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Robust Deterministic Abstractions for Supervising Discrete-Time Continuous Systems 18th

Robust Deterministic Abstractions for Supervising Discrete-T...

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18th International Conference on Reachability Problems (RP)

作者： Priser, Gwendal Vanneaux, Elena Frehse, Goran Inst Polytech Paris ENSTA Paris U2IS Paris France

ISBN: (纸本)9783031726200;9783031726217

We present a method for constructing discrete abstractions for discrete-time, continuous-state systems. Related approaches construct a discrete bisimulation, which leaves little room for non-determinism in the outputs and quickly leads to highly complex models since all concrete behavior is covered. Our approach is to relax these requirements and build a satisficing solution: a discrete abstraction that is deterministic, robust, and as complete as possible under the given parameters. This allows us to balance granularity and computational feasibility. We leverage linearization and linear feedback control to extend the approach from globally contractive systems to systems with contractive cycles. The resulting abstraction directly induces a supervisor policy. The approach is illustrated with numerical experiments and has potential applications in various domains where system safety and reversibility are essential.

关键词： continuous dynamical systems discrete abstraction robustness supervision

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M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms 45th

M(otion)-Mode Based Prediction of Ejection Fraction Using Ec...

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45th Annual Conference of the German-Association-for-Pattern-Recognition (DAGM GCPR)

作者： Ozkan, Ece Sutter, Thomas M. Hu, Yurong Balzer, Sebastian Vogt, Julia E. MIT Dept Brain & Cognit Sci E25-618 Cambridge MA 02139 USA Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Swiss Fed Inst Technol Dept Informat Technol & Elect Engn Zurich Switzerland Swiss Fed Inst Technol Dept Biosyst Sci & Engn Zurich Switzerland

ISBN: (纸本)9783031546044;9783031546051

Early detection of cardiac dysfunction through routine screening is vital for diagnosing cardiovascular diseases. An important metric of cardiac function is the left ventricular ejection fraction (EF), where lower EF is associated with cardiomyopathy. Echocardiography is a popular diagnostic tool in cardiology, with ultrasound being a low-cost, real-time, and non-ionizing technology. However, human assessment of echocardiograms for calculating EF is time-consuming and expertise-demanding, raising the need for an automated approach. In this work, we propose using the M(otion)-mode of echocardiograms for estimating the EF and classifying cardiomyopathy. We generate multiple artificial M-mode images from a single echocardiogram and combine them using off-the-shelf model architectures. Additionally, we extend contrastive learning (CL) to cardiac imaging to learn meaningful representations from exploiting structures in unlabeled data allowing the model to achieve high accuracy, even with limited annotations. Our experiments show that the supervised setting converges with only ten modes and is comparable to the baseline method while bypassing its cumbersome training process and being computationally much more efficient. Furthermore, CL using M-mode images is helpful for limited data scenarios, such as having labels for only 200 patients, which is common in medical applications.

关键词： Echocardiography M-mode Ultrasound Ejection Fraction computer Assisted Diagnosis (CAD)

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Cryptanalysis of Short and Provable Secure Lattice-Based Signature Scheme 1

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13th International Conference on Security, Privacy, and Applied Cryptographic Engineering (SPACE)

作者： Kumar, Ramakant Padhye, Sahadeo Rawal, Swati Motilal Nehru Natl Inst Technol Allahabad Dept Math Prayagraj 211004 India EY Global 6 More Londan Pl London SE12AF England

ISBN: (数字)9783031515835

ISBN: (纸本)9783031515828;9783031515835

Fenghe and Zhenhua proposed a short and provable secure lattice-based signature scheme in the standard model in 2016. Their aim was to construct a short signature without using any lattice delegation technique. They claimed that their scheme is strongly unforgeable under the hardness of the shortest integer solution (SIS) problem. In this article, we highlight a flaw in the signature scheme proposed by Fenghe and Zhenhua. We show that an adversary can generate a valid message-signature pair by solving a linear system of equations. We also show that the design of the scheme leaks some information about the secret key.

