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2nd International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the International Conference on Medical Image Computing and computer Assisted Interventions, MICCAI 2024

作者： Jha, Debesh Rauniyar, Ashish Hagos, Desta Haileselassie Sharma, Vanshali Tomar, Nikhil Kumar Zhang, Zheyuan Isler, Ilkin Durak, Gorkem Wallace, Michael Yazici, Cemal Berzin, Tyler Biswas, Koushik Bagci, Ulas Machine and Hybrid Intelligence Laboratory Northwestern University Evanston United States SINTEF Digital Trondheim Norway Department of Electrical Engineering and Computer Science Howard University WashingtonDC United States Department of Computer Science University of Central Florida Orlando United States Mayo Clinic Florida Jacksonville United States Department of Medicine University of Chicago Chicago United States Beth Israel Deaconess Medical Center Harvard Medical School Boston United States

ISBN: (纸本)9783031727863

Generative Artificial Intelligence (AI) has the potential to transform medicine. It is helpful to clinicians and radiologists for diagnosis, screening, treatment planning, interventions, and drug development. It benefits the clinical flow with real-time decision-support systems. While generative AI can potentially improve healthcare, it also introduces new ethical issues that require careful analysis and mitigation strategies. This work emphasizes the ethical aspects of generative AI in medical imaging, aiming to ensure that advancements in this field align with established ethical principles and societal values. We delve into the ethical implications surrounding bias, fairness, patient privacy, consent, transparency, explainability, intellectual property, and data ownership. Furthermore, we discuss regulations governing the use of synthetic medical data. To promote equitable application of these powerful tools, we also propose clear guidelines for promoting fairness, mitigating bias, and ensuring diversity within generative AI models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Differential privacy

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Transfer Learning Trained LSTM Models for Household Load Profile Forecasting

Transfer Learning Trained LSTM Models for Household Load Pro...

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Grid Edge Technologies Conference & Exposition (Grid Edge), IEEE PES

作者： Roshan Klein-Seetharaman Xiangqi Zhu Barry Mather Department of Mathematics Yale University New Haven USA Electrical Engineering and Computer Science Oregon State University Corvallis USA National Renewable Energy Laboratory Power System Engineering Center Golden USA

ISBN: (数字)9798350352528

ISBN: (纸本)9798350352535

Grid edge renewable energy resources, such as rooftop solar photovoltaics, closely interact with consumer load profiles. Therefore, forecasting future electricity demand, ideally at the individual household level, is indispensable. In this paper, we present a transfer learning enhanced household load profile forecasting method. First, we tune a long short-term memory forecasting model to perform day-ahead prediction of household electricity load profiles. Then we improve these individualized models using transfer learning, and we use k-means clustering to create optimal source data sets. We find average improvements of 4.38% (largest improvement of 10.71%) when the entire data set was used to train the source model and 2.45% (largest improvement of 11.57%) in the mean absolute error when households were first clustered and used to train separate source models for each cluster. We find that transfer learning with clustered data can effectively boost the forecasting performance of the LSTM models. We use realistic household power measurements for 148 real residential households in Austin, Texas.

关键词： Photovoltaic systems Renewable energy sources Power measurement Electricity Transfer learning Predictive models Data models Forecasting Long short term memory Load modeling

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An active power control of DFIG-based wind turbine generators for frequency regulation with expected dynamic performance

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Applied Energy 2025年 391卷

作者： Zhao, Teyang Liu, Hui Wang, Ni Su, Jinshuo Luo, Zhiqiang Ma, Siyu School of Electrical Engineering Guangxi University Nanning530004 China Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning530004 China The State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau 519000 China

The escalating wind power penetration presents a substantial challenge in ensuring the system frequency stability. Although wind turbine generators (WTGs) can offer rapid frequency support by the presetting power trajectory response (PPTR), it will result in a secondary frequency dip (SFD) while facing the demand of restoring rotor speed after frequency regulation. Moreover, the frequency overshoot will occur due to the fixed power increment provided by PPTR under minor disturbances. In this paper, an active power control strategy of DFIG-based WTGs is proposed for eliminating frequency overshoot and mitigating SFD while providing power support for the system frequency. A rotor-speed-based power increment and power attenuation trajectory are designed to enhance the primary frequency nadir while ensuring the operation stability of WTGs. After that, SFD will be mitigated by the proposed parabolic-formed compensation power. Moreover, a power increment control mode is proposed to eliminate the frequency overshoot by a membership-function-based global controller, which can smoothly switch the combined inertial response and the improved PPTR to provide a flexible power increment. Finally, the validity of the proposed strategy in improving frequency nadir, eliminating frequency overshoot, and mitigating SFD are verified by simulations under different wind power penetration levels, disturbances, and wind conditions. © 2025

