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Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2

作者： Talledo, D.A. Miano, A. Di Carlo, F. Bonano, M. Mele, A. Stella, A. Lanari, R. Meda, A. Prota, A. Saetta, A. Department of Architecture and Arts University IUAV of Venice Dorsoduro 2206 Venice30123 Italy Department of Structures for Engineering and Architecture University of Naples Federico II Via Claudio 21 Naples80125 Italy Department of Civil Engineering and Computer Science Engineering University of Rome "Tor Vergata" Via del Politecnico 1 Rome00133 Italy - Institute for Electromagnetic Sensing of the Environment Via Diocleziano 328 Naples80124 Italy

ISBN: (纸本)9783031391088

Structural Health Monitoring (SHM) is a field of increasing interest and worthy of new approaches and innovative applications. Italian territory is rich of architectural and cultural heritage that needs to be managed, monitored and conserved. This work presents a possible framework for the monitoring of such heritage that is suitable for large scale analyses and permits a fast and quick assessment, useful to the stakeholders responsible for its management. The proposed algorithms are based on an appealing technique, that gained popularity during the last years in the field of SHM, represented by the advanced multi-temporal differential synthetic aperture radar interferometry. Although the exploitation of these technique for the SHM of architectural and cultural heritage is still an open issue, different applications available in literature show promising potentialities. The algorithms and procedures proposed in this work are applied to a case study area located in the historic centre of Rome (Italy) to show the potentialities of the method. To this aim, COSMO-SkyMed ascending and descending datasets are processed applying the small baseline method obtaining deformation time series and mean velocity maps of the permanent scatterers located in the investigated area, for both geometry acquisitions. The information from these datasets are then elaborated and integrated with information from other data sources in order to provide a first estimation of potentially critical elements within the analyzed stock at urban level. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Structural health monitoring

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ArmorCLIP: A Hybrid Defense Strategy for Boosting Adversarial Robustness in Vision-Language Models

arXiv

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arXiv 2024年

作者： Li, Yijun Liang, Yuhan Niu, Yumeng Shen, Qianhe Liu, Hangyu Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China Faculty of Engineering University of Bristol BristolBS8 1TH United Kingdom Computer Science and Technology Beijing University of Civil Engineering and Architecture Beijing102612 China Computer Science Mathematics & Statistics University of Toronto Mississauga MississaugaL5L 1C6 Canada Xi'an Tieyi ICC Shanxi Xian710054 China

The robustness of Vision-Language Models (VLMs) such as CLIP is critical for their deployment in safety-critical applications like autonomous driving, healthcare diagnostics, and security systems, where accurate interpretation of visual and textual data is essential. However, these models are highly susceptible to adversarial attacks, which can severely compromise their performance and reliability in real-world scenarios. Previous methods have primarily focused on improving robustness through adversarial training and generating adversarial examples using models like FGSM, AutoAttack, and DeepFool. However, these approaches often rely on strong assumptions, such as fixed perturbation norms or predefined attack patterns, and involve high computational complexity, making them challenging to implement in practical settings. In this paper, we propose a novel adversarial training framework that integrates multiple attack strategies and advanced machine learning techniques to significantly enhance the robustness of VLMs against a broad range of adversarial attacks. Experiments conducted on real-world datasets, including CIFAR-10 and CIFAR-100, demonstrate that the proposed method significantly enhances model robustness. The fine-tuned CLIP model achieved an accuracy of 43.5% on adversarially perturbed images, compared to only 4% for the baseline model. The neural network model achieved a high accuracy of 98% in these challenging classification tasks, while the XGBoost model reached a success rate of 85.26% in prediction tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Impact of Image Sensor Input Faults on Pruned Neural Networks for Object Detection

Impact of Image Sensor Input Faults on Pruned Neural Network...

