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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Depaoli, Fabio Felicioni, Stefano Ponzio, Francesco Aliberti, Alessandro MacIi, Enrico Bondioli, Federica Padovano, Elisa Di Cataldo, Santa Dept. of Control and Computer Engineering Politecnico di Torino Italy Dept. of Applied Science and Technology Politecnico di Torino Italy Interuniv. Dept. of Reg. and Urban Studies and Planning Politecnico di Torino Italy

ISBN: (纸本)9798350361230

Laser powder bed fusion (L-PBF) is the most popular Additive Manufacturing (AM) process for metals. It builds a 3D object layer-by-layer, by spreading metal powder on top of the previous layer and selectively melting it with a laser. Despite its many advantages, large-scale production may be hampered by the large number of process parameters and the challenges associated with their optimization. We propose an automated parameter selection approach based on process signatures extracted from a parameterized simulation of the process. Specifically, we outline a rapid data-driven simulation method based on physics-Informed Neural Network (PINN). This approach involves training a neural network to solve the partial differential equation describing the process at varying values of a parameter of interest (for example, the laser power), thus eliminating the need for repeated Finite Elements Method (FEM) simulations. Our preliminary experiments demonstrate the feasibility of our approach. © 2024 IEEE.

关键词： Smart manufacturing

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Second Harmonic Generation in Colloidal MoS2 Nanorods

Second Harmonic Generation in Colloidal MoS2 Nanorods

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2023 Novel Optical Materials and Applications, NOMA 2023

作者： Lambora, Simran Jyothsna, K.M. Bag, Urmila Raghunathan, Varun Bhardwaj, Asha Dept. of Instrumentation and Applied physics Indian Institute of Science Karnataka Bangalore560012 India Dept. of Electrical Communication Engineering Indian Institute of Science Karnataka Bangalore560012 India

We report synthesis of blue emitting MoS2 nanorods using colloidal heat-up method with blue-shifted absorption and photoluminescence spectra compared to 2D and bulk counterpart. Second harmonic generation is observed ... 详细信息

关键词： Blue shift

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Efficient Atrophy Mapping: A Single-Step U-Net Approach for Rapid Brain Change Estimation 3

Efficient Atrophy Mapping: A Single-Step U-Net Approach for ...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024

作者： Raciti, Riccardo Rondinella, Alessia Puglisi, Lemuel Guarnera, Francesco Ravì, Daniele Battiato, Sebastiano University of Catania Dept. of Math and Computer Science Catania Italy School of Physics Engineering and Cs University of Hertfordshire Hatfield United Kingdom

ISBN: (纸本)9798350378009

The estimation of brain atrophy is crucial for eval-uating brain diseases and analyzing neurodegeneration. Existing methods for computing atrophy maps often suffer from lengthy processing times due to the computational cost of multi-step processing. In this work, we propose a novel technique for atrophy map calculation using a single U-net-based architecture. This approach consolidates multiple traditional medical imaging processing steps into a single process, aiming to accelerate the computational time required. Specifically, our method estimates structural changes by generating a flow map from two longitudinal Magnetic Resonance Imaging (MRI) scans of the same subject. We trained and evaluated our system on a dataset comprising 2000 Tl-weighted MRI scans sourced from two different public datasets on Alzheimer's Disease. Experimental results demonstrate a considerable reduction in execution time while maintaining atrophy mapping performance comparable to state-of-the-art solutions. We believe that our pipeline could significantly benefit clinical applications for measuring brain atrophy, especially in scenarios requiring the evaluation of large cohorts, such as clinical trials. Our code is freely available at https://***/Efficient Atrophy Mapping: A Single-Step U-net Approach for Rapid Brain Change Estimation. © 2024 IEEE.

关键词： Magnetic resonance imaging

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ECC's Achilles'Heel: Unveiling Weak Keys in Standardized Curves 8

ECC's Achilles'Heel: Unveiling Weak Keys in Standardized Cur...