关键词： Frequency stability

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Distributed Massive MIMO-Aided Task Offloading in Satellite-Terrestrial Integrated Multi-Tier VEC Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Yixin Liang, Shaoling Wang, Kunlun Chen, Wen Li, Yonghui Karagiannidis, George K. East China Normal University School of Communication and Electronic Engineering Shanghai200241 China Guangxi Key Laboratory of Digital Infrastructure Nanning530000 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China University of Sydney School of Electrical and Information Engineering Australia Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54 124 Greece

This paper proposes a distributed massive multiple-input multiple-output (DM-MIMO) aided multi-tier vehicular edge computing (VEC) system. In particular, each vehicle terminal (VT) offloads its computational task to the roadside unit (RSU) by orthogonal frequency division multiple access (OFDMA), which can be computed locally at the RSU and offloaded to the central processing unit (CPU) via massive satellite access points (SAPs) for remote computation. By considering the partial task offloading model, we consider the joint optimization of the task offloading, subchannel allocation and precoding optimization to minimize the total cost in terms of total delay and energy consumption. To solve this non-convex problem, we transform the original problem into three sub-problems and use the alternate optimization algorithm to solve it. First, we transform the subcarrier allocation problem of discrete variables into the convex optimization problem of continuous variables. First, we transform the subcarrier allocation problem of discrete variables into the convex optimization problem of continuous variables. Then, we use multiple quadratic transformations and the Lagrange multiplier method to transform the non-convex subproblem of optimizing precoding vectors into a convex problem, while the task offloading subproblem is a convex problem. Given the subcarrier and the task allocation and precoding result, we finally find the joint optimized results by the iterative optimization algorithm. Simulation results show that our proposed algorithm is superior to other benchmarks. © 1967-2012 IEEE.

关键词： Convex optimization

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The Impact of Observer Presence on Trainees' Mental States and Performance in Remote Military Training with Virtual Humans in Mixed Reality Environment 25

The Impact of Observer Presence on Trainees' Mental States a...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing systems

作者： JunSeo Park Yechan Yang Gerard Jounghyun Kim Hanseob Kim Digital Experience Laboratory Korea University Seoul Republic of Korea and Republic of Korea Navy Seoul Republic of Korea Digital Experience Laboratory Korea University Seoul Republic of Korea Department of Computer Science and Engineering Korea University Seoul Republic of Korea

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A Lightweight Method to Survey with Protecting Privacy yet Maintaining Accuracy 18th

A Lightweight Method to Survey with Protecting Privacy yet...

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18th International Conference on Wireless Artificial Intelligent Computing systems and Applications, WASA 2024

作者： Wang, Yuxuan Di, Xinyu Liu, Ningbo Zhang, Xianchao Ren, Wei School of Computer Science China University of Geosciences Wuhan China Department of Computer Science University of Toronto TorontoONM5S 1A1 Canada International College Chongqing University of Technology Chongqing China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing University Jiaxing China Ministry of Education Chengdu China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR CASM Beijing China

ISBN: (纸本)9783031714665

In a survey, a lot of questions and answers are listed and participators will select one of the answers for each question. Sometimes, participators may not be willing to select the preferred one item in the answers because the item may damage the privacy of themselves. If this question is not answered, then it reveals that the question or the answers are sensitive, which also damages the privacy. Besides, each participator may have distinct privacy concerns even for the same questions and answers, thus the privacy-aware questions and answers cannot be determined and be removed in advance. Thus, the dilemma is how to select the answers for privacy-aware questions yet maintain the utility of the answering results in the survey. In this paper, we propose a general method to protect the various privacy in the investigation without the knowledge of privacy to be protected in advance. The main idea is that participators can randomly select answers if the privacy is the concern for themselves in the answers for this question. Our method is lightweight so as to be convenient in practices. We extensively analyze the accuracy of survey results to justify that our method can protect the privacy yet maintain the utility of the investigation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Differential privacy

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General and Offset-Resistant Physical-Layer Acknowledgement Approach for Cross-Technology Communication

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IEEE Transactions on Communications 2025年

作者： Yao, Shumin Zhao, Qinglin Zhou, MengChu Feng, Li Zhang, Peiyun Albeshri, Aiiad Macau University of Science and Technology School of Computer Science and Engineering Avenida Wei Long Taipa China Pengcheng Laboratory Department of Broadband Communication Shenzhen518066 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States Nanjing University of Information Science & Technology Engineering Research Center of Digital Forensics of Ministry of Education School of Computer Science Nanjing210044 China King Abdulaziz University Department of Computer Science Jeddah21481 Saudi Arabia