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IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems

作者： Yizhi Chen Wenyao Zhu Dejiu Chen Omar Mohammed Parthib Khound Zhonghai Lu School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Industrial Engineering and Management KTH Royal Institute of Technology Stockholm Sweden Chair of Reliability of Technical Systems and Electrical Measurement University of Siegen Siegen Germany

ISBN: (数字)9798350366884

ISBN: (纸本)9798350366891

Object detection is one of the most fundamental problems in computer vision, and image sensors are commonly used for this. In this paper, we present the impact of image sensor faults on pruned neural networks for object detection. We compare the error sensitivities of networks after network slimming, networks after magnitude-based pruning, and native compact models. We also explore different spatial fault types with three intensities. Furthermore, we have developed a temporal error model based on realistic aging image sensor faults. The results illuminate that the performance on clean images is important as the mean Average Precision (mAP) experiences a decrease with an increase in injected faults. Additionally, we demonstrate that the size of the model does not invariably yield a decisive impact on error tolerance when comparing small models such as pruned models and native compact models.

关键词： Image sensors Performance evaluation Fault tolerance Sensitivity Neural networks Fault tolerant systems Object detection Aging Very large scale integration Transformers

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F3D: Accelerating 3D Convolutional Neural Networks in Frequency Space Using ReRAM 21

F3D: Accelerating 3D Convolutional Neural Networks in Freque...

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Proceedings of the 58th Annual ACM/IEEE Design Automation Conference

作者： Bosheng Liu Zhuoshen Jiang Wu Jigang Xiaoming Chen Yinhe Han Peng Liu School of Computer Science and Technology Guangdong University of Technology China and State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences Beijing China School of Computer Science and Technology Guangdong University of Technology China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781665432740

3D convolutional neural networks (CNNs) are widely deployed in video analysis. Fast algorithms such as fast Fourier transforms (FFTs) are gaining popularity in reducing computation complexity for their superior capability of replacing convolutions with simpler element-wise multiplications. Conventional frequency-domain dedicated accelerators employ memory hierarchy organization for high throughput but at the expensive costs of a significant amount of data movements and energy consumptions. This paper presents F3D, a processing-in-memory frequency-domain accelerator using resistive random access memory (ReRAM). F3D supports frequency-domain complex number multiplications directly in ReRAM-based crossbar architecture. We alleviate the overheads of redundant data movements in ReRAM-based complex number multiplications by data reuse and the inherent symmetry of inputs in the frequency space. Evaluation results demonstrate that F3D outperforms state-of-the-art accelerators with significant improvements in performance and energy efficiency.

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An Efficient Vectorization Scheme for Stencil Computation

An Efficient Vectorization Scheme for Stencil Computation

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Kun Li Liang Yuan Yunquan Zhang Yue Yue Hang Cao State Key Laboratory of Computer Architecture Chinese Academy of Sciences Institute of Computing Technology Beijing School of Computer Science and Technology University of Chinese Academy of Sciences Beijing

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization and tiling techniques, aiming at exploiting the in-core data parallelism and data locality respectively. In this paper, the downsides of existing vectorization schemes are analyzed. Briefly, they either incur data alignment conflicts or hurt the data locality when integrated with tiling. Then we propose a novel transpose layout to preserve the data locality for tiling and reduce the data reorganization overhead for vectorization simultaneously. To further improve the data reuse at the register level, a time loop unroll-and-jam strategy is designed to perform multistep stencil computation along the time dimension. Experimental results on the AVX2 and AVX-S12 CPUs show that our approach obtains a competitive performance with the classic vectorization methods (Auto Vectorization and Data Reorganization), state-of-the-art compilers (Pluto and SDSL), and highly-optimized work (DLT and Tessellation).

