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arXiv 2021年

作者： Wang, Yixiang Liu, Jiqiang Chang, Xiaolin Wang, Jianhua Rodríguez, Ricardo J. Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China Dept. of Computer Science and Systems Engineering University of Zaragoza

White-box Adversarial Example (AE) attacks towards Deep Neural Networks (DNNs) have a more powerful destructive capacity than black-box AE attacks in the fields of AE strategies. However, almost all the white-box approaches lack interpretation from the point of view of DNNs. That is, adversaries did not investigate the attacks from the perspective of interpretable features, and few of these approaches considered what features the DNN actually learns. In this paper, we propose an interpretable white-box AE attack approach, DI-AA, which explores the application of the interpretable approach of the deep Taylor decomposition in the selection of the most contributing features and adopts the Lagrangian relaxation optimization of the logit output and Lp norm to further decrease the perturbation. We compare DI-AA with six baseline attacks (including the state-of-the-art attack AutoAttack) on three datasets. Experimental results reveal that our proposed approach can 1) attack non-robust models with comparatively low perturbation, where the perturbation is closer to or lower than the AutoAttack approach;2) break the TRADES adversarial training models with the highest success rate;3) the generated AE can reduce the robust accuracy of the robust black-box models by 16% to 31% in the black-box transfer attack. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Modeling supports the implementation of urban greening as a response to the challenges of sustainable spatial planning

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Journal of Environmental Management 2025年 386卷 125648页

作者： Kim, Eun Sub Hyun, Jung Hee Kim, Na Yeon Heo, Su Jeong Kim, Da Seul Lee, Dong Kun Low-Carbon and Climate Impact Research Centre School of Energy and Environment City University of Hong Kong Tat Chee Ave Hong Kong Kowloon Tong China Systemic Risk and Resilience Research Group Advancing Systems Analysis International Institute for Applied Systems Analysis Austria Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Program Seoul National University Seoul08826 Korea Republic of Forest Disaster & Environment Department National Institute of Forest Science Seoul Korea Republic of Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of

Urban greening is critical for sustainable urban development, climate change mitigation, and biodiversity conservation. However, the effectiveness of urban greening varies depending on the specific goals (e.g., enhancing biodiversity, reducing urban heat, or both) and their spatial implementation. To address the spatial variability in the effectiveness of greening, we propose a spatial decision support model based on the non-dominated sorting genetic algorithm-II (NSGA-II). This model aims to optimize urban greening locations to maximize biomass density, mitigate urban heat stress, and improve landscape connectivity. Applied to Suwon City, South Korea, the model's effectiveness was evaluated against a business-as-usual (BAU) scenario across four scenarios: connectivity-based, biomass density-based, heat stress-based, and an integrated-based scenario. The integrated approach, balancing trade-offs between ecological benefits and implementation costs, outperformed the BAU scenario by 8.84 %. Despite highlighting a weaker correlation with heat stress mitigation, this outcome indicates significant improvements in biomass density and landscape connectivity. Our findings underscore the necessity of an integrated planning approach to urban greening, as it can contribute toward attaining urban development goals. Additionally, by proposing an app-based model for policymakers, our outputs should enable the reconciliation of multiple environmental objectives in urban landscapes. © 2025 Elsevier Ltd

关键词： Biotic

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Nature-Based Solutions Can Potentially Contribute to Biomass Density, Heat Stress Mitigation, and Biodiversity

SSRN

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SSRN 2023年

作者： Kim, Eun Sub Hyun, Jung Hee Kim, Na Yeon Heo, Su Jeong Kim, Shin Woo Kim, Da Sle Lee, Dong Kun Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Program Seoul National University Seoul08826 Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of Systemic Risk and Resilience Research Group Advancing Systems Analysis International Institute for Applied Systems Analysis Austria Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of

