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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Tomasz Marciniak Agnieszka Stankiewicz Przemysław Zaradzki Department of Control Robotics and Electrical Engineering Division of Electronic Systems and Signal Processing Institute of Automatic Control and Robotics Poznan University of Technology Poznan Poland

This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using the author’s publicly available CAVRI-C database. A 3D version of the U-Net artificial neural network was used. Various dimensions of the input blocks were investigated to determine their influence on the segmentation process. The effectiveness of the proposed solutions was evaluated using various metrics and the results obtained were compared with the 2D solution, also based on neural networks. The use of the proposed solutions allowed us to improve the segmentation even by 15% (in the case of the F1-score).

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Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study

arXiv

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arXiv 2023年

作者： Khanal, Saroj Graf, Christoph Liang, Zhirui Dvorkin, Yury Ünel, Burçin The Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States The Departments of Electrical and Computer Engineering Department and Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218 United States The Institute for Policy Integrity New York University School of Law New YorkNY10012 United States

Despite ambitious offshore wind targets in the U.S. and globally, offshore grid planning guidance remains notably scarce, contrasting with well-established frameworks for onshore grids. This gap, alongside the increasing penetration of offshore wind and other clean-energy resources in onshore grids, highlights the urgent need for a coordinated planning framework. Our paper describes a multi-objective, multistage generation, storage and transmission expansion planning model to facilitate efficient and resilient large-scale adoption of offshore wind power. Recognizing regulatory emphasis and, in some cases, requirements to consider externalities, this model explicitly accounts for negative externalities: greenhouse gas emissions and local emission-induced air pollution. Utilizing an 8-zone ISO-NE test system and a 9-zone PJM test system, we explore grid expansion sensitivities such as impacts of optimizing Points of Interconnection (POIs) versus fixed POIs, negative externalities, and consideration of extreme operational scenarios resulting from offshore wind integration. Our results indicate that accounting for negative externalities necessitates greater upfront investment in clean generation and storage (balanced by lower expected operational costs). Optimizing POIs could significantly reshape offshore topology or POIs, and lower total cost. Finally, accounting for extreme operational scenarios typically results in greater operational costs and sometimes may alter onshore line investment. Copyright © 2023, The Authors. All rights reserved.

关键词： Investments

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The Impact of the Digital Transformation of Education on Literacy

The Impact of the Digital Transformation of Education on Lit...

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International IEEE Conference and Workshop: Óbuda on electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills.

关键词： Power engineering Epidemics Navigation Knowledge acquisition Digital transformation Education Information age Digital intelligence Cultural differences Problem-solving

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Distilling BlackBox to Interpretable models for Efficient Transfer Learning

arXiv

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arXiv 2023年

作者： Ghosh, Shantanu Yu, Ke Batmanghelich, Kayhan Department of Electrical and Computer Engineering Boston University BostonMA United States Intelligent Systems Program University of Pittsburgh PittsburghPA United States

Building generalizable AI models is one of the primary challenges in the healthcare domain. While radiologists rely on generalizable descriptive rules of abnormality, Neural Network (NN) models suffer even with a slight shift in input distribution (e.g., scanner type). Fine-tuning a model to transfer knowledge from one domain to another requires a significant amount of labeled data in the target domain. In this paper, we develop an interpretable model that can be efficiently fine-tuned to an unseen target domain with minimal computational cost. We assume the interpretable component of NN to be approximately domain-invariant. However, interpretable models typically underperform compared to their Blackbox (BB) variants. We start with a BB in the source domain and distill it into a mixture of shallow interpretable models using human-understandable concepts. As each interpretable model covers a subset of data, a mixture of interpretable models achieves comparable performance as BB. Further, we use the pseudo-labeling technique from semi-supervised learning (SSL) to learn the concept classifier in the target domain, followed by fine-tuning the interpretable models in the target domain. We evaluate our model using a real-life large-scale chest-X-ray (CXR) classification dataset. The code is available at: https://github. com/batmanlab/MICCAI-2023-Route-interpret-repeat-CXRs. © 2023, CC BY.

关键词： Large dataset

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Privacy-Preserving Adversarial Network (PPAN) for Continuous non-Gaussian Attributes

Privacy-Preserving Adversarial Network (PPAN) for Continuous...

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IEEE/ACM International Symposium on Big Data Computing (BDC)

作者： Mohammadhadi Shateri Fabrice Labeau Department of Systems Engineering École de Technologie Supérieure Montreal Canada Department of Electrical and Computer Engineering McGill University Montreal Canada

A privacy-preserving adversarial network (PPAN) was recently proposed as an information-theoretical framework to address the issue of privacy in data sharing. The main idea of this model was to use mutual information as the privacy measure and adversarial training of two deep neural networks, one as the mechanism and another as the adversary. The performance of the PPAN model for the discrete synthetic data, MNIST handwritten digits, and continuous Gaussian data was evaluated and compared to the analytically optimal trade-off. In this study, we evaluate the PPAN model for continuous non-Gaussian data, i.e. smart meters data, where lower and upper bounds of the privacy-preserving problem are used. These bounds include the Kraskov (KSG) estimation of entropy and mutual information that is based on the k-th nearest neighbor. In addition to the synthetic data sets, a practical case for hiding the actual electricity consumption from smart meter readings is examined. The results show that for continuous non-Gaussian data, the PPAN model performs within the determined optimal ranges and close to the lower bound.

关键词： Training Privacy Upper bound Time series analysis Estimation Data models Entropy

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Trojan Playground: A Reinforcement Learning Framework for Hardware Trojan Insertion and Detection

arXiv

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arXiv 2023年

作者： Sarihi, Amin Patooghy, Ahmad Jamieson, Peter Badawy, Abdel-Hameed A. The Klipsch School of Electrical and Computer Engineering New Mexico State University Las CrucesNM88001 United States The Department of Computer Systems Technology North Carolina A&T State University GreensboroNC27411 United States The Electrical and Computer Engineering Department Miami University OxfordOH45056 United States

Current Hardware Trojan (HT) detection techniques are mostly developed based on a limited set of HT benchmarks. Existing HT benchmark circuits are generated with multiple shortcomings, i.e., i) they are heavily biased by the designers’ mindset when created, and ii) they are created through a one-dimensional lens, mainly the signal activity of nets. We introduce the first automated Reinforcement Learning (RL) HT insertion and detection framework to address these shortcomings. In the HT insertion phase, an RL agent explores the circuits and finds locations best for keeping inserted HTs hidden. On the defense side, we introduce a multi-criteria RL-based HT detector that generates test vectors to discover the existence of HTs. Using the proposed framework, one can explore the HT insertion and detection design spaces to break the limitations of human mindset and benchmark issues, ultimately leading toward the next generation of innovative detectors. We demonstrate the efficacy of our framework on ISCAS-85 benchmarks, provide the attack and detection success rates, and define a methodology for comparing our techniques. © 2023, CC BY.

关键词： Reinforcement learning

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Subdiffusive transport in the Fredkin dynamical universality class

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Physical Review B 2025年第18期111卷 184317-184317页

作者： Catherine McCarthy Hansveer Singh Sarang Gopalakrishnan Romain Vasseur Department of Physics University of Massachusetts Amherst Massachusetts 01003 USA Max Planck Institute for the Physics of Complex Systems 01187 Dresden Germany Department of Electrical and Computer Engineering Princeton University Princeton New Jersey 08544 USA Department of Theoretical Physics University of Geneva 24 quai Ernest-Ansermet 1211 Geneva Switzerland

Fredkin-type kinetic constraints appear in systems ranging from classical interfaces to th e Fredkin and Motzkin quantum spin chains. Here, we identify a pseudolocal conserved charge associated with Fredkin-constrained dynamics that may be leveraged to subdiffusively bound the dynamical exponent z≥5/2. Our results establish that transport in Fredkin-constrained systems belongs to a distinct dynamical universality class that is separate from ordinary diffusion. This universality class is stable to local perturbations that conserve the pseudolocal charge.

关键词： Dynamics

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Internet-of-Things technology and applications for clean energy systems

Energy Conversion and Economics

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Energy Conversion and Economics 2021年第4期2卷 183-185页

作者： Strunz, Kai Wang, Xuanyuan Guo, Qinglai Xie, Le Zhang, Song Fang, Xin Wang, Jianxiao School of Electrical Engineering and Computer Science Berlin10587 Germany State Grid Jibei Electric Power Co. LTD. Beijing China Department of Electrical Engineering Tsinghua University Beijing China Department of Electrical and Computer Engineering Texas A&M University College StationTX United States Department of Business Architecture and Technology ISO New England Inc. HolyokeMA United States Power Systems Engineering Center National Renewable Energy Laboratory GoldenCO United States School of Electrical and Electronic Engineering North China Electric Power University Beijing China

[...]future research interests regarding IESSs are summarised. A multi-stage PMU placement strategy was developed to alleviate power system vulnerability to possible false data injection attacks, where forward dynamic programming was used to distribute the capital cost of PMUs over a certain period. Three clustering methods, including linear regression, density-based spatial clustering of applications with noise (DBSCAN), and Gaussian mixture models (GMM), were combined for bad PMU data detection.

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Reusability potential of spacecraft solar panels 74

Reusability potential of spacecraft solar panels

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74th International Astronautical Congress, IAC 2023

作者： Clauss, Margot Cho, Mengu Bursachi, Noé Laufer, René Weiss, Bernd Ronnbäck, Anna Öhrwall Department of Computer Science Electrical and Space Engineering Luleå University of Technology Rymdcampus Bengt Hultqvists väg 1 Kiruna981 92 Sweden Department of Space Systems Engineering Kyushu Institute of Technology Kitakyushu8048550 Japan Centre National d'étude Spatiale 18 Av. Edouard Belin Toulouse31400 France Department of Social Sciences Technology and Arts Luleå University of Technology Laboratorievägen 14 LULEÅSE-971 87 Sweden

Sustainability is a major subject for society and industries. Circularity seems to be the next step in this development. Regarding the space industry, implementing sustainability poses different challenges, and many pieces of knowledge and technologies are still missing: to capture a spacecraft in space, the infrastructure to process it, the policy on sustainable space, etc. Nevertheless, those are emerging with risk-taking and non-traditional satellite development and management methods such as Lean satellites. The space community must foresee the requirements to reuse a spacecraft after its end of life. It should answer questions such as how can one reuse a spacecraft? Is it even possible? Can the space industry use findings from other industries to implement reusability? For example, can we implement solar panel end-of-life processes used on Earth in space? This paper will study the reusability of solar panels since they are a common part of most satellites and are composed of rare materials. The capability to reuse them in space might be a first step for space circularity since it will maximize the value of a spacecraft mission to its customers by giving value to something considered nowadays as debris. The concept of reusing spacecraft solar panels can be integrated into a Lean satellite project. Nonetheless, reusing solar panels in space requires understanding their degradation due to the space environment, investigating the applicability of Earth solar panels' end-of-life processes in space, and their potential performances after those processes. It requires also to design reusable solar panels either by making them easier to reprocess or by making them transferable from one spacecraft to another spacecraft. Some missions such as the Hubble Space Telescope, i.e., HST, mission present reusability characteristics in their design. HST was designed to be maintained in space and its solar panels were replaced twice by astronauts during the time of the space shuttl

关键词： Materials Reusability Reuse Solar panels Spacecraft

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An Economic Feasibility Study for Off-Grid Hybrid Renewable Energy Resources

An Economic Feasibility Study for Off-Grid Hybrid Renewable ...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Emmanuel Idowu Ogunwole Senthil Krishnamurthy Department of Electrical Electronic and Computer Engineering Center for Substation Automation and Energy Management Systems Cape Peninsula University of Technology Cape Town South Africa

Renewable energy resources (RES) are gaining popularity worldwide. As a result, renewable energy sources (RES) are now considered an alternative source of electric power generation in many communities. Furthermore, using renewable energy sources reduces pollution caused by coal and the release of carbon into the atmosphere by power plants. This article focuses on the economic feasibility of renewable energy resources since it is one of the obstacles in building and executing effective and efficient power generation with RES. An optimizer function of HOMER Pro software was employed in this study to develop a cost-effective power-generating RES configuration. The system uses an IEEE 14-Bus load demand of 259 MW supplied by five generators tested the design system in an IEEE 14-Bus test system with a total load demand of 259 MW supplied by five generators. The loads were classified as critical or non-critical. Three case studies were considered: 1. a case in which all five generators supplied the loads, 2. a case in which one generator was replaced by solar PV with the same generating capacity, and 3. a case in which two generators were replaced by both solar PV and wind turbine respectively. The decrease in net present cost (NPC), Levelized cost (COE), and operating cost (OC) demonstrate the efficacy of the proposed system topologies with various forms of RES.

关键词： Renewable energy sources Wind Costs systems architecture Generators Software Wind turbines

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