关键词： Concurrent computing Distributed processing Layout Parallel processing Registers Computational efficiency Kernel

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Theoretical Assessment of Environmental Factors and Untreated Infectious Individuals in the Transmission Dynamics of Buruli ulcer

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Applied Mathematics 2024年第8期15卷 477-498页

作者： Codjo Cesaire Yadouleton Myriam Djoukwe Tapi Judicael Deguenon Ghislain Emmanuel Sopoh International Chair in Mathematical Physics and Applications University of Abomey-Calavi Abomey-Calavi Benin Department of Mathematics and Computer Science Faculty of Science University of Douala Douala Cameroon Polytechnic School of Abomey-Calavi University of Abomey-Calavi Abomey-Calavi Benin Regional Institute for Public Health University of Abomey-Calavi Abomey-Calavi Benin

Buruli ulcer is the third most common mycobacterial disease worldwide, posing a significant public health burden, especially in impoverished regions of West and Central Africa, such as Benin. The management of Buruli ulcer (BU) in Africa is often hindered by limited resources, delays in treatment, and inadequate medical facilities. Additionally, a portion of the population does not seek hospital care, which facilitates the continued presence of the pathogen in the environment. This paper aims to investigate the role of environmental factors in the transmission of Buruli ulcer. We develop a mathematical model to describe the dynamics of Buruli ulcer transmission, incorporating the presence of the bacterium in the environment. Theoretical results are presented to demonstrate that the model is well-posed. We compute the equilibria, including the disease-free equilibrium and the endemic equilibrium, and study their stability. To achieve this, we derive a threshold parameter called the basic reproduction number ℛ0, which determines whether the disease will persist in a human population. If ℛ0is less than one, the disease will eventually die out;if ℛ0is greater than one, the disease will persist. Sensitivity analysis is performed to understand the impact of various parameters on the dynamics of Buruli ulcer transmission and to identify the parameters that influence the basic reproduction number ℛ0. Finally, numerical simulations are conducted to validate the theoretical results obtained from the mathematical analysis.

关键词： Buruli Ulcer Mathematical Models Equilibria Stability

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Cox-ResNet: A Survival Analysis Model Based on Residual Neural Networks for Gene Expression Data

Cox-ResNet: A Survival Analysis Model Based on Residual Neur...

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IEEE International Conference on Networking, Sensing and Control

作者： Qingyan Yin Wangwang Chen Ruiping Wu Zhi Wei School of Science Xi'an University of Architecture and Technology Xi'an China Department of Computer Science New Jersey Institute of Technology Newark USA

ISBN: (纸本)9781665472449

Survival analysis with genomics data provides a deep understanding of biological processes related to prognosis and disease progression at the molecular level. However, high-dimensional small sample genome data causes computational challenges in survival analysis. To address this problem of overfitting and poor interpretation of existing models, we applied the deep learning technology to genome data and proposed a survival analysis model based on an image-based residual neural network model, called Cox-ResNet. High-dimensional gene expression data was embedded into 2D images according to gene positions on chromosomes, and then a residual network model based on Cox proportional hazards was introduced to perform survival analysis. We demonstrated the performance of Cox-ResNet on five datasets of different cancer types from TCGA, comparing it with the cutting-edge survival analysis methods. The Cox-ResNet model not only shows better performance in prediction accuracy, but also biologically interpretable, by generating heat-maps and prognostic genes for high-risk groups with the guided Grad-Cam visualization method. By performing protein-protein interaction network analysis, we examined hub genes and their biological functions for the bladder cancer. These findings confirm that Cox-ResNet model provides a new solution for discovering the driver genes of poor cancer prognosis.

关键词： Analytical models Biological system modeling Computational modeling Genomics Data models Gene expression Bioinformatics

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LAT-UP: Exposing Layout-Level Analog Hardware Trojans Using Contactless Optical Probing

LAT-UP: Exposing Layout-Level Analog Hardware Trojans Using ...

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IEEE computer Society Annual Symposium on VLSI

作者： Sajjad Parvin Mehran Goli Thilo Krachenfels Shahin Tajik Jean-Pierre Seifert Frank Sill Torres Rolf Drechsler Institute of Computer Science University of Bremen Germany Cyber-Physical Systems DFKI GmbH Germany Chair of Security in Telecommunications Technische Universität Berlin Germany Department of Electrical and Computer Engineering Worcester Polytechnique Institute USA Fraunhofer SIT Germany German Aerospace Center Institute for the Protection of Maritime Infrastructures Germany