Nature-based solutions (NBS) are actions to protect, sustainably manage, or restore natural ecosystems. They are increasingly recognized worldwide as a key strategy for sustainable development, integrating climate change adaptation and mitigation and biodiversity conservation. NBS is fundamental to the quality of life of residents, and urban planning often includes strategies that are directly or indirectly related to greening. Although numerous studies have been conducted to quantitatively evaluate the benefits of NBS, analysis of the potential effect of NBS remains insufficient. Therefore, we developed a spatial decision-making support model that optimizes the location of NBS on multiple effects (biomass density, urban heat stress mitigation, and landscape connectivity) using a Non-Sorting dominated Genetic Algorithm-II (NSGA-II). Potential was assessed by comparing the NBS plan considering co-benefits with NBS strategy scenarios focused on individual objectives connectivity, biomass density, heat stress based scenario(CBS, BBS, and HBS). The model was applied to Suwon City, South Korea, demonstrating the potential of an integrated approach to maximize co-benefits simultaneously. The analysis revealed a trade-off between NBS benefits and implementation costs, with performance improvement in one objective often leading to decreased performance in others. Correlation analysis revealed significant positive correlations among the three objectives, with heat stress showing the lowest correlation. Simulations under four distinct scenarios highlighted the diverse potential arrangements of NBS and their effects. An integrated strategy demonstrated a consistently high overall value (a 221% improvement), which proved to be the most efficient approach when considering all aspects collectively. This study underscores the potential benefits of integrating multiple objectives into urban green space planning, thereby providing valuable insights for sustainable urban development.

关键词： Biodiversity

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ASD Detection using Higuchi’s Fractal Dimension from EEG

ASD Detection using Higuchi’s Fractal Dimension from EEG

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IEEE International Conference on Biomedical Engineering, computer and Information Technology for Health

作者： Zahrul Jannat Peya Md. Ferdous M. A. H. Akhand Mohammed Golam Zilani Nazmul Siddique Dept. of Computer Science and Engineering Khulna University of Engineering & Technology Khulna Bangladesh James Cook University Queensland Australia School of Computing Engineering and Intelligent Systems Ulster University United Kingdom

ISBN: (数字)9781665466219

ISBN: (纸本)9781665466226

Autism or Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder marked by repetitive and characteristic patterns of behavior as well as social communication and interaction impairments. Nowadays ASD is a great concern worldwide and its detection is an important issue for the better treatment. As ASD is neurodevelopmental disorder, brain signals play, especially electroencephalography (EEG), is shown potential sources for ASD detection. There are different approaches for ASD detection with processing and/or transforming EEG signals. This study investigated ASD detection employing fractal dimension measure on EEG data. Higuchi’s Fractal Dimension (HFD) is measured in resting-state eyes-closed EEG recording of 25 subjects. It is identified that HFD is sensitive to the brain activity and ASD detection is possible from HFD values.

关键词： Autism Brain Electric potential Psychology Electroencephalography Fractals Complexity theory

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A Data logger for educational purposes of a laboratory chemical reactor: an IoT approach

A Data logger for educational purposes of a laboratory chemi...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： José Lima Thadeu Brito Olga Ferreira Maria J. Afonso Vítor H. Pinto José A. Carvalho Paulo Costa Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Laboratório Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal Centre for Robotic in Industry and Intelligent Systems Institute for Systems and Computer Engineering Technology and Science (INESC-TEC) Porto Portugal CeDRI SusTEC INESC-TEC Faculty of Engineering of University of Porto (FEUP) Porto Portugal SusTEC ESTiG Instituto Politécnico de Bragança Bragança Portugal ARISE & ECE Dept. Research Center for Systems and Technologies (SYSTEC) FEUP CeDRI SusTEC INESC-TEC FEUP

This paper presents the development of an acquisition system and data logger from an existing set of three continuous stirred-tank reactors in series. The reactors are currently used in chemical engineering educational laboratories to perform kinetic and tracer experiments. In this sense, to accomplish the store data process, the volumetric flow rate and the concentration of tracer, reactants and/or products of the reaction must be acquired as a function of time. In the original experimental setup, only the signal conditioning system was operational, while the acquisition, visualization, and control systems were obsolete and damaged. Thus, a new system composed of an interface and real-time acquisition data is proposed alongside preserving the main reactor structure. A graphical user interface and the automation of the various actuators were developed based on worldwide usage and low cost, respectively. This system, based on a common 8-bit microcontroller and an application developed in Lazarus, allows the storage of the acquired data in a time-series database. In this way, students can analyze the results later or in real time. Moreover, remote access allows controlling the reactor and getting data by the Internet of Things (IoT) resources. Additionally, the proposed system using IoT allows data to be shared with the community as a dataset.