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8th Italian Conference on Cyber Security, ITASEC 2024

作者： Talotti, Enrico Paier, Matteo Miculan, Marino University of Udine Dept. of Mathematics Computer Science and Physics Italy IMT Alti Studi Lucca Italy Ca' Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Italy

The strength of Elliptic curve cryptography (ECC) relies on curve choice. This work analyzes weak keys in standardized curves, i.e., private keys within small subgroups of the auxiliary group ∗p. We quantify weak key prevalence across standardized curves, revealing a potential vulnerability due to numerous small divisors in auxiliary group orders. To address this, we leverage the implicit baby-steps giant-steps algorithm, which transforms the complex elliptic curve discrete logarithm problem into a simpler problem within ∗p. This enables efficient detection of weak keys in small-order subgroups. Our findings highlight the importance of rigorous key testing in applications using standardized ECC. While random weak keys are unlikely, malicious actors could exploit this by manipulating key generation libraries. To this end, we show how users can assess their private key vulnerabilities and mitigate risks by eliminating weak keys. Hence, this work contributes to improved ECC security through proactive key management practices. Copyright © 2024 for this paper by its authors.

关键词： Geometry

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Evaluation and Comparison of Facial Recognition Technology in Drawn Portraits 13

Evaluation and Comparison of Facial Recognition Technology i...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Chang, Cheng Fanjiang, Yong-Yi Hung, Chi-Huang Chen, Jung-Hua Phung, Kiem-Trinh Trieu, Van-Duc Fu Jen Catholic University Graduate Institute of Applied Science and Engineering New Taipei City Taiwan Fu Jen Catholic University Graduate Institute of Applied Science and Engineering Dept. of Computer Science and Information Engineering New Taipei City Taiwan Fu Jen Catholic University Lee-Ming Institute of Technology Graduate Institute of Applied Science and Engineering Dept. of Information Technology New Taipei Taiwan Fu Jen Catholic University Dept. of Computer Science and Information Engineering New Taipei City Taiwan Lee-Ming Institute of Technology Dept. Electronical Engineering New Taipei City Taiwan

ISBN: (纸本)9798350355079

Numerous studies have proposed various methods and applications for facial recognition. In camera-equipped environments, these methods can easily identify real faces. However, recognizing faces on printed or Portrait Drawing becomes more complex. In other words, real faces are three-dimensional, and while algorithms can sample feature values, identifying portrait drawing face on paper is relatively more challenging. This study evaluates and compares the effectiveness of various facial recognition techniques on paper-based images, including Haar-cascade, MTCNN, and Dlib 68 feature points. © 2024 IEEE.

关键词： Face recognition

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Netstaldi: A Modular Distributed Architecture for Incremental Network Discovery 8

Netstaldi: A Modular Distributed Architecture for Incrementa...

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8th Italian Conference on Cyber Security, ITASEC 2024

作者： Paier, Matteo Pizzolitto, Mattia Foresti, Gian Luca Miculan, Marino University of Udine Dept. of Mathematics Computer Science and Physics Italy IMT Alti Studi Lucca Italy Ca'Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Italy

Maintaining a comprehensive understanding of a network's connected devices is fundamental for robust security. This knowledge is crucial for tasks like vulnerability assessments, identifying potential attack surfaces, and network mapping. In this paper, we propose Netstaldi, a distributed architecture specifically designed for incremental and secure network discovery. Our architecture leverages non-intrusive network scanning techniques based on standard TCP/IP protocols, eliminating the need for monitoring agents on individual devices. This approach prioritizes scalability, modularity, and resilience, making it well-suited to handle large and dynamic network environments. We have implemented a prototype system based on this architecture, utilizing established open source tools. This system has been successfully tested on a large, real-world network. The results are promising: the tool efficiently scans the entire network within a few hours, and the intuitive GUI allows administrators to interactively explore the generated network map to identify and address potential vulnerabilities and misconfigurations. Copyright © 2024 for this paper by its authors.

关键词： Network security

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Probing Forbidden Low-Frequency Raman Modes in MoS2 via Plasmonic Nanoparticle

Probing Forbidden Low-Frequency Raman Modes in MoS2 via Plas...

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2024 JSAP-Optica Joint Symposia, JSAP 2024

作者： Zong, Zhen Morisaki, Ryosuke Sugiyama, Kanami Higashi, Masahiro Umakoshi, Takayuki Verma, Prabhat Dept. of Applied Physics Osaka Univ Japan Dept. of Molecular Engineering Kyoto Univ. Japan Dept. of Complex Systems Science Nagoya Univ. Japan Institute of Advanced Co-Creation Studies Osaka Univ Japan

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Exploring Mixed-Grid Environments for Drone-Based Last-Mile Logistics Optimization 20

Exploring Mixed-Grid Environments for Drone-Based Last-Mile ...

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20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Sorbelli, Francesco Betti Coro, Federico Pinotti, Cristina M. Shende, Anil University of Perugia Dept. of Computer Science and Mathematics Italy University of Padua Dept. of Mathematics Italy Roanoke College Dept. of Math. CS & Physics United States

ISBN: (纸本)9798350324334

In recent years, drone-based delivery systems have gained significant attention for last-mile logistics in various domains. This study focuses on optimizing drone deliveries in mixed-grid environments, which combine urban and rural areas. The objective is to minimize the sum of distances between the delivery locations and the drone's depot. By selecting the optimal depot placement, we aim to improve factors such as expected delivery time, energy consumption, and environmental impacts. To address this optimization problem, we conducted a comprehensive comparison of several state-of-the-art algorithms specifically designed for computing the drone placement in mixed-grid environments. Our evaluation utilized synthetic and quasi-real data and two distinct scenarios were considered: the full-grid scenario, and the partial-grid scenario. Through empirical analyses, we demonstrate the effectiveness of the proposed algorithms and provide valuable insights into their trade-offs in terms of performance and time complexity. © 2023 IEEE.

关键词： Drones

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Blockchain-based federated learning with checksums to increase security in Internet of Things solutions

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Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 4685-4694页

作者： Prokop, Katarzyna Polap, Dawid Srivastava, Gautam Lin, Jerry Chun-Wei Faculty of Applied Mathematics Silesian University of Technology Kaszubska 23 Gliwice44-100 Poland Dept. of Math and Computer Science Brandon University BrandonMBR7A 6A9 Canada Research Centre for Interneural Computing China Medical University Taichung Taiwan Western Norway University of Applied Sciences Bergen Norway Dept. of Computer Science and Math Lebanese American University Beirut1102 Lebanon

Federated learning is becoming a practical solution for machine learning (ML) in industry. This is due to the possibility of implementing artificial intelligence (AI) systems and training its models on private data sets. However, this is not an ideal solution as it is possible to manipulate or even intercept the model during its transmission between the server and workers. In this paper, we propose a solution to ensure the security of the model transmitted between units in FL. The given model is encrypted with AES, DES, RSA algorithms, then a checksum is determined. This checksum with a private key is stored as a transaction on a blockchain. In the case of sending the model and its modification, the recipient can easily verify whether it is correct. The proposed solution has been described, tested, and compared to indicate its advantages and disadvantages. Conducted experiments were based on analyzing the communication time between participants, the accuracy of machine learning models, and attack detection. In terms of attack detection on the blockchain, we reached 81% thanks to the checksum mechanism. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Blockchain

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A Birds Species Detection Utilizing an Effective Hybrid Model 21

A Birds Species Detection Utilizing an Effective Hybrid Mode...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Rafa, Sara Abbas Al-Qfail, Zohaa Mubarak Adil Nafea, Ahmed Abd-Hood, Samia F. Al-Ani, Mohammed M Alameri, Saeed Amer College of Law and Political Science University of Anbar Dept. Law Ramadi Iraq College of Computer Science and Information Technology University of Anbar Dept. Artificail Inteligence Ramadi Iraq Selangor Bangi Malaysia Seiyun University Dept. Computer Science Faculty of Applied Sciences Hadhramout Yemen Hadhramout University Faculty of Computers and Information Almukalla Hadhramout Yemen Seiyun University Dept. Department of Information Technology Hadhramout Yemen

ISBN: (纸本)9798350374131

The aim of this study is to improve the performance of detection Birds Species by proposed a hybrid model using a combination of MobileNetV2 for feature extraction, an Autoencoder for dimensionality reduction, and Support Vector Machines (SVM) for classification. The methodology includes preprocessing, augmentation, feature extraction, and classification phases. The proposed model is evaluated using the Bird Species dataset, consisting of 525 bird species the dataset is carefully curated to ensure cleanliness and absence of leakage between sets. The evaluation metrics include precision, recall, accuracy, and F-measure. The results have shown the efficiency of the proposed model in bird species classification. © 2024 IEEE.

关键词： Support vector machines

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