The insertion of a Hardware Trojan (HT) into a chip after the in-house layout design is outsourced to a chip manufacturer for fabrication is a major concern, especially for mission-critical applications. While several HT detection methods have been developed based on side-channel analysis and physical measurements to overcome this problem, there exist stealthy analog HTs, i.e., capacitive and dopant-level HTs, which have negligible or even zero overhead on the chip. Thus, these stealthy HTs cannot be detected using the aforementioned methods. In this work, we propose a novel analytical approach to detect these Layout-level Analog Trojans (LAT). Our proposed method uses an extension of Optical Probing (OP) for LAT detection, namely, the Laser Logic State Imaging (LLSI) technique. In principle, to detect LATs using LLSI, we only need the golden design and not a golden chip, which is not typically available. As we take advantage of LLSI to detect HTs, our approach is non-invasive, less costly, and scalable to larger designs. We report experimental results on a malicious RISC-V to demonstrate the effectiveness of our approach in detecting LATs.

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Addressing Economic Dispatch Problem with Multiple Fuels Using Oscillatory Particle Swarm Optimization

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computers, Materials & Continua 2021年第12期69卷 2863-2882页

作者： Jagannath Paramguru Subrat Kumar Barik Ajit Kumar Barisal Gaurav Dhiman Rutvij HJhaveri Mohammed Alkahtani Mustufa Haider Abidi KIIT University BhubaneswarOdishaIndia Department of Electrical Engineering CETBhubaneswarOdishaIndia Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Computer Science&Engineering Pandit Deendayal Petroleum UniversityGandhinagarIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Economic dispatch has a significant effect on optimal economical operation in the power systems in industrial revolution 4.0 in terms of considerable savings in *** non-linearity are added to make the fossil fuel-based power systems more *** order to achieve an accurate economical schedule,valve point loading effect,ramp rate constraints,and prohibited operating zones are being considered for realistic *** this paper,an improved,and modified version of conventional particle swarm optimization(PSO),called Oscillatory PSO(OPSO),is devised to provide a cheaper schedule with optimum *** conventional PSO is improved by deriving a mechanism enabling the particle towards the trajectories of oscillatory motion to acquire the entire search space.A set of differential equations is implemented to expose the condition for trajectory motion in *** adaptive inertia weights,this OPSO method provides an optimized cost of generation as compared to the conventional particle swarm optimization and other new meta-heuristic approaches.

关键词： Economic load dispatch valve point loading industry 4.0 prohibited operating zones ramp rate limit oscillatory particle swarm optimization

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Investigation of Circular Patch Antenna for Wi-Fi and Bluetooth Applications 3

Investigation of Circular Patch Antenna for Wi-Fi and Blueto...

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3rd International Conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Ghassan Majeed, Maryam Qasim, Haitham Bashar Kosimova, Shakhlokhon Diame, Hussein Alaa Lafta, Alaa M. Alchilibi, Haider Al-Kunooze University College Computer Engineer Department Basra Iraq Al-Esraa University College Forensic Sciences Department Baghdad Iraq Fergana Polytechnic Institute Department of Architecture Fergana Uzbekistan National University of Science and Technology Dhi Qar Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad10022 Iraq

ISBN: (纸本)9798350330724

The purpose of this paper is to examine and contrast the Novel Circular Patch Antenna employing FR4 and RT Droid (CPA). Resonant frequency of 2.5 GHz in a static medium. To create the antenna, we use the HFSS and two different sample sets. Ten samples are taken from each antenna at 80% G-Power. Assume that the members of Group 1 are all CPAs that use the FR4 substrate. The Novel circular patch antenna (CPA) on RT roger's substrate is in the second group under consideration. This antenna operates at 2.5 GHz to measure reflectance at both ends. A VSWR of 2.1786 dB was measured at 2.4 GHz for a circular CPA designed for RT rogers, while the measured value for a CPA with FR4 was 0.7088 dB. The significance level in SPSS was 0.038 (p 0.05). The findings of this study show that RT rogers is approximately as effective as the FR4 substrate. © 2023 IEEE.

关键词： Natural frequencies

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