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Non-Linear Age of Information: An Energy Efficient Receiver-Centric Approach

arXiv

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arXiv 2021年

作者： Miridakis, Nikolaos I. Tsiftsis, Theodoros A. Yang, Guanghua The Institute of Physical Internet School of Intelligent Systems Science & Engineering Jinan University Zhuhai Campus Zhuhai519070 China The Dept. of Informatics and Computer Engineering University of West Attica Aegaleo 12243 Greece

The age of information (AoI) performance metric for point-to-point wireless communication systems is analytically studied under Rician-faded channels and when the receiver is equipped with multiple antennas. The general scenario of a non-linear AoI function is considered, which includes the conventional linear AoI as a special case. The stop-and-wait transmission policy is adopted, where the source node samples and then transmits new data only upon the successful reception of previous data. This approach can serve as a performance benchmark for any queuing system used in practice. New analytical and closed-form expressions are derived with respect to the average AoI and average peak AoI for the considered system configuration. We particularly focus on the energy efficiency of the said mode of operation, whereas some useful engineering insights are provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

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A new smart-cropping pipeline for prostate segmentation using deep learning networks

arXiv

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arXiv 2021年

作者： Zaridis, Dimitrios G. Mylona, Eugenia Tachos, Nikolaos S. Marias, Kostas Papanikolaou, Nikolaos Tsiknakis, Manolis Fotiadis, Dimitrios I. The Dept. of Biomedical Research FORTH-IMBB Ioannina Greece The Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering University of Ioannina IoanninaGR 45110 Greece The Institute of Computer Science FORTH Heraklion Greece The Dept. of Electrical and Computer Engineering Hellenic Mediterranean University Greece The Centre for the Unknown Champalimaud Foundation Clinical Computational Imaging Group Lisbon Portugal Crete Heraklion Greece The Dept. of Biomedical Research Institute of Molecular Biology and Biotechnology FORTH Ioannina Greece The Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina IoanninaGR 45110 Greece

Prostate segmentation from magnetic resonance imaging (MRI) is a challenging task. In recent years, several network architectures have been proposed to automate this process and alleviate the burden of manual annotation. Although the performance of these models has achieved promising results, there is still room for improvement before these models can be used safely and effectively in clinical practice. One of the major challenges in prostate MR image segmentation is the presence of class imbalance in the image labels where the background pixels dominate over the prostate. In the present work we propose a DL-based pipeline for cropping the region around the prostate from MRI images to produce a more balanced distribution of the foreground pixels (prostate) and the background pixels and improve segmentation accuracy. The effect of DL-cropping for improving the segmentation performance compared to standard center-cropping is assessed using five popular DL networks for prostate segmentation, namely U-net, U-net+, Res Unet++, Bridge U-net and Dense U-net. The proposed smart-cropping outperformed the standard center cropping in terms of segmentation accuracy for all the evaluated prostate segmentation networks. In terms of Dice score, the highest improvement was achieved for the Unet+ and ResU-net++ architectures corresponding to 8.9% and 8%, respectively. © 2021, CC BY.

关键词： Image segmentation

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Healthier and Independent Living of the Elderly: Interoperability in a Cross-Project Pilot

Healthier and Independent Living of the Elderly: Interoperab...

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2022 Interoperability for Enterprise systems and Applications Workshops, I-ESA Workshops 2022

作者： Agostinho, Carlos Pimenta, Andreia Marques, Maria Tsiouris, Kostas M. Kalatzis, Fanis Nikitas, Christos Iliadou, Eleftheria Occhipinti, Mattia Kouris, Ioannis Koutsouris, Dimitrios Basdekis, Ioannis Koloutsou, Konstantina Gallo, Luigi de Pietro, Giueppe Jardim-Goncalves, Ricardo FCT-Campus Caparica2829-516 Portugal NOVA School of Science and Technology Caparica2829-516 Portugal Secretaria Regional de Saúde e Ptroteção Civil Rua da Carreira nº107 Funchal9000-042 Portugal Unit of Medical Technology and Intelligent Information Systems Dept. of Material Science and Engineering University of Ioannina IoanninaGR45110 Greece National Kapodistrian University of Athens First Department of Otolaryngology-Head and Neck Surgery ‘Hippokrateio’ General Hospital Athens Greece Università degli Studi di Milano Computer Science Department Milan Italy Biomedical Engineering Laboratory Institute of Communication and Computer Systems National Technical University of Athens Heroon Polytechneiou 9 15780 Greece SPHYNX Technology Solutions AG Zug Switzerland National Research Council of Italy Via P. Bucci cubo 8/9C Rende87036 Italy

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by anyone owning a smartphone and parameters such as heart rate, step counts, calorie intake, sleep quality, can be collected and used not only to monitor and improve the individual’s health condition but also to prevent illnesses. However, for the benefits of e-health to take place, digital health data, either Electronic Health Records (EHR) or sensor data from the IoMT, must be shared, maintaining privacy and security requirements but unlocking the potential for research an innovation throughout EU. This paper demonstrates the added value of such interoperability requirements, and a form of accomplishing them through a cross-project pilot. © 2022 CEUR-WS. All rights reserved.

关键词： Interoperability

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Evaluation of Fatigue and Attention Levels in Multi-target Scenario using CNN

Evaluation of Fatigue and Attention Levels in Multi-target S...

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2020 International computer Symposium, ICS 2020

作者： Sandeep Vara Sankar, D Ko, Li-Wei National Chiao Tung University International Ph.D Program in Interdisciplinary Neuroscience Dept. of Biological Science and Technology Hsinchu Taiwan National Chiao Tung University Center for Intelligent Drug Systems and Smart Bio-Devices Department of Biological Science and Technology Hsinchu Taiwan

ISBN: (纸本)9781728192550

Fatigue is a behavioral phenomenon that occurs when a user conducts focused mental activity for a prolonged duration resulting in performance errors or lapse. This paper presents an electroencephalogram (EEG)-based fatigue and attention level detection using 2-dimensional convolutional neural networks (2D-CNN). The experimental paradigm was designed to identify and detect a target object from a multi- target scenario. The results show that our proposed model provides a classification accuracy of 86.12%, which is ~18%, ~16% and ~10% higher than the Bayesian linear discriminant analysis (BLDA), support vector machine (SVM) and bootstrap aggregating (bagging tree) algorithms. Further, the decreased session-wise accuracy levels observed for each subject after the 4th experimental session postulates cognitive state disparities were caused due to increased fatigue and dropped attention levels. These biomarkers were assessed by comparing the resting theta and alpha band powers with the rapid serial visual presentation (RSVP) performance of the later sessions (sessions 5 to 7). The results show an inverse relationship between the RSVP classification performance and the resting EEG power, validating that the subjects' performance is affected by the physiological state biomarkers like fatigue and attention for prolonged brain-computer interface (BCI) experiments. Our findings demonstrate that the resting theta and alpha band powers can be considered as indicative measures to interpret mental fatigue and attention deficit problems. © 2020 IEEE.

关键词： Brain computer interface

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Two-sided matching markets in the ELLIS 2020 PhD program

arXiv

引用

arXiv 2021年

作者： Mordig, Maximilian Vecchia, Riccardo Della Cesa-Bianchi, Nicolò Schölkopf, Bernhard Max-Planck Institute for Intelligent Systems Tübingen Germany ETH Zürich Switzerland Artificial Intelligence Lab Bocconi University Milano Italy Dept. of Computer Science DSRC University of Milan Italy

The ELLIS PhD program is a European initiative that supports excellent young researchers by connecting them to leading researchers in AI. In particular, PhD students are supervised by two advisors from different countries: an advisor and a co-advisor. In this work we summarize the procedure that, in its final step, matches students to advisors in the ELLIS 2020 PhD program. The steps of the procedure are based on the extensive literature of two-sided matching markets and the college admissions problem [Knuth and De Bruijn, 1997, Gale and Shapley, 1962, Roth and Sotomayor, 1992]. We introduce PolyGS, an algorithm for the case of two-sided markets with quotas on both sides (also known as many-to-many markets) which we use throughout the selection procedure of pre-screening, interview matching and final matching with advisors. The algorithm returns a stable matching in the sense that no unmatched persons prefer to be matched together rather than with their current partners (given their indicated preferences). Roth [1984] gives evidence that only stable matchings are likely to be adhered to over time. Additionally, the matching is student-optimal. Preferences are constructed based on the rankings each side gives to the other side and the overlaps of research fields. We present and discuss the matchings that the algorithm produces in the ELLIS 2020 PhD program. © 2021, CC BY.

关键词： Students

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