关键词： Lattice-Based Cryptography Cryptanalysis Short Signature Signature Scheme Standard Model

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Investigating Avalanche Risk Impact on Accommodation Facilities in the Municipalities of Abruzzo Region 24th

Investigating Avalanche Risk Impact on Accommodation Facilit...

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24th International Conference on Computational science and Its Applications (ICCSA)

作者： Pietrangeli, Sara Guisa, Donatella Fiorini, Lorena Saganeiti, Lucia Univ Aquila Dept Civil Construct Architectural & Environm Eng Via G Gronchi 18 I-67100 Laquila Italy

ISBN: (纸本)9783031652844;9783031652851

The increase in outdoor recreational activities, particularly ski tourism and trekking, has led to a significant intensification of anthropic presence in mountain regions, with a consequent growth in demand for facilities and infrastructure. This trend, also observed in Abruzzo region, has caused the urban expansion, in and near avalanche-prone areas, increasing the risk to human settlements. Catastrophic events, such as the tragic disaster involving the Hotel Rigopiano in the municipality of Farindola (Abruzzo, Italy) on 18 January 2017, highlight the urgency of addressing avalanche risk. Avalanches, defined as a sudden instability of the snowpack and its subsequent sliding down on a slope, pose a serious threat to settlements, residential areas and infrastructure. Legislative measures, such as the Regional Law No. 47/92 and the Avalanche Hazard Location Map, aim to mitigate avalanche risk by regulating land use in vulnerable areas. The methodology developed in this article focuses on the construction of static and dynamic risk scenarios using user-friendly data, contributing to a wider multi-risk analysis framework. Furthermore, the work presented is aligned with the goals of the SICURA project, which aims to build risk scenarios within a global framework of smart security technologies.

关键词： Avalanche risk Urban planning SICURA project Accommodation facilities

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Presshammer: Rowhammer and Rowpress Without Physical Address Information 21st

Presshammer: Rowhammer and Rowpress Without Physical Address...

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21st Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA)

作者： Juffinger, Jonas Neela, Sudheendra Raghav Heckel, Martin Schwarz, Lukas Adamsky, Florian Gruss, Daniel Graz Univ Technol Graz Austria Hof Univ Appl Sci Hof Germany

ISBN: (纸本)9783031641701;9783031641718

Modern DRAM is susceptible to fault attacks that undermine the entire system's security. The most well-studied disturbance effect is Rowhammer, where an attacker repeatedly opens and closes (i.e., hammers) different rows, which can lead to bitflips in adjacent rows. Different hammering strategies include double-sided, hammering two rows sandwiching a victim row, and one-location, hammering a single row. One-location Rowhammer requires no physical address information, as any location in memory is mapped to a DRAM row, and no relation between rows is required for hammering. The recently discovered Rowpress differs from Rowhammer by not hammering rows but keeping them open longer, evident by a disjoint set of affected memory locations. In this paper, we examine the differences between four attack variants: one-location Rowhammer, a one-location Rowpress variant we developed, double-sided Rowhammer, and double-sided Rowpress on a set of 12 DDR4 modules. Our methodology is to hammer and press the exact same set of physical memory locations in all attack variants. Surprisingly, our results show that on 4 out of 12 DDR4 modules, we were only able to reproduce double-sided Rowhammer but none of the other attack variants. On 2 DDR4 modules, we were able to reproduce all attack variants. We find that the number of unique bitflip locations ranges from 161 to 15 612, when hammering the exact same set of physical memory locations. Our one-location Rowhammer attack induces roughly the same amount of bitflips as double-sided Rowhammer, however, only 61.8% of bitflip locations overlap. We explain this by one-location Rowhammer inducing bitflips due to the Rowhammer as well as the Rowpress effect, making the differentiation of both methods difficult, therefore, calling it Presshammer. Based on our observed bitflips, we develop the first end-to-end one-location Rowpress attack. One-location Rowpress requires only minimal physical address information that an attacker can acquire throu

关键词： Side channel attack

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Partial-Labeled Abdominal Organ and Cancer Segmentation via Cascaded Dual-Decoding U-Net 1

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Conference of the International Challenge on Fast, Low- Resource and Accurate Organ and Pan-Cancer Segmentation in Abdomen CT (FLARE)

作者： Ye, Zhiyu Zheng, Hairong Zhang, Tong Shenzhen Inst Adv Technol Shenzhen Peoples R China Peng Cheng Lab Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (数字)9783031587764

ISBN: (纸本)9783031587757;9783031587764

In the FLARE2023 challenge, we developed a cascaded dual-decoding U-Net framework to address the complex task of partial-labeled abdominal organ and cancer segmentation. Initially, we explored the potential of 3D transformer-based models but transitioned to 2D U-Net solutions due to computational resource and inference time constraints. We first trained separate 3D models for cancer and full-organ segmentation using data that included labels for both cancer and full organs. Subsequently, we generated pseudo labels for unlabeled and partially labeled data based on these initial models. To enable a single model to effectively learn and infer both organ and cancer labels within images, we designed a dual-decoding structure based on the 2D U-Net architecture. Our training process involved several steps with various subsets of the training data. By comparing our model trained without unlabeled data, we discussed the impact of unlabeled data and its pseudo labels on the experimental results. Our method, the version trained without unlabeled data, achieved an average DSC score of 83.22% for organs and 33.22% for lesions on the validation set. The average running time and area under the GPU memory-time curve were 33.8 s and 50066.25 MB, respectively. The codes has been open-sourced to https://***/OpenMedIA/pclmedia_FLARE23.

关键词： FLARE2023 Partial-labeled abdominal organ and cancer segmentation U-Net

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Blurry Boundary Segmentation with Semantic-Aware Feature Learning 28th

Blurry Boundary Segmentation with Semantic-Aware Feature Lea...

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28th Annual Conference on Medical Image Understanding and Analysis (MIUA)

作者： Xiao, Qiuyu Nie, Dong Univ North Carolina Chapel Hill Dept Comp Sci Chapel Hill NC 27599 USA

ISBN: (纸本)9783031669576;9783031669583

Encoder-decoder architectures are widely adopted for medical image segmentation tasks. These models utilize lateral skip connections to capture and fuse both semantic and resolution information in deep layers, enhancing segmentation accuracy. However, in many applications, such as images with blurry boundaries, these models often struggle to precisely locate complex boundaries and segment tiny isolated parts due to the fuzzy information passed through the skip connections from the encoder layers. To solve this challenging problem, we first analyze why simple skip connections are insufficient for accurately locating indistinct boundaries. Based on this analysis, we propose a semantic-guided encoder feature learning strategy. This strategy aims to learn high-resolution semantic encoder features, enabling more accurate localization of blurry boundaries and enhancing the network's ability to selectively learn discriminative features. Additionally, we further propose a soft contour constraint mechanism to model the blurry boundary detection. Experimental results on real clinical datasets demonstrate that our proposed method achieves state-of-the-art segmentation accuracy, particularly in regions with blurry boundaries. Further analysis confirms that our proposed network components significantly contribute to performance improvements. Experiments on additional datasets validate the generalization ability of our proposed method.

关键词： Semantics

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A Backward-Characteristics Monotonicity Preserving Method for Stiff Transport Problems 24th

A Backward-Characteristics Monotonicity Preserving Method fo...

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24th International Conference on Computational science (ICCS)

作者： Asmouh, Ilham Ouardghi, Abdelouahed Univ Innsbruck Inst Math Technikerstr 13 A-6020 Innsbruck Austria Forschungszentrum Julich Julich Supercomp Ctr Julich Germany

ISBN: (纸本)9783031637858;9783031637834

Convection-diffusion problems in highly convective flows can exhibit complicated features such as sharp shocks and shear layers which involve steep gradients in their solutions. As a consequence, developing an efficient computational solver to capture these flow features requires the adjustment of the local scale difference between convection and diffusion terms in the governing equations. In this study, we propose a monotonicity preserving backward characteristics scheme combined with a second-order BDF2-Petrov-Galerkin finite volume method to deal with the multiphysics nature of the problem. Unlike the conventional Eulerian techniques, the two-step backward differentiation procedure is applied along the characteristic curves to obtain a second-order accuracy. Numerical results are presented for several benchmark problems including sediment transport in coastal areas. The obtained results demonstrate the ability of the new algorithm to accurately maintain the shape of the computed solutions in the presence of sharp gradients and shocks.

关键词： Flow transport Backward characteristics method Petrov-Galerkin finite volume method Backward differentiation formula (BDF2)

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SMT-Based Symbolic Model-Checking for Operator Precedence Languages 36th

SMT-Based Symbolic Model-Checking for Operator Precedence La...

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36th International Conference on computer-Aided Verification (CAV)

作者： Chiari, Michele Geatti, Luca Gigante, Nicola Pradella, Matteo TU Wien Treitlstr 3 A-1040 Vienna Austria Univ Udine Udine Italy Free Univ Bozen Bolzano Bolzano Italy Politecn Milan Milan Italy

ISBN: (纸本)9783031656262;9783031656279

Operator Precedence Languages (OPL) have been recently identified as a suitable formalism for model checking recursive procedural programs, thanks to their ability of modeling the program stack. OPL requirements can be expressed in the Precedence Oriented Temporal Logic (POTL), which features modalities to reason on the natural matching between function calls and returns, exceptions, and other advanced programming constructs that previous approaches, such as Visibly Pushdown Languages, cannot model effectively. Existing approaches for model checking of POTL have been designed following the explicit-state, automata-based approach, a feature that severely limits their scalability. In this paper, we give the first symbolic, SMT-based approach for model checking POTL properties. While previous approaches construct the automaton for both the POTL formula and the model of the program, we encode them into a (sequence of) SMT formulas. The search of a trace of the model witnessing a violation of the formula is then carried out by an SMT-solver, in a Bounded Model Checking fashion. We carried out an experimental evaluation, which shows the effectiveness of the proposed solution.

关键词： SMT-based Model Checking Tree-shaped Tableau Temporal Logic Operator Precedence Languages

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UPDN: Pedestrian Detection Network for Unmanned Aerial Vehicle Perspective 40th

UPDN: Pedestrian Detection Network for Unmanned Aerial Vehic...

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40th computer Graphics International Conference (CGI)

作者： Jiang, Minghua Wang, Yulin Guo, Mengsi Liu, Li Yu, Feng Wuhan Text Univ Sch Comp Sci & Artificial Intelligence Wuhan 430200 Peoples R China Engn Res Ctr Hubei Prov Clothing Informat Wuhan 430200 Peoples R China

ISBN: (纸本)9783031500749;9783031500756

Pedestrian detection for Unmanned Aerial Vehicle (UAV) perspective has significant potential in the fields of computer vision and intelligent systems. However, current methods have some limitations in terms of accuracy and real-time detection of small targets, which severely affects their practical application. To address these challenges, we propose UPDN, a novel network designed to improve detection comprehensive performance while maintaining high speed as much as possible. To achieve this objective, UPDN incorporates two key modules: the Spatial Pyramid Convolution and Pooling Module (SPCPM) and the Efficient Attention Module (EAM). The SPCPM effectively captures multi-scale features from pedestrian regions, enabling better detection of small targets. The EAM optimizes network operations by selectively focusing on informative regions, enhancing the overall efficiency of the detection process. Experimental results on the constructed dataset demonstrate that UPDN outperforms other classic detection methods. It achieves state-of-the-art results in terms of both Average Precision (AP) and F1 score, achieving a detection speed of 107.37 frames per second (FPS). In summary, UPDN provides an efficient and reliable solution for pedestrian detection from a UAV perspective, offering a feasible approach for real-world applications.

关键词： Pedestrian detection UAV Small target

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