Cross-technology communication (CTC) enables direct communications among devices with heterogeneous wireless technologies (e.g., Bluetooth, WiFi, ZigBee, etc.), thereby reducing the cost and complexity of their interconnections. However, CTC is essentially unreliable due to the technology heterogeneity, and most existing CTC designs do not provide acknowledgment (ACK) feedback to ensure reliable data transmission. Few ACK designs are only applicable to feedback for ZigBee-WiFi pair and are vulnerable to sampling offsets that inherently exist in CTC. In this work, we propose a General and Offset-resistant Physical-layer ACK approach, called GOP-ACK, to support reliable feedback with practical considerations. Its core idea lies in encoding ACK messages with offset-resistant signal that has two benefits: 1) it can be adapted to a wide range of CTC scenarios with minimal adjustment, and 2) it can be effortlessly and robustly detected even in the presence of sampling offsets. We offer practical guidelines to tackle key deployment challenges related to signal construction, efficient and robust transmission, and effective firmware module reuse, enabling the application of GOP-ACK to specific CTC scenarios. Based on these guidelines, we implement two design cases: ZigBee-to-BLE and ZigBee-to-WiFi feedback, and propose a theoretical model to analyze their performance. We then conduct real-world experiments and extensive simulations to verify its feasibility and superiority over the state of the art, thereby enhancing the practicality of CTC greatly. © 1972-2012 IEEE.

关键词： Firmware

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Improving meteorological drought simulation in Iran using wavelet-enhanced deep learning models

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Theoretical and Applied Climatology 2025年第5期156卷 1-15页

作者： Heydarizad, Mojtaba Liu, Zhongfang Stojanovic, Milica Sorí, Rogert Mohammadabadi, Hamid Ghalibaf Ali, Aamir Minaei, Masoud State Key Laboratory of Marine Geology Tongji University Shanghai 200092 China Environmental Physics Laboratory (EPhysLab) Centro de Investigación Mariña Universidade de Vigo Campus As Lagoas s/n Ourense 32004 Spain Department of Computer Engineering Ferdowsi University of Mashhad Mashhad *** Iran School of Ocean and Earth Science Tongji University Shanghai 200092 China Department of Geography Ferdowsi University of Mashhad Mashhad *** Iran Geographic Information Science/System and Remote Sensing Laboratory (GISSRS: Lab) Ferdowsi University of Mashhad Mashhad *** Iran

In recent decades, the intensification of meteorological droughts has significantly impacted semi-arid and arid regions, including Iran. This study aims to develop a high-accuracy simulation framework for the Standardized Precipitation Index (SPI) at 1-, 3-, and 6-month timescales (SPI-1, SPI-3, and SPI-6), using 40 years (1980–2019) of ERA5 precipitation data. Fourteen climatic predictors were employed to simulate SPI values using two machine learning approaches: a Deep Neural Network (DNN) and a hybrid model combining DNN with the Discrete Wavelet Transform (DNN–Wavelet). Evaluation across multiple metrics confirmed that the DNN–Wavelet model consistently outperformed the standalone DNN model by effectively capturing both temporal and frequency-domain features. Predictor importance analysis using Shapley Additive Explanations (SHAP) identified dew point temperature, mean sea level pressure, and evaporation rate as the primary drivers of SPI variations. In addition, multiscale wavelet analysis and Bivariate Wavelet Coherence (BWC) revealed strong time–frequency correlations between SPI drought indices and key climatic variables. The proposed DNN–Wavelet model shows strong potential as a reliable approach for simulating drought conditions, particularly in data-scarce and drought-prone regions such as Iran. Its application can enhance understanding of drought dynamics and support strategic and sustainable water resource planning. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.

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DSAA: Cross-modal transferable double sparse adversarial attacks from images to videos

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Neurocomputing 2025年 639卷

作者： Han, Xueqiang Zhang, Shihui Wang, Houlin Tian, Qing School of Information Science and Engineering Yanshan University Hebei Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei Qinhuangdao China Department of Computer Science University of Alabama at Birmingham AL United States

Recent preliminary research has examined cross-modal attacks, enabling the transition of unlabeled attacks from images to videos. The current cross-modal attacks are mainly dense attacks, while sparse attacks have not been explored. To bridge this gap, this paper proposes a cross-modal transferable double sparse adversarial attack (DSAA) method. Specifically, DSAA incorporates both spatial sparsity and temporal sparsity. Firstly, we design a novel double-cross-shaped patch paradigm to achieve spatial sparsity. Leveraging this patch for perturbation addition enables a more effective global impact on video frames. Subsequently, we propose a uniform temporal sparsity strategy to achieve temporal sparsity. Even if only half of the frames are perturbed, the resulting average attack success rate remains comparable to that of perturbing all frames. Furthermore, we take into account the luminance, contrast, and structure of images and propose a structural similarity loss function (SSLF). By utilizing SSLF to measure the similarity of intermediate feature maps and incorporating it into perturbation optimization, DSAA achieves excellent attack performance. Extensive experiments demonstrate DSAA's superiority over state-of-the-art approaches in terms of attack success rate. The proposed DSAA uses video adversarial examples generated by four ImageNet-pretrained image models on Kinetics-400 and UCF-101 to attack six video recognition models, achieving average attack success rates of 85.83% and 82.02%, respectively. © 2025 Elsevier B.V.

关键词： Cross-modal attacks Spatial sparsity Temporal sparsity Unlabeled attacks Video adversarial examples

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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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