due to potential task expiration. In order to minimize the expected (time average) cost over a time horizon, we formulate a Dynamic Programming (DP) equation and analyze it to describe properties of a candidate optimal offloading policy. The DP equation suffers from the well-known "Curse of Dimensionality" that makes computations intractable, especially when the state space is infinite. In order to reduce the computational burden, we identify three important properties of the optimal policy. Based on these properties, we show that it suffices to evaluate the DP equation on a finite subset of the state space only. We then show that the optimal task offloading decision associated with a state can be inferred from the decision taken at its "adjacent" states, further reducing the computational load. Finally, we provide numerical results to evaluate the influence of different parameters on the system performance as well as verify the theoretical results. © 2022, CC BY.

关键词： Computation offloading

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SlideMLP: A Pure Multi-layer Perceptrons Method For Medical Image Segmentation

SlideMLP: A Pure Multi-layer Perceptrons Method For Medical ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chaoqi Han Bingcai Chen Chanjuan Liu Qian Ning Victor C.M. Leung Shouzhen Jiao Qing Liu School of Computer Science and Technology Dalian University of Technology Dalian China Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology Dalian China College of Electronics and Information Engineering Sichuan University Chengdu China Dept. of Electrical and Computer Engineering The University of British Columbia Vancouver Canada

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Convolutional Neural Networks and Attention-based Transformer have emerged as the preferred models for medical image processing. Recently, specific network architectures relying solely on multilayer perceptrons (MLPs) have gained popularity and demonstrated excellent results in various computer vision tasks. In particular, CycleMLP has demonstrated good performance in dense prediction tasks owing to its adaptability to image size and linear computational complexity. However, the basic operator of CycleMLP has a fixed sampling location for any feature map and samples very few target organs in medical images characterized by an extreme imbalance between foreground and background. Therefore, effectively extracting the features of target organs becomes challenging. In this paper, we propose a new MLP-like module, SlideMLP, by considering the sparsity of target organs in medical images. This module extracts a set of offsets from the input feature maps and utilizes these offsets to re-select the sampling points. This approach effectively enhances the sampling rate of target organs while retaining the advantages of CycleMLP. Additionally, we constructed a U-shaped network with a pure MLP using this module and assessed its robustness using two datasets with different modalities. Comparative results with state-of-the-art methods demonstrate that the method proposed in this paper can achieve a substantial Dice Similarity Coe cient (DSC) while utilizing fewer parameters.

关键词： Image segmentation Neural networks Network architecture Multilayer perceptrons Feature extraction Transformers Robustness

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Pseudo-label Assisted Optimization of Multi-branch Network for Cross-domain Person Re-identification

Pseudo-label Assisted Optimization of Multi-branch Network f...

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IEEE International Conference on Mechatronics and Automation

作者： Zhengyang Wang Shuxiang Guo Xue Shang Xiufen Ye College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China Department of Electrical and Computer Engineering National University of Singapore Singapore School of Life science Beijing Institute of Technology Beijing China

Person re-identification plays an important role in the field of robot intelligence perception and public safety. Its main task is to identify person targets under cross-camera. However, the domain diversity between different datasets poses a clear challenge for adapting a model trained on one dataset to another. Currently, person re-identification methods based on domain adaptive learning and pseudo-label have made good progress on this problem. Unfortunately, inferior pseudo-labels and source domain noise affect the performance. In order to improve the quality of generated pseudo-labels and enhance the feature representation capability of the model, we propose a pseudo-label assisted optimization of a multi-branch person re-identification method. The multi-branch network is able to extract and represent more effective global and local features, and the generated pseudo-labels are optimized by using cosine similarity and DBSCAN clustering on the feature vectors, thus improving the consistency of the supervised information to enhance the cross-domain recognition performance. We also use a loss function combining cross-entropy loss and triplet loss to make the best feature learning. Experiments show that our method performs well in the Market-to-Duke and Duke-to-Market cross-domain recognition tasks.

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Algal Bloom Front Tracking Using an Unmanned Surface Vehicle: Numerical Experiments Based on Baltic Sea Data

Algal Bloom Front Tracking Using an Unmanned Surface Vehicle...

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OCEANS 2021: San Diego - Porto

作者： Fonseca, Joana Aguiar, Miguel Sousa, Joao Borges De Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science and Digital Futures StockholmSE-10044 Sweden Portugal

ISBN: (纸本)9780692935590

We consider the problem of tracking moving algal bloom fronts using an unmanned surface vehicle (USV) equipped with a sensor that measures the concentration of chlorophyll a. Chlorophyll a is a green pigment found in plants, and its concentration is an indicator of phytoplankton abundance. Our algal bloom front tracking mission consists of three stages: deployment, data collection, and front tracking. At the deployment stage, a satellite collects an image of the sea from which the location of the front, the reference value for the concentration at this front and, consequently, the appropriate initial position for the USV are determined. At the data collection stage, the USV collects data points to estimate the local algal gradient as it crosses the front. Finally, at the front tracking stage, an adaptive algorithm based on recursive least squares fitting using recent past sensor measures is executed. We evaluate the performance of the algorithm and its sensitivity to measurement noise through MATLAB simulations. We also present an implementation of the algorithm on the DUNE onboard software platform for marine robots and validate it using simulations with satellite model forecasts from Baltic sea data. © 2021 MTS.

关键词： Unmanned surface vehicles

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Risk Modeling and Traceability of Boundary Attacks on Internet of Power systems Based on Complex Networks 9

Risk Modeling and Traceability of Boundary Attacks on Intern...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Li, Xin Qu, Zhaoyang Yu, Tong Xie, Ming Yu, Fu Ding, Wei Northeast Electric Power University School of Electrical Engineering Jilin132012 China People's Bank of China Qinghai Provincial Branch Xining810000 China China Southern Power Grid Guangxi Power Grid Co. Ltd. Research Institute Nanning530023 China China Guizhou Power Grid Co. Ltd. Bijie Power Supply Bureau Bijie551700 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China

ISBN: (纸本)9798350391367

With the increasing intelligence of power IoT terminal devices, the massive volume of data transmission, and the widespread adoption of shared services, traditional terminal boundary security mechanisms are unable to keep up with the rapid development of network technologies and applications. Additionally, they fail to trace and source network attacks, leading to frequent organized and purposeful malicious attack incidents. To address these issues, this paper proposes a research method for risk modeling and traceability of boundary attacks on power IoT terminals based on complex networks. First, based on the node information of power IoT terminal devices and complex network theory, a terminal boundary attack network (TBAN) is established. Next, using indicators related to complex network theory, such as degree, in-degree, and out-degree, the terminal boundary attack network is analyzed. Furthermore, a staged TBAN is proposed to analyze the attack risks at different times. Then, combining causal theory, a method for tracing and sourcing terminal boundary attacks based on a causal Bayesian network is proposed to identify and trace malicious attacks. Finally, validation and testing analysis are conducted using the actual deployment of power IoT terminal devices. The proposed analysis method transforms the spatial characteristics of the power IoT terminal boundary into a temporally sequential TBAN, which not only visually reflects attack risks but also reveals the temporal relationships of terminal boundary attacks between lines. © 2024 IEEE.

关键词： Internet of things

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Map2Schedule: An End-to-End Link Scheduling Method for Urban V2V Communications

arXiv

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arXiv 2023年

作者： Zhang, Lihao Sun, Haijian Sun, Jin Parasuraman, Ramviyas Ye, Yinghui Hu, Rose Qingyang The School of Electrical and Computer Engineering University of Georgia AthensGA United States The School of Computing University of Georgia AthensGA United States Shanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications China The Electrical and Computer Engineering Department Utah State University LoganUT United States

Urban vehicle-to-vehicle (V2V) link scheduling with shared spectrum is a challenging problem. Its main goal is to find the scheduling policy that can maximize system performance (usually the sum capacity of each link or their energy efficiency). Given that each link can experience interference from all other active links, the scheduling becomes a combinatorial integer programming problem and generally does not scale well with the number of V2V pairs. Moreover, link scheduling requires accurate channel state information (CSI), which is very difficult to estimate with good accuracy under high vehicle mobility. In this paper, we propose an end-to-end urban V2V link scheduling method called Map2Schedule, which can directly generate V2V scheduling policy from the city map and vehicle locations. Map2Schedule delivers comparable performance to the physical-model-based methods in urban settings while maintaining low computation complexity. This enhanced performance is achieved by machine learning (ML) technologies. Specifically, we first deploy the convolutional neural network (CNN) model to estimate the CSI from street layout and vehicle locations and then apply the graph embedding model for optimal scheduling policy. The results show that the proposed method can achieve high accuracy with much lower overhead and latency. © 2023, CC BY.

关键词： Channel state information

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Dissipative State Feedback of General Linear Time-Delay systems: Applications of the Kronecker-Seuret Decomposition Concept

SSRN

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SSRN 2024年

作者： Feng, Qian Zheng, Wei Xing Wang, Xiao Yu Xiao, Feng School of Control and Computer Engineering North China Electric Power University Beijing China School of Computer Data and Mathematical Sciences Western Sydney University Sydney Australia State Key Laboratory of Alternative Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China

Stabilizing autonomous linear time delay systems, particularly when addressing an unlimited number of pointwise and distributed delays (DDs) under dissipative constraints, poses a significant challenge. Existing solutions are often hindered by theoretical limitations, numerical obstacles, or an inability to address the complexities of the delay integral kernels. In this paper, we propose a unified framework to tackle the above problem by employing the concept of the Kronecker-Seuret decomposition (KSD) for matrix-valued functions, which we recently have developed for the analysis of complex delay structures in coordination with the Krasovski\u{\i} functional approach. Our strategy can simultaneously address two distinct control problems, where the matrix kernels of DDs can contain an unlimited number of square-integrable functions. We show in detail how the KSD can factorize and approximate different kernel functions simultaneously without introducing conservatism. Furthermore, the use of KSD also enables us to construct complete-type functionals, whose integral kernels can include any number of weakly differentiable and linearly independent functions, underpinned by the utilization of novel integral inequalities derived from the least-squares principle. The solution to each synthesis problem comprises two theorems accompanied by an iterative algorithm, which can be utilized as a single package to compute controller gains, thus eliminating the need for nonlinear solvers. We present the testing results of two challenging examples, which could not be addressed by existing methods, to demonstrate the effectiveness of our methodology. Additionally, the paper reviews recent advancements in the research of time-delay systems, providing a valuable reference for both emerging and established researchers. © 2024, The Authors. All rights reserved.

关键词： State feedback

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Graphene Bridge Heterostructure Devices for Negative Differential Transconductance Circuit Applications

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Nano-Micro Letters 2023年第2期15卷 161-171页

作者： Minjong Lee Tae Wook Kim Chang Yong Park Kimoon Lee Takashi Taniguchi Kenji Watanabe Min‑gu Kim Do Kyung Hwang Young Tack Lee Department of Electrical and Computer Engineering Inha UniversityIncheon 22212Republic of Korea Department of Materials Science and Engineering The University of Texas at DallasRichardsonTX 75080USA Center for Opto‑Electronic Materials and Devices Post‑Silicon Semiconductor InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Physics Kunsan National UniversityGunsan 54150Republic of Korea Advanced Materials Laboratory National Institute for Materials ScienceTsukuba 305‑0044Japan Department of Information and Communication Engineering Inha UniversityIncheon 22212Republic of Korea Division of Nanoscience and Technology KIST SchoolUniversity of Science and Technology(UST)Seoul 02792Republic of Korea Department of Electronic Engineering Inha UniversityIncheon 22212Republic of Korea

Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction *** this study,we demonstrate graphene(Gr)-bridge heterostructure devices consisting of laterally series-connected ambipolar semiconductor/Gr-bridge/n-type molybdenum disulfide as a channel material for field-effect transistors(FET).Unlike conventional FET operation,our Gr-bridge devices exhibit nonclassical transfer characteristics(humped transfer curve),thus possessing a negative differential *** phenomena are interpreted as the operating behavior in two series-connected FETs,and they result from the gate-tunable contact capacity of the Gr-bridge ***-value logic inverters and frequency tripler circuits are successfully demonstrated using ambipolar semiconductors with narrow-and wide-bandgap materials as more advanced circuit applications based on non-classical transfer ***,we believe that our innovative and straightforward device structure engineering will be a promising technique for future multi-functional circuit applications of 2D nanoelectronics.

关键词： Graphene bridge Heterostructure device Non-classical transfer characteristics Multi-value logic inverter Frequency tripler

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Channel Estimation for Movable Antenna Communication systems Based on Compressed Sensing

Channel Estimation for Movable Antenna Communication Systems...

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IEEE Conference on Wireless Communications and Networking

作者： Songqi Cao Lipeng Zhu Xiangyu Pi Zhenyu Xiao Boyu Ning School of Electronic and- Inforrmation Engineering Beihang University Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

This paper proposes a general channel estimation framework for movable antenna (MA) communication systems. In this framework, the channel state information between the entire transmitter (Tx) and receive (Rx) regions can be re-constructed, so as to find the optimal positions of the MAs for reaping performance gains. Specifically, the field-response channel structure is utilized to represent the channel response in terms of the angles of departure (AoDs), angles of arrival (AoAs), and complex coefficients of the multi-path components (MPCs). Then, the compressed sensing method is employed to jointly estimate the MPC information, i.e., the AoDs, AoAs, and complex coefficients of the paths, with a limited number of channel measurements. Notably, the measurement matrix under the proposed framework is fundamentally determined by the Tx-MA and Rx-MA measurement positions, which further affects the channel estimation performance. In this regard, four MA measurement position setups are proposed, and the channel estimation performance of each setup is further compared. Finally, simulation results show that the complete CSI between the entire Tx and Rx regions can be reconstructed by our proposed channel estimation framework with a high accuracy.

关键词： Antenna measurements Communication systems Atmospheric measurements Simulation Channel estimation Position measurement Particle